Guangyu Robert Yang

Functional Dichotomy of Orbitofrontal Cortex and Anterior Cingulate Cortex Subregions in Decision-Making and Brain-Body Regulation

This study investigates the functional roles of the caudal orbitofrontal cortex (cOFC) and pregenual anterior cingulate cortex (pACC) in macaques using multimodal recordings and electrical microstimulation, finding distinct roles in decision-making and autonomic responses.

Scaling Properties for Artificial Neural Network Models of a Small Nervous System

This study examines how data and model size affect the accuracy of ANN models predicting neural activity in C. elegans, finding log-linear data scaling and nonlinear model scaling.

Natural constraints explain working memory capacity limitations in sensory-cognitive models

This study shows that pre-training sensory regions of neural networks with natural images can explain working memory capacity limitations without parameter fitting or hyperparameter tuning.

Meta-learning local synaptic plasticity for continual familiarity detection

The paper develops a neural network model with anti-Hebbian plasticity to detect familiarity in images, showing better performance than Hebbian models and replicating experimental results.

Evolving the Olfactory System with Machine Learning

This study shows that artificial neural networks trained on olfactory tasks develop structural and functional features similar to fly and mouse olfactory systems.

Ecologically pre-trained RNNs explain suboptimal animal decisions

The paper shows that pre-trained RNNs in ecological tasks mimic rats' suboptimal decision-making in 2AFC tasks by gating across-trial evidence after errors.

Constructing neural network models from brain data reveals representational transformations underlying adaptive behavior

The paper constructs neural network models from fMRI data to reveal how conjunction hubs support adaptive behavior through integrative computations.

Circuit mechanisms for the maintenance and manipulation of information in working memory

This study uses RNN models to show that short-term plasticity supports memory maintenance for short delays, while persistent activity emerges for information manipulation tasks.

Understanding the functional and structural differences across excitatory and inhibitory neurons

The paper uses an artificial neural network to study why excitatory and inhibitory neurons differ in selectivity and connectivity, finding that these differences can be explained by a few factors.

Inter-areal balanced amplification enhances signal propagation in a large-scale circuit model of the primate cortex

This study shows that balanced amplification across cortical areas enables stable signal propagation in a primate cortex model, supporting the ignition model of conscious processing.

Response Reversal During Top-Down Modulation In Cortical Circuits With Multiple Interneuron Types

The paper develops a theoretical framework and cortical circuit model to explain response reversal in mouse V1 neural populations under top-down modulation.

Clustering and compositionality of task representations in a neural network trained to perform many cognitive tasks

This study trains a neural network to perform 20 cognitive tasks and finds that it develops functionally specialized clusters and compositional task representations.