Search results for "Spike train"
showing 10 items of 13 documents
An Information-Theoretic Framework to Measure the Dynamic Interaction between Neural Spike Trains
2021
Understanding the interaction patterns among simultaneous recordings of spike trains from multiple neuronal units is a key topic in neuroscience. However, an optimal approach of assessing these interactions has not been established, as existing methods either do not consider the inherent point process nature of spike trains or are based on parametric assumptions that may lead to wrong inferences if not met. This work presents a framework, grounded in the field of information dynamics, for the model-free, continuous-time estimation of both undirected (symmetric) and directed (causal) interactions between pairs of spike trains. The framework decomposes the overall information exchanged dynami…
Spike train statistics for consonant and dissonant musical accords in a simple auditory sensory model
2010
The phenomena of dissonance and consonance in a simple auditory sensory model composed of three neurons are considered. Two of them, here so-called sensory neurons, are driven by noise and subthreshold periodic signals with different ratio of frequencies, and its outputs plus noise are applied synaptically to a third neuron, so-called interneuron. We present a theoretical analysis with a probabilistic approach to investigate the interspike intervals statistics of the spike train generated by the interneuron. We find that tones with frequency ratios that are considered consonant by musicians produce at the third neuron inter-firing intervals statistics densities that are very distinctive fro…
Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics
2012
In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESC), exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing s…
Changes in neural drive to calf muscles during steady submaximal contractions after repeated static stretches
2021
Key points: Repeated static-stretching interventions consistently increase the range of motion about a joint and decrease total joint stiffness, but findings on the changes in muscle and connective-tissue properties are mixed. The influence of these stretch-induced changes on muscle function at submaximal forces is unknown. To address this gap in knowledge, the changes in neural drive to the plantar flexor muscles after a static-stretch intervention were estimated. Neural drive to the plantar flexor muscles during a low-force contraction increased after repeated static stretches. These findings suggest that adjustments in motor unit activity are necessary at low forces to accommodate reduct…
A device for spike train sampling with built-in memory.
1987
Abstract The described interface to a digital computer measures interspike interval durations with a resolution of 10 μs. A built-in first-in first-out (FIFO) memory relieves the host computer from frequent I/O intensive tasks. The internal FIFO buffer can store up to 512 data words (wordlength is 16 bit) and works on the dual-port principle. This way the acquisition of a neuronal spike train is completely independent of the computer's simultaneously ongoing data access. A simple handshake protocol between the interface and the computer prevents any overhead communication. The buffer architecture of the instrument releases the host computer from high speed I/O handling schemes like real-tim…
Hardware-accelerated spike train generation for neuromorphic image and video processing
2014
Recent studies concerning Spiking Neural Networks show that they are a powerful tool for multiple applications as pattern recognition, image tracking, and detection tasks. The basic functional properties of SNN reside in the use of spike information encoding as the neurons are specifically designed and trained using spike trains. We present a novel and efficient frequency encoding algorithm with Gabor-like receptive fields using probabilistic methods and targeted to FPGA for online pro-cessing. The proposed encoding is versatile, modular and, when applied to images, it is able to perform simple image transforms as edge detection, spot detection or removal, and Gabor-like filtering without a…
The resemblance of an autocorrelation function to a power spectrum density for a spike train of an auditory model
2013
In this work we develop an analytical approach for calculation of the all-order interspike interval density (AOISID), show its connection with the autocorrelation function, and try to explain the discovered resemblance of AOISID to the power spectrum of the same spike train.
Components of after-hyperpolarization in magnocellular neurones of the rat supraoptic nucleusin vitro
1998
1. The pharmacological sensitivity of hyperpolarizing components of spike train after-potentials was examined in sixty-one magnocellular neurones of the rat supraoptic nucleus using intracellular recording techniques in a brain slice preparation. 2. In 26 % of all neurones a slow after-hyperpolarization (AHP) was observed in addition to a fast AHP. In 31 % of all neurones a depolarizing after-potential (DAP) was observed. 3. The fast AHP was blocked by apamin whereas the slow AHP was blocked by charybdotoxin (ChTX). The DAP was enhanced by ChTX or a DAP was unmasked if not present during the control period. 4. Low concentrations of TEA (0.15-1.5 mM) induced effects on the slow AHP and the D…
Information – theoretic characterization of concurrent activity of neural spike trains
2021
The analysis of massively parallel spike train recordings facilitates investigation of communications and synchronization in neural networks. In this work we develop and evaluate a measure of concurrent neural activity, which is based on intrinsic firing properties of the recorded neural units. An overall single neuron activity is unfolded in time and decomposed into working and non-firing state, providing a coarse, binary representation of the neurons functional state. We propose a modified measure of mutual information to reflect the degree of simultaneous activation and concurrency in neural firing patterns. The measure is shown to be sensitive to both correlations and anti-correlations,…
Topology of synaptic connectivity constrains neuronal stimulus representation, predicting two complementary coding strategies
2020
In motor-related brain regions, movement intention has been successfully decoded from in-vivo spike train by isolating a lower-dimension manifold that the high-dimensional spiking activity is constrained to. The mechanism enforcing this constraint remains unclear, although it has been hypothesized to be implemented by the connectivity of the sampled neurons. We test this idea and explore the interactions between local synaptic connectivity and its ability to encode information in a lower dimensional manifold through simulations of a detailed microcircuit model with realistic sources of noise. We confirm that even in isolation such a model can encode the identity of different stimuli in a lo…