Alina Peter

The paper shows that primate amygdala neurons have visual selectivity linked to valence without conditioning, using image-computable models to predict this relationship.

The paper shows that some neurons in the human amygdala and hippocampus encode face identities based on shared visual features rather than invariant semantic concepts.

The paper shows that human visual gamma responses to color stimuli are not biased toward red when thalamic input strength is equalized, finding no difference between red and green stimuli but weak responses to blue.

The paper shows that in macaque V1, repeated visual stimuli lead to reduced firing rates and increased gamma-band synchronization, specific to the stimulus and its location, and generalize to natural images.

The paper shows that repeated visual stimuli cause stimulus-specific changes in gamma-band activity and functional connectivity in human visual cortex, with effects persisting after a delay.

The paper uses self-supervised deep neural networks to study how V1 activity predicts natural images, finding distinct roles for synchronization and firing rates in predictive coding.

The paper analyzes gamma oscillations in macaque V1, showing they can be modeled by a linear harmonic oscillator driven by noise, capturing amplitude-duration correlations and other features.

The paper shows that surface color and predictability modulate V1 firing rates and gamma oscillations, with synchrony indicating predictability from spatial context.