Spike separation in multiunit records: A multivariate analysis of spike descriptive parameters

Vibert, Jean-François; Costa, Juliana dos Santos

doi:10.1016/0013-4694(79)90219-0

Cited by 39 publications

(14 citation statements)

References 16 publications

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“…14-16 for principal component analysis). The validity of these spike parameters in identifying different waveforms in multiunit recordings has been discussed in extenso (16)(17)(18)(19). The waveform parameters of up to 4096 spikes are then displayed in pairs using an x/y point plot format.…”

Section: Methodsmentioning

confidence: 99%

Single unit components of the hypothalamic multiunit electrical activity associated with the central signal generator that directs the pulsatile secretion of gonadotropic hormones.

Cárdenas

Ördög

O’Byrne

et al. 1993

Proc. Natl. Acad. Sci. U.S.A.

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Vertebrate reproduction is dependent on the operation of a central signal generator that directs the episodic release of gonadotropin-releasing hormone, a neuropeptide that stimulates secretion of the pituitary gonadotropic hormones and, thereby, controls gonadal function. The electrophysiological correlates of this pulse generator are characterized by abrupt increases in hypothalamic multiunit electrical activity (MUA voDleys) invariably associated with the initiation of secretory episodes of luteinizing hormone. Using cluster analysis, we extracted single units from the multiunit signals recorded from the mediobasal hypothalamus of four intact and four ovariectomized rhesus monkeys. Of the 40 individual units identified in this manner, 24 increased their frequency with the MUA volleys. The onset and termination of these single-unit bursts occurred coincidently with those of the MUA volleys in both intact and ovariectomized animals, indicating that the longer duration of the MUA voDleys characteristic of the gonadectomized animals was due not to the sequential activation of different units but to the longer bursts of the individual cels. Four other units showed decreases in firing rate during the MUA volleys, while the frequency of the remainder did not change. All the examined units were active during the intervals between the volleys of electrical activity. The results indicate that the MUA voDleys associated with the activity of the gonadotropin-releasing hormone pulse generator represent the simultaneous increase in firing rate of some individual hypothalamic neurons and the decrease in the frequency of others.The rhythmic, pulsatile secretion of the pituitary gonadotropic hormones, described in every vertebrate studied in this regard, is governed by a hypothalamic "clock" generally referred to as the gonadotropin-releasing hormone (GnRH) pulse generator. The operation of this signal generator at an appropriate frequency for the species is an absolute requirement for normal gonadal function (see ref. 1 for review).In the rhesus monkey, this central signal generator fires approximately once an hour and has been localized in the region ofthe arcuate nucleus (2), but -its cellular basis remains in doubt (3). Abrupt increases in multiunit activity (MUA volleys) that are invariably synchronous with the initiation of luteinizing hormone pulses measured in peripheral blood (Fig. 1) have been recorded from this area in the rhesus monkey (4), rat (5), and goat (6). The unitary association between luteinizing hormone pulses and these electrical signals has been observed in a variety of experimental circumstances (4, 7-11) as well as during the normal menstrual cycle (12) and has permitted the conclusion that these MUA volleys are the electrophysiological manifestations of GnRH pulse generator activity.The publication costs of this article were defrayed in part by page charge payment. This article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. §1734 solely to indicate this fact....

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Section: Methodsmentioning

confidence: 99%

Single unit components of the hypothalamic multiunit electrical activity associated with the central signal generator that directs the pulsatile secretion of gonadotropic hormones.

Cárdenas

Ördög

O’Byrne

et al. 1993

Proc. Natl. Acad. Sci. U.S.A.

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“…Separation of neurons using these three parameters is based on physiology where and for a particular neuron are dependent on the distance of the site from the neuron, the size of the neuron, and the spatial configuration of the dendritic tree [17]. The first principal component, represented by amplitude parameters and , contained 60%-65% [16] of the total information in Vibert's study. The time between and is also derived from physiology and is dependent on the distance of the recording site from the neuron axon hillock [18].…”

Section: Neural Spike Discriminationmentioning

confidence: 99%

“…The time between and is also derived from physiology and is dependent on the distance of the recording site from the neuron axon hillock [18]. This second principal component contained 15%-20% [16] of the information in Vibert's experiments. Since the neural spike detection ASIC shown in Fig.…”

Section: Neural Spike Discriminationmentioning

confidence: 99%

“…Vibert [16] evaluated neural spike separation based on eight parameters of the neural spike and concluded that using three parameters, (the maximum positive spike amplitude), (the minimum negative spike amplitude), and (the time between and ), not only adequately sorted spikes but was actually superior to spike separation using more parameters. This was because the additional parameters were all correlated with one or more of , , and , while , , and were found to be uncorrelated.…”

Section: Neural Spike Discriminationmentioning

confidence: 99%

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A three-dimensional neural recording microsystem with implantable data compression circuitry

Olsson

Wise

2005

IEEE J. Solid-State Circuits

214

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Abstract-A 256-site, fully implantable, 3-D neural recording microsystem has been developed. The microsystem incorporates four active neural probes with integrated circuitry for site selection, amplification, and multiplexing. The probes drive an embedded data-compression ASIC that successfully detects neural spikes in the presence of neural and circuit noise. The spike detection ASIC achieves a factor of 12 bandwidth reduction while preserving the key features of the action potential waveshape necessary for spike discrimination. This work extends the total number of neural channels that can be recorded across a transcutaneous inductively coupled wireless link from 25 to 312. When a spike is detected, this ASIC serially shifts the 5-bit amplitude and 5-bit address of the spike off of the chip over a single 2.5 Mb/s wired or wireless line. The spike detection ASIC occupies 6 mm 2 in 0.5 m features and consumes 2.6 mW while the entire microsystem consumes 5.4 mW of power from a 3-V supply.

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“…Methods for intramuscular EMG decomposition date back to the 70's. In the earlier approaches, the user usually had to manually select and classify the detected MUAPs in order to identify the MUAPt [6], [7], [8]. Later, automatic methods were developed, all based on MUAP waveform classification [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19], [20].…”

Section: Introductionmentioning

confidence: 99%

Decomposition of Multi-Channel Intramuscular EMG Signals by Cyclostationary-Based Blind Source Separation

Roussel

Ravier

Haritopoulos

et al. 2017

IEEE Trans. Neural Syst. Rehabil. Eng.

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We propose a novel decomposition method for electromyographic (EMG) signals based on blind source separation. Using the cyclostationary properties of motor unit action potential trains (MUAPt), it is shown that MUAPt can be decomposed by joint diagonalization of the cyclic spatial correlation matrix of the observations. After modeling of the source signals, we provide the proof of orthogonality of the sources and of their delayed versions in a cyclostationary context. We tested the proposed method on simulated signals and showed that it can decompose up to 6 sources with a probability of correct detection and classification >95%, using only 8 recording sites. Moreover, we tested the method on experimental multi-channel signals recorded with thinfilm intramuscular electrodes, with a total of 32 recording sites. The rate of agreement of the decomposed MUAPt with those obtained by an expert using a validated tool for decomposition was >93%.Index Terms -EMG, Decomposition, Motor Unit, Firing Rate, Blind Source Separation, Cyclostationary Process, CycloSOBI, convolutive mixture, pulse train separation I IntroductionThe muscle contraction is generated by functional units --the motor units (MU, [1]) --each composed of a motoneuron (MN) innervating a group of muscle fibers. MNs generate electrical impulses, the action potentials (AP), which induce the activation of muscle fibers. The contraction force is controlled by the number of recruited MUs (recruitment) and by the density of APs within the train of each MU (rate coding) [2].The density of APs can be quantified by the inter-spike interval (ISI) or by its inverse value which is referred to as the firing rate (FR). These quantities can be defined in an instantaneous way, or with average values, or through their distributions. The EMG signal comprises the sum of the MUAP trains (MUAPt) of the active MUs. The identification of the MUAPt from the EMG provides the means to identify the neural drive to muscles. This procedure is often termed decomposition of the EMG and has provided fundamental insights into motor unit physiology and neural control of movement [3][4]. In addition to basic neurophysiologic investigations, decomposition of the EMG has also clinical relevance [5]. Acknowledgments The present work is part of the French national project ECOTECH (www.echotechsan.org) which is supported by the French National Agency for research, contract no ANR-12-TECS-0020. The work was also partly funded by the European Research Council (ERC) via the ERC Advanced Grant DEMOVE (No. 267888; to DF). The authors are grateful to Silvia Muceli for providing the experimental data.In this paper, we address the problem of EMG decomposition. Methods for intramuscular EMG decomposition date back to the 70's. In the earlier approaches, the user usually had to manually select and classify the detected MUAPs in order to identify the [34]. The BSS approach has been recently used also for decomposing multi-channel intramuscular EMG signals [35].Here, we propose a new cyclostationary based B...

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Spike separation in multiunit records: A multivariate analysis of spike descriptive parameters

Cited by 39 publications

References 16 publications

Single unit components of the hypothalamic multiunit electrical activity associated with the central signal generator that directs the pulsatile secretion of gonadotropic hormones.

Single unit components of the hypothalamic multiunit electrical activity associated with the central signal generator that directs the pulsatile secretion of gonadotropic hormones.

A three-dimensional neural recording microsystem with implantable data compression circuitry

Decomposition of Multi-Channel Intramuscular EMG Signals by Cyclostationary-Based Blind Source Separation

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