scispace - formally typeset
G

Gabriel Koch Ocker

Researcher at Allen Institute for Brain Science

Publications -  45
Citations -  1552

Gabriel Koch Ocker is an academic researcher from Allen Institute for Brain Science. The author has contributed to research in topics: Spike train & Neural coding. The author has an hindex of 15, co-authored 42 publications receiving 1018 citations. Previous affiliations of Gabriel Koch Ocker include University of Pittsburgh & Carnegie Mellon University.

Papers
More filters
Journal ArticleDOI

A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex

TL;DR: An open, large-scale physiological survey of activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset is reported, revealing response specializations within the mouseVisual cortex.
Journal ArticleDOI

The mechanics of state-dependent neural correlations.

TL;DR: This work examines three separate mechanisms that modulate spike train correlations: changes in input correlations, internal fluctuations and the transfer function of single neurons in feedforward pathways and shows how the same approach can explain the modulation of correlations in recurrent networks.
Journal ArticleDOI

Survey of spiking in the mouse visual system reveals functional hierarchy

Joshua H. Siegle, +91 more
- 20 Jan 2021 - 
TL;DR: In this paper, a large-scale dataset of tens of thousands of units in six cortical and two thalamic regions in the brains of mice responding to a battery of visual stimuli is presented.
Posted ContentDOI

A large-scale, standardized physiological survey reveals higher order coding throughout the mouse visual cortex

TL;DR: An open, large-scale physiological survey of neural activity in the awake mouse visual cortex: the Allen Brain Observatory Visual Coding dataset is reported, revealing functional differences across these dimensions and showing that visual cortical responses are sparse but correlated.
Journal ArticleDOI

Attentional modulation of neuronal variability in circuit models of cortex

TL;DR: A novel analysis of population recordings in rhesus primate visual area V4 showing that a single biophysical mechanism may underlie these diverse neural correlates of attention, including inhibitory neurons and excitatory neurons, which are more sensitive to stimulus specific bottom-up inputs.