Stimulus-related Changes Research Articles

Intra-V1 functional networks and classification of observed stimuli.

Previous studies suggest that co-fluctuations in neural activity within V1 (measured with fMRI) carry information about observed stimuli, potentially reflecting various cognitive mechanisms. This study explores the neural sources shaping this information by using different fMRI preprocessing methods. The common response to stimuli shared by all individuals can be emphasized by using inter-subject correlations or de-emphasized by deconvolving the fMRI with hemodynamic response functions (HRFs) before calculating the correlations. The latter approach shifts the balance towards participant-idiosyncratic activity. Here, we used multivariate pattern analysis of intra-V1 correlation matrices to predict the Level or Shape of observed Navon letters employing the types of correlations described above. We assessed accuracy in inter-subject prediction of specific conjunctions of properties, and attempted intra-subject cross-classification of stimulus properties (i.e., prediction of one feature despite changes in the other). Weight maps from successful classifiers were projected onto the visual field. A control experiment investigated eye-movement patterns during stimuli presentation. All inter-subject classifiers accurately predicted the Level and Shape of specific observed stimuli. However, successful intra-subject cross-classification was achieved only for stimulus Level, but not Shape, regardless of preprocessing scheme. Weight maps for successful Level classification differed between inter-subject correlations and deconvolved correlations. The latter revealed asymmetries in visual field link strength that corresponded to known perceptual asymmetries. Post-hoc measurement of eyeball fMRI signals did not find differences in gaze between stimulus conditions, and a control experiment (with derived simulations) also suggested that eye movements do not explain the stimulus-related changes in V1 topology. Our findings indicate that both inter-subject common responses and participant-specific activity contribute to the information in intra-V1 co-fluctuations, albeit through distinct sub-networks. Deconvolution, that enhances subject-specific activity, highlighted interhemispheric links for Global stimuli. Further exploration of intra-V1 networks promises insights into the neural basis of attention and perceptual organization.

Functional Neuroimaging in Patients With Disorders of Consciousness: Caution Advised.

Functional Neuroimaging in Patients With Disorders of Consciousness: Caution Advised.

HP03: Abnormal Dynamic Neuronal Connectivity in children with dystonia

Dystonia is a network disorder resulting from dysfunction of, or abnormal connectivity within, the cortico-basal ganglia-cerebellar network. Despite the dynamic nature of the disorder, stimulus-related changes in connectivity have not been studied. We investigate modulation of neuronal connectivity by a proprioceptive stimulus in dystonia. Methods: Sixteen young people with dystonia and eight controls participated (age 6-20years, mean 12.5). A robotic wrist interface delivered passive wrist extension movements, producing a brief stretch of the right wrist flexors. Scalp EEG (10-20 system) was sampled at 2500Hz. Wrist position was monitored and movement onset synchronised with EEG. Data were segmented into epochs (1 second pre- and 3.5 seconds post-stimulus). Up to 160 epochs were averaged per subject to produce a Stretch Evoked Potential (StretchEP). Event-related network dynamics were estimated using the imaginary part of Wavelet Transform Coherency, excluding volume conduction, with bootstrapping to test for significance against random coupling between brain areas. The overall engagement of cortical areas into short-lived stimulus-related networks (global microscale nodal strength - GMNS) was estimated for each subject. Results: Clear StretchEPs were evoked over contralateral sensorimotor cortex. Individual dynamic connectivity maps revealed particularly strong event-related connectivity in the theta (4-8Hz) band in dystonia. At group level, theta band GMNS was significantly higher in dystonia than controls (p=0.045). The spatial extent of the networks was also stronger in dystonia than controls (non-significant trend). Conclusion: Young people with dystonia show an exaggerated dynamic network response to proprioceptive stimuli, displaying excessive, widespread theta-band synchronisation and over-recruitment across the sensorimotor network.

Phase- and amplitude-coupling are tied by an intrinsic spatial organization but show divergent stimulus-related changes

Functional connectivity (FC), thought to provide a window into neural communication, has become a core focus in the study of brain function and cognition. However, there is no consensus on how to conceptualize large-scale FC in electrophysiology. Phase coupling (PhC), defined as coupling between the phases of two signals, reflects the synchronization of rhythmic oscillation cycles. Conversely, amplitude coupling (AmpC), defined as coupling between the envelopes of two signals, reflects correlation of activation amplitude. Despite quantifying different electrophysiological properties, the relationship between PhC and AmpC remains largely unknown. We assessed spatial and temporal correspondence between PhC and AmpC over 5 canonical frequency bands during a cue-based motor task using electrocorticography (ECoG) in 18 patients (8 females) undergoing presurgical monitoring. Significant correspondence between the spatial pattern of PhC and AmpC was detected during stimulus processing across all subjects and frequency bands (R ​≈ ​0.50 for theta, decreasing with increasing frequency). The cross-measure spatial correlation vanished almost entirely when accounting for the portion of FC equally present during pre- and post-stimulus intervals, suggesting that the spatial correlations reflect intrinsic FC independent of stimulus processing. Stimulus-related processing modulated both PhC and AmpC, however in a spatially independent manner. Examining the linear temporal correlation, we found no evidence for linear dependence between PhC and AmpC. Supporting the robustness of our findings, results extended to a verb generation task in a second ECoG dataset of 6 subjects. We conclude that PhC and AmpC reflect intrinsic FC similarly across space, but exhibit divergent stimulus-related FC changes over space and time.

Study of sensory information processing depending on visual stimulus complexity based on multichannel EEG signals

Introduction: Analysis of electrical activity in the cortical neural network during the processing of visual information is one ofthe most interesting issues in modern neuroscience. The particular attention of the researchers is attracted by the study of neuralactivity during complex visual stimuli processing. Purpose: Studying the process of sensory information processing in the corticalneural network based on recorded electrical activity signals (EEG). Results: We have studied neural activity during visual informationprocessing based on the stimulus-related change in the spectral EEG energy in the 15–30 Hz frequency band. Using the developedapproach, we analyzed the influence of the visual stimulus complexity on the features of spatio-temporal neural activity. It has beenfound that at low complexity the spectral amplitude of the EEG in the range of 15–30 Hz increases mainly in the parietal zone. Withincreasing complexity, the spectral amplitude of the EEG increases simultaneously in different parts of the cortex, mainly in the frontalregion. Practical relevance: The identified features of neural dynamics can be used in the development of passive brain-computerinterfaces to monitor a person’s cognitive state and evaluate the cognitive load in real time.

K-th Nearest Neighbor (KNN) Entropy Estimates of Complexity and Integration from Ongoing and Stimulus-Evoked Electroencephalographic (EEG) Recordings of the Human Brain.

Information-theoretic measures for quantifying multivariate statistical dependence have proven useful for the study of the unity and diversity of the human brain. Two such measures–integration, I(X), and interaction complexity, CI(X)–have been previously applied to electroencephalographic (EEG) signals recorded during ongoing wakeful brain states. Here, I(X) and CI(X) were computed for empirical and simulated visually-elicited alpha-range (8–13 Hz) EEG signals. Integration and complexity of evoked (stimulus-locked) and induced (non-stimulus-locked) EEG responses were assessed using nonparametric k-th nearest neighbor (KNN) entropy estimation, which is robust to the nonstationarity of stimulus-elicited EEG signals. KNN-based I(X) and CI(X) were also computed for the alpha-range EEG of ongoing wakeful brain states. I(X) and CI(X) patterns differentiated between induced and evoked EEG signals and replicated previous wakeful EEG findings obtained using Gaussian-based entropy estimators. Absolute levels of I(X) and CI(X) were related to absolute levels of alpha-range EEG power and phase synchronization, but stimulus-related changes in the information-theoretic and other EEG properties were independent. These findings support the hypothesis that visual perception and ongoing wakeful mental states emerge from complex, dynamical interaction among segregated and integrated brain networks operating near an optimal balance between order and disorder.

Shifts of Gamma Phase across Primary Visual Cortical Sites Reflect Dynamic Stimulus-Modulated Information Transfer.

Distributed neural processing likely entails the capability of networks to reconfigure dynamically the directionality and strength of their functional connections. Yet, the neural mechanisms that may allow such dynamic routing of the information flow are not yet fully understood. We investigated the role of gamma band (50–80 Hz) oscillations in transient modulations of communication among neural populations by using measures of direction-specific causal information transfer. We found that the local phase of gamma-band rhythmic activity exerted a stimulus-modulated and spatially-asymmetric directed effect on the firing rate of spatially separated populations within the primary visual cortex. The relationships between gamma phases at different sites (phase shifts) could be described as a stimulus-modulated gamma-band wave propagating along the spatial directions with the largest information transfer. We observed transient stimulus-related changes in the spatial configuration of phases (compatible with changes in direction of gamma wave propagation) accompanied by a relative increase of the amount of information flowing along the instantaneous direction of the gamma wave. These effects were specific to the gamma-band and suggest that the time-varying relationships between gamma phases at different locations mark, and possibly causally mediate, the dynamic reconfiguration of functional connections.

Reduction of physiological noise with independent component analysis improves the detection of nociceptive responses with fMRI of the human spinal cord

The evaluation of spinal cord neuronal activity in humans with functional magnetic resonance imaging (fMRI) is technically challenging. Major difficulties arise from cardiac and respiratory movement artifacts that constitute significant sources of noise. In this paper we assessed the Correction of Structured noise using spatial Independent Component Analysis (CORSICA). FMRI data of the cervical spinal cord were acquired in 14 healthy subjects using gradient-echo EPI. Nociceptive electrical stimuli were applied to the thumb. Additional data with short TR (250 ms, to prevent aliasing) were acquired to generate a spatial map of physiological noise derived from Independent Component Analysis (ICA). Physiological noise was subsequently removed from the long-TR data after selecting independent components based on the generated noise map. Stimulus-evoked responses were analyzed using the general linear model, with and without CORSICA and with a regressor generated from the cerebrospinal fluid region. Results showed higher sensitivity to detect stimulus-related activation in the targeted dorsal segment of the cord after CORSICA. Furthermore, fewer voxels showed stimulus-related signal changes in the CSF and outside the spinal region, suggesting an increase in specificity. ICA can be used to effectively reduce physiological noise in spinal cord fMRI time series.

Assessment of synchrony in multiple neural spike trains using loglinear point process models

Neural spike trains, which are sequences of very brief jumps in voltage across the cell membrane, were one of the motivating applications for the development of point process methodology. Early work required the assumption of stationarity, but contemporary experiments often use time-varying stimuli and produce time-varying neural responses. More recently, many statistical methods have been developed for nonstationary neural point process data. There has also been much interest in identifying synchrony, meaning events across two or more neurons that are nearly simultaneous at the time scale of the recordings. A natural statistical approach is to discretize time, using short time bins, and to introduce loglinear models for dependency among neurons, but previous use of loglinear modeling technology has assumed stationarity. We introduce a succinct yet powerful class of time-varying loglinear models by (a) allowing individual-neuron effects (main effects) to involve time-varying intensities; (b) also allowing the individual-neuron effects to involve autocovariation effects (history effects) due to past spiking, (c) assuming excess synchrony effects (interaction effects) do not depend on history, and (d) assuming all effects vary smoothly across time. Using data from primary visual cortex of an anesthetized monkey we give two examples in which the rate of synchronous spiking can not be explained by stimulus-related changes in individual-neuron effects. In one example, the excess synchrony disappears when slow-wave "up" states are taken into account as history effects, while in the second example it does not. Standard point process theory explicitly rules out synchronous events. To justify our use of continuous-time methodology we introduce a framework that incorporates synchronous events and provides continuous-time loglinear point process approximations to discrete-time loglinear models.

Early and Recent Trends in Psychophysiology

The Journal of Psychophysiology (JoP) has faced considerable changes due to external influences during the last 10 years. Those included change of the editor and the editorial board, new policies, changes concerning the Federation of the European Psychophysiology Societies (FEPS), and so forth. Moreover, changes in psychophysiology itself, in particular advances in methods, have occurred during the last 10 years which might be reflected in JoP. In the present editorial I will try to point out developments and trends in psychophysiology as far as they are reflected in JoP, by comparing recent contents to the contents 10 years ago. To begin with, when comparing the issues of 1999 and 2000 to the more recent issues in 2009 and 2010 the reader is struck by several general changes. The most general change is due to the fact that the publisher decided to publish JoP as electronic version only starting in 2008. This change was mainly made by the reason that readers are increasingly wanting to handle journals in digital rather than paper form, as this allows readers to make better use of the information in a journal from the comfort of their desks. As to the contents of the journal, three general changes can be observed: First, in the old issues the Abstracts of the annual meetings of the member societies of FEPS captured a huge part of the earlier volumes since one of the reasons for JoP was the publishing of the abstracts of the society meetings. Such abstracts are fairly important for young psychophysiologists. The main problem with the abstracts was the steadily rising scale of the society meetings, and hence the amount of the abstracts. For example, 200 abstracts from a large society meeting would fill an entire issue. In consequence an increasing backlog of abstracts from earlier years had developed during the early years, which has strongly affected the intended purpose, namely timely publication of abstracts. Also, a journal only filled with abstract does not sell. Consequently the FEPS delegates have voted to cancel the publication of society abstracts, which changes JoP in a way that only papers are published in the more recent issues. A second change which can be observed is the fade-out of book reviews, which were frequent in the old times, for example, three book reviews already in the first issue of Vol. 13, 1999, while there were no book reviews in Vols. 23 and 24, 10 years later. A third and deplorable general change is the fade-out of letters to the editor or short commentaries over the years, which were frequent in the old times and reflected lively debates (e.g., Carretie & Iglesias, 1999; Kayser & Tenke, 1999; Ohman, 1999). The fourth general change, which was made possible by the dropout of the abstracts, was the increase of special issues on important topics. In Vols. 13 and 14 there was no special issue, but the continuation of an earlier method topic, namely the correction of ocular artifacts, which covers only four discussion papers in Vol. 14 (Barrett, 2000; Croft, 2000; Picton, van Roon, Armilio, Berg, Ille, & Scherg, 2000; Verleger, 2000). In sharp contrast, in the more recent Vols. 23 and 24 there were three special issues, namely on neuroelectric oscillations along the Lifespan (Yordanova, Kolev, & Rothenberger, 2009), cognitive effects of alcohol (Tomberg, 2010), and on consciousness and its neurofunctional descriptors (Meucci & Sannita, 2010). As can be seen, the topics of the recent special issues are devoted to cognitive neuroscience, while the older special issue was on techniques. This reflects a general trend in contents which will be discussed in more detail in the following. A considerable part of the old volumes was devoted to method topics which were then mainly focused on peripheral measures. For example, Koers, Mulder, and van der Veen (1999) compared two methods to assess stimulus-related changes in heart rate and blood pressure, Keil, Elbert, and Taub (1999) determined the value of accelerometry as a measure of real-world outcome by comparing it with EMG, Smeja, Foerster, Fuchs, Emmans, Hornig, and Fahrenberg (1999) describe an accelerometric method to quantify tremor activity and posture in real life, and Kettunen, Ravaja, and Keltikangas-Jarvinen (2000) proposed a smoothing method to detect coupled responses in psychophysiological time series. Such method papers were often followed by lively comments (e.g., Jennings, 1999; Velden, 1999) which show the hot debate about new method approaches in the earlier

Method for detection of changes in the EEG induced by the presence of sensory stimuli

The onset and offset of sensory stimuli evoke transient changes in the electroencephalogram (EEG) that can be detected by linear and/or nonlinear analysis. However, there is presently no systematic procedure to quantify the brain-electrical-activity correlate of the presence of a stimulus (as opposed to its onset evoked potential). We describe a method for detecting a stimulus-related change in brain electrical activity that persists while the stimulus is present (presence effect). The method, which is based on phase-space embedding of the EEG time series followed by quantitative analysis of the recurrence plot of the embedded signal, was used to demonstrate the occurrence of a presence effect in separate groups of human subjects exposed to sound, a magnetic field, and light. Any form of law-governed dynamical activity induced in the EEG can be detected, particularly activity that is nonlinearly related to the stimulus. Salient mathematical features of the method were reproduced in a model EEG system containing known nonlinear determinism.

Declarative memory formation in hippocampal sclerosis: an intracranial event-related potentials study

The functional deficits associated with hippocampal sclerosis during declarative memory formation are largely unknown. In this study, we analyzed intracranial event-related potentials recorded from the medial temporal lobes of nine epilepsy patients performing a word memorization task. We used frequency-specific wavelet analysis to assess stimulus-related changes in power and intertrial phase coherence. Statistical analysis revealed a significant decrease of stimulus-induced power in the delta and theta range on the side of pathology. No significant differences in phase locking were observed. Findings indicate a reduced availability of recruitable neural assemblies not only in the hippocampus but also in the rhinal cortex during memory formation. Network functions related to the timing of neural responses to the stimulus appear to be preserved.

Different states of energy metabolism in the vertebrate retina can be identified by stimulus-related changesin near UV transmission

Our aim was to identify different states of energy metabolism in the perfused isolated vertebrate retina by simultaneous recordings of light-evoked changes of transretinal potential (TRP) and spectroscopic changes related to oxidation of pyridine nucleotides. Isolated retinas were obtained from R.esc. and superfused. For each setting, three experiments were performed. Eighteen retinas were used. TRP as a response to light stimulation was recorded simultaneously with stimulus-induced transmission shift at 350 nm. These responses were recorded under normal conditions, under withdrawal of oxygen and glucose, and after addition of electron transport inhibitors and uncouplers of oxidative phosphorylation. Under normal conditions, TRP was strongly correlated with transmission shift after light stimulation. Without oxygen, amplitudes of stimulus-related TRP decreased and response related increase of transmission at 350 nm was reduced. The retina showed a much higher general absorption of the analyzing light. During glucose lack, an overall increase in transmission at 350 nm could be observed. The addition of Amytal yielded a specific reduction of the OFF components. Cyanide attenuated the ON and OFF components. Dinitrophenol yielded a considerable loss of the electrical ON response. Transmission change was affected less than electrical signal. Chlorophenylhydrazine induced a reproducible reduction of electrical responses, with a relative increase of transmission shift at 350 nm. In the isolated perfused retina, different states of energy metabolism and their specific impact on neuroretinal responses can be examined by simultaneous recordings of stimulus-related neuronal activity and spectroscopic changes.

Optophysiology: Depth-resolved probing of retinal physiology with functional ultrahigh-resolution optical coherence tomography

Noncontact, depth-resolved, optical probing of retinal response to visual stimulation with a <10-microm spatial resolution, achieved by using functional ultrahigh-resolution optical coherence tomography (fUHROCT), is demonstrated in isolated rabbit retinas. The method takes advantage of the fact that physiological changes in dark-adapted retinas caused by light stimulation can result in local variation of the tissue reflectivity. fUHROCT scans were acquired from isolated retinas synchronously with electrical recordings before, during, and after light stimulation. Pronounced stimulus-related changes in the retinal reflectivity profile were observed in the inner/outer segments of the photoreceptor layer and the plexiform layers. Control experiments (e.g., dark adaptation vs. light stimulation), pharmacological inhibition of photoreceptor function, and synaptic transmission to the inner retina confirmed that the origin of the observed optical changes is the altered physiological state of the retina evoked by the light stimulus. We have demonstrated that fUHROCT allows for simultaneous, noninvasive probing of both retinal morphology and function, which could significantly improve the early diagnosis of various ophthalmic pathologies and could lead to better understanding of pathogenesis.

Spectral representation—analyzing single-unit activity in extracellularly recorded neuronal data without spike sorting

One step in the conventional analysis of extracellularly recorded neuronal data is spike sorting, which separates electrical signal into action potentials from different neurons. Because spike sorting involves human judgment, it can be subjective and time intensive, particularly for large sets of neurons. Here we propose a simple, automated way to construct alternative representations of neuronal activity, called spectral representation (SR). In this approach, neuronal spikes are mapped to a discrete space of spike waveform features and time. Spectral representation enables us to find single-unit stimulus-related changes in neuronal activity without spike sorting. We tested the ability of this method to predict stimuli using both simulated data and experimental data from an auditory mapping study in anesthetized marmoset monkeys. We find that our approach produces more accurate classification of stimuli than spike-sorted data for both simulated and experimental conditions. Furthermore, this method lends itself to automated analysis of extracellularly recorded neuronal ensembles. Additionally, we suggest ways in which these representations can be readily extended to assist in spike sorting and the evaluation of single-neuron peri-stimulus time histograms.

Trial-to-trial variability of cortical evoked responses: implications for the analysis of functional connectivity

Objectives: The time series of single trial cortical evoked potentials typically have a random appearance, and their trial-to-trial variability is commonly explained by a model in which random ongoing background noise activity is linearly combined with a stereotyped evoked response. In this paper, we demonstrate that more realistic models, incorporating amplitude and latency variability of the evoked response itself, can explain statistical properties of cortical potentials that have often been attributed to stimulus-related changes in functional connectivity or other intrinsic neural parameters. Methods: Implications of trial-to-trial evoked potential variability for variance, power spectrum, and interdependence measures like cross-correlation and spectral coherence, are first derived analytically. These implications are then illustrated using model simulations and verified experimentally by the analysis of intracortical local field potentials recorded from monkeys performing a visual pattern discrimination task. To further investigate the effects of trial-to-trial variability on the aforementioned statistical measures, a Bayesian inference technique is used to separate single-trial evoked responses from the ongoing background activity. Results: We show that, when the average event-related potential (AERP) is subtracted from single-trial local field potential time series, a stimulus phase-locked component remains in the residual time series, in stark contrast to the assumption of the common model that no such phase-locked component should exist. Two main consequences of this observation are demonstrated for statistical measures that are computed on the residual time series. First, even though the AERP has been subtracted, the power spectral density, computed as a function of time with a short sliding window, can nonetheless show signs of modulation by the AERP waveform. Second, if the residual time series of two channels co-vary, then their cross-correlation and spectral coherence time functions can also be modulated according to the shape of the AERP waveform. Bayesian estimation of single-trial evoked responses provides further proof that these time-dependent statistical changes are due to remnants of the evoked phase-locked component in the residual time series. Conclusions: Because trial-to-trial variability of the evoked response is commonly ignored as a contributing factor in evoked potential studies, stimulus-related modulations of power spectral density, cross-correlation, and spectral coherence measures is often attributed to dynamic changes of the connectivity within and among neural populations. This work demonstrates that trial-to-trial variability of the evoked response must be considered as a possible explanation of such modulation.

Tracking the development of the N1 from age 3 to adulthood: an examination of speech and non-speech stimuli

Objectives: To examine developmental changes in the N1a, N1b and N1c evoked by a tone and a speech consonant (/da/).Methods: Subjects (n=70 for tones; n=69 for /da/) were grouped into 2 year intervals (age 3–16) and adults. They listened to a tone (2 kHz; 36 ms; 77 dB SL; ISI=600 ms; n=346) or a speech consonant /da/ (female voice recording; 7 ms VOT; 212 ms; 72 dB SL; ISI=600 ms; n=349) while watching a Disney® screensaver. EEG was recorded from 26 electrodes referenced to Cz. An averaged reference was computed off-line. Amplitude and latency data were analyzed with repeated-measures ANOVAs for age×electrode, and age×N1 component, respectively.Results: Left hemisphere N1a was mature before age 3 whereas the right hemisphere N1a matured around 7–8 years. The vertex N1b showed a parietal distribution which shifted anteriorly with age. The N1c showed age- and stimulus-related changes. The N1c measured over the left hemisphere matured earlier than the N1c over the right hemisphere. The N1c to /da/ matured earlier than that to tones.Conclusions: Auditory processing undergoes steady and subtle developmental changes. These changes follow different maturational patterns depending on the type of stimuli. The evidence suggests earlier development of the left hemisphere and earlier development of the generators underlying speech processing.

Visually guided motor imagery activates sensorimotor areas in humans

Stimulus-related changes in ongoing electroencephalography (EEG) over sensorimotor areas were investigated during a visually cued motor imagery task. Four subjects were instructed to imagine one-sided hand movements in response to visual cue stimuli. The EEG was recorded from central areas using 27 electrodes set at distances of 2.5 cm. The method of common spatial filters was used to extract discriminatory information of EEG patterns recorded during the two motor imagery conditions. Single EEG trials were classified in intervals of 250 ms for a 8-s period starting 3 s prior to stimulus presentation. The results suggest that perception of the visual cue stimulus modifies oscillations in sensorimotor areas specific to the indicated hand starting as soon as 250–500 ms after stimulus onset.

The Computation of Evoked Heart Rate and Blood Pressure

Abstract For many years psychophysiologists have been interested in stimulus related changes in heart rate and blood pressure. To represent these evoked heart rate and blood pressure patterns, heart rate and blood pressure data have to be transformed into equidistant time series. This paper presents an extensive comparison between two methods. The most often used method is based on linear interpolation, also known as weighted averaging. The low pass filtering method presented here is based on a well-known model for the generation of heart beats, the integral pulse frequency modulation model (IPFM). The comparison shows that the results of the filtering and interpolation procedures are virtually identical. Practically, small differences between the methods disappear in the averaging process. Therefore, the interpolation method is a suitable practical alternative to the computationally complex filtering method.

Responsiveness of Human Cortical Activity to Rhythmical Stimulation: A Three-Modality, Whole-Cortex Neuromagnetic Investigation

We developed numerical indicators to quantify stimulus-related changes in cortical magnetic signals recorded from nine healthy subjects while they received 1- to 2.5-s trains of 15 stimuli (somatosensory, visual, or auditory in separate runs) at rates from 6 to 14 Hz, intermingled with 1.6-s pauses. A locking index (L) was introduced to quantify how well the responses are time locked to the stimuli and a global change factor (GC) to indicate changes in the whole-cortex oscillatory activity in the 5- to 25-Hz frequency range. The responses were visualized with color-coded images illustrating cortical reactivity for all stimulus rates simultaneously. These color maps clearly showed that the modality-specific cortical signals were enhanced at frequencies corresponding to the stimulus rate during the trains. For somatosensory stimulation the activity in the vicinity of the somatosensory hand area was enhanced at most stimulus rates, suggesting mainly superposition of evoked responses. In individuals with strong posterior resting rhythm, visual stimuli typically entrained activity in the parietooccipital sulcus at stimulus rates close to the main frequency of the spontaneous activity, probably reflecting driving of the intrinsic cortical rhythm, whereas in subjects with little spontaneous parietooccipital rhythm the cortical signal appeared to be composed mainly of visual evoked responses. No modality-specific enhancement was observed during auditory stimulation. During the pauses between the trains, the cortical signals were significantly suppressed compared with the resting condition: The peak activity (7–13 Hz) was modulated within, but also outside, the modality-specific areas, and the signals outside the frequency peaks of maximum power were consistently and reproducibly suppressed over the whole cortex by all stimuli.