Psychophysiological Assessment of Buddhist Taiwanese Chanting

The psychophysiological responses and subjective experience correlates of Buddhist chanting were recorded from a 54 year-old female Buddhist monk who performed chanting for approximately 30 to 60 minutes twice daily for 25 years. The measutes included respiration rate from upper thorax, blood volume pulse (BVP) from left middle finger with heart rate derived from BVP, finger temperature from right index finger, skin conductance (SC) from the left index finger and the ring finger and sutface electromyographic (sEMG) from right trapezius and left sternocleidomastoid muscles (SCM) and were recorded during normal chanting sequence which included reading sutra aloud with her eyes open (chanting "The Samanta-Mukha") and silent mental repetition of sutra with the eyes closed (chanting "The Heart Sutra" inside her mind). After chanting she reported feeling peaceful, more relaxation with a total focus of attention and "consciousness"-an experience that was similar to when she chanted in the temple with other monks. The most significant finding was that respiration rate changed from 7.2 br/min during pre-baseline, to 12.1 brlmin during reading sutra aloud, 5.7 brlmin during silent mental repetition of sutra and 7.5 brl/min during post-baseline. Respiratory sinus arrhythmia (RSA) was significantly higher during post-baseline than reading chanting and silent mental repetition of sutra. All physiological measures were significantly different for each condition. This study suggests that the subjective experience associated with chanting can not be attributed to increased RSA and slower breathing as it depends upon the style of chanting. The spiritual experience associated with chanting appears to be evoked through the focused attention on the sutra

Informational and Neuromuscular Contributions to Anchoring in Rhythmic Wrist Cycling

Continuous rhythmic movements are often geared toward particular points in the movement cycle, as evidenced by a local reduction in trajectory variability. These so-called anchor points provide a window into motor control, since changes in the degree of anchoring may reveal how informational and/or neuromuscular properties are exploited in the organization of rhythmic movements. The present experiment examined the relative contributions of informational timing (metronome beeps) and neuromuscular (wrist postures) constraints on anchoring by systematically varying both factors at movement reversal points. To this end, participants cycled their right wrist in a flexed, neutral, or extended posture, either self-paced or synchronized to a metronome pacing peak flexion, peak extension, or both peak flexion and extension. The effects of these manipulations were assessed in terms of kinematics, auditory-motor coordination, and muscle activity. The degree of anchoring seen at the reversal points depended on the degree of compatibility of the prevailing configuration of neuromuscular and informational timing constraints, which had largely independent effects. We further observed systematic changes in muscular activity, which revealed distinct contributions of posture- and muscle-dependent neuromuscular properties to motor control. These findings indicate that the anchor-based discretization of the control of continuous rhythmic wrist movements is determined by both informational timing and neuromuscular constraints in a task-specific manner with subtle interactions between the two, and exemplify how movement variability may be exploited to gain such insights

Visuomotor transformation for interception: catching while fixating

Catching a ball involves a dynamic transformation of visual information about ball motion into motor commands for moving the hand to the right place at the right time. We previously formulated a neural model for this transformation to account for the consistent leftward movement biases observed in our catching experiments. According to the model, these biases arise within the representation of target motion as well as within the transformation from a gaze-centered to a body-centered movement command. Here, we examine the validity of the latter aspect of our model in a catching task involving gaze fixation. Gaze fixation should systematically influence biases in catching movements, because in the model movement commands are only generated in the direction perpendicular to the gaze direction. Twelve participants caught balls while gazing at a fixation point positioned either straight ahead or 14° to the right. Four participants were excluded because they could not adequately maintain fixation. We again observed a consistent leftward movement bias, but the catching movements were unaffected by fixation direction. This result refutes our proposal that the leftward bias partly arises within the visuomotor transformation, and suggests instead that the bias predominantly arises within the early representation of target motion, specifically through an imbalance in the represented radial and azimuthal target motion

Visual and musculoskeletal underpinnings of anchoring in rhythmic visuo-motor tracking

Anchoring, that is, a local reduction in kinematic (i.e., spatio-temporal) variability, is commonly observed in cyclical movements, often at or around reversal points. Two kinds of underpinnings of anchoring have been identified—visual and musculoskeletal—yet their relative contributions and interrelations are largely unknown. We conducted an experiment to delineate the effects of visual and musculoskeletal factors on anchoring behavior in visuo-motor tracking. Thirteen participants (reduced to 12 in the analyses) tracked a sinusoidally moving visual target signal by making flexion–extension movements about the wrist, while both visual (i.e., gaze direction) and musculoskeletal (i.e., wrist posture) factors were manipulated in a fully crossed (3 × 3) design. Anchoring was affected by both factors in the absence of any significant interactions, implying that their contributions were independent. When gaze was directed to one of the target turning points, spatial endpoint variability at this point was reduced, but not temporal endpoint variability. With the wrist in a flexed posture, spatial and temporal endpoint variability were both smaller for the flexion endpoint than for the extension endpoint, while the converse was true for tracking with the wrist extended. Differential anchoring effects were absent for a neutral wrist posture and when gaze was fixated in between the two target turning points. Detailed analyses of the tracking trajectories in terms of velocity profiles and Hooke’s portraits showed that the tracking dynamics were affected more by wrist posture than by gaze direction. The discussion focuses on the processes underlying the observed independent effects of gaze direction and wrist posture on anchoring as well as their implications for the notion of anchoring as a generic feature of sensorimotor coordination

A Re-Appraisal of the Effect of Amplitude on the Stability of Interlimb Coordination Based on Tightened Normalization Procedures

The stability of rhythmic interlimb coordination is governed by the coupling between limb movements. While it is amply documented how coordinative performance depends on movement frequency, theoretical considerations and recent empirical findings suggest that interlimb coupling (and hence coordinative stability) is actually mediated more by movement amplitude. Here, we present the results of a reanalysis of the data of Post, Peper, and Beek (2000), which were collected in an experiment aimed at teasing apart the effects of frequency and amplitude on coordinative stability of both steady-state and perturbed in-phase and antiphase interlimb coordination. The dataset in question was selected because we found indications that the according results were prone to artifacts, which may have obscured the potential effects of amplitude on the post-perturbation stability of interlimb coordination. We therefore redid the same analysis based on movement signals that were normalized each half-cycle for variations in oscillation center and movement frequency. With this refined analysis we found that (1) stability of both steady-state and perturbed coordination indeed seemed to depend more on amplitude than on movement frequency per se, and that (2) whereas steady-state antiphase coordination became less stable with increasing frequency for prescribed amplitudes, in-phase coordination became more stable at higher frequencies. Such effects may have been obscured in previous studies due to (1) unnoticed changes in performed amplitudes, and/or (2) artifacts related to inappropriate data normalization. The results of the present reanalysis therefore give cause for reconsidering the relation between the frequency, amplitude, and stability of interlimb coordination

Cognitive Information Processing

Contains reports on six research projects.National Institutes of Health (Grant 5 PO1 GM14940-03)National Institutes of Health (Grant 5 PO1 GM15006-03)Joint Services Electronics Programs (U. S. Army, U. S. Navy, and U.S. Air Force) under Contract DA 28-043-AMC-02536(E)National Institutes of Health (Grant 5 TO1 GM01555-03

Stress detection using wearable physiological sensors

As the population increases in the world, the ratio of health carers is rapidly decreasing. Therefore, there is an urgent need to create new technologies to monitor the physical and mental health of people during their daily life. In particular, negative mental states like depression and anxiety are big problems in modern societies, usually due to stressful situations during everyday activities including work. This paper presents a machine learning approach for stress detection on people using wearable physiological sensors with the �final aim of improving their quality of life. The presented technique can monitor the state of the subject continuously and classify it into "stressful" or "non-stressful" situations. Our classification results show that this method is a good starting point towards real-time stress detection

Cognitive Information Processing

Contains reports on six research projects.National Institutes of Health (Grant 5 PO1 GM14940-04)National Institutes of Health (Grant 5 PO1 GM15006-03)Joint Services Electronics Programs (U. S. Army, U. S. Navy, and U. S. Air Force) under Contract DA 28-043-AMC-02536(E