Stratification of responses to tDCS intervention in a healthy pediatric population based on resting-state EEG profiles.

Transcranial Direct Current Stimulation (tDCS) is a non-invasive neuromodulation technique with a wide variety of clinical and research applications. As increasingly acknowledged, its effectiveness is subject dependent, which may lead to time consuming and cost ineffective treatment development phases. We propose the combination of electroencephalography (EEG) and unsupervised learning for the stratification and prediction of individual responses to tDCS. A randomized, sham-controlled, double-blind crossover study design was conducted within a clinical trial for the development of pediatric treatments based on tDCS. The tDCS stimulation (sham and active) was applied either in the left dorsolateral prefrontal cortex or in the right inferior frontal gyrus. Following the stimulation session, participants performed 3 cognitive tasks to assess the response to the intervention: the Flanker Task, N-Back Task and Continuous Performance Test (CPT). We used data from 56 healthy children and adolescents to implement an unsupervised clustering approach that stratify participants based on their resting-state EEG spectral features before the tDCS intervention. We then applied a correlational analysis to characterize the clusters of EEG profiles in terms of participant's difference in the behavioral outcome (accuracy and response time) of the cognitive tasks when performed after a tDCS-sham or a tDCS-active session. Better behavioral performance following the active tDCS session compared to the sham tDCS session is considered a positive intervention response, whilst the reverse is considered a negative one. Optimal results in terms of validity measures was obtained for 4 clusters. These results show that specific EEG-based digital phenotypes can be associated to particular responses. While one cluster presents neurotypical EEG activity, the remaining clusters present non-typical EEG characteristics, which seem to be associated with a positive response. Findings suggest that unsupervised machine learning can be successfully used to stratify and eventually predict responses of individuals to a tDCS treatment.

Author Correction: Hypnotic analgesia reduces brain responses to pain seen in others.

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Hypnotic analgesia reduces brain responses to pain seen in others.

Brain responses to pain experienced by oneself or seen in other people show consistent overlap in the pain processing network, particularly anterior insula, supporting the view that pain empathy partly relies on neural processes engaged by self-nociception. However, it remains unresolved whether changes in one's own pain sensation may affect empathic responding to others' pain. Here we show that inducing analgesia through hypnosis leads to decreased responses to both self and vicarious experience of pain. Activations in the right anterior insula and amygdala were markedly reduced when participants received painful thermal stimuli following hypnotic analgesia on their own hand, but also when they viewed pictures of others' hand in pain. Functional connectivity analysis indicated that this hypnotic modulation of pain responses was associated with differential recruitment of right prefrontal regions implicated in selective attention and inhibitory control. Our results provide novel support to the view that self-nociception is involved during empathy for pain, and demonstrate the possibility to use hypnotic procedures to modulate higher-level emotional and social processes.

Increased Gamma Brainwave Amplitude Compared to Control in Three Different Meditation Traditions.

Despite decades of research, effects of different types of meditation on electroencephalographic (EEG) activity are still being defined. We compared practitioners of three different meditation traditions (Vipassana, Himalayan Yoga and Isha Shoonya) with a control group during a meditative and instructed mind-wandering (IMW) block. All meditators showed higher parieto-occipital 60-110 Hz gamma amplitude than control subjects as a trait effect observed during meditation and when considering meditation and IMW periods together. Moreover, this gamma power was positively correlated with participants meditation experience. Independent component analysis was used to show that gamma activity did not originate in eye or muscle artifacts. In addition, we observed higher 7-11 Hz alpha activity in the Vipassana group compared to all the other groups during both meditation and instructed mind wandering and lower 10-11 Hz activity in the Himalayan yoga group during meditation only. We showed that meditation practice is correlated to changes in the EEG gamma frequency range that are common to a variety of meditation practices.

Oculometric variations during mind wandering.

A significant body of literature supports the contention that pupil size varies depending on cognitive load, affective state, and level of drowsiness. Here we assessed whether oculometric measures such as gaze position, blink frequency and pupil size were correlated with the occurrence and time course of self-reported mind-wandering episodes. We recorded the pupil size of two subjects engaged in a monotonous breath counting task while keeping their eyes on a fixation cross. This task is conducive to producing mind-wandering episodes. Each subject performed ten 20-min sessions, for total duration of about 4 h. Subjects were instructed to report spontaneous mind-wandering episodes by pressing a button when they lost count of their breath. After each button press, subjects filled in a short questionnaire describing the characteristics of their mind-wandering episode. We observed larger pupil size during the breath-focusing period compared to the mind-wandering period (p < 0.01 for both subjects). Our findings contradict previous research showing a higher baseline pupil size during mind wandering episodes in visual tasks. We discuss possible explanations for this discrepancy. We also analyzed nine other oculometric measures including blink rate, blink duration and gaze position. We built a support vector machine (SVM) classifier and showed that mean pupil size was the most reliable predictor of mind wandering in both subjects. The classification accuracy of mind wandering data segments vs. breath-focusing data segments was 81% for the first subject and 77% for the second subject. Additionally, we analyzed oculometric measures in light of the phenomenological data collected in the questionnaires. We showed that how well subjects remembered their thoughts while mind wandering was positively correlated with pupil size (subject 1, p < 0.001; subject 2, p < 0.05). Feelings of well being were also positively correlated with pupil size (subject 1, p < 0.001; subject 2, p < 0.001). Our results suggest that oculometric data could be used as a neurocognitive marker of mind-wandering episodes.

Plasticity of visual attention in Isha yoga meditation practitioners before and after a 3-month retreat.

Meditation has lately received considerable interest from cognitive neuroscience. Studies suggest that daily meditation leads to long lasting attentional and neuronal plasticity. We present changes related to the attentional systems before and after a 3 month intensive meditation retreat. We used three behavioral psychophysical tests - a Stroop task, an attentional blink task, and a global-local letter task-to assess the effect of Isha yoga meditation on attentional resource allocation. 82 Isha yoga practitioners were tested at the beginning and at the end of the retreat. Our results showed an increase in correct responses specific to incongruent stimuli in the Stroop task. Congruently, a positive correlation between previous meditation experience and accuracy to incongruent Stroop stimuli was also observed at baseline. We also observed a reduction of the attentional blink. Unexpectedly, a negative correlation between previous meditation experience and attentional blink performance at baseline was observed. Regarding spatial attention orientation as assessed using the global-local letter task, participants showed a bias toward local processing. Only slight differences in performance were found pre- vs. post- meditation retreat. Biasing toward the local stimuli in the global-local task and negative correlation of previous meditation experience with attentional blink performance is consistent with Isha practices being focused-attention practices. Given the relatively small effect sizes and the absence of a control group, our results do not allow clear support nor rejection of the hypothesis of meditation-driven neuronal plasticity in the attentional system for Isha yoga practice.

Stability of ICA decomposition across within-subject EEG datasets.

Independent Component Analysis (ICA) has been successfully used to identify brain related signals and artifacts from multi-channel electroencephalographic (EEG) data. However the stability of ICA decompositions across sessions from a single subject has not been investigated. The goal of this study was to isolate EEG independent components (ICs) across sessions for each subject so as to assess whether ICs are reproducible across sessions. We used 64-channel EEG data recorded from two subjects during a simple mind-wandering experiment. Each subject participated in 11 twenty-minute sessions over a period of five weeks. Extended Infomax ICA decomposition was performed on the continuous data of each session. We used a simple IC clustering technique based on correlation of scalp topographies. Several clusters of homogenous components were identified for each subject. Typical component clusters accounting for eye movement and eye blink artifacts were identified. Both clusters included one component from each recording session. In addition, several clusters corresponding to brain electrical sources, among them clusters exhibiting prominent alpha, beta and Mu band activities, included components from most sessions. These results present evidence that ICA can provide relatively stable solutions across sessions, with important implications for Brain Computer Interface research.

Lost in thoughts: neural markers of low alertness during mind wandering.

During concentration tasks, spontaneous attention shifts occurs towards self-centered matters. Little is known about the brain oscillatory activity underlying these mental phenomena. We recorded 128-channels electroencephalographic activity from 12 subjects performing a breath-counting task. Subjects were instructed to press a button whenever, based on their introspective experience, they realized their attention had drifted away from the task. Theta (4-7 Hz) and delta (2-3.5 Hz) EEG activity increased during mind wandering whereas alpha (9-11 Hz) and beta (15-30 Hz) decreased. A passive auditory oddball protocol was presented to the subjects to test brain-evoked responses to perceptual stimuli during mind wandering. Mismatch negativity evoked at 100 ms after oddball stimuli onset decreased during mind wandering whereas the brain-evoked responses at 200 ms after stimuli onset increased. Spectral analyses and evoked related potential results suggest decreased alertness and sensory processing during mind wandering. To our knowledge, our experiment is one of the first neuro-imaging studies that relies purely on subjects' introspective judgment, and shows that such judgment may be used to contrast different brain activity patterns.