scholarly journals Single neuron firing cascades underlie global spontaneous brain events

2021 ◽  
Author(s):  
Xiao Liu ◽  
David A. Leopold ◽  
Yifan Yang

AbstractThe resting brain consumes enormous energy and shows highly organized spontaneous activity. To investigate how this activity is manifest among single neurons, we analyzed spiking discharges of ∼10,000 isolated cells recorded from multiple cortical and subcortical regions of the mouse brain during immobile rest. We found that firing of a significant proportion (∼70%) of neurons conformed to a ubiquitous, temporally sequenced cascade of spiking that was synchronized with global events and elapsed over timescales of 5-10 seconds. Across the brain, two intermixed populations of neurons supported orthogonal cascades. The relative phases of these cascades determined, at each moment, the response magnitude evoked by an external visual stimulus. Furthermore, the spiking of individual neurons embedded in these cascades was time locked to physiological indicators of arousal, including local field potential (LFP) power, pupil diameter, and hippocampal ripples. These findings demonstrate that the large-scale coordination of low-frequency spontaneous activity, which is commonly observed in brain imaging and linked to arousal, sensory processing, and memory, is underpinned by sequential, large-scale temporal cascades of neuronal spiking across the brain.

2021 ◽  
Vol 118 (47) ◽  
pp. e2105395118
Author(s):  
Xiao Liu ◽  
David A. Leopold ◽  
Yifan Yang

The resting brain consumes enormous energy and shows highly organized spontaneous activity. To investigate how this activity is manifest among single neurons, we analyzed spiking discharges of ∼10,000 isolated cells recorded from multiple cortical and subcortical regions of the mouse brain during immobile rest. We found that firing of a significant proportion (∼70%) of neurons conformed to a ubiquitous, temporally sequenced cascade of spiking that was synchronized with global events and elapsed over timescales of 5 to 10 s. Across the brain, two intermixed populations of neurons supported orthogonal cascades. The relative phases of these cascades determined, at each moment, the response magnitude evoked by an external visual stimulus. Furthermore, the spiking of individual neurons embedded in these cascades was time locked to physiological indicators of arousal, including local field potential power, pupil diameter, and hippocampal ripples. These findings demonstrate that the large-scale coordination of low-frequency spontaneous activity, which is commonly observed in brain imaging and linked to arousal, sensory processing, and memory, is underpinned by sequential, large-scale temporal cascades of neuronal spiking across the brain.


2018 ◽  
Author(s):  
Meyer Gabriel ◽  
Caponcy Julien ◽  
Paul A. Salin ◽  
Comte Jean-Christophe

AbstractLocal field potential (LFP) recording is a very useful electrophysiological method to study brain processes. However, this method is criticized for recording low frequency activity in a large area of extracellular space potentially contaminated by distal activity. Here, we theoretically and experimentally compare ground-referenced (RR) with differential recordings (DR). We analyze electrical activity in the rat cortex with these two methods. Compared with RR, DR reveals the importance of local phasic oscillatory activities and their coherence between cortical areas. Finally, we show that DR provides a more faithful assessment of functional connectivity caused by an increase in the signal to noise ratio, and of the delay in the propagation of information between two cortical structures.


2002 ◽  
Vol 87 (4) ◽  
pp. 2137-2148 ◽  
Author(s):  
Sean M. O'Connor ◽  
Rune W. Berg ◽  
David Kleinfeld

We tested if coherent signaling between the sensory vibrissa areas of cerebellum and neocortex in rats was enhanced as they whisked in air. Whisking was accompanied by 5- to 15-Hz oscillations in the mystatial electromyogram, a measure of vibrissa position, and by 5- to 20-Hz oscillations in the differentially recorded local field potential (∇LFP) within the vibrissa area of cerebellum and within the ∇LFP of primary sensory cortex. We observed that only 10% of the activity in either cerebellum or sensory neocortex was significantly phase-locked to rhythmic motion of the vibrissae; the extent of this modulation is in agreement with the results from previous single-unit measurements in sensory neocortex. In addition, we found that 40% of the activity in the vibrissa areas of cerebellum and neocortex was significantly coherent during periods of whisking. The relatively high level of coherence between these two brain areas, in comparison with their relatively low coherence with whisking per se, implies that the vibrissa areas of cerebellum and neocortex communicate in a manner that is incommensurate with whisking. To the extent that the vibrissa areas of cerebellum and neocortex communicate over the same frequency band as that used by whisking, these areas must multiplex electrical activity that is internal to the brain with activity that is that phase-locked to vibrissa sensory input.


2017 ◽  
Author(s):  
Anika Gupta ◽  
Heiko Horn ◽  
Parisa Razaz ◽  
April Kim ◽  
Michael Lawrence ◽  
...  

ABSTRACTLarge-scale cancer sequencing studies have uncovered dozens of mutations critical to cancer initiation and progression. However, a significant proportion of genes linked to tumor propagation remain hidden, often due to noise in sequencing data confounding low frequency alterations. Further, genes in networks under purifying selection (NPS), or those that are mutated in cancers less frequently than would be expected by chance, may play crucial roles in sustaining cancers but have largely been overlooked. We describe here a statistical framework that identifies genes that have a first order protein interaction network significantly depleted for mutations, to elucidate key genetic contributors to cancers. Not reliant on and thus, unbiased by, the gene of interest’s mutation rate, our approach has identified 685 putative genes linked to cancer development. Comparative analysis indicates statistically significant enrichment of NPS genes in previously validated cancer vulnerability gene sets, while further identifying novel cancer-specific candidate gene targets. As more tumor genomes are sequenced, integrating systems level mutation data through this network approach should become increasingly useful in pinpointing gene targets for cancer diagnosis and treatment.


2014 ◽  
Vol 112 (4) ◽  
pp. 741-751 ◽  
Author(s):  
Ramanujan Srinath ◽  
Supratim Ray

Neural activity across the brain shows both spatial and temporal correlations at multiple scales, and understanding these correlations is a key step toward understanding cortical processing. Correlation in the local field potential (LFP) recorded from two brain areas is often characterized by computing the coherence, which is generally taken to reflect the degree of phase consistency across trials between two sites. Coherence, however, depends on two factors—phase consistency as well as amplitude covariation across trials—but the spatial structure of amplitude correlations across sites and its contribution to coherence are not well characterized. We recorded LFP from an array of microelectrodes chronically implanted in the primary visual cortex of monkeys and studied correlations in amplitude across electrodes as a function of interelectrode distance. We found that amplitude correlations showed a similar trend as coherence as a function of frequency and interelectrode distance. Importantly, even when phases were completely randomized between two electrodes, amplitude correlations introduced significant coherence. To quantify the contributions of phase consistency and amplitude correlations to coherence, we simulated pairs of sinusoids with varying phase consistency and amplitude correlations. These simulations confirmed that amplitude correlations can significantly bias coherence measurements, resulting in either over- or underestimation of true phase coherence. Our results highlight the importance of accounting for the correlations in amplitude while using coherence to study phase relationships across sites and frequencies.


Author(s):  
Sean Reed ◽  
Sonia Jego ◽  
Antoine Adamantidis

This chapter discusses the history, practice, and application of electroencephalography (EEG) and local field potential (LFP) recordings, with a particular focus on animal models. EEG measures the fluctuations of electrical activity resulting from ionic currents in the brain. These measurements are often taken from electrodes placed on the surface of the scalp, or in animal models, directly on the skull. LFP recordings are more invasive, measuring electrical current from all nearby dendritic synaptic activity within a volume of tissue. These two techniques are useful in determining how neural activity can synchronize during different behavioral or motivational states.


2011 ◽  
Vol 32 (2) ◽  
pp. 306-317 ◽  
Author(s):  
Marta Gómez-Galán ◽  
Julia Makarova ◽  
Irene Llorente-Folch ◽  
Takeyori Saheki ◽  
Beatriz Pardo ◽  
...  

The deficiency in the mitochondrial aspartate/glutamate transporter Aralar/AGC1 results in a loss of the malate-aspartate NADH shuttle in the brain neurons, hypomyelination, and additional defects in the brain metabolism. We studied the development of cortico/hippocampal local field potential (LFP) in Aralar/AGC1 knockout (KO) mice. Laminar profiles of LFP, evoked potentials, and unit activity were recorded under anesthesia in young (P15 to P22) Aralar-KO and control mice as well as control adults. While LFP power increased 3 to 7 times in both cortex and hippocampus of control animals during P15 to P22, the Aralar-KO specimens hardly progressed. The divergence was more pronounced in the CA3/hilus region. In parallel, spontaneous multiunit activity declined severely in KO mice. Postnatal growth of hippocampal-evoked potentials was delayed in KO mice, and indicated abnormal synaptic and spike electrogenesis and reduced output at P20 to P22. The lack of LFP development in KO mice was accompanied by the gradual appearance of epileptic activity in the CA3/hilus region that evolved to status epilepticus. Strikingly, CA3 bursts were poorly conducted to the CA1 field. We conclude that disturbed substrate supply to neuronal mitochondria impairs development of cortico—hippocampal LFPs. Aberrant neuronal electrogenesis and reduced neuron output may explain circuit dysfunction and phenotype deficiencies.


2020 ◽  
Author(s):  
Zhang Yu ◽  
Ping Chen ◽  
Zhi-yi Tu ◽  
Yi-heng Liu ◽  
Zhi-ru Wang ◽  
...  

Abstract In this study, in vitro intact hippocampal preparation model was utilized to observe the effects of propofol and ketamine on the neural oscillations in CA1 of rat hippocampus. The intact hippocampi were dissected from the brain tissues of rats aged 14-16 days postnatal. Local field potential (LFP) recordings were performed with propofol and ketamine bath application at different concentrations. The power spectrum intensity of LFP in all the frequency bands, including delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz) and gamma (30-80 Hz), were inhibited in a concentrationdependent manner by both general anesthetics. In order to further investigate the underlying mechanisms, the major binding site of propofol and ketamine were blocked respectively by picrotoxin and (2R)-amino-5-phosphonopentanoate when bath applying the general anesthetics. It revealed that the inhibitory effect of propofol on hippocampal oscillations might be via γ-aminobutyric acid A receptor, while the inhibitory effect of ketamine might be unconcerned with N-methyl-D-aspartic acid receptor.


2018 ◽  
Author(s):  
Y. Zhou ◽  
A. Sheremet ◽  
Y. Qin ◽  
J.P. Kennedy ◽  
N.M. DiCola ◽  
...  

ABSTRACTLocal field potential (LFP) oscillations are the superposition of excitatory/inhibitory postsynaptic potentials. In the hippocampus, the 20-55 Hz range (‘slow gamma’) is proposed to support cognition independent of other frequencies. However, this band overlaps with theta harmonics. We aimed to dissociate the generators of slow gamma versus theta harmonics with current source density and different LFP decompositions. Hippocampal theta harmonic and slow gamma generators were not dissociable. Moreover, comparison of wavelet, ensemble empirical-mode (EEMD), and Fourier decompositions produced distinct outcomes with wavelet and EEMD failing to resolve high-order theta harmonics well defined by Fourier analysis. The varying sizes of the time-frequency atoms used by wavelet distributed the higher-order harmonics over a broader range giving the impression of a low frequency burst (“slow gamma”). The absence of detectable slow gamma refutes a multiplexed model of cognition in favor of the energy cascade hypothesis in which dependency across oscillatory frequencies exists.


2021 ◽  
Vol 15 ◽  
Author(s):  
Shuihan Qiu ◽  
Kaijia Sun ◽  
Zengru Di

The collective electrophysiological dynamics of the brain as a result of sleep-related biological drives in Drosophila are investigated in this paper. Based on the Huber-Braun thermoreceptor model, the conductance-based neurons model is extended to a coupled neural network to analyze the local field potential (LFP). The LFP is calculated by using two different metrics: the mean value and the distance-dependent LFP. The distribution of neurons around the electrodes is assumed to have a circular or grid distribution on a two-dimensional plane. Regardless of which method is used, qualitatively similar results are obtained that are roughly consistent with the experimental data. During wake, the LFP has an irregular or a regular spike. However, the LFP becomes regular bursting during sleep. To further analyze the results, wavelet analysis and raster plots are used to examine how the LFP frequencies changed. The synchronization of neurons under different network structures is also studied. The results demonstrate that there are obvious oscillations at approximately 8 Hz during sleep that are absent during wake. Different time series of the LFP can be obtained under different network structures and the density of the network will also affect the magnitude of the potential. As the number of coupled neurons increases, the neural network becomes easier to synchronize, but the sleep and wake time described by the LFP spectrogram do not change. Moreover, the parameters that affect the durations of sleep and wake are analyzed.


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