scholarly journals Network Amplification of Local Fluctuations Causes High Spike Rate Variability, Fractal Firing Patterns and Oscillatory Local Field Potentials

1994 ◽  
Vol 6 (5) ◽  
pp. 795-836 ◽  
Author(s):  
Marius Usher ◽  
Martin Stemmler ◽  
Christof Koch ◽  
Zeev Olami
Keyword(s):  
Power Spectrum ◽  
Local Field ◽  
Neural Activity ◽  
Cortical Neurons ◽  
Interspike Interval ◽  
Field Potential ◽  
External Source ◽  
Recurrent Network ◽  
Stochastic Input ◽  
Behaving Monkeys

We investigate a model for neural activity in a two-dimensional sheet of leaky integrate-and-fire neurons with feedback connectivity consisting of local excitation and surround inhibition. Each neuron receives stochastic input from an external source, independent in space and time. As recently suggested by Softky and Koch (1992, 1993), independent stochastic input alone cannot explain the high interspike interval variability exhibited by cortical neurons in behaving monkeys. We show that high variability can be obtained due to the amplification of correlated fluctuations in a recurrent network. Furthermore, the cross-correlation functions have a dual structure, with a sharp peak on top of a much broader hill. This is due to the inhibitory and excitatory feedback connections, which cause “hotspots” of neural activity to form within the network. These localized patterns of excitation appear as clusters or stripes that coalesce, disintegrate, or fluctuate in size while simultaneously moving in a random walk constrained by the interaction with other clusters. The synaptic current impinging upon a single neuron shows large fluctuations at many time scales, leading to a large coefficient of variation (CV) for the interspike interval statistics. The power spectrum associated with single units shows a 1/f decay for small frequencies and is flat at higher frequencies, while the power spectrum of the spiking activity averaged over many cells—equivalent to the local field potential—shows no 1/f decay but a prominent peak around 40 Hz, in agreement with data recorded from cat and monkey cortex (Gray et al. 1990; Eckhorn et al. 1993). Firing rates exhibit self-similarity between 20 and 800 msec, resulting in 1/f-like noise, consistent with the fractal nature of neural spike trains (Teich 1992).

scholarly journals Chronic Stability of Single-Channel Neurophysiological Correlates of Gross and Fine Reaching Movements in the Rat

2019 ◽  
Author(s):  
David T. Bundy ◽  
David J Guggenmos ◽  
Maxwell D Murphy ◽  
Randolph J. Nudo
Keyword(s):  
Motor Cortex ◽  
Local Field ◽  
Neural Activity ◽  
Local Field Potential ◽  
Primary Motor Cortex ◽  
Spectral Power ◽  
Premotor Cortex ◽  
Field Potential ◽  
Motor Recovery ◽  
Reaching Movements

AbstractFollowing injury to motor cortex, reorganization occurs throughout spared brain regions and is thought to underlie motor recovery. Unfortunately, the standard neurophysiological and neuroanatomical measures of post-lesion plasticity are only indirectly related to observed changes in motor execution. While substantial task-related neural activity has been observed during motor tasks in rodent primary motor cortex and premotor cortex, the long-term stability of these responses in healthy rats is uncertain, limiting the interpretability of longitudinal changes in the specific patterns of neural activity during motor recovery following injury. This study examined the stability of task-related neural activity associated with execution of reaching movements in healthy rodents. Rats were trained to perform a novel reaching task combining a ‘gross’ lever press and a ‘fine’ pellet retrieval. In each animal, two chronic microelectrode arrays were implanted in motor cortex spanning the caudal forelimb area (rodent primary motor cortex) and the rostral forelimb area (rodent premotor cortex). We recorded multiunit spiking and local field potential activity from 10 days to 7-10 weeks post-implantation to characterize the patterns of neural activity observed during each task component and analyzed the consistency of channel-specific task-related neural activity. Task-related changes in neural activity were observed on the majority of channels. While the task-related changes in multi-unit spiking and local field potential spectral power were consistent over several weeks, spectral power changes were more stable, despite the trade-off of decreased spatial and temporal resolution. These results show that rodent primary and premotor cortex are both involved in reaching movements with stable patterns of task-related activity across time, establishing the relevance of the rodent for future studies designed to examine changes in task-related neural activity during recovery from focal cortical lesions.

scholarly journals Large- and multi-scale networks in the rodent brain during novelty exploration

2020 ◽  
Author(s):  
Michael X Cohen ◽  
Bernhard Englitz ◽  
Arthur S C França
Keyword(s):  
Prefrontal Cortex ◽  
Parietal Cortex ◽  
Local Field ◽  
Neural Activity ◽  
Large Scale ◽  
Field Potential ◽  
Brain Regions ◽  
Data Availability ◽  
Data Matrix ◽  
Temporal Scales

AbstractNeural activity is coordinated across multiple spatial and temporal scales, and these patterns of coordination are implicated in both healthy and impaired cognitive operations. However, empirical cross-scale investigations are relatively infrequent, due to limited data availability and to the difficulty of analyzing rich multivariate datasets. Here we applied frequency-resolved multivariate source-separation analyses to characterize a large-scale dataset comprising spiking and local field potential activity recorded simultaneously in three brain regions (prefrontal cortex, parietal cortex, hippocampus) in freely-moving mice. We identified a constellation of multidimensional, inter-regional networks across a range of frequencies (2-200 Hz). These networks were reproducible within animals across different recording sessions, but varied across different animals, suggesting individual variability in network architecture. The theta band (~4-10 Hz) networks had several prominent features, including roughly equal contribution from all regions and strong inter-network synchronization. Overall, these findings demonstrate a multidimensional landscape of large-scale functional activations of cortical networks operating across multiple spatial, spectral, and temporal scales during open-field exploration.Significance statementNeural activity is synchronized over space, time, and frequency. To characterize the dynamics of large-scale networks spanning multiple brain regions, we recorded data from the prefrontal cortex, parietal cortex, and hippocampus in awake behaving mice, and pooled data from spiking activity and local field potentials into one data matrix. Frequency-specific multivariate decomposition methods revealed a cornucopia of neural networks defined by coherent spatiotemporal patterns over time. These findings reveal a rich, dynamic, and multivariate landscape of large-scale neural activity patterns during foraging behavior.

Ultrasonic thalamic stimulation modulates neural activity of thalamus and motor cortex in the mouse

2021 ◽  
Author(s):  
Xingran Wang ◽  
Jiaqing Yan ◽  
Huiran Zhang ◽  
Yi Yuan
Keyword(s):  
Motor Cortex ◽  
Power Spectrum ◽  
Neural Activity ◽  
Field Potential ◽  
Strong Connection ◽  
Coupling Relationship ◽  
Thalamic Stimulation ◽  
Neural Activities ◽  
Relationship Of ◽  
Local Field Potential Lfp

Abstract Objective. Previous studies have demonstrated that ultrasound thalamic stimulation (UTS) can treat disorders of consciousness. However, it is still unclear how UTS modulates neural activity in the thalamus and cortex. Approach. In this study, we performed UTS in mice and recorded the neural activities including spike and local field potential (LFP) of the thalamus and motor cortex. We analyzed the firing rate of spikes and the power spectrum of LFPs and evaluated the coupling relationship between LFPs from the thalamus and motor cortex with Granger causality. Main results. Our results clearly indicate that UTS can directly induce neural activity in the thalamus and indirectly induce neural activity in the motor cortex. We also found that there is a strong connection relationship of neural activity between thalamus and motor cortex under UTS. Significance. These results demonstrate that UTS can modulate the neural activity of the thalamus and motor cortex in mice. It has the potential to provide guidance for the ultrasound treatment of thalamus-related diseases.

Population encoding of spatial frequency, orientation, and color in macaque V1

1994 ◽  
Vol 72 (5) ◽  
pp. 2151-2166 ◽  
Author(s):  
J. D. Victor ◽  
K. Purpura ◽  
E. Katz ◽  
B. Mao
Keyword(s):  
Spatial Frequency ◽  
Local Field ◽  
Neural Activity ◽  
Local Field Potential ◽  
Field Potential ◽  
Orientation Tuning ◽  
Information Rate ◽  
Response Dynamics ◽  
Spatial Tuning ◽  
Band Limited

1. We recorded local field potentials in the parafoveal representation in the primary visual cortex of anesthetized and paralyzed macaque monkeys with a multicontact electrode that provided for sampling of neural activity at 16 sites along a vertical penetration. Differential recordings at adjacent contacts were transformed into an estimate of current source density (CSD), to provide a measure of local neural activity. 2. We used m-sequence stimuli to map the region of visual space that provided input to the recording site. The local field potential recorded in macaque V1 has a population receptive field (PRF) size of approximately 2 deg2. 3. We assessed spatial tuning by the responses to two-dimensional Gaussian noise, spatially filtered to retain power only within one octave. Responses to achromatic band-limited noise stimuli revealed a prominent band-pass spatial tuning in the upper layers, but a more low-pass spatial tuning in lower layers. 4. We assessed orientation tuning by the responses to band-limited noise whose spectrum was further restricted to lie within 45 degrees wedges. The local field potential showed evidence of orientation tuning at most sites. Orientation tuning in upper and lower layers was manifest by systematic variations not only in response size but also in response dynamics. 5. We assessed chromatic tuning by the responses to isotropic band-limited noise modulated in a variety of directions in tristimulus space. Some lower-layer locations showed a nulling of response under near-isoluminant conditions. However, response dynamics in upper and lower layers depended not only on luminance contrast, but also on chromatic inputs. 6. Responses to near-isoluminant stimuli and to low-contrast luminance modulation were shifted to lower spatial frequencies. 7. We determined the extent to which various temporal frequencies in the response conveyed information concerning spatial frequency, orientation, and color under the steady-state conditions used in these studies. In each case, information is distributed in the response dynamics across a broad temporal frequency range, beginning at 4 Hz (the lowest frequency used). For spatial frequency the information rate remains significant up to at least 25 Hz. For orientation tuning and chromatic tuning, the information rate is lower overall and remains significant up to 13 Hz. In contrast, for texture discrimination, information is shifted to lower temporal frequencies.

scholarly journals Visual cortex neurons phase-lock selectively to subsets of LFP oscillations

2019 ◽  
Vol 121 (6) ◽  
pp. 2364-2378 ◽  
Author(s):  
N. V. Swindale ◽  
M. A. Spacek
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Local Field ◽  
Rem Sleep ◽  
Local Field Potential ◽  
Cortical Neurons ◽  
Field Potential ◽  
Frequency Selective ◽  
Visual Cortex Neurons ◽  
Local Field Potential Lfp

It is generally thought that apart from receptive field differences, such as preferred orientation and spatial frequency selectivity, primary visual cortex neurons are functionally similar to each other. However, the genetic diversity of cortical neurons plus the existence of inputs additional to those required to explain known receptive field properties might suggest otherwise. Here we report the existence of desynchronized states in anesthetized cat area 17 lasting up to 45 min, characterized by variable narrow-band local field potential (LFP) oscillations in the range 2–100 Hz and the absence of a synchronized 1/ f frequency spectrum. During these periods, spontaneously active neurons phase-locked to variable subsets of LFP oscillations. Individual neurons often ignored frequencies that others phase-locked to. We suggest that these desynchronized periods may correspond to REM sleep-like episodes occurring under anesthesia. Frequency-selective codes may be used for signaling during these periods. Hence frequency-selective combination and frequency-labeled pathways may represent a previously unsuspected dimension of cortical organization. NEW & NOTEWORTHY We investigated spontaneous neuronal firing during periods of desynchronized local field potential (LFP) activity, resembling REM sleep, in anesthetized cats. During these periods, neurons synchronized their spikes to specific phases of multiple LFP frequency components, with some neurons ignoring frequencies that others were synchronized to. Some neurons fired at phase alignments of frequency pairs, thereby acting as phase coincidence detectors. These results suggest that internal brain signaling may use frequency combination codes to generate temporally structured spike trains.

scholarly journals Random recurrent networks near criticality capture the broadband power distribution of human ECoG dynamics

2016 ◽  
Author(s):  
Rishidev Chaudhuri ◽  
Biyu He ◽  
Xiao-Jing Wang
Keyword(s):  
Power Spectrum ◽  
Power Distribution ◽  
Random Network ◽  
Field Potential ◽  
Power Spectra ◽  
Low Frequency ◽  
Recurrent Network ◽  
Network Activity ◽  
Brain Diseases ◽  
Low Frequency Power

The power spectrum of brain electric field potential recordings is dominated by an arrhythmic broadband signal but a mechanistic account of its underlying neural network dynamics is lacking. Here we show how the broadband power spectrum of field potential recordings can be explained by a simple random network of nodes near criticality. Such a recurrent network produces activity with a combination of a fast and a slow autocorrelation time constant, with the fast mode corresponding to local dynamics and the slow mode resulting from recurrent excitatory connections across the network. These modes are combined to produce a power spectrum similar to that observed in human intracranial EEG (i.e., electrocorticography, ECoG) recordings. Moreover, such a network naturally converts input correlations across nodes into temporal autocorrelation of the network activity. Consequently, increased independence between nodes results in a reduction in low-frequency power, which offers a possible explanation for observed changes in ECoG power spectra during task performance. Lastly, changes in network coupling produce changes in network activity power spectra reminiscent of those seen in human ECoG recordings across different arousal states. This model thus links macroscopic features of the empirical ECoG power spectrum to a parsimonious underlying network structure and proposes potential mechanisms for changes in ECoG power spectra observed across behavioral and arousal states. This provides a computational framework within which to generate and test hypotheses about the cellular and network mechanisms underlying whole brain electrical dynamics, their variations across behavioral states as well as abnormalities associated with brain diseases.

scholarly journals Establishing an Animal Model of Single-Sided Deafness in Chinchilla lanigera

2019 ◽  
Vol 161 (6) ◽  
pp. 1004-1011
Author(s):  
Renee M. Banakis Hartl ◽  
Nathaniel T. Greene ◽  
Victor Benichoux ◽  
Anna Dondzillo ◽  
Andrew D. Brown ◽  
...  
Keyword(s):  
Animal Model ◽  
Inferior Colliculus ◽  
Local Field ◽  
Neural Activity ◽  
Local Field Potential ◽  
Preliminary Investigation ◽  
Field Potential ◽  
Normal Hearing ◽  
Auditory Brainstem Responses ◽  
Single Sided Deafness

Objectives (1) To characterize changes in brainstem neural activity following unilateral deafening in an animal model. (2) To compare brainstem neural activity from unilaterally deafened animals with that of normal-hearing controls. Study Design Prospective controlled animal study. Setting Vivarium and animal research facilities. Subjects and Methods The effect of single-sided deafness on brainstem activity was studied in Chinchilla lanigera. Animals were unilaterally deafened via gentamycin injection into the middle ear, which was verified by loss of auditory brainstem responses (ABRs). Animals underwent measurement of ABR and local field potential in the inferior colliculus. Results Four animals underwent chemical deafening, with 2 normal-hearing animals as controls. ABRs confirmed unilateral loss of auditory function. Deafened animals demonstrated symmetric local field potential responses that were distinctly different than the contralaterally dominated responses of the inferior colliculus seen in normal-hearing animals. Conclusion We successfully developed a model for unilateral deafness to investigate effects of single-sided deafness on brainstem plasticity. This preliminary investigation serves as a foundation for more comprehensive studies that will include cochlear implantation and manipulation of binaural cues, as well as functional behavioral tests.

scholarly journals LFP clustering in cortex reveals a taxonomy of Up states and near-millisecond, ordered phase-locking in cortical neurons

2019 ◽  
Vol 122 (4) ◽  
pp. 1794-1809
Author(s):  
Catalin C. Mitelut ◽  
Martin A. Spacek ◽  
Allen W. Chan ◽  
Tim H. Murphy ◽  
Nicholas V. Swindale
Keyword(s):  
Local Field ◽  
Local Field Potential ◽  
Cortical Neurons ◽  
State Transition ◽  
Slow Wave Sleep ◽  
Field Potential ◽  
State Transitions ◽  
Wide Field ◽  
Cortical Function ◽  
Up States

During slow-wave sleep and anesthesia, mammalian cortex exhibits a synchronized state during which neurons shift from a largely nonfiring to a firing state, known as an Up-state transition. Up-state transitions may constitute the default activity pattern of the entire cortex (Neske GT. Front Neural Circuits 9: 88, 2016) and could be critical to understanding cortical function, yet the genesis of such transitions and their interaction with single neurons is not well understood. It was recently shown that neurons firing at rates >2 Hz fire spikes in a stereotyped order during Up-state transitions (Luczak A, McNaughton BL, Harris KD. Nat Rev Neurosci 16: 745–755, 2015), yet it is still unknown if Up states are homogeneous and whether spiking order is present in neurons with rates <2 Hz (the majority). Using extracellular recordings from anesthetized cats and mice and from naturally sleeping rats, we show for the first time that Up-state transitions can be classified into several types based on the shape of the local field potential (LFP) during each transition. Individual LFP events could be localized in time to within 1–4 ms, more than an order of magnitude less than in previous studies. The majority of recorded neurons synchronized their firing to within ±5–15 ms relative to each Up-state transition. Simultaneous electrophysiology and wide-field imaging in mouse confirmed that LFP event clusters are cortex-wide phenomena. Our findings show that Up states are of different types and point to the potential importance of temporal order and millisecond-scale signaling by cortical neurons. NEW & NOTEWORTHY During cortical Up-state transitions in sleep and anesthesia, neurons undergo brief periods of increased firing in an order similar to that occurring in awake states. We show that these transitions can be classified into distinct types based on the shape of the local field potential. Transition times can be defined to <5 ms. Most neurons synchronize their firing to within ±5–15 ms of the transitions and fire in a consistent order.

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