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Jul 28, 2006

Neurofeedback for children with ADHD: a comparison of SCP- and theta/beta-protocols

Neurofeedback for children with ADHD: a comparison of SCP- and theta/beta-protocols

Prax Kinderpsychol Kinderpsychiatr. 2006;55(5):384-407

Authors: Leins U, Hinterberger T, Kaller S, Schober F, Weber C, Strehl U

Research groups have consistently reported on behavioral and cognitive improvements of children with ADHD after neurofeedback. However, neurofeedback has not been commonly accepted as a treatment for ADHD. This is due, in part, to several methodological limitations. The neurofeedback literature is further complicated by having several different training protocols. Differences between the clinical efficacy of such protocols have not been examined. This study addresses previous methodological shortcomings while comparing the training of theta-beta-frequencies (theta-beta-group) with the training of slow cortical potentials (SCP-group). Each group comprised of 19 children with ADHD that were blind to group assignment. The training procedure consisted of 30 sessions and a six months follow-up training. Pre-/post measures at pretest, the end of the training and the follow-up included tests of attention, intelligence and behavioral variables. After having already reported intermediate data (Strehl et al. 2004), this paper gives account on final results: Both groups are able to voluntarily regulate cortical activity, with the extent of learned self-regulation depending on task and condition. Both groups improve in attention and IQ. Parents and teachers report significant behavioral and cognitive improvements. Clinical effects for both groups remain stable six months after training. Groups do not differ in behavioral or cognitive outcome variables.

Brain-computer interfaces for 1-D and 2-D cursor control

Brain-computer interfaces for 1-D and 2-D cursor control: designs using volitional control of the EEG spectrum or steady-state visual evoked potentials.

IEEE Trans Neural Syst Rehabil Eng
. 2006 Jun;14(2):225-9

Authors: Trejo LJ, Rosipal R, Matthews B

We have developed and tested two electroencephalogram (EEG)-based brain-computer interfaces (BCI) for users to control a cursor on a computer display. Our system uses an adaptive algorithm, based on kernel partial least squares classification (KPLS), to associate patterns in multichannel EEG frequency spectra with cursor controls. Our first BCI, Target Practice, is a system for one-dimensional device control, in which participants use biofeedback to learn voluntary control of their EEG spectra. Target Practice uses a KPLS classifier to map power spectra of 62-electrode EEG signals to rightward or leftward position of a moving cursor on a computer display. Three subjects learned to control motion of a cursor on a video display in multiple blocks of 60 trials over periods of up to six weeks. The best subject's average skill in correct selection of the cursor direction grew from 58% to 88% after 13 training sessions. Target Practice also implements online control of two artifact sources: 1) removal of ocular artifact by linear subtraction of wavelet-smoothed vertical and horizontal electrooculograms (EOG) signals, 2) control of muscle artifact by inhibition of BCI training during periods of relatively high power in the 40-64 Hz band. The second BCI, Think Pointer, is a system for two-dimensional cursor control. Steady-state visual evoked potentials (SSVEP) are triggered by four flickering checkerboard stimuli located in narrow strips at each edge of the display. The user attends to one of the four beacons to initiate motion in the desired direction. The SSVEP signals are recorded from 12 electrodes located over the occipital region. A KPLS classifier is individually calibrated to map multichannel frequency bands of the SSVEP signals to right-left or up-down motion of a cursor on a computer display. The display stops moving when the user attends to a central fixation point. As for Target Practice, Think Pointer also implements wavelet-based online removal of ocular artifact; however, in Think Pointer muscle artifact is controlled via adaptive normalization of the SSVEP. Training of the classifier requires about 3 min. We have tested our system in real-time operation in three human subjects. Across subjects and sessions, control accuracy ranged from 80% to 100% correct with lags of 1-5 s for movement initiation and turning. We have also developed a realistic demonstration of our system for control of a moving map display (http://ti.arc.nasa.gov/).

Retina projector to help blind people

From New Scientist

Partially blind people can now read using a machine that projects images directly onto their retinal cells.


The Retinal Imaging Machine Vision System (RIMVS) can also be used to explore virtual buildings, allowing people to familiarise themselves with new places.

The device, developed by Elizabeth Goldring, a poetry professor at the Massachusetts Institute of Technology, who is herself partially blind, is designed for people who suffer vision loss due to obstructions such as haemorrhages or diseases that erode the cells on the retina.

The user looks through a viewfinder and the images are focused directly onto the retina. The person can guide the light to find the areas that still work best. The machine uses LED light and costs just $4000.