scholarly journals An Interneuron Circuit Reproducing Essential Spectral Features of Field Potentials

2018 ◽  
Vol 30 (5) ◽  
pp. 1296-1322 ◽  
Author(s):  
Reinoud Maex
Keyword(s):  
Computational Study ◽  
Electrical Coupling ◽  
Field Potential ◽  
Low Frequency ◽  
Reciprocal Inhibition ◽  
Mammalian Brain ◽  
Power Scaling ◽  
Field Potentials ◽  
Neuronal Synchrony ◽  
Α Rhythm

Recent advances in engineering and signal processing have renewed the interest in invasive and surface brain recordings, yet many features of cortical field potentials remain incompletely understood. In the computational study that follows, we show that a model circuit of interneurons, coupled via both GABAA receptor synapses and electrical synapses, reproduces many essential features of the power spectrum of local field potential (LFP) recordings, such as 1/ f power scaling at low frequency (below 10 Hz), power accumulation in the γ-frequency band (30–100 Hz), and a robust α rhythm in the absence of stimulation. The low-frequency 1/ f power scaling depends on strong reciprocal inhibition, whereas the α rhythm is generated by electrical coupling of intrinsically active neurons. As in previous studies, the γ power arises through the amplification of single-neuron spectral properties, owing to the refractory period, by parameters that favor neuronal synchrony, such as delayed inhibition. This study also confirms that both synaptic and voltage-gated membrane currents contribute substantially to the LFP and that high-frequency signals such as action potentials quickly taper off with distance. Given the ubiquity of electrically coupled interneuron circuits in the mammalian brain, they may be major determinants of the recorded potentials.

scholarly journals Computational study of synchrony in fields and microclusters of ephaptically coupled neurons

2015 ◽  
Vol 113 (9) ◽  
pp. 3229-3241 ◽  
Author(s):  
R. Greg Stacey ◽  
Lennart Hilbert ◽  
Thomas Quail
Keyword(s):  
Electric Fields ◽  
Computational Study ◽  
Extracellular Volume ◽  
Low Frequency ◽  
Spike Timing ◽  
Single Action ◽  
Neuronal Synchrony ◽  
Single Spike ◽  
Ephaptic Coupling

Neuronal hypersynchrony is implicated in epilepsy and other diseases. The low-frequency, spatially averaged electric fields from many thousands of neurons have been shown to promote synchrony. It remains unclear whether highly transient, spatially localized electric fields from single action potentials (ephaptic coupling) significantly affect spike timing of neighboring cells and in consequence, population synchrony. In this study, we simulated the extracellular potentials and the resulting coupling between neurons in the NEURON environment and generalized their connection rules to create an oscillator network model of a sheet of ephaptically coupled neurons. With the use of both models, we explained several aspects of epileptiform behavior not previously modeled by synaptically coupled networks. Importantly, reduction of neuron spacing induced synchronization via single-spike ephaptic coupling, agreeing with seizure suppression seen clinically and in vitro via extracellular volume adjustment. Further reduction of neuron spacing yielded locally synchronized clusters, providing a mechanism for recent in vitro observations of localized neuronal synchrony in the absence of synaptic and gap-junction coupling.

scholarly journals Spine-shaped gold protrusions improve the adherence and electrical coupling of neurons with the surface of micro-electronic devices

2009 ◽  
Vol 6 (41) ◽  
pp. 1153-1165 ◽  
Author(s):  
Aviad Hai ◽  
Ada Dormann ◽  
Joseph Shappir ◽  
Shlomo Yitzchaik ◽  
Carmen Bartic ◽  
...  
Keyword(s):  
Action Potentials ◽  
Signal To Noise Ratio ◽  
Electronic Devices ◽  
Electrical Coupling ◽  
Field Potential ◽  
Fundamental Property ◽  
Microscopic Analysis ◽  
Field Potentials ◽  
Electron Microscopic ◽  
Micro Structures

Interfacing neurons with micro- and nano-electronic devices has been a subject of intense study over the last decade. One of the major problems in assembling efficient neuro-electronic hybrid systems is the weak electrical coupling between the components. This is mainly attributed to the fundamental property of living cells to form and maintain an extracellular cleft between the plasma membrane and any substrate to which they adhere. This cleft shunts the current generated by propagating action potentials and thus reduces the signal-to-noise ratio. Reducing the cleft thickness, and thereby increasing the seal resistance formed between the neurons and the sensing surface, is thus a challenge and could improve the electrical coupling coefficient. Using electron microscopic analysis and field potential recordings, we examined here the use of gold micro-structures that mimic dendritic spines in their shape and dimensions to improve the adhesion and electrical coupling between neurons and micro-electronic devices. We found that neurons cultured on a gold-spine matrix, functionalized by a cysteine-terminated peptide with a number of RGD repeats, readily engulf the spines, forming tight apposition. The recorded field potentials of cultured Aplysia neurons are significantly larger using gold-spine electrodes in comparison with flat electrodes.

scholarly journals Lateral phase differences in a population model of the visual cortex are sufficient for the development of rhythmic spatial sampling

2020 ◽  
Author(s):  
Justin D. Yi ◽  
Katsushi Arisaka
Keyword(s):  
Visual Cortex ◽  
Spatial Attention ◽  
Phase Difference ◽  
Computational Study ◽  
Field Potential ◽  
Low Frequency ◽  
Probability Of Detection ◽  
Population Activity ◽  
Attention Task ◽  
Phase Differences

AbstractWhen attending to many spatially distributed visual stimuli, attention is reweighted rhythmically at 4-8 Hz. The probability of detection depends on the phase at which a stimulus is deployed relative to this intrinsic rhythm. The reweighting oscillations can be observed both electrophysiologically and behaviorally, and appear to be regulated by the pulvinar. Based on these findings, we considered the computational consequences of allowing feedback to shape the distribution of inhibitory oscillations from the thalamus, as measured by a local field potential (LFP) phases in the 8 Hz low alpha-band, across laterally-connected regions of the visual cortex. We constructed a population activity model with lateral and feedforward connections. In agreement with prior models, we found that the sign of the lateral phase difference in the inhibitory low-frequency oscillations regulated the direction of communication between the laterally-connected regions. Furthermore, the phase difference induced periodicity in the dynamics of a downstream winner-takes-all attractor network such that periodic switching between states was observed. We finally simulated a simple spatial attention task. We found rhythmic 8 Hz sampling between two regions when a lateral phase difference was present—an effect that disappeared when the lateral phase difference was zero. These findings are in agreement with spatial attention literature and suggest that lateral phase differences are essential for manifesting communicational asymmetries in laterally-connected visual cortices. Our model predicts that population-specific phase differences are critical for sampling the spatial extent of stimuli.Author summaryWe conducted a computational study of the effects of lateral phase differences in a simulated model of the visual cortex. Lateral phase differences are defined to be when the phase of an intrinsic low-frequency inhibitory oscillation varies consistently across populations in the same cortical area. For example, our model was intended to capture the dynamics of a retinotopic cortex where feedback from the frotoparietal areas via the pulvinar nucleus assigned laterally-connected regions of the visual cortex different phases. We found that the sign of the phase differences influenced the direction of lateral communication. Furthermore, the phase differences introduced rhythmicity in the downstream areas, thus allowing us to simulate rhythmic spatial selection of stimuli. Prior to the current study, the influence of inter-areal phase differences in feedforward models had been well characterized. Our model provides new insights into the dynamics of population-specific lateral phase differences and predicts that the development of phase differences across the visual cortex are critical for the allocation of attention in space.

scholarly journals A Simulation on Relation between Power Distribution of Low-Frequency Field Potentials and Conducting Direction of Rhythm Generator Flowing through 3D Asymmetrical Brain Tissue

Symmetry ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 900
Author(s):  
Hao Cheng ◽  
Manling Ge ◽  
Abdelkader Nasreddine Belkacem ◽  
Xiaoxuan Fu ◽  
Chong Xie ◽  
...  
Keyword(s):  
Brain Tissue ◽  
Power Distribution ◽  
Low Frequency ◽  
Field Potentials ◽  
Spatial Spread ◽  
Rhythm Generator ◽  
Equivalent Dipole ◽  
Head Surface ◽  
Brain Rhythm ◽  
Deep Brain

Although the power of low-frequency oscillatory field potentials (FP) has been extensively applied previously, few studies have investigated the influence of conducting direction of deep-brain rhythm generator on the power distribution of low-frequency oscillatory FPs on the head surface. To address this issue, a simulation was designed based on the principle of electroencephalogram (EEG) generation of equivalent dipole current in deep brain, where a single oscillatory dipole current represented the rhythm generator, the dipole moment for the rhythm generator’s conducting direction (which was orthogonal and rotating every 30 degrees and at pointing to or parallel to the frontal lobe surface) and the (an)isotropic conduction medium for the 3D (a)symmetrical brain tissue. Both the power above average (significant power value, SP value) and its space (SP area) of low-frequency oscillatory FPs were employed to respectively evaluate the strength and the space of the influence. The computation was conducted using the finite element method (FEM) and Hilbert transform. The finding was that either the SP value or the SP area could be reduced or extended, depending on the conducting direction of deep-brain rhythm generator flowing in the (an)isotropic medium, suggesting that the 3D (a)symmetrical brain tissue could decay or strengthen the spatial spread of a rhythm generator conducting in a different direction.

scholarly journals Integral Equations for Problems on Wave Propagation in Near-Earth Plasma

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1395
Author(s):  
Danila Kostarev ◽  
Dmitri Klimushkin ◽  
Pavel Mager
Keyword(s):  
Magnetic Field ◽  
Integral Equations ◽  
Field Potential ◽  
Low Frequency ◽  
Fredholm Equation ◽  
Compression Waves ◽  
Parallel Component ◽  
Electric Field Potential ◽  
The Magnetic Field ◽  
Low Frequency Waves

We consider the solutions of two integrodifferential equations in this work. These equations describe the ultra-low frequency waves in the dipol-like model of the magnetosphere in the gyrokinetic framework. The first one is reduced to the homogeneous, second kind Fredholm equation. This equation describes the structure of the parallel component of the magnetic field of drift-compression waves along the Earth’s magnetic field. The second equation is reduced to the inhomogeneous, second kind Fredholm equation. This equation describes the field-aligned structure of the parallel electric field potential of Alfvén waves. Both integral equations are solved numerically.

Dynamic coupling among neocortical neurons during evoked and spontaneous spike-wave seizure activity

1994 ◽  
Vol 72 (5) ◽  
pp. 2051-2069 ◽  
Author(s):  
M. Steriade ◽  
F. Amzica
Keyword(s):  
Cortical Neurons ◽  
Time Course ◽  
Early Stage ◽  
Field Potential ◽  
Time Lags ◽  
Temporal Relations ◽  
Intracellular Recordings ◽  
Field Potentials ◽  
Thalamic Nuclei ◽  
Spike Wave

1. We investigated the development from patterns of electroencephalogram (EEG) synchronization to paroxysms consisting of spike-wave (SW) complexes at 2–4 Hz or to seizures at higher frequencies (7–15 Hz). We used multisite, simultaneous EEG, extracellular, and intracellular recordings from various neocortical areas and thalamic nuclei of anesthetized cats. 2. The seizures were observed in 25% of experimental animals, all maintained under ketamine and xylazine anesthesia, and were either induced by thalamocortical volleys and photic stimulation or occurred spontaneously. Out of unit and field potential recordings within 370 cortical and 65 thalamic sites, paroxysmal events occurred in 70 cortical and 8 thalamic sites (approximately 18% and 12%, respectively), within which a total of 181 neurons (143 extracellular and 38 intracellular) were simultaneously recorded in various combinations of cell groups. 3. Stimulus-elicited and spontaneous SW seizures at 2–4 Hz lasted for 15–35 s and consisted of barrages of action potentials related to the spiky depth-negative (surface-positive) field potentials, followed by neuronal silence during the depth-positive wave component of SW complexes. The duration of inhibitory periods progressively increased during the seizure, at the expense of the phasic excitatory phases. 4. Intracellular recordings showed that, during such paroxysms, cortical neurons displayed a tonic depolarization (approximately 10–20 mV), sculptured by rhythmic hyperpolarizations. 5. In all cases, measures of synchrony demonstrated time lags between discharges of simultaneously recorded cortical neurons, from as short as 3–10 ms up to 50 ms or even longer intervals. Synchrony was assessed by cross-correlograms, by a method termed first-spike-analysis designed to detect dynamic temporal relations between neurons and relying on the detection of the first action potential in a spike train, and by a method termed sequential-field-correlation that analyzed the time course of field potentials simultaneously recorded from different cortical areas. 6. The degree of synchrony progressively increased from preseizure sleep patterns to the early stage of the SW seizure and, further, to its late stage. In some cases the time relation between neurons during the early stages of seizures was inversed during late stages. 7. These data show that, although the common definition of SW seizures, regarded as suddenly generalized and bilaterally synchronous activities, may be valid at the macroscopic EEG level, cortical neurons display time lags between their rhythmic spike trains, progressively increased synchrony, and changes in the temporal relations between their discharges during the paroxysms.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Novel neuronal and astrocytic mechanisms in thalamocortical loop dynamics

2002 ◽  
Vol 357 (1428) ◽  
pp. 1675-1693 ◽  
Author(s):  
Vincenzo Crunelli ◽  
Kate L. Blethyn ◽  
David W. Cope ◽  
Stuart W. Hughes ◽  
H. Rheinallt Parri ◽  
...  
Keyword(s):  
Low Voltage ◽  
Electrical Coupling ◽  
Low Frequency ◽  
Network Activity ◽  
Thalamic Neuron ◽  
Cellular Mechanisms ◽  
Brain Areas ◽  
Sensory Stimuli ◽  
Loop Dynamics ◽  
Intracellular Ca

In this review, we summarize three sets of findings that have recently been observed in thalamic astrocytes and neurons, and discuss their significance for thalamocortical loop dynamics. (i) A physiologically relevant ‘window’ component of the low–voltage–activated, T–type Ca 2+ current ( I Twindow ) plays an essential part in the slow (less than 1 Hz) sleep oscillation in adult thalamocortical (TC) neurons, indicating that the expression of this fundamental sleep rhythm in these neurons is not a simple reflection of cortical network activity. It is also likely that I Twindow underlies one of the cellular mechanisms enabling TC neurons to produce burst firing in response to novel sensory stimuli. (ii) Both electrophysiological and dye–injection experiments support the existence of gap junction–mediated coupling among young and adult TC neurons. This finding indicates that electrical coupling–mediated synchronization might be implicated in the high and low frequency oscillatory activities expressed by this type of thalamic neuron. (iii) Spontaneous intracellular Ca 2+ ([Ca 2+ ] i ) waves propagating among thalamic astrocytes are able to elicit large and long–lasting N –methyl–D–aspartate–mediated currents in TC neurons. The peculiar developmental profile within the first two postnatal weeks of these astrocytic [Ca 2+ ] i transients and the selective activation of these glutamate receptors point to a role for this astrocyte–to–neuron signalling mechanism in the topographic wiring of the thalamocortical loop. As some of these novel cellular and intracellular properties are not restricted to thalamic astrocytes and neurons, their significance may well apply to (patho)physiological functions of glial and neuronal elements in other brain areas.

Low-frequency stimulation at the troughs of theta-oscillation induces long-term depression of previously potentiated CA1 synapses

1996 ◽  
Vol 75 (2) ◽  
pp. 877-884 ◽  
Author(s):  
P. T. Huerta ◽  
J. E. Lisman
Keyword(s):  
Hippocampal Slices ◽  
Field Potential ◽  
Low Frequency ◽  
Long Term Depression ◽  
Low Frequency Stimulation ◽  
Bath Application ◽  
Stable Conditions ◽  
Theta Frequency ◽  
Frequency Stimulation

1. The induction of long-term weakening of synaptic transmission in rat hippocampal slices was examined in CA1 synapses during cholinergic modulation. 2. Bath application of the cholinergic agonist carbachol (50 microM) activated an oscillation of the local field potential in the theta-frequency range (5-12 Hz), termed theta. It was previously shown that a stimulation train of 40 single shocks (at 0.1 Hz) to the Schaffer collateral-commisural afferents, each synchronized with positive peaks of theta, caused homosynaptic long-term enhancement in CA1. Furthermore, long-term depression (LTD) was sporadically observed when the stimulation train was given at negative troughs of theta. Here we have sought to determine stable conditions for LTD induction during theta. 3. Synaptic weakening was reliably obtained, by giving 40 shocks (at 0.1 Hz) at theta-troughs, only in pathways that had been previously potentiated. This decrement, termed theta-LTD, was synapse specific because it did not occur in an independent pathway not stimulated during theta. The interval between the initial potentiating tetanus and theta-LTD induction could be as long as 90 min. 4. theta-LTD could be saturated; after consecutive episodes of theta-LTD induction, no significant further depression was obtained. Moreover, theta-LTD could be reversed by tetanic stimulation. 5. theta-LTD could prevent the induction of LTD by 600-900 pulses at 1 Hz. This suggests that the two protocols may share common mechanisms at the synaptic level. 6. We conclude that single presynaptic spikes that occur at low frequency and are properly timed to the troughs of theta may be a relevant mechanism for decreasing the strength of potentiated synapses.

scholarly journals Dynamics of scalar potentials in theory of gravity

2019 ◽  
Vol 97 (8) ◽  
pp. 880-894
Author(s):  
M. Zubair ◽  
Farzana Kousar ◽  
Saira Waheed
Keyword(s):  
Scalar Field ◽  
Field Potential ◽  
Graphical Analysis ◽  
Chaplygin Gas ◽  
Field Potentials ◽  
De Sitter ◽  
Field Equations ◽  
Barotropic Fluid ◽  
First Case ◽  
De Sitter Universe

In this paper, we explore the nature of scalar field potential in [Formula: see text] gravity using a well-motivated reconstruction scheme for flat Friedmann–Robertson–Walker (FRW) geometry. The beauty of this scheme lies in the assumption that the Hubble parameter can be expressed in terms of scalar field and vice versa. Firstly, we develop field equations in this gravity and present some general explicit forms of scalar field potential via this technique. In the first case, we take the de Sitter universe model and construct some field potentials by taking different cases for the coupling function. In the second case, we derive some field potentials using the power law model in the presence of different matter sources like barotropic fluid, cosmological constant, and Chaplygin gas for some coupling functions. From graphical analysis, it is concluded that using some specific values of the involved parameters, the reconstructed scalar field potentials are cosmologically viable in both cases.

scholarly journals Deep Learning Based Proarrhythmia Analysis Using Field Potentials Recorded from Human Pluripotent Stem Cells Derived Cardiomyocytes

2018 ◽  
Author(s):  
Zeinab Golgooni ◽  
Sara Mirsadeghi ◽  
Mahdieh Soleymani Baghshah ◽  
Pedram Ataee ◽  
Hossein Baharvand ◽  
...  
Keyword(s):  
Neural Network ◽  
Stem Cells ◽  
Deep Learning ◽  
Pluripotent Stem Cells ◽  
Field Potential ◽  
Input Sequence ◽  
Patient Specific ◽  
Field Potentials ◽  
Drug Induced

AbstractAimAn early characterization of drug-induced cardiotoxicity may be possible by combining comprehensive in vitro pro-arrhythmia assay and deep learning techniques. The goal of this study was to develop a deep learning method to automatically detect irregular beating rhythm as well as abnormal waveforms of field potentials in an in vitro cardiotoxicity assay using human pluripotent stem cell (hPSC) derived cardiomyocytes and multi-electrode array (MEA) system.Methods and ResultsWe included field potential waveforms from 380 experiments which obtained by application of some cardioactive drugs on healthy and/or patient-specific induced pluripotent stem cells derived cardiomyocytes (iPSC-CM). We employed convolutional and recurrent neural networks, in order to develop a new method for automatic classification of field potential recordings without using any hand-engineered features. In the proposed method, a preparation phase was initially applied to split 60-second long recordings into a series of 5-second long windows. Thereafter, the classification phase comprising of two main steps was designed. In the first step, 5-second long windows were classified using a designated convolutional neural network (CNN). In the second step, the results of 5-second long window assessments were used as the input sequence to a recurrent neural network (RNN). The output was then compared to electrophysiologist-level arrhythmia (irregularity or abnormal waveforms) detection, resulting in 0.84 accuracy, 0.84 sensitivity, 0.85 specificity, and 0.88 precision.ConclusionA novel deep learning approach based on a two-step CNN-RNN method can be used for automated analysis of “irregularity or abnormal waveforms” in an in vitro model of cardiotoxicity experiments.

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