Distinct behavioral effects of prefrontal and parietal cortex inactivations on an accumulation of evidence task in the rat


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Numerous brain regions have been shown to have neural correlates of gradually accumulating evidence for decision-making, but the causal roles of these regions in decisions driven by accumulation of evidence have yet to be determined. Here, in rats performing a sensory evidence accumulation task, we inactivated the frontal orienting fields (FOF) and posterior parietal cortex (PPC), two rat cortical regions that have neural correlates of accumulating evidence and that have been proposed as central to decision-making. We used a detailed model of the decision process to analyze the effect of inactivations. Inactivation of the FOF induced substantial performance impairments that were quantitatively best described as an impairment in the output pathway of an evidence accumulator with a long integration time constant (>240ms). In contrast, we found a minimal role for PPC in decisions guided by accumulating evidence, even while finding a strong role for PPC in internally-guided decisions.

Frequently Asked Questions for: The Atoms of Neural Computation



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Based on a survey of the literature, we attempt to answer Frequently Asked Questions on issues of cortical uniformity vs. non-uniformity, the neural mechanisms of symbolic variable binding, and other issues highlighted in (Marcus, Marblestone and Dean. “The Atoms of Neural Computation”. Science. 31 October 2014. Vol 346. Issue 6209).

Arousal and locomotion make distinct contributions to cortical activity patterns and visual encoding


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Spontaneous and sensory-evoked cortical activity is highly state-dependent, yet relatively little is known about transitions between distinct waking states. Patterns of activity in mouse V1 differ dramatically between quiescence and locomotion, but this difference could be explained by either motor feedback or a change in arousal levels. We recorded single cells and local field potentials from area V1 in mice head-fixed on a running wheel and monitored pupil diameter to assay arousal. Using naturally occurring and induced state transitions, we dissociated arousal and locomotion effects in V1. Arousal suppressed spontaneous firing and strongly altered the temporal patterning of population activity. Moreover, heightened arousal increased the signal-to-noise ratio of visual responses and reduced noise correlations. In contrast, increased firing in anticipation of and during movement was attributable to locomotion effects. Our findings suggest complementary roles of arousal and locomotion in promoting functional flexibility in cortical circuits.

Application of the radial distribution function for quantitative analysis of neuropil microstructure in stratum radiatum of CA1 region in hippocampus.


Various structures in the brain contain many important clues to the brain?s development and function. Among these, the microscopic organization of neural tissue is of particular interest since such organization has direct potential to affect the formation of local synaptic connectivity between axons and dendrites, serving as an important factor affecting the brain?s development. While the organization of the brain at large and intermediate scales had been well studied, the organization of neural tissue at micrometer scales remains largely unknown. In particular, at present it is not known what specific structures exist in neuropil at micrometer scales, what effect such structures have on formation of synaptic connectivity, and what processes shape the micrometer-scale organization of neuropil. In this work, we present an analysis of recent electron microscopy reconstructions of blocks of neuropil tissue from rat s. radiatum of hippocampal CA1 to provide insights into these questions. We propose a new statistical method for systematically analyzing the small-scale organization of neuropil based on an adaptation of the approach of radial distribution functions from statistical physics. Our results show that the micrometer-scale organization of hippocampal CA1 neuropil can be viewed as a disordered arrangement of axonal and dendritic processes without significant small-scale positional coordinations. We observe several deviations from this picture in the distributions of glia and dendritic spines. Finally, we study the relationship between local synaptic connectivity and the small-scale organization of neuropil.

Supervised learning sets benchmark for robust spike detection from calcium imaging signals


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We present a new data-driven approach to inferring spikes from calcium imaging signals using supervised training of non-linear spiking neuron models. Our technique yields a substantially better performance compared to previous generative modeling approaches, reconstructing spike trains accurately at high temporal resolution even from previously unseen datasets. Future data acquired in new experimental conditions can easily be used to further improve its spike prediction accuracy and generalization performance.