Abstract

The information contents of memory are the cornerstone of the most influential models in cognition. To illustrate, consider that in predictive coding, a prediction implies that specific information is propagated down from memory through the visual hierarchy. Likewise, recognizing the input implies that sequentially accrued sensory evidence is successfully matched with memorized information (categorical knowledge). Although the existing models of prediction, memory, sensory representation and categorical decision are all implicitly cast within an information processing framework, it remains a challenge to precisely specify what this information is, and therefore where, when and how the architecture of the brain dynamically processes it to produce behaviour. Here, we review a framework that addresses these challenges for the studies of perception and categorization–stimulus information representation (SIR). We illustrate how SIR can reverse engineer the information contents of memory from behavioural and brain measures in the context of specific cognitive tasks that involve memory. We discuss two specific lessons from this approach that generally apply to memory studies: the importance of task, to constrain what the brain does, and of stimulus variations, to identify the specific information contents that are memorized, predicted, recalled and replayed.This article is part of the Theo Murphy meeting issue ‘Memory reactivation: replaying events past, present and future’.

Highlights

  • The machinery that performs visual cognition has an extraordinary range of capabilities that is supported by the most powerful of sensory systems

  • If we aim to understand the mechanisms that use memorized information contents, a useful starting point is to characterize what these contents are, to be able to trace their specific reactivation into brain activity, and thereby bridge the interpretation gap

  • These task-irrelevant features do not influence the participants’ categorization responses, they were among the features that were most strongly represented in brain activity in early visual cortex

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Summary

Introduction

The machinery that performs visual cognition has an extraordinary range of capabilities that is supported by the most powerful of sensory systems. These are only very few of many categorizations that our brains perform apparently continuously and effortlessly To accomplish this feat, current models in the cognitive sciences assume that the categorization processes performed by the brain use memory representations, both to predict the incoming stimulus (e.g. a street, the type of a car or the emotion of a face) and to categorize it (e.g. as ‘Byres Road’, ‘new Beetle’, ‘face’ or ‘happy’, figure 1). Current models in the cognitive sciences assume that the categorization processes performed by the brain use memory representations, both to predict the incoming stimulus (e.g. a street, the type of a car or the emotion of a face) and to categorize it (e.g. as ‘Byres Road’, ‘new Beetle’, ‘face’ or ‘happy’, figure 1) In these processes, the information contents royalsocietypublishing.org/journal/rstb Phil. If we aim to understand the mechanisms that use memorized information contents (e.g. for categorization, as we will illustrate, and for prediction and reactivation, as we will discuss), a useful starting point is to characterize what these contents are, to be able to trace their specific reactivation into brain activity, and thereby bridge the interpretation gap

The stimulus information representation framework
What do we learn from the intersections of SIR?
General discussion
Conclusion
Findings
Methods

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