Transcranial direct current stimulation's effect on novice versus experienced learning.

Transcranial direct current stimulation (TDCS) is a non-invasive form of brain stimulation applied via a weak electrical current passed between electrodes on the scalp. In recent studies, TDCS has been shown to improve learning when applied to the prefrontal cortex (e.g., Kincses et al. in Neuropsychologia 42:113-117, 2003; Clark et al. Neuroimage in 2010). The present study examined the effects of TDCS delivered at the beginning of training (novice) or after an hour of training (experienced) on participants' ability to detect cues indicative of covert threats. Participants completed two 1-h training sessions. During the first 30 min of each training session, either 0.1 mA or 2.0 mA of anodal TDCS was delivered to the participant. The anode was positioned near F8, and the cathode was placed on the upper left arm. Testing trials immediately followed training. Accuracy in classification of images containing and not-containing threat stimuli during the testing sessions indicated: (1) that mastery of threat detection significantly increased with training, (2) that anodal TDCS at 2 mA significantly enhanced learning, and (3) TDCS was significantly more effective in enhancing test performance when applied in novice learners than in experienced learners. The enhanced performance following training with TDCS persisted into the second session when TDCS was delivered early in training.

Commonalities and differences among vectorized beamformers in electromagnetic source imaging.

A number of beamformers have been introduced to localize neuronal activity using magnetoencephalography (MEG) and electroencephalography (EEG). However, currently available information about the major aspects of existing beamformers is incomplete. In the present study, detailed analyses are performed to study the commonalities and differences among vectorized versions of existing beamformers in both theory and practice. In addition, a novel beamformer based on higher-order covariance analysis is introduced. Theoretical formulas are provided on all major aspects of each beamformer; to examine their performance, computer simulations with different levels of correlation and signal-to-noise ratio are studied. Then, an empirical data set of human MEG median-nerve responses with a large number of neuronal generators is analyzed using the different beamformers. The results show substantial differences among existing MEG/EEG beamformers in their ways of describing the spatial map of neuronal activity. Differences in performance are observed among existing beamformers in terms of their spatial resolution, false-positive background activity, and robustness to highly correlated signals. Superior performance is obtained using our novel beamformer with higher-order covariance analysis in simulated data. Excellent agreement is also found between the results of our beamformer and the known neurophysiology of the median-nerve MEG response.

Predicting EEG responses using MEG sources in superior temporal gyrus reveals source asynchrony in patients with schizophrenia.

OBJECTIVE: An integrated analysis using Electroencephalography (EEG) and magnetoencephalography (MEG) is introduced to study abnormalities in early cortical responses to auditory stimuli in schizophrenia. METHODS: Auditory responses were recorded simultaneously using EEG and MEG from 20 patients with schizophrenia and 19 control subjects. Bilateral superior temporal gyrus (STG) sources and their time courses were obtained using MEG for the 30-100 ms post-stimulus interval. The MEG STG source time courses were used to predict the EEG signal at electrode Cz. RESULTS: In control subjects, the STG sources predicted the EEG Cz recording very well (97% variance explained). In schizophrenia patients, the STG sources accounted for substantially (86%) and significantly (P<0.0002) less variance. After MEG-derived STG activity was removed from the EEG Cz signal, the residual signal was dominated by 40 Hz activity, an indication that the remaining variance in EEG is probably contributed by other brain generators, rather than by random noise. CONCLUSIONS: Integrated MEG and EEG analysis can differentiate patients and controls, and suggests a basis for a well established abnormality in the cortical auditory response in schizophrenia, implicating a disorder of functional connectivity in the relationship between STG sources and other brain generators.