Kohitij Kar

Hierarchical Optimization predicts Plasticity in the Macaque Inferior Temporal Cortex following Object Training

The paper models plasticity in macaque inferior temporal cortex after object training using ANN simulations, showing gradient descent approximates observed neural changes.

Motion-Dependent Object Perception Reveals Limits of Current Video Neural Networks

The paper evaluates how motion affects object perception in artificial vision systems and finds that video-based models can replicate human motion-dependent improvements, aligning with primate visual representations.

Adaptive recruitment of cortex-wide recurrence for visual object recognition

The paper tests the adaptive recurrence hypothesis by comparing fMRI and EEG responses to images recognized by humans but differing in their solvability by a feedforward deep neural network, finding that parieto-frontal networks are recruited when ventral stream processing is insufficient.

Distinct contributions of memorability and object recognition to the representational goals of the macaque inferior temporal cortex

The paper shows that models trained for both object recognition and image memorability better align with primate IT cortex responses than models trained solely for recognition.

Facial expression discrimination emerges from neural subspaces shared with detection and identity

The paper shows that neural subspaces in the macaque inferior temporal cortex shared with face identity also support facial expression discrimination, revealing a unified coding framework for social signals.

Reverse Predictivity: Going Beyond One-Way Mapping to Compare Artificial Neural Network Models and Brains

This paper introduces reverse predictivity to compare ANN models and primate brains, finding asymmetry in representation and identifying common and unique ANN units.

Object motion representation in the macaque ventral stream -- a gateway to understanding the brain's intuitive physics engine

This study investigates how rhesus macaques' ventral visual pathway processes object motion speed and direction, revealing its role in predictive behaviors and challenging traditional functional segregation of visual cortices.

Cell-type specific population codes link inferior temporal cortex to object recognition behavior

The paper investigates how cell-type specific neural populations in macaque IT cortex contribute to object recognition behavior, finding that excitatory neurons better predict behavior than inhibitory neurons.

The Impact of Scene Context on Visual Object Recognition: Comparing Humans, Monkeys, and Computational Models

This study compares human and rhesus macaque visual object recognition in different contexts, finding similar behavioral patterns but highlighting gaps in explaining these with neural data or models.

Recurrent Connections in the Primate Ventral Visual Stream Mediate a Tradeoff Between Task Performance and Network Size During Core Object Recognition

This study develops ConvRNN models to simulate primate ventral visual stream processing, finding that recurrent networks achieve better task performance and efficiency than deeper feedforward networks.

Aligning Model and Macaque Inferior Temporal Cortex Representations Improves Model-to-Human Behavioral Alignment and Adversarial Robustness

This study improves AI models by aligning their representations with macaque brain data, enhancing behavioral alignment and adversarial robustness.

A computational probe into the behavioral and neural markers of atypical facial emotion processing in autism.

The paper uses primate vision ANNs to investigate neural markers of atypical facial emotion processing in autism, finding behavioral mismatches and linking IT cortex activity to amygdala function.

Fast recurrent processing via ventral prefrontal cortex is needed by the primate ventral stream for robust core visual object recognition

This study shows that ventral prefrontal cortex (vPFC) is critical for recurrent processing in macaque IT cortex, which is necessary for robust visual object recognition of late-solved images.

A potential cortical precursor of visual word form recognition in untrained monkeys

The paper investigates neuronal representations of letters and letter strings in macaque monkeys and shows that IT cortex can support orthographic processing tasks similar to baboon behavior.

Brain-Score: Which Artificial Neural Network for Object Recognition is most Brain-Like?

Among dozens of ImageNet-trained networks scored against macaque V4/IT recordings and human behavior, DenseNet-169, CORnet-S and ResNet-101 rank highest, and brain similarity stops tracking accuracy above 70% top-1.

Transcranial alternating current stimulation attenuates BOLD adaptation and increases functional connectivity

This study shows that tACS at 10 Hz reduces BOLD adaptation in the human motion area and increases functional connectivity with the dorsal attention network.

Neural Population Control via Deep Image Synthesis

The paper uses deep image synthesis to control primate V4 neural activity, achieving population-level control beyond natural levels.

Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior

The paper shows that recurrent circuits in the primate ventral stream are critical for object recognition, as challenge images require longer processing and are poorly predicted by feedforward models.

Large-scale, high-resolution comparison of the core visual object recognition behavior of humans, monkeys, and state-of-the-art deep artificial neural networks

This paper compares human, monkey, and deep neural network performance in object recognition at the image level, finding that current models fail to predict primate behavior.