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Kemal S Turker - One of the best experts on this subject based on the ideXlab platform.
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Cutaneous silent period evoked in human first dorsal interosseous muscle motor units by laser stimulation
Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology, 2016Co-Authors: Mehmet C. Kahya, Oguz Sebik, Kemal S TurkerAbstract:Painful stimulation of the hand results in an inhibitory response in the hand muscles known as the cutaneous silent period (CSP). In this study, we employed probability- and frequency-based analysis methods to examine the CSP induced by laser stimuli. Subjects were asked to contract their first dorsal interosseous muscle so that selected motor units discharged at a rate of about 8Hz. Laser pulses were delivered to the palm of the hand, and reflex responses were recorded. The stimuli generated CSP in all test subjects. We found that the latency of the CSP evoked using laser stimulation was longer than that the previously published latency values of the CSP evoked using electrical stimulation. Using only the presently generated laser induced CSP data, the CSP duration was longer when analyzed via Peristimulus frequencygram method compared to the probability-based methods such as Peristimulus Time Histogram and surface electromyogram. In the light of the current results, we suggest that laser stimulation could be used when studying pain pathways in human subjects and the frequency-based analysis methods can be preferred because they are previously shown to be more reliable for obtaining the synaptic activity profile. These results can be used to standardize the CSP methods in basic and clinical research.
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Cutaneous silent period in human FDI motor units
Experimental Brain Research, 2010Co-Authors: Mehmet C. Kahya, Ş. Utku Yavuz, Kemal S TurkerAbstract:In this study, we aimed to use both the probability-based and the frequency-based analyses methods simultaneously to examine cutaneous silent period (CSP) induced by strong electrical currents. Subjects were asked to contract their first dorsal interosseus muscles so that one motor unit monitored via intramuscular wire electrodes discharged at a rate of approximately 8 Hz. Strong electrical stimuli were delivered to the back of the hand that created a subjective discomfort level of between 4 and 7 [0–10 visual analogue scale] and induced cutaneous silent period in all units. It was found that the duration of the CSP was significantly longer when the same data were analysed using frequency-based analysis method compared with the probability-based methods. Frequency-based analysis indicated that the strong electrical stimuli induce longer lasting inhibitory currents than what was indicated using the probability-based analyses such as surface electromyogram and Peristimulus Time Histogram. Usage of frequency-based analysis for bringing out the synaptic activity underlying CSP seems essential as its characteristics have been subject to a large number of studies in experimental and clinical settings.
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a study of synaptic connection between low threshold afferent fibres in common peroneal nerve and motoneurones in human tibialis anterior
Experimental Brain Research, 2008Co-Authors: Orawan Prasartwuth, Erdal Binboga, Kemal S TurkerAbstract:We have induced H-reflex responses in human tibialis anterior motor units and analysed the results using the classical technique, Peristimulus Time Histogram (PSTH), and a new technique, Peristimulus frequencygram (PSF). The PSF has recently been shown to be more reliable than the PSTH for indicating the synaptic connections on motoneurones, and therefore we wished to examine the differences between the two analysis methods. Experiments were conducted on eleven healthy subjects (7 males and 4 females) who did not have any known neurological disorder. The subject sat comfortably on a dental chair and the common peroneal nerve was stimulated. In each experiment, about 600 electrical stimuli were applied to the nerve randomly between 1 and 2 s. The recordings were taken with both by surface electromyogram (SEMG) and as single motor unit potentials. We found that, when a stimulus induces an H-reflex, it also generates a period of reduced activity (silent period) and a long latency excitation in the PSTH. However, the PSF records in general do not match the indications of the PSTH records. For example, when the PSTH indicated existence of a silent period immediately following the H-reflex response, the discharge rate of the unit was in fact higher than the prestimulus rate. On the contrary, during the PSTH illustrated long latency excitatory response, the discharge rate was lower than the prestimulus rate. Our findings suggest that PSF gives significantly different results compared with the PSTH in determining the synaptic connection of the low threshold muscle afferents to the motoneurones. While PSTH indicated that there was a silent period immediately after the H-reflex, the PSF demonstrated that the silent period was actually a continuation of the net excitatory effect and not a genuine inhibition since the small number of action potentials occured during this period displayed higher discharge rates than the prestimulus level. Furthermore, the long latency excitation, as it was indicated in the PSTH; was actually a net inhibitory effect since the large number of spikes that occured during that period had lower discharge rates than the prestimulus average. In the lights of the recent brain slice findings and completely different results obtained using the two analysis techniques, we suggest that the PSF analysis should be used along with the PSTH to illustrate the net synaptic connection between peripheral receptors and motoneurones in the human nervous system.
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A new method for eliciting and studying H-reflexes in the human masseter
Archives of oral biology, 1997Co-Authors: Sheila Scutter, Kemal S Turker, J. YangAbstract:Abstract A non-invasive method is presented for transmuscular stimulation of the masseteric nerve, using a frame to apply a cathode to the mandibular notch and an anode to the inside of the mouth. The H-reflex response was recorded using surface, macro and single motor-unit (SMU) electromyography (EMG) from the masseter. The latency of the reflex response representing the H-reflex in SMUs was determined from the cumulative sum of the Peristimulus Time Histogram. This latency was then corrected using a spike-trigger averaging technique, where the SMU spikes were used as triggers and the macro EMG recording as the source. SMU latencies for the H-reflex in masseter were in the range 5.9–8.8 msec, whereas H-reflex latencies for surface EMG varied between 5.4 and 6.4 msec.
Valérie Ventura - One of the best experts on this subject based on the ideXlab platform.
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Statistical Assessment of Time-Varying Dependence Between Two Neurons
2018Co-Authors: Can Cai, Robert Kass, Valérie VenturaAbstract:The joint Peristimulus Time Histogram (JPSTH) provides a visual representation of the dynamics of correlated activity for a pair of neurons. There are many ways to adjust the JPSTH for the Time-varying firing-rate modulation of each neuron, and then to define a suitable measure of Time-varying correlated activity. Our approach is to introduce a statistical model for the Time-varying joint spiking activity so that the joint firing rate can be estimated more efficiently. We have applied an adaptive smoothing method, which has been shown to be effective in capturing sudden changes in firing rate, to the ratio of joint firing probability to the probability of firing predicted by independence. A Bootstrap procedure, applicable to both Poisson and non-Poisson data, was used to define a statistical significance test of whether a large ratio could be due to chance alone. A numerical simulation showed that the Bootstrap-based significance test has very nearly the correct rejection probability, and can have markedly better power to detect departures from independence than does an approach based on testing contiguous bins in the JPSTH. In a companion paper (Cai et al. 2004b) we show how this formulation can accommodate latency and Time-varying excitability effects, which can confound spike timing effects.
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Trial-to-Trial Variability and its Effect on Time-Varying Dependence Between Two Neurons
2018Co-Authors: Can Cai, Robert Kass, Valérie VenturaAbstract:The joint Peristimulus Time Histogram (JPSTH) and cross-correlogram provide a visual representation of correlated activity for a pair of neurons, and the way this activity may increase or decrease over Time. In a companion paper (Cai et al. 2004a) we showed how a Bootstrap evaluation of the peaks in the smoothed diagonals of the JPSTH may be used to establish the likely validity of apparent Time-varying correlation. As noted by Brody (1999a,b) and Ben-Shaul et al. (2001), trial-to-trial variation can confound correlation and synchrony effects. In this paper we elaborate on that observation, and present a method of estimating the Time-dependent trial-to-trial variation in spike trains that may exceed the natural variation displayed by Poisson and non-Poisson point processes. The statistical problem is somewhat subtle because relatively few spikes per trial are available for estimating a firing-rate function that fluctuates over Time. The method developed here uses principal components of the trial-to-trial variability in firing rate functions to obtain a small number of parameters (typically two or three) that characterize the deviation of each trial's firing rate function from the across-trial average firing rate, represented by the smoothed PSTH. The Bootstrap significance test of Cai et al. (2004a) is then modified to accommodate these general excitability effects. This methodology allows an investigator to assess whether excitability effects are constant or Time-varying, and whether they are shared by two neurons. It is shown that trial-to-trial variation can, in the absence of synchrony, lead to an increase in correlation in spike counts between two neurons as the length of the interval over which spike counts are computed is increased. In data from two V1 neurons we find that highly statistically significant evidence of dependence disappears after adjustment for Time-varying trial-to-trial variation.
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Traditional waveform based spike sorting yields biased rate code estimates
Proceedings of the National Academy of Sciences of the United States of America, 2009Co-Authors: Valérie VenturaAbstract:Much of neuroscience has to do with relating neural activity and behavior or environment. One common measure of this relationship is the firing rates of neurons as functions of behavioral or environmental parameters, often called tuning functions and receptive fields. Firing rates are estimated from the spike trains of neurons recorded by electrodes implanted in the brain. Individual neurons' spike trains are not typically readily available, because the signal collected at an electrode is often a mixture of activities from different neurons and noise. Extracting individual neurons' spike trains from voltage signals, which is known as spike sorting, is one of the most important data analysis problems in neuroscience, because it has to be undertaken prior to any analysis of neurophysiological data in which more than one neuron is believed to be recorded on a single electrode. All current spike-sorting methods consist of clustering the characteristic spike waveforms of neurons. The sequence of first spike sorting based on waveforms, then estimating tuning functions, has long been the accepted way to proceed. Here, we argue that the covariates that modulate tuning functions also contain information about spike identities, and that if tuning information is ignored for spike sorting, the resulting tuning function estimates are biased and inconsistent, unless spikes can be classified with perfect accuracy. This means, for example, that the commonly used Peristimulus Time Histogram is a biased estimate of the firing rate of a neuron that is not perfectly isolated. We further argue that the correct conceptual way to view the problem out is to note that spike sorting provides information about rate estimation and vice versa, so that the two relationships should be considered simultaneously rather than sequentially. Indeed we show that when spike sorting and tuning-curve estimation are performed in parallel, unbiased estimates of tuning curves can be recovered even from imperfectly sorted neurons.
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Statistical Assessment of Time-Varying Dependency Between Two Neurons
Journal of neurophysiology, 2005Co-Authors: Valérie Ventura, Can Cai, Robert E. KassAbstract:The joint Peristimulus Time Histogram (JPSTH) provides a visual representation of the dynamics of correlated activity for a pair of neurons. There are many ways to adjust the JPSTH for the Time-varying firing-rate modulation of each neuron, and then to define a suitable measure of Time-varying correlated activity. Our approach is to introduce a statistical model for the Time-varying joint spiking activity so that the joint firing rate can be estimated more efficiently. We have applied an adaptive smoothing method, which has been shown to be effective in capturing sudden changes in firing rate, to the ratio of joint firing probability to the probability of firing predicted by independence. A bootstrap procedure, applicable to both Poisson and non-Poisson data, was used to define a statistical significance test of whether a large ratio could be attributable to chance alone. A numerical simulation showed that the bootstrap-based significance test has very nearly the correct rejection probability, and can have markedly better power to detect departures from independence than does an approach based on testing contiguous bins in the JPSTH. In a companion paper, we show how this formulation can accommodate latency and Time-varying excitability effects, which can confound spike timing effects.
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Trial-to-trial variability and its effect on Timevarying dependence between two neurons
Cambridge University Press, 2005Co-Authors: Can Cai, Robert E. Kass, Valérie VenturaAbstract:The joint Peristimulus Time Histogram (JPSTH) and cross-correlogram provide a visual representation of correlated activity for a pair of neurons, and the way this activity may increase or decrease over Time. In a companion paper (Cai et al. 2004a) we showed how a Bootstrap evaluation of the peaks in the smoothed diagonals of the JPSTH may be used to establish the likely validity of apparent Time-varying correlation. As noted by Brody (1999a,b) and Ben-Shaul et al. (2001), trial-to-trial variation can confound correlation and synchrony effects. In this paper we elaborate on that observation, and present a method of estimating the Time-dependent trial-to-trial variation in spike trains that may exceed the natural variation displayed by Poisson and non-Poisson point processes. The statistical problem is somewhat subtle because relatively few spikes per trial are available for estimating a firing-rate function that fluctuates over Time. The method developed here uses principal components of the trial-to-trial variability in firing rate functions to obtain a small number of parameters (typically two or three) that characterize the deviation of each trial’s firing rate function from the across-trial average firing rate, represented by th
Michael A. Nordstrom - One of the best experts on this subject based on the ideXlab platform.
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Responses of single motor units in human masseter to transcranial magnetic stimulation of either hemisphere.
The Journal of Physiology, 2003Co-Authors: Sophie L. Pearce, Timothy S. Miles, Philip D. Thompson, Michael A. NordstromAbstract:The corticobulbar inputs to single masseter motoneurons from the contra- and ipsilateral motor cortex were examined using focal transcranial magnetic stimulation (TMS) with a figure-of-eight stimulating coil. Fine-wire electrodes were inserted into the masseter muscle of six subjects, and the responses of 30 motor units were examined. All were tested with contralateral TMS, and 87 % showed a short-latency excitation in the Peristimulus Time Histogram at 7.0 ± 0.3 ms. The response was a single peak of 1.5 ± 0.2 ms duration, consistent with monosynaptic excitation via a single D- or I1-wave volley elicited by the stimulus. Increased TMS intensity produced a higher response probability (n= 13, paired t test, P 0.05). Of the motor units tested with ipsilateral TMS, 56 % responded with a reduced firing probability without a preceding excitation, and 19 % did not respond. These data suggest that masseter motoneurons receive monosynaptic input from the motor cortex that is asymmetrical from each hemisphere, with most low threshold motoneurons receiving short-latency excitatory input from the contralateral hemisphere only.
Robert E. Kass - One of the best experts on this subject based on the ideXlab platform.
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NOTE Communicated by Terence Sanger A Spike-Train Probability Model
2015Co-Authors: Robert E. Kass, Val Âerie VenturaAbstract:Poisson processes usually provide adequate descriptions of the irregular-ity in neuron spike Times after pooling the data across large numbers of trials, as is done in constructing the Peristimulus Time Histogram. When probabilities are needed to describe the behavior of neurons within in-dividual trials, however, Poisson process models are often inadequate. In principle, an explicit formula gives the probability density of a single spike train in great generality, but without additional assumptions, the ring-rate intensity function appearing in that formula cannot be esti-mated. We propose a simple solution to this problem, which is to assume that the Time at which a neuron res is determined probabilistically by, and only by, two quantities: the experimental clock Time and the elapsed Time since the previous spike. We show that this model can be tted with standard methods and software and that it may used successfully to t neuronal data.
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Statistical Assessment of Time-Varying Dependency Between Two Neurons
Journal of neurophysiology, 2005Co-Authors: Valérie Ventura, Can Cai, Robert E. KassAbstract:The joint Peristimulus Time Histogram (JPSTH) provides a visual representation of the dynamics of correlated activity for a pair of neurons. There are many ways to adjust the JPSTH for the Time-varying firing-rate modulation of each neuron, and then to define a suitable measure of Time-varying correlated activity. Our approach is to introduce a statistical model for the Time-varying joint spiking activity so that the joint firing rate can be estimated more efficiently. We have applied an adaptive smoothing method, which has been shown to be effective in capturing sudden changes in firing rate, to the ratio of joint firing probability to the probability of firing predicted by independence. A bootstrap procedure, applicable to both Poisson and non-Poisson data, was used to define a statistical significance test of whether a large ratio could be attributable to chance alone. A numerical simulation showed that the bootstrap-based significance test has very nearly the correct rejection probability, and can have markedly better power to detect departures from independence than does an approach based on testing contiguous bins in the JPSTH. In a companion paper, we show how this formulation can accommodate latency and Time-varying excitability effects, which can confound spike timing effects.
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Trial-to-trial variability and its effect on Timevarying dependence between two neurons
Cambridge University Press, 2005Co-Authors: Can Cai, Robert E. Kass, Valérie VenturaAbstract:The joint Peristimulus Time Histogram (JPSTH) and cross-correlogram provide a visual representation of correlated activity for a pair of neurons, and the way this activity may increase or decrease over Time. In a companion paper (Cai et al. 2004a) we showed how a Bootstrap evaluation of the peaks in the smoothed diagonals of the JPSTH may be used to establish the likely validity of apparent Time-varying correlation. As noted by Brody (1999a,b) and Ben-Shaul et al. (2001), trial-to-trial variation can confound correlation and synchrony effects. In this paper we elaborate on that observation, and present a method of estimating the Time-dependent trial-to-trial variation in spike trains that may exceed the natural variation displayed by Poisson and non-Poisson point processes. The statistical problem is somewhat subtle because relatively few spikes per trial are available for estimating a firing-rate function that fluctuates over Time. The method developed here uses principal components of the trial-to-trial variability in firing rate functions to obtain a small number of parameters (typically two or three) that characterize the deviation of each trial’s firing rate function from the across-trial average firing rate, represented by th
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Statistical smoothing of neuronal data.
Network (Bristol England), 2003Co-Authors: Robert E. Kass, Val Rie Ventura, Can CaiAbstract:The purpose of smoothing (filtering) neuronal data is to improve the estimation of the instantaneous firing rate. In some applications, scientific interest centres on functions of the instantaneous firing rate, such as the Time at which the maximal firing rate occurs or the rate of increase of firing rate over some experimentally relevant period. In others, the instantaneous firing rate is needed fo rp robability-based calculations. In this paper we point to the very substantial gains in statistical efficiency from smoothing methods compared to using the Peristimulus–Time Histogram (PSTH), and we also demonstrate a new method of adaptive smoothing known as Bayesian adaptive regression splines (DiMatteo I, Genovese C R and Kass R E 2001 Biometrika 88 1055–71). We briefly review additional applications of smoothing with non-Poisson processes and in the joint PSTH for a pair o fn eurons.
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a spike train probability model
Neural Computation, 2001Co-Authors: Robert E. Kass, Valérie VenturaAbstract:Poisson processes usually provide adequate descriptions of the irregularity in neuron spike Times after pooling the data across large numbers of trials, as is done in constructing the Peristimulus Time Histogram. When probabilities are needed to describe the behavior of neurons within individual trials, however, Poisson process models are often inadequate. In principle, an explicit formula gives the probability density of a single spike train in great generality, but without additional assumptions, the firing-rate intensity function appearing in that formula cannot be estimated. We propose a simple solution to this problem, which is to assume that the Time at which a neuron fires is determined probabilistically by, and only by, two quantities: the experimental clock Time and the elapsed Time since the previous spike. We show that this model can be fitted with standard methods and software and that it may used successfully to fit neuronal data.
Markus Weber - One of the best experts on this subject based on the ideXlab platform.
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determinants of double discharges in amyotrophic lateral sclerosis and kennedy disease
Clinical Neurophysiology, 2009Co-Authors: Markus Weber, Vanessa M Ferreira, Andrew EisenAbstract:OBJECTIVE: Double discharges (DDs) of the motor unit are frequent in amyotrophic lateral sclerosis (ALS) and Kennedy's disease (KD). This likely reflects changes in the intrinsic properties of motor neurons but in ALS changes in corticomotoneuronal inputs may also contribute. We determined the corticomotoneuronal contribution to DDs. METHODS: DD prevalence, intra-doublet interval (IDI) of DDs and their timing with respect to transcranial magnetic stimulation (TMS)-induced primary peaks (PPs) in the Peristimulus Time Histogram (PSTH) were measured in 23 ALS patients (96 motor units), 11 patients with KD (45 motor units) and 13 control subjects (60 motor units). RESULTS: In patients with KD more motor units (82%) fired DDs than in ALS patients (51%) and control subjects (63%); (p=0.013). DDs occurred before (pre-peak), during (peak), and after (post-suppression) the Peristimulus Time Histogram (PSTH) primary peak. The prevalence of pre-peak DD in KD was 4.06-fold higher (95% CI 0.53-2.81; p=0.0014) than in controls. In contrast the prevalence of ALS peak DDs was 4.79-fold higher (95% CI 1.09-21.10; p=0.041) than in controls. Both pre-peak and peak IDIs were significantly prolonged in ALS compared with controls (p>0.003). Motor unit action potential (MUAP) amplitude, size of the excitatory postsynaptic potential (EPSP) and interspike interval (ISI) all correlated significantly with pre-peak, but not peak DD prevalence. CONCLUSIONS: A high peak DD prevalence with prolonged IDIs in ALS are consistent with complex, multiple descending corticomotoneuronal volleys, indicating that the upper motor neuron contributes to the generation of DDs in ALS. SIGNIFICANCE: Although double discharges are a manifestation of reinnervating motor neurons in ALS the corticomotoneuronal descending input is also influential and probably accounts for some of the distinguishing features of DDs in ALS.
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Corticomotoneuronal activity in ALS: changes in the Peristimulus Time Histogram over Time.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology, 2000Co-Authors: Markus Weber, Andrew Eisen, Masashi NakajimaAbstract:Abstract Objective : The primary peak in the Peristimulus Time Histogram (PSTH) reflects the initial rising phase of the excitatory post-synaptic potential (EPSP) evoked at the anterior horn cell. In ALS the primary peak is delayed in onset, increased in duration and desynchronized, abnormalities reflecting dysfunction of the corticomotoneurons. It is not known whether these abnormalities change over Time in amyotrophic lateral sclerosis (ALS). Methods : PSTHs were constructed from changes in the firing probability of single, voluntarily activated motor units subjected to subthreshold transcranial magnetic stimuli. We studied 58 motor units in12 patients with ALS on two separate occasions (mean Time interval of 10.6±1.6 months). Results were compared with 49 motor units in 11 age matched controls. Results : All the parameters except the amplitude differed significantly between normals and patients. In general the primary peak in ALS was complex, desynchronized and occasionally consisted of a double peak. The abnormalities persisted or were accentuated at the follow up visit. This was reflected by an increase in the number of excess bins, longer duration and latency and decrease of synchrony. Conclusions : Increasing desynchronization of the primary peak over Time in ALS reflects dysfunction of the monosynaptic corticomotoneuronal pathway and may also reflect activation of additional slow conducting and/or polysynaptic corticomotoneuronal connections.