Periodic Reporting for period 2 - Hot-Coal WM (The Hot-Coal hypothesis of working memory)
Período documentado: 2022-12-01 hasta 2024-05-31
What is the problem/issue being addressed?
Working memory (WM) is a fundamental cognitive capability. It refers to our ability to hold, select
and manipulate several objects in mind simultaneously. It allows us to engage in flexible behavior and is tightly
linked to fluid intelligence. This project will answer an essential, yet unsolved aspect of WM: How can
primates use their WM in a generalized way and control what they think about? If you hear ‘apple’, ‘stone’
and ‘pear’ in sequence, and then you are asked to imagine the first fruit, how is it that you do not confuse
apples with pears?
There are many competing models of WM, but the biologically detailed models all lack in their ability to generalize.
Neural networks can be trained to perform similar WM tasks as primates do, a major difference
is that primates generalize their training. They can learn the task on a set of objects, then perform it on a novel
set. Computational models typically rely on changing the connections between units to achieve the desired
activity patterns to solve the task. Since these activity patterns depend on the objects held in WM, the training
does not translate to novel objects. Thus we need new models to understand how this is achieved.
What are the overall objectives?
Here we will propose a new solution to how WM control is generalized, the Hot-Coal model of WM. It relies on a novel computational
principle in which spatial location of information, rather than connectivity, is controlled by excitatory bursts
to support cognition. We will explore this principle and test it in data. We will analyze primate data and record and analyze human
data using EEG and fMRI. The overall objective is to validate the model in data and explore its computational capabilities using simulations.
Why is it important for society?
Working memory breaks is a fundamental aspect of being human and is closely related to our train of thought: how we organize our thoughts in time and plan actions.
Working memory is implicated in many of the most common and costly cognitive disorders. Specifically, it is the control aspects of working memory, which we study here, that are most strongly implicated in dementia and ADHD.
The new theory could constitute a significant advance in the mechanistic understanding of one of the most central and puzzling components of cognition. In the long run it could also lead to deeper insights into cognitive disorders.
Working memory (WM) is a fundamental cognitive capability. It refers to our ability to hold, select
and manipulate several objects in mind simultaneously. It allows us to engage in flexible behavior and is tightly
linked to fluid intelligence. This project will answer an essential, yet unsolved aspect of WM: How can
primates use their WM in a generalized way and control what they think about? If you hear ‘apple’, ‘stone’
and ‘pear’ in sequence, and then you are asked to imagine the first fruit, how is it that you do not confuse
apples with pears?
There are many competing models of WM, but the biologically detailed models all lack in their ability to generalize.
Neural networks can be trained to perform similar WM tasks as primates do, a major difference
is that primates generalize their training. They can learn the task on a set of objects, then perform it on a novel
set. Computational models typically rely on changing the connections between units to achieve the desired
activity patterns to solve the task. Since these activity patterns depend on the objects held in WM, the training
does not translate to novel objects. Thus we need new models to understand how this is achieved.
What are the overall objectives?
Here we will propose a new solution to how WM control is generalized, the Hot-Coal model of WM. It relies on a novel computational
principle in which spatial location of information, rather than connectivity, is controlled by excitatory bursts
to support cognition. We will explore this principle and test it in data. We will analyze primate data and record and analyze human
data using EEG and fMRI. The overall objective is to validate the model in data and explore its computational capabilities using simulations.
Why is it important for society?
Working memory breaks is a fundamental aspect of being human and is closely related to our train of thought: how we organize our thoughts in time and plan actions.
Working memory is implicated in many of the most common and costly cognitive disorders. Specifically, it is the control aspects of working memory, which we study here, that are most strongly implicated in dementia and ADHD.
The new theory could constitute a significant advance in the mechanistic understanding of one of the most central and puzzling components of cognition. In the long run it could also lead to deeper insights into cognitive disorders.
We have so far focused on analysing electrophysiological data in animal models to test the main hypothesis of the project. This has lead to 3 research publications. In particular, the paper accepted this year in Nature Communications (2023) provides direct experimental evidence for the major hypothesis of this project., i. e. spatial computing In addition to analyzing additional data from non-human primates we have also collected two data sets for from humans using EEG and MEG. With this data we will test if there is evidence for spatial computing also in humans. Simultaneously we are developing models of working memory using computer simulations. Here we try to capture and understand the observations we make in the electrophysiological data. This has to date lead to one publication.
We have provided direct experimental evidence that the spatial dimensions of cortex are utilized to control information in working memory in primates. This is the most central aspect of the project and constitutes progress beyond state of the art. We expect to find similar evidence from humans, and to develop mathematical neural network models that can replicate our electrophysiological findings before the end of the project.