The feedback correct-related positivity : sensitivity of the event-related brain potential to unexpected positive feedback

The N200 and the feedback error-related negativity (fERN) are two components of the event-related brain potential (ERP) that share similar scalp distributions, time courses, morphologies, and functional dependencies, which raises the question as to whether they are actually the same phenomenon. To investigate this issue, we recorded the ERP from participants engaged in two tasks that independently elicited the N200 and fERN. Our results indicate that they are, in fact, the same ERP component and further suggest that positive feedback elicits a positive-going deflection in the time range of the fERN. Taken together, these results indicate that negative feedback elicits a common N200 and that modulation of fERN amplitude results from the superposition on correct trials of a positive-going deflection that we term the feedback correct-related positivity

Newborns discriminate novel from harmonic sounds: a study using magnetoencephalography

Objective: We investigated whether newborns respond differently to novel and deviant sounds during quiet sleep. Methods: Twelve healthy neonates were presented with a three-stimulus oddball paradigm, consisting of frequent standard (76%), infrequent deviant (12%), and infrequent novel stimuli (12%). The standards and deviants were counterbalanced between the newborns and consisted of 500 and 750 Hz tones with two upper harmonics. The novel stimuli contained animal, human, and mechanical sounds. All stimuli had a duration of 300 ms and the stimulus onset asynchrony was 1 s. Evoked magnetic responses during quiet sleep were recorded and averaged offline. Results: Two deflections peaking at 345 and 615 ms after stimulus onset were observed in the evoked responses of most of the newborns. The first deflection was larger to novel and deviant stimuli than to the standard and, furthermore, larger to novel than to deviant stimuli. The second deflection was larger to novel and deviant stimuli than to standards, but did not differ between the novels and deviants. Conclusions: The two deflections found in the present study reflect different mechanisms of auditory change detection and discriminative processes. Significance: The early brain indicators of novelty detection may be crucial in assessing the normal and abnormal cortical function in newborns. Further, studying evoked magnetic fields to complex auditory stimulation in healthy newborns is needed for studying the newborns at-risk for cognitive or language problems

Comparison of an open-hardware electroencephalography amplifier with medical grade device in brain-computer interface applications

Brain-computer interfaces (BCI) are promising communication devices between humans and machines. BCI based on non-invasive neuroimaging techniques such as electroencephalography (EEG) have many applications , however the dissemination of the technology is limited, in part because of the price of the hardware. In this paper we compare side by side two EEG amplifiers, the consumer grade OpenBCI and the medical grade g.tec g.USBamp. For this purpose, we employed an original montage, based on the simultaneous recording of the same set of electrodes. Two set of recordings were performed. During the first experiment a simple adapter with a direct connection between the amplifiers and the electrodes was used. Then, in a second experiment, we attempted to discard any possible interference that one amplifier could cause to the other by adding "ideal" diodes to the adapter. Both spectral and temporal features were tested -- the former with a workload monitoring task, the latter with an visual P300 speller task. Overall, the results suggest that the OpenBCI board -- or a similar solution based on the Texas Instrument ADS1299 chip -- could be an effective alternative to traditional EEG devices. Even though a medical grade equipment still outperforms the OpenBCI, the latter gives very close EEG readings, resulting in practice in a classification accuracy that may be suitable for popularizing BCI uses.Comment: PhyCS - International Conference on Physiological Computing Systems, Jul 2016, Lisbon, Portugal. SCITEPRESS, 201

Temporal regularity effects on pre-attentive and attentive processing of deviance

Temporal regularity allows predicting the temporal locus of future information thereby potentially facilitating cognitive processing. We applied event-related brain potentials (ERPs) to investigate how temporal regularity impacts pre-attentive and attentive processing of deviance in the auditory modality. Participants listened to sequences of sinusoidal tones differing exclusively in pitch. The inter-stimulus interval (ISI) in these sequences was manipulated to convey either isochronous or random temporal structure. In the pre-attentive session, deviance processing was unaffected by the regularity manipulation as evidenced in three event-related-potentials (ERPs): mismatch negativity (MMN), P3a, and reorienting negativity (RON). In the attentive session, the P3b was smaller for deviant tones embedded in irregular temporal structure, while the N2b component remained unaffected. These findings confirm that temporal regularity can reinforce cognitive mechanisms associated with the attentive processing of deviance. Furthermore, they provide evidence for the dynamic allocation of attention in time and dissociable pre-attentive and attention-dependent temporal processing mechanisms

Mind over chatter: plastic up-regulation of the fMRI alertness network by EEG neurofeedback

EEG neurofeedback (NFB) is a brain-computer interface (BCI) approach used to shape brain oscillations by means of real-time feedback from the electroencephalogram (EEG), which is known to reflect neural activity across cortical networks. Although NFB is being evaluated as a novel tool for treating brain disorders, evidence is scarce on the mechanism of its impact on brain function. In this study with 34 healthy participants, we examined whether, during the performance of an attentional auditory oddball task, the functional connectivity strength of distinct fMRI networks would be plastically altered after a 30-min NFB session of alpha-band reduction (n=17) versus a sham-feedback condition (n=17). Our results reveal that compared to sham, NFB induced a specific increase of functional connectivity within the alertness/salience network (dorsal anterior and mid cingulate), which was detectable 30 minutes after termination of training. Crucially, these effects were significantly correlated with reduced mind-wandering 'on-task' and were coupled to NFB-mediated resting state reductions in the alpha-band (8-12 Hz). No such relationships were evident for the sham condition. Although group default-mode network (DMN) connectivity was not significantly altered following NFB, we observed a positive association between modulations of resting alpha amplitude and precuneal connectivity, both correlating positively with frequency of mind-wandering. Our findings demonstrate a temporally direct, plastic impact of NFB on large-scale brain functional networks, and provide promising neurobehavioral evidence supporting its use as a noninvasive tool to modulate brain function in health and disease

Feeling happy enhances early spatial encoding of peripheral information automatically: electrophysiological time-course and neural sources.

Previous research has shown that positive mood may broaden attention, although it remains unclear whether this effect has a perceptual or a postperceptual locus. In this study, we addressed this question using high-density event-related potential methods. We randomly assigned participants to a positive or a neutral mood condition. Then they performed a demanding oddball task at fixation (primary task ensuring fixation) and a localization task of peripheral stimuli shown at three positions in the upper visual field (secondary task) concurrently. While positive mood did not influence behavioral performance for the primary task, it did facilitate stimulus localization on the secondary task. At the electrophysiological level, we found that the amplitude of the C1 component (reflecting an early retinotopic encoding of the stimulus in V1) was enhanced in the positive, as compared with the neutral, mood group. Importantly, this effect appeared to be largely automatic, because it occurred regardless of the task relevance of the peripheral stimulus and prior to top-down gain control effects seen at the level of the subsequent P1 component. This early effect was also observed irrespective of a change of the target-related P300 component (primary task) by positive mood. These results suggest that positive mood can automatically boost the spatial encoding of peripheral stimuli early on following stimulus onset. This effect can eventually underlie the broadening of spatial attention, which has been associated with this specific mood state

Using EEG and NIRS for brain-computer interface and cognitive performance measures: a pilot study

This study addresses two important problem statements, namely, selection of training datasets for online Brain-Computer Interface (BCI) classifier training and determination of participant concentration levels during an experiment. The work also attempted a pilot study to integrate electroencephalograms (EEGs) and Near Infra Red Spectroscopy (NIRS) for possible applications such as the BCI and for measuring cognitive levels. Two experiments are presented, the first being a mathematical task interleaved with rest states using NIRS only. In the next, integration of the EEG-NIRS with reference to P300-based BCI systems as well as the experimental conditions designed to elicit the concentration levels (denoted as ON and OFF states here) during the paradigm, are presented. The first experiment indicates that NIRS can be used to differentiate a concentrated (i.e., mental activity) level from the rest. However, the second experiment reveals statistically significant results using the EEG only. We present details about the equipment used, the participants as well as the signal processing and machine learning techniques implemented to analyse the EEG and NIRS data. After discussing the results, we conclude by describing the research scope as well as the possible pitfalls in this work from a NIRS viewpoint, which presents an opportunity for future research exploration for BCI and cognitive performance measures