Global Attractors of Neural Firing-rate in Early Development

2021 ◽  
pp. 131-143
Keyword(s):  
Firing Rate ◽  
Early Development ◽  
Global Attractors ◽  
Neural Firing

Global attractor alphabet of neural firing modes

2013 ◽  
Vol 110 (4) ◽  
pp. 907-915 ◽  
Author(s):  
Yoram Baram
Keyword(s):  
Firing Rate ◽  
Global Attractor ◽  
Single Neuron ◽  
Global Attractors ◽  
Neuronal Firing ◽  
Passive State ◽  
Rate Model ◽  
Neural Firing ◽  
Neural Interaction ◽  
Parameter Dependent

The elementary set, or alphabet, of neural firing modes is derived from the widely accepted conductance-based rectified firing-rate model. The firing dynamics of interacting neurons are shown to be governed by a multidimensional bilinear threshold discrete iteration map. The parameter-dependent global attractors of the map morph into 12 attractor types. Consistent with the dynamic modes observed in biological neuronal firing, the global attractor alphabet is highly visual and intuitive in the scalar, single-neuron case. As synapse permeability varies from high depression to high potentiation, the global attractor type varies from chaotic to multiplexed, oscillatory, fixed, and saturated. As membrane permeability decreases, the global attractor transforms from active to passive state. Under the same activation, learning and retrieval end at the same global attractor. The bilinear threshold structure of the multidimensional map associated with interacting neurons generalizes the global attractor alphabet of neuronal firing modes to multineuron systems. Selective positive or negative activation and neural interaction yield combinatorial revelation and concealment of stored neuronal global attractors.

Modeling Reaching Impairment After Stroke Using a Population Vector Model of Movement Control That Incorporates Neural Firing-Rate Variability

2003 ◽  
Vol 15 (11) ◽  
pp. 2619-2642 ◽  
Author(s):  
David J. Reinkensmeyer ◽  
Mario G. Iobbi ◽  
Leonard E. Kahn ◽  
Derek G. Kamper ◽  
Craig D. Takahashi
Keyword(s):  
Cell Death ◽  
Standard Deviation ◽  
Firing Rate ◽  
Movement Control ◽  
Vector Model ◽  
Neural Firing ◽  
Population Vector ◽  
Directional Error ◽  
Wide Range ◽  
Impairment Severity

The directional control of reaching after stroke was simulated by including cell death and firing-rate noise in a population vector model of movement control. In this model, cortical activity was assumed to cause the hand to move in the direction of a population vector, defined by a summation of responses from neurons with cosine directional tuning. Two types of directional error were analyzed: the between-target variability, defined as the standard deviation of the directional error across a wide range of target directions, and the within-target variability, defined as the standard deviation of the directional error for many reaches to a single target. Both between and within-target variability increased with increasing cell death. The increase in between-target variability arose because cell death caused a nonuniform distribution of preferred directions. The increase in within-target variability arose because the magnitude of the population vector decreased more quickly than its standard deviation for increasing cell death, provided appropriate levels of firing-rate noise were present. Comparisons to reaching data from 29 stroke subjects revealed similar increases in between and within-target variability as clinical impairment severity increased. Relationships between simulated cell death and impairment severity were derived using the between and within-target variability results. For both relationships, impairment severity increased similarly with decreasing percentage of surviving cells, consistent with results from previous imaging studies. These results demonstrate that a population vector model of movement control that incorporates cosine tuning, linear summation of unitary responses, firing-rate noise, and random cell death can account for some features of impaired arm movement after stroke.

scholarly journals Phase-tuned neuronal firing encodes human contextual representations for navigational goals

2017 ◽  
Author(s):  
Andrew J Watrous ◽  
Jonathan Miller ◽  
Salman E Qasim ◽  
Itzhak Fried ◽  
Joshua Jacobs
Keyword(s):  
Firing Rate ◽  
Medial Temporal Lobe ◽  
Single Neuron ◽  
Detection Algorithm ◽  
Neuronal Firing ◽  
Neural Firing ◽  
Categorical Information ◽  
High Frequency Activity ◽  
Oscillation Detection ◽  
Intracranial Recordings

AbstractWe previously demonstrated that the phase of oscillations modulates neural activity representing categorical information using human intracranial recordings and high-frequency activity from local field potentials (Watrous et al., 2015b). We extend these findings here using human single-neuron recordings during a navigation task. We identify neurons in the medial temporal lobe with firing-rate modulations for specific navigational goals, as well as for navigational planning and goal arrival. Going beyond this work, using a novel oscillation detection algorithm, we identify phase-locked neural firing that encodes information about a person’s prospective navigational goal in the absence of firing rate changes. These results provide evidence for navigational planning and contextual accounts of human MTL function at the single-neuron level. More generally, our findings identify phase-coded neuronal firing as a component of the human neural code.

scholarly journals Resting-State Neural Firing Rate Is Linked to Cardiac-Cycle Duration in the Human Cingulate and Parahippocampal Cortices

2019 ◽  
Vol 39 (19) ◽  
pp. 3676-3686 ◽  
Author(s):  
Kayeon Kim ◽  
Josef Ladenbauer ◽  
Mariana Babo-Rebelo ◽  
Anne Buot ◽  
Katia Lehongre ◽  
...  
Keyword(s):  
Firing Rate ◽  
Resting State ◽  
Cardiac Cycle ◽  
Cycle Duration ◽  
Neural Firing

A General Likelihood Framework for Characterizing the Time Course of Neural Activity

2011 ◽  
Vol 23 (10) ◽  
pp. 2537-2566 ◽  
Author(s):  
Michael J. Prerau ◽  
Uri T. Eden
Keyword(s):  
Missing Data ◽  
Firing Rate ◽  
General Framework ◽  
Time Course ◽  
Estimation Accuracy ◽  
General Point ◽  
Neural Firing ◽  
Conditional Intensity ◽  
Intensity Estimation ◽  
Rate Estimation

We develop a general likelihood-based framework for use in the estimation of neural firing rates, which is designed to choose the temporal smoothing parameters that maximize the likelihood of missing data. This general framework is algorithm-independent and thus can be applied to a multitude of established methods for firing rate or conditional intensity estimation. As a simple example of the use of the general framework, we apply it to the peristimulus time histogram and kernel smoother, the methods most widely used for firing rate estimation in the electrophysiological literature and practice. In doing so, we illustrate how the use of the framework can employ the general point process likelihood as a principled cost function and can provide substantial improvements in estimation accuracy for even the most basic of rate estimation algorithms. In particular, the resultant kernel smoother is simple to implement, efficient to compute, and can accurately determine the bandwidth of a given rate process from individual spike trains. We perform a simulation study to illustrate how the likelihood framework enables the kernel smoother to pick the bandwidth parameter that best predicts missing data, and we show applications to real experimental spike train data. Additionally, we discuss how the general likelihood framework may be used in conjunction with more sophisticated methods for firing rate and conditional intensity estimation and suggest possible applications.

Chronic Electrophysiological and Behavioral Response in Rats due to Cerebral Ischemic Stroke in the Motor Cortex

2009 ◽  
Vol 2 (1) ◽  
Author(s):  
M. A. Midgett ◽  
P. J. Rousche
Keyword(s):  
Motor Cortex ◽  
Firing Rate ◽  
Behavioral Response ◽  
Neural Firing ◽  
Dynamic Changes ◽  
Post Stroke ◽  
Cylinder Test ◽  
Cerebral Ischemic Stroke ◽  
Cerebral Ischemic ◽  
Time Required

This work is the beginning of a study investigating dynamic changes of electrophysiological and correlative behavioral response in rats before, during and after stroke in the motor cortex. The animals need training sessions to regularly perform the behavioral tests. The standard deviation of total paw touches in the cylinder test (n=4) and the time required to eat a single strand of pasta (n=3) decreased by a factor of 1.7 and 3.6 respectively after 5 days of training. Behaviorally, post-stroke, average cylinder touches decreased by a factor of 5.6, and pasta adjustments increased by a factor of 3.6 suggesting impairments due to stroke. The pre-stroke mean neural firing rate was 94 spikes per second (spk/s), this increased to 146 spk/s during the 20 minute stroke induction, and was only 4 spk/s 20 min post-stroke. The firing rate has increased to near pre-stroke levels in the 2nd and 3rd days following stroke.

Intensity and frequency characteristics of pacinian corpuscles. I. Action potentials

1984 ◽  
Vol 51 (4) ◽  
pp. 793-811 ◽  
Author(s):  
S. J. Bolanowski ◽  
J. J. Zwislocki
Keyword(s):  
Firing Rate ◽  
Phase Locking ◽  
Stimulus Frequency ◽  
Receptor Potential ◽  
Frequency Characteristics ◽  
Maximum Sensitivity ◽  
Response Criterion ◽  
Neural Firing ◽  
Pacinian Corpuscles ◽  
Amplitude Frequency Characteristic

The mechanisms by which pacinian corpuscles, isolated from cat mesentery, transduce mechanical stimuli have been measured for directly applied sinusoidal deformations. Stimulus-response relationships were measured as follows: intensity characteristics, which relate the receptor-potential magnitude or the neural firing rate to stimulus intensity; amplitude-frequency characteristics, which relate the stimulus amplitude to stimulus frequency for a given response criterion; and phase-frequency characteristics, which relate the phase angle between the stimulus and the receptor response to stimulus frequency. This report, the first in a series of three, deals with the characteristics reflected in the neural firing rate. The two reports that follow deal with the receptor potential, which, if of sufficient amplitude, generates the propagated action potential. In the majority of the pacinian corpuscles investigated, the intensity characteristics for neural firing rates were steep at low stimulus intensities and plateaued at submultiples and multiples of the stimulus frequency as stimulus intensity was increased. Poststimulus time and interval histograms reveal that the plateaus occur as a result of phase locking to the stimulus. The submultiples and multiples of stimulus frequency at which phase locking was found and the length of the plateaus depended on stimulus frequency. These plateaus were eliminated with the use of narrow-band noise stimuli. The amplitude-frequency characteristics obtained with either a criterion of constant firing rate or that of a constant number of neural spikes per stimulus cycle were U-shaped functions. Their positions along both the intensity and frequency continua are affected by response criterion. For example, the mean (n = 19) amplitude-frequency characteristic generated with a constant firing rate criterion of 1 spike/s has a maximum sensitivity of about -37.0 dB re 1-micron peak and a best frequency (BF, stimulus frequency where maximum sensitivity occurs) of 465 Hz. The bandwidth, measured by Q3 dB, is 1.02. Alternatively, the average (n = 16) amplitude-frequency characteristic obtained with a response criterion of 1 spike per stimulus cycle has a maximum sensitivity of about -25.0 dB re 1-micron peak, a BF of 270 Hz and Q3 dB value of 1.16. Spontaneous activity (SPA; activity in the absence of controlled stimuli) was found in 13.6% of the pacinian corpuscles. Intensity characteristics and frequency characteristics of these corpuscles show features similar to those of corpuscles without spontaneous activity except that the intensity characteristics asymptote to SPA levels at low stimulus intensities.(ABSTRACT TRUNCATED AT 400 WORDS)

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