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Journal ArticleDOI

Survey of spiking in the mouse visual system reveals functional hierarchy

Joshua H. Siegle, +91 more
- 20 Jan 2021 - 
- Vol. 592, Iss: 7852, pp 86-92
TLDR
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.
Abstract
The anatomy of the mammalian visual system, from the retina to the neocortex, is organized hierarchically1. However, direct observation of cellular-level functional interactions across this hierarchy is lacking due to the challenge of simultaneously recording activity across numerous regions. Here we describe a large, open dataset-part of the Allen Brain Observatory2-that surveys spiking from tens of thousands of units in six cortical and two thalamic regions in the brains of mice responding to a battery of visual stimuli. Using cross-correlation analysis, we reveal that the organization of inter-area functional connectivity during visual stimulation mirrors the anatomical hierarchy from the Allen Mouse Brain Connectivity Atlas3. We find that four classical hierarchical measures-response latency, receptive-field size, phase-locking to drifting gratings and response decay timescale-are all correlated with the hierarchy. Moreover, recordings obtained during a visual task reveal that the correlation between neural activity and behavioural choice also increases along the hierarchy. Our study provides a foundation for understanding coding and signal propagation across hierarchically organized cortical and thalamic visual areas.

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Citations
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Journal ArticleDOI

Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings

TL;DR: A suite of electrophysiological tools comprising a miniaturized high-density probe, recoverable chronic implant fixtures, and algorithms for automatic post hoc motion correction are demonstrated, enabling an order-of-magnitude increase in the number of sites that can be recorded in small animals, such as mice, and the ability to record from them stably over long time scales.
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Large-scale neural recordings call for new insights to link brain and behavior

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Large-scale neural recordings call for new insights to link brain and behavior

TL;DR: In this article , the authors describe emerging tools and technologies being used to probe large-scale brain activity and new approaches to characterize behavior in the context of such measurements, and elaborate on existing modeling frameworks to interpret these data and argue that the interpretation of brain-wide neural recordings calls for new theoretical approaches that may depend on the desired level of understanding.
Journal ArticleDOI

Representational drift in the mouse visual cortex.

TL;DR: In this article, the authors analyzed large-scale optical and electrophysiological recordings from six visual cortical areas in behaving mice that were repeatedly presented with the same natural movies and found representational drift over timescales spanning minutes to days across multiple visual areas, cortical layers, and cell types.
References
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Proceedings Article

ImageNet Classification with Deep Convolutional Neural Networks

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Receptive fields, binocular interaction and functional architecture in the cat's visual cortex

TL;DR: This method is used to examine receptive fields of a more complex type and to make additional observations on binocular interaction and this approach is necessary in order to understand the behaviour of individual cells, but it fails to deal with the problem of the relationship of one cell to its neighbours.
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The NumPy Array: A Structure for Efficient Numerical Computation

TL;DR: In this article, the authors show how to improve the performance of NumPy arrays through vectorizing calculations, avoiding copying data in memory, and minimizing operation counts, which is a technique similar to the one described in this paper.
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