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Recurrent amplification of grid-cell activity.

Hippocampus
High-level cognitive abilities such as navigation and spatial memory are thought to rely on the activity of grid cells in the medial entorhinal cortex (MEC), which encode the animal's position in space with periodic triangular patterns. Yet the neura...

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...

Third-order nanocircuit elements for neuromorphic engineering.

Nature
Current hardware approaches to biomimetic or neuromorphic artificial intelligence rely on elaborate transistor circuits to simulate biological functions. However, these can instead be more faithfully emulated by higher-order circuit elements that nat...

Biological batch normalisation: How intrinsic plasticity improves learning in deep neural networks.

PloS one
In this work, we present a local intrinsic rule that we developed, dubbed IP, inspired by the Infomax rule. Like Infomax, this rule works by controlling the gain and bias of a neuron to regulate its rate of fire. We discuss the biological plausibilit...

Learning probabilistic neural representations with randomly connected circuits.

Proceedings of the National Academy of Sciences of the United States of America
The brain represents and reasons probabilistically about complex stimuli and motor actions using a noisy, spike-based neural code. A key building block for such neural computations, as well as the basis for supervised and unsupervised learning, is th...

Turing Universality of Weighted Spiking Neural P Systems with Anti-spikes.

Computational intelligence and neuroscience
Weighted spiking neural P systems with anti-spikes (AWSN P systems) are proposed by adding anti-spikes to spiking neural P systems with weighted synapses. Anti-spikes behave like spikes of inhibition of communication between neurons. Both spikes and ...

Optical Mapping-Validated Machine Learning Improves Atrial Fibrillation Driver Detection by Multi-Electrode Mapping.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypoth...

Systematic errors in connectivity inferred from activity in strongly recurrent networks.

Nature neuroscience
Understanding the mechanisms of neural computation and learning will require knowledge of the underlying circuitry. Because it is difficult to directly measure the wiring diagrams of neural circuits, there has long been an interest in estimating them...

Spiking Neural P Systems with Extended Channel Rules.

International journal of neural systems
This paper discusses a new variant of spiking neural P systems (in short, SNP systems), spiking neural P systems with extended channel rules (in short, SNP-ECR systems). SNP-ECR systems are a class of distributed parallel computing models. In SNP-ECR...