Biomedical subjects

Gabriel Curio

Publications and source records attributed to Gabriel Curio.

At least 19 recordsLinked to original sources

PubMed2006

Mental chronometry of target detection: human thalamus leads cortex.

Attentive monitoring of environmental stimuli is most fundamental for rapid target detection. The aim of this study was to assess the timing of thalamic versus cortical processes involved in this cognitive operation. To this end, simultaneous depth and scalp EEG was recorded in eight patients with essential tremor, undergoing thalamic deep brain stimulation (DBS), when the DBS electrodes could be accessed via their temporarily externalized leads. The patients performed an oddball task consisting of 300 presentations of one frequent and two rare visual cues, appearing in randomized order. One of the rare cues was defined as a target, the occurrences of which had to be indicated by a button press (motor condition) or silently counted (non-motor condition). At the scalp and the thalamus, event-related potentials (ERP) were largest upon target presentation, with peak latencies in the time domain of classical P300 responses. Remarkably, target-specific thalamic ERP emerged significantly prior to scalp P300. Furthermore, whereas scalp ERP had a higher amplitude upon rare than upon frequent non-target signals, thalamic ERP were independent of stimulus probability. This pattern was identified during motor and non-motor task execution. We conclude that the human thalamus specifically supports the early recognition of target events and can widely distribute this label through its divergent cortical projections.

Adult↗

PubMed2006

Enhancing the signal-to-noise ratio of ICA-based extracted ERPs.

When decomposing single trial electroencephalography it is a challenge to incorporate prior physiological knowledge. Here, we develop a method that uses prior information about the phase-locking property of event-related potentials in a regularization framework to bias a blind source separation algorithm toward an improved separation of single-trial phase-locked responses in terms of an increased signal-to-noise ratio. In particular, we suggest a transformation of the data, using weighted average of the single trial and trial-averaged response, that redirects the focus of source separation methods onto the subspace of event-related potentials. The practical benefit with respect to an improved separation of such components from ongoing background activity and extraneous noise is first illustrated on artificial data and finally verified in a real-world application of extracting single-trial somatosensory evoked potentials from multichannel EEG-recordings.

Algorithms↗

PubMed2006

Combined optimization of spatial and temporal filters for improving brain-computer interfacing.

Brain-computer interface (BCI) systems create a novel communication channel from the brain to an output device by bypassing conventional motor output pathways of nerves and muscles. Therefore they could provide a new communication and control option for paralyzed patients. Modern BCI technology is essentially based on techniques for the classification of single-trial brain signals. Here we present a novel technique that allows the simultaneous optimization of a spatial and a spectral filter enhancing discriminability rates of multichannel EEG single-trials. The evaluation of 60 experiments involving 22 different subjects demonstrates the significant superiority of the proposed algorithm over to its classical counterpart: the median classification error rate was decreased by 11%. Apart from the enhanced classification, the spatial and/or the spectral filter that are determined by the algorithm can also be used for further analysis of the data, e.g., for source localization of the respective brain rhythms.

Algorithms↗

PubMed2006

The Berlin Brain-Computer Interface: EEG-based communication without subject training.

The Berlin Brain-Computer Interface (BBCI) project develops a noninvasive BCI system whose key features are 1) the use of well-established motor competences as control paradigms, 2) high-dimensional features from 128-channel electroencephalogram (EEG), and 3) advanced machine learning techniques. As reported earlier, our experiments demonstrate that very high information transfer rates can be achieved using the readiness potential (RP) when predicting the laterality of upcoming left- versus right-hand movements in healthy subjects. A more recent study showed that the RP similarily accompanies phantom movements in arm amputees, but the signal strength decreases with longer loss of the limb. In a complementary approach, oscillatory features are used to discriminate imagined movements (left hand versus right hand versus foot). In a recent feedback study with six healthy subjects with no or very little experience with BCI control, three subjects achieved an information transfer rate above 35 bits per minute (bpm), and further two subjects above 24 and 15 bpm, while one subject could not achieve any BCI control. These results are encouraging for an EEG-based BCI system in untrained subjects that is independent of peripheral nervous system activity and does not rely on evoked potentials even when compared to results with very well-trained subjects operating other BCI systems.

Algorithms↗

PubMed2006

Now you feel it--now you don't: ERP correlates of somatosensory awareness.

We investigated correlates of somatosensory awareness for supra theshold stimuli using event-related potentials in a masking paradigm: Conscious perception of a weak, but suprathreshold "target" stimulus was suppressed in a significant number of trials when followed by a higher-intensity "mask" stimulus. ERPs were compared for trials with perceived versus unperceived target stimuli. Early ERPs (P60, N80), generated in the contralateral S1, were found independent of stimulus perception. In contrast, for consciously perceived target stimuli, amplitude enhancements were observed for the P100 and N140. Thus, early activation of S1 is not sufficient to warrant conscious stimulus perception. Conscious stimulus processing differs significantly from unconscious processing starting around 100 ms after stimulus presentation when the signal is processed in parietal and frontal cortices, brain regions crucial for stimulus access into conscious perception.

Adult↗

PubMed2005

Tonic neuronal activation during simple and complex finger movements analyzed by DC-magnetoencephalography.

Functional neuroimaging techniques map neuronal activation indirectly via local concomitant cortical vascular/metabolic changes. In a complementary approach, DC-magnetoencephalography measures neuronal activation dynamics directly, notably in a time range of the slow vascular/metabolic response. Here, using this technique neuronal activation dynamics and patterns for simple and complex finger movements are characterized intraindividually: in 6/6 right-handed subjects contralateral prolonged (30 s each) complex self-paced sequential finger movements revealed stronger field amplitudes over the pericentral sensorimotor cortex than simple movements. A consistent lateralization for contralateral versus ipsilateral finger movements was not found (4/6). A subsequent sensory paradigm focused on somatosensory afferences during the motor tasks and the reliability of the measuring technique. In all six subjects stable sustained neuronal activation during electrical median nerve stimulation was recorded. These neuronal quasi-tonic activation characteristics provide a new non-invasive neurophysiological measure to interpret signals mapped by functional neuroimaging techniques.

Adult↗

PubMed2005

Spatio-spectral filters for improving the classification of single trial EEG.

Data recorded in electroencephalogram (EEG)-based brain-computer interface experiments is generally very noisy, non-stationary, and contaminated with artifacts that can deteriorate discrimination/classification methods. In this paper, we extend the common spatial pattern (CSP) algorithm with the aim to alleviate these adverse effects. In particular, we suggest an extension of CSP to the state space, which utilizes the method of time delay embedding. As we will show, this allows for individually tuned frequency filters at each electrode position and, thus, yields an improved and more robust machine learning procedure. The advantages of the proposed method over the original CSP method are verified in terms of an improved information transfer rate (bits per trial) on a set of EEG-recordings from experiments of imagined limb movements.

Brain↗

PubMed2004

Does familiarity facilitate the cortical processing of music sounds?

Automatic cortical sound discrimination, as indexed by the mismatch negativity (MMN) component of the auditory evoked potential, is facilitated for familiar speech sounds (phonemes). In musicians as compared to non-musicians, an enhanced MMN has been observed for complex non-speech sounds. Here, musically trained subjects were presented with sequences of either familiar (tonal) or structurally matched unfamiliar (atonal) triad chords, both with either fixed or randomly transposed chord root pitch. The MMN elicited by deviant chords did not differ for familiar and unfamiliar triad sequences, and was undiminished even to unfamiliar deviant sounds which were consciously undetectable. Only subsequent attention-related components indicated facilitated cognitive processing of familiar sounds, corresponding to higher behavioral detection scores.

Acoustic Stimulation↗

PubMed2004

Neurovascular coupling analyzed non-invasively in the human brain.

Most functional brain imaging methods detect neuronal activations indirectly through the accompanying neurovascular response. Here, we demonstrate that a novel methodological approach, the combination of DC-magnetoencephalography (DC-MEG) and near-infrared spectroscopy (NIRS), allows non-invasive assessment of the dynamics of neurovascular coupling in the human brain: detecting directly slow neuronal processes (with time constants of 30s), DC-MEG revealed, even in unaveraged recordings, sustained neuronal activations at pericentral hand cortices contralateral to repetitive finger movements; these were accompanied by the ensuing local vascular response showing similar dynamical features as quantified by simultaneously recorded NIRS. This non-invasive approach opens a new avenue for the understanding of neurovascular coupling during physiological tasks as well as in diseases involving slow neuronal depolarization shifts and alterations of blood flow, such as stroke or migraine.

Adult↗

PubMed2004

Non-invasive magnetic detection of human injury currents.

OBJECTIVE: Injury currents are a hallmark of acute lesions in polarized cells. Our objective was to develop a non-invasive technique for monitoring human near-DC injury currents in vivo. METHODS: Using diagnostic muscle biopsy as controlled paradigm, injury-related magnetic DC-fields were mapped for 60 min postsurgery over leg muscle lesions of 9 subjects. A 49-channel magnetometer was used in combination with a mechanical horizontal modulation of the subject beneath the sensor array. RESULTS: Magnetic DC-field maps showed salient differences between biopsy and contralateral legs in 8/9 patients with a characteristic slowly decaying field in all biopsy legs. A variety of anomalous DC-field patterns was recorded over the biopsy sites, corresponding to theoretically predicted geometric variations of equivalent DC-current dipoles, i.e. wound surfaces, pointing into opposing muscle fibre ends. By contrast, all control measurements showed an elongated dipolar DC-field pattern. Additionally, mean global DC-field strengths were significantly higher over biopsy legs compared to the contralateral site. CONCLUSIONS: Our pilot data illustrate that human injury currents can be detected using non-invasive magnetometry. Thus, DC-magnetometry may provide an essential new tool for clinical monitoring of injury currents, possibly also in brain tissue, e.g. in case of anoxic or peri-infarct depolarizations.

Adult↗

PubMed2004

Short-term (approximately 600 ms) prediction of perturbation dynamics for 10- and 20-Hz MEG rhythms in human primary sensorimotor hand cortices.

The pericentral primary sensorimotor cortices generate the "mu rhythm" with a distinct spectral signature exhibiting two peaks, generated predominantly anterior (20 Hz) or posterior (10 Hz) to the central sulcus; it defines a "background" network state upon which somatosensory inputs will impinge. We used the high spatiotemporal resolution of magnetoencephalography to analyze the perturbation dynamics of these cortical rhythms in response to a series of paired electric median nerve stimuli: single trials were sorted off-line according to increasing power of the 10- or 20-Hz rebounds which occurred 300-600 ms after the first stimulus; using subaverages formed from the upper and lower 20% of this distribution, we analyzed somatosensory evoked fields (SEF) and power modifications caused by the second stimulus in the pair. We report three key findings: (1) the power level of rhythm rebounds triggered by the first stimulus predicted the rebound strength after the second stimulus applied 600 ms later; yet, it was uncorrelated across the 2.4-s interval separating subsequent stimulus pairs. (2) Conventional averaging camouflages substantial trial-to-trial variations of rhythm dynamics including, for example, even non-occurrences of rhythm rebounds. (3) For six of the seven subjects, the background rhythm power did not affect any SEF component; for the subject with the strongest rhythms only intracortically generated deflections (peaking after the thalamocortical input component N20m) varied as function of pre-stimulus 10- or 20-Hz power. Thus, the perturbation dynamics of the pericentral mu rhythm exhibits a significant intertrial variance, which becomes effective mainly at a time scale larger than 600 ms.

Adult↗

PubMed2004

The BCI Competition 2003: progress and perspectives in detection and discrimination of EEG single trials.

Interest in developing a new method of man-to-machine communication--a brain-computer interface (BCI)--has grown steadily over the past few decades. BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways of nerves and muscles. These systems use signals recorded from the scalp, the surface of the cortex, or from inside the brain to enable users to control a variety of applications including simple word-processing software and orthotics. BCI technology could therefore provide a new communication and control option for individuals who cannot otherwise express their wishes to the outside world. Signal processing and classification methods are essential tools in the development of improved BCI technology. We organized the BCI Competition 2003 to evaluate the current state of the art of these tools. Four laboratories well versed in EEG-based BCI research provided six data sets in a documented format. We made these data sets (i.e., labeled training sets and unlabeled test sets) and their descriptions available on the Internet. The goal in the competition was to maximize the performance measure for the test labels. Researchers worldwide tested their algorithms and competed for the best classification results. This paper describes the six data sets and the results and function of the most successful algorithms.

Adult↗

PubMed2004

Brain-computer communication and slow cortical potentials.

A thought translation device (TTD) has been designed to enable direct brain-computer communication using self-regulation of slow cortical potentials (SCPs). However, accuracy of SCP control reveals high intersubject variability. To guarantee the highest possible communication speed, some important aspects of training SCPs are discussed. A baseline correction of SCPs can increase performance. Multichannel recordings show that SCPs are of highest amplitude around the vertex electrode used for feedback, but in some subjects more global distributions were observed. A new method for control of eye movement is presented. Sequential effects of trial-to-trial interaction may also cause difficulties for the user. Finally, psychophysiological factors determining SCP communication are discussed.

Adult↗

PubMed2004

BCI Competition 2003--Data set III: probabilistic modeling of sensorimotor mu rhythms for classification of imaginary hand movements.

Brain-computer interfaces require effective online processing of electroencephalogram (EEG) measurements, e.g., as a part of feedback systems. We present an algorithm for single-trial online classification of imaginary left and right hand movements, based on time-frequency information derived from filtering EEG wideband raw data with causal Morlet wavelets, which are adapted to individual EEG spectra. Since imaginary hand movements lead to perturbations of the ongoing pericentral mu rhythm, we estimate probabilistic models for amplitude modulation in lower (10 Hz) and upper (20 Hz) frequency bands over the sensorimotor hand cortices both contra- and ipsilaterally to the imagined movements (i.e., at EEG channels C3 and C4). We use an integrative approach to accumulate over time evidence for the subject's unknown motor intention. Disclosure of test data labels after the competition showed this approach to succeed with an error rate as low as 10.7%.

Algorithms↗

PubMed2004

Boosting bit rates in noninvasive EEG single-trial classifications by feature combination and multiclass paradigms.

Noninvasive electroencephalogram (EEG) recordings provide for easy and safe access to human neocortical processes which can be exploited for a brain-computer interface (BCI). At present, however, the use of BCIs is severely limited by low bit-transfer rates. We systematically analyze and develop two recent concepts, both capable of enhancing the information gain from multichannel scalp EEG recordings: 1) the combination of classifiers, each specifically tailored for different physiological phenomena, e.g., slow cortical potential shifts, such as the pre-movement Bereitschaftspotential or differences in spatio-spectral distributions of brain activity (i.e., focal event-related desynchronizations) and 2) behavioral paradigms inducing the subjects to generate one out of several brain states (multiclass approach) which all bare a distinctive spatio-temporal signature well discriminable in the standard scalp EEG. We derive information-theoretic predictions and demonstrate their relevance in experimental data. We will show that a suitably arranged interaction between these concepts can significantly boost BCI performances.

Algorithms↗

PubMed2004

Electrophysiological evidence for altered early cerebral somatosensory signal processing in schizophrenia.

Various studies have indicated an impairment of sensory signal processing in schizophrenic patients. Anatomical and functional imaging studies have indicated morphological and metabolic abnormalities in the thalamus in schizophrenia. Other results give evidence for an additional role of cortical dysfunction in sensory processing in schizophrenia. Advanced analysis of human median nerve somatosensory evoked potentials (SEPs) reveals a brief oscillatory burst of low-amplitude and high-frequency activity ( approximately 600 Hz), the so-called high frequency oscillations (HFOs). The present study explores the behavior of HFOs in a cohort of schizophrenic patients in comparison to a group of controls. HFOs in the group of patients appeared with a delayed latency. In the low-frequency part of the SEPs an increase in amplitude was found. These results are interpreted to reflect a lack of somatosensory inhibition in the somatosensory pathway, either at a thalamic or a cortical level.

Adult↗

PubMed2004

Looking for faces: Attention modulates early occipitotemporal object processing.

Looking for somebody's face in a crowd is one of the most important examples of visual search. For this goal, attention has to be directed to a well-defined perceptual category. When this categorically selective process starts is, however, still unknown. To this end, we used magnetoencephalography (MEG) recorded over right human occipitotemporal cortex to investigate the time course of attentional modulation of perceptual processes elicited by faces and by houses. The first face-distinctive MEG response was observed at 160-170 ms (M170). Nevertheless, attention did not start to modulate face processing before 190 ms. The first house-distinctive MEG activity was also found around 160-170 ms. However, house processing was not modulated by attention before 280 ms (90 ms later than face processing). Further analysis revealed that the attentional modulation of face processing is not due to later, for example, back-propagated activation of the M170 generator. Rather, subsequent stages of occipitotemporal object processing were modulated in a category-specific manner and with preferential access to face processing.

Adult↗

PubMed2003

Functional dissociation of a subcortical and cortical component of high-frequency oscillations in human somatosensory evoked potentials by motor interference.

To identify the possibly divergent impact on early and late high-frequency oscillations (HFOs) in human somatosensory evoked potentials (SEPs), we have studied motor interference effects on the HFOs, and the relevance of such effects for the controversy concerning their origins. While the late HFO is thought to be generated in the somatosensory cortex, there is an ongoing discussion whether the early burst is of cortical or subcortical origin. Movements of the index finger were performed in parallel with median nerve SEP recordings. The intracortically generated N20-SEP and the late HFO were attenuated by the motor task, while the brainstem low-frequency P14-SEP and the early HFO remained unaffected. These differing effects are consistent with a generation of the early HFOs by cortical presynaptic activity in terminals of the thalamocortical projection, and confirm a postsynaptic intracortical origin of the late burst subcomponent.

Adult↗