A multimodal cell census and atlas of the mammalian primary motor cortex

ABSTRACT We report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties

Orbitofrontal cortex neurons: role in olfactory and visual association learning

1. The orbitofrontal cortex is implicated in the rapid learning of new associations between visual stimuli and primary reinforcers such as taste. It is also the site of convergence of information from olfactory, gustatory, and visual modalities. To investigate the neuronal mechanisms underlying the formation of odor-taste associations, we made recordings from olfactory neurons in the orbitofrontal cortex during the performance of an olfactory discrim-ination task and its reversal in macaques. 2. It was found that 68 % of odor-responsive neurons modified their responses after the changes in the taste reward associations of the odorants. Full reversal of the neuronal responses was seen in 25 % of these neurons. Extinction of the differential neuronal responses after task reversal was seen in 43 % of these neurons. 3. For comparison, visually responsive orbitofrontal neurons were tested during reversal of a visual discrimination task. Seventy-one percent of these visual cells showed rapid full reversal of the visual stimulus to which they responded, when the association of the visual stimulus with taste was reversed in the reversal task. 4. These findings demonstrate that the responses of many orbitofrontal cortex olfactory neurons are modified by and depend on the taste with which the odor is associated. 5. This modification is likely to be important for setting the motivational value of olfactory stimuli for feeding and other re-warded behavior. However, it is less complete, and much slower, than the modifications found for orbitofrontal visual neurons during visual-taste reversal. This relative inflexibility of olfactory re-sponses is consistent with the need for some stability in odor-taste associations to facilitate the formation and perception of flavors

Firing Rate Distributions and Efficiency of Information Transmission of Inferior Temporal Cortex Neurons to Natural Visual Stimuli

The distribution of responses of sensory neurons to ecological stimulation has been proposed to be designed to maximize information transmission, which according to a simple model would imply an exponential distribution of spike counts in a given time window. We have used recordings from inferior temporal cortex neurons responding to quasi-natural visual stimulation (presented using a video of everyday lab scenes, and a large number of static images of faces and natural scenes) to assess the validity of this exponential model and to develop an alternative simple model of spike count distributions. We find that the exponential model has to be rejected in 84% of cases (at the P ! 0:01 level). A new model, which accounts for the firing rate distribution found in terms of slow and fast variability in the inputs which produce neuronal activation, is rejected statistically in only 16% of cases. Finally, we show that the neurons are moderately efficient at transmitting information, ..

Responses of neurons in primary and inferior temporal visual cortices to natural scenes.

The primary visual cortex (V1) is the first cortical area to receive visual input, and inferior temporal (IT) areas are among the last along the ventral visual pathway. We recorded, in area V1 of anaesthetized cats and area IT of awake macaque monkeys, responses of neurons to videos of natural scenes. Responses were analysed to test various hypotheses concerning the nature of neural coding in these two regions. A variety of spike-train statistics were measured including spike-count distributions, interspike interval distributions, coefficients of variation, power spectra, Fano factors and different sparseness measures. All statistics showed non-Poisson characteristics and several revealed self-similarity of the spike trains. Spike-count distributions were approximately exponential in both visual areas for eight different videos and for counting windows ranging from 50 ms to 5 seconds. The results suggest that the neurons maximize their information carrying capacity while maintaining a fixed long-term-average firing rate, or equivalently, minimize their average firing rate for a fixed information carrying capacity

Firing Rate Distributions and Efficiency of Information Transmission of Inferior Temporal Cortex Neurons to Natural Visual Stimuli

The distribution of responses of sensory neurons to ecological stimulation has been proposed to be designed to maximize information transmission, which according to a simple model would imply an exponential distribution of spike counts in a given time window. We have used recordings from inferior temporal cortex neurons responding to quasi-natural visual stimulation (presented using a video of everyday lab scenes and a large number of static images of faces and natural scenes) to assess the validity of this exponential model and to develop an alternative simple model of spike count distributions. We Žnd that the exponential model has to be rejected in 84% of cases (at the p < 0.01 level). A new model, which accounts for the Žring rate distribution found in terms of slow and fast variability in the inputs that produce neuronal activation, is rejected statistically in only 16% of cases. Finally, we show that the neurons are moderately efŽcient at transmitting information but not optimally efficient. c