Synaptic Theory of Chunking in Working Memory

TL;DR

This paper proposes a synaptic model where short-term plasticity enables the formation of chunks in working memory, allowing for hierarchical representations and exceeding basic capacity, supported by neural data and experiments.

Contribution

It introduces a novel synaptic mechanism for chunking in working memory, explaining how hierarchical and dynamic chunking occurs in the brain.

Findings

Model predicts capacity limits based on basic working memory capacity.

Neural data from epileptic patients supports the model.

Memory experiments confirm the role of chunking in cognition.

Abstract

Working memory often appears to exceed its basic span by organizing items into compact representations called chunks. Chunking can be learned over time for familiar inputs; however, it can also arise spontaneously for novel stimuli. Such on-the-fly structuring is crucial for cognition, yet the underlying neural mechanism remains unclear. Here we introduce a synaptic theory of chunking, in which short-term synaptic plasticity enables the formation of chunk representations in working memory. We show that a specialized population of ``chunking neurons'' selectively controls groups of stimulus-responsive neurons, akin to gating. As a result, the network maintains and retrieves the stimuli in chunks, thereby exceeding the basic capacity. Moreover, we show that our model can dynamically construct hierarchical representations within working memory through hierarchical chunking. A consequence of this proposed mechanism is a new limit on the number of items that can be stored and subsequently retrieved from working memory, depending only on the basic working memory capacity when chunking is not invoked. Predictions from our model were confirmed by analyzing single-unit responses in epileptic patients and memory experiments with verbal material. Our work provides a novel conceptual and analytical framework for understanding how the brain organizes information in real time.