scholarly journals Sleep regulation of the distribution of cortical firing rates

2016 ◽  
Author(s):  
Daniel Levenstein ◽  
Brendon O. Watson ◽  
John Rinzel ◽  
György Buzsáki
Keyword(s):  
Firing Rate ◽  
Neuronal Firing ◽  
Skewed Distribution ◽  
Slow Oscillation ◽  
Brain State ◽  
Neuronal System ◽  
Sleep Regulation ◽  
Firing Rates ◽  
Memory Traces ◽  
Intrinsic Firing

ABSTRACTSleep is thought to mediate mnemonic and homeostatic functions. However, the mechanism by which this brain state can implement both the “selective” plasticity needed to consolidate novel memory traces as well as the “general” plasticity necessary to maintain a well-functioning neuronal system is unclear. Recent findings show that both of these functions differentially affect neurons based on their intrinsic firing rate, a ubiquitous neuronal heterogeneity. Furthermore, they are both implemented by the NREM slow oscillation, which also distinguishes neurons based on firing rate during sequential activity at the DOWN->UP transition. These findings suggest a mechanism by which spiking activity during the slow oscillation acts to maintain network statistics that promote a skewed distribution of neuronal firing rates, and “perturbation” of that activity by hippocampal replay acts to integrate new memory traces into the existing cortical network.

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.

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 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 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 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.

scholarly journals Ion channel degeneracy enables robust and tunable neuronal firing rates

2015 ◽  
Vol 112 (38) ◽  
pp. E5361-E5370 ◽  
Author(s):  
Guillaume Drion ◽  
Timothy O’Leary ◽  
Eve Marder
Keyword(s):  
Ion Channel ◽  
Firing Rate ◽  
Ionic Currents ◽  
Neuronal Firing ◽  
Neuron Models ◽  
Firing Rates ◽  
Wide Range ◽  
Current Curve ◽  
Important Means ◽  
High Firing

Firing rate is an important means of encoding information in the nervous system. To reliably encode a wide range of signals, neurons need to achieve a broad range of firing frequencies and to move smoothly between low and high firing rates. This can be achieved with specific ionic currents, such as A-type potassium currents, which can linearize the frequency-input current curve. By applying recently developed mathematical tools to a number of biophysical neuron models, we show how currents that are classically thought to permit low firing rates can paradoxically cause a jump to a high minimum firing rate when expressed at higher levels. Consequently, achieving and maintaining a low firing rate is surprisingly difficult and fragile in a biological context. This difficulty can be overcome via interactions between multiple currents, implying a need for ion channel degeneracy in the tuning of neuronal properties.

scholarly journals Neuronal Firing Rates and Patterns in the Globus Pallidus Internus of Patients With Cervical Dystonia Differ From Those With Parkinson's Disease

2007 ◽  
Vol 98 (2) ◽  
pp. 720-729 ◽  
Author(s):  
Joyce K. H. Tang ◽  
Elena Moro ◽  
Neil Mahant ◽  
William D. Hutchison ◽  
Anthony E. Lang ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Firing Rate ◽  
Globus Pallidus ◽  
Cervical Dystonia ◽  
Neuronal Firing ◽  
Globus Pallidus Internus ◽  
Motor Symptoms ◽  
Firing Rates ◽  
Irregular Pattern

Cervical dystonia (CD) is a movement disorder that involves involuntary turning and twisting of the neck caused by abnormal muscle contraction. Deep brain stimulation (DBS) in the globus pallidus internus (GPi) is used to treat both CD and the motor symptoms of Parkinson's disease (PD). It has been suggested that the differing motor symptoms in CD and PD may arise from a decreased GPi output in CD and elevation of output in PD. To test this hypothesis, extracellular recordings of GPi neuronal activity were obtained during stereotactic surgery for the implantation of DBS electrodes in seven idiopathic CD and 14 PD patients. The mean GPi neuronal firing rate recorded from CD patients was lower than that in PD patients ( P < 0.001; means ± SE: 71.4 ± 2.2 and 91.7 ± 3.0 Hz, respectively). Furthermore, GPi neurons fired in a more irregular pattern consisting of more frequent and longer pauses in CD compared with PD patients. When comparisons were done based on locations of recordings, these differences in firing rates and patterns were limited to the ventral portion of the GPi. In contrast, no difference in firing rate or pattern was observed in the globus pallidus externus between the two groups. These findings suggest that alterations in both firing rate and firing pattern may underlie the differing motor symptoms associated with these two movement disorders.

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.

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