AIMC Topic: Neocortex

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A disector-based framework for the automatic optical fractionator.

Journal of chemical neuroanatomy Jul 15, 2022
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 ...
Humans Artificial Intelligence Cell Count Neurons Neocortex Algorithms Animals Mice
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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 Jun 27, 2022
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...
Humans Neocortex Neural Networks, Computer Learning Models, Neurological Systems Theory
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Anomalous Behavior Detection Framework Using HTM-Based Semantic Folding Technique.

Computational and mathematical methods in medicine Mar 16, 2021
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...
Humans Neural Networks, Computer Machine Learning Pattern Recognition, Automated Electronic Data Processing Memory Neocortex Models, Neurological Natural Language Processing Semantics Algorithms Learning Computational Biology
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Cyclic transitions between higher order motifs underlie sustained asynchronous spiking in sparse recurrent networks.

PLoS computational biology Sep 30, 2020
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...
Animals Models, Neurological Action Potentials Neural Networks, Computer Algorithms Computer Simulation Neurons Markov Chains Neocortex
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Exploiting defective RRAM array as synapses of HTM spatial pooler with boost-factor adjustment scheme for defect-tolerant neuromorphic systems.

Scientific reports Jul 16, 2020
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...
Data Accuracy Synapses Transistors, Electronic Pattern Recognition, Automated Memory Neocortex Algorithms Computer Simulation Data Management Neural Networks, Computer Software Humans
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BrainSpace: a toolbox for the analysis of macroscale gradients in neuroimaging and connectomics datasets.

Communications biology Mar 5, 2020
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...
Reproducibility of Results Magnetic Resonance Imaging Brain Mapping Predictive Value of Tests Workflow Image Interpretation, Computer-Assisted Nerve Net Humans Diffusion Tensor Imaging Artificial Intelligence Neocortex
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Divisive gain modulation enables flexible and rapid entrainment in a neocortical microcircuit model.

Journal of neurophysiology Feb 5, 2020
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...
Models, Neurological Nerve Net Interneurons Neural Inhibition Humans Neocortex Neural Networks, Computer Animals
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A null model of the mouse whole-neocortex micro-connectome.

Nature communications Aug 29, 2019
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...
Neocortex Neural Networks, Computer Connectome Models, Statistical Nerve Net Neurons Models, Animal Brain Animals Mice
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Automatic ground truth for deep learning stereology of immunostained neurons and microglia in mouse neocortex.

Journal of chemical neuroanatomy Mar 2, 2019
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, ...
Histological Techniques Animals Deep Learning Microglia Neocortex Image Processing, Computer-Assisted Cell Count Mice Neurons
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Effect of dilution in asymmetric recurrent neural networks.

Neural networks : the official journal of the International Neural Network Society Apr 16, 2018
We study with numerical simulation the possible limit behaviors of synchronous discrete-time deterministic recurrent neural networks composed of N binary neurons as a function of a network's level of dilution and asymmetry. The network dilution measu...
Hippocampus Machine Learning Humans Neocortex Learning Neural Networks, Computer Models, Neurological
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