Jul 29, 2008
Auditory and Spatial Navigation Imagery in Brain-Computer Interface using Optimized Wavelets
Auditory and Spatial Navigation Imagery in Brain-Computer Interface using Optimized Wavelets.
J Neurosci Methods. 2008 Jul 6;
Authors: Cabrera AF, Dremstrup K
Features extracted with optimized wavelets were compared with standard methods for a Brain-Computer Interface driven by non-motor imagery tasks. Two non-motor imagery tasks were used, Auditory Imagery of a familiar tune and Spatial Navigation Imagery through a familiar environment. The aims of this study were to evaluate which method extracts features that could be best differentiated and determine which channels are best suited for classification. EEG activity from 18 electrodes over the temporal and parietal lobes of nineteen healthy subjects was recorded. The features used were autoregressive and reflection coefficients extracted using autoregressive modeling with several model orders and marginals of the wavelet spaces generated by the Discrete Wavelet Transform (DWT). An optimization algorithm with 4 and 6 taps filters and mother wavelets from the Daubechies family were used. The classification was performed for each single channel and for all possible combination of two channels using a Bayesian Classifier. The best classification results were found using the marginals of the Optimized DWT spaces for filters with 6 taps in a 2 channels classification basis. Classification using 2 channels was found to be significantly better than using 1 channel (p<<0.01). The marginals of the optimized DWT using 6 taps filters showed to be significantly better than the marginals of the Daubechies family and autoregressive coefficients. The influence of the combination of number of channels and feature extraction method over the classification results was not significant (p=0.97).
22:17 Posted in Brain training & cognitive enhancement | Permalink | Comments (0) | Tags: brain computer interface
Jul 28, 2008
Does erotic stimulus presentation design affect brain activation patterns?
Does erotic stimulus presentation design affect brain activation patterns? Event-related vs. blocked fMRI designs.
Behav Brain Funct. 2008 Jul 22;4(1):30
Authors: Buehler M, Vollstaedt-Klein S, Klemen J, Smolka MN
ABSTRACT: BACKGROUND: Existing brain imaging studies, investigating sexual arousal via the presentation of erotic pictures or film excerpts, have mainly used blocked designs with long stimulus presentation times. METHODS: To clarify how experimental functional magnetic resonance imaging (fMRI) design affects stimulus-induced brain activity, we compared brief event-related presentation of erotic vs. neutral stimuli with blocked presentation in 10 male volunteers. RESULTS: Brain activation differed depending on design type in only 10% of the voxels showing task related brain activity. Differences between blocked and event-related stimulus presentation were found in occipitotemporal and temporal regions (Brodmann Area (BA) 19, 37, 48), parietal areas (BA 7, 40) and areas in the frontal lobe (BA 6, 44). CONCLUSIONS: Our results suggest that event-related designs might be a potential alternative when the core interest is the detection of networks associated with immediate processing of erotic stimuli. Additionally, blocked, compared to event-related, stimulus presentation allows the emergence and detection of non-specific secondary processes, such as sustained attention, motor imagery and inhibition of sexual arousal.
13:18 Posted in Mental practice & mental simulation | Permalink | Comments (0) | Tags: mental simulation
Development and preliminary evaluation of a prototype audiovisual biofeedback device
Development and preliminary evaluation of a prototype audiovisual biofeedback device incorporating a patient-specific guiding waveform.
Phys Med Biol. 2008 May 12;53(11):N197-N208
Authors: Venkat RB, Sawant A, Suh Y, George R, Keall PJ
The aim of this research was to investigate the effectiveness of a novel audio-visual biofeedback respiratory training tool to reduce respiratory irregularity. The audiovisual biofeedback system acquires sample respiratory waveforms of a particular patient and computes a patient-specific waveform to guide the patient's subsequent breathing. Two visual feedback models with different displays and cognitive loads were investigated: a bar model and a wave model. The audio instructions were ascending/descending musical tones played at inhale and exhale respectively to assist in maintaining the breathing period. Free-breathing, bar model and wave model training was performed on ten volunteers for 5 min for three repeat sessions. A total of 90 respiratory waveforms were acquired. It was found that the bar model was superior to free breathing with overall rms displacement variations of 0.10 and 0.16 cm, respectively, and rms period variations of 0.77 and 0.33 s, respectively. The wave model was superior to the bar model and free breathing for all volunteers, with an overall rms displacement of 0.08 cm and rms periods of 0.2 s. The reduction in the displacement and period variations for the bar model compared with free breathing was statistically significant (p = 0.005 and 0.002, respectively); the wave model was significantly better than the bar model (p = 0.006 and 0.005, respectively). Audiovisual biofeedback with a patient-specific guiding waveform significantly reduces variations in breathing. The wave model approach reduces cycle-to-cycle variations in displacement by greater than 50% and variations in period by over 70% compared with free breathing. The planned application of this device is anatomic and functional imaging procedures and radiation therapy delivery.
13:17 Posted in Biofeedback & neurofeedback | Permalink | Comments (0) | Tags: biofeedback, neurofeedback
Energetic assessment of trunk postural modifications induced by a wearable audio-biofeedback system
Energetic assessment of trunk postural modifications induced by a wearable audio-biofeedback system.
Med Eng Phys. 2008 Jul 2;
Authors: Giansanti D, Dozza M, Chiari L, Maccioni G, Cappello A
13:16 Posted in Biofeedback & neurofeedback | Permalink | Comments (0) | Tags: biofeedback, neurofeedback




