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.

scholarly journals Acetylcholine-gated current translates wake neuronal firing rate information into a spike timing-based code in Non-REM sleep, stabilizing neural network dynamics during memory consolidation

2021 ◽  
Vol 17 (9) ◽  
pp. e1009424
Author(s):  
Quinton M. Skilling ◽  
Bolaji Eniwaye ◽  
Brittany C. Clawson ◽  
James Shaver ◽  
Nicolette Ognjanovski ◽  
...  
Keyword(s):  
Firing Rate ◽  
Memory Consolidation ◽  
Neuronal Excitability ◽  
Network Models ◽  
Nrem Sleep ◽  
Spike Timing ◽  
Neuronal Firing ◽  
Information Encoding ◽  
Firing Rates

Sleep is critical for memory consolidation, although the exact mechanisms mediating this process are unknown. Combining reduced network models and analysis of in vivo recordings, we tested the hypothesis that neuromodulatory changes in acetylcholine (ACh) levels during non-rapid eye movement (NREM) sleep mediate stabilization of network-wide firing patterns, with temporal order of neurons’ firing dependent on their mean firing rate during wake. In both reduced models and in vivo recordings from mouse hippocampus, we find that the relative order of firing among neurons during NREM sleep reflects their relative firing rates during prior wake. Our modeling results show that this remapping of wake-associated, firing frequency-based representations is based on NREM-associated changes in neuronal excitability mediated by ACh-gated potassium current. We also show that learning-dependent reordering of sequential firing during NREM sleep, together with spike timing-dependent plasticity (STDP), reconfigures neuronal firing rates across the network. This rescaling of firing rates has been reported in multiple brain circuits across periods of sleep. Our model and experimental data both suggest that this effect is amplified in neural circuits following learning. Together our data suggest that sleep may bias neural networks from firing rate-based towards phase-based information encoding to consolidate memories.

Internal Pallidal Neuronal Activity During Mild Drug-Related Dyskinesias in Parkinson's Disease: Decreased Firing Rates and Altered Firing Patterns

2007 ◽  
Vol 97 (4) ◽  
pp. 2627-2641 ◽  
Author(s):  
J. I. Lee ◽  
L. Verhagen Metman ◽  
S. Ohara ◽  
P. M. Dougherty ◽  
J. H. Kim ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Firing Rate ◽  
Spike Trains ◽  
Neuronal Firing ◽  
Low Doses ◽  
Significant Group ◽  
Firing Patterns ◽  
Firing Rates ◽  
Before And After

The neuronal basis of hyperkinetic movement disorders has long been unclear. We now test the hypothesis that changes in the firing pattern of neurons in the globus pallidus internus (GPi) are related to dyskinesias induced by low doses of apomorphine in patients with advanced Parkinson's disease (PD). During pallidotomy for advanced PD, the activity of single neurons was studied both before and after administration of apomorphine at doses just adequate to induce dyskinesias (21 neurons, 17 patients). After the apomorphine injection, these spike trains demonstrated an initial fall in firing from baseline. In nine neurons, the onset of on was simultaneous with that of dyskinesias. In these spike trains, the initial fall in firing rate preceded and was larger than the fall at the onset of on with dyskinesias. Among the three neurons in which the onset of on occurred before that of dyskinesias, the firing rate did not change at the time of onset of dyskinesias. After injection of apomorphine, dyskinesias during on with dyskinesias often fluctuated between transient periods with dyskinesias and those without. Average firing rates were not different between these two types of transient periods. Transient periods with dyskinesias were characterized by interspike interval (ISI) independence, stationary spike trains, and higher variability of ISIs. A small but significant group of neurons demonstrated recurring ISI patterns during transient periods of on with dyskinesias. These results suggest that mild dyskinesias resulting from low doses of apomorphine are related to both low GPi neuronal firing rates and altered firing patterns.

Changes in Granule Cell Firing Rates Precede Locally Recorded Spontaneous Seizures by Minutes in an Animal Model of Temporal Lobe Epilepsy

2008 ◽  
Vol 99 (5) ◽  
pp. 2431-2442 ◽  
Author(s):  
Mark R. Bower ◽  
Paul S. Buckmaster
Keyword(s):  
Temporal Lobe Epilepsy ◽  
Dentate Gyrus ◽  
Firing Rate ◽  
Temporal Lobe ◽  
Granule Cells ◽  
Neuronal Firing ◽  
Seizure Onset ◽  
Electrographic Seizure ◽  
Firing Rates ◽  
Spontaneous Seizures

Although much is known about persistent molecular, cellular, and circuit changes associated with temporal lobe epilepsy, mechanisms of seizure onset remain unclear. The dentate gyrus displays many persistent epilepsy-related abnormalities and is in the mesial temporal lobe where seizures initiate in patients. However, little is known about seizure-related activity of individual neurons in the dentate gyrus. We used tetrodes to record action potentials of multiple, single granule cells before and during spontaneous seizures in epileptic pilocarpine-treated rats. Subsets of granule cells displayed four distinct activity patterns: increased firing before seizure onset, decreased firing before seizure onset, increased firing only after seizure onset, and unchanged firing rates despite electrographic seizure activity in the immediate vicinity. No cells decreased firing rate immediately after seizure onset. During baseline periods between seizures, action potential waveforms and firing rates were similar among the four subsets of granule cells in epileptic rats and in granule cells of control rats. The mean normalized firing rate of granule cells whose firing rates increased before seizure onset deviated from baseline earliest, beginning 4 min before dentate gyrus electrographic seizure onset, and increased progressively, more than doubling by seizure onset. It is generally assumed that neuronal firing rates increase abruptly and synchronously only when electrographic seizures begin. However, these findings show heterogeneous and gradually building changes in activity of individual granule cells minutes before spontaneous seizures.

scholarly journals In vivo Interictal Neuronal Signatures of Human Periventricular Nodular Heterotopia

2019 ◽  
Author(s):  
Valerio Frazzini ◽  
Stephen Whitmarsh ◽  
Katia Lehongre ◽  
Pierre Yger ◽  
Jean-Didier Lemarechal ◽  
...  
Keyword(s):  
Epileptic Activity ◽  
Neuronal Firing ◽  
Periventricular Nodular Heterotopia ◽  
Firing Rates ◽  
Neuronal Populations ◽  
Malformation Of Cortical Development ◽  
Nodular Heterotopia ◽  
Epileptic Spikes ◽  
Drug Resistant Epilepsy

AbstractPeriventricular nodular heterotopia (PNH) is a common type of malformation of cortical development and a cause of drug-resistant epilepsy. In contrast with other cortical malformations, no consistent interictal patterns have yet been identified in PNH, and it remains controversial whether epileptic activity originates within nodules. The current study addresses the heterogeneity in LFP signatures, as well as the question of epileptogenicity of nodules, by means of microelectrode recordings implanted within PNH tissues in two epileptic patients. Microelectrodes also allowed the first in vivo recording of heterotopic neurons in humans, permitting the investigation of neuronal firing rates during patterns of interictal activity. Highly consistent interictal patterns (IPs) were identified within PNH: 1) trains of periodic slow waves and 2) isolated slow deflections, both with superimposed fast activity, and 3) epileptic spikes. Neuron firing rates were significantly modulated during all IPs, suggesting that different IPs were generated by the same local neuronal populations. To conclude, this study presents the first in vivo microscopic description of local PNH microcircuits in humans and their organization into multiple epileptic neurophysiological patterns, providing a first pathognomonic signature of human PNH.

scholarly journals Binding of the synaptic vesicle radiotracer [11C]UCB-J is unchanged during functional brain activation using a visual stimulation task

2020 ◽  
pp. 0271678X2094619
Author(s):  
Kelly Smart ◽  
Heather Liu ◽  
David Matuskey ◽  
Ming-Kai Chen ◽  
Kristen Torres ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Synaptic Vesicle ◽  
Visual Stimulation ◽  
Brain Activation ◽  
Compartment Model ◽  
Neuronal Firing ◽  
Binding Potential ◽  
Reference Tissue ◽  
Vesicle Exocytosis

The positron emission tomography radioligand [11C]UCB-J binds to synaptic vesicle glycoprotein 2 A (SV2A), a regulator of vesicle release. Increased neuronal firing could potentially affect tracer concentrations if binding site availability is altered during vesicle exocytosis. This study assessed whether physiological brain activation induces changes in [11C]UCB-J tissue influx ( K1), volume of distribution ( VT), or binding potential ( BPND). Healthy volunteers ( n = 7) underwent 60-min [11C]UCB-J PET scans at baseline and during intermittent presentation of 8-Hz checkerboard visual stimulation. Sensitivity to intermittent changes in kinetic parameters was assessed in simulations, and visual stimulation was repeated using functional magnetic resonance imaging to characterize neural responses. VT  and K1 were determined using the one-tissue compartment model and BPND using the simplified reference tissue model. In primary visual cortex, K1 increased 34.3 ± 15.5% ( p = 0.001) during stimulation, with no change in other regions ( ps  >  0.12). K1 change was correlated with fMRI BOLD response (r = 0.77, p = 0.043). There was no change in VT (−3.9 ± 8.8%, p =  0.33) or BPND (−0.2 ± 9.6%, p =  0.94) in visual cortex nor other regions ( ps  >  0.19). Therefore, despite robust increases in regional tracer influx due to blood flow increases, binding measures were unchanged during stimulation. [11C]UCB-J VT and BPND are likely to be stable in vivo measures of synaptic density.

scholarly journals Separating Spike Count Correlation from Firing Rate Correlation

2016 ◽  
Vol 28 (5) ◽  
pp. 849-881 ◽  
Author(s):  
Giuseppe Vinci ◽  
Valérie Ventura ◽  
Matthew A. Smith ◽  
Robert E. Kass
Keyword(s):  
Firing Rate ◽  
Cortical Neurons ◽  
Experimental Manipulation ◽  
Response Variability ◽  
Spike Count ◽  
Firing Rates ◽  
Area V4 ◽  
Rate Correlation ◽  
Over Time

Populations of cortical neurons exhibit shared fluctuations in spiking activity over time. When measured for a pair of neurons over multiple repetitions of an identical stimulus, this phenomenon emerges as correlated trial-to-trial response variability via spike count correlation (SCC). However, spike counts can be viewed as noisy versions of firing rates, which can vary from trial to trial. From this perspective, the SCC for a pair of neurons becomes a noisy version of the corresponding firing rate correlation (FRC). Furthermore, the magnitude of the SCC is generally smaller than that of the FRC and is likely to be less sensitive to experimental manipulation. We provide statistical methods for disambiguating time-averaged drive from within-trial noise, thereby separating FRC from SCC. We study these methods to document their reliability, and we apply them to neurons recorded in vivo from area V4 in an alert animal. We show how the various effects we describe are reflected in the data: within-trial effects are largely negligible, while attenuation due to trial-to-trial variation dominates and frequently produces comparisons in SCC that, because of noise, do not accurately reflect those based on the underlying FRC.

scholarly journals Stretching and squeezing of neuronal log firing rate distribution by psychedelic and intrinsic brain state transitions

2021 ◽  
Author(s):  
Bradley Dearnley ◽  
Martynas Dervinis ◽  
Melissa Shaw ◽  
Michael Okun
Keyword(s):  
Neuronal Population ◽  
Neuronal Firing ◽  
State Transitions ◽  
Brain State ◽  
Rate Distribution ◽  
Firing Rates ◽  
Neuronal Populations ◽  
Psychedelic Drugs ◽  
Large Populations ◽  
Intrinsic Fluctuations

AbstractHow psychedelic drugs change the activity of cortical neuronal populations and whether such changes are specific to transition into the psychedelic brain state or shared with other brain state transitions is not well understood. Here, we used Neuropixels probes to record from large populations of neurons in prefrontal cortex of mice given the psychedelic drug TCB-2. Drug ingestion significantly stretched the distribution of log firing rates of the population of recorded neurons. This phenomenon was previously observed across transitions between sleep and wakefulness, which suggested that stretching of the log-rate distribution can be triggered by different kinds of brain state transitions and prompted us to examine it in more detail. We found that modulation of the width of the log-rate distribution of a neuronal population occurred in multiple areas of the cortex and in the hippocampus even in awake drug-free mice, driven by intrinsic fluctuations in their arousal level. Arousal, however, did not explain the stretching of the log-rate distribution by TCB-2. In both psychedelic and naturally occurring brain state transitions, the stretching or squeezing of the log-rate distribution of an entire neuronal population reflected concomitant changes in two subpopulations, with one subpopulation undergoing a downregulation and often also stretching of its neurons’ log-rate distribution, while the other subpopulation undergoes upregulation and often also a squeeze of its log-rate distribution. In both subpopulations, the stretching and squeezing were a signature of a greater relative impact of the brain state transition on the rates of the slow-firing neurons. These findings reveal a generic pattern of reorganisation of neuronal firing rates by different kinds of brain state transitions.

scholarly journals Firing rate homeostasis occurs in the absence of neuronal activity-regulated transcription

2019 ◽  
Author(s):  
Kelsey M. Tyssowski ◽  
Katherine C. Letai ◽  
Samuel D. Rendall ◽  
Anastasia Nizhnik ◽  
Jesse M. Gray
Keyword(s):  
Firing Rate ◽  
Neuronal Activity ◽  
Cortical Neurons ◽  
Molecular Mechanisms ◽  
Neuronal Circuits ◽  
Electrode Arrays ◽  
Knock Out ◽  
Firing Rates ◽  
The Face ◽  
Homeostatic Mechanisms

ABSTRACTDespite dynamic inputs, neuronal circuits maintain relatively stable firing rates over long periods. This maintenance of firing rate, or firing rate homeostasis, is likely mediated by homeostatic mechanisms such as synaptic scaling and regulation of intrinsic excitability. Because some of these homeostatic mechanisms depend on transcription of activity-regulated genes, including Arc and Homer1a, we hypothesized that activity-regulated transcription would be required for firing rate homeostasis. Surprisingly, however, we found that cultured mouse cortical neurons grown on multi-electrode arrays homeostatically adapt their firing rates to persistent pharmacological stimulation even when activity-regulated transcription is disrupted. Specifically, we observed firing rate homeostasis Arc knock-out neurons, as well as knock-out neurons lacking activity-regulated transcription factors, AP1 and SRF. Firing rate homeostasis also occurred normally during acute pharmacological blockade of transcription. Thus, firing rate homeostasis in response to increased neuronal activity can occur in the absence of neuronal-activity-regulated transcription.SIGNIFICANCE STATEMENTNeuronal circuits maintain relatively stable firing rates even in the face of dynamic circuit inputs. Understanding the molecular mechanisms that enable this firing rate homeostasis could potentially provide insight into neuronal diseases that present with an imbalance of excitation and inhibition. However, the molecular mechanisms underlying firing rate homeostasis are largely unknown.It has long been hypothesized that firing rate homeostasis relies upon neuronal activity-regulated transcription. For example, a 2012 review (PMID 22685679) proposed it, and a 2014 modeling approach established that transcription could theoretically both measure and control firing rate (PMID 24853940). Surprisingly, despite this prediction, we found that cortical neurons undergo firing rate homeostasis in the absence of activity-regulated transcription, indicating that firing rate homeostasis is controlled by non-transcriptional mechanisms.

scholarly journals The Effect of Correlated Variability on the Accuracy of a Population Code

1999 ◽  
Vol 11 (1) ◽  
pp. 91-101 ◽  
Author(s):  
L. F. Abbott ◽  
Peter Dayan
Keyword(s):  
Firing Rate ◽  
Neuronal Firing ◽  
Population Code ◽  
Firing Rates ◽  
Large Populations ◽  
Neuronal Firing Rate ◽  
General Limit ◽  
Widespread Belief ◽  
The Impact

We study the impact of correlated neuronal firing rate variability on the accuracy with which an encoded quantity can be extracted from a population of neurons. Contrary to widespread belief, correlations in the variabilities of neuronal firing rates do not, in general, limit the increase in coding accuracy provided by using large populations of encoding neurons. Furthermore, in some cases, but not all, correlations improve the accuracy of a population code.

scholarly journals Firing rate and pattern heterogeneity in the globus pallidus arise from a single neuronal population

2013 ◽  
Vol 109 (2) ◽  
pp. 497-506 ◽  
Author(s):  
Christopher A. Deister ◽  
Ramana Dodla ◽  
David Barraza ◽  
Hitoshi Kita ◽  
Charles J. Wilson
Keyword(s):  
Firing Rate ◽  
Globus Pallidus ◽  
Cell Types ◽  
Neuronal Population ◽  
Constant Current ◽  
Inhibitory Synapses ◽  
Projection Neurons ◽  
Distinct Cell Type

Intrinsic heterogeneity in networks of interconnected cells has profound effects on synchrony and spike-time reliability of network responses. Projection neurons of the globus pallidus (GPe) are interconnected by GABAergic inhibitory synapses and in vivo fire continuously but display significant rate and firing pattern heterogeneity. Despite being deprived of most of their synaptic inputs, GPe neurons in slices also fire continuously and vary greatly in their firing rate (1–70 spikes/s) and in regularity of their firing. We asked if this rate and pattern heterogeneity arises from separate cell types differing in rate, local synaptic interconnections, or variability of intrinsic properties. We recorded the resting discharge of GPe neurons using extracellular methods both in vivo and in vitro. Spike-to-spike variability (jitter) was measured as the standard deviation of interspike intervals. Firing rate and jitter covaried continuously, with slow firing being associated with higher variability than faster firing, as would be expected from heterogeneity arising from a single physiologically distinct cell type. The relationship between rate and jitter was unaffected by blockade of GABA and glutamate receptors. When the firing rate of individual neurons was altered with constant current, jitter changed to maintain the rate-jitter relationship seen across neurons. Long duration (30–60 min) recordings showed slow and spontaneous bidirectional drift in rate similar to the across-cell heterogeneity. Paired recordings in vivo and in vitro showed that individual cells wandered in rate independently of each other. Input conductance and rate wandered together, in a manner suggestive that both were due to fluctuations of an inward current.

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