1 citations · 1 across the 7 of their papers we have counts for
8 papers
Common-Mode Collapse and Recovery in Direct Feedback Alignment
Varun Reddy, Bernardo L. Sabatini, Houman Safaai
Direct feedback alignment (DFA) trains hidden layers through fixed random projections of output error. With tanh hidden units and independent sigmoid outputs, plain stochastic grad…
When Branch-Local Shunting Helps: A Gain-Load-Alignment Principle for Dendritic E/I Networks
Houman Safaai, Maceo Richards, Naeem Khoshnevis +1
Biological neurons combine excitatory and inhibitory (E/I) activity on branched dendrites through shunting, in which inhibition divisively attenuates excitation. Whether this impro…
Synaptic clustering emerges from learning and supports covariance discrimination
Ilenna Simone Jones, Maceo Richards, Houman Safaai +2
Functional synapse clusters (FSCs) are synapses with correlated presynaptic activity that are colocalized on the same neuronal dendritic branch. FSCs have been observed after learn…
Shunting Inhibition and Dendritic Branching Shape Local Credit Assignment
Houman Safaai, Maceo Richards, Bernardo L. Sabatini
Biological neurons assign credit across branching dendrites, where synaptic drive, conductance, local voltage, and somatic teaching signals interact to shape plasticity. We study c…
Conditioned Direct Feedback Alignment via Activity and Error Geometry
Houman Safaai, Varun Reddy, Bernardo L. Sabatini
Direct feedback alignment (DFA) trains hidden layers with fixed random projections of the output error. Even when this feedback provides useful credit, unequal scales across activi…
Feature leakage and the identifiability of direct-dependency entropy models of neural activity
Houman Safaai, Bernardo L. Sabatini
Biological neurons receive thousands of synaptic inputs on branching, electrically excitable dendrites, yet population activity is often modeled with direct input-output rules in w…
Task Relevance Is Not Local Replaceability: A Two-Axis View of Channel Information
Houman Safaai, Andrew T. Landau, Celia C. Beron +2
Channel importance in vision networks is usually summarized by a single score. That summary hides two different questions: how much a channel is related to the task, and whether it…
ALIGN: Adversarial Learning for Generalizable Speech Neuroprosthesis
Zhanqi Zhang, Shun Li, Bernardo L. Sabatini +2
Intracortical brain-computer interfaces (BCIs) can decode speech from neural activity with high accuracy when trained on data pooled across recording sessions. In realistic deploym…