@article {5360,
	title = {Skip Connections Increase the Capacity of Associative Memories in Variable Binding Mechanisms},
	number = {142},
	year = {2023},
	month = {06/2023},
	abstract = {<p>The flexibility of intelligent behavior is fundamentally attributed to the ability to separate and assign structural information from content in sensory inputs. Variable binding is the atomic computation that underlies this ability. In this work, we investigate the implementation of variable binding via pointers of assemblies of neurons, which are sets of excitatory neurons that fire together. The Assembly Calculus is a framework that describes a set of operations to create and modify assemblies of neurons. We focus on the project (which creates assemblies) and reciprocal-project (which performs vari- able binding) operations and study the capacity of networks in terms of the number of assemblies that can be reliably created and retrieved. We find that assembly calculus networks implemented through Hebbian plasticity resemble associative memories in their structure and behavior. However, for net- works with N neurons per brain area, the capacity of variable binding networks (0.01N) is an order of magnitude lower than the capacity of assembly creation networks (0.22N). To alleviate this drop in capacity, we propose a skip connection between the input and variable assembly, which boosts the capacity to a similar order of magnitude (0.1N ) as the Project operation, while maintain its biological plausibility.</p>
},
	author = {Yi Xie and Yichen Li and Akshay Rangamani}
}
@article {5084,
	title = {An approximate representation of objects underlies physical reasoning},
	journal = {psyArXiv},
	year = {2022},
	month = {03/2022},
	abstract = {<p>People make fast and reasonable predictions about the physical behavior of everyday objects. To do so, people may be using principled approximations, similar to models developed by engineers for the purposes of real-time physical simulations. We hypothesize that people use simplified object approximations for tracking and action (the "body" representation), as opposed to fine-grained forms for recognition (the "shape" representation). We used three classic psychophysical tasks (causality perception, collision detection, and change detection) in novel settings that dissociate body and shape. People{\textquoteright}s behavior across tasks indicates that they rely on approximate bodies for physical reasoning, and that this approximation lies between convex hulls and fine-grained shapes.</p>
},
	url = {https://psyarxiv.com/vebu5/},
	author = {Yichen Li and YingQiao Wang and Tal Boger and Kevin A Smith and Samuel J Gershman and Tomer Ullman}
}
