Zazen meditation and no-task resting EEG compared with LORETA intracortical source localization

Meditation is a self-induced and willfully initiated practice that alters the state of consciousness. The meditation practice of Zazen, like many other meditation practices, aims at disregarding intrusive thoughts while controlling body posture. It is an open monitoring meditation characterized by detached moment-to-moment awareness and reduced conceptual thinking and self-reference. Which brain areas differ in electric activity during Zazen compared to task-free resting? Since scalp electroencephalography (EEG) waveforms are reference-dependent, conclusions about the localization of active brain areas are ambiguous. Computing intracerebral source models from the scalp EEG data solves this problem. In the present study, we applied source modeling using low resolution brain electromagnetic tomography (LORETA) to 58-channel scalp EEG data recorded from 15 experienced Zen meditators during Zazen and no-task resting. Zazen compared to no-task resting showed increased alpha-1 and alpha-2 frequency activity in an exclusively right-lateralized cluster extending from prefrontal areas including the insula to parts of the somatosensory and motor cortices and temporal areas. Zazen also showed decreased alpha and beta-2 activity in the left angular gyrus and decreased beta-1 and beta-2 activity in a large bilateral posterior cluster comprising the visual cortex, the posterior cingulate cortex and the parietal cortex. The results include parts of the default mode network and suggest enhanced automatic memory and emotion processing, reduced conceptual thinking and self-reference on a less judgmental, i.e., more detached moment-to-moment basis during Zazen compared to no-task resting.

Emotional stability promotes intelligence

Emotional stability promotes intelligence In the research field of the relationship between intelligence and personality factors, one of the most consistent findings is that intelligence is positively correlated with emotional stability. However, few studies have considered this relationship in children, and very few have differentiated between types of intelligence as well as underlying differences in working memory capacity when explaining the relationship between intelligence scores and emotional stability. In this study, the level of emotional stability and performance in a proxy for fluid and crystallized intelligence as well as in two working memory tasks was assessed in a sample of 397 primary school children. Results reveal that emotional stability is significantly positively related to vocabulary (crystallized intelligence), moderated by high working memory performance, but unrelated to abstract reasoning (fluid intelligence). This was interpreted as indicating that the positive relationship between intelligence and emotional stability is mainly due to learning advantages starting in early age, due to high working memory performance, rather than to higher general intelligence. This bears the important implication that emotionally labile children (high level of neuroticism) should be supported to regulate their negative emotions, intrusive thoughts and anxiety as early as possible to eliminate progressive learning disadvantages. One approach to do so is by specific working memory training targeting the improvement of emotional regulation skills.

Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts

Prompted reports of recall of spontaneous, conscious experiences were collected in a no-input, no-task, no-response paradigm (30 random prompts to each of 13 healthy volunteers). The mentation reports were classified into visual imagery and abstract thought. Spontaneous 19-channel brain electric activity (EEG) was continuously recorded, viewed as series of momentary spatial distributions (maps) of the brain electric field and segmented into microstates, i.e. into time segments characterized by quasi-stable landscapes of potential distribution maps which showed varying durations in the sub-second range. Microstate segmentation used a data-driven strategy. Different microstates, i.e. different brain electric landscapes must have been generated by activity of different neural assemblies and therefore are hypothesized to constitute different functions. The two types of reported experiences were associated with significantly different microstates (mean duration 121 ms) immediately preceding the prompts; these microstates showed, across subjects, for abstract thought (compared to visual imagery) a shift of the electric gravity center to the left and a clockwise rotation of the field axis. Contrariwise, the microstates 2 s before the prompt did not differ between the two types of experiences. The results support the hypothesis that different microstates of the brain as recognized in its electric field implement different conscious, reportable mind states, i.e. different classes (types) of thoughts (mentations); thus, the microstates might be candidates for the `atoms of thought'.

Beyond words: Sensory properties of depressive thoughts

Verbal thoughts (such as negative cognitions) and sensory phenomena (such as visual mental imagery) are usually conceptualised as distinct mental experiences. The present study examined to what extent depressive thoughts are accompanied by sensory experiences and how this is associated with symptom severity, insight of illness and quality of life. A large sample of mildly to moderately depressed patients (N = 356) was recruited from multiple sources and asked about sensory properties of their depressive thoughts in an online study. Diagnostic status and symptom severity were established over a telephone interview with trained raters. Sensory properties of negative thoughts were reported by 56.5% of the sample (i.e., sensation in at least one sensory modality). The highest prevalence was seen for bodily (39.6%) followed by auditory (30.6%) and visual (27.2%) sensations. Patients reporting sensory properties of thoughts showed more severe psychopathological symptoms than those who did not. The degree of perceptuality was marginally associated with quality of life. The findings support the notion that depressive thoughts are not only verbal but commonly accompanied by sensory experiences. The perceptuality of depressive thoughts and the resulting sense of authenticity may contribute to the emotional impact and pervasiveness of such thoughts, making them difficult to dismiss for their holder.

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.