même tâche et un même type de dépendances, les performances des babouins seraient relativement stables d'un test à l'autre.

<figure><img src="image_65.png" /><figcaption>**Figure 2** Performances des participants dans l'Expérience 1 de l'Etude I en fonction de leurs performances dans l'Expérience 2 (Langage 2) de cette même étude.</figcaption></figure>

## Effets de la Tâche et du Type de Dépendance

La Figure 3 représente les performances des babouins dans les différents tests. Les valeurs de ces corrélations sont rapportées dans la Table 3. Une corrélation positive restant non significative est observée entre les deux tâches dans lesquelles les babouins devaient apprendre des dépendances non-adjacentes (r = 0.34, *p* = 0.11). Une corrélation positive significative (r = 0.85, *p* < 0.01) est observée entre les deux tâches d'apprentissage de dépendances adjacentes. Les performances des babouins ne sont en revanche pas corrélées entre les expériences impliquant des types de dépendance différents. Des corrélations négatives tendent même à être observées entre les performances des babouins dans la tâche visuo-spatiale d'apprentissage de dépendances adjacentes, et celles obtenues dans les deux tâches d'apprentissage de dépendances non-adjacentes.

Les performances des babouins ne sont donc pas corrélées au sein d'une même tâche (i.e. visuo-spatiale ou visuelle) lorsque le type de dépendance diffère. Ainsi, les babouins qui
obtiennent les meilleures performances dans l'apprentissage de dépendances adjacentes ne sont
pas ceux qui parviennent à apprendre les dépendances non-adjacentes.
<figure><img src="image_66.png" /><figcaption>**Figure 3** Performances individuelles en fonction des différentes expériences, pour un même type de dépendance (en bleu), et pour des dépendances différentes (en violet). Types de dépendances : Nadj = non-adjacentes, Adj = adjacentes ; Tâches : VS = visuo-spatiale, V = visuelle. L2 = langage 2.</figcaption></figure>
<table><caption>Table 3 Corrélation entre les différentes tâches d'apprentissage statistique</caption><thead><tr><th rowspan="3"></th><th rowspan="3"></th><th rowspan="3"></th><th colspan="2">Nadj</th><th>Adj</th></tr><tr><th>VS</th><th>V</th><th>VS</th></tr><tr><th>Etude I - Exp. 2 (L2)</th><th>Etude II</th><th>Minier et al. (2016)</th></tr></thead><tbody><tr><td>Nadj</td><td>V</td><td>Etude II</td><td>r = 0.34, n = 15, p = 0.11<br/>[-0.10, 0.77]</td><td></td><td></td></tr><tr><td></td><td>VS</td><td>Minier et al. (2016)</td><td>r = -0.52, n = 9, p = 0.15<br/>[-0.88, 0.21]</td><td>r = -55, n = 9, p = 0.12<br/>[-0.89, 0.17]</td><td></td></tr><tr><td></td><td>Adj</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td>V</td><td>Etude II</td><td>r = -20, n = 15, p = 0.47<br/>[-0.65, 0.35]</td><td>r = -0.12, n = 16, p = 0.65<br/>[-0.58, 0.40]</td><td>r = .85, n = 8, p &lt; 0.01<br/>[0.38, 0.97]</td></tr></tbody></table>

Note : Les valeurs entre crochets indiquent les intervalles de confiance à 95%.

## Apprentissage Statistique et Mémoire de Travail

L'apprentissage de dépendances non-adjacentes est susceptible d'impliquer davantage la mémoire de travail que l'apprentissage de dépendances adjacentes. En effet, cet apprentissage pourrait nécessiter le maintien temporaire en mémoire de travail du premier élément de la séquence, l'élément prédictif, pour détecter son association avec l'élément prédictible. Nous avons donc examiné si les performances d'apprentissage statistique des babouins, pour l'un et l'autre de ces types de dépendance, corrélaient avec une mesure de leurs capacités de mémoire de travail. La Figure 4 et la Table 4 présentent les corrélations entre les performances des babouins dans la tâche de SOPT et les différentes expériences d'apprentissage statistique. Une corrélation positive proche du seuil de significativité (r = 0.47, p = 0.06) est observée entre la tâche SOPT et l'expérience dans laquelle les babouins devaient apprendre des dépendances non-adjacentes dans la tâche visuelle (Nadj-V, Etude II). Aucune autre corrélation significative n'est observée.
<figure><img src="image_67.png" /><figcaption>**Figure 4** Performances des participants dans la tâche de SOPT, en fonction de leurs performances dans les différentes expériences d'apprentissage statistique.</figcaption></figure>

<table><caption>**Table 4** Corrélations entre les différentes tâches d'apprentissage statistique</caption><thead><tr><th rowspan="3"></th><th colspan="2">Nadj</th><th colspan="2">Adj</th></tr><tr><th>VS</th><th>V</th><th>VS</th><th>V</th></tr><tr><th>Etude I - Exp. 2 (L2)</th><th>Etude II</th><th>Minier et al. (2016)</th><th>Etude II</th></tr></thead><tbody><tr><td>SOPT</td><td>r = -0.15, n = 17, p = .56<br/>[-0.59, 0.36]</td><td>r = 0.47, n = 16, p = .06<br/>[-0.03, 0.79]</td><td>r = -0.25, n = 9, p = .52<br/>[-0.78, 0.50]</td><td>r = 0.09, n = 16, p = .74<br/>[-0.43, 0.56]</td></tr></tbody></table>

Les valeurs entre crochets indiquent les intervalles de confiance à 95%.

Ces résultats confirment donc partiellement notre hypothèse : notre mesure de la mémoire de travail des babouins tend à être corrélée avec leurs performances dans l'une de nos expériences testant leur capacité à détecter des régularités non-adjacentes, tandis qu'elles ne sont pas significativement corrélées à leurs performances dans deux tâches d'apprentissage de dépendances adjacentes.

## Discussion

Dans cette étude, nous avons réalisé des analyses corrélationnelles sur un ensemble d'expériences réalisées sur un même groupe de babouin. Afin de discuter les résultats obtenus au regard de la littérature, nous avons résumé dans la Table 5 les principaux résultats des deux seules études dont nous ayons connaissance ayant effectuées des analyses similaires chez l'humain. Misyak et Christiansen (2012) ont soumis un groupe de participants humains à deux tests successifs, l'un visant à évaluer leurs capacités d'apprentissage de dépendances
adjacentes, et l'autre de dépendances non-adjacentes. Ils ont dans les deux cas utilisé une tâche présentée dans la modalité auditive, impliquant la présentation de stimuli linguistiques (pseudomots). Siegelman et Frost (2015) ont employé une plus grande diversité de tâches d'apprentissage statistique. Dans ces deux études, les participants étaient également soumis à une batterie de tests évaluant d'autres fonctions cognitives (mémoire de travail, QI, traitement de langue naturelle, etc). Ci-dessous nous discutons nos résultats au regard des données de la littérature, pour chacune des questions examinées.

<table><caption>**Table 5** Résultats de deux études examinant les corrélations entre les performances individuelles d'apprentissage statistique en fonction du type de dépendance et de la tâche chez l'humain.</caption><thead><tr><th rowspan="3"></th><th rowspan="3"></th><th rowspan="3"></th><th colspan="2">Misyak &amp; Christiansen (2012)</th><th colspan="4">Siegelman &amp; Frost (2015)</th></tr><tr><th colspan="2">Adj</th><th colspan="2">Adj</th><th colspan="2">Nadj</th></tr><tr><th>Aud-V</th><th>Vis-NV</th><th>Aud-NV</th><th>Aud-V</th><th>Aud-V</th></tr></thead><tbody><tr><td rowspan="2">Misyak &amp; Christiansen (2012)</td><td>Adj</td><td>Aud-V</td><td rowspan="2">0.14</td><td></td><td></td><td></td><td></td></tr><tr><td>Nadj</td><td>Aud-V</td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="3">Siegelman &amp; Frost (2015)</td><td rowspan="2">Adj</td><td>Vis-NV</td><td></td><td>0.58</td><td></td><td></td><td></td></tr><tr><td>Aud-NV</td><td></td><td>-0.29</td><td>0.23</td><td></td><td></td></tr><tr><td>Nadj</td><td>Aud-V</td><td></td><td>0.11</td><td>0.10</td><td>0.63</td><td></td></tr><tr><td></td><td></td><td>Aud-V</td><td></td><td>-0.22</td><td>-0.25</td><td>-0.04</td><td>0.31</td></tr></tbody></table>

Valeurs des corrélations (r) intra-tests (en bleu) et inter-tests (en noir). Types de dépendances : Adj = adjacentes, Nadj = non-adjacentes. Tâches : Aud-V = auditive verbale, Aud-NV = auditive non-verbale, Vis-NV = visuelle non-verbale.

## Stabilité des Performances Individuelles

Nous avons observé une stabilité relative des performances des babouins au sein d'une même tâche et pour un même type de dépendance. A notre connaissance, seule l'étude de Siegelman et Frost (2015) a également évalué la stabilité intra-test des performances de leurs participants. Comme le montre la Table 5, ils ont observé une certaine réplicabilité intra-test, qui varie cependant d'une tâche à l'autre. Nos données suggèrent que les performances individuelles des babouins dans une tâche d'apprentissage statistique donnée permettent de prédire leurs performances ultérieures dans cette même tâche et pour le même type de dépendance, mais la conduite de réplications additionnelles serait nécessaire pour confirmer la tendance observée.
## Effets de la Tâche et du Type de Dépendance

Un examen des corrélations inter-tâches et inter-dépendances a révélé que les performances individuelles des babouins étaient influencées par le type de dépendance à apprendre (adjacente ou non-adjacente), tandis que la tâche ne semble pas avoir d'effet majeur. Les performances des babouins dans les expériences impliquant l'apprentissage de dépendances adjacentes d'une part, et celles impliquant l'apprentissage de dépendances non-adjacentes d'autre part, ne sont pas corrélés entre elles. Ces résultats sont similaires à ceux obtenus dans la littérature chez l'humain (cf. Table 5).

A la différence de Siegelman et Frost (2015) cependant, nos résultats indiquent que les performances des babouins dans une tâche corrélait de manière significative ou tendaient à l'être, avec leurs performances dans l'autre tâche, pour un type de dépendance donné. Cette différence de résultats entre ces deux études pourrait toutefois découler des tâches que nous avons employées. En effet, bien que nos deux tâches présentent des différences importantes (la tâche visuo-spatiale impliquant la prédiction de la localisation d'un stimulus, tandis que la tâche visuelle implique la prédiction de sa forme), elles impliquent toutes deux la modalité visuelle. Nos résultats suggèrent donc *a minima* qu'au sein de cette modalité, pour un même type de dépendance, les performances individuelles des babouins tendent à être stables d'une tâche à l'autre.

## Apprentissage Statistique et Mémoire de Travail

Nous avons fait l'hypothèse que l'extraction de régularités non-adjacentes serait susceptible d'impliquer la mémoire de travail de manière plus importante que celle de régularités adjacentes. Nous avons donc testé si des différences inter-individuelles de mémoire de travail, mesurée à l'aide d'une tâche de SOPT, corrèlent avec les performances des babouins dans les expériences d'apprentissage de dépendances non-adjacentes. Notre hypothèse est partiellement supportée par les analyses corrélationnelles effectuées. Les babouins qui parviennent à maintenir en mémoire de travail le plus grand nombre d'items dans la tâche de SOPT sont également ceux ayant obtenu les meilleures performances dans l'une de nos expériences impliquant des dépendances non-adjacentes. Chez l'humain, Misyak et
Christiansen (2012) rapportent une forte corrélation positive entre une mesure de la mémoire de travail (verbale) et les performances de leurs participants pour l'apprentissage de dépendances non-adjacentes (r = 0.53, *p* < 0.01). Toutefois, cette mesure est également corrélée avec l'apprentissage de dépendances adjacentes (r = 0.46, *p* < 0.05). De leur côté, Siegelman et Frost (2015) ne trouvent aucune corrélation entre les performances de leurs participants pour l'extraction de dépendances non-adjacentes et deux mesures de la mémoire de travail (mémoire de travail générale et verbale).

## Conclusions

Les données issues de nos analyses corrélationnelles suggèrent que les babouins étant le plus sensibles aux dépendances non-adjacentes ne sont pas ceux présentant la plus forte sensibilité pour les dépendances adjacentes, et *vice-versa*. Ces résultats sont compatibles avec deux hypothèses de la littérature : (1) l'apprentissage de dépendances adjacentes et non-adjacentes est supporté par des mécanismes de nature différente (e.g. Peña, Bonatti, Nespor, & Mehler, 2002), et (2) ces deux apprentissages reposent sur les mêmes mécanismes d'apprentissage statistique, mais l'apprentissage de dépendances non-adjacentes est susceptible d'impliquer de manière plus importante la mémoire de travail (e.g. Wilson, Marslen-Wilson, & Petkov, 2017). Les analyses corrélationnelles que nous avons menées pour examiner les liens potentiels entre l'apprentissage de dépendances non-adjacentes et la mémoire de travail, ainsi que ceux de la littérature chez l'humain, ne soutiennent que partiellement cette deuxième hypothèse. Des recherches supplémentaires sur cette question seraient nécessaires pour apporter des conclusions plus solides, par exemple en examinant si les capacités d'apprentissage de dépendances non-adjacentes de différentes espèces corrèlent ou non avec leurs capacités de mémoire de travail.

Un dernier aspect de nos résultats retient notre attention : nous avons observé une tendance à des corrélations négatives entre les performances des babouins pour l'apprentissage de dépendances adjacentes et non-adjacentes, pour certaines de nos expériences. Une corrélation négative a également été observée par Siegelman et Frost (2015) entre deux de leurs tâches (r = -0.25, *p* < 0.05 ; cf. Table 5). Ces résultats suggèrent que les individus présentant la plus forte sensibilité aux dépendances adjacentes ne seraient pas seulement pas les plus sensibles aux dépendances non-adjacentes, mais qu'ils seraient moins sensibles à ces
dépendances, et *vice-versa*. Ces observations suggèrent une troisième hypothèse : une sensibilité importante aux régularités locales pourrait se ferait au détriment de la sensibilité à des régularités non-adjacentes. A l'inverse, une focalisation moins importante sur les régularités locales pourrait permettre aux autres individus d'être sensibles aux régularités plus distantes.
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Annexe 1 Mode de calcul de la somme des scores obtenus dans la tâche SOPT.

<table><thead><tr><th>Sujet</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>Somme</th></tr></thead><tbody><tr><td>ANG</td><td>0.96</td><td>0.68</td><td></td><td></td><td></td><td>1.64</td></tr><tr><td>ARI</td><td>0.95</td><td>0.79</td><td>0.53</td><td></td><td></td><td>2.27</td></tr><tr><td>BOB</td><td>0.96</td><td>0.79</td><td>0.51</td><td></td><td></td><td>2.26</td></tr><tr><td>BRI</td><td>0.97</td><td>0.66</td><td>0.29</td><td></td><td></td><td>1.92</td></tr><tr><td>DAN</td><td>0.98</td><td>0.91</td><td>0.64</td><td></td><td></td><td>2.54</td></tr><tr><td>DOR</td><td>0.98</td><td>0.93</td><td>0.80</td><td>0.63</td><td></td><td>3.34</td></tr><tr><td>DRE</td><td>0.98</td><td>0.93</td><td>0.73</td><td>0.49</td><td></td><td>3.13</td></tr><tr><td>EWI</td><td>0.99</td><td>0.88</td><td>0.66</td><td>0.41</td><td></td><td>2.94</td></tr><tr><td>FAN</td><td>0.99</td><td>0.96</td><td>0.85</td><td>0.68</td><td>0.47</td><td>3.95</td></tr><tr><td>FEL</td><td>0.96</td><td>0.86</td><td>0.62</td><td></td><td></td><td>2.44</td></tr><tr><td>FEY</td><td>0.98</td><td>0.89</td><td>0.70</td><td>0.44</td><td></td><td>3.00</td></tr><tr><td>FIL</td><td>0.98</td><td>0.86</td><td>0.64</td><td>0.37</td><td></td><td>2.86</td></tr><tr><td>FLU</td><td>0.97</td><td>0.86</td><td>0.61</td><td></td><td></td><td>2.43</td></tr><tr><td>HAR</td><td>0.96</td><td>0.71</td><td>0.41</td><td></td><td></td><td>2.09</td></tr><tr><td>HER</td><td>0.98</td><td>0.83</td><td>0.57</td><td></td><td></td><td>2.37</td></tr><tr><td>KAL</td><td>0.96</td><td>0.46</td><td></td><td></td><td></td><td>1.42</td></tr><tr><td>VIO</td><td>0.97</td><td>0.73</td><td>0.43</td><td></td><td></td><td>2.13</td></tr><tr><td>VIV</td><td>0.95</td><td>0.67</td><td></td><td></td><td></td><td>1.62</td></tr></tbody></table>

Dans les colonnes intitulées 2-6 sont indiqués les scores moyens obtenus par chaque sujet sur l'ensemble de l'année 2015, pour chaque niveau de difficulté de la tâche (de deux à six items à sélectionner).
V. ETUDE IV – Traitement de Grammaires Supra-Régulières
chez le Babouin

Malassis, R., Fagot, J., & Dehaene, S. (en préparation).

Nous avons vu que les études réalisées sur l’apprentissage de grammaires supra-régulières n’offraient pas pour le moment de démonstration non-ambiguë de cette capacité chez une autre espèce que l’humain (cf. section II.2.3.3 du volet théorique). Toutefois, nous avons émis l’hypothèse que ces échecs puissent s’expliquer par un biais des singes vers le traitement d’informations locales (e.g. détection de répétitions immédiates, apprentissage de dépendances adjacentes), et qu’ils ne révèlent donc peut-être pas une réelle incapacité des différentes espèces NH testées à traiter ce type de grammaire.

Dans le travail présenté ci-dessous, nous avons introduit deux modifications par rapport
à ces études précédentes. La première de ces modifications a consisté à s'intéresser aux
grammaires centrée-emboîtée et croisée plutôt qu'à la grammaire AⁿBⁿ. En effet nous avons vu
que cette dernière avait été largement utilisées jusqu'ici pour la conduite d'expériences chez
l'animal NH, sans succès. Les problèmes méthodologiques inhérents à l'utilisation de cette
grammaire (présence d'indices locaux et de surface rendant non nécessaire le traitement de la
grammaire sous-jacente) nous ont conduit à considérer que cette grammaire ne constitue pas un
matériel à privilégier pour évaluer l'hypothèse de la supra-régularité. De plus, comparer
l'apprentissage des grammaires centrée-emboîtées et croisées permet de situer plus finement
les capacités syntaxiques d'une espèce donnée (Fitch & Friederici, 2012), puisqu'elles sont
respectivement une grammaire non-contextuelle et une grammaire contextuelle (cf. Figure 3, p.
20). Nous avons donc testé la capacité des babouins à traiter d'une part des séquences
comportant plusieurs dépendances organisées de manière centrée-emboîtée, en employant une
grammaire en miroir (Mirror grammar) dans laquelle la seconde moitié de la séquence est
l'image en miroir de la première moitié (Figure 28). Nous avons d'autre part testé leur capacité
à traiter des séquences comportant plusieurs dépendances croisées, en utilisant une grammaire
en copie (Copy grammar) dans laquelle la seconde moitié de la séquence est une copie de la
première moitié.
<figure><img src="image_68.png" /><figcaption>**Figure 28** Illustration de l'organisation centrée-emboîtée des dépendances dans une séquence générée par une grammaire Mirror (à gauche), et de l'organisation croisée des dépendances dans une grammaire Copy (à droite).</figcaption></figure>

La seconde nouveauté implémentée dans notre étude est que nous avons testé les babouins dans une tâche de prédiction plutôt que dans une tâche de classification. Ceci nous permet de prévenir l'exploitation par le babouin d'une seule régularité locale, les babouins devant répondre à chaque élément de la séquence. Cette méthode permet également de nous renseigner sur les prédictions des babouins sur chacun des éléments de la séquence.

Dans cette étude, les babouins ont d'abord été exposés à un ensemble de 64 séquences de la forme AB|BA (Expérience Mirror) ou AB|AB (Expérience Copy), générées à partir de 16 éléments. Nous avons choisi d'utiliser un nombre important d'exemplaires afin de favoriser une généralisation de la réponse à d'autres séquences ayant les mêmes propriétés structurelles (Katz, Wright, & Bodily, 2007; Maugard, Wasserman, Castro, & Fagot, 2014).

Les babouins étaient ensuite soumis à une série de tests, dans lesquels de nouvelles séquences de longueur étendue (i.e. comportant six éléments au lieu de quatre) leur étaient présentées. Certaines de ces séquences étaient congruentes avec la grammaire (Mirror : ABC|CBA ; Copy : ABC|ABC), et d'autres non-congruentes, leurs deux derniers éléments étant inversés (Mirror : ABC|CAB ; Copy : ABC|ACB). Les temps de réponse sur chaque élément de la seconde moitié de la séquence étaient mesurés. Nos prédictions étaient que si les babouins détectent la violation de la structure, alors leurs temps de réponse devraient être plus élevés dans les séquences non-congruentes que dans les séquences congruentes.

Les résultats révèlent que les babouins ont réagi aux violations de la grammaire Mirror, y compris pour les séquences test ne comprenant que des transitions adjacentes nouvelles. En
revanche, ils n'ont pas réagi aux violations de la grammaire Copy. En d'autres termes, nos résultats suggèrent que les babouins ont été sensibles dans cette tâche à une organisation centrée-emboîtée, mais pas à une organisation croisée des dépendances.

Pour éviter toute redondance avec l'introduction de cette thèse, je ne présente ici que les sections « méthodes » et « résultats » de ce travail. Je reviendrai sur l'interprétation de ces résultats dans le volet discussion de ce manuscrit.
General Procedure

This experiment used an adaptation of the serial response time task (Nissen & Bullemer, 1987) which is illustrated in Figure 1. In practice, each sequence was split in two halves. In each trial, the baboons firstly saw the first half of the sequence, corresponding to several targets appearing successively in specific locations of a 4 x 4 matrix on a touch screen. No response to this first part of the sequence was required. After a short delay, the second half of the sequence was presented on the touch screen, and the subjects had to touch the target, each time it appeared on the screen (Figure 1). Response times collection on those touches provides a measure of the participants expectations about the location of the incoming target. Requiring responses on the second half of the sequence only allowed us to compare response times on the same motor sequences across conditions and experiments. All baboons (n = 14) performed sequentially both mirror & copy experiments, order being counterbalanced across participants.

<figure><img src="image_69.png" /><figcaption>**Figure 1** (A) Timeline of a trial (example of a 6-target mirror sequence). After seeing the first half of the sequence (blue targets) displayed on a touchscreen, baboons had to touch the (red) targets of the second half. (B, C) General principles of the experimental design. (B) Baboons were first exposed to 4-target sequences of the form AB | BA (mirror experiment) or AB | AB (copy experiment). (C) They were then tested on consistent and inconsistent 6-target sequences.</figcaption></figure>

Table 1 present an overview of the experiments timeline. Baboons were first presented
with sequences of four targets, following either a mirror (AB|BA) or a copy structure (AB|AB).
After this exposure phase, baboons received a series of four tests (Test 1, Test 2, Test 3, Control), in which sequences of six targets, instead of four, were presented to the baboons. These tests assessed whether the baboons were sensitive to the structure underlying the targets' displacements in novel sequences of extended length.

<table><caption>**Table 1 Overview of the experiments timeline.**</caption><thead><tr><th rowspan="2">Phases</th><th rowspan="2">Description</th><th rowspan="2">Conditions</th><th rowspan="2">Prop. of Trials</th><th colspan="2">Sequences structure</th><th rowspan="2">No. of blocks</th></tr><tr><th>Mirror experiment</th><th>Copy experiment</th></tr></thead><tbody><tr><td>Exposure</td><td>4-target sequences</td><td>Baseline</td><td>100%</td><td>AB | BA</td><td>AB | AB</td><td>40</td></tr><tr><td rowspan="3">Test 1</td><td rowspan="3">6-target sequences</td><td>Baseline</td><td>4/6</td><td>ABC | CBA</td><td>ABC | ABC</td><td rowspan="3">4</td></tr><tr><td>Consistent</td><td>1/6</td><td>ABC | CAB</td><td>ABC | ACB</td></tr><tr><td>Inconsistent</td><td>1/6</td><td>ABC | ACB</td><td>ABC | ACB</td></tr><tr><td colspan="7">Interruption (2 months)</td></tr><tr><td rowspan="4">Control</td><td rowspan="4">Presentation of the different sequence structures at equal frequencies</td><td>Mirror-Consistent</td><td>1/4</td><td>ABC | CBA</td><td></td><td rowspan="4">4</td></tr><tr><td>Mirror-Inconsistent</td><td>1/4</td><td>ABC | CAB</td><td></td></tr><tr><td>Repeat-Consistent</td><td>1/4</td><td>ABC | ABC</td><td></td></tr><tr><td>Repeat-Inconsistent</td><td>1/4</td><td>ABC | ACB</td><td></td></tr><tr><td>Exposure</td><td>4-target sequences</td><td>Baseline</td><td>100%</td><td>AB | BA</td><td>AB | AB</td><td>20</td></tr><tr><td rowspan="2">Test 2</td><td rowspan="2">6-target sequences containing familiar 4-target sequences</td><td>Consistent</td><td>1/7</td><td></td><td></td><td rowspan="2">4</td></tr><tr><td>Inconsistent</td><td>1/7</td><td></td><td></td></tr><tr><td rowspan="3">Test 3</td><td rowspan="3">6-target sequences made of novel targets combinations</td><td>Baseline</td><td>3/7</td><td>= Test 1</td><td></td><td rowspan="3">4</td></tr><tr><td>Consistent</td><td>1/7</td><td></td><td></td></tr><tr><td>Inconsistent</td><td>1/7</td><td></td><td></td></tr></tbody></table>

Note: All baboons (n = 14) performed sequentially both mirror & repeat experiment, order being counterbalanced across participants. Tests 2 and 3 were conducted concurrently.

In Test 1, baboons were presented with two types of test sequences presented at equal frequencies: consistent sequences (mirror: ABC|CBA; copy: ABC|ABC), and inconsistent ones, in which the last two targets were presented in a reversed order. These sequences were of the form ABC | CAB in the mirror experiment, and ABC|ACB in the copy experiment (violations underlined). In all those test sequences, the targets appeared at locations on the matrix which were never used before within sequences of six targets.
The structure of the consistent and inconsistent sequences was similar in Tests 2 and 3, in which we manipulated the novelty of the subsets of four targets composing the complete sequences of six targets. In Test 2, test sequences contained baseline sequences. For instance, the inconsistent mirror sequence 4 5 3 | 3 4 5 (these numbers refer to different locations on the matrix, see *Supplementary Information*) involved violations of the subsequences 4 5 | 5 4 and 5 3 | 3 5, which are both 4-target baseline sequences encountered a substantial number of times during the exposure phase. In Test 3, the sequences did not contain baseline sequences, as they were constructed with novel combinations of locations.

In the Control test, the four types of sequences (mirror consistent, mirror inconsistent, copy consistent, copy inconsistent) were presented at equal frequencies. This test was administered after a 2-month interruption of the experiment.

## Predictions

This series of tests allowed precise predictions about the baboons' pattern of response times, depending on the regularities learned during the exposure phase. Our rationale was that detection of the violations should result in slower response times on inconsistent sequences compared to consistent sequences. If baboons relied on rote memorization of the baseline sequences, they should succeed in Tests 1 and 2, but should fail to notice the violations occurring in Test 3. By contrast, if baboons' behavior was triggered by idiosyncratic features of the different sequences types, rather than sensitivity to the underlying structure, we should observe in the Control phase a pattern of responses similar to Tests 1-3 phases. Finally, if baboons are sensitive to the mirror and/or copy structure, they should show slower response times on inconsistent trials in Tests 1-3, while no difference would be observed in the Control test.

## Participants and apparatus

Participants were 14 Guinea baboons (*Papio papio*, 8 females, age range 4-21 years) from the CNRS primate facility (Rousset-sur-Arc, France). They live within a larger group of 26 individuals, within a 700 m2 outdoor enclosure and had a permanent access to ten Automated
Learning Devices for Monkeys (ALDM, for a detailed description, see (Joël Fagot & Bonté, 2010b; Joël Fagot & Paleressompoulle, 2009) equipped with a 19-inch touch screen and a food dispenser. The main feature of ALDM equipment is that a radio frequency identification reader (RFID) identifies each baboon via a microchip implanted in each arm. The baboons can therefore participate to the research at will, without being captured, as the test programs recognize them automatically. The experiment was controlled by the EPrime software (Version 2.0, Psychology Software Tools, Pittsburgh).

## Task

Each trial began by the display of a fixation cross (120 x 120 pixels) presented at the bottom of the screen. Touching this stimulus triggered the display of a matrix of 16 (4 x 4) white crosses (60 x 60 pixels each), one of these crosses (hereafter, location) being replaced by a target stimulus (a blue circle of 80 x 80 pixels). This target was displayed during 225 ms, before it moved to another location on the screen for another period of 225 ms. There was no delay between the offset of the target and its next display. During this first phase of the trial, participants should not touch the screen. After disappearance of the second target, the screen remained devoid of targets (only the matrix of locations remained display) for an interval of 125 ms. This interval signaled the middle of the sequence. In the second part of the trial, participants had to touch the targets. Another target (red circle of 80 x 80 pixels) was used to facilitate the distinction between the two phases of the trial. A correct touch of this target immediately triggered the reappearance of the target at another location of the matrix. Trial ended when the participant touched this last target. An accurate completion of the second half of the sequence delivered grains of dry wheat inside the ALDM test unit. An incorrect response (i.e., selection of an incorrect location, or a touch on the screen during the display of the first half of the sequence or the interval signaling the middle of the sequence) stopped the trial and triggered a 5-sec timeout without food reward. Trials in which the participants failed to select a stimulus within 5-sec after the third or fourth target's appearance aborted and presented again in the next trial. This procedure was followed for sequences of four targets. The same procedure was used for sequences of six targets, with the exception that the interval signaling the middle of the sequence lasted 300 ms instead of 125 ms. The time elapsed between the appearance of each target and the baboon's touch on this target were recorded as the response times.
Experimental design

We describe below the procedure used for each phase of the experiments. Each experiment involved exposure phases, a pre-test phase, and four testing phases (Tests 1-3, Control). The lists of all the sequences used in each phase are available in *Supplementary Information*. Unless otherwise noted, for each phase, the sequences were generated with the following constrains: (1) the frequency of each location across all sequences and within each position was equated, (2) repetitions were avoided (i.e. no location could be used twice within a sequence half). Moreover, within all pre-test and test phases, sequences were equated for motor constrains across conditions and experiments (i.e. the second halves of the sequences were identical in the mirror consistent, mirror inconsistent, copy consistent and copy inconsistent conditions). In addition, to prevent learning of the novel sequences during the testing periods, the first halves of the sequences were also equated between conditions, rendering the second half unpredictable on that basis. Sequences from the different conditions therefore differed from each other only regarding the matching between their two halves. For instance, for a given combination of three locations {3, 4, 5}, the following sequences were generated: 453|**354** , 543|**354** , 453|**345** , and 543|**345** (mirror experiment); 345|**354** , 354|**354** , 345|**345** , and 354|**345** (copy experiment; bold and underlined characters denote motor sequences shared across conditions and experiments; note that first halves of the sequences are equated between conditions within each experiment). Custom-written Python codes (www.python.org) were used to generate the sequences.

Exposure phases

For the exposure phases, sixty-four 4-target baseline sequences were constructed. Each
of the 16 locations of the matrix was presented four times in the first position of the sequence
and combined with four different locations presented in second position of the sequence (i.e.
16 * 4 = 64 sequences; transitional probabilities between the first and second locations = .25).
The same combinations of locations were used to generate the mirror and copy baseline
sequences. Before Test 1, as well as Tests 2-3, baboons performed an exposure phase of twenty
96-trial blocks during which these 64 4-target baseline sequences were presented. In addition,
right before each test (including control), baseline sequences of six targets were presented to
the baboons during one block to familiarize them with the introduction of additional targets.
For Tests 1-3, these sequences were the same baseline sequences as those presented during the corresponding tests. For the Control test, a different set of sequences was generated, having the same balanced structure (1/4 of each sequence type).

## Pre-tests

Baboons received two pre-tests, aiming at verifying that they payed attention to the first half of the sequences. In the first pre-test, 1/6 of the trials were consistent sequences consisting in novel combinations of locations, and 1/6 of the trials were made of the same novel combinations but followed the reverse pattern (i.e. in the mirror experiment, consistent and inconsistent sequences were of the form AB | BA and AB | AB, respectively, and *vice-versa* in the copy experiment). The remaining 4/6 of the trials were 4-target baseline sequences (the same as those presented during the exposure phases), randomly intermixed with the novel sequences. Baboons performed four 96-trials blocks. Results were analyzed using a repeated-measures ANOVA conducted on RTs for the third target and involving the experiment (Mirror, Copy) and the condition (Consistent, Inconsistent) as within-participant factors. This analysis revealed an Experiment * Condition interaction (F (1, 13) = 70.92, p < .001, ηₚ² = .85). Post-hoc Tukey's HSD tests revealed that baboons were faster to respond to the third target in sequences of the form AB | BA in both experiments (mirror experiment: Mean ± SD = 307 ± 85 ms; copy experiment: 415 ± 69 ms) compared to sequences of the form AB | AB (mirror: 469 ± 43 ms; copy: 433 ± 36 ms). Results from this first pre-test confirm that baboons payed attention at least to the last displayed target. But they also indicated that immediate repetition of a target in the middle of the sequence triggered shorter response times compared with non-repeated target, regardless of the experiment. This observation is consistent with previous findings suggesting that immediate repetition of an item within a sequence is a particularly salient feature (e.g. (M. H. de Vries et al., 2008; J. Gervain et al., 2008); Malassis & Fagot, in prep). Following these observations, we decided to avoid applying violations to the first target occurring after the middle of the sequence.

In a second pre-test, baboons were therefore presented with inconsistent sequences of the form AB | BC (mirror experiment) and AB | AC (copy experiment), the last target appearing at a location that differed from those of the first half of the sequence. Experimental settings were otherwise identical to Pre-test 1. A repeated-measures ANOVA was conducted on RTs on the fourth target and involving the experiment (Mirror, Copy) and the condition (Consistent,
Inconsistent) as within-participant factors. It showed a main effect of condition, F (1, 13) =
10.62, *p* < .01, ηₚ² = .45. Baboons' response times were overall slower in inconsistent (Mean ±
SD = 466 ± 85 ms) compared to consistent sequences (443 ± 99 ms). No other main effect or
interaction were found (*ps* > .38). These results indicate that baboons detected the introduction
of an incorrect location at the end of the sequence in both experiments, confirming that they
payed attention to the first half of the sequences.

Test 1

In Test 1, 1/6 of the trials were consistent sequences (mirror: ABC | CBA, copy: ABC |
ABC), and another 1/6 of the trials were inconsistent sequences in which the last two targets
were presented in a reversed order (mirror: ABC | CAB, copy: ABC | ACB). We chose to apply
violations to the last two targets (instead to, e.g., reversing the order of the fourth and fifth
targets) because results from our first pre-test revealed that the presence/absence of a repetition
of a location in the middle of the sequence was particularly salient for the baboons. In the
remaining 4/6 of the trials, a novel set of six baseline sequences made of six instead of four
targets. These sequences were randomly intermixed with the consistent and inconsistent
sequences.

To construct the three types of sequences presented during Test 1, we randomly split the
16 possible locations in two sets. A first set of six locations (locations 1, 2, 3, 10, 13 and 15)
was used to generate six baseline sequences for each experiment. The remaining 10 locations
were used to generate 80 test sequences (20 sequences per condition and experiment).
Consistent and inconsistent sequences of Test 1 were therefore made of targets' locations which
never occurred in sequences of six targets before.

Test 1 involved four 100-trial blocks (60 baseline, 20 consistent and 20 inconsistent
sequences per block). As noted previously, the baboons received a re-exposure phase of twenty
96-trial blocks before to perform Test 1, during which they were exposed to the set of 64 4-
target baseline sequences. In addition, they were exposed right before Test 1 to the set of six 6-
target baseline sequences during one block, to familiarize them with the introduction of
additional targets.

Control Test
The control test was conducted between Test 1 and Tests 2-3. To limit potential influences of previous exposure on the Control phase, this test was administered after a 2-month of break, during which the baboons were exposed to different unrelated tasks. During this test, four types of 6-target sequences (mirror consistent, mirror inconsistent, copy consistent, copy inconsistent) were presented at equal frequencies, randomly intermixed. The control test was conducted with the same set of sequences as in Test 3, to favor comparison across tests types. Control phase involved four 64-trial blocks (16 sequences of each structure per block).

## Tests 2-3

Tests 2 and 3 were conducted concurrently. In that phase, $1/7$ of the trials were consistent 6-target sequences made of familiar 4-target baseline sequences, $1/7$ of the trials were inconsistent sequences made of the same baseline sequences, $1/7$ of the trials were consistent sequences made of novel targets combinations, and $1/7$ of the trials were inconsistent sequences made of the same novel targets combinations. During the remaining $3/7$ of the trials, baboons were presented with a novel set of 6-target baseline sequences, randomly intermixed with the consistent and inconsistent sequences.

A novel set of forty-eight 6-target baseline sequences was generated for each experiment, using the 16 locations of the matrix. Thirty-two (16 consistent, 16 inconsistent) test sequences were generated for Test 2 from combinations of 4-target baseline sequences. The same amount of sequences was generated for Test 3, using combinations of locations which were neither presented in any of the 4-target baseline sequence, nor in any of the 6-target baseline sequences generated for Tests 2-3. However, some of these combinations have already been used in other phases (pre-tests and Test 1). Our rationale was that no learning could have taken place during this previous exposure, as the combinations of locations were presented an equal number of time within consistent and inconsistent sequences. As it was impossible to both equate for the frequency of each location within each position and the familiarity *versus* novelty of the combinations of locations, the former variable was not controlled in these last phases (Tests 2 and 3, and Control). Tests 2-3 involved four 112-trial blocks (48 baseline sequences, 16 consistent and 16 inconsistent sequences from each test per block).

## Data analyses
Incorrect trials were removed from the data set (3.35 %), as well as RTs greater than three standard deviations from the mean (2.43 % of the remaining trials; computed for each participant, target and phase, after removal of trials with any abnormally long RT, i.e. > 3 seconds). All the analyses used as dependent variable the response times (RTs) on the different targets (i.e., the time elapsed between the apparition of each target and the participant's touch). For the analyses conducted on Tests 1-3, we conducted only planned pair-wise comparisons in relation to our predictions (i.e. assessment of the difference in RTs between consistent and inconsistent sequences), and therefore use two-tailed paired t-tests with Bonferroni-Holm correction (alpha level = .05). Other post-hoc analyses were conducted using Tukey's HSD tests, as we had no predictions regarding other differences in RTs. Statistical analyses were done with R (V3.1.1, www.R-project.org).

## Results

### Main results

Analyses conducted on the response times (RTs) in Tests 1-3 for each experiment (Figure 2), were performed using a repeated-measures ANOVA involving the condition (Consistent, Inconsistent), experiment (Mirror, Copy), test (1-3), and target (4-6) as within-participant factors. It revealed a significant interaction among condition, experiment and target ($F(2, 26) = 7.43, p < .01, \eta_p^2 = .37$). Pairwise comparisons between RTs in the consistent and inconsistent conditions showed a reliable difference in the mirror experiment for Target 5. This difference corresponded to slower response times on the first violation occurring in mirror sequences. No other significant difference was found between these two conditions. Importantly, no interaction between these factors (condition, experiment, target) and test was found ($p = .44$), indicating that the observed slowdown did not differ among tests. This result confirms that baboons reacted to violations of the mirror structure occurring in test sequences containing familiar baseline sequences, as well as to those occurring in sequences made of entirely novel combinations of locations. Consequently, baboons' results in this mirror experiment cannot be accounted for by rote learning of the baseline sequences, but instead reveal correct generalization to novel sequences following a mirror pattern. By contrast, baboons' response times remained unaffected by the violations occurring in copy sequences.
Taken together, these results suggest that baboons are sensitive to the mirror structure, while they fail to notice, or exploit, the copy structure in the current task.

<figure><img src="image_70.png" /><figcaption>**Figure 2** Mean response times on each target and for each condition, in Tests 1-3 of the mirror and copy experiments. Error bars represent standard errors after subtraction of the individuals mean response times.</figcaption></figure>

To tease apart sensitivity to the mirror structure after repeated exposure and potential effects of idiosyncratic features of the different sequences types, data from the Control phase were analyzed. As a consistency effect was only observed for Target 5 in Tests 1-3, we examined RTs on that target as a function of sequence type. We found no difference between mirror consistent (Mean ± SD = 458 ± 53 ms), mirror inconsistent (462 ± 59 ms), copy consistent (456 ± 41 ms) and copy inconsistent sequences (449 ± 58 ms), $F(3, 39) = 0.77, p = .52$ in the Control test. This result confirms that when they are presented at equal frequencies, the different sequence types did not elicit differential response times.
Additional results

The ANOVA conducted on data from Tests 1-3 (Figure 2), also revealed a significant
interaction between experiment and target, F (2, 26) = 43.18, p < .001, ηₚ² = .77. Post-hoc
analyses showed that RTs differed among the three targets, for both experiments (Mirror: Target
1 < Target 2 < Target 3; Copy: Target 1 > Target 2 < Target 3). RTs were moreover significantly
faster in the mirror experiment compared to the copy experiment for Target 1, and longer for
Target 3. The ANOVA revealed in addition a main effect of experiment, F (1, 13) = 26.76, p <
.001, ηₚ² = .67, corresponding to overall faster RTs in the mirror (Mean ± SD = 433 ± 199 ms)
compared to the copy experiment (461 ± 193 ms). This effect appears however to be attributable
to the especially fast RTs on the first target in the mirror experiment. The ANOVA revealed a
main effect of target as well, F (2, 26) = 27.63, p < .001, ηₚ² = .68, corresponding to significantly
slower RTs for Target 3 (496 ± 233 ms) compared to both Targets 1 (416 ± 195 ms) and 2 (430
± 144 ms). Finally, a main effect of test was found, F (2, 26) = 10.70, p < .001, ηₚ² = .45, RTs
being overall greater in Test 3 (466 ± 208 ms) compared to both Tests 1 (432 ± 190 ms) and 2
(447 ± 193 ms). This result suggest that baboons were slower to perform the novel motor
transitions involved in Test 3.
DISCUSSION GENERALE

<figure><img src="image_71.png" /></figure>
# I. Résumé et Discussion des Travaux Expérimentaux

Dans cette thèse, nous avons étudié le traitement de régularités séquentielles et grammaticales dans une perspective comparée. Nous nous sommes plus particulièrement intéressés au traitement des grammaires supra-régulières. Une revue de la littérature sur l'apprentissage de grammaires artificielles a montré qu'aucune étude ne permettait de conclure de manière non-ambiguë quant à la capacité d'une autre espèce que l'humain à traiter ce type de grammaire. L'objectif de cette thèse était d'examiner l'hypothèse selon laquelle ces échecs soient imputables à des difficultés que rencontrent les animaux NH pour le traitement des dépendances non-adjacentes et l'extraction de propriétés structurelles.

Cette hypothèse a été testée à l'aide d'une série de quatre études menées chez le babouin de Guinée, visant d'une part à vérifier que l'extraction de régularités à longue distance pose des difficultés particulières à cette espèce (Etudes I-III), et d'autre part à tester si les babouins s'avéraient sensibles à des grammaires supra-régulières dans des conditions expérimentales prévenant l'exploitation exclusive de régularités locales (Etude IV).

<table><caption>**Table 4** Récapitulatif des études réalisées, en fonction de la question étudiée, du type de régularité et du matériel employé.</caption><thead><tr><th>Question</th><th>Etude</th><th>Régularités</th><th>Matériel</th></tr></thead><tbody><tr><td rowspan="3">Effet de distance</td><td>Etude I</td><td>Associations</td><td>A<sub>1</sub>XB<sub>1</sub>, A<sub>2</sub>XB<sub>2</sub></td></tr><tr><td>Etude II</td><td>Répétitions</td><td>AA, ABA</td></tr><tr><td>Etude III</td><td>Associations &amp; Répétitions</td><td>A<sub>1</sub>XB<sub>1</sub>, A<sub>2</sub>XB<sub>2</sub> (Etude I), AA, ABA (Etude II), A<sub>1</sub>B<sub>1</sub>C<sub>1</sub>, A<sub>2</sub>B<sub>2</sub>C<sub>2</sub>, A<sub>3</sub>B<sub>3</sub>C<sub>3</sub> (Minier et al. 2016)</td></tr><tr><td>Supra-régularité</td><td>Etude IV</td><td>Répétitions</td><td>ABCCBA, ABCABC</td></tr></tbody></table>
# I.1 Effet de la distance

## I.1.1 Etude I

Dans notre première étude, nous avons examiné le traitement d'associations non-adjacentes ($A_1XB_1$, $A_2XB_2$) chez le babouin et l'humain. Dans une série de deux expériences, nous avons mis en évidence des continuités, mais également des discontinuités entre ces deux espèces. Dans l'Expérience 1, nous avons montré que les babouins étaient capables d'apprendre des dépendances non-adjacentes dans une tâche de pointage sériel. La deuxième expérience montre que le babouin partagent avec l'humain (e.g. Frost & Monaghan, 2016) la capacité à généraliser les associations non-adjacentes apprises à de nouveaux éléments intermédiaires. Ces données confirment que les babouins ont bien appris les dépendances entretenues entre les éléments non-adjacents, plutôt qu'une collection de triplets. Les performances de généralisation des babouins sont toutefois influencées par des facteurs perceptifs (ici, spatiaux), ce qui fait écho à des résultats obtenus chez l'humain pour l'extraction de régularités dans la modalité auditive (e.g. Creel, Newport, & Aslin, 2004; Onnis, Monaghan, Richmond, & Chater, 2005).

Mais cette étude montre également que l'apprentissage de dépendances non-adjacentes nécessite une quantité d'exposition considérablement plus importante chez les babouins que chez des humains testés dans des conditions expérimentales similaires. En effet, on observe cet apprentissage après 400 présentations de chacune des dépendances non-adjacentes chez le babouin, tandis qu'il est observé dès les 50 premières présentations chez l'humain. Ces données sont à comparer avec celles obtenues dans une autre étude menée au sein de notre laboratoire (Rey, Minier, Malassis, Bogaerts, & Fagot, 2018, en annexe p. 324). Dans cette étude, babouins et humains devaient apprendre des dépendances adjacentes dans une tâche de pointage sériel. Dans ce cas, et pour ce type de dépendances, il n'y avait pas de différence dans les dynamiques d'apprentissage entre ces deux espèces. Les résultats rapportés dans notre l'Etude I ne semblent donc pas refléter une difficulté d'ordre générale pour le babouin à extraire des régularités dans la tâche de pointage sériel. Ces résultats sont particulièrement intéressants au regard de la première hypothèse de travail de cette thèse : l'extraction de régularités à longue distance, qui constitue un prérequis cognitif pour le traitement de grammaires supra-régulières, semble bien présenter une difficulté particulière pour le babouin par rapport à l'humain.
I.1.2 Etude II

Dans notre seconde étude, nous avons examiné l'hypothèse selon laquelle les babouins sont plus sensibles à des régularités structurelles locales (pattern comportant une répétition immédiate d'un élément) qu'à des régularités plus distantes (pattern comportant une répétition non-adjacente). La première expérience montre que les babouins sont capables d'apprendre et de généraliser ces deux types de patterns. Ils réagissent toutefois davantage aux violations de répétitions immédiates qu'à des violations des dépendances non-adjacentes. Dans une deuxième expérience, nous avons examiné si les babouins s'avéraient sensibles aux répétitions même lorsqu'elles n'étaient pas prédicibles, en leur présentant à fréquence égale des séquences de la forme ABB, ABA et ABC. Les données obtenues révèlent que les babouins sont sensibles uniquement aux répétitions adjacentes dans ces conditions. Ils présentent une tendance à répondre plus rapidement à celles-ci dès les tout premiers essais, ainsi qu'une accélération progressive au cours de l'expérience, tandis que leurs temps de réponse restent stables pour les deux autres types de séquences. Nous avons vu dans la section V.1 du volet théorique que la sensibilité aux répétitions adjacentes et non-adjacentes suit chez l'humain un calendrier développemental différent, une sensibilité à ces premières étant observée plus précocement (Gervain, Macagno, Cogoi, Pena, & Mehler, 2008; Gervain & Werker, 2013; Johnson et al., 2009). Nos résultats rejoignent ces données, en montrant que les répétitions immédiates sont particulièrement saillantes pour le babouin. Des expériences comparatives supplémentaires seront nécessaires pour vérifier si ce phénomène est partagé avec d'autres espèces, notamment par des espèces animales qui ne font pas partie de l'ordre des primates. Toutefois, notre étude permet plusieurs conclusions sur les plans méthodologique et théorique.

Du point de vue des méthodes, les résultats de notre étude rendent discutable l'utilisation de procédures comparant des patterns à répétition immédiate (AAB/ABB) à d'autres patterns comportant une répétition non-adjacente (ABA) pour l'étude de l'apprentissage de régularités structurelles (Chen, van Rossum, & ten Cate, 2015; Hauser & Glynn, 2009; Murphy, Mondragón, & Murphy, 2008; Ravignani & Sonnweber, 2017; Spierings & ten Cate, 2016; van Heijningen, Chen, van Laatum, van der Hulst, & ten Cate, 2013). En effet, la plus grande difficulté à apprendre les patterns ne comportant aucune répétition adjacente (ABA) que met en évidence notre étude ne permet pas d'exclure la possibilité que les animaux testés se basent exclusivement sur la détection de la présence d'une répétition immédiate dans ces tâches (ten
Cate & Okanoya, 2012). Pour éviter ce problème d'interprétation, nous préconisons donc d'employer la méthodologie de notre première expérience (sur le modèle de Gervain et al. 2008; Gervain & Werker, 2013), dans laquelle nous avons comparé chacun de ces deux patterns à des séquences ne comportant pas de répétition (ABC). D'autre part, nos résultats tendent à confirmer que la grammaire A<sup>n</sup>B<sup>n</sup> n'est pas adaptée pour tester l'hypothèse de la supra-régularité. En effet, les séquences générées par cette grammaire (qui consistent en un nombre *n* d'éléments appartenant à une catégorie A suivis du même nombre *n* d'éléments d'une catégorie B, les catégories A et B étant marquées perceptivement) comportent nécessairement des répétitions immédiates d'éléments appartenant à une même catégorie perceptive. Les résultats des deux études ayant examiné les stratégies individuelles employées par les animaux (van Heijningen et al., 2009; Ravignani et al., 2015) avaient déjà mis en évidence que la détection de répétitions immédiates était une stratégie privilégiée par une majorité de participants. La présente étude confirme que ces répétitions constituent un indice extrêmement saillant qui nécessite peu d'exposition pour être détecté. Etudier le traitement de grammaires supra-régulières doit donc passer par l'utilisation de grammaires ne permettant pas aux participants d'utiliser cette stratégie (grammaires centrées-emboîtées et croisées).

D'un point de vue théorique, ces données interrogent la nature des mécanismes sous-
tendant la détection des répétitions. Nous avons vu dans la section V.3.3 du volet théorique que certains auteurs proposent l'existence de mécanismes spécialisés pour cette opération (Endress, Dehaene-Lambertz, & Mehler, 2007; Endress, Nespor, & Mehler, 2009). Les résultats de notre seconde expérience sont compatibles avec cette hypothèse, puisque d'un point de vue statistique l'occurrence de ces répétitions était équiprobable avec les deux autres types de structure (ABA et ABC). Notre étude suggère donc que si ces mécanismes sont à l'origine la détection des répétitions, ils sont largement partagés au sein de la lignée des primates et opèrent dans différentes modalités sensorielles (ici, dans la modalité visuelle). Ils seraient toutefois limités à la détection de répétitions immédiates chez le babouin. Une explication alternative de la saillance des répétitions immédiates est qu'elles cumulent deux facteurs facilitant l'extraction de régularités statistiques : la similarité perceptive (Creel et al., 2004; Onnis et al., 2005), et leur caractère adjacent (Gebhart, Newport, & Aslin, 2009; Newport & Aslin, 2004; Wilson, Smith, & Petkov, 2015). Cette hypothèse diffère de la précédente en ce qu'elle ne postule pas l'existence de mécanismes **spécialisés** pour la détection de répétitions, mais que cette opération reposerait sur des mécanismes d'apprentissage statistique. Enfin, les résultats de notre seconde
étude illustrent de nouveau un effet majeur de la distance entre les éléments entretenant des relations prédictives sur les performances des babouins.

### I.1.3 Etude III

Dans notre troisième étude, nous avons examiné les performances individuelles des babouins dans différentes études (nos Etudes 1 et 2, ainsi que celle de Minier, Fagot, & Rey, 2016). Ces analyses ont révélé que pour un même type de dépendances (adjacentes d'une part, et non-adjacentes d'autre part), les performances sont fortement corrélées d'une expérience à l'autre. En revanche, les babouins qui parviennent à extraire les dépendances non-adjacentes ne sont pas ceux obtenant les meilleures performances dans les tâches d'apprentissage de régularités adjacentes. Ces résultats rejoignent ceux obtenus dans des études employant des méthodes similaires chez l'humain (Misyak & Christiansen, 2012; Siegelman & Frost, 2015). Les études de ce type sont encore peu nombreuses, mais l'étude des différences inter-individuelles offre une porte d'entrée vers une meilleure compréhension des mécanismes d'apprentissage sous-jacents (Frost, Armstrong, Siegelman, & Christiansen, 2015; Siegelman, Bogaerts, Christiansen, & Frost, 2017). Nos résultats montrent que ces questions peuvent être étudiées chez l'animal NH comme elles le sont chez l'humain, en administrant à un même groupe d'individus différentes tâches d'apprentissage de régularités séquentielles.

L'absence de corrélation statistiquement significatives entre performances individuelles dans des tâches d'extraction de régularités adjacentes et non-adjacentes suggère que des contraintes différentes opèrent sur ces deux apprentissages. Notre hypothèse selon laquelle les capacités d'apprentissage de régularités non-adjacentes seraient corrélées avec les capacités de la mémoire de travail de l'individu n'est que partiellement validée par nos analyses. Des recherches supplémentaires sont donc nécessaires pour tester cette hypothèse. Selon une explication complémentaire, cette absence de corrélation pourrait également s'expliquer par des différences inter-individuelles dans les stratégies employées. Pacton, Sobaco, et Perruchet (2015; voir également Pacton & Perruchet, 2008) ont en effet proposé que ces deux types de dépendances sont traitées par les mêmes mécanismes d'apprentissage statistiques, mais que les processus attentionnels contraignent le type de dépendances apprises (voir section V.3.2 du volet théorique). Selon cette théorie, c'est le traitement attentionnel conjoint de deux éléments qui permet d'apprendre les relations qu'ils entretiennent, indépendamment de leur distance. Les
événements proches dans le temps ayant une plus grande probabilité de se retrouver simultanément - ou presque - dans le focus attentionnel, ceci expliquerait que les relations adjacentes soient de plus souvent celles traitées « par défaut » (e.g. Gómez, 2002). Du moins, c'est le cas lorsque d'autres facteurs n'entrent pas en conflit avec cette proximité temporelle. Or, dans nos expériences, les régularités non-adjacentes impliquent systématiquement les éléments situés aux deux extrémités des séquences (e.g. A₁XB₁, ABA). Les extrémités des séquences sont connues pour être particulièrement saillantes<fnref n="33" />. Ainsi, certains babouins pourraient focaliser leur attention sur les événements proches dans le temps (i.e. adjacents), tandis que d'autres se focaliseraient davantage sur les évènements situés en début et fin de séquence, ce qui pourrait expliquer au moins en partie les différences inter-individuelles observées.

Enfin, le fait que les performances individuelles des babouins tendent à être corrélées d'une tâche à l'autre pour un même type de dépendance est particulièrement intéressant. La corrélation positive significative observée entre les performances individuelles des babouins dans une tâche d'apprentissage de probabilités transitionnelles entre éléments adjacents (Minier et al., 2016), et dans une tâche de détection de répétitions immédiates (Etude II), supporte l'hypothèse selon laquelle ces deux opérations reposeraient sur les mêmes mécanismes d'apprentissage statistique, plutôt que l'hypothèse selon laquelle la détection de répétitions reposerait sur un mécanisme spécialisé. Il est toutefois impossible de conclure sur la base d'analyses de corrélations, et d'autres méthodes devront être employées pour infirmer cette hypothèse ou la valider.

### I.1.4 Conclusions sur les Etudes I-III

Prises dans leur ensemble, ces trois premières études tendent à valider notre première hypothèse de travail, qui était que les babouins rencontrent des difficultés particulières pour l'extraction de dépendances non-adjacentes. Rappelons que chez l'humain, une tendance similaire est observée : les régularités locales tendent à être exploitées en priorité (e.g. de Vries, Monaghan, Knecht, & Zwitserlood, 2008; Wilson et al., 2015). Notre hypothèse n'est donc pas

<footnote n="33">³³ Du fait des effets classiques de primauté et de récence, ou, selon certains auteurs, de l'existence de mécanismes spécialisés dans l'extraction de régularités présentes en bordure de séquence (e.g. Endress et al., 2009).</footnote>
qu'il existe une discontinuité entre humains et NH dans la priorité donnée au informations locales et à plus longue distance. Mais que ce bais vers l'exploitation d'informations locales serait plus fort chez l'animal NH, du fait d'une asymétrie plus importante dans le degré de difficulté que présente l'apprentissage de ces deux types de régularités.

Une limite de cette thèse est qu'elle avait pour objectif de mettre en évidence ce phénomène, et non d'en offrir une explication. Des travaux devront être consacré à cette question<fnref n="34" />. En définitive, les résultats de nos trois premières études tendent à confirmer que les échecs des différentes espèces testées sur l'apprentissage de grammaires supra-régulières (e.g. van Heijningen, Visser, Zuidema, & ten Cate, 2009; Ravignani, Westphal-Fitch, Aust, Schlumpp, & Fitch, 2015) puissent être imputéss-au moins en partie- à des limitations cognitives pour le traitement de régularités non-adjacentes.

# I.2 Traitement de grammaires supra-régulières

## I.2.1 Etude IV

Dans notre quatrième et dernière étude, nous avons testé la capacité des babouins à traiter des grammaires supra-régulières: une grammaire en miroir, qui implique des dépendances centrées-emboîtées, et une grammaire en copie, qui implique des dépendances croisées (Fitch & Friederici, 2012). Nous avons proposé en conclusion de la section II.2 (volet théorique) qu'un matériel expérimental permettant l'exploitation d'indices locaux saillants n'était pas adapté pour tester la capacité d'une espèce à traiter une grammaire donnée. Nous avons donc, en complément de notre choix de ne pas utiliser la grammaire AⁿBⁿ, choisi d'employer une tâche d'un type nouveau. Dans une adaptation de la tâche de pointage sériel, les babouins devaient visionner la première moitié d'une séquence de déplacement d'une cible,

<footnote n="34">³⁴ Les différences de performances pour l'extraction de régularités non-adjacentes entre l'humain et les autres espèces pourraient notamment découler de différences interspécifiques de capacité de stockage en mémoire de travail (Etude III ; Joël Fagot & De Lillo, 2011), de compression de l'information (e.g. Chekaf, Cowan, & Mathy, 2016; Chekaf, Gauvrit, Guida, & Mathy, 2018), ou encore de formation de représentations explicites et le recodage verbal (e.g. Rey et al., 2018).</footnote>
avant de suivre la cible dans la deuxième moitié de la séquence. Cette tâche implique donc que
le participant émette une réponse sur chaque élément prédictible plutôt que d’effectuer un
jugement sur la séquence (jugement pouvant être effectué comme nous l’avons vu en exploitant
exclusivement une sous-partie de la séquence, van Heijningen et al., 2009; Ravignani et al.,
2015). Dans notre tâche, les babouins étaient donc encouragés à traiter l’ensemble des
régularités présentes dans les séquences. L’utilisation de cette procédure nous a permis de
mettre en évidence des résultats suggérant pour la première fois chez une autre espèce que
l’humain la capacité à traiter la grammaire en miroir. En revanche, les babouins se sont révélés
insensibles à la grammaire en copie dans cette tâche.

Ces données suggèrent que cette espèce de primates NH possède des capacités
computationnelles supra-régulières. Cependant, ces capacités semblent restreintes aux
grammaires non-contextuelles comme la grammaire en miroir, puisque les babouins échouent
à traiter la grammaire en copie, qui est un exemple de grammaire contextuelle. Ces données
sont compatibles avec la hiérarchie proposée par Chomsky, les grammaires non-contextuelles
constituent l'ensemble des grammaires supra-régulières ayant la puissance générative la plus
restreinte (1956, 1957 ; voir Figure 3, p. 20). Les capacités computationnelles des babouins
resteraient donc plus limitées que celles des humains, ces derniers parvenant à traiter des
dépendances croisées, dans les langues naturelles (Bresnan, Kaplan, Peters, & Zaenen, 1982;
Culy, 1985; Jäger & Rogers, 2012), et dans des paradigmes d'apprentissage de langages
artificiels (Uddén, Ingvar, Hagoort, & Petersson, 2012).

Nous proposons cependant une explication alternative de nos résultats. Nos données
suggèrent en effet l'existence d'un effet de récence important dans notre étude. L'effet de
récence correspond à une meilleure rétention des derniers éléments de la première moitié de la
séquence. Cet effet prédit des temps de réponse plus rapides pour les premiers éléments de la
seconde moitié de la séquence. Or ceci est bien observé dans l'expérience testant leur capacité
à traiter la grammaire en miroir (Figure 29). Un tel effet de récence pourrait avoir facilité
l'apprentissage de cette grammaire (Rey, Perruchet, & Fagot, 2012). En suivant la même
logique, l'apprentissage de la grammaire en copie aurait pu bénéficier d'un effet de primauté
(meilleure rétention des premiers éléments, ce qui prédit des temps de réponse plus courts sur
la première cible par rapport à la seconde cible, et sur la seconde par rapport à la troisième).
Mais nous n'observons pas cet effet : la Figure 29 montre les temps de réponse des babouins
pour la grammaire en copie ne sont pas plus rapides pour le premier élément par rapport au
second. En l'absence de cet effet, cette facilitation potentielle n'est pas disponible pour la
grammaire en copie.

<figure><img src="image_72.png" /><figcaption>**Figure 29** Temps de réponse (RTs) des babouins dans l'Etude IV, moyennées sur les Tests 1-3, pour les séquences congruentes dans les expériences testant l'apprentissage de la grammaire en miroir (à gauche), et de la grammaire en copie (à droite).</figcaption></figure>

Des expériences ayant étudié la mémorisation de séquences de stimuli chez le primate
NH ont montré que seul un effet de récence était observé lorsque le délai entre la présentation
de cette séquence et le test est court (Wright, Rivera, Katz, & Bachevalier, 2003), comme c'est
le cas dans la tâche que nous avons utilisée (avec un délai de 350ms entre les deux moitiés de
la séquence). Pour des délais plus longs, en revanche (à partir de deux secondes chez le macaque
rhésus, et de dix secondes chez le capucin), on observe également un effet de primauté (Wright
et al., 2003). Il serait donc essentiel de tester la capacité des primates NH à traiter des
grammaires en copie avec un délai plus important entre les deux moitiés de séquences.

L'idée ici n'est pas de réduire le traitement de grammaires supra-régulières à une tâche
de mémorisation de séquence. En effet, l'extraction de régularités grammaticales implique un
traitement des propriétés structurelles d'un ensemble de séquences isomorphes, et non pas
seulement la rétention en mémoire de travail d'une séquence<fnref n="35" />. Mais nous proposons que les
propriétés de la mémoire de travail soient susceptibles de jouer un rôle clé dans la définition du
type de structure que pourra traiter un système cognitif.

Les résultats de l'Etude IV sont corroborés par un travail mené en parallèle par Wang & Dehaene (soumis) chez le macaque. Dans cette étude, l'apprentissage de grammaires en miroir et en copie a été testé à l'aide d'une tâche de production de séquences. Les séquences étaient séparées en deux moitiés, et pour la première moitié les singes devaient seulement regarder la cible se déplacer, comme dans notre expérience. Mais les singes devaient ensuite non pas suivre les déplacements de la cible, mais produire la seconde moitié de la séquence (i.e. les réponses n'étaient pas indicées). Cette recherche a montré que, dans ce dispositif, les singes étaient capables, après un entraînement conséquent, de produire des séquences en miroir et en copie. De plus, ils ont pu généraliser la grammaire en miroir à de nouvelles séquences et de nouvelles configurations, ce qui confirme que les singes n'ont pas seulement appris un ensemble de séquences, mais bien extrait la règle abstraite sous-jacente. Malheureusement, cette étude ne comporte pas de test de généralisation pour la grammaire en copie, ce qui interdit toute conclusion quant à la capacité du macaque à traiter une grammaire contextuelle.

I.2.2 Conclusions sur l'Etude IV

Notre étude suggère donc que le babouin est capables de maîtriser une grammaire en
miroir, et possèdent donc a minima une mémoire « à pile » (Chomsky, 1956, 1957; Fitch, 2014 ;
voir la section I.2 du volet théorique). Ce travail révèle donc la capacité d'une espèce animale
NH à traiter une grammaire supra-régulière, capacité qui avait été proposée comme étant
potentiellement restreinte à l'espèce humaine (Fitch & Hauser, 2004). Nos résultats vont dans
le sens de la seconde hypothèse de travail de cette thèse, i.e. que la mise en évidence de la
capacité d'une espèce à traiter une grammaire supra-régulière nécessite de prévenir

<footnote n="35">³⁵ Les données de notre étude montrent bien que les temps de réponse des babouins ne reflètent pas simplement un effet de récence. En effet, dans notre expérience contrôle, dans laquelle nous avons présenté à fréquence égale des séquences congruentes et non-congruentes, les babouins ne se comportent pas différemment en réponse à ces deux types de séquences. En revanche, après une exposition répétée à des séquences générées par la grammaire en miroir, ils réagissent à la violation survenant dans les séquences non-congruentes avec cette grammaire. C'est donc bien une extraction de la structure en miroir que nous observons dans notre étude, mais nous proposons que cet apprentissage ait pu être favorisé par un effet de récence.</footnote>
l'exploitation exclusive de régularités locales pour effectuer la tâche. Toutefois, le succès du babouin à traiter une grammaire en miroir comme celui du macaque (Wang & Dehaene, soumis), mis au regard des échecs des différentes espèces précédemment testées (singe tamarin, Fitch & Hauser, 2004; diamant mandarin, van Heijningen et al., 2009; kéa et pigeon, Ravignani et al., 2015), peuvent également refléter des différences interspécifiques dans la capacité à traiter des grammaires supra-régulières. La conduite d'études comparatives chez ces différentes espèces, en manipulant de manière systématique le type de grammaire et de tâche utilisés permettra de valider l'une ou l'autre de ces hypothèses.

## I.3 Conclusions sur les procédures expérimentales

La conduite d'expériences contrôlés en laboratoire permet, en complément de l'observation des comportements et productions naturelles, d'étudier finement les mécanismes entrant en jeu dans le traitement de régularités grammaticales. Mais cette méthode rencontre fréquemment des critiques, qui portent notamment sur le fait que ces expériences impliquent fréquemment un entraînement conséquent des animaux, comme c'est le cas des expériences que nous avons mené dans cette thèse.

Watumull, Hauser, Roberts, & Hornstein (2014) ont ainsi proposé que la conduite d'expériences comparatives reposant sur un paradigme d'habituation-déshabituation<fnref n="36" /> soit à privilégier par rapport à l'emploi du conditionnement opérant, qui peut impliquer un entraînement sur des centaines, voire milliers d'essais. Ceci repose toutefois sur une sous-estimation de la quantité d'exposition typiquement dispensée dans les tâches d'habituation-déshabituation. Dans une expérience testant l'apprentissage de dépendances non-adjacentes chez le tamarin par exemple, Newport, Hauser, Spaepen, et Aslin (2004) exposent les participants à ces régularités durant 21 minutes. Au cours de ces 21 minutes, chaque dépendance

<footnote n="36">³⁶ Pour rappel, dans les paradigmes d'habituation-déshabituation, les participants sont typiquement exposés de manière passive à des régularités (e.g. auditives) durant quelques minutes. Puis ce qu'ils ont appris est évalué en mesurant les réponses d'orientation (latence, durée) du participant lors de la diffusion de séquences congruentes et non-congruentes avec ces régularités. Ces expériences n'impliquent pas de renforcement des réponses des participants. Dans un paradigme de conditionnement opérant, les participants sont renforcés différentiellement (i.e. ils reçoivent une récompense en cas de réponse correcte, tandis qu'ils ne reçoivent pas de récompense et se voient éventuellement infligés une pénalité en cas de réponse incorrecte).</footnote>
est diffusée 672 fois au total. A titre de comparaison, la première expérience de notre Etude I, dans laquelle nous examinions le décours temporel de cet apprentissage chez le babouin et l'humain, impliquait 500 présentations de chaque dépendance non-adjacente. La quantité d'exposition dispensée dans ces deux études, qui impliquent pourtant des paradigmes expérimentaux bien différents, est donc sensiblement similaire.

Les tâches que nous avons utilisées dans cette thèse correspondaient à un troisième type de paradigme expérimental, reposant sur un renforcement non-différentiel. Les babouins étaient récompensés à chaque fin d'essai (i.e. à chaque complétion correcte de séquence), qu'ils aient extrait ou non les régularités sous-jacentes. Cette méthode a pour avantage de (1) maintenir la motivation des participants, (2) s'assurer qu'ils traitent les séquences, (3) permettre d'avoir une mesure continue de l'apprentissage. Cette procédure offre donc la possibilité de collecter des données comparatives de qualité, puisqu'elle met les animaux dans des conditions de simple exposition aux régularités proches de celles de la plupart des tâches d'apprentissage de langage artificiel conduites chez l'humain.

De manière plus générale, à l'instar de la plupart des expériences menées en laboratoire, les données de cette thèse ont été acquises chez un groupe de singes bien particuliers. En effet, ces individus peuvent être considérés comme étant « suren traînés » à effectuer des tâches cognitives implémentées dans des expériences informatisées. Les données obtenues sont donc susceptibles de ne pas mettre en lumière les performances typiques de cette espèce, mais leurs capacités « potentielles » (Lyn, 2017). En ce sens, la démarche poursuivie dans cette thèse n'était pas d'étudier seulement les types de régularités privilégiés par le babouin, mais d'examiner si dans des conditions expérimentales appropriées, ils parviennent à effectuer des apprentissages plus complexes.

## II. Implications pour les Théories sur l'Evolution de la Syntaxe

Nos recherches ouvrent la porte à la conduite de travaux chez le babouin visant à déterminer si elles sont également capables d'enchâssement récursif (cf. sections I.3.2 du volet théorique), la possession de capacités computationnelles supra-régulières constituant un
prérequis à cette opération (e.g. Fitch & Hauser, 2004). Il reste également à déterminer si les babouins sont capables de traiter une grammaire supra-régulière implémentée dans des séquences organisées hiérarchiquement (section I.5).

Mais nos recherches suggèrent également que les contraintes mnésiques jouent un rôle déterminant dans la définition des régularités syntaxiques que peuvent extraire les babouins. Ces contraintes mnésiques sont également observées chez l'humain : un nombre conséquent d'études montre que notre capacité à traiter des phrases suivant une structure centrée-emboîtée est limité à un faible nombre d'emboîtements (Bach, Brown, & Marslen-wilson, 1986; Hakes, Evans, & Brannon, 1976; Karlsson, 2007, 2010; Marks, 1968; George A. Miller & Isard, 1964; M. D. Wang, 1970). Une analyse de corpus effectuée par Karlsson (2007) sur plusieurs langues montre par exemple que les phrases comportant plus de deux niveaux d'emboîtement sont quasiment absentes du langage parlé. Ces données rendent la simple distinction entre grammaires régulières et supra-régulières, basée sur une notion d'infinité virtuelle (voir section I.2 du volet théorique), peu pertinente, comme le soulignent de Vries, Christiansen, et Petersson (2011): « *A theory of psychological processing typically focuses on actual and measurable performance.* » (p. 11). Etant donné les limites perceptives et mnésiques intrinsèques aux systèmes cognitifs biologiques (Petersson, Folia, & Hagoort, 2012), les théories sur l'évolution de la syntaxe prenant en compte ces contraintes pourraient s'avérer plus pertinentes (Christiansen & Chater, 2008, 2015). Wilson, Marslen-Wilson, et Petkov (2017) proposent ainsi de replacer les différents types de régularités séquentielles dans un continuum de complexité croissante, caractérisé par deux dimensions quantitatives : la distance séparant les éléments entretenant des dépendances (i.e. en termes de nombre d'éléments intermédiaires), et le nombre de dépendances à traiter, comme illustré par la Figure 30.
<figure><img src="image_73.png" /><figcaption>**Figure 30** Taxonomie de différents types de régularités séquentielles, replacées au sein d'un continuum de complexité croissante en fonction de la distance séparant les éléments dépendants (axe vertical), et le nombre de ces dépendances (axe horizontal). Modifié d'après Wilson et al. (2017).</figcaption></figure>

De manière plus générale, la perspective adoptée dans cette thèse a été de décomposer le traitement de grammaires supra-régulières en prérequis cognitifs. En poursuivant cette démarche, nous nous sommes inspirés de théories sur l'évolution de la syntaxe qui proposent que la complexité et la productivité des langues naturelles, par rapport aux systèmes de communication des autres espèces, ne s'expliquerait pas par une apparition saltatoire de certaines capacités spécifiques au cours de l'évolution récente de l'espèce humaine (e.g. la capacité d'effectuer des computations récursives, Hauser et al., 2002 ; voir également Chomsky, 2017), mais par des modifications graduelles des mécanismes cognitifs supportant le traitement des régularités séquentielles (e.g. Christiansen & Chater, 2015; Seidenberg, MacDonald, & Saffran, 2002). Dans cette perspective, les recherches comparatives menées ont pour objectif d'identifier les éléments de continuité et de discontinuité dans le traitement de régularités séquentielles, qui pourraient expliquer les différences de capacités syntaxiques observées entre l'humain et les autres espèces.

Un nombre croissant de recherches comparatives adoptent cette démarche. Par exemple, des travaux de Ghirlanda, Lind, et Enquist (2017) suggèrent des différences importantes entre
les humains et les autres espèces dans le degré de résolution des représentations de séquences.
Ces auteurs proposent que ces différences aient des conséquences majeures sur la capacité de
ces espèces à discriminer des séquences, et donc à extraire des régularités syntaxiques. Santolin
et Saffran (2018) proposent de leur côté de privilégier la conduite de recherches visant à mieux
comprendre les propriétés et contraintes des mécanismes d'apprentissage statistique chez les
différentes espèces (i.e. qui ne soient pas centrées sur la mise en évidence de capacités
supposément spécifiques à l'espèce humaine). Ces recherches pourront nous informer en retour
sur les liens que ces mécanismes entretiennent avec le traitement de la syntaxe. Toujours dans
cette perspective, nous proposons que l'étude des régularités séquentielles exploitée
préférentiellement par les animaux NH permette de mieux comprendre pourquoi ceux-ci se
focalisent sur certaines propriétés de la séquence plutôt que d'autres, souvent au détriment de
l'extraction de la grammaire sous-jacente (Chen et al., 2015; van Heijningen et al., 2009;
Ravignani et al., 2015; Spierings & ten Cate, 2016; van Heijningen et al., 2013). Par exemple,
nous avons mené une étude qui suggère que l'information positionnelle (e.g. A apparaît en
première position, B en second) est favorisée lorsqu'elle entre en conflit avec l'information
relationnelle (A est associé à B), même dans le cas de simples associations adjacentes (Fagot,
Malassis, & Medam, 2018, en annexe p. 310). Ce phénomène ne semble donc ne pas être
restreint aux régularités syntaxiques complexes.

Dans le même sens, nous proposons d'élargir cette perspective à l'étude des fonctions
cognitives qui ne relèvent pas spécifiquement du traitement des régularités séquentielles. Par
exemple, des recherches menées chez l'animal NH sur la perception visuelle montrent que le
biais vers l'exploitation préférentielle de régularités locales n'est pas seulement observé pour
des séquences. On l'observe également dans des tâches requérant de traiter des figures visuelles
complexes, impliquant l'intégration de plusieurs sous-éléments (pour une revue, voir Fagot &
Barbet, 2006). Ce type de données est susceptible de révéler des contraintes générales opérant
sur la cognition NH, qui pourraient expliquer certaines spécificités de la cognition humaine
pour des fonctions cognitives de plus haut niveau telles que le langage. Dans la section suivante,
nous discutons plus en détail de ces aspects.
### III. Perspectives : Etudier l'Evolution du Langage à travers l'Etude Comparative des Fonctions Cognitives Générales

Nous présentons ici en guise d'ouverture un chapitre théorique issu de l'ouvrage "Origins of human language: continuities and splits with nonhuman primates" (Eds. L-J Boë, J Fagot, P Perrier, & J-L Schwartz). Ce chapitre est le fruit d'une collaboration au sein de l'équipe. Nous y passons en revue des données comparatives issues de domaines d'études divers, tel le traitement de régularités séquentielles, mais également la perception visuelle ou encore la catégorisation, et recensons un certain nombre de différences se dessinant entre l'humain, d'une part, et les primates NH, d'autre part. Nous argumentons que l'étude comparative de certaines fonctions cognitives générales (i.e. non directement liées au langage) soit fondamentale pour une meilleure compréhension de l'évolution du langage humain.
Joël Fagot, Raphaëlle Malassis,
Tiphaine Medam and Marie Montant

*Laboratory of Cognitive Psychology, Institute of Language, Communication and the Brain, Aix-Marseille University, and CNRS*

# Comparing Human and Nonhuman Animal Performance on Domain-General Functions: Towards a Multiple Bottleneck Scenario of Language Evolution

**Abstract:** How come that *Homo sapiens* is the sole animal species communicating with a language (i.e., a human language)? Theorists of language evolution have mostly adopted a human-centered approach to address this question. This chapter discusses the limits of this approach and proposes an alternative that consists in studying the domain general functions that serve language comprehension and production from a comparative and evolutionary perspective. Special attention is given to domain general processes which allow humans and animals to integrate information in space and time, and thus develop perceptual and more conceptual abstract categories. This chapter presents illustrative studies that reveal the various aspects in which these integration processes differ in human and nonhuman animals. Finally, we discuss the source of these species differences and their potential implications for our understanding of language evolution.

**Keywords:** Animal communication, integration processes, categorization, language evolution, baboons

# 1. Introduction

## 1.1 Limits of strictly human-centered approaches

In the various scientific disciplines interested in language evolution – anatomy, physiology, paleoanthropology, linguistics, psychology, neurosciences, computer sciences – the precisely defined architecture of human language is classically used as the basic reference, the *canon*, to which all nonhuman communication systems are compared. Said differently, the communication system of *Homo sapiens* – an approximately 200,000 year-old isolated species (there are no other living species in the genus *Homo*) with almost
1.5kg brain tissue, living in complex societies with a long history of cultural evolution -is used as the unique reference system in most comparative studies on language evolution (for a review, Hauser et al., 2002). Obviously, this makes sense given that the purpose of these comparative studies was not to build a descriptive catalogue of other animal communication systems but to better understand human language evolution. However, when pushed too far, such an anthropomorphic approach can be misleading because, by definition, nonhuman animals cannot equal human animals in performance when it comes to human language. A current caveat in human-centered comparisons consists in assuming non-explicitly that nonhuman cognitive architectures must *resemble* human cognitive architecture, in parts or as a whole. However, such an assumption can hold only if: 1) human and nonhuman cognitive architectures had followed similar evolutionary paths and were adapted to comparable environmental, social and biological constraints, and 2) if the cognitive architecture of each species was a construction made of independent (non-interacting) cognitive components that are not sensitive to developmental and phylogenic factors. Given that every species has a unique cognitive architecture, it seems like a vain enterprise to search for strictly identical components in humans and nonhuman animals.

Consider one example: syntax. Different types of syntaxes have been formalized in Chomsky's hierarchy, from simple (finite state) grammars to complex (supra-regular) grammars. In an attempt to better understand human cognitive "uniqueness", major efforts have been put in the investigation of nonhuman species' ability to process supra-regular grammars (e.g., Fitch and Hauser, 2004; Gentner et al, 2006; Abe and Watanabe, 2011). Unsurprisingly, nonhuman animals do not equal *Homo sapiens* in that particular type of linguistic computation. The very attempt to search for strict human-like syntax in nonhuman animals implies that there is only one way to compute information in a complex communication system: the human way. This view does not consider the possibility that each species, even phylogenetically close to *Homo sapiens*, might have developed its own original and complex -possibly multimodal- cognitive architecture, which does not include human-like syntax. It also neglects the existence of interactions between the various components of a cognitive architecture whose effects increase over phylogenetical and developmental time scales (syntax might not exist as an independent computational subsystem, not even in
humans, see Seidenberg and MacDonald, 1999). These interactions make it very unlikely that complex integrated levels of computation (syntax-like processes) in the cognitive architectures of two different species resemble each other.

We must acknowledge, however, that more and more studies are looking for simpler forms of syntax in nonhuman animals. This approach has recently gained interest in the field of ethology and to some extent in linguistics (for a review, Schlenker et al., 2016; see also Petkov and Wilson, 2012). It refers to basic learning principles that allow the extraction of combinatorial semantics, statistical regularities, or adjacent and nonadjacent dependencies according to which qualitatively comparable basic learning principles are supposed to hold for human as well as nonhuman communication sequence learning (e.g., Seidenberg et al., 2002).

The narrow anthropomorphic approach of language evolution that we question here is not only found in linguistics but has dominated other domains as well, such as comparative anatomy. Rapid progress of imaging techniques over the past 20 years has spurred a frantic search for the anatomical landmark of language in *Homo sapiens*. After a couple of unsuccessful attempts to teach human vocal language to nonhuman primates (e.g., Hayes, 1951), it has become clear that our closest cousins – chimpanzees – are not able to pronounce human phonemes. The first proposed explanation for the incapacity to produce speech was that their larynx was too high (e.g., Lieberman, 1968, 1975). The existence of a physical limitation for speech in chimps has been admitted in the research community for many years. However, recent studies suggest that vocal tract anatomy cannot suffice to explain the absence of speech in nonhuman mammals (for a review, Fitch 2010). Fitch et al. (2016) inferred from X-ray videos and a modeling approach that macaca's tract has the potential to produce a broad range of speech sounds. This was confirmed in one of our recent study in which we recorded the spontaneous vocalization of baboons (*Papio papio*, Boë et al., 2017). We found that the baboons produce sounds that share the acoustic F1/F2 formant properties of human [i æ a o u] vowels, and those baboon sounds were produced by movements of the tongue in a human-like articulatory space defined by two axes (anterior-posterior and superior-inferior, see Boë et al., 2017 for more details). Therefore, the inability of nonhuman primates to produce human phonemes is more likely
due differences in the neural circuits that command oro-facial muscles, or
to other cognitive differences, than to differences in the anatomy of the
vocal tracts.

Other anatomical factors have been proposed to explain the uniqueness
of language in the human species. Most of them concern human-centered
brain features. Neuroscientists have been looking for the homologue struc-
tures of Broca's area and Wernicke's area in the brain of various apes.
Broca and Wernicke are important regions of the human brain whose injury
provokes severe language disorders, the so-called Broca's and Wernicke's
aphasias. Because of interspecific anatomical differences, direct comparisons
of brain regions across species are difficult to make. Instead, researchers
have compared brain asymmetries across species. In the human brain, the
language function is mostly hosted in the left hemisphere. Broca's area,
Wernicke's area and the *planum temporale* are bigger in the left than in the
right hemisphere (Geschwind and Levitsky, 1968). Those asymmetries, that
were first thought to be unique to humans, have been observed as well in
nonhuman primates (e.g., Cantalupo and Hopkins, 2001; Cantalupo et al.,
2003). In a recent paper, Gomez-Robles and collaborators (2013) propose
that, at a whole brain scale, there is continuity in asymmetric variation
between humans and chimpanzees: similar brain asymmetries exist in both
species, even though the human brain tends to be a little more asymmetric
and more sensitive to developmental constraints.

More recently, tremendous efforts have been put into the identification of
precise brain regions or neural structures that might be unique to humans
and explain the emergence of language in our species. For example, Leroy
et al. (2014) have proposed that the superior temporal sulcus (STS) critically
differs in human and nonhuman species: human STS is deeper in the right
hemisphere compared to the left, and this depth asymmetry is not found
in chimps. Given that STS is central in the perisylvian language region,
this particular landmark could be a promising “human-only” candidate.
However, as the authors acknowledge, the link between this anatomical
feature and the language ability in humans remains loose: MRI anatomical
measurements made on various groups of human subjects show that the STS
depth asymmetry is bigger in men than in women, it persists in children with
impaired language development, and is unchanged in adults with reversed
language lateralization (*situs inversus*). To drive the point home, an even
more recent study shows that the very same STS brain asymmetry exists in baboons (Meguerditchian et al., 2016). Further investigations on the relationship between variation in human brain anatomy (at a brain network scale) and variation in human language function are needed before one can make between-species comparisons and draw convincing conclusions about the role of precise human brain features in the evolution of human language.

The literature on human brain landmarks for language also raises a crucial question: what can gross anatomy tell us about fine-grained and complex interacting cognitive functions, in particular in a comparative perspective? Without a well-defined theoretical model of the anatomy-to-function relationship in each species that would make the comparison possible, the explanatory power of anatomy brain differences remains very limited. This would not be the case if we knew precisely the functional significance of those particular brain regions in their neural networks, in both species. For example, recent studies have shown that the homologue of Broca's area in chimps is involved in communicative behaviors (Taglialatela et al., 2008; 2011), however little is known about the type of computation it makes, or about the way it deals with a combination of communicative gestures and vocalizations, or about the way this region interacts with deeper structures involved in emotional vocalizations (Jürgens, 1979). Just like the linguistic/cognitive human-centered components, the anatomical landmarks of language -when strictly human-inspired (and functionally underspecified)- seem of very little explanatory value to understand language evolution in the human lineage, at least in the current state of our scientific knowledge.

The search for a unique (cognitive or anatomical) key factor at the origin of human language will inevitably lead to a stalemate. Brains, just like the cognitive function they host, are shaped by species-specific phylogenetical and developmental trajectories. They are complex systems and the differences between human and nonhuman brains and functions cannot be easily reduced to single “keys” components, especially when a strict human-centered definition of these components is applied.
## 1.2 An alternative ...

What could be the alternative to this narrow human-centered approach? In this chapter, we propose to step backward to enlarge our view of language evolution. Rather than focusing on the presence or absence of strictly human-inspired language features in nonhuman animals, we believe that an alternative is to examine the background of the language function, namely the inherited domain-general elements of “the machinery required to master human language” (Saffran and Thiessen, 2008), that might be used in non-human species for communicative and/or other purposes. Domain-general mechanisms correspond to learning devices that apply to a variety of different cognitive functions, as opposed to domain-specific mechanisms that are dedicated to specific cognitive functions. The opposition between domain-general *versus* domain-specific mechanisms was first proposed in a cognitive development framework where Skinner's view (1957) was opposed to that of Chomsky (1959). In the present chapter, we use the notion of domain-general mechanism in a more evolutionary perspective. This idea we defend here is that the human language-device is mainly made of domain-general elements, some of which are shared with other species (either because they were present in a common ancestor or they result from convergence processes). These inherited cognitive components are very likely to take different forms in different species, as a function of the cognitive domain they are involved in, because different domains show different regularities and constraints that shape these components. However, we expect that the close comparison between human and nonhuman performance will reveal what aspects of those domain-general cognitive components are shared across species. The underlying hypothesis we uphold here is that complex and phylogenetically recent cognitive functions, including language, are probably the product of intense re-use and re-combination of subsets of inherited anatomical, cognitive, behavioral components (Anderson 2010). Phylogenetically close species might share some (but not all) of these components, as a support of communication and/or other cognitive functions. For example, the serial organization and structuration of elements that we find in the processing of syntax might as well serve the planning of complex motor sequences in humans (Koechlin and Jubault, 2006), in other primates or in birds, including the sequences of bird's songs (Suzuki et al., 2016).
In the remaining part of this chapter, we will firstly describe some of the multilevel integrative processes that are critically involved in human language, which likely evolved from domain-general inherited functions. We will then consider and discuss main findings of the literature on comparative cognition regarding these domain general mechanisms. In this context, we will pay special attention to the mechanisms by which animals integrate stimulus information at various levels, from low level perceptual grouping mechanisms that lead to global percepts, to more cognitively complex processing mechanisms that make it possible to associate meanings to objects or categories for example. Importantly, this chapter is not aimed at making an exhaustive review of the literature regarding these cognitive processes. Our goal is to document potential *species* differences and similarities concerning these processes, and to illustrate these differences and similarities by a selection of suggestive findings. In a final section of this paper, we will discuss the potential impact of these results on our understanding of language evolution.

# 2. Integration processes in nonhuman animals

## 2.1 Integration in time and space

Language production and comprehension involve the processing of a continuous flow of information, and a temporal integration of the different linguistic elements. There is an obvious connection between sequential learning and language, because these two cognitive processes require the extraction and further handling of elements occurring in temporal sequences. However, because most behaviors have a temporal structure, the capacity to relate events in the time dimension might derive from a domain-general function that is involved in many different contexts, beyond language. We will consider below four different aspects of sequence processing, which are the ability to (1) remember sequence of events, and to process that sequence as temporally ordered, (2) to learn the transitional probabilities of items occurring in sequence, (3) to learn and process nonadjacent dependencies, and therefore to know that event A is followed by event B with intervening events between them, and (4) to gain information regarding the general structure of the sequence (i.e., syntax as concerns human language). For all these problems, we document below which aspects of sequence processing seem shared by animals and humans, and which aspects seem more restricted to humans.
### 2.1.1 *Serial list learning*

List learning corresponds to the capacity to both remember items in a list, but also to remember their temporal ordering. Nonhuman animals can learn and remember lists of items, (e.g. Terrace et al., 2003). Comparative investigations of serial list learning in animals, especially pigeons and monkeys, suggest that the memory of lists of items is not qualitatively different from what is found in humans. When taught that A<B, B<C, C<D, D<E, various nonhuman species have been able to properly order previously un-trained test pairs such as C<E. Pigeons and monkeys show serial position effects (Wright et al., 1985) sharing similarities with those of humans. Monkeys also show the symbolic distance effects found in humans: their latency to compare two items is shorter when the items are far apart in the list (e.g., AC vs CD; Colombo and Frost, 2001). All these discoveries show that animals are capable of developing representations of series of items based on their ordinal position. Although the succession of words in a sentence is not strictly equivalent to a succession of unrelated items, serial list learning capacity is probably necessary in both cases. These results encourage the view that the underlying features of the learned representations are shared by human and nonhuman animals, suggesting quite old evolutionary mechanisms for item list learning.

### 2.1.2 *Processing of adjacent dependencies and chunking*

Adjacent dependencies refer to a predictive relationship between one event and the event immediately following it in the sequence. Consider two three-item sequences, the sequences A-B-C and A-B-D, which are presented an equal number of times. In this very small corpus composed of two sequences, A is always followed by B and B is followed half time by C and half time by D. The transitional probability between A and B is thus equal to 1, while the transitional probability between either B and C or B and D is equal to .5. Consideration of the transitional probabilities is one of the mechanisms promoting the learning of auditory and visual sequences in humans (e.g., Hunt and Aslin, 2001). It is one of the mechanisms by which children learn word boundaries and segment speech streams into words: in a sentence, the transitional probability between the last syllable of a word
and the first syllable of the following word is lower than the probability between two successive syllables within one word (Saffran et al., 1996).

Comparative studies have shown that a high transitional probability between two AB items facilitates the processing of the second B item in pigeons and monkeys. Froehlich et al. (2004), for instance, tested pigeons in a serial response time task requiring to peck a stimulus appearing sequentially at three possible locations and in a predefined order. The transitional probabilities between the stimulus locations were controlled in this task, and the authors report that response time to peck is a direct function of these probabilities. Thus, high transitional probabilities gave rise to short response times at the second location of the considered pair, while low transitional probabilities gave rise to longer response times. These authors directly compared their results on pigeons to Hunt and Aslin's study conducted on humans (2001), and report that although slower, pigeons processed information at roughly the same rate as humans, as reflected in similar overall regression slopes (Figure 1).

<figure><img src="image_74.png" /><figcaption>Figure 1: Average response times of pigeons and humans depending on transitional predictability of the items in a sequence. Results on pigeons are from Froehlich et al. (2004), those on humans are from Hunt and Aslin (2001). Also shown are linear regression lines for the two sets of data. Pigeons responded slower but processed information at roughly the same rate as reflected in similar overall slopes. Figure adapted from Froehlich et al. (2004).</figcaption></figure>
In humans, the processing of transitional probabilities between adjacent elements comes with another type of processing known as chunking that consists in clustering information within sequences (e.g., the syllables in a word). Chunking in humans occurs during the memorization of verbal items, but chunking is not restricted to verbal material, and can be found as well in the visual domain (e.g., Orbán et al., 2008). Experimental evidence suggests that the capacity to organize sequences in chunks is also in the scope of numerous animal species (rats: Fountain, 1990; pigeons: Terrace, 1991; tamarins: Hauser et al., 2001; baboons: Minier et al., 2016). In a recent experiment involving a serial response time task, it was found for example that baboons organized 9-items sequences in three chunks of three items each, and that these chunks precisely included the items sharing the highest transitional probabilities (Minier, Rey and Fagot, 2016). Therefore, it seems that human and nonhuman animals are prone to statistical learning making use of transitional probabilities to both segment streams of (visual or auditory) information and organize the elements composing these streams into chunks.

### 2.1.3 Nonadjacent dependencies

Equally important for language is the capacity to detect and learn non-adjacent dependencies. Consider the following sequence structure A-X-B: A is followed by a variable item X, and item X is systematically followed by B. Given this structure, there is a nonadjacent transitional probability of 1 between A and B. Learning nonadjacent dependencies is important for language. For instance, a listener has to detect the relation between the subject and the verb in a sentence despite the presence of intervening words such as adverbs. This capacity can also be useful in very different nonlinguistic contexts, for example when we have to detect a systematic relation between two events separated in time (e.g., the ring of the doorbell signaling that someone is coming), and irrespective of the intervening other events. Experiments have shown that humans and animals can both process nonadjacent dependencies in temporal sequences of events, although non-adjacent probabilities are more difficult to detect and learn that adjacent dependencies (humans: Newport and Aslin, 2004; tamarins: Newport et al., 2004; rats: Fountain and Benson, 2006). Moreover, there are similarities
between species regarding the factors that affect the learning of nonadjacent dependencies (e.g., facilitatory effect of perceptual similarity of the nonadjacent elements in both humans and monkeys; humans: Creel et al., 2004; Gebhart et al., 2009; squirrel monkeys: Ravignani et al., 2013).

However, animals may have more difficulties when presented with complex sequences. Wilson et al. (2015) tested two monkeys and 33 humans using an auditory artificial grammar containing both adjacent and nonadjacent (long-distance) relationships. After an initial exposure to the sequences, the subjects from the two species were exposed to sequences containing violations of either the adjacent or both adjacent and nonadjacent relationships. Both species showed sensitivity to adjacent transitions, but only humans, and even roughly half of them, indicated significant sensitivity to nonadjacent dependencies. Wilson et al. (2015) concluded that in some conditions, nonadjacent probabilities are less salient in macaques than in humans. Although replications and extensions are required, this study suggests that, compared to monkeys, humans have a greater facility to deal with several dependencies of different types (i.e. both adjacent and nonadjacent) at the same time.

### 2.1.4 Learning of sequence structure

Learning the structure of a sequence requires the extraction of the relationships between the constitutive elements of that sequence. This kind of learning probably supports, among others, the encoding of grammatical and syntactic linguistic regularities (e.g., in most German sentences, the verb is at the end). However, such structural regularities also exist in many other (non-linguistic) domains, such as the motor domain. For instance, Byrne et al. (2001) reported that the preparation of food items requiring complex manipulations (thistle leaves) in wild gorillas follows a hierarchical sequential organization.

Marcus et al. (1999) have shown that very young 7-month-old infants can quickly learn that sequences of auditory stimuli follow an ABB or an ABA structure. The processing of such structures was also studied in nonhuman animals, but the results were quite inconclusive: zebra finches (Heijningen et al., 2012), rats (Toro and Trobalón, 2005) and even rhesus macaques (Procyk et al., 2000) do not seem to catch the difference between
the ABA vs ABB structures. One study compared zebra finches and humans using the same experimental procedure and stimuli (Chen et al., 2015): zebra finches did not learn these two types of structures, while humans learned them readily. There is to our knowledge only one study in which an animal species could successfully learn sequence patterns of the ABA/ABB type. This study from Spierings and Ten Cate (2016) compared two avian species, budgerigars and zebra finches, and obtained positive results in the former. From this set of experiments, we can conclude that learning the structure of sequences might very well be in the scope of some nonhuman species, but this ability is clearly not as developed as it is in humans.

### 2.1.4 *Integration in space*

We documented above that human language function makes great use of temporal information, but spatial information is also crucially important for language. Infants at very young age learn that words and communicative gestures refer to entities in their immediate surrounding space. Words also make it possible to refer to objects that are spatially (or temporally) absent (the displacement feature proposed by the linguist Charles Hock ett in 1960 to characterize human language). Finally, nonverbal forms of language, such as sign language or writing gestures strongly rely on an encoding of spatial information. No doubt that being capable to integrate and combine information in the spatial domain is also a domain general function important for a complex use of language.

In the late seventies, Navon (1977) has shown that human subjects tend to process the global shapes of visual object before they process their constitutive (local) details. This effect has been named the “global precedence effect” and is often considered to be an attentional phenom enon. Global precedence in humans was demonstrated in experimental research using large letters (global shape) made of smaller letters (local features). The degree to which animals perceive the global properties of the visual input in comparison to more featural ones has been an issue in animal cognition for some time. In our laboratory, we explored this effect in baboons (Deruelle and Fagot, 1998; Fagot and Deruelle 1997) using large shapes (square, circle, cross) made of smaller shapes (again square, circle, and cross) as stimuli. In our tests, the baboons were re-
quired to either match (Fagot and Deruelle, 1997) or identify (Deruelle and Fagot, 1998) these stimuli considering either their global or local structure. For comparative purposes, humans were also tested in the same experimental conditions.

<figure><img src="image_75.png" /><figcaption>Figure 2: Processing of the global/local stimulus structure in humans and baboons. Left: Illustration of the stimuli used with humans and baboons in Fagot and Deruelle (1997). This experiment required to match hierarchical stimuli considering their global or local structure (in this local trial, they have to match the circle made of circles, with the square made of circles, considering their common local features). Right: percentage correct obtained in humans and baboons in global and local trials. Humans showed an advantage to process the global structure of the stimuli, while baboons showed a local advantage. This local advantage in baboons is accounted for by a general difficulty to “group” the local elements of the hierarchical global/local stimuli into a global whole. Humans are much less sensitive than monkeys to the spatial distance separating the local elements (e.g., Deruelle and Fagot, 1998). Figure adapted from Fagot and Deruelle (1997).</figcaption></figure>

These experiments revealed a striking species differences in global-local processing (Figure 2). Human participants exhibited the global advantage already found by Navon (1977), whereas baboons demonstrated their best performance and fastest response times in the local condition. Several experiments were conducted to understand the cause of this human-baboon difference, which suggested that the performance of the baboons strongly depended on the distance separating the local elements (Deruelle and Fagot, 1998): when the distance was enlarged, the strength of the local bias increased and this effect was amplified in baboons compared to humans. This
effect has been replicated many times in pigeons, capuchin monkeys and chimpanzees (for reviews, see Fagot and Barbet, 2006; Fagot and Parron, 2012).

At first glance, one might consider local precedence in animals as a purely
perceptual/attentional phenomenon, but we propose that it is more than
this. One of the main properties of language is that it can convey informa-
tion about things that are not immediately present (spatially or temporally;
Hockett, 1960). This displacement feature is crucial in the comparison
between human language and other forms of primate communication. We
have previously proposed (Fagot and Barbet, 2006) that a strong local bias
limits the processing of the relation between and among objects. This effect
is for instance demonstrated in Fagot and Parron (2010), showing that an
increase in the separation of the distance between two bars of either identi-
cal or different colors limits the classification of this stimulus on a same/
different relational basis. We suggest that a strong bias in favor of a local
processing mode (in either the spatial or temporal domain) in nonhuman
animals might place important constraints on their communicative systems.
It reduces the possibility to make non (temporally or spatially) adjacent
relations between or among the communicative signals, and between or
among the communicative signals and the objects in the real word to which
they refer, especially when they are far or absent.

## 2.2 Integration of stimulus dimensions and sensory modalities.

Animals, including humans, live in a rich world of information, and dealing
with this complexity is probably critical for the survival of every species.
The processing of this complexity may be achieved by a variety of cognitive
mechanisms, which include, among others, the integration of the differ-
ent perceptual dimensions into single entities (i.e., integration of stimulus
dimensions), and the grouping of various exemplars of a given object into
categories (e.g., object categorization; see a discussion of this issue below).
Interestingly, these functions, which are of general adaptive value, are all
critical for a multidimensional/multimodal system, such as language. For
instance, speech comprehension requires that multiple prosodic (e.g., into-
nation, stress) and phonemic (e.g., voice onset time, place of articulation)
dimensions present in the acoustic signal are processed and integrated.
Language comprehension is also achieved using a multimodal/multisensory mode of processing when various auditory and visual information are simultaneously integrated (e.g., for the mapping of the lip movements with the auditory signals).

### 2.2.1 Combining multiple stimulus dimensions

Discrimination tasks are often proposed to animals as a mean to assess their perceptual abilities. Typically, stimuli are presented to the subjects, and the subjects' behavioral responses to some perceptual dimensions or combinations of dimensions are reinforced, while responses to the non-relevant dimensions are not. Evidence suggests that animals can discriminate stimuli along various dimensions: color, shape, luminance, orientation of the visual objects, or the pitch of auditory stimuli. Animals can as well base their behavioral responses on combination of two or more stimulus dimensions. For instance, Cook (2001) showed that pigeons can learn to select the computer screen area where horizontal green lines are presented, while avoiding the screen areas showing non-green lines and green lines in a non-horizontal orientation.

In their review article, Lea and Wills (2008) comment on three main trends emerging from the literature on learned discrimination in nonhuman animals. The first one is that unidimensional discrimination is easier to learn than multidimensional discrimination based on combinations of features or conjunctions. Smith et al. (2012) have for instance trained monkeys to sort sine wave gratings depending on their orientations or both the orientation and spatial frequency considered in conjunction. Learning was much faster in the unidimensional than in the bi-dimensional test condition. Another example of this effect comes from research on conceptual discrimination by monkeys (e.g., D'Amato and van Sant, 1988) and the demonstration that discrimination performance relies strongly on an analysis of features, such as color, rather than on configurations of features. Lea and Wills' (2008) second conclusion is that when the stimuli are made of multiple relevant dimensions, nonhuman animals express a tendency to focus their attention on one dimension only, mostly when this dimension has sufficient discriminative values. There are also multiple examples of this trend in the literature. In our laboratory, we found that baboons discriminated
computerized human faces considering exclusively the contour of the face (Martin-Malivel and Fagot, 2001) or pixel luminance information (Martin-Malivel et al., 2006), instead of the multiple levels of information (e.g., configural information, identity, etc.) that the facial stimuli may provide, and that humans process. Finally, Lea and Wills' (2008) report than even with ingenious experimental designs, attempts to force nonhuman animals to process multiple aspects of the stimuli mostly lead to failures. This can be nicely illustrated by Dépy et al. (1997). The baboons in this study were initially trained to discriminate between two categories of stimuli defined by the possession of any combination of two out of three possible binary features. Baboons could sort these two classes of stimuli to a good accuracy level, albeit after a long training process of several thousands of trials, but remained unable to take the three discriminative features into consideration to achieve this performance, two of the three features taking a leading role in the task.

Wang et al. (2015) recently recorded the brain activity (IRMf) of rhesus monkeys and humans in two test phases. In the first phase, subjects from the two species perceived passively sequences of four tones, the last one being either of a lower or higher pitch than the first three. After this habituation procedure, the same subjects perceived sequences violating the general structure used during the habituation phase. Thus, some test sequences contained a number of tones different from the habituation sequences (number deviant), some other sequences contained four tone units with identical pitch (sequence deviant), and a last set of sequences differed from the habituation sequences regarding both the number of items and pitch. In both species, homologous brain areas were particularly responsive to violations in number (intraparietal and dorso premotor areas), and sequence (ventral prefrontal and basal ganglia), but humans were the only primates showing a joint sensitivity to both factors in the perisylvian language region (bilateral inferior frontal and superior temporal gyri). One limitation of this study is that an absence of evidence in baboons is not the evidence of an absence. Although this study does not address directly the relationship between brain and behavior, its results suggest that the perisylvian region is involved in humans only in the integration of various stimulus dimensions contained in auditory sequences of stimuli.
### 2.2.2 Combining multiple sensory modalities

The question of multimodal integration warrants a discussion in this section, due to its relevance to the origin of language. Evidence suggests that the ability to integrate information across sensory modalities in not at all restricted to humans. Cross-modal integration was demonstrated for instance using task requiring the processing of multi-sensory stimuli (Lanz et al., 2013), cross-modal interference tasks in baboons (Martin-Malivel and Fagot, 2001), and cross-modal matching tasks in chimpanzees (e.g., Davenport and Rogers, 1970). Unfortunately, we are aware of only one study in which the performance of humans and nonhuman animals were directly compared in cross modal tasks using the same stimulus material. This experiment from Fagot et al. (2000) requested the subjects to categorize pictures of humans and baboons in one condition, and human and baboon vocalizations in another one. In this experiment, the subjects of the two species perceived a prime prior to the presentation of the stimulus to be categorized. Depending on the condition, the prime could be a picture or a vocalization of baboons or humans and three conditions were tested: intra-modal visual-visual priming, intermodal auditory-visual priming, and intramodal visual-auditory priming. Three subjects out of four in each species demonstrated intra-modal priming. Inter-modal priming was demonstrated in the three out of four human subjects in the auditory-visual condition, and all four in the visual-auditory condition, but it was only found in one baboon out of four in each intermodal condition, suggesting that inter-modal integration is more difficult in baboons than in humans. Given the small number of subjects involved in this study, a replication is warranted before drawing any firm conclusion on the evolution of intra-modal integration.

## 2.3 Categorization and conceptual integration

A central aspect of human cognition is our ability to form categories of various kinds of objects or mental entities. Categorization implies that the exemplars of each category are grouped into classes considering physical or more abstract properties. Categorization is a domain-general ability that is fundamental for a variety of more specialized functions (e.g., inference or decision making), including the language function considered in this book.
Historically, Herrnstein and Loveland (1964) were the first to demon-
strate categorical abilities in nonhuman animals. They showed that pi-
geons could sort pictures of humans and pictures devoid of humans in two
open-ended categories. Since this study, numerous papers have confirmed
that various animal species can efficiently categorize stimuli considering
low level perceptual stimulus dimensions, such as the pitch for auditory
stimuli, and the color, shape, size, motion, orientation, luminance for visual
stimuli (see for instance Berg and Grace, 2011, where pigeons were trained
to categorize sine-wave disks considering their spatial frequency and ori-
entation). However, the ability of nonhuman animals to apply categorical
processes to more abstract – human-like – stimulus dimensions remains a
matter of debate.

2.3.1 *Equivalence classes: grouping arbitrary items within the same category*

An important aspect of language is its arbitrariness. Arbitrariness corre-
sponds to the fact that nothing in the physical form (acoustic properties)
of most words refers to the objects they designate. For example, the word
“car” does not “sound” like the vehicle it refers to. Therefore, words can
refer to things in the real world, and things can refer to words, although
there is no natural or necessary connection between them. In that case,
words and objects are linked by a relation of equivalence, and the many ex-
emplars of a given category of object (e.g., many different tables that vary in
shape and color) can be categorized under a unique word label. The ability
to form arbitrary connections between words and objects during ontogeny
probably comes from the many co-occurrences of words-objects pairs that
infants encounter during development. We presume that this ability relies
on a more domain-general capacity to make associative (arbitrary) connec-
tions between items, or categories of items.

Experiments on “stimulus equivalence” have directly addressed the ca-
pacity of human and nonhuman species to group arbitrary items into cat-
egories, on the basis of their associative history (Sidman and Tailby, 1982).
The prototypical design of stimulus equivalence experiments is shown in
Figure 3. In stimulus equivalence experiments, the subject first learns a
network of associations (shown in black in Figure 3) with repeated expo-
sures to these associations. Then, probe trials (shown by the red arrows in Figure 3) test if the subject (1) can associate each stimulus to itself (e.g., associate A to A, reflexivity relation), (2) can revert the trained relations (e.g., associate B to A, symmetry), and can associate the stimuli that have a common associate (associate A to C, transitivity). According to Sidman and Tailby (1982), stimulus equivalence is fully shown if the subject demonstrates, without further training, the relations of reflexivity, symmetry and transitivity in post training trials. One may easily imagine the serious limits of a cognitive system that would fail in this task. The formation of equivalence classes has the power to permit to use stimuli interchangeably, and is probably the corner stone of complex symbolic thought.

*Figure 3: Typical paradigm for experiments on stimulus equivalence. In this experimental design, the black arrows illustrate the trained associations. The dotted arrows illustrate the untrained associations that emerge in humans after an initial training phase (e.g., Sidman and Tailby, 1982).*

<figure><img src="image_76.png" /></figure>

Equivalence relations emerge early in human infancy (23-month old, Lipkens et al., 1993). By contrast, the formation of equivalence classes seems especially difficult for nonhuman animals such as pigeons or monkeys, and among the three relations sustaining stimulus equivalence, the relation of symmetry seems the most difficult one to acquire. Lionello-DeNolf (2009) reviewed a total of 24 articles on symmetry testing, and found that the vast majority of these articles reported negative results. Moreover, the handful of articles reporting more positive findings all used a very small number of subjects who received special training procedures, such as long training combining symmetry and reflexivity trials (Frank and Wasserman, 2005) or forms of symbolic training (Pepperberg, 2006).

A recent paper from our research group nicely illustrates that difficulty (Medam et al., 2016). We trained baboons to associate pictures of bears and
pictures of cars to two different shapes which served as category labels. The baboons demonstrated category learning in this task, but failed to respond correctly when asked to reverse the trained relation and to associate the category labels to the pictures of cars and bears. The immediate conclusion from this study and others (see Lionello-DeNolf, 2009) is that the preferred mode of processing in nonhuman animals is not favorable to the spontaneous emergence of symmetrical relations, which is fundamental for the emergence of equivalences classes. Arbitrariness, as defined by linguists, requires arbitrary, bidirectional associations between the words and their referent (e.g., the written “CAT” refers to the cat animal, as the cat animal refers to the “CAT”). Evidence suggests that nonhuman animals too can form arbitrary associations between various items with no logical connections between them, but they apparently have great difficulties to process these associations as bi-directional.

### 2.3.2 First order relations

Nonhuman animals can master a broad range of discrimination tasks, and some of them involve the processing of first-order relations. First-order relations refer to spatial or more abstract relations among objects, such as the fact that an object is above or below another one, or that two objects have the same functions. Particularly important for our linguistic system is the first-order relation of sameness/differentness. Our language makes great use of categories, and the abstract concept of sameness is essential for the development of verbal categories. The concept of sameness can provide the basis for the most complex cognitive operations, such as the conservation of volumes or areas, or analogical reasoning (see below). Without this concept, we would be unable to understand sentences such as “This is a cat!”, and to get from this sentence the idea that the animal we see belongs to the cat category. We would as well be unable to understand sentences such as “It is warm again”, suggesting a similarity between the current and past weather. Comparative psychologists have shown that a variety of nonhuman animal species, such as the chimpanzee (Premack, 1983), the baboon (Wasserman et al., 2001) and the rat (Wasserman et al., 2012), succeed in learning same-different relational tasks. However, the nature of the mechanisms supporting this competence in nonhuman animals, and their similarity with humans, remain unclear.
Wright and Katz (2006) asked the following question: how much training nonhuman animals need to form the same/different concept? To answer this question, they tested pigeons, capuchin monkeys and rhesus monkeys with the same test design. Animals from the three species saw two pictures in succession on a touch screen, and two kinds of trials were distinguished. In the “same” trials, the second picture was identical to the first one, while it was different from the first one in the “different” trials. In both kinds of trials, a white key was always displayed on the right of the second picture. When the first and second pictures were identical (identical trials), then the subject was asked to touch/peck the second picture to obtain a reward. If the second picture was different from the first one (different trials), then a touch/peck at the white response key was considered correct. The monkeys needed much less items (about 32) to develop the concept of sameness, than did the pigeons (256). The number of trials children would need in this task is not known, but studies have shown that children can categorize cats as different from dogs with only 12 training exemplars (Quinn et al., 1993), and by 10 months of age, they can form categories with only 7 or 8 training exemplars (Younger and Cohen, 1986). The data therefore suggest an evolutionary trend in this ability: humans would require exposure to a smaller number of items than the other animals, to form categories and develop same/different concepts.

The concept of sameness can be applied to a broad range of attributes, from the most perceptual to the most abstract ones, and another interesting issue in the comparative literature is to know if animals use the same kind of information as humans, when solving similar tasks requiring an abstract concept of sameness/differentness. This kind of questions has been addressed extensively by Wasserman and collaborators (see review in Wasserman et al., in press; Wasserman et al., 2004). These authors trained pigeons, baboons and humans to categorize displays resembling those of the top of Figure 4. They consisted in arrays of 16 icons which were either all same (same relation) or all different (different relation). After they received this category training, the subjects were tested with arrays containing mixtures of icons, in which some icons were duplicated a number of times in the array. The authors reasoned that if the subjects have formed the concept of sameness, then they should classify the arrays containing at least one item different from the others as “different arrays”, irrespective of the fact that some icons are repeated. Figure 4 illustrates the most substantial findings of this set of experiments. This
figure indicates the percentage of different responses with the mixtures, as a function of the entropy of the stimulus. Entropy in this experiment should be understood as a quantification of the perceptual variability of the array: the all-same arrays have an entropy of 0, and the all different-arrays have the highest possible entropy value of 4 (mixtures have intermediate entropy values).

<figure><img src="image_77.png" /><figcaption>Figure 4: Use of perceptual (entropy) cues by pigeons, monkeys and humans, in a same/different discrimination task. The top panel shows the kind of displays employed in Wasserman and collaborators' experiments (Wasserman et al., 2004, left: same array, right: different array). The bottom figure shows that the same-different response of monkeys and pigeons is controlled in this task by the entropy of the arrays while 80% of the humans used more abstract cues in this task. Figure adapted from Wasserman et al. (2004).</figcaption></figure>
The bottom part of Figure 4 shows that the behaviour of the baboons and the pigeons was controlled by the entropy of the arrays, which is a perceptual cue. Response from a subset of humans (about 20% of the group) was also largely controlled by the entropy of the arrays, but this constraint was rereleased in most of the subjects (80%) who treated the arrays containing at least one item different from the others as illustrations of the “different” concept. It can therefore be concluded that humans expressed more abstract judgments than pigeons and baboons in this task. We will not present in this chapter the full series of experiments using this kind of stimuli with animals (for a recent review, see Wasserman et al., in press), but the reader should be aware that clear demonstrations also exists that monkeys can also base their same/different responses on abstract cues independently of the entropy of the stimuli (Flemmig et al., 2013). Nevertheless, although several animal species seem capable of abstract same/different judgements, humans, more readily than other animals, apply qualitative, rule-based frameworks on the Same-Different discrimination task.

### 2.3.3 Analogical (second-order) relational processing

Our linguistic systems make great use of analogies, and our capacity to produce and understand analogies is considered by many as the “the Fuel and Fire of Thinking” (Hofstater and Sander, 2013). Developmental studies have shown that analogical reasoning is facilitated in children by the capacity to represent abstract relations in symbolic terms via linguistic labels (Christie and Gentner, 2014).

Most research on analogical reasoning in animals has used the Relational Matching-to-Sample task (RMTS: e.g., Fagot and Thompson, 2011) illustrated in Figure 5. In this task, the subject first perceives one pair of objects which are either identical or different. Two comparison pairs are then presented, and the subject must indicate the stimulus pair exemplifying the same (same or different) relation as the sample pair. In other words, the task can be conceptualized as “if AA then BB, and if AB then CD”. Researchers in the domain of comparative cognition have tested several animal species, including pigeons, monkeys and apes using the RMTS task (for a review, see Wasserman, Castro and Fagot, in press). Most of these attempts failed (Thompson and Oden, 2000), but a handful of studies also provide more
positive results, in particular in tests involving thousands of training trials
(e.g., Fagot and Thompson, 2011).

<figure><img src="image_78.png" /><figcaption>Figure 5: Illustration of the relational matching task used, in baboons, with color (left part of the figure) and shape (right) stimuli.</figcaption></figure>

In our laboratory, we could demonstrate that the baboons can successfully solve the RMTS task with pairs of color patches as stimuli (Fagot and Parron, 2010, see Figure 5). In a different study (Fagot and Thompson, 2011), we could further demonstrate that baboons can also solve this RMTS task considering the shape of the items (Figure 5). Again, this cognitive feat also required an extensive training period (from 17 to 30 000 trials per subject). In both studies, the different generalization tests confirmed the real abstract nature of the processes at work in these two tasks. For instance, the baboons could continue to solve the task with a high level of performance when we used novel colors (Fagot and Parron, 2010), and novel shapes (Fagot and Thompson, 2011) as stimuli. However, although cognitive flexibility is suggested by these findings, the data also suggest limits in this processing. In Fagot and Parron's (2010) study, color cues were in fact proposed to 6 baboons, and 4 of these 6 subjects eventually learned the task. In Fagot and Thompson's (2011) study, the same task was given one year later to a larger group of subjects, including the 6 already tested in Fagot and Parron (2010). Six out of 29 baboons learned the RMTS task with shapes, but importantly, none of the baboons who had initially learned the task with colors could also learn it with shapes. In other words, learning the RMTS task with color
cues did not help at all the subjects to learn. Generalization across domains
is central to analogical reasoning in humans, and is probably what makes
human reasoning so flexible. Generalization across domains allows us, for
instance, to understand the meaning of a sentence like “atoms are like tiny
solar systems” or “life is a gift, a chocolate box”. Baboons – and probably
other nonhuman primates as well – are quite flexible to process items and
their relations within given domains, those they have been trained with
(e.g., color), but are clearly not as skilled as humans to generalize across
domains. This, we believe, is another factor that may greatly affect nonhu-
man animal’s potential for developing elaborated forms of language.

**3. Summary and Conclusions**

The main goal of the chapter was to examine the origin of human language
from the standpoint of comparative psychology. Language in its various
forms (e.g., gesture, writing, speech) is a multi-level integrative process
that requires, at the perceptual stage, the segmentation and grouping of
perceptual information to extract the general meanings of the communica-
tive signals. We have argued above that many of the integrative processes
involved in the language function are in fact domain-general processes that
can also be found in non-linguistic functions.

Considering that language uses a multitude of domain-general functions,
examination of these functions in animals and especially in nonhuman pri-
mates should provide important information on the cognitive background
that made it possible for language to emerge in our evolutionary history.
Following this reasoning, we comparatively examined in this chapter a
number of domain-general cognitive functions, which imply various forms
of integration of perceptual/conceptual information. Among the considered
functions, we examined the ability of animals to integrate information in
time and space, to combine stimulus dimensions, to group objects into cat-
egories, and to develop conceptual/relational processes (first- and second-
order concepts). Of course, this list is not exhaustive but we believe that it
represents a significant selection of basic cognitive domain-general processes
that serve language perception and comprehension.

The present overview of the literature allowed us to reach two main
conclusions. First, we have identified clear-cut demonstrations that non-
human animals are capable of grouping information in time and space, can combine stimulus dimensions, and can form categories at different levels of abstractness. Thus, we suggest that these functions are shared by humans and nonhumans, at least to some extent, and that they are not language specific (i.e., they have a long phylogenetic history). Second, the literature also reveals important differences in performance among nonhuman animals, and between nonhuman animals and humans. For example, evidence suggest that, compared to humans, in nonhuman animals the integration of information in time and space is more “local”, and the capacity to integrate the information on a larger scale is more restricted. When we come to consider how animals integrate various stimulus dimensions, experimental evidence suggest that they tend to focus on some particular physical dimensions of the stimuli more than humans do, and they hardly combine information from different stimulus dimensions. When we come to consider more general categorization processes, it appears that nonhuman primates form categories but their categories seem to be more strongly tied to the perceptual input than those of humans, and abstract processes, when they emerge, need many more trials to develop, and/or do not generalize to untrained dimensions as readily as for humans. In other words, for most of the integrative functions we have considered in this chapter, nonhuman animals show behaviors that differ at least quantitatively, if not qualitatively from human behavior, and we propose that these differences might be the bottlenecks for the evolution of language. Obviously, evolution has no direction and mastering some human-like language is not and has never been an issue in nonhuman animals. However, it might be that a particular pattern of development of these domain-general functions was a prerequisite to the emergence of human language, and that favorable conjunctions occurred only once in the phylogeny of the primate group, giving rise to the human language. The idea that some domain-general nonlinguistic functions form the bottlenecks of language evolution will be further developed below.

To account for the evolution of language, many theorists have focused their attention on language specific functions, which were considered as key factors for the evolution of human language. For example, many traditional theories claimed that only humans have a low larynx (which was disconfirmed since), or that only humans have the ability to understand
and produce recursive structures allowing an infinite variability in language production. Here, we do not want to discount these explanations, but we think that they do not take the problem at its roots. At this point in the scientific endeavor, we think that it is now necessary to step back a bit to enlarge our view of the problem. Doing so, we can imagine two different scenarios on the origin of language.

The "language-first" scenario would be that our primate/prehominid ancestors had rather limited cognitive resources and it was the appearance of language that boosted their general cognitive capacities. Although there is no doubt that language is a booster for cognitive functions, we think that this scenario does not hold. To illustrate our rebuttal of this theory, imagine an animal cognitive system with a limited working memory span of N=1 item. How could a language system develop with such limited memory resources? A clear expansion of this memory system would be required before the animal would have a chance to develop a proto-language system. This very extreme example shows that language evolution requires a cognitive background to support it, and it is only when such a cognitive background has evolved – potentially as a response to ecological pressures – that a form of proto-language can have a chance to emerge.

The second possible scenario, called “prerequisites-first”, is that language only emerged in our evolutionary history once critical domain-general functions had gained in cognitive power in our animal/pre-hominid ancestors. This scenario raises one major question: which domain general function(s), or combination of functions, must have evolved at first for the emergence of language? We have no clear answer to this question but can provide several lines of thinking on this issue. First, we note that studies focusing on the so called low level perceptual mechanisms showed important differences between the platyrrhines and catarrhines species, but very little differences are observed in perceptual functions in monkeys, apes and human species (see for instance Fobes and King, 1982 for a review of visual perception). This mere fact suggests that the evolution of these perceptual functions is probably not the factor that made the difference and triggered the evolution of speech in humans. Secondly, comparative experiments suggest more pervasive differences between humans and the other primates in two domains at least. The first domain of importance is the domain of working memory. Working memory in humans seems to depart from that of other animal
species in several important aspects, for instance regarding the ability to process large amount of information in parallel (e.g., Fagot and De Lillo, 2011), or to process long-distance dependencies (e.g., Wilson et al., 2015). Although not discussed in the context of this chapter, working memory in humans may also qualitatively depart from that of the other animals in its use of a phonological loop facilitating memorization in the short term. The second domain for which strong differences emerge between humans and the other animals is the domain of attention. Nonhuman animals seem to focus on single stimulus dimensions more than humans do, and tend to have a more local mode of processing of the perceptual input than humans. There remains a debate on whether the increase in cognitive functions followed the phylogenetic order, from the remote prosimian species to the ape species phylogenetically closest to humans (e.g., Reader et al., 2011), or whether variations in cognitive power among the different primate species have occurred at multiple times in the course of evolution, in independent unrelated primates groups, for instance under the pressure of social factors such as the complexity of the social network (Dunbar, 1998). Discussing these hypotheses is out of the scope of the current chapter. However, whatever the source of this increment in cognitive power is, we propose that the language ability appeared in the evolution of primates at a point in time where domain-general cognitive capacities, especially those pertaining to attention and working memory converged and were sufficiently developed to permit its evolution. This idea is in line with recent usage-based theories suggesting that that language could be acquired in humans by means of domain-general – evolutionary old – processes (Bybee, 2010; Tomasello, 2005).

From a more practical standpoint, we conclude from this chapter that the comparative investigation of non-linguistic, domain general functions should be considered of central importance in the debate on the evolution of language. Unfortunately, real comparative studies, in which humans and other species are tested on the same problems using the same tasks, are relatively rare in this literature, and most of them only concern a very limited number of species. Such studies will become mandatory to further test the hypothesis that the expansion of domain-general functions in nonhuman primates served as a basis for the evolution of language.
## Acknowledgements

This project was supported by ANR-16-CONV-0002 (ILCB), ANR-11-LA-BX-0036 (BLRI) and ANR-11-IDEX-0001-02 (A*MIDEX).

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IV. Conclusions

Il a été proposé que l’espèce humaine se distinguerait des autres espèces par sa capacité
à traiter des grammaires supra-régulières (Fitch & Hauser, 2004), prérequis pour la formation
des représentations récursivement enchâssées (Fitch, 2014; Hauser et al., 2002). L’étude
comparative des capacités syntaxiques en laboratoire s’est par conséquent essentiellement
concentré sur cette question cette dernière décennie (Petkov & Wilson, 2012). Notre revue
détaillée de cette littérature montre que de nombreux problèmes méthodologiques empêchent
de conclure quant à la capacité ou non d’une autre espèce que l’humain à traiter des grammaires
supra-régulières. La principale limite que nous avons identifiée est que le matériel employé
dans ces études permettait aux animaux testés de baser leur comportement sur diverses
stratégies alternatives, rendant non nécessaire le traitement de la grammaire sous-jacente.

Les travaux que nous avons mené au cours de cette thèse ont confirmé que les prérequis
cognitifs pour l'extraction de grammaires supra-régulières, et notamment l'apprentissage de
régularités non-adjacentes, posent des difficultés particulières aux babouins. Mais ils suggèrent
également que dans des conditions expérimentales prévenant l'exploitation unique de
régularités locales ils se montrent sensibles à une structure en miroir, et semblent donc posséder
des capacités computationnelles supra-régulières.

Cet ensemble de données pose la question de la pertinence de la simple distinction entre
grammaires régulières et supra-régulières pour étudier l'histoire évolutive des capacités
syntaxiques. La recherche de discontinuités évolutives permettant d'expliquer la productivité
des langues naturelles par rapport aux systèmes de communication des autres espèces pourrait
donc se focaliser à l'avenir sur d'autres pistes. Nous pensons notamment que le caractère
séquentiel du langage implique de manière particulière la mémoire, et que cette fonction
cognitive pourrait constituer l'un des facteurs cruciaux orientant le type de régularités qu'une
espèce pourra exploiter. Ces contraintes s'appliquent toutefois également, bien que dans une
autre mesure, à l'espèce humaine. Le texte de Perec rapporté au tout début de ce manuscrit
l'illustre très bien. Il s'agit d'un palindrome de lettres (i.e. suivant une structure en miroir, la
première lettre étant la même à la dernière, la seconde la même que l'avant-dernière, et ainsi de
suite):
« Trace l'inégal palindrome. [...] e mord ni la plage ni l'écart. »

Le texte dans son intégralité comprend 1247 mots. On raconte que lors d'une expérience réalisée en 1989, des enseignants et étudiants ayant lu ce texte en ont conclu qu'il devait avoir été produit sous l'influence « soit de de l'écriture automatique, soit d'un esprit gravement paranoïaque, soit de stupéfiants puissants. » (Audin & Fournel, 2014). Que penser de cette structure, qui peut être produite par un oulipien chevronné, mais ne peut être perçue par le lecteur non averti ? Etudier le traitement de la syntaxe en partant de l'usage qui en est fait, et en prenant en compte les fonctions cognitives dites *domain-general*, nous semble ainsi être l'approche la plus féconde pour comprendre l'évolution du langage.
# Glossaire

*Note : un lexique des concepts principaux de quelques concepts de linguistique générative peut être trouvé dans l'Encadré 1, p. 16.*

**ALL** : *Artificial Language Learning* – Apprentissage de langages artificiels

**AGL** : *Artificial Grammar Learning* – Apprentissage de grammaires artificielles

**BA** : *Brodmann Areas* – Aires de Brodmann

**FLT** : *Formal Language Theory* – Théorie des langages formels

**NH** : non-humain

**Dendrophilie** : hypothèse formulée par Fitch (2014), selon laquelle l'humain manifesterait une propension particulière à inférer des structures hiérarchiques à partir de données séquentielles.

**Grammaire A"B"** : grammaire supra-régulière générant des expressions constituées d'un nombre *n* d'éléments appartenant à une catégorie A suivis du même nombre *n* d'éléments d'une catégorie B, e.g. aabb, aaabbb.

**Grammaire centrée-emboîtée** : grammaire supra-régulière non-contextuelles générant des expressions constituées de plusieurs dépendances centrées-emboîtées, i.e. le dernier élément de la première moitié de la séquence est associé au premier élément de la seconde moitié, l'avant-dernier élément de la première moitié est associé au second élément de la deuxième moitié, et ainsi de suite. e.g. $A_1A_2B_2B_1$, $A_1A_2A_3B_3B_2B_1$.

**Grammaire croisée** : grammaire supra-régulière générant des expressions constituées de plusieurs dépendances croisées ; i.e. le premier élément de la première moitié de la séquence est associé au premier élément de la seconde moitié, le second élément de la première moitié est associé au second élément de la deuxième moitié, et ainsi de suite. e.g. $A_1A_2B_1B_2$, $A_1A_2A_3B_1B_2B_3$.
**Grammaire en miroir** : constitue un type particulier de grammaire centrée-emboîtée. Génère des expressions consistant en une série X, suivie par l'image en miroir de X. e.g. abba, abccba.

**Grammaire en copie** : constitue un type particulier de grammaire croisée. Génère des expressions consistant en une série X, suivie par la répétition de cette même série X. e.g. abba, abcabc.

**Grammaires supra-régulières** : grammaires générant des expressions nécessitant un automate à états-finis doté d'une mémoire additive pour être reconnues. On distingue les grammaires supra-régulières non contextuelles, requérant une mémoire « à pile » (en anglais, *push-down stack*), et les grammaires supra-régulières contextuelles, requérant une mémoire « à file » (*queue*).

**Grammaires régulières** : grammaires générant des expressions nécessitant un simple automate à états-finis pour être reconnues.

**Grammaires supra-régulières indexées** : grammaires dans lesquelles les différents éléments A et B sont appariés. e.g. $A_1A_2B_2B_1$, les index indiquant les appariements : $A_1$ est apparié avec $B_1$, mais pas avec $B_2$, etc. Les grammaires centrée-emboîtée et croisée sont des grammaires supra-régulières indexées, contrairement à la grammaire $A^nB^n$.

**Pattern** : structure sous-jacente à un ensemble de séquence isomorphes, e.g. ABB, ABA.

**Récursivité** : une fonction récursive est une fonction pouvant être réappliquée à un résultat (*output*) issu d'une application antérieure de cette même fonction. En linguistique générative, on parle d'enchâssement récursif des syntagmes.
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