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Dopamine plays an important role in the modulation of neuroplasticity, which serves as the physiological basis of cognition. The physiological effects of dopamine depend on receptor subtypes, and the D1 receptor is critically involved in learning and memory formation. Evidence from both animal and human studies shows a dose-dependent impact of D1 activity on performance. However, the direct association between physiology and behavior in humans remains unclear. In this study, four groups of healthy participants were recruited, and each group received placebo or medication inducing a low, medium, or high amount of D1 activation via the combination of levodopa and a D2 antagonist. After medication, fMRI was conducted during a visuomotor learning task. The behavioral results revealed an inverted U-shaped effect of D1 activation on task performance, where medium-dose D1 activation led to superior learning effects, as compared to placebo as well as low- and high-dose groups. A respective dose-dependent D1 modulation was also observed for cortical activity revealed by fMRI. Further analysis demonstrated a positive correlation between task performance and cortical activation at the left primary motor cortex. Our results indicate a nonlinear curve of D1 modulation on motor learning in humans and the respective physiological correlates in corresponding brain areas., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Magnetic field tomography (MFT) was used to extract estimates for distributed source activity from average and single trial MEG signals recorded while subjects identified objects (including faces) and facial expressions of emotion. Regions of interest (ROIs) were automatically identified from the MFT solutions of the average signal for each subject. For one subject the entire set of MFT estimates obtained from unaveraged data was also used to compute simultaneous time series for the single trial activity in different ROIs. Three pairs of homologous areas in each hemisphere were selected for further analysis: posterior calcarine sulcus (PCS), fusiform gyrus (FM), and the amygdaloid complex (AM). Mutual information (MI) between each pair of the areas was computed from all single trial time series and contrasted for different tasks (object or emotion recognition) and categories within each task. The MI analysis shows that through feed-forward and feedback linkages, the "computation" load associated with the task of identifying objects and emotions is spread across both space (different ROIs and hemispheres) and time (different latencies and delays in couplings between areas)-well within 200 ms, different objects separate first in the right hemisphere PCS and FG coupling while different emotions separate in the right hemisphere FG and AM coupling, particularly at latencies after 200 ms.

Subjects were trained to detect changes in the frequency of 21 Hz tactile stimulation applied to digits 2 + 3 + 4 (fusion group) or 2 + 4 (segregation group) of the right hand. The 21 Hz steady-state response for digit 3 was measured by 64 channel EEG on mapping trials before and after training. Discrimination improved over 3 days, confirming that subjects attended to the training stimuli. The 21 Hz response was larger on training than on mapping trials, indicating sensitivity of the response to the strength of cortical activation. Under these conditions the 21 Hz response for digit 3 decreased after training in both groups on day 1. On day 3 this effect reversed in a subset of fusion subjects while segregation continued to yield decreases. The findings suggest that somatosensory representations are dynamically modified by the sensory input experienced on a task.

A method of analysing biomagnetic signals is presented which focuses attention on activity in a specific region of interest. The method is based on the construction of virtual sensors, corresponding to linear combinations of lead fields that are optimally localized within the region of interest. This method is fast and stable. It is tested against physiologically plausible computer generated signals and also against more elaborate analysis of real data. The results show that the method can be very effective as a fast scanning tool identifying activity from pre-defined regions of interest.

This paper presents a multivariate analysis of evoked responses and their spatiotemporal dynamics as measured with electro- or magnetoencephalography. This analysis uses standard techniques (ManCova) to make possible statistical inference about differential responses, after the data have been transformed using singular value decomposition. The generality of this approach is limited only by the assumptions implicit in the general linear model and can range from simple analyses like Hotelling's T2 test (in comparing evoked responses among different conditions) to complex analyses of a multivariate regression type (e.g., characterizing the response components associated with a behavioral or psychophysical parameter). To illustrate the technique we have characterized time-dependent changes (both within and between trials) in magnetic fields, evoked by self-paced movements. Our illustrative analysis showed that movement-evoked components were less prone to adaptation than premovement components, suggesting that functionally distinct (preparatory and early executive) biomagnetic signals show differential adaptation.

Magnetic field tomography (MFT) provides 3-dimensional estimates of brain activity, from non-contact, non-invasive measurements of the magnetic field generated by coherent electrical activity in the brain. MFT analysis of averaged auditory "odd-ball" data show cortical and deep activation, presumably from the amygdala and hippocampus. These results are compared with MFT estimates obtained from a patient who had undergone lobectomy which removed these structures. The variability from subject to subject is confounded by variability between trials for the same subject; the relationship between the averaged and single trials is probed by bi-hemispheric simultaneous measurements performed under the same odd-ball paradigm and by MFT analysis of auditory evoked data and interictal epileptic activity.