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Neocortex

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Automatic ground truth for deep learning stereology of immunostained neurons and microglia in mouse neocortex.

Journal of chemical neuroanatomy
Collection of unbiased stereology data currently relies on relatively simple, low throughput technology developed in the mid-1990s. In an effort to improve the accuracy and efficiency of these integrated hardware-software-digital microscopy systems, ...

A null model of the mouse whole-neocortex micro-connectome.

Nature communications
In connectomics, the study of the network structure of connected neurons, great advances are being made on two different scales: that of macro- and meso-scale connectomics, studying the connectivity between populations of neurons, and that of micro-s...

BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets.

Communications biology
Understanding how cognitive functions emerge from brain structure depends on quantifying how discrete regions are integrated within the broader cortical landscape. Recent work established that macroscale brain organization and function can be describ...

Divisive gain modulation enables flexible and rapid entrainment in a neocortical microcircuit model.

Journal of neurophysiology
Neocortical circuits exhibit a rich dynamic repertoire, and their ability to achieve entrainment (adjustment of their frequency to match the input frequency) is thought to support many cognitive functions and indicate functional flexibility. Although...

Exploiting defective RRAM array as synapses of HTM spatial pooler with boost-factor adjustment scheme for defect-tolerant neuromorphic systems.

Scientific reports
A crossbar array architecture employing resistive switching memory (RRAM) as a synaptic element accelerates vector-matrix multiplication in a parallel fashion, enabling energy-efficient pattern recognition. To implement the function of the synapse in...

Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks.

PLoS computational biology
A basic-yet nontrivial-function which neocortical circuitry must satisfy is the ability to maintain stable spiking activity over time. Stable neocortical activity is asynchronous, critical, and low rate, and these features of spiking dynamics contrib...

Anomalous Behavior Detection Framework Using HTM-Based Semantic Folding Technique.

Computational and mathematical methods in medicine
Upon the working principles of the human neocortex, the Hierarchical Temporal Memory model has been developed which is a proposed theoretical framework for sequence learning. Both categorical and numerical types of data are handled by HTM. Semantic F...

Learning in deep neural networks and brains with similarity-weighted interleaved learning.

Proceedings of the National Academy of Sciences of the United States of America
Understanding how the brain learns throughout a lifetime remains a long-standing challenge. In artificial neural networks (ANNs), incorporating novel information too rapidly results in catastrophic interference, i.e., abrupt loss of previously acquir...

A disector-based framework for the automatic optical fractionator.

Journal of chemical neuroanatomy
Stereology-based methods provide the current state-of-the-art approaches for accurate quantification of numbers and other morphometric parameters of biological objects in stained tissue sections. The advent of artificial intelligence (AI)-based deep ...

The cytoarchitectonic landscape revealed by deep learning method facilitated precise positioning in mouse neocortex.

Cerebral cortex (New York, N.Y. : 1991)
Neocortex is a complex structure with different cortical sublayers and regions. However, the precise positioning of cortical regions can be challenging due to the absence of distinct landmarks without special preparation. To address this challenge, w...