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Electrophysiological Phenomena

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Vowel decoding from single-trial speech-evoked electrophysiological responses: A feature-based machine learning approach.

Brain and behavior
INTRODUCTION: Scalp-recorded electrophysiological responses to complex, periodic auditory signals reflect phase-locked activity from neural ensembles within the auditory system. These responses, referred to as frequency-following responses (FFRs), ha...

A robot for high yield electrophysiology and morphology of single neurons in vivo.

Nature communications
Single-cell characterization and perturbation of neurons provides knowledge critical to addressing fundamental neuroscience questions including the structure-function relationship and neuronal cell-type classification. Here we report a robot for effi...

Stochastic spike synchronization in a small-world neural network with spike-timing-dependent plasticity.

Neural networks : the official journal of the International Neural Network Society
We consider the Watts-Strogatz small-world network (SWN) consisting of subthreshold neurons which exhibit noise-induced spikings. This neuronal network has adaptive dynamic synaptic strengths governed by the spike-timing-dependent plasticity (STDP). ...

Electrophysiological Muscle Classification Using Multiple Instance Learning and Unsupervised Time and Spectral Domain Analysis.

IEEE transactions on bio-medical engineering
OBJECTIVE: Electrophysiological muscle classification (EMC) is a crucial step in the diagnosis of neuromuscular disorders. Existing quantitative techniques are not sufficiently robust and accurate to be reliably clinically used. Here, EMC is modeled ...

Behavior, Electrophysiology, and Robotics Experiments to Study Lateral Line Sensing in Fishes.

Integrative and comparative biology
The lateral line system is a sensory system unique to fishes and amphibians. It is composed of distributed mechanosensory hair cell organs on the head and body (neuromasts), which are sensitive to pressure gradients and water movements. Over the last...

Network structure and input integration in competing firing rate models for decision-making.

Journal of computational neuroscience
Making a decision among numerous alternatives is a pervasive and central undertaking encountered by mammals in natural settings. While decision making for two-option tasks has been studied extensively both experimentally and theoretically, characteri...

Unsupervised identification of states from voltage recordings of neural networks.

Journal of neuroscience methods
BACKGROUND: Modern techniques for multi-neuronal recording produce large amounts of data. There is no automatic procedure for the identification of states in recurrent voltage patterns.

A coarse-graining framework for spiking neuronal networks: from strongly-coupled conductance-based integrate-and-fire neurons to augmented systems of ODEs.

Journal of computational neuroscience
Homogeneously structured, fluctuation-driven networks of spiking neurons can exhibit a wide variety of dynamical behaviors, ranging from homogeneity to synchrony. We extend our partitioned-ensemble average (PEA) formalism proposed in Zhang et al. (Jo...

A supervised machine learning approach to characterize spinal network function.

Journal of neurophysiology
Spontaneous activity is a common feature of immature neuronal networks throughout the central nervous system and plays an important role in network development and consolidation. In postnatal rodents, spontaneous activity in the spinal cord exhibits ...