scholarly journals Neurogrid simulates cortical cell-types, active dendrites, and top-down attention

2021 ◽  
Author(s):  
Ben Varkey Benjamin ◽  
Nicholas A. Steinmetz ◽  
Nick N. Oza ◽  
John Jose Aguayo ◽  
Kwabena Boahen
Keyword(s):  
Cortical Cell ◽  
Cell Types ◽  
Top Down ◽  
Active Dendrites

scholarly journals Neurogrid simulates cortical cell-types, active dendrites, and top-down attention

2021 ◽  
Author(s):  
Kwabena Boahen
Keyword(s):  
Analog Circuits ◽  
Digital Simulation ◽  
Cortical Cell ◽  
Cell Types ◽  
Synaptic Connections ◽  
Top Down ◽  
Cognitive Behaviors ◽  
Systems Neuroscience ◽  
Active Dendrites ◽  
Cortical Models

A central challenge for systems neuroscience and artificial intelligence is to understand how cognitive behaviors arise from large, highly interconnected networks of neurons. Digital simulation is linking cognitive behavior to neural activity to bridge this gap in our understanding at great expense in time and electricity. A hybrid analog-digital approach, whereby slow analog circuits, operating in parallel, emulate graded integration of synaptic currents by dendrites while a fast digital bus, operating serially, emulates all-or-none transmission of action potentials by axons, may improve simulation efficacy. Due to the latter's serial operation, this approach has not scaled beyond millions of synaptic connections (per bus). This limit was broken by following design principles the neocortex uses to minimize its wiring. The resulting hybrid analog-digital platform, Neurogrid, scales to billions of synaptic connections, between up to a million neurons, and simulates cortical models in real-time using a few watts of electricity. Here, we demonstrate that Neurogrid simulates cortical models spanning five levels of experimental investigation: biophysical, dendritic, neuronal, columnar, and area. Bridging these five levels with Neurogrid revealed a novel way active dendrites could mediate top-down attention.

scholarly journals Single-nucleus and single-cell transcriptomes compared in matched cortical cell types

PLoS ONE ◽  
2018 ◽  
Vol 13 (12) ◽  
pp. e0209648 ◽  
Author(s):  
Trygve E. Bakken ◽  
Rebecca D. Hodge ◽  
Jeremy A. Miller ◽  
Zizhen Yao ◽  
Thuc Nghi Nguyen ◽  
...  
Keyword(s):  
Single Cell ◽  
Cortical Cell ◽  
Cell Types ◽  
Single Nucleus

Cortical cell types and intermediate filament arrangements correlate with fiber curvature in Japanese human hair

2009 ◽  
Vol 166 (1) ◽  
pp. 46-58 ◽  
Author(s):  
Warren G. Bryson ◽  
Duane P. Harland ◽  
Jonathan P. Caldwell ◽  
James A. Vernon ◽  
Richard J. Walls ◽  
...  
Keyword(s):  
Intermediate Filament ◽  
Human Hair ◽  
Cortical Cell ◽  
Cell Types

scholarly journals Chandelier cell anatomy and function reveal a variably distributed but common signal

2020 ◽  
Author(s):  
Casey M. Schneider-Mizell ◽  
Agnes L. Bodor ◽  
Forrest Collman ◽  
Derrick Brittain ◽  
Adam A. Bleckert ◽  
...  
Keyword(s):  
Large Scale ◽  
Pyramidal Neurons ◽  
Cell Activity ◽  
Cortical Cell ◽  
Cell Types ◽  
Structural Features ◽  
Target Neuron ◽  
Chandelier Cell ◽  
Chandelier Cells

AbstractThe activity and connectivity of inhibitory cells has a profound impact on the operation of neuronal networks. While the average connectivity of many inhibitory cell types has been characterized, we still lack an understanding of how individual interneurons distribute their synapses onto their targets and how heterogeneous the inhibition is onto different individual excitatory neurons. Here, we use large-scale volumetric electron microscopy (EM) and functional imaging to address this question for chandelier cells in layer 2/3 of mouse visual cortex. Using dense morphological reconstructions from EM, we mapped the complete chandelier input onto 153 pyramidal neurons. We find that the number of input synapses is highly variable across the population, but the variability is correlated with structural features of the target neuron: soma depth, soma size, and the number of perisomatic synapses received. Functionally, we found that chandelier cell activity in vivo was highly correlated and tracks pupil diameter, a proxy for arousal state. We propose that chandelier cells provide a global signal whose strength is individually adjusted for each target neuron. This approach, combining comprehensive structural analysis with functional recordings of identified cell types, will be a powerful tool to uncover the wiring rules across the diversity of cortical cell types.

scholarly journals Single nucleus multi-omics links human cortical cell regulatory genome diversity to disease risk variants

2019 ◽  
Author(s):  
Chongyuan Luo ◽  
Hanqing Liu ◽  
Fangming Xie ◽  
Ethan J. Armand ◽  
Kimberly Siletti ◽  
...  
Keyword(s):  
Single Cell ◽  
Disease Risk ◽  
Single Cells ◽  
Cortical Cell ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Integrative Approach ◽  
Risk Variants ◽  
Human Frontal Cortex ◽  
Single Nucleus

ABSTRACTSingle-cell technologies enable measure of unique cellular signatures, but are typically limited to a single modality. Computational approaches allow integration of diverse single-cell datasets, but their efficacy is difficult to validate in the absence of authentic multi-omic measurements. To comprehensively assess the molecular phenotypes of single cells in tissues, we devised single-nucleus methylCytosine, Chromatin accessibility and Transcriptome sequencing (snmC2T-seq) and applied it to post-mortem human frontal cortex tissue. We developed a computational framework to validate fine-grained cell types using multi-modal information and assessed the effectiveness of computational integration methods. Correlation analysis in individual cells revealed distinct relations between methylation and gene expression. Our integrative approach enabled joint analyses of the methylome, transcriptome, chromatin accessibility and conformation for 63 human cortical cell types. We reconstructed regulatory lineages for cortical cell populations and found specific enrichment of genetic risk for neuropsychiatric traits, enabling prediction of cell types with causal roles in disease.

scholarly journals Stiffness of Human Hair Correlates with the Fractions of Cortical Cell Types

Cosmetics ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 24 ◽  
Author(s):  
Yusuke Ezawa ◽  
Shinobu Nagase ◽  
Akira Mamada ◽  
Shigeto Inoue ◽  
Kenzo Koike ◽  
...  
Keyword(s):  
Human Hair ◽  
Fluorescent Dyes ◽  
Cortical Cell ◽  
Cell Types ◽  
Cortical Cells ◽  
Force Microscopy ◽  
Bending Modulus ◽  
Hair Samples ◽  
Fluorescence Light ◽  
The Difference

(1) Background: The objective of this work was to elucidate the hair microstructure which correlates with the stiffness of human hair fibers. (2) Methods: Bending moduli of hair fibers were evaluated for the hair samples from 156 Japanese female subjects. Hair transverse sections were dual-stained with fluorescent dyes which can stain para- and ortho-like cortical cells separately, and observed under a fluorescence light microscope. Atomic force microscopy nanoindentation measurements were performed to examine the modulus inside macrofibrils. (3) Results: The difference in bending moduli between the maximum and the minimum values was more than double. The hair of high bending modulus was rich in para-like cortical cells and the bending modulus significantly correlated with the fraction of para-like cortical cells to the whole cortex. On the other hand, the elastic moduli inside macrofibrils were almost same for the para- and ortho-like cortical cells. (4) Conclusions: Hair bending modulus depends on the fractions of the constitutional cortical cell types. The contribution of the intermacrofibrillar materials, which differed in their morphologies and amounts of para- and ortho-like cortical cells, is plausible as a cause of the difference in the modulus of the cortical cell types.

Cortical cell types from spike trains

1993 ◽  
Vol 17 (1) ◽  
pp. 39-45 ◽  
Author(s):  
M. Taira ◽  
A.P. Georgopoulos
Keyword(s):  
Cortical Cell ◽  
Cell Types ◽  
Spike Trains

Neural Dynamics, Bifurcations, and Firing Rates in a Quadratic Integrate-and-Fire Model with a Recovery Variable. I: Deterministic Behavior

2012 ◽  
Vol 24 (8) ◽  
pp. 2078-2118 ◽  
Author(s):  
Eli Shlizerman ◽  
Philip Holmes
Keyword(s):  
Cortical Cell ◽  
Domain Of Attraction ◽  
Cell Types ◽  
Change Analysis ◽  
Fire Model ◽  
Firing Rates ◽  
Integrate And Fire ◽  
Single Compartment ◽  
Averaging Theorem ◽  
Deterministic Behavior

We study the dynamics of a quadratic integrate-and-fire model of a single-compartment neuron with a slow recovery variable, as input current and parameters describing timescales, recovery variable, and postspike reset change. Analysis of a codimension 2 bifurcation reveals that the domain of attraction of a stable hyperpolarized rest state interacts subtly with reset parameters, which reposition the system state after spiking. We obtain explicit approximations of instantaneous firing rates for fixed values of the recovery variable, and use the averaging theorem to obtain asymptotic firing rates as a function of current and reset parameters. Along with the different phase-plane geometries, these computations provide explicit tools for the interpretation of different spiking patterns and guide parameter selection in modeling different cortical cell types.

scholarly journals Comprehensive in situ mapping of human cortical transcriptomic cell types

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Christoffer Mattsson Langseth ◽  
Daniel Gyllborg ◽  
Jeremy A. Miller ◽  
Jennie L. Close ◽  
Brian Long ◽  
...  
Keyword(s):  
Brain Function ◽  
Cortical Cell ◽  
Cell Types ◽  
Cell Type ◽  
Cortical Cells ◽  
Human Cortex ◽  
Single Nucleus ◽  
Genetic Signatures ◽  
Cell Typing

AbstractThe ability to spatially resolve the cellular architecture of human cortical cell types over informative areas is essential to understanding brain function. We combined in situ sequencing gene expression data and single-nucleus RNA-sequencing cell type definitions to spatially map cells in sections of the human cortex via probabilistic cell typing. We mapped and classified a total of 59,816 cells into all 75 previously defined subtypes to create a first spatial atlas of human cortical cells in their native position, their abundances and genetic signatures. We also examined the precise within- and across-layer distributions of all the cell types and provide a resource for the cell atlas community. The abundances and locations presented here could serve as a reference for further studies, that include human brain tissues and disease applications at the cell type level.

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