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15 papers · 1 filter
Representational constraints underlying similarity between task-optimized neural systems
Tahereh Toosi
Neural systems, artificial and biological, show similar representations of inputs when optimized to perform similar tasks. In visual systems optimized for tasks similar to object r…
Attention for Causal Relationship Discovery from Biological Neural Dynamics
Ziyu Lu, Anika Tabassum, Shruti Kulkarni +4
This paper explores the potential of the transformer models for learning Granger causality in networks with complex nonlinear dynamics at every node, as in neurobiological and biop…
Plug-and-Play Stability for Intracortical Brain-Computer Interfaces: A One-Year Demonstration of Seamless Brain-to-Text Communication
Chaofei Fan, Nick Hahn, Foram Kamdar +6
Intracortical brain-computer interfaces (iBCIs) have shown promise for restoring rapid communication to people with neurological disorders such as amyotrophic lateral sclerosis (AL…
Uncovering Intermediate Variables in Transformers using Circuit Probing
Michael A. Lepori, Thomas Serre, Ellie Pavlick
Neural network models have achieved high performance on a wide variety of complex tasks, but the algorithms that they implement are notoriously difficult to interpret. It is often…
A voxel-level approach to brain age prediction: A method to assess regional brain aging
Neha Gianchandani, Mahsa Dibaji, Johanna Ospel +4
Brain aging is a regional phenomenon, a facet that remains relatively under-explored within the realm of brain age prediction research using machine learning methods. Voxel-level p…
A perspective on neuroscience data standardization with Neurodata Without Borders
Andrea Pierré, Tuan Pham, Jonah Pearl +3
Neuroscience research has evolved to generate increasingly large and complex experimental data sets, and advanced data science tools are taking on central roles in neuroscience res…