Gamma-band neural synchrony due to autobiographical fact violation in a self-referential question

Progressive Increase of High-Frequency EEG Oscillations during Meditation is Associated with its Trait Effects on Heart Rate and Proteomics: A Study on the Tibetan Buddhist

Meditation has been a spiritual and healing practice in the East for thousands of years. However, the neurophysiologic mechanisms underlying its traditional form remain unclear. In this study, we recruited a large sample of monks (n = 73) who practice Tibetan Buddhist meditation and compared with meditation-naive local controls (n = 30). Their electroencephalography (EEG) and electrocardiogram signals were simultaneously recorded and blood samples were collected to investigate the integrative effects of Tibetan Buddhist on brain, heart, and proteomics. We found that the EEG activities in monks shifted to a higher frequency from resting to meditation. Meditation starts with decrease of the (pre)frontal delta activity and increase of the (pre)frontal high beta and gamma activity; while at the deep meditative state, the posterior high-frequency activity was also increased, and could be specified as a biomarker for the deep meditation. The state increase of posterior high-frequency EEG activity was significantly correlated with the trait effects on heart rate and nueropilin-1 in monks, with the source of brain-heart correlation mainly locating in the attention and emotion networks. Our study revealed that the effects of Tibetan Buddhist meditation on brain, heart, and proteomics were highly correlated, demonstrating meditation as an integrative body-mind training.

Covert Intention to Answer "Yes" or "No" Can Be Decoded from Single-Trial Electroencephalograms (EEGs)

Interpersonal communication is based on questions and answers, and the most useful and simplest case is the binary “yes or no” question and answer. The purpose of this study is to show that it is possible to decode intentions on “yes” or “no” answers from multichannel single-trial electroencephalograms, which were recorded while covertly answering to self-referential questions with either “yes” or “no.” The intention decoding algorithm consists of a common spatial pattern and support vector machine, which are employed for the feature extraction and pattern classification, respectively, after dividing the overall time-frequency range into subwindows of 200 ms × 2 Hz. The decoding accuracy using the information within each subwindow was investigated to find useful temporal and spectral ranges and found to be the highest for 800–1200 ms in the alpha band or 200–400 ms in the theta band. When the features from multiple subwindows were utilized together, the accuracy was significantly increased up to ∼86%. The most useful features for the “yes/no” discrimination was found to be focused in the right frontal region in the theta band and right centroparietal region in the alpha band, which may reflect the violation of autobiographic facts and higher cognitive load for “no” compared to “yes.” Our task requires the subjects to answer self-referential questions just as in interpersonal conversation without any self-regulation of the brain signals or high cognitive efforts, and the “yes” and “no” answers are decoded directly from the brain activities. This implies that the “mind reading” in a true sense is feasible. Beyond its contribution in fundamental understanding of the neural mechanism of human intention, the decoding of “yes” or “no” from brain activities may eventually lead to a natural brain-computer interface.

THE POWER OF NEURAL OSCILLATIONS TO INFORM SENTENCE COMPREHENSION: A LINGUISTIC PERSPECTIVE

The field of psycholinguistics is currently experiencing an explosion of interest in the analysis of neural oscillations - rhythmic brain activity synchronized at different temporal and spatial levels. Given that language comprehension relies on a myriad of processes, which are carried out in parallel in distributed brain networks, there is hope that this methodology might bring the field closer to understanding some of the more basic (spatially and temporally distributed, yet at the same time often overlapping) neural computations that support language function. In this review we discuss existing proposals linking oscillatory dynamics in different frequency bands to basic neural computations, and review relevant theories suggesting associations between band-specific oscillations and higher-level cognitive processes. More or less consistent patterns of oscillatory activity related to certain types of linguistic processing can already be derived from the evidence that has accumulated over the past few decades. The centerpiece of the current review is a synthesis of such patterns grouped by linguistic phenomenon. We restrict our review to evidence linking measures of oscillatory power to the comprehension of sentences, as well as linguistically (and/or pragmatically) more complex structures. For each grouping, we provide a brief summary and a table of associated oscillatory signatures that a psycholinguist might expect to find when employing a particular linguistic task. Summarizing across different paradigms, we conclude that a handful of basic neural oscillatory mechanisms are likely recruited in different ways and at different times for carrying out a variety of linguistic computations.

Covert Intention to Answer to Self-Referential Questions Is Represented in Alpha-Band Local and Interregional Neural Synchronies

The most fundamental and simplest intention for interpersonal communication may be the intentions to answer “yes” or “no” to a question, based on a binary decision. However, the neural mechanism of this type of intention has not been investigated in detail. The main purpose of this study was to investigate cortical processing of the “yes/no” intentions to answer self-referential questions. Multichannel electroencephalograms (EEGs) were recorded while covertly answering self-referential questions with either “yes” or “no”. Event-related spectral perturbation (ERSP) and interregional phase synchrony (PS) were investigated to identify the differences in local and global neural synchronies between two intentions. We found that the local and interregional neural synchronies in the alpha-band were significantly different between “yes” and “no,” especially at the period of retaining the intention in mind, which was greater for “no” than for “yes.” These results can be interpreted to signify that a higher cognitive load during working memory retention or higher attentional demand is required for the “no” intention compared to “yes.” Our findings suggest that both local and global neural synchronies in the alpha-band may be significantly differentiated during a critical temporal epoch, according to the contents of the mental representation of the intention.