926 resultados para EEG, fMRI, sinestesia
Resumo:
One of the major aims of BCI research is devoted to achieving faster and more efficient control of external devices. The identification of individual tap events in a motor imagery BCI is therefore a desirable goal. EEG is recorded from subjects performing and imagining finger taps with their left and right hands. A Differential Evolution based feature selection wrapper is used in order to identify optimal features in the spatial and frequency domains for tap identification. Channel-frequency band combinations are found which allow differentiation of tap vs. no-tap control conditions for executed and imagined taps. Left vs. right hand taps may also be differentiated with features found in this manner. A sliding time window is then used to accurately identify individual taps in the executed tap and imagined tap conditions. Highly statistically significant classification accuracies are achieved with time windows of 0.5 s and more allowing taps to be identified on a single trial basis.
Resumo:
OBJECTIVE: The anticipation of adverse outcomes, or worry, is a cardinal symptom of generalized anxiety disorder. Prior work with healthy subjects has shown that anticipating aversive events recruits a network of brain regions, including the amygdala and anterior cingulate cortex. This study tested whether patients with generalized anxiety disorder have alterations in anticipatory amygdala function and whether anticipatory activity in the anterior cingulate cortex predicts treatment response. METHOD: Functional magnetic resonance imaging (fMRI) was employed with 14 generalized anxiety disorder patients and 12 healthy comparison subjects matched for age, sex, and education. The event-related fMRI paradigm was composed of one warning cue that preceded aversive pictures and a second cue that preceded neutral pictures. Following the fMRI session, patients received 8 weeks of treatment with extended-release venlafaxine. RESULTS: Patients with generalized anxiety disorder showed greater anticipatory activity than healthy comparison subjects in the bilateral dorsal amygdala preceding both aversive and neutral pictures. Building on prior reports of pretreatment anterior cingulate cortex activity predicting treatment response, anticipatory activity in that area was associated with clinical outcome 8 weeks later following treatment with venlafaxine. Higher levels of pretreatment anterior cingulate cortex activity in anticipation of both aversive and neutral pictures were associated with greater reductions in anxiety and worry symptoms. CONCLUSIONS: These findings of heightened and indiscriminate amygdala responses to anticipatory signals in generalized anxiety disorder and of anterior cingulate cortex associations with treatment response provide neurobiological support for the role of anticipatory processes in the pathophysiology of generalized anxiety disorder.
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Accurate single trial P300 classification lends itself to fast and accurate control of Brain Computer Interfaces (BCIs). Highly accurate classification of single trial P300 ERPs is achieved by characterizing the EEG via corresponding stationary and time-varying Wackermann parameters. Subsets of maximally discriminating parameters are then selected using the Network Clustering feature selection algorithm and classified with Naive-Bayes and Linear Discriminant Analysis classifiers. Hence the method is assessed on two different data-sets from BCI competitions and is shown to produce accuracies of between approximately 70% and 85%. This is promising for the use of Wackermann parameters as features in the classification of single-trial ERP responses.
Resumo:
Over the last 25years, "mindblindness" (deficits in representing mental states) has been one of the primary explanations behind the hallmark social-communication difficulties in autism spectrum conditions (ASC). However, highlighting neural systems responsible for mindblindness and their relation to variation in social impairments has remained elusive. In this study we show that one of the neural systems responsible for mindblindness in ASC and its relation to social impairments is the right temporo-parietal junction (RTPJ). Twenty-nine adult males with ASC and 33 age and IQ-matched Controls were scanned with fMRI while making reflective mentalizing or physical judgments about themselves or another person. Regions of interest within mentalizing circuitry were examined for between-group differences in activation during mentalizing about self and other and correlations with social symptom severity. RTPJ was the only mentalizing region that responded atypically in ASC. In Controls, RTPJ was selectively more responsive to mentalizing than physical judgments. This selectivity for mentalizing was not apparent in ASC and generalized across both self and other. Selectivity of RTPJ for mentalizing was also associated with the degree of reciprocal social impairment in ASC. These results lend support to the idea that RTPJ is one important neural system behind mindblindness in ASC. Understanding the contribution of RTPJ in conjunction with other neural systems responsible for other component processes involved in social cognition will be illuminating in fully explaining the hallmark social-communication difficulties of autism.
Resumo:
BACKGROUND: Humans from an early age look longer at preferred stimuli, and also typically look longer at facial expressions of emotion, particularly happy faces. Atypical gaze patterns towards social stimuli are common in Autism Spectrum Conditions (ASC). However, it is unknown if gaze fixation patterns have any genetic basis. In this study, we tested if variations in the cannabinoid receptor 1 (CNR1) gene are associated with gaze duration towards happy faces. This gene was selected because CNR1 is a key component of the endocannabinoid system, involved in processing reward, and in our previous fMRI study we found variations in CNR1 modulates the striatal response to happy (but not disgust) faces. The striatum is involved in guiding gaze to rewarding aspects of a visual scene. We aimed to validate and extend this result in another sample using a different technique (gaze tracking). METHODS: 30 volunteers (13 males, 17 females) from the general population observed dynamic emotion expressions on a screen while their eye movements were recorded. They were genotyped for the identical four SNPs in the CNR1 gene tested in our earlier fMRI study. RESULTS: Two SNPs (rs806377 and rs806380) were associated with differential gaze duration for happy (but not disgust) faces. Importantly, the allelic groups associated with greater striatal response to happy faces in the fMRI study were associated with longer gaze duration for happy faces. CONCLUSIONS: These results suggest CNR1 variations modulate striatal function that underlies the perception of signals of social reward such as happy faces. This suggests CNR1 is a key element in the molecular architecture of perception of certain basic emotions. This may have implications for understanding neurodevelopmental conditions marked by atypical eye contact and facial emotion processing, such as ASC.
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To investigate the neural network of overt speech production, eventrelated fMRI was performed in 9 young healthy adult volunteers. A clustered image acquisition technique was chosen to minimize speechrelated movement artifacts. Functional images were acquired during the production of oral movements and of speech of increasing complexity (isolated vowel as well as monosyllabic and trisyllabic utterances). This imaging technique and behavioral task enabled depiction of the articulo-phonologic network of speech production from the supplementary motor area at the cranial end to the red nucleus at the caudal end. Speaking a single vowel and performing simple oral movements involved very similar activation of the corticaland subcortical motor systems. More complex, polysyllabic utterances were associated with additional activation in the bilateral cerebellum,reflecting increased demand on speech motor control, and additional activation in the bilateral temporal cortex, reflecting the stronger involvement of phonologic processing.
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The experience of pain occurs when the level of a stimulus is sufficient to elicit a marked affective response, putatively to warn the organism of potential danger and motivate appropriate behavioral responses. Understanding the biological mechanisms of the transition from innocuous to painful levels of sensation is essential to understanding pain perception as well as clinical conditions characterized by abnormal relationships between stimulation and pain response. Thus, the primary objective of this study was to characterize the neural response associated with this transition and the correspondence between that response and subjective reports of pain. Towards this goal, this study examined BOLD response profiles across a range of temperatures spanning the pain threshold. 14 healthy adults underwent functional magnetic resonance imaging (fMRI) while a range of thermal stimuli (44-49oC) were applied. BOLD responses showed a sigmoidal profile along the range of temperatures in a network of brain regions including insula and mid- cingulate, as well as a number of regions associated with motor responses including ventral lateral nuclei of the thalamus, globus pallidus and premotor cortex. A sigmoid function fit to the BOLD responses in these regions explained up to 85% of the variance in individual pain ratings, and yielded an estimate of the temperature of steepest transition from non-painful to painful heat that was nearly identical to that generated by subjective ratings. These results demonstrate a precise characterization of the relationship between objective levels of stimulation, resulting neural activation, and subjective experience of pain and provide direct evidence for a neural mechanism supporting the nonlinear transition from innocuous to painful levels along the sensory continuum.
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The dynamics of inter-regional communication within the brain during cognitive processing – referred to as functional connectivity – are investigated as a control feature for a brain computer interface. EMDPL is used to map phase synchronization levels between all channel pair combinations in the EEG. This results in complex networks of channel connectivity at all time–frequency locations. The mean clustering coefficient is then used as a descriptive feature encapsulating information about inter-channel connectivity. Hidden Markov models are applied to characterize and classify dynamics of the resulting complex networks. Highly accurate levels of classification are achieved when this technique is applied to classify EEG recorded during real and imagined single finger taps. These results are compared to traditional features used in the classification of a finger tap BCI demonstrating that functional connectivity dynamics provide additional information and improved BCI control accuracies.
Resumo:
Brain-Computer Interfacing (BCI) has been previously demonstrated to restore patient communication, meeting with varying degrees of success. Due to the nature of the equipment traditionally used in BCI experimentation (the electroencephalograph) it is mostly conned to clinical and research environments. The required medical safety standards, subsequent cost of equipment and its application/training times are all issues that need to be resolved if BCIs are to be taken out of the lab/clinic and delivered to the home market. The results in this paper demonstrate a system developed with a low cost medical grade EEG amplier unit in conjunction with the open source BCI2000 software suite thus constructing the cheapest per electrode system available, meeting rigorous clinical safety standards. Discussion of the future of this technology and future work concerning this platform are also introduced.
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In recent years, Germany has significantly increased its share of electricity produced from renewable sources, which is mainly due to the Renewable Energy Act (EEG). The EEG substantially impacts the dynamics of intra-day electricity prices by increasing the likelihood of negative prices. In this paper, we present a non-Gaussian process to model German intra-day electricity prices and propose an estimation procedure for this model. Most importantly, our model is able to generate extreme positive and negative spikes. A simulation study demonstrates the ability of our model to capture the characteristics of the data.
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Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are often comorbid and share behavioural-cognitive abnormalities in sustained attention. A key question is whether this shared cognitive phenotype is based on common or different underlying pathophysiologies. To elucidate this question, we compared 20 boys with ADHD to 20 age and IQ matched ASD and 20 healthy boys using functional magnetic resonance imaging (fMRI) during a parametrically modulated vigilance task with a progressively increasing load of sustained attention. ADHD and ASD boys had significantly reduced activation relative to controls in bilateral striato–thalamic regions, left dorsolateral prefrontal cortex (DLPFC) and superior parietal cortex. Both groups also displayed significantly increased precuneus activation relative to controls. Precuneus was negatively correlated with the DLPFC activation, and progressively more deactivated with increasing attention load in controls, but not patients, suggesting problems with deactivation of a task-related default mode network in both disorders. However, left DLPFC underactivation was significantly more pronounced in ADHD relative to ASD boys, which furthermore was associated with sustained performance measures that were only impaired in ADHD patients. ASD boys, on the other hand, had disorder-specific enhanced cerebellar activation relative to both ADHD and control boys, presumably reflecting compensation. The findings show that ADHD and ASD boys have both shared and disorder-specific abnormalities in brain function during sustained attention. Shared deficits were in fronto–striato–parietal activation and default mode suppression. Differences were a more severe DLPFC dysfunction in ADHD and a disorder-specific fronto–striato–cerebellar dysregulation in ASD.
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Despite growing evidence on the neural bases of emotion regulation, little is known about the mechanisms underlying individual differences in cognitive regulation of negative emotion, and few studies have used objective measures to quantify regulatory success. Using a trait-like psychophysiological measure of emotion regulation, corrugator electromyography, we obtained an objective index of the ability to cognitively reappraise negative emotion in 56 healthy men (session 1), who returned 1.3 years later to perform the same regulation task using fMRI (session 2). Results indicated that the corrugator measure of regulatory skill predicted amygdala-prefrontal functional connectivity. Individuals with greater ability to down-regulate negative emotion as indexed by corrugator at session 1 showed not only greater amygdala attenuation but also greater inverse connectivity between the amygdala and several sectors of the prefrontal cortex while down-regulating negative emotion at session 2. Our results demonstrate that individual differences in emotion regulation are stable over time and underscore the important role of amygdala-prefrontal coupling for successful regulation of negative emotion.
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A common procedure for studying the effects on cognition of repetitive transcranial magnetic stimulation (rTMS) is to deliver rTMS concurrent with task performance, and to compare task performance on these trials versus on trials without rTMS. Recent evidence that TMS can have effects on neural activity that persist longer than the experimental session itself, however, raise questions about the assumption of the transient nature of rTMS that underlies many concurrent (or "online") rTMS designs. To our knowledge, there have been no studies in the cognitive domain examining whether the application of brief trains of rTMS during specific epochs of a complex task may have effects that spill over into subsequent task epochs, and perhaps into subsequent trials. We looked for possible immediate spill-over and longer-term cumulative effects of rTMS in data from two studies of visual short-term delayed recognition. In 54 subjects, 10-Hz rTMS trains were applied to five different brain regions during the 3-s delay period of a spatial task, and in a second group of 15 subjects, electroencephalography (EEG) was recorded while 10-Hz rTMS was applied to two brain areas during the 3-s delay period of both spatial and object tasks. No evidence for immediate effects was found in the comparison of the memory probe-evoked response on trials that were vs. were not preceded by delay-period rTMS. No evidence for cumulative effects was found in analyses of behavioral performance, and of EEG signal, as a function of task block. The implications of these findings, and their relation to the broader literature on acute vs. long-lasting effects of rTMS, are considered.
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Current methods for estimating event-related potentials (ERPs) assume stationarity of the signal. Empirical Mode Decomposition (EMD) is a data-driven decomposition technique that does not assume stationarity. We evaluated an EMD-based method for estimating the ERP. On simulated data, EMD substantially reduced background EEG while retaining the ERP. EMD-denoised single trials also estimated shape, amplitude, and latency of the ERP better than raw single trials. On experimental data, EMD-denoised trials revealed event-related differences between two conditions (condition A and B) more effectively than trials lowpass filtered at 40 Hz. EMD also revealed event-related differences on both condition A and condition B that were clearer and of longer duration than those revealed by low-pass filtering at 40 Hz. Thus, EMD-based denoising is a promising data-driven, nonstationary method for estimating ERPs and should be investigated further.
Resumo:
The present study addresses three methodological questions that have been ignored in previous research on EEG indices of the human mirror neuron system (hMNS), particularly in regard to autistic individuals. The first question regards how to elicit the EEG indexed hMNS during movement observation: Is hMNS activation best elicited using long stimulus presentations or multiple short repetitions? The second question regards what EEG sensorimotor frequency bands reflect sensorimotor reactivity during hand movement observation? The third question regards how widespread is the EEG reactivity over the sensorimotor cortex during movement observation? The present study explored sensorimotor alpha and low beta reactivity during hand movement versus static hand or bouncing balls observation and compared two experimental protocols (long exposure vs. multiple repetitions) in the same participants. Results using the multiple repetitions protocol indicated a greater low beta desynchronisation over the sensorimotor cortex during hand movement compared to static hand and bouncing balls observation. This result was not achieved using the long exposure protocol. Therefore, the present study suggests that the multiple repetitions protocol is a more robust protocol to use when exploring the sensorimotor reactivity induced by hand action observation. In addition, sensorimotor low beta desynchronisation was differently modulated during hand movement, static hand and bouncing balls observation (non-biological motion) while it was not the case for sensorimotor alpha and that suggest that low beta may be a more sensitive index of hMNS activation during biological motion observation. In conclusion the present study indicates that sensorimotor reactivity of low beta during hand movement observation was found to be more widespread over the sensorimotor cortex than previously thought.