Synaptic Theory of Chunking in Working Memory
This work addresses a fundamental cognitive problem for neuroscience and psychology by explaining real-time information organization in the brain, though it is incremental as it builds on existing chunking theories with a specific neural mechanism.
The authors tackled the problem of how the brain spontaneously organizes novel stimuli into chunks in working memory, proposing a synaptic theory where short-term synaptic plasticity enables chunk formation, leading to a model that predicts and confirms new capacity limits through neural data and memory experiments.
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.