AI Medical Compendium Topic:
Models, Neurological

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Learning to represent continuous variables in heterogeneous neural networks.

Cell reports
Animals must monitor continuous variables such as position or head direction. Manifold attractor networks-which enable a continuum of persistent neuronal states-provide a key framework to explain this monitoring ability. Neural networks with symmetri...

Coherent oscillations in balanced neural networks driven by endogenous fluctuations.

Chaos (Woodbury, N.Y.)
We present a detailed analysis of the dynamical regimes observed in a balanced network of identical quadratic integrate-and-fire neurons with sparse connectivity for homogeneous and heterogeneous in-degree distributions. Depending on the parameter va...

Surrogate gradients for analog neuromorphic computing.

Proceedings of the National Academy of Sciences of the United States of America
To rapidly process temporal information at a low metabolic cost, biological neurons integrate inputs as an analog sum, but communicate with spikes, binary events in time. Analog neuromorphic hardware uses the same principles to emulate spiking neural...

A connectivity-constrained computational account of topographic organization in primate high-level visual cortex.

Proceedings of the National Academy of Sciences of the United States of America
Inferotemporal (IT) cortex in humans and other primates is topographically organized, containing multiple hierarchically organized areas selective for particular domains, such as faces and scenes. This organization is commonly viewed in terms of evol...

The structural aspects of neural dynamics and information flow.

Frontiers in bioscience (Landmark edition)
BACKGROUND: Neurons have specialized structures that facilitate information transfer using electrical and chemical signals. Within the perspective of neural computation, the neuronal structure is an important prerequisite for the versatile computatio...

A neural surveyor to map touch on the body.

Proceedings of the National Academy of Sciences of the United States of America
Perhaps the most recognizable sensory map in all of neuroscience is the somatosensory homunculus. Although it seems straightforward, this simple representation belies the complex link between an activation in a somatotopic map and the associated touc...

The neural architecture of language: Integrative modeling converges on predictive processing.

Proceedings of the National Academy of Sciences of the United States of America
The neuroscience of perception has recently been revolutionized with an integrative modeling approach in which computation, brain function, and behavior are linked across many datasets and many computational models. By revealing trends across models,...

Dynamic Spatiotemporal Pattern Recognition With Recurrent Spiking Neural Network.

Neural computation
Our real-time actions in everyday life reflect a range of spatiotemporal dynamic brain activity patterns, the consequence of neuronal computation with spikes in the brain. Most existing models with spiking neurons aim at solving static pattern recogn...

Neuromorphic learning with Mott insulator NiO.

Proceedings of the National Academy of Sciences of the United States of America
Habituation and sensitization (nonassociative learning) are among the most fundamental forms of learning and memory behavior present in organisms that enable adaptation and learning in dynamic environments. Emulating such features of intelligence fou...

Hidden coexisting firings in fractional-order hyperchaotic memristor-coupled HR neural network with two heterogeneous neurons and its applications.

Chaos (Woodbury, N.Y.)
The firing patterns of each bursting neuron are different because of the heterogeneity, which may be derived from the different parameters or external drives of the same kind of neurons, or even neurons with different functions. In this paper, the di...