Katharine A. Shapcott

This study compares sustained attention dynamics across mice, monkeys, and humans using a shared VR task and hidden Markov models, finding greater similarity in attentional states than expected.

The paper compares human discrimination performance between oriented gratings and natural object morphs, finding that morphs are discriminated faster and over a larger range due to local color and texture features.

This study uses facial features from mice and monkeys to infer internal cognitive states during a foraging task, finding comparable state-task relationships across species.

The paper introduces a test to assess the relevance of trial-averaged neuronal metrics to neuronal computation, finding they are less relevant in less controlled settings.

The paper investigates the role of monkey primary visual cortex in working memory using recordings during a delayed match-to-sample task, finding that V1 maintains a fading trace of the sample stimulus and that test responses depend on probabilistic contingencies.

DomeVR provides an immersive VR environment for neuroscience experiments using Unreal Engine 4, offering modular tools for task control, logging, and multi-species testing.

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 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 shows that theta-rhythmic multi-unit activity in visual cortex arises from center-surround receptive field interactions and correlates with reaction time fluctuations during attention tasks.