AIMC Topic: Neurons

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Elucidating the selection mechanisms in context-dependent computation through low-rank neural network modeling.

eLife
Humans and animals exhibit a remarkable ability to selectively filter out irrelevant information based on context. However, the neural mechanisms underlying this context-dependent selection process remain elusive. Recently, the issue of discriminatin...

Keypoint-based modeling reveals fine-grained body pose tuning in superior temporal sulcus neurons.

Nature communications
Body pose and orientation serve as vital visual signals in primate non-verbal social communication. Leveraging deep learning algorithms that extract body poses from videos of behaving monkeys, applied to a monkey avatar, we investigated neural tuning...

Stable recurrent dynamics in heterogeneous neuromorphic computing systems using excitatory and inhibitory plasticity.

Nature communications
Many neural computations emerge from self-sustained patterns of activity in recurrent neural circuits, which rely on balanced excitation and inhibition. Neuromorphic electronic circuits represent a promising approach for implementing the brain's comp...

Uncovering memorization effect in the presence of spurious correlations.

Nature communications
Machine learning models often rely on simple spurious features - patterns in training data that correlate with targets but are not causally related to them, like image backgrounds in foreground classification. This reliance typically leads to imbalan...

Brainstem noradrenergic modulation of the kisspeptin neuron GnRH pulse generator in mice.

Nature communications
Brainstem noradrenaline (NA) neurons modulate the activity of many neural networks including those responsible for the control of fertility. Using brain slice electrophysiology, we demonstrate that the arcuate nucleus kisspeptin (ARN) neurons, recent...

A simplified minimodel of visual cortical neurons.

Nature communications
Artificial neural networks (ANNs) have been shown to predict neural responses in primary visual cortex (V1) better than classical models. However, this performance often comes at the expense of simplicity and interpretability. Here we introduce a new...

Brain-wide input-output analysis of tuberal nucleus somatostatin neurons reveals hierarchical circuits for orchestrating feeding behavior.

Nature communications
Feeding is an innate behavior critical for survival but is also influenced by many non-nutritional factors such as emotion, social context and environmental conditions. Recently, tuberal nucleus somatostatin (SST) neurons have been identified as a ke...

Neurons throughout the brain embed robust signatures of their anatomical location into spike trains.

eLife
Neurons in the brain are known to encode diverse information through their spiking activity, primarily reflecting external stimuli and internal states. However, whether individual neurons also embed information about their own anatomical location wit...

Optogenetic neural spheroids excite primary neural network.

Journal of neural engineering
Optical stimulation ofneurons requires prior transfection with light gated ion channels. This additional step brings complexity and requires optimization. Simplification of the process will ease the undertaking of studies on biological neural network...

The architecture design and training optimization of spiking neural network with low-latency and high-performance for classification and segmentation.

Neural networks : the official journal of the International Neural Network Society
Spiking Neural Networks (SNNs) are the new third generation of bio-mimetic neural networks suitable for large-scale parallel computation due to its advantages of low power consumption and low latency. However, most of the training algorithms and netw...