Summary: A recent study demonstrates that learning difficulties, more than storage capacity, contribute to working memory limits. Researchers demonstrated that having too much information at once confounds the head, preventing it from learning and making use of it properly using a system model of the basal ganglia and brain.
The concept demonstrated that the mind pays for this requirement by strategically” chunking” related information along, improving performance. These studies also shed light on dopamine-related diseases like Parkinson’s and ADHD, suggesting fresh treatment strategies targeting the basal ganglia and brain.
Major Information
- Learning affects memory capacity: To avoid overloaded and maximize learning, the brain limits working memory capacity.
- Chunking Strategy: To save space, the head pushes related information, improving remember performance.
- Dopamine’s Role: Problems in serotonin supply affect memory performance, linking working storage shortfalls to conditions like Parkinson’s and ADHD.
Origin: Brown University
Working storage is what enables people to combine various details in short-term contexts, such as making a mental grocery list, shopping, remembering, and therefore dialing a phone number.  ,
Scientists acknowledge that working memory has a limited potential, but they also offer opposing theories about how and why this is the case. However, recent studies from Brown University’s Carney Institute for Brain Science demonstrates why working memory has limitations.
Aneri Soni, a graduate student in his laboratory, and Michael Frank, a teacher of cognitive and psychological sciences at the Carney Institute, created a new system design of the basal ganglia and the brain, which demonstrates why there are limitations on working storage.
According to , their review published in , covering, the answer has to do with understanding.
The calculations we conducted demonstrate that if we did hang more than a small number of things at once, it becomes too challenging to learn how to manage but many pieces of information at once, leading to confusion and inability to use the information it does maintain, Soni said. Our research also demonstrates that the brain learns to strategically tap into a mechanism to help conserve space when faced with these constraints.
Because the neurotransmitter dopamine plays an important role in how learning relates to working memory, the researchers said these findings shed new light on dopamine-related disorders such as Parkinson’s disease, attention deficit-hyperactivity disorder ( ADHD ) and schizophrenia.
The team made their discovery by creating and testing a new computer model of the brain that resembled the findings of an experiment conducted in 2018 by researchers in Frank’s lab and those in Matt Nassar, a Carney Institute assistant professor of neuroscience and cognitive and psychological sciences.
In order to conserve space, that study demonstrated that people are capable of” chunking” information by combining related pieces of information together in working memory.  ,
When Soni gave her model a copy of the 2018 experiment, she was confident that she had created a brain-like computer model capable of compressing data. She asked the model to recall which colored block was pointing in which direction after showing it a model with different colored blocks oriented in various directions.
The model picked up the art of strategically combining information over the course of several trials, beginning to piece together similar colors like blue and light blue.  ,
The lab’s simulations with the new model point to learning, rather than capacity, as the real driver of working memory, Soni said. She demonstrated this by running the tests on a model with plenty of room for items but no chunking capability.
She discovered that the model without the chunking mechanism did not appear to realize it had access to such a large amount of storage and was worse at both storing and retrieving the items, despite the model with the chunking mechanism being able to strategically store information to its full storage capacity.
A mechanism that mimics the human brain’s dopamine delivery system is a crucial component to the model’s learning process, Soni said. The dopamine delivery system kicked in when the model was better at recalling the location of a larger number of blocks because it had clustered similar colors together to save space, telling the model to keep using this approach when confronted with the same set of constraints in subsequent trials.
In another part of the experiments, Soni altered the model’s dopamine delivery system to emulate what is known about dopamine levels in patients with Parkinson’s disease, schizophrenia and ADHD. Without a healthy dopamine delivery system, the model did not learn how to use its storage space as effectively and divided items as frequently when she subjected the model to the same series of trials.  ,
New findings like this show how computational brain science can advance psychiatry, said Frank, who directs Carney’s Center for Computational Brain Science.  ,
” Take Parkinson’s disease as an example”, Frank said. Because the movement changes are so obvious, the majority of people identify it as a movement disorder. But it turns out that Parkinson’s patients also have changes in working memory. Although they are typically treated with prefrontal cortex-targeting medications, our findings suggest that we should be looking into whether or not these medications help to reduce symptoms.
Frank asserted that more comprehensive knowledge of what happens in people who have dopamine-related disorders ‘ basal ganglia and thalamus may encourage clinicians to choose between treatment options.  ,
Funding: This research was supported by the Department of Defense ( ONR MURI Award N00014-23-1-2792 ) and the National Institute of Mental Health ( R01 MH084840-08A1, T32MH115895 ). The National Institutes of Health ( S10OD025181 ) provided funding for computing hardware.
About this research news regarding memory and learning
Author: Corrie Pikul
Source: Brown University
Contact: Corrie Pikul – Brown University
Image: The image is credited to Neuroscience News
Original Research: Open access.
Michael Frank and colleagues ‘” Adaptive chunking increases effective working memory capacity in a prefrontal cortex and basal ganglia circuit.” eLife
Abstract
In a prefrontal cortex and basal ganglia circuit, adaptive chunking increases effective working memory capacity.
How and why is working memory ( WM ) capacity limited? Traditional cognitive theories emphasize either limitations on the number or types of items that can be stored ( slots models ) or loss of precision as the load increases ( resource models ).
We demonstrate that a neural network model of prefrontal cortex and basal ganglia can learn to store multiple items using the same prefrontal populations, creating resource-like constraints within a slot-like system, and causing a trade-off between the quantity and the precision of information.
Such” chunking” strategies are adapted from normative models and human performance as reinforcement learning and WM task demands.
Moreover, adaptive performance requires a dynamic range of dopaminergic signals to adjust striatal gating policies, providing a new interpretation of WM difficulties in patient populations such as Parkinson’s disease, ADHD and schizophrenia.
These simulations also point to a computational rather than anatomical limit to WM capacity.
