Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural population geometry: An approach for understanding biological and
  artificial neural networks   Advances in experimental neuroscience have transformed our ability to explore
the structure and function of neural circuits. At the same time, advances in
machine learning have unleashed the remarkable computational power of
artificial neural networks (ANNs). While these two fields have different tools
and applications, they present a similar challenge: namely, understanding how
information is embedded and processed through high-dimensional representations
to solve complex tasks. One approach to addressing this challenge is to utilize
mathematical and computational tools to analyze the geometry of these
high-dimensional representations, i.e., neural population geometry. We review
examples of geometrical approaches providing insight into the function of
biological and artificial neural networks: representation untangling in
perception, a geometric theory of classification capacity, disentanglement and
abstraction in cognitive systems, topological representations underlying
cognitive maps, dynamic untangling in motor systems, and a dynamical approach
to cognition. Together, these findings illustrate an exciting trend at the
intersection of machine learning, neuroscience, and geometry, in which neural
population geometry provides a useful population-level mechanistic descriptor
underlying task implementation. Importantly, geometric descriptions are
applicable across sensory modalities, brain regions, network architectures and
timescales. Thus, neural population geometry has the potential to unify our
understanding of structure and function in biological and artificial neural
networks, bridging the gap between single neurons, populations and behavior.

25
The categories of this paper are: patt-sol
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
21
The categories of this paper are: adap-org
18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
35
The categories of this paper are: mtrl-th
29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
28
The categories of this paper are: alg-geom