# The recombined memory: associative inference in Alzheimer's disease

Mohamad El Haj, Ahmed A Moustafa, Frédérique Robin, Guillaume Chapelet

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Mohamad El Haj, Ahmed A Moustafa, Frédérique Robin, Guillaume Chapelet. The recombined memory: associative inference in Alzheimer's disease. Aging Clinical and Experimental Research, 2023, 35, pp.1005 - 1013. 10.1007/s40520-023-02372-4. hal-04597115

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<figure><img src="image_1.png" /></figure>

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# The recombined memory: associative inference in Alzheimer's disease

Mohamad El Haj<fnref n="1" />,<fnref n="2" />,<fnref n="3" /> Ⓒ · Ahmed A. Moustafa<fnref n="4" />,<fnref n="5" /> · Frédérique Robin<fnref n="1" /> · Guillaume Chapelet<fnref n="2" />,<fnref n="6" />

Received: 9 December 2022 / Accepted: 15 February 2023
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023

## Abstract

**Background** Associative inference refers to an adaptive ability that allows flexible recombination of information acquired during previous experiences to make new connections that they have not directly experienced. This cognitive ability has been widely associated with the hippocampus.

**Aims** We investigated associative inference in patients with Alzheimer's disease and control participants.

**Methods** The task has two phases. In the training phase, participants learned to encode overlapping pairs of objects (AB + BC). In the test phase, participants were invited to retrieve previously see associations (i.e., AB, BC) as well as novel associations between the previously exposed objects (i.e., AC). In addition, we test the relationship between associative inference and cognitive flexibility.

**Results** Analysis demonstrated lower associative inference in AD patients than in control participants. Interestingly, performance on the associative inference task was significantly correlated with low performance on a cognitive flexibility task in AD patients.

**Discussion** Our findings demonstrate a compromise of the ability to flexibly combine new representations from prior memories in AD, which is likely related to the hippocampal dysfunction in AD.

**Keywords** Alzheimer's disease · Associative inference · Episodic memory · Flexibility · Hippocampus

## Introduction

In everyday life, many judgments and decision-making do not require direct experience but rather require inference based on knowledge learned across distinct experiences. Consider the following example, imagine you encounter an unfamiliar person (say B) chatting with your colleague A

(i.e., association between A and B). Several minutes later, you see the unfamiliar person (B) chatting with another unfamiliar person, C (i.e., association between B and C). From the knowledge acquired on the first episode, you may infer that your colleague knows the second unfamiliar person (association between A and C). Hence, successful associative inference depends on our ability to retrieve past memories to determine how events experienced at different times are related. Associative inference may be considered as a flexible and adaptive behavior because accurate predictions and decision-making are often based on “connecting the dots” mechanisms, that is, inference on how elements of a novel experience are related to one another as well as to our previous experiences [1–3]. Considering the importance of associative inference for reasoning and decision-making, in the current study, we investigated this associative mechanism in Alzheimer’s disease (AD). We assessed associative inference in AD for the following reasons: AD has been associated with a compromise of cognitive flexibility [4, 5] and because associative inference has been considered as a mechanism based on flexibility [1]. Accordingly, one may expect for compromise of associative inference in AD.

<figure><img src="image_1.png" /></figure>

<footnote>Mohamad El Haj
mohamad.elhaj@univ-nantes.fr</footnote>

<footnote n="1">¹ Laboratoire de Psychologie Des Pays de La Loire (LPPL-EA 4638), Nantes Université, Univ Angers, 44000 Nantes, France</footnote>

<footnote n="2">² Clinical Gerontology Department, CHU Nantes, Bd Jacques Monod, 44093 Nantes, France</footnote>

<footnote n="3">³ Institut Universitaire de France, Paris, France</footnote>

<footnote n="4">⁴ School of Psychology, Faculty of Society and Design, Bond University, Gold Coast, QLD, Australia</footnote>

<footnote n="5">⁵ Department of Human Anatomy and Physiology, the Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa</footnote>

<footnote n="6">⁶ CHU Nantes, Inserm CIC04, Nantes, France</footnote>
# The recombined memory: associative inference in Alzheimer's disease

Mohamad El Haj<fnref n="1" />,<fnref n="2" />,<fnref n="3" /> Ⓒ · Ahmed A. Moustafa<fnref n="4" />,<fnref n="5" /> · Frédérique Robin<fnref n="1" /> · Guillaume Chapelet<fnref n="2" />,<fnref n="6" />

Received: 9 December 2022 / Accepted: 15 February 2023
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023

## Abstract

**Background** Associative inference refers to an adaptive ability that allows flexible recombination of information acquired during previous experiences to make new connections that they have not directly experienced. This cognitive ability has been widely associated with the hippocampus.

**Aims** We investigated associative inference in patients with Alzheimer's disease and control participants.

**Methods** The task has two phases. In the training phase, participants learned to encode overlapping pairs of objects (AB + BC). In the test phase, participants were invited to retrieve previously see associations (i.e., AB, BC) as well as novel associations between the previously exposed objects (i.e., AC). In addition, we test the relationship between associative inference and cognitive flexibility.

**Results** Analysis demonstrated lower associative inference in AD patients than in control participants. Interestingly, performance on the associative inference task was significantly correlated with low performance on a cognitive flexibility task in AD patients.

**Discussion** Our findings demonstrate a compromise of the ability to flexibly combine new representations from prior memories in AD, which is likely related to the hippocampal dysfunction in AD.

**Keywords** Alzheimer's disease · Associative inference · Episodic memory · Flexibility · Hippocampus

## Introduction

In everyday life, many judgments and decision-making do not require direct experience but rather require inference based on knowledge learned across distinct experiences. Consider the following example, imagine you encounter an unfamiliar person (say B) chatting with your colleague A

(i.e., association between A and B). Several minutes later, you see the unfamiliar person (B) chatting with another unfamiliar person, C (i.e., association between B and C). From the knowledge acquired on the first episode, you may infer that your colleague knows the second unfamiliar person (association between A and C). Hence, successful associative inference depends on our ability to retrieve past memories to determine how events experienced at different times are related. Associative inference may be considered as a flexible and adaptive behavior because accurate predictions and decision-making are often based on “connecting the dots” mechanisms, that is, inference on how elements of a novel experience are related to one another as well as to our previous experiences [1–3]. Considering the importance of associative inference for reasoning and decision-making, in the current study, we investigated this associative mechanism in Alzheimer’s disease (AD). We assessed associative inference in AD for the following reasons: AD has been associated with a compromise of cognitive flexibility [4, 5] and because associative inference has been considered as a mechanism based on flexibility [1]. Accordingly, one may expect for compromise of associative inference in AD.

<footnote>✉ Mohamad El Haj
mohamad.elhaj@univ-nantes.fr</footnote>

<footnote n="1">¹ Laboratoire de Psychologie Des Pays de La Loire (LPPL-EA 4638), Nantes Université, Univ Angers, 44000 Nantes, France</footnote>

<footnote n="2">² Clinical Gerontology Department, CHU Nantes, Bd Jacques Monod, 44093 Nantes, France</footnote>

<footnote n="3">³ Institut Universitaire de France, Paris, France</footnote>

<footnote n="4">⁴ School of Psychology, Faculty of Society and Design, Bond University, Gold Coast, QLD, Australia</footnote>

<footnote n="5">⁵ Department of Human Anatomy and Physiology, the Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa</footnote>

<footnote n="6">⁶ CHU Nantes, Inserm CIC04, Nantes, France</footnote>
We also evaluated associative inference in AD because associative inference has been widely associated with hippocampal function, a brain region that is preferentially targeted by the neuropathological processes of AD [6]. The hippocampal volume is considered as a core clinical biomarker for the development and diagnosis of AD [7–10]. The hippocampus has been widely associated with associative inference. Theoretical models suggest that the ability to flexibly combine new representations from prior memories is supported by the hippocampus via associative memory networks, in which single representations are connected to one another in terms of features they have in common [11, 12]; these networks thus allow the creation of novel, never directly experienced representation. In a similar vein, the “cross-episode binding” account [13] suggests that memory representations are separately, but flexibly encoded, and, at retrieval, they are recombined by to the hippocampus to generate new representations. These theoretical accounts have been supported by research exploring mechanisms by which the hippocampus underlies the assimilation of preexisting knowledge into new representations. A series of studies on lesioned rats using the associative inference paradigms support these findings. In these studies, the hippocampal network was damaged prior to learning either by lesions to the hippocampus proper [14] or by disconnecting the hippocampus from its cortical and subcortical connections [15]. These studies demonstrated a negative effect of hippocampal lesions on associative inference. Similar findings were observed in a study in which hippocampal damage was conducted in rats after the acquisition of overlapping memories [16]. A negative effect of hippocampal lesions on associative inference was also observed in a study on monkeys with lesions to the hippocampal system [17]. Together, these animal studies suggest that the hippocampus plays a key role in judgments that require a flexible recombination of learned relationships.

In humans, neuroimaging research provides evidence that the hippocampus plays a key role in successful inference during retrieval. For instance, Preston, Shrager [18] asked healthy participants to process old and new associations. Findings show that while the posterior hippocampus was engaged during memory for all associations, bilateral anterior hippocampus was solely engaged during memory for new associations. In a similar vein, Heckers and colleagues [19, 20] observed greater hippocampal engagement for retrieval of overlapping associations than intact associations. The involvement of the hippocampus in associative inference was not only observed for retrieval, but also for encoding. A study observed reliable left hippocampal activation for encoding of old associations [21]. The present results suggest a critical role for regions connected to the hippocampus and/or medial prefrontal cortex in inference beyond learning of pairwise relations.

Critically, Zeithamova and Preston [3] used an associative inference task in which participants were required to associate information across overlapping experiences (AB, BC), and to transfer these associations into novel pairs (AC). Encoding activation in the hippocampus and parahippocampal cortex predicted memory for novel pairs. According to Zeithamova and Preston [3], these findings suggest that the hippocampus supports an integrative encoding mechanism by which overlapping experiences are linked into a combined representation during learning (for a similar view, see, [22–24]). The involvement of the hippocampus in encoding during associative inference was also reported by Schlichting, Zeithamova [2] who used high-resolution functional magnetic resonance imaging. The authors observed that activation of right CA1 during encoding of events that overlapped with prior knowledge predicted successful inferences about the relationships among events. The findings of Zeithamova and Preston [3] and Schlichting, Zeithamova [2] are important because we used their associative inference paradigm. In other words, performance of our AD participants on this paradigm can be associated with potential hippocampus activity.

The compromise of associative inference, as may be observed in AD, can be also linked with compromise of associative mechanisms. There is a body of research demonstrating difficulties in AD patients to associate separate elements together to form a memory representation (for a review, see, [25]). In this research, association was typically evaluated by asking AD patients to retain the location of letters in grids, so as to subsequently decide whether letters appeared in the same location as before or not [4, 26–28]. Associative memory was also evaluated by Sperling, Bates [29] who assessed AD patients using a task requiring retention of associations between names and faces; interestingly, performance on this task was associated with low activation in the hippocampus. Together, research demonstrates difficulties in AD patients to process simple associations (AB, BC). However, it is still unclear whether AD patients have difficulties to recombine these associations (AC) to create a new memory representation.

To summarize, associative inference has been considered as a flexible and adaptive behavior allowing accurate predictions and decision-making [1–3]. Yet, we are not aware of any published study that has directly tested associative inference in AD. Studying associative inference in AD would reveal whether AD patients are able to recombine elements from past experiences to inference on how elements of a novel experience are related to previous experiences. We compared performance of AD patients and control participants on the associative inference paradigm as used by Zeithamova and colleagues [2, 3]. This paradigm required encoding pairs of items (AB, BC). During the test phase, participants were required to retrieve old associations (AB,
We also evaluated associative inference in AD because associative inference has been widely associated with hippocampal function, a brain region that is preferentially targeted by the neuropathological processes of AD [6]. The hippocampal volume is considered as a core clinical biomarker for the development and diagnosis of AD [7–10]. The hippocampus has been widely associated with associative inference. Theoretical models suggest that the ability to flexibly combine new representations from prior memories is supported by the hippocampus via associative memory networks, in which single representations are connected to one another in terms of features they have in common [11, 12]; these networks thus allow the creation of novel, never directly experienced representation. In a similar vein, the “cross-episode binding” account [13] suggests that memory representations are separately, but flexibly encoded, and, at retrieval, they are recombined by to the hippocampus to generate new representations. These theoretical accounts have been supported by research exploring mechanisms by which the hippocampus underlies the assimilation of preexisting knowledge into new representations. A series of studies on lesioned rats using the associative inference paradigms support these findings. In these studies, the hippocampal network was damaged prior to learning either by lesions to the hippocampus proper [14] or by disconnecting the hippocampus from its cortical and subcortical connections [15]. These studies demonstrated a negative effect of hippocampal lesions on associative inference. Similar findings were observed in a study in which hippocampal damage was conducted in rats after the acquisition of overlapping memories [16]. A negative effect of hippocampal lesions on associative inference was also observed in a study on monkeys with lesions to the hippocampal system [17]. Together, these animal studies suggest that the hippocampus plays a key role in judgments that require a flexible recombination of learned relationships.

In humans, neuroimaging research provides evidence that the hippocampus plays a key role in successful inference during retrieval. For instance, Preston, Shrager [18] asked healthy participants to process old and new associations. Findings show that while the posterior hippocampus was engaged during memory for all associations, bilateral anterior hippocampus was solely engaged during memory for new associations. In a similar vein, Heckers and colleagues [19, 20] observed greater hippocampal engagement for retrieval of overlapping associations than intact associations. The involvement of the hippocampus in associative inference was not only observed for retrieval, but also for encoding. A study observed reliable left hippocampal activation for encoding of old associations [21]. The present results suggest a critical role for regions connected to the hippocampus and/or medial prefrontal cortex in inference beyond learning of pairwise relations.

Critically, Zeithamova and Preston [3] used an associative inference task in which participants were required to associate information across overlapping experiences (AB, BC), and to transfer these associations into novel pairs (AC). Encoding activation in the hippocampus and parahippocampal cortex predicted memory for novel pairs. According to Zeithamova and Preston [3], these findings suggest that the hippocampus supports an integrative encoding mechanism by which overlapping experiences are linked into a combined representation during learning (for a similar view, see, [22–24]). The involvement of the hippocampus in encoding during associative inference was also reported by Schlichting, Zeithamova [2] who used high-resolution functional magnetic resonance imaging. The authors observed that activation of right CA1 during encoding of events that overlapped with prior knowledge predicted successful inferences about the relationships among events. The findings of Zeithamova and Preston [3] and Schlichting, Zeithamova [2] are important because we used their associative inference paradigm. In other words, performance of our AD participants on this paradigm can be associated with potential hippocampus activity.

The compromise of associative inference, as may be observed in AD, can be also linked with compromise of associative mechanisms. There is a body of research demonstrating difficulties in AD patients to associate separate elements together to form a memory representation (for a review, see, [25]). In this research, association was typically evaluated by asking AD patients to retain the location of letters in grids, so as to subsequently decide whether letters appeared in the same location as before or not [4, 26–28]. Associative memory was also evaluated by Sperling, Bates [29] who assessed AD patients using a task requiring retention of associations between names and faces; interestingly, performance on this task was associated with low activation in the hippocampus. Together, research demonstrates difficulties in AD patients to process simple associations (AB, BC). However, it is still unclear whether AD patients have difficulties to recombine these associations (AC) to create a new memory representation.

To summarize, associative inference has been considered as a flexible and adaptive behavior allowing accurate predictions and decision-making [1–3]. Yet, we are not aware of any published study that has directly tested associative inference in AD. Studying associative inference in AD would reveal whether AD patients are able to recombine elements from past experiences to inference on how elements of a novel experience are related to previous experiences. We compared performance of AD patients and control participants on the associative inference paradigm as used by Zeithamova and colleagues [2, 3]. This paradigm required encoding pairs of items (AB, BC). During the test phase, participants were required to retrieve old associations (AB,
BC) or inference new ones (AC). We expected less correct inferences in AD patients than in control participants. To assess whether the compromise of associative inference in AD would be related with difficulties to flexibly recombine the associations, we administrated an independent cognitive flexibility task. We expected significant correlations between associative inference and this flexibility task in AD patients.

# Methods

## Participants

We recruited 27 participants with a clinical diagnosis of probable AD at the mild stage (19 women and 8 men; M age = 71.48 years, SD = 4.73; M years of formal educa- tion = 8.85, SD = 2.11) and 30 control older adults (19 women and 11 men; M age = 68.67 years, SD = 6.75; M years of formal education = 9.20, SD = 2.37). The AD par- ticipants were recruited from local retirement homes and were diagnosed with probable AD dementia of the amnestic form by an experienced neurologist and/or geriatrician based on the National Institute on Aging-Alzheimer's Association clinical criteria [30]. The control participants were often spouses or companions of AD patients. The control partici- pants were independent and living at their homes, and were matched with the AD patients according to age [t(55) = 1.62, p > 0.10], sex [X² (1, N = 57) = 0.32, p > 0.10], and educa- tional level [t(55) = 0.68, p > 0.10].

Exclusion criteria for both AD patients and control par- ticipants were as follows: significant neurological or psychi- atric illness, history of clinical depression, habitual alcohol or illicit drug use. All participants presented no major visual or auditory acuity deficits that would have prevented com- pletion of study tasks. They freely consented to participate and were able to withdraw whenever they wished.

## Cognitive functions

We evaluated cognitive characteristics of all participants with a battery assessing general cognitive functioning, episodic memory, verbal fluency, inhibition, flexibility, and depression. General cognitive functioning was assessed with the Mini Mental State Exam on which the maximum score is 30 points [31]. Episodic memory was evaluated with the Grober and Buschke [32]. On this task, participants had to retain 16 words, each of which describes an item (e.g., guitar) that belongs to a different semantic category (e.g., musical instruments). The participants read the 16 words, one word at a time. Immediately after the word reading, we provided the corresponded semantic category (e.g., “the musical instrument was”) and participants were required to retrieve the word. This immediate cued recall was succeeded

by a distraction phase during which participants had to count backwards from 374 in 20 s. This distraction phase was succeeded by two minutes of free recall and the score from this phase provided a measure of episodic recall (16 points maximum).

Verbal fluency was assessed using a task on which par- ticipants had two minutes to generate as many words as they could beginning with the letter P. Proper nouns and varia- tions on words (e.g., “psychology” and “psychologist”) were not allowed. Score was the number of correctly generated words. Inhibition was assessed with the Stroop task [33]. This task consisted of three subtests: word reading, color naming, and color-word interference. In the word reading subtest, participants had to read 100 words printed in black ink, all words naming colors. In the color naming subtest, they had to name the color of 100 colored ink squares. In the color-word interference subtest, participants had to name the color of 100 color-words printed in incongruously colored ink (for instance, the word “red” was written in blue). Inhi- bition score referred to the completion time for the interfer- ence condition minus the average completion time for word reading and color naming.

Flexibility was assessed with the Plus-Minus task that included three lists, each containing 20 numbers. On List 1, participants had to add one to each number, whereas on List 2 they had to subtract one from each number, and, on List 3, to add and subtract one alternately. The score referred to the difference between the time participants needed to com- plete List 3 and the average time that participants needed to complete Lists 1 and 2. Note that the Plus-Minus task was chosen following the model of Miyake, Friedman [34] who considered this task as a reliable evaluation of cogni- tive flexibility. For assessment of depression, the Hospital Anxiety and Depression Scale [35] was administered. This self-report scale consists of seven items on a four-point scale from 0 (not present) to 3 (considerable). As recommended by Herrmann [36], the cut-off for definite depression was set at > 10/21 points. Neuropsychological and clinical scores for study participants are summarized in Table 1.

## Procedures

The assessment of associative inference replicated pro- cedures by Zeithamova and Preston [3] and Schlichting, Zeithamova [2]. We, however, slightly modified their procedures by reducing the number of stimuli, to avoid a potential fatigability and/or a floor effect in AD patients. Stimuli consisted of 36 colored images of common objects. The objects were associated to construct 12 overlapping associations (6 AB pairs + 6 BC pairs) and 6 unique, non- overlapping pairs (XY). Overlapping pairs (AB + BC) con- sisted of two objects (A & C) that shared an association with a third overlapping object (B). Non-overlapping pairs
BC) or inference new ones (AC). We expected less correct inferences in AD patients than in control participants. To assess whether the compromise of associative inference in AD would be related with difficulties to flexibly recombine the associations, we administrated an independent cognitive flexibility task. We expected significant correlations between associative inference and this flexibility task in AD patients.

# Methods

## Participants

We recruited 27 participants with a clinical diagnosis of probable AD at the mild stage (19 women and 8 men; M age = 71.48 years, SD = 4.73; M years of formal educa- tion = 8.85, SD = 2.11) and 30 control older adults (19 women and 11 men; M age = 68.67 years, SD = 6.75; M years of formal education = 9.20, SD = 2.37). The AD par- ticipants were recruited from local retirement homes and were diagnosed with probable AD dementia of the amnestic form by an experienced neurologist and/or geriatrician based on the National Institute on Aging-Alzheimer's Association clinical criteria [30]. The control participants were often spouses or companions of AD patients. The control partici- pants were independent and living at their homes, and were matched with the AD patients according to age [t(55) = 1.62, p > 0.10], sex [X² (1, N = 57) = 0.32, p > 0.10], and educa- tional level [t(55) = 0.68, p > 0.10].

Exclusion criteria for both AD patients and control par- ticipants were as follows: significant neurological or psychi- atric illness, history of clinical depression, habitual alcohol or illicit drug use. All participants presented no major visual or auditory acuity deficits that would have prevented com- pletion of study tasks. They freely consented to participate and were able to withdraw whenever they wished.

## Cognitive functions

We evaluated cognitive characteristics of all participants with a battery assessing general cognitive functioning, episodic memory, verbal fluency, inhibition, flexibility, and depression. General cognitive functioning was assessed with the Mini Mental State Exam on which the maximum score is 30 points [31]. Episodic memory was evaluated with the Grober and Buschke [32]. On this task, participants had to retain 16 words, each of which describes an item (e.g., guitar) that belongs to a different semantic category (e.g., musical instruments). The participants read the 16 words, one word at a time. Immediately after the word reading, we provided the corresponded semantic category (e.g., "the musical instrument was...) and participants were required to retrieve the word. This immediate cued recall was succeeded

by a distraction phase during which participants had to count backwards from 374 in 20 s. This distraction phase was succeeded by two minutes of free recall and the score from this phase provided a measure of episodic recall (16 points maximum).

Verbal fluency was assessed using a task on which par- ticipants had two minutes to generate as many words as they could beginning with the letter P. Proper nouns and varia- tions on words (e.g., "psychology" and "psychologist") were not allowed. Score was the number of correctly generated words. Inhibition was assessed with the Stroop task [33]. This task consisted of three subtests: word reading, color naming, and color-word interference. In the word reading subtest, participants had to read 100 words printed in black ink, all words naming colors. In the color naming subtest, they had to name the color of 100 colored ink squares. In the color-word interference subtest, participants had to name the color of 100 color-words printed in incongruously colored ink (for instance, the word "red" was written in blue). Inhi- bition score referred to the completion time for the interfer- ence condition minus the average completion time for word reading and color naming.

Flexibility was assessed with the Plus-Minus task that included three lists, each containing 20 numbers. On List 1, participants had to add one to each number, whereas on List 2 they had to subtract one from each number, and, on List 3, to add and subtract one alternately. The score referred to the difference between the time participants needed to com- plete List 3 and the average time that participants needed to complete Lists 1 and 2. Note that the Plus-Minus task was chosen following the model of Miyake, Friedman [34] who considered this task as a reliable evaluation of cogni- tive flexibility. For assessment of depression, the Hospital Anxiety and Depression Scale [35] was administered. This self-report scale consists of seven items on a four-point scale from 0 (not present) to 3 (considerable). As recommended by Herrmann [36], the cut-off for definite depression was set at > 10/21 points. Neuropsychological and clinical scores for study participants are summarized in Table 1.

## Procedures

The assessment of associative inference replicated pro- cedures by Zeithamova and Preston [3] and Schlichting, Zeithamova [2]. We, however, slightly modified their procedures by reducing the number of stimuli, to avoid a potential fatigability and/or a floor effect in AD patients. Stimuli consisted of 36 colored images of common objects. The objects were associated to construct 12 overlapping associations (6 AB pairs + 6 BC pairs) and 6 unique, non- overlapping pairs (XY). Overlapping pairs (AB + BC) con- sisted of two objects (A & C) that shared an association with a third overlapping object (B). Non-overlapping pairs
<table><caption>**Table 1** Cognitive characteristics of Alzheimer's disease (AD) patients and control participants</caption><thead><tr><th></th><th>Task</th><th>AD n=27</th><th>Controls n=30</th></tr></thead><tbody><tr><td>General cognitive functioning</td><td>Mini-mental state examination (MMSE)</td><td>21.41 (1.80)***</td><td>27.77 (1.48)</td></tr><tr><td>Episodic memory</td><td>Grober and Buschke</td><td>5.74 (2.23)***</td><td>10.93 (3.03)</td></tr><tr><td>Verbal fluency</td><td>Letter “P”</td><td>16.78 (5.80)***</td><td>23.93 (4.54)</td></tr><tr><td>Inhibition</td><td>Stroop</td><td>57.15 (9.63)***</td><td>35.50 (9.47)</td></tr><tr><td>Flexibility</td><td>Plus-minus</td><td>12.91 (6.19)***</td><td>5.84 (3.16)</td></tr><tr><td>Depression</td><td>HADS</td><td>8.26 (1.23)*</td><td>6.93 (2.42)</td></tr></tbody></table>

Standard deviations are given between brackets; the maximum score on the MMSE was 30 points; performance on the Grober and Buschke's task referred to free recall and the maximum score was 16 points: the fluency score was the number of correctly generated words; scores on the Stroop and Plus-minus tasks referred to reaction time; the cut-off on the HADS (Hospital Anxiety and Depression Scale) was > 10/2 points; differences between groups were significant at: *p* < .05, **p* < .001

(XY) consisted of two unique objects that did not share an overlapping relation with other pairings. The presentation of objects across all pairs and the order of presentation were randomized across participants. Stimuli was presented on a 15.6-inch LCD display, and the task was conducted with the software package Psychopy [37].

As illustrated in Fig. 1, the associative inference task consisted of an encoding and a test phase. In the encoding phase, participants were invited to retain associations between object pairs (AB, BC, XY). Encoding was intentional, and participants were instructed that they would be tested on directly learned associations as well as indirectly

related associations. The encoding phase consisted of four cycles during which four condition blocks (AB, BC, X, XY) were each presented once. In each cycle, AB blocks always preceded BC blocks and X blocks always preceded XY blocks. Each objects-pair was presented for 5 s. The encoding phase was succeeded by the test phase on which participants were tested on previously learned associations (AB, BC, XY) and inference ones (AC). During each test trial, a cue object (e.g., object A) was presented on the top of the screen and two choice objects were presented on the bottom of the screen (e.g., two objects B). Participants were invited to make a forced-choice decision, with no time-constraint,

<figure><img src="image_2.png" /><figcaption>**Fig. 1** In the associative inference task, participants learned in the encoding phase overlapping pairs of objects (AB + BC). In the test phase, participants were presented with three objects, the top (here, the mug) one served as the cue and the bottom ones served as two choices. On the direct test trials, participants had to select the areophane as this object was directly associated with the mug in the encoding phase. In the inference trials, participants had to select the hammer, as both the mug and the hammer were paired with the airplane in the encoding phase. Importantly, correct choices are circled here for illustrative purposes only (not shown to participants)</figcaption></figure>
<table><caption>**Table 1** Cognitive characteristics of Alzheimer's disease (AD) patients and control participants</caption><thead><tr><th></th><th>Task</th><th>AD n = 27</th><th>Controls n = 30</th></tr></thead><tbody><tr><td>General cognitive functioning</td><td>Mini-mental state examination (MMSE)</td><td>21.41 (1.80)***</td><td>27.77 (1.48)</td></tr><tr><td>Episodic memory</td><td>Grober and Buschke</td><td>5.74 (2.23)***</td><td>10.93 (3.03)</td></tr><tr><td>Verbal fluency</td><td>Letter “P”</td><td>16.78 (5.80)***</td><td>23.93 (4.54)</td></tr><tr><td>Inhibition</td><td>Stroop</td><td>57.15 (9.63)***</td><td>35.50 (9.47)</td></tr><tr><td>Flexibility</td><td>Plus-minus</td><td>12.91 (6.19)***</td><td>5.84 (3.16)</td></tr><tr><td>Depression</td><td>HADS</td><td>8.26 (1.23)*</td><td>6.93 (2.42)</td></tr></tbody></table>

Standard deviations are given between brackets; the maximum score on the MMSE was 30 points; performance on the Grober and Buschke's task referred to free recall and the maximum score was 16 points: the fluency score was the number of correctly generated words; scores on the Stroop and Plus-minus tasks referred to reaction time; the cut-off on the HADS (Hospital Anxiety and Depression Scale) was > 10/2 points; differences between groups were significant at: *p* < .05, **p* < .001

(XY) consisted of two unique objects that did not share an overlapping relation with other pairings. The presentation of objects across all pairs and the order of presentation were randomized across participants. Stimuli was presented on a 15.6-inch LCD display, and the task was conducted with the software package Psychopy [37].

As illustrated in Fig. 1, the associative inference task consisted of an encoding and a test phase. In the encoding phase, participants were invited to retain associations between object pairs (AB, BC, XY). Encoding was intentional, and participants were instructed that they would be tested on directly learned associations as well as indirectly

related associations. The encoding phase consisted of four cycles during which four condition blocks (AB, BC, X, XY) were each presented once. In each cycle, AB blocks always preceded BC blocks and X blocks always preceded XY blocks. Each objects-pair was presented for 5 s. The encoding phase was succeeded by the test phase on which participants were tested on previously learned associations (AB, BC, XY) and inference ones (AC). During each test trial, a cue object (e.g., object A) was presented on the top of the screen and two choice objects were presented on the bottom of the screen (e.g., two objects B). Participants were invited to make a forced-choice decision, with no time-constraint,

<figure><img src="image_2.png" /><figcaption>**Fig. 1** In the associative inference task, participants learned in the encoding phase overlapping pairs of objects (AB + BC). In the test phase, participants were presented with three objects, the top (here, the mug) one served as the cue and the bottom ones served as two choices. On the direct test trials, participants had to select the areophane as this object was directly associated with the mug in the encoding phase. In the inference trials, participants had to select the hammer, as both the mug and the hammer were paired with the airplane in the encoding phase. Importantly, correct choices are circled here for illustrative purposes only (not shown to participants)</figcaption></figure>
this to decide which of the two choice objects was previously
associated with the cue object. For inference trials, partici-
pants were explained that the association between the cue
(object A) and the correct response (object C) was indirect,
in other words, that the association was mediated through
a third object that shared an association with both the cue
(object A) and the other object (object B). Participants were
also explained that the incorrect choice was another familiar
object studied at encoding, but that did not share a common
association with the cue. No time constraint was imposed
on the decision.

As suggested by Zeithamova and Preston [3] and Schli-
chtung, Zeithamova [2], the inference trials (AC) during
the test phase were presented prior to corresponding AB
and BC trials, so as to ensure that participants could not
form an association between A and C objects. Also, for both
directly learned and inference trials, the incorrect choice
objects were all familiar objects that had been studied in the
context of another object different from the cue. Therefore,
correct responses required memory for learned associations
and could not be made based on familiarity of the choice
objects. Regarding the dependent variables, performance
referred to the percentage of correct retrieval of previously
learned associations (AB + BC) and correct associative
inference (AC), with the first variable indicating memory
for the directly learned associations and the second indicat-
ing the ability to infer associations between the previously
exposed objects.

Results

To examine our first hypothesis, we compared differences
between AD patients and control participants on percent-
age of correct retrieval of previously learned associations
and inference ones. Owing to abnormal distribution of the
data, non-parametrical tests were conducted. When reporting
significant differences, we report effect size: d=0.2 can be
considered as a small effect size, d=0.5 a medium effect size
and d=0.8 a large effect size [38]. Note that effect size was
calculated for non-parametric tests according to the recom-
mendations of Rosenthal and DiMatteo [39] and Ellis [40].
To examine our second hypothesis, we carried out Spearman
correlations between correct retrieval of inference associa-
tions and flexibility, we also assessed correlations with the
remaining cognitive tests (i.e., general cognitive ability,
episodic memory, fluency, and inhibition), this to evaluate
potential relationship between these cognitive variables and
associative inference. For all tests, level of significance was
set as p≤0.05, p values between 0.051 and 0.10 were con-
sidered as trend.

Poor associative inference in AD

Percentages of correct retrieval of previously learned asso-
ciations and percentages of correct associative inference
are depicted in Fig. 2. Mann-Whitney's U tests showed
lower correct retrieval of previously learned associations
in AD patients than in control participants, with a respec-
tive mean of 39.96 (SD=14.08) and 59.90 (SD=12.63)
(Z= - 4.59, *p* < 0.001, Cohen's *d* = 1.53). AD patients also
showed lower associative inference than control participants,
with a respective mean of 26.30 (SD = 11.01) and 36.47
(SD= 10.95) (Z = - 3.23, *p* = 0.01, Cohen's *d* = 0.95). Wil-
coxon's tests showed lower correct associative inference than
correct retrieval of previously learned associations in AD
patients (Z = - 3.21, *p* = 0.01, Cohen's *d* = 1.57) and controls
(Z = - 4.55, *p* < 0.001, Cohen's *d* = 2.98).

Correlations between associative inference
and flexibility in AD

Significant correlations were observed between associa-
tive inference and flexibility in AD patients (r = - 0.54,
p < 0.01) and control participants (r = - 0.53, p < 0.01)
(see Fig. 3). The negative correlation meant that the higher
associative inference was, the longer completion time on
the plus-minus task was (i.e., the poorer flexibility was).
Associative inference was also correlated with episodic
memory in AD patients (r = 0.41, p < 0.05) and control par-
ticipants (r = 0.42, p < 0.05). No significant correlations were
observed between associative inference and general cogni-
tive ability, fluency, or inhibition in AD patients or control
participants (p > 0.1). Significant correlations were observed
between correct retrieval of previously learned associations
and episodic memory in AD patients (r = 0.51, p < 0.01) and
control participants (r = - 0.50, p < 0.01), but no significant
correlations were observed between this correct retrieval and

<figure><img src="image_3.png" /><figcaption>**Fig. 2** Percentage of correct retrieval of previously learned asso-
ciations and percentage of correct associative inference in Alzheimer's
disease patients and control participants. Error bars represent inter-
vals of 95% within-subjects confidence</figcaption></figure>
this to decide which of the two choice objects was previously
associated with the cue object. For inference trials, partici-
pants were explained that the association between the cue
(object A) and the correct response (object C) was indirect,
in other words, that the association was mediated through
a third object that shared an association with both the cue
(object A) and the other object (object B). Participants were
also explained that the incorrect choice was another familiar
object studied at encoding, but that did not share a common
association with the cue. No time constraint was imposed
on the decision.

As suggested by Zeithamova and Preston [3] and Schli-
chtung, Zeithamova [2], the inference trials (AC) during
the test phase were presented prior to corresponding AB
and BC trials, so as to ensure that participants could not
form an association between A and C objects. Also, for both
directly learned and inference trials, the incorrect choice
objects were all familiar objects that had been studied in the
context of another object different from the cue. Therefore,
correct responses required memory for learned associations
and could not be made based on familiarity of the choice
objects. Regarding the dependent variables, performance
referred to the percentage of correct retrieval of previously
learned associations (AB + BC) and correct associative
inference (AC), with the first variable indicating memory
for the directly learned associations and the second indicat-
ing the ability to infer associations between the previously
exposed objects.

Results

To examine our first hypothesis, we compared differences
between AD patients and control participants on percent-
age of correct retrieval of previously learned associations
and inference ones. Owing to abnormal distribution of the
data, non-parametrical tests were conducted. When reporting
significant differences, we report effect size: d=0.2 can be
considered as a small effect size, d=0.5 a medium effect size
and d=0.8 a large effect size [38]. Note that effect size was
calculated for non-parametric tests according to the recom-
mendations of Rosenthal and DiMatteo [39] and Ellis [40].
To examine our second hypothesis, we carried out Spearman
correlations between correct retrieval of inference associa-
tions and flexibility, we also assessed correlations with the
remaining cognitive tests (i.e., general cognitive ability,
episodic memory, fluency, and inhibition), this to evaluate
potential relationship between these cognitive variables and
associative inference. For all tests, level of significance was
set as p≤0.05, p values between 0.051 and 0.10 were con-
sidered as trend.

Poor associative inference in AD

Percentages of correct retrieval of previously learned asso-
ciations and percentages of correct associative inference
are depicted in Fig. 2. Mann-Whitney's U tests showed
lower correct retrieval of previously learned associations
in AD patients than in control participants, with a respec-
tive mean of 39.96 (SD=14.08) and 59.90 (SD=12.63)
(Z= - 4.59, p < 0.001, Cohen's d = 1.53). AD patients also
showed lower associative inference than control participants,
with a respective mean of 26.30 (SD = 11.01) and 36.47
(SD= 10.95) (Z = - 3.23, p = 0.01, Cohen's d = 0.95). Wil-
coxon's tests showed lower correct associative inference than
correct retrieval of previously learned associations in AD
patients (Z = - 3.21, p = 0.01, Cohen's d = 1.57) and controls
(Z = - 4.55, p < 0.001, Cohen's d = 2.98).

Correlations between associative inference
and flexibility in AD

Significant correlations were observed between associa-
tive inference and flexibility in AD patients (r = - 0.54,
p < 0.01) and control participants (r = - 0.53, p < 0.01)
(see Fig. 3). The negative correlation meant that the higher
associative inference was, the longer completion time on
the plus-minus task was (i.e., the poorer flexibility was).
Associative inference was also correlated with episodic
memory in AD patients (r = 0.41, p < 0.05) and control par-
ticipants (r = 0.42, p < 0.05). No significant correlations were
observed between associative inference and general cogni-
tive ability, fluency, or inhibition in AD patients or control
participants (p > 0.1). Significant correlations were observed
between correct retrieval of previously learned associations
and episodic memory in AD patients (r = 0.51, p < 0.01) and
control participants (r = - 0.50, p < 0.01), but no significant
correlations were observed between this correct retrieval and

<figure><img src="image_3.png" /><figcaption>**Fig. 2** Percentage of correct retrieval of previously learned associations and percentage of correct associative inference in Alzheimer's disease patients and control participants. Error bars represent intervals of 95% within-subjects confidence</figcaption></figure>
<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /><figcaption>**Fig. 3** Correlations between associative inference and flexibility in Alzheimer's disease patients (a) and control participants (b)</figcaption></figure>

general cognitive ability, fluency, flexibility, or inhibition in AD patients or control participants. Note that significant correlations were observed between correct retrieval of previously learned associations and associative inference in AD patients ($r=0.43, p<0.05$) and control participants ($r=0.45, p<0.05$).

## Discussion

The ability to extract information from a past experience and use this information flexibly is a fundamental mechanism for memory, inference, and decision-making. We evaluated this ability in AD using an associative inference task. Our results demonstrated a decreased ability to correctly retrieve previously learned associations (AB + BC associations) as well as low ability to infer associations between the previously exposed objects (AC associations) in AD patients. Interestingly, associative inference in AD patients was significantly correlated with cognitive flexibility.

The core contribution of this study is adding to the literature an empirical evidence on the compromise of associative inference in AD. Our AD participants demonstrated difficulties to infer associations between the previously presented objects. In other words, they demonstrated difficulties to recombine previously learned information to generate new associations and representations. This associative inference

difficulty can be linked with a compromise of cognitive flexibility and episodic memory in AD. This assumption is supported by our correlation analysis. To begin with flexibility, associative inference has been considered as an ability requiring flexible recombination of learned relationships [1–3]. Associative inference does not only require the retrieval of previously learned information, but also to flexibly recombine this information. Supporting this consideration, our AD participants demonstrated significant correlations between associative inference and flexibility. The compromise of flexibility in AD has been observed by research on executive function in general [41–43] and, more specifically, by studies demonstrating difficulties in AD patients to shift avenues of thoughts or actions to perceive and recombine information in different ways [4, 5]. Besides its significant correlations with flexibility, associative inference was significantly correlated with episodic memory, not surprisingly as associative inference, at least as evaluated in our study, requires the retrieval of the previously encountered objects. Further support to the relationship between associative inference and episodic memory can be found in our correlational analysis as we observed significant correlations between associative inference and the ability to retrieve the previous associations (i.e., memory for the AB + BC associations). Therefore, the low associative inference, as observed in our AD participants, was related with their episodic performance. As published in a multitude of studies, AD is associated with a compromise of episodic memory and this compromise has been considered as the cognitive hallmark of the disease [30, 44, 45]. Taken together, our findings demonstrate a relationship between the compromise of associative inference and the compromise of both flexibility and episodic memory in AD.

At the neural level, the compromise of associative inference, as observed in AD, can be linked with compromise of the hippocampus. As mentioned in the introduction, the hippocampus is preferentially targeted by the neuropathological processes of AD [6] and the hippocampal volume is typically reduced in the disease [7–10]. Hippocampal damage, as observed in AD, may be associated with a compromise in associative inference. This assumption can be supported by the body of literature indicating that the ability to flexibility combine experiences in novel ways to infer novel relationships between items or events (i.e., associative inference) crucially depends on the hippocampus [1–3, 15–20]. The hippocampal involvement in associative inference can be illustrated with a study by Zeithamova, Manthuruthil [46] who investigated whether events overlap significantly modulates the medial temporal lobe and Acetylcholine responses. The authors found that when events were repeated across learning, a decreased activation across the medial temporal lobe was observed, suggesting a reduced encoding demands for familiar information.
<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /><figcaption>**Fig. 3** Correlations between associative inference and flexibility in Alzheimer's disease patients (a) and control participants (b)</figcaption></figure>

general cognitive ability, fluency, flexibility, or inhibition in AD patients or control participants. Note that significant correlations were observed between correct retrieval of previously learned associations and associative inference in AD patients ($r=0.43, p<0.05$) and control participants ($r=0.45, p<0.05$).

Discussion

The ability to extract information from a past experience and use this information flexibly is a fundamental mechanism for memory, inference, and decision-making. We evaluated this ability in AD using an associative inference task. Our results demonstrated a decreased ability to correctly retrieve previously learned associations (AB + BC associations) as well as low ability to infer associations between the previously exposed objects (AC associations) in AD patients. Interestingly, associative inference in AD patients was significantly correlated with cognitive flexibility.

The core contribution of this study is adding to the literature an empirical evidence on the compromise of associative inference in AD. Our AD participants demonstrated difficulties to infer associations between the previously presented objects. In other words, they demonstrated difficulties to recombine previously learned information to generate new associations and representations. This associative inference

difficulty can be linked with a compromise of cognitive flexibility and episodic memory in AD. This assumption is supported by our correlation analysis. To begin with flexibility, associative inference has been considered as an ability requiring flexible recombination of learned relationships [1–3]. Associative inference does not only require the retrieval of previously learned information, but also to flexibly recombine this information. Supporting this consideration, our AD participants demonstrated significant correlations between associative inference and flexibility. The compromise of flexibility in AD has been observed by research on executive function in general [41–43] and, more specifically, by studies demonstrating difficulties in AD patients to shift avenues of thoughts or actions to perceive and recombine information in different ways [4, 5]. Besides its significant correlations with flexibility, associative inference was significantly correlated with episodic memory, not surprisingly as associative inference, at least as evaluated in our study, requires the retrieval of the previously encountered objects. Further support to the relationship between associative inference and episodic memory can be found in our correlational analysis as we observed significant correlations between associative inference and the ability to retrieve the previous associations (i.e., memory for the AB + BC associations). Therefore, the low associative inference, as observed in our AD participants, was related with their episodic performance. As published in a multitude of studies, AD is associated with a compromise of episodic memory and this compromise has been considered as the cognitive hallmark of the disease [30, 44, 45]. Taken together, our findings demonstrate a relationship between the compromise of associative inference and the compromise of both flexibility and episodic memory in AD.

At the neural level, the compromise of associative inference, as observed in AD, can be linked with compromise of the hippocampus. As mentioned in the introduction, the hippocampus is preferentially targeted by the neuropathological processes of AD [6] and the hippocampal volume is typically reduced in the disease [7–10]. Hippocampal damage, as observed in AD, may be associated with a compromise in associative inference. This assumption can be supported by the body of literature indicating that the ability to flexibility combine experiences in novel ways to infer novel relationships between items or events (i.e., associative inference) crucially depends on the hippocampus [1–3, 15–20]. The hippocampal involvement in associative inference can be illustrated with a study by Zeithamova, Manthuruthil [46] who investigated whether events overlap significantly modulates the medial temporal lobe and Acetylcholine responses. The authors found that when events were repeated across learning, a decreased activation across the medial temporal lobe was observed, suggesting a reduced encoding demands for familiar information.
However, for information overlapping with other events, an increased activation in the entorhinal cortex was observed, reflecting the need to accommodate new information. Critically, within the hippocampus, the overlapping information resulted in an activation of the CA1 area. According to Zeithamova, Manthuruthil [46], these findings demonstrate that the medial temporal lobes and midbrain areas response to information overlap mirrors integration of new content into existing memories and formation of relational memory networks that span previous knowledge. The implication of the CA1 in associative inference can be interpreted in terms of the comparator function of this area [46–48]. The CA1 receives input from the entorhinal cortex and CA3, allowing information about current sensory experience from the entorhinal cortex to be compared with memory-based expectations derived from the CA3 [49]. Supporting the comparator role of the CA1, a study found activation of the CA1 during processing of altered object configurations within a familiar environment [47]. A comprehensive view about the hippocampal involvement in associative inference is the following [22–24, 46, 50], an activation decreases in the hippocampus mirrors simple associative processes (AB, BC associations) whereas an activation increases mirrors the comparison between present events and previous experiences (BC associations).

Although the present paper primarily focuses on the potential involvement of the hippocampus, other brain areas (especially the prefrontal cortex) can be considered. For instance, a, increased medial temporal lobe- prefrontal cortex coupling was observed by Zeithamova and Preston [3] during the processing of inference associations compared with retrieval of directly learned associations. According to Zeithamova and Preston [3] these findings suggest distinct encoding and retrieval mechanisms that support memory flexibility, with a unique role for medial temporal lobe in cross-episode binding during encoding and an interactive role of medial temporal lobe- prefrontal cortex during flexible transfer at retrieval. The involvement of the prefrontal cortex in associative inference was also highlighted by Schlichting, Mumford [51] who reported that, while the posterior hippocampus and anterior medial prefrontal cortex maintain memories for individual events, anterior hippocampus and posterior medial prefrontal cortex integrate these events across memories. These findings are interesting because cognitive function in aging has been widely associated with a diminished function of the prefrontal cortex [52]. Therefore, compromise of the prefrontal cortex, as may be observed in normal aging and AD [53], can be associated with a diminished associative inference.

One potential limitation of our study is the lack of neuroimaging data. Although this data may provide further support to the involvement of the hippocampus in the compromise of associative inference in AD, it is worthy to highlight

that our data provide reliable behavioral evidence for the relationship between compromise of associative inference and flexibility in a population with hippocampal dysfunction. Another limitation may be the effect size as G\*Power analysis suggests that a sample size of 37 subjects would be required for each population to perform Mann–Whitney’s *U*. That said, it is worth noting that the effect size of our analyses is fairly large, for instance, the AD vs control participants comparison on retrieval of previously learned associations was associated with Cohen’s *d* = 1.53.

To summarize, several memory research studies in AD have focused on how patients encode, store, and retrieve memories for individual experiences. However, in everyday life, it is rare that an appropriate decision can be made on the basis of a single previous experience; rather, most decisions and actions require to recombine knowledge derived across multiple experiences. Therefore, the core contribution of this study is adding to the literature an empirical evidence on difficulties of AD patients to flexibly recombine information from past experience to make novel inferences and representations.

**Author contributions** Study conception and design: MEH. Data collection: MEH and GC. Data analysis and interpretation: MEH, AAM, FR and GC. Manuscript writing: MEH and AAM. All authors critically reviewed the manuscript and approved the final version to be published.

**Data availability** Data is available upon request by email to the first author.

## Declarations

**Conflict of interest** The authors report no conflicts with any product mentioned or concept discussed in this article. The study was supported by LABEX DISTALZ.

**Ethics approval** The study was conducted in accordance with the principles of the Declaration of Helsinki with a favorable opinion (number 20202-A02276-33) from the Committee for the Protection of Persons (the French national ethical board).

**Consent to participate** Written informed consent was obtained from all participants.

## References

1. Zeithamova D, Schlichting ML, Preston AR (2012) The hippocampus and inferential reasoning: building memories to navigate future decisions. Front Hum Neurosci 6:70

2. Schlichting ML, Zeithamova D, Preston AR (2014) CA1 subfield contributions to memory integration and inference. Hippocampus 24:1248–1260

3. Zeithamova D, Preston AR (2010) Flexible memories: differential roles for medial temporal lobe and prefrontal cortex in cross-episode binding. J Neurosci 30:14676–14684
However, for information overlapping with other events, an increased activation in the entorhinal cortex was observed, reflecting the need to accommodate new information. Critically, within the hippocampus, the overlapping information resulted in an activation of the CA1 area. According to Zeithamova, Manthuruthil [46], these findings demonstrate that the medial temporal lobes and midbrain areas response to information overlap mirrors integration of new content into existing memories and formation of relational memory networks that span previous knowledge. The implication of the CA1 in associative inference can be interpreted in terms of the comparator function of this area [46–48]. The CA1 receives input from the entorhinal cortex and CA3, allowing information about current sensory experience from the entorhinal cortex to be compared with memory-based expectations derived from the CA3 [49]. Supporting the comparator role of the CA1, a study found activation of the CA1 during processing of altered object configurations within a familiar environment [47]. A comprehensive view about the hippocampal involvement in associative inference is the following [22–24, 46, 50], an activation decreases in the hippocampus mirrors simple associative processes (AB, BC associations) whereas an activation increases mirrors the comparison between present events and previous experiences (BC associations).

Although the present paper primarily focuses on the potential involvement of the hippocampus, other brain areas (especially the prefrontal cortex) can be considered. For instance, a, increased medial temporal lobe- prefrontal cortex coupling was observed by Zeithamova and Preston [3] during the processing of inference associations compared with retrieval of directly learned associations. According to Zeithamova and Preston [3] these findings suggest distinct encoding and retrieval mechanisms that support memory flexibility, with a unique role for medial temporal lobe in cross-episode binding during encoding and an interactive role of medial temporal lobe- prefrontal cortex during flexible transfer at retrieval. The involvement of the prefrontal cortex in associative inference was also highlighted by Schlichting, Mumford [51] who reported that, while the posterior hippocampus and anterior medial prefrontal cortex maintain memories for individual events, anterior hippocampus and posterior medial prefrontal cortex integrate these events across memories. These findings are interesting because cognitive function in aging has been widely associated with a diminished function of the prefrontal cortex [52]. Therefore, compromise of the prefrontal cortex, as may be observed in normal aging and AD [53], can be associated with a diminished associative inference.

One potential limitation of our study is the lack of neuroimaging data. Although this data may provide further support to the involvement of the hippocampus in the compromise of associative inference in AD, it is worthy to highlight

that our data provide reliable behavioral evidence for the relationship between compromise of associative inference and flexibility in a population with hippocampal dysfunction. Another limitation may be the effect size as G\*Power analysis suggests that a sample size of 37 subjects would be required for each population to perform Mann–Whitney’s *U*. That said, it is worth noting that the effect size of our analyses is fairly large, for instance, the AD vs control participants comparison on retrieval of previously learned associations was associated with Cohen’s *d* = 1.53.

To summarize, several memory research studies in AD have focused on how patients encode, store, and retrieve memories for individual experiences. However, in everyday life, it is rare that an appropriate decision can be made on the basis of a single previous experience; rather, most decisions and actions require to recombine knowledge derived across multiple experiences. Therefore, the core contribution of this study is adding to the literature an empirical evidence on difficulties of AD patients to flexibly recombine information from past experience to make novel inferences and representations.

**Author contributions** Study conception and design: MEH. Data collection: MEH and GC. Data analysis and interpretation: MEH, AAM, FR and GC. Manuscript writing: MEH and AAM. All authors critically reviewed the manuscript and approved the final version to be published.

**Data availability** Data is available upon request by email to the first author.

## Declarations

**Conflict of interest** The authors report no conflicts with any product mentioned or concept discussed in this article. The study was supported by LABEX DISTALZ.

**Ethics approval** The study was conducted in accordance with the principles of the Declaration of Helsinki with a favorable opinion (number 20202-A02276-33) from the Committee for the Protection of Persons (the French national ethical board).

**Consent to participate** Written informed consent was obtained from all participants.

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2. Schlichting ML, Zeithamova D, Preston AR (2014) CA1 subfield contributions to memory integration and inference. Hippocampus 24:1248–1260

3. Zeithamova D, Preston AR (2010) Flexible memories: differential roles for medial temporal lobe and prefrontal cortex in cross-episode binding. J Neurosci 30:14676–14684
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23. Moustafa AA, Hewedi DH, Eissa AM et al (2012) The relationship between associative learning, transfer generalization, and homocysteine levels in mild cognitive impairment. *PLoS One* 7:e46496

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25. El Haj M, Kessels RPC (2013) Context Memory in Alzheimer's Disease. *Dement Geriatr Cogn Dis Extra* 3:342-350

26. El Haj M, Postal V, Allain P (2013) Destination memory in Alzheimer's disease: when I imagine telling Ronald Reagan about Paris. *Cortex* 49:82-89

27. Parra MA, Abrahams S, Logie RH et al (2010) Visual short-term memory binding deficits in familial Alzheimer's disease. *Brain* 133:2702-2713

28. Parra MA, Abrahams S, Fabi K et al (2009) Short-term memory binding deficits in Alzheimer's disease. *Brain* 132:1057-1066

29. Sperling RA, Bates JF, Chua EF et al (2003) fMRI studies of associative encoding in young and elderly controls and mild Alzheimer's disease. *J Neurol Neurosurg Psychiatry* 74:44-50

30. McKhann GM, Knopman DS, Chertkow H et al (2011) The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. *Alzheimer's Dement* 7:263-269

31. Folstein MF, Folstein SE, McHugh PR (1975) "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. *J Psychiatr Res* 12:189-198

32. Grober E, Buschke H (1987) Genuine memory deficits in dementia. *Dev Neuropsychol* 3:13-36

33. Stroop JR (1935) Studies of interference in serial verbal reactions. *J Exp Psychol* 18:643-662

34. Miyake A, Friedman NP, Emerson MJ et al (2000) The unity and diversity of executive functions and their contributions to complex "frontal lobe" tasks: a latent variable analysis. *Cogn Psychol* 41:49-100

35. Zigmond AS, Snaith RP (1983) The hospital anxiety and depression scale. *Acta Psychiatr Scand* 67:361-370

36. Herrmann C (1997) International experiences with the hospital anxiety and depression scale-a review of validation data and clinical results. *J Psychosom Res* 42:17-41

37. Peirce JW (2007) PsychoPy-psychophysics software in python. *J Neurosci Methods* 162:8-13

38. Cohen J (1988) Statistical power analysis for the behavioral sciences. Erlbaum Associates, Hillsdale, NJ

39. Rosenthal R, DiMatteo MR (2001) Meta-analysis: recent developments in quantitative methods for literature reviews. *Annu Rev Psychol* 52:59-82

40. Ellis PD (2010) The essential guide to effect sizes: statistical power, meta-analysis, and the interpretation of research results. Cambridge University Press, New York, NY

41. Baudic S, Barba GD, Thibaudet MC et al (2006) Executive function deficits in early Alzheimer's disease and their relations with episodic memory. *Arch Clin Neuropsychol* 21:15-21

42. Duarte A, Hayasaka S, Du A et al (2006) Volumetric correlates of memory and executive function in normal elderly, mild cognitive impairment and Alzheimer's disease. *Neurosci Lett* 406:60-65

43. Kirova AM, Bays RB, Lagalwar S (2015) Working memory and executive function decline across normal aging, mild cognitive impairment, and Alzheimer's disease. *Biomed Res Int* 2015:748212

44. El Haj M, Antoine P, Amouyel P et al (2016) Apolipoprotein E (APOE) epsilon4 and episodic memory decline in Alzheimer's disease: a review. *Ageing Res Rev* 27:15-22

45. El Haj M, Antoine P, Nandrino JL et al (2015) Autobiographical memory decline in Alzheimer's disease, a theoretical and clinical overview. *Ageing Res Rev* 23:183-192

46. Zeithamova D, Manthuruthil C, Preston AR (2016) Repetition suppression in the medial temporal lobe and midbrain is altered by event overlap. *Hippocampus* 26:1464-1477

47. Duncan K, Ketz N, Inati SJ et al (2012) Evidence for area CA1 as a match/mismatch detector: a high-resolution fMRI study of the human hippocampus. *Hippocampus* 22:389-398

48. Chen J, Olsen RK, Preston AR et al (2011) Associative retrieval processes in the human medial temporal lobe: hippocampal
retrieval success and CA1 mismatch detection. Learn Mem
18:523–528

49. Lisman JE, Grace AA (2005) The hippocampal-VTA loop: controlling the entry of information into long-term memory. Neuron 46:703–713

50. Schlichting ML, Preston AR (2015) Memory integration: neural mechanisms and implications for behavior. Curr Opin Behav Sci 1:1–8

51. Schlichting ML, Mumford JA, Preston AR (2015) Learning-related representational changes reveal dissociable integration and separation signatures in the hippocampus and prefrontal cortex. Nat Commun 6:8151

52. West R (1996) An application of prefrontal cortex function theory to cognitive aging. Psychol Bull 120:272–292

53. DeKosky ST, Scheff SW (1990) Synapse loss in frontal cortex biopsies in Alzheimer's disease: correlation with cognitive severity. Ann Neurol 27:457–464

**Publisher's Note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
retrieval success and CA1 mismatch detection. Learn Mem
18:523–528

49. Lisman JE, Grace AA (2005) The hippocampal-VTA loop: controlling the entry of information into long-term memory. Neuron 46:703–713

50. Schlichting ML, Preston AR (2015) Memory integration: neural mechanisms and implications for behavior. Curr Opin Behav Sci 1:1–8

51. Schlichting ML, Mumford JA, Preston AR (2015) Learning-related representational changes reveal dissociable integration and separation signatures in the hippocampus and prefrontal cortex. Nat Commun 6:8151

52. West R (1996) An application of prefrontal cortex function theory to cognitive aging. Psychol Bull 120:272–292

53. DeKosky ST, Scheff SW (1990) Synapse loss in frontal cortex biopsies in Alzheimer's disease: correlation with cognitive severity. Ann Neurol 27:457–464

**Publisher's Note** Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.