scholarly journals Local differences in neuronal activation level decorrelate spatially coherent global fluctuations in gamma rhythms

2017 ◽  
Author(s):  
Kaushik J. Lakshminarasimhan ◽  
Nikos K. Logothetis ◽  
Georgios A. Keliris
Keyword(s):  
Firing Rate ◽  
Field Potential ◽  
Statistical Technique ◽  
Rate Code ◽  
Firing Rates ◽  
Activation Level ◽  
Gamma Rhythms ◽  
Global Fluctuations ◽  
Neuronal Coherence ◽  
Local Field Potential Lfp

AbstractNeuronal coherence is thought to constitute a unique substrate for information transmission distinct from firing rate. However, since the spatial scale of extracellular oscillations typically exceeds that of firing rates, it is unclear whether coherence complements or compromises the rate code. We examined responses in the macaque primary visual cortex and found that fluctuations in gamma-band (~40Hz) neuronal coherence correlated more with firing rate than oscillations in the local-field-potential (LFP). Although the spatial extent of LFP rhythms was broader, that of neuronal coherence was indistinguishable from firing rates. To identify the mechanism, we developed a statistical technique to isolate the rhythmic component of the spiking process and found that above results are explained by an activation-dependent increase in neuronal sensitivity to gamma-rhythmic input. Such adaptive changes in sensitivity to rhythmic inputs might constitute a fundamental homeostatic mechanism that prevents globally coherent inputs from undermining spatial resolution of the neural code.

Variability in somatosensory cortical neuron discharge: effects on capacity to signal different stimulus conditions using a mean rate code

1978 ◽  
Vol 41 (2) ◽  
pp. 338-349 ◽  
Author(s):  
R. C. Schreiner ◽  
G. K. Essick ◽  
B. L. Whitsel
Keyword(s):  
Firing Rate ◽  
Linear Equation ◽  
Cortical Neuron ◽  
Single Neuron ◽  
Rate Code ◽  
Firing Rates ◽  
Discrimination Criterion ◽  
The Mean ◽  
Change In Mean ◽  
The Relationship

1. The present study is based on the demonstration (8, 9) that the relationship between mean interval (MI) and standard deviation (SD) for stimulus-driven activity recorded from SI neurons is well fitted by the linear equation SD = a X MI + b and on the observations that the values of the slope (a) and y intercept (b) parameters of this relationship are independent of stimulus conditions and may vary widely from one neuron to the next (8). 2. A criterion for the discriminability of two different mean firing rates requiring that the mean intervals of their respective interspike interval (ISI) distributions be separated by a fixed interval (expressed in SD units) is developed and, on the basis of this criterion, a graphical display of the capacity of a neuron with a known SD-MI relationship to reflect a change in stimulus conditions with a change in mean firing rate is derived. Using this graphical approach, it is shown that the parameters of the SD-MI relationship for a single neuron determine a range of firing frequencies, within which that neuron exhibits the greatest capacity to signal differences in stimulus conditions using a frequency code. 3. The discrimination criterion is modified to incorporate the changes in the symmetry of the ISI distribution observed to accompany changes in mean firing rate. It is shown that, although the observed symmetry changes do influence the capacity of a cortical neuron to signal a change in stimulus conditions with a change in mean firing rate, they do not alter the range of firing rates (determined by the parameters of the SD-MI relationship) within which the capacity for discrimination is maximal. 4. The maximal number of firing levels that can be distinguished by a somatosensory cortical neuron (using the same discrimination criterion described above) discharging within a specified range of mean frequencies also is demonstrated to depend on the parameters of the linear equation which relates SD to MI. 5. Two approaches based on the t test for differences between two means are developed in an attempt to ascertain the minimum separation of the mean intervals of the ISI distributions necessary for two different mean firing rates to be discriminated with 80% certainty.

scholarly journals Coding of digit displacement by cell spiking and network oscillations in the monkey sensorimotor cortex

2012 ◽  
Vol 108 (12) ◽  
pp. 3342-3352 ◽  
Author(s):  
Claire L. Witham ◽  
Stuart N. Baker
Keyword(s):  
Firing Rate ◽  
Primary Motor Cortex ◽  
Field Potential ◽  
Oscillatory Activity ◽  
Significant Information ◽  
Information Theoretic ◽  
Sensory State ◽  
Somatosensory Cortices ◽  
Finger Flexion ◽  
Local Field Potential Lfp

β-Band oscillations occur in motor and somatosensory cortices and muscle activity. Oscillations appear most strongly after movements, suggesting that they may represent or probe the limb's final sensory state. We tested this idea by training two macaque monkeys to perform a finger flexion to one of four displacements, which was then held for 2 s without visual feedback of absolute displacement. Local field potential (LFP) and single unit spiking were recorded from the rostral and caudal primary motor cortex and parietal areas 3a, 3b, 2, and 5. Information theoretic analysis determined how well unit firing rate or the power of LFP oscillations coded finger displacement. All areas encoded significant information about finger displacement after the movement into target, both in β-band (∼20 Hz) oscillatory activity and unit firing rate. On average, the information carried by unit firing was greater (0.07 bits) and peaked earlier (0.73 s after peak velocity) than that by LFP β-oscillations (0.05 bits and 0.95 s). However, there was considerable heterogeneity among units: some cells did not encode maximal information until midway through the holding phase. In 30% of cells, information in rate lagged information in LFP oscillations recorded at the same site. Finger displacement may be represented in the cortex in multiple ways. Coding the digit configuration immediately after a movement probably relies on nonoscillatory feedback, or efference copy. With increasing delay after movement cessation, oscillatory processing may also play a part.

scholarly journals An uncertainty principle for neural coding: Conjugate representations of position and velocity are mapped onto firing rates and co-firing rates of neural spike trains

2019 ◽  
Author(s):  
Ryan Grgurich ◽  
Hugh T. Blair
Keyword(s):  
Firing Rate ◽  
Uncertainty Principle ◽  
Neural Coding ◽  
Spike Trains ◽  
Grid Cells ◽  
Rate Code ◽  
Biologically Inspired ◽  
Firing Rates ◽  
Neural Populations ◽  
Similar Information

AbstractThe hippocampal system contains neural populations that encode an animal’s position and velocity as it navigates through space. Here, we show that such populations can embed two codes within their spike trains: a firing rate code (R) conveyed by within-cell spike intervals, and a co-firing rate code (Ṙ) conveyed by between-cell spike intervals. These two codes behave as conjugates of one another, obeying an analog of the uncertainty principle from physics: information conveyed in R comes at the expense of information in Ṙ, and vice versa. An exception to this trade-off occurs when spike trains encode a pair of conjugate variables, such as position and velocity, which do not compete for capacity across R and Ṙ. To illustrate this, we describe two biologically inspired methods for decoding R and Ṙ, referred to as sigma and sigma-chi decoding, respectively. Simulations of head direction (HD) and grid cells show that if firing rates are tuned for position (but not velocity), then position is recovered by sigma decoding, whereas velocity is recovered by sigma-chi decoding. Conversely, simulations of oscillatory interference among theta-modulated “speed cells” show that if co-firing rates are tuned for position (but not velocity), then position is recovered by sigma-chi decoding, whereas velocity is recovered by sigma decoding. Between these two extremes, information about both variables can be distributed across both channels, and partially recovered by both decoders. These results suggest that neurons with different spatial and temporal tuning properties—such as speed versus grid cells—might not encode different information, but rather, distribute similar information about position and velocity in different ways across R and Ṙ. Such conjugate coding of position and velocity may influence how hippocampal populations are interconnected to form functional circuits, and how biological neurons integrate their inputs to decode information from firing rates and spike correlations.

scholarly journals Is there an Intrinsic Relationship between LFP Beta Oscillation Amplitude and Firing Rate of Individual Neurons in Macaque Motor Cortex?

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Joachim Confais ◽  
Nicole Malfait ◽  
Thomas Brochier ◽  
Alexa Riehle ◽  
Bjørg Elisabeth Kilavik
Keyword(s):  
Motor Cortex ◽  
Firing Rate ◽  
Oscillation Amplitude ◽  
Field Potential ◽  
Control Analysis ◽  
Single Trial ◽  
Beta Oscillations ◽  
Visuomotor Behavior ◽  
Local Field Potential Lfp ◽  
Beta Oscillation

Abstract The properties of motor cortical local field potential (LFP) beta oscillations have been extensively studied. Their relationship to the local neuronal spiking activity was also addressed. Yet, whether there is an intrinsic relationship between the amplitude of beta oscillations and the firing rate of individual neurons remains controversial. Some studies suggest a mapping of spike rate onto beta amplitude, while others find no systematic relationship. To help resolve this controversy, we quantified in macaque motor cortex the correlation between beta amplitude and neuronal spike count during visuomotor behavior. First, in an analysis termed “task-related correlation”, single-trial data obtained across all trial epochs were included. These correlations were significant in up to 32% of cases and often strong. However, a trial-shuffling control analysis recombining beta amplitudes and spike counts from different trials revealed these task-related correlations to reflect systematic, yet independent, modulations of the 2 signals with the task. Second, in an analysis termed “trial-by-trial correlation”, only data from fixed trial epochs were included, and correlations were calculated across trials. Trial-by-trial correlations were weak and rarely significant. We conclude that there is no intrinsic relationship between the firing rate of individual neurons and LFP beta oscillation amplitude in macaque motor cortex.

scholarly journals Primary sensorimotor cortex exhibits complex dependencies of spike-field coherence on neuronal firing rates, field power, and behavior

2018 ◽  
Vol 120 (1) ◽  
pp. 226-238 ◽  
Author(s):  
F. I. Arce-McShane ◽  
B. J. Sessle ◽  
C. F. Ross ◽  
N. G. Hatsopoulos
Keyword(s):  
Functional Connectivity ◽  
Firing Rate ◽  
Local Field ◽  
Sensorimotor Cortex ◽  
Field Potential ◽  
Neuronal Firing ◽  
Firing Rates ◽  
Linear Relationships ◽  
And Behavior ◽  
Field Coherence

Spike-field coherence (SFC) is widely used to assess cortico-cortical interactions during sensorimotor behavioral tasks by measuring the consistency of the relative phases between the spike train of a neuron and the concurrent local field potentials (LFPs). Interpretations of SFC as a measure of functional connectivity are complicated by theoretical work suggesting that estimates of SFC depend on overall neuronal activity. We evaluated the dependence of SFC on neuronal firing rates, LFP power, and behavior in the primary motor (MIo) and primary somatosensory (SIo) areas of the orofacial sensorimotor cortex of monkeys ( Macaca mulatta) during performance of a tongue-protrusion task. Although we occasionally observed monotonically increasing linear relationships between coherence and firing rate, we most often found highly complex, nonmonotonic relationships in both SIo and MIo and sometimes even found that coherence decreased with increasing firing rate. The lack of linear relationships was also true for both LFP power and tongue-protrusive force. Moreover, the ratio between maximal firing rate and the firing rate at peak coherence deviated significantly from unity, indicating that MIo and SIo neurons achieved maximal SFC at a submaximal level of spiking. Overall, these results point to complex relationships of SFC to firing rates, LFP power, and behavior during sensorimotor cortico-cortical interactions: coherence is a measure of functional connectivity whose magnitude is not a mere monotonic reflection of changes in firing rate, LFP power, or the relevantly controlled behavioral parameter. NEW & NOTEWORTHY The concern that estimates of spike-field coherence depend on the firing rates of single neurons has influenced analytical methods employed by experimental studies investigating the functional interactions between cortical areas. Our study shows that the overwhelming majority of the estimated spike-field coherence exhibited complex relations with firing rates of neurons in the orofacial sensorimotor cortex. The lack of monotonic relations was also evident after testing the influence of local field potential power and force on spike-field coherence.

Synchronization of neurons during local field potential oscillations in sensorimotor cortex of awake monkeys

1996 ◽  
Vol 76 (6) ◽  
pp. 3968-3982 ◽  
Author(s):  
V. N. Murthy ◽  
E. E. Fetz
Keyword(s):  
Firing Rate ◽  
Local Field ◽  
Sensorimotor Cortex ◽  
Local Field Potential ◽  
Field Potential ◽  
Peak Latency ◽  
Peak Amplitude ◽  
Firing Rates ◽  
Multiple Units ◽  
40 Hz

1. The neural activity associated with 20- to 40-Hz oscillations in sensorimotor cortex of awake monkeys was investigated by recording action potentials of single and multiple units. At a given site, activity of many units became synchronized with local field potential (LFP) oscillations. Cycle-triggered histograms (CTHs) of unit spikes aligned on cycles of LFP oscillations indicated that about two thirds of the recorded units (n = 268) were entrained with LFP oscillations. On average, units had the highest probability of spiking 2.7 ms before peak LFP negativity, corresponding to a -27.6 degrees phase shift relative to the negative peak of the LFP. 2. The average relative modulation amplitude (RMA), defined as the ratio of amplitude of oscillatory component of CTH and the baseline multiplied by 100, was 45 +/- 27% (mean +/- SD). The RMAs of single units did not differ significantly from those of multiple units. 3. Phase shifts and RMAs did not vary systematically with the cortical depth of recorded units. 4. Autocorrelation histograms (ACHs) of entrained units exhibited clear 20- to 40-Hz periodicity if they were compiled with spikes that occurred during oscillatory episodes in LFPs. ACHs of spikes outside oscillatory episodes usually did not show periodicity. Global ACHs of all spikes typically showed weak or no evidence of periodic activity. 5. Cross-correlation histograms (CCHs) between pairs of units complied with all spikes, whether they occurred during or outside LFP oscillations, seldom revealed significant features (19 of 134 pairs or 14%). However, CCHs compiled with spikes that occurred during oscillatory episodes (OS-CCHs) had significant features in 67 of 134 pairs recorded ipsilaterally; in these 67 cases, units at both sites showed modulation in CTHs. 6. The latencies of the OS-CCH peaks (taking the medial unit as reference) were normally distributed about a mean of -0.5 +/- 13 ms. Normalized peak height of CCHs (peak/baseline x 100) was, on average, 14.3 +/- 11.2%. Peak latency and normalized peak amplitude did not change significantly with horizontal separation of recorded precentral pairs up to 14 mm. 7. Units in the left and right hemispheres could become synchronized during oscillations. Significant features in OS-CCH were detected in 22 of 42 pairs of units recorded bilaterally. The average peak latency was 0.2 +/- 8.0 ms and the average normalized peak amplitude was 10 +/- 8%. These parameters did not differ significantly from those for ipsilateral OS-CCHs. 8. Oscillations tended to affect both the temporal structure and net rate of unit firing. For each unit, the firing rate was clamped to a narrow range of frequencies during oscillatory episodes. The coefficient of variation (SD/mean) of firing rates was significantly reduced during oscillatory episodes compared with prior rates (P < 0.001, paired t-test). However, the overall mean firing rate of each unit during all oscillatory episodes did not differ from its average rate immediately before the episodes. Thus oscillatory episodes tended to clamp mean firing rates to the cells' average rates outside episodes. 9. The strength of synchronization between units during oscillatory episodes was unrelated to their involvement in the task. For pairs of precentral units recorded ipsilaterally, the probability of occurrence of significant features in the OS-CCH was slightly larger when both units of the pair were task related (33 of 56 pairs or 59%) than when only one unit was task related (20 of 39 pairs or 51%) or neither unit was task related (7 of 16 or 44%). However, these differences were not statistically significant. The magnitude of the correlation peak and the latency to peak were also not significantly different for the three cases. 10. These results suggest that units across wide regions can become transiently synchronized specifically during LFP oscillations, even if their spikes are uncorrelated during nonoscillatory periods.

scholarly journals Is there an intrinsic relationship between LFP beta oscillation amplitude and firing rate of individual neurons in monkey motor cortex?

2019 ◽  
Author(s):  
Joachim Confais ◽  
Nicole Malfait ◽  
Thomas Brochier ◽  
Alexa Riehle ◽  
Bjørg Elisabeth Kilavik
Keyword(s):  
Motor Cortex ◽  
Firing Rate ◽  
Oscillation Amplitude ◽  
Field Potential ◽  
Spike Rate ◽  
Behavioral Task ◽  
Beta Oscillations ◽  
Macaque Monkeys ◽  
Local Field Potential Lfp ◽  
Beta Oscillation

ABSTRACTIt is a long-standing controversial issue whether an intrinsic relationship between the local field potential (LFP) beta oscillation amplitude and the spike rate of individual neurons in the motor cortex exists. Beta oscillations are prominent in motor cortical LFPs, and their relationship to the local neuronal spiking activity has been extensively studied. Many studies demonstrated that the spikes of individual neurons lock to the phase of LFP beta oscillations. However, the results concerning whether there is also an intrinsic relationship between the amplitude of LFP beta oscillations and the firing rate of individual neurons are contradictory. Some studies suggest a systematic mapping of spike rates onto LFP beta amplitude, and others find no systematic relationship. To resolve this controversy, we correlated the amplitude of LFP beta oscillations recorded in motor cortex of two male macaque monkeys with spike counts of individual neurons during visuomotor behavior, in two different manners. First, in an analysis termed task-related correlation, data obtained across all behavioral task epochs was included. These task-related correlations were frequently significant, and in majority of negative sign. Second, in an analysis termed trial-by-trial correlation, only data from a fixed pre-cue task epoch was included, and correlations were calculated across trials. Such trial-by-trial correlations were weak and rarely significant. We conclude that there is no intrinsic relationship between the firing rate of individual neurons and LFP beta oscillation amplitude in macaque motor cortex, beyond each of these signals being modulated by external factors such as the behavioral task.SIGNIFICANCE STATEMENTWe addressed the long-standing controversial issue of whether there is an intrinsic relationship between the local field potential (LFP) beta oscillation amplitude and the spike rate of individual neurons in the motor cortex. In two complementary analyses of data from macaque monkeys, we first demonstrate that the unfolding behavioral task strongly affects both the LFP beta amplitude and the neuronal spike rate, creating task-related correlations between the two signals. However, when limiting the influence of the task, by restricting our analysis to a fixed task epoch, correlations between the two signals were largely eliminated. We conclude that there is no intrinsic relationship between the firing rate of individual neurons and LFP beta oscillation amplitude in motor cortex.

scholarly journals A deep convolutional visual encoding model of neuronal responses in the LGN

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Eslam Mounier ◽  
Bassem Abdullah ◽  
Hani Mahdi ◽  
Seif Eldawlatly
Keyword(s):  
Firing Rate ◽  
Visual Information ◽  
Visual Stimulation ◽  
Neuronal Population ◽  
Neuronal Firing ◽  
Electrode Arrays ◽  
Deep Convolutional Neural Networks ◽  
Firing Rates ◽  
Spatiotemporal Representation

AbstractThe Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.

Coherent network oscillations by olfactory interneurons: modulation by endogenous amines

1993 ◽  
Vol 69 (6) ◽  
pp. 1930-1939 ◽  
Author(s):  
A. Gelperin ◽  
L. D. Rhines ◽  
J. Flores ◽  
D. W. Tank
Keyword(s):  
Second Messengers ◽  
Field Potential ◽  
Learning Ability ◽  
Odor Recognition ◽  
Axonal Projections ◽  
Odor Learning ◽  
Olfactory Systems ◽  
Olfactory Interneurons ◽  
Limax Maximus ◽  
Local Field Potential Lfp

1. The procerebral (PC) lobe of the terrestrial mollusk Limax maximus contains a highly interconnected network of local olfactory interneurons that receives direct axonal projections from the two pairs of noses. This olfactory processing network generates a 0.7-Hz oscillation in its local field potential (LFP) that is coherent throughout the network. The oscillating LFP is modulated by natural odorants applied to the neuroepithelium of the superior nose. 2. Two amines known to be present in the PC lobe, dopamine and serotonin, increase the frequency of the PC lobe oscillation and alter its waveform. 3. Glutamate, another putative neurotransmitter known to be present in the lobe, suppresses the PC lobe oscillation by a quisqualate-type receptor and appears to be used by one of the two classes of neurons in the PC lobe to generate the basic LFP oscillation. 4. The known activation of second messengers in Limax PC lobe by dopamine and serotonin together with their effects on the oscillatory rhythm suggest the hypothesis that these amines augment mechanisms mediating synaptic plasticity in the olfactory network, similar to hypothesized effects of amines in vertebrate olfactory systems. 5. The use of a distributed network of interneurons showing coherent oscillations may relate to the highly developed odor recognition and odor learning ability of Limax.

Encoding timing and intensity in the ventral cochlear nucleus of the cat

1986 ◽  
Vol 56 (2) ◽  
pp. 261-286 ◽  
Author(s):  
W. S. Rhode ◽  
P. H. Smith
Keyword(s):  
Firing Rate ◽  
Cochlear Nucleus ◽  
Auditory Nerve ◽  
Cell Types ◽  
Nerve Fibers ◽  
Frequency Selectivity ◽  
Firing Rates ◽  
Ventral Cochlear Nucleus ◽  
Auditory Nerve Fibers ◽  
Different Cell Types

Physiological response properties of neurons in the ventral cochlear nucleus have a variety of features that are substantially different from the stereotypical auditory nerve responses that serve as the principal source of activation for these neurons. These emergent features are the result of the varying distribution of auditory nerve inputs on the soma and dendrites of the various cell types within the nucleus; the intrinsic membrane characteristics of the various cell types causing different responses to the same input in different cell types; and secondary excitatory and inhibitory inputs to different cell types. Well-isolated units were recorded with high-impedance glass microelectrodes, both intracellularly and extracellularly. Units were characterized by their temporal response to short tones, rate vs. intensity relation, and response areas. The principal response patterns were onset, chopper, and primary-like. Onset units are characterized by a well-timed first spike in response to tones at the characteristic frequency. For frequencies less than 1 kHz, onset units can entrain to the stimulus frequency with greater precision than their auditory nerve inputs. This implies that onset units receive converging inputs from a number of auditory nerve fibers. Onset units are divided into three subcategories, OC, OL, and OI. OC units have extraordinarily wide dynamic ranges and low-frequency selectivity. Some are capable of sustaining firing rates of 800 spikes/s at high intensities. They have the smallest standard deviation and coefficient of variation of the first spike latency of any cells in the cochlear nuclei. OC units are candidates for encoding intensity. OI and OL units differ from OC units in that they have dynamic ranges and frequency selectivity ranges much like those of auditory nerve fibers. They differ from one another in their steady-state firing rates; OI units fire mainly at the onset of a tone. OI units also differ from OL units in that they prefer frequency sweeps in the low to high direction. Primary-like-with-notch (PLN) units also respond to tones with a well-timed first spike. They differ from onset cells in that the onset peak is not always as precise as the spontaneous rate is higher. A comparison of spontaneous firing rate and saturation firing rate of PLN units with auditory nerve fibers suggest that PLN units receive one to four auditory nerve fiber inputs. Chopper units fire in a sustained regular manner when they are excited by sound.(ABSTRACT TRUNCATED AT 400 WORDS)

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