Behrad Noudoost

The paper investigates how extrastriate cortex encodes and reads out perisaccadic temporal information, finding that neuronal responses bias and smooth temporal representations of presaccadic stimuli.

The paper investigates whether V4 neuron firing rate changes during saccades can explain perceptual mislocalization, finding they do not systematically correlate with the magnitude of mislocalization.

The paper investigates neural bursting activity in human prefrontal and temporal brain areas during visual working memory and finds that gamma and beta bursting correlates with memory performance and is coupled via a phase-burst code.

The paper uses MODWT to analyze LFPs in primate visual areas and finds working memory modulates oscillatory frequency and power, with specific frequency components correlating with firing rates.

This study shows that prefrontal working memory signals enhance phase-coded visual information in V4 neurons through beta oscillations, confirmed by pharmacological inactivation and a network model.

The paper quantifies perisaccadic spatial bias using computational models and reveals the role of extrastriate neurons in visual mislocalization.

This study investigates how prefrontal cortex activity influences spatial sensitivity of extrastriate neurons by inactivating FEF and measuring changes in V4 neuron responses.

This study investigates the role of frontal eye field (FEF) activity in spatial working memory and motor preparation by testing the effects of FEF inactivation on task performance.

The paper develops a computational model to study how extrastriate cortex neurons maintain visual representations during eye movements, finding that they preserve a memory of the visual scene to ensure continuous perception.

The paper shows that working memory gates visual cortical input to prefrontal neurons in monkeys, enhancing visual input when it matches remembered locations.

The paper shows that coordination between prefrontal and temporal cortex, measured by phase-locking of spikes and LFPs, predicts working memory performance and object-selective persistent activity.