A computational model of cognitive interference without neural inhibitory mechanisms

A computational model of cognitive interference without neural inhibitory mechanisms Serge Thill (serge.thill@his.se) Informatics Research Centre, University of Sk¨ovde PO BOX 401, Sk¨ovde, Sweden Robert Lowe (robert.lowe@his.se) Informatics Research Centre, University of Sk¨ovde PO BOX 401, Sk¨ovde, Sweden Abstract dence has uncovered that areas of motor and premotor cor- tex that become active during physical movement overlap with areas activated during the reading of the specific affected movement, e.g. hand, foot (Hauk et al., 2004). Buccino et al. (2005) for instance found an interference effect when human subjects, required to produce hand or foot responses to partic- ular verb forms, produced physical movements apt to the ac- tion described in the particular sentence. Latency of response increasedin this case as compared to when a movement was required that was inapt to the particular action described (see Chersi et al., 2010, for a more detailed discussion). Interference between one cognitive behavior or sensory stim- ulus and subsequent behaviors is a commonly observed effect in the study of human cognition and Psychology. Traditional connectionist approaches explain this phenomenon by mutu- ally inhibiting neural populations underlying those behaviors. Here, we present an alternative model, relying on a more de- tailed use of synaptic dynamics, in which populations of purely excitatory neurons can nonetheless interfere with each other, causing inhibition of activation for a varying amount of time. The fundamental, biologically motivated, mechanism in the model relies on current “spilling over” from an active neu- ral population into another one, thereby depleting the latter population’s synaptic resources. The principles underlying the model may find applications even in the design of problem- solving artificial neural networks. Keywords: Neural modeling; Synaptic dynamics; Cognitive Interference. Introduction The effects on cognitive performance of interference in the process of associating temporally contiguous behaviors or events is a well studied phenomenon in the research disci- plines of psychology and animal learning. Simply, it consists of the effects on working memory or memory recall of the presence of stimuli (or motor activations) that are non-critical to the learning of particular response/event associations. In the case of animal learning, it is best understood as entail- ing distractorstimuli introduced prior to (proactive) or after (retroactive) a task stimulus designed to be reliably predic- tive of another (e.g. rewarding) stimulus. In human learning, interference can manifest in learning deficits subsequent to pairing either context relevant (Oliveri et al., 2004) or incon- gruent (Buccino et al., 2005) motor actions and verbal de- scriptions. In every day human activities, the interference ef- fect has implications for recall of important events, e.g. eye witness testimony (see Bouton, 2007). Laboratory controlled studies of interference often utilize the delayed matching-to-sample (DMTS) paradigm whereby the subject is required to produce the desired behavioral re- sponse over a pre-determined delay period (or inter-stimulus- interval). In such cases, interference is a function of the strength of a ‘distractor’ stimulus and may induce forget- ting (cf. Roberts & Grant, 1978), impaired learning (Revusky, 1971) or memory retrieval deficits (Gordon et al., 1981). Some forms of associative learning may be more or less prone to the interference effect. Recent neuro-scientific evi- Models exist that attempt to capture empirically demon- strated features of the interference phenomenon specified at the level of both connectionist and more neurobiologically motivated levels of abstraction. A seminal model of Mc- Geoch (1932) proffered a connectionist account of interfer- ence whereby responses learned during a given time win- dow would compete for retrieval by way of mutual inhibi- tion. Essentially, this offered a classical account of ‘distrac- tor’ stimuli inhibiting the influence of task-specific stimuli. The learned associative strengths of the responses determined the ‘winner’ which was, however, premised on the biologi- cal implausability of there being independence, as opposed to overlap, between the available responses. Mensink & Raaijmakers (1988) provided a stochastic search model of retrieval that was able to describe behav- ioral data accounting for many of the effects of interference, e.g. proactive inhibition, retroactive inhibition, spontaneous recovery - where previously learned associations become be- haviorally extinguished but, presumably still reside in mem- ory. More recently, neural models have been put forward to ac- count for the ability of organisms to retain spatial information about stimuli over delay periods in the face of distracting (in- terfering) stimuli. Spencer et al. (2009) have described how the tuning of parameters of an interaction kernel on a dynamic neural field representing spatial working memory permits the development of activation peaks. These peaks are sustained through the use of tuned local excitation and global inhibi- tion parameters on the kernel that afford more or less robust- ness to noise and distractor stimuli presented to the spatial field. Self-sustained activity can be achieved through bistable unit dynamics (cf. Amari, 1977) such that input or noise in-