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Patients with paralysis will one day rely on clinically-available brain-machine interfaces (BMI) to facilitate activities of daily living. As such, the ability to generate dexterous reaching movements remains a prime target of BMI algorithms research. The Bayesian approach to BMI algorithms requires a statistical model to describe reaching movements. To date, available models have either required...
Advances in neural electrode technology are enabling brain recordings with increasingly fine spatial and temporal resolution. We explore spatio-temporal (ST) patterns of local field potential spikes using a new high-density active electrode array with 500 μm resolution. We record subdural micro-electrocorticographic (μECoG) signals in vivo from a feline model of acute neocortical epileptiform spikes...
The unilaterally lesioned rat model of Parkinson's disease which fails to orient to the food stimuli presented on the contralateral side of its preferential side of body could be induced by the injection of 6-hydroxydopamine (6-OHDA) into the medial forebrain bundle (MFB). We employed transcranial direct current stimulation (tDCS, current intensity: 80 μA, and 40 μA; anodal electrode area: 3.14 mm...
Efficient methods for Local Field Potential (LFP) signal analysis amenable to interpretation are becoming increasingly relevant. LFP signals are believed, in part, to reflect neural action potential activity, and LFP frequency modulations are linked to spiking events. Furthermore, LFP signals are increasingly accessible in human brain regions previously unreachable due to a proliferation of deep brain...
Low-power devices that can detect clinically relevant correlations in physiologically-complex patient signals can enable systems capable of closed-loop response (e.g., controlled actuation of therapeutic stimulators, continuous recording of disease states, etc.). In ultra-low-power platforms, however, hardware error sources are becoming increasingly limiting. In this paper, we present how data-driven...
In the context of drug resistant partial epilepsy, intra-cerebral electrical stimulation (Deep Brain Stimulation) constitutes one of the means of investigation to locate epileptic volume. This exogenous source can then activate the underlying epileptic networks and generate an electrophysiological reaction. The purpose of this work is to estimate and eliminate the overlapping electrical stimulation...
Analysis of exhaled trace gases is a novel methodology for gaining continuous and non-invasive information on the clinical state of an individual. This paper serves to explore some potential applications of breath gas analysis in anesthesia, describing a monitoring scheme for target site concentrations and cardiac output via physiological modeling and real-time breath profiles of the anesthetic agent...
We evaluated neurovascular and autonomic response to a Divided Attention task within a group of 16 healthy subjects, by means of Electroencephalography, Electrocardiography, functional Near Infrared Spectroscopy techniques, acquired simultaneously. We exctracted Alpha (8–13,5 Hz) and Beta (13,5–30 Hz) power rhythms with a spectral autoregressive residual model, and inter-beat-interval (RR series)...
Partial directed coherence (PDC) as a frequency-domain representation of Granger casuality (GC) could detect both strength and direction of cortical interactions by multivari-ate autoregressive (MVAR) model of electroencephalography (EEG). In the present study, we investigate the underlying neural networks mechanisms of “rotational uncertainty effect” during mental rotation (MR) task by PDC analysis...
Considerable evidences have shown a decrease of neu-ronal activity in the left frontal lobe of depressed patients, but the underlying cortical network is still unclear. The present study intends to investigate the conscious-state brain network patterns in depressed patients compared with control individuals. Cortical functional connectivity is quantified by the partial directed coherence (PDC) analysis...
Multivariate Granger causality in the time-frequency domain as a representation of time-varying cortical connectivity in the brain has been investigated for the adult case. This is, however, not the case in newborns as the nature of the transient changes in the newborn EEG is different from that of adults. This paper aims to evaluate the performance of the time-varying versions of the two popular...
Burst suppression is an electroencephalogram pattern observed in states of severely reduced brain activity, such as general anesthesia, hypothermia and anoxic brain injuries. The burst suppression ratio (BSR), defined as the fraction of EEG spent in suppression per epoch, is the standard quantitative measure used to characterize burst suppression. We present a state space model to compute a dynamic...
Cognitive control of emotion plays an important role in maintaining emotional stability in people's daily life. However, the neural mechanism remains unclear. This study examined the induced gamma activity in response to emotional expressions which was associated with the cognitive regulation. Electroencephalogram (EEG) was recorded in fifteen normal subjects when detecting emotional expressions....
We present a set of formulas for the receptive fields of the vestibular neurons that are motivated by Galilean invariance. We show that these formulas explain non-trivial data in neurophysiology, and suggest new hypothesis to be tested in dynamical 3D conditions. Moreover our model offers a way for neuronal computing with 3D displacements, which is reputed to be hard, underlying the vestibular reflexes...
In the last decades, many investigations were done to examine the effects of sensorineural hearing loss on the speech perception ability. Besides testing hearing impaired persons, there is also the possibility to simulate the hearing loss. Therefore, some electrophysiological as well as speech recognition studies were performed in normal hearing subjects using techniques to model the sensorineural...
Brain Hyperscanning, i.e. the simultaneous recording of the cerebral activity of different human subjects involved in interaction tasks, is a very recent field of Neuroscience aiming at understanding the cerebral processes generating and generated by social interactions. This approach allows the observation and modeling of the neural signature specifically dependent on the interaction between subjects,...
Electrocorticography (ECoG) is an emerging tool to map brain functions in the context of neurosurgical intervention. Previous mapping methods based on the event related power spectrum are prone to noise. To improve the robustness of cortical function mapping, general linear model (GLM), which has been widely used in the analysis of functional magnetic resonance imaging (fMRI) data, is applied to bandpass...
The complexity of the human brain and the limitation of any one imaging approach motivates the need for multimodal measurements to better understand cerebral processing. A very natural goal is to integrate electrophysiological and hemodynamic activity. Among them, concurrent EEG-fMRI studies have shown great promise for understanding intrinsic brain properties yet analyzing such data presents a significant...
Electroencephalogram (EEG) recordings of brain activities can be processed in order to augment the brain's cognitive, sensory, or motor functionality. A representative, yet analytically tractable, model is essential to EEG processing. Several studies have examined different statistical models for EEG power spectrum. But recent studies have shown that not only the power, but also the phase of the spectrum,...
Motor imagery (MI) brain-computer interfaces (BCIs) translate a subject's motor intention to a command signal. Most MI BCIs use power features in the mu or beta rhythms, while several results have been reported using a measure of phase synchrony, the phase-locking value (PLV). In this study, we investigated the performance of various phase-based features, including instantaneous phase difference (IPD)...
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