AIMC Topic: Nerve Net

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Homeostatic Activity-Dependent Tuning of Recurrent Networks for Robust Propagation of Activity.

The Journal of neuroscience : the official journal of the Society for Neuroscience
UNLABELLED: Developing neuronal networks display spontaneous bursts of action potentials that are necessary for circuit organization and tuning. While spontaneous activity has been shown to instruct map formation in sensory circuits, it is unknown wh...

Best facilitated cortical activation during different stepping, treadmill, and robot-assisted walking training paradigms and speeds: A functional near-infrared spectroscopy neuroimaging study.

NeuroRehabilitation
BACKGROUND: Robot-assisted and treadmill-gait training are promising neurorehabilitation techniques, with advantages over conventional gait training, but the neural substrates underpinning locomotor control remain unknown particularly during differen...

Framework for single input single output nanonetwork-based realistic molecular communication.

IET nanobiotechnology
Mobile ad hoc molecular nanonetwork (MAMNET) is a new paradigm for the realisation of future nanonetworks. In MAMNET, transmission of nanoscale information from nanomachine to infostation is based on collision and adhesion. In this study, the authors...

Electrical and Optical Activation of Mesoscale Neural Circuits with Implications for Coding.

The Journal of neuroscience : the official journal of the Society for Neuroscience
UNLABELLED: Artificial activation of neural circuitry through electrical microstimulation and optogenetic techniques is important for both scientific discovery of circuit function and for engineered approaches to alleviate various disorders of the ne...

A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex.

The Journal of neuroscience : the official journal of the Society for Neuroscience
UNLABELLED: Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in ...

Constructing Precisely Computing Networks with Biophysical Spiking Neurons.

The Journal of neuroscience : the official journal of the Society for Neuroscience
UNLABELLED: While spike timing has been shown to carry detailed stimulus information at the sensory periphery, its possible role in network computation is less clear. Most models of computation by neural networks are based on population firing rates....

Intrinsic excitability state of local neuronal population modulates signal propagation in feed-forward neural networks.

Chaos (Woodbury, N.Y.)
Reliable signal propagation across distributed brain areas is an essential requirement for cognitive function, and it has been investigated extensively in computational studies where feed-forward network (FFN) is taken as a generic model. But it is s...

The relative efficiency of modular and non-modular networks of different size.

Proceedings. Biological sciences
Most biological networks are modular but previous work with small model networks has indicated that modularity does not necessarily lead to increased functional efficiency. Most biological networks are large, however, and here we examine the relative...

Synchronization, non-linear dynamics and low-frequency fluctuations: analogy between spontaneous brain activity and networked single-transistor chaotic oscillators.

Chaos (Woodbury, N.Y.)
In this paper, the topographical relationship between functional connectivity (intended as inter-regional synchronization), spectral and non-linear dynamical properties across cortical areas of the healthy human brain is considered. Based upon functi...

Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

Methods in molecular biology (Clifton, N.J.)
Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion tha...