Multi-focal Stimulation of the Cortico-cerebellar Loop During the Acquisition of a Novel Hand Motor Skill in Chronic Stroke Survivors

Impairment of hand motor function is a frequent consequence after a stroke and strongly determines the ability to regain a self-determined life. An influential research strategy for improving motor deficits is the combined application of behavioral training and non-invasive brain stimulation of the motor cortex (M1). However, a convincing clinical translation of the present stimulation strategies has not been achieved yet. One alternative and innovative approach is to target the functionally relevant brain network-based architecture, e.g., the dynamic interactions within the cortico-cerebellar system during learning. Here, we tested a sequential multifocal stimulation strategy targeting the cortico-cerebellar loop. Anodal transcranial direct current stimulation (tDCS) was applied simultaneously to a hand-based motor training in N = 11 chronic stroke survivors during four training sessions on two consecutive days. The tested conditions were: sequential multifocal (M1-cerebellum (CB)-M1-CB) vs. monofocal control stimulation (M1-sham-M1-sham). Additionally, skill retention was assessed 1 and 10 days after the training phase. Paired-pulse transcranial magnetic stimulation data were recorded to characterize stimulation response determining features. The application of CB-tDCS boosted motor behavior in the early training phase in comparison to the control condition. No faciliatory effects on the late training phase or skill retention were detected. Stimulation response variability was related to the magnitude of baseline motor ability and short intracortical inhibition (SICI). The present findings suggest a learning phase-specific role of the cerebellar cortex during the acquisition of a motor skill in stroke and that personalized stimulation strategies encompassing several nodes of the underlying brain network should be considered.

Investigating the role of the fusiform face area and occipital face area using multifocal transcranial direct current stimulation

The functional role of the occipital face area (OFA) and the fusiform face area (FFA) in face recognition is inconclusive to date. While some research has shown that the OFA and FFA are involved in early (i.e., featural processing) and late (i.e., holistic processing) stages of face recognition respectively, other research suggests that both regions are involved in both early and late stages of face recognition. Thus, the current study aims to further examine the role of the OFA and the FFA using multifocal transcranial direct current stimulation (tDCS). In Experiment 1, we used computer-generated faces. Thirty-five participants completed whole face and facial features (i.e., eyes, nose, mouth) recognition tasks after OFA and FFA stimulation in a within-subject design. No difference was found in recognition performance after either OFA or FFA stimulation. In Experiment 2 with 60 participants, we used real faces, provided stimulation following a between-subjects design and included a sham control group. Results showed that FFA stimulation led to enhanced efficiency of facial features recognition. Additionally, no effect of OFA stimulation was found for either facial feature or whole face recognition. These results suggest the involvement of FFA in the recognition of facial features.

Optimization of multifocal transcranial current stimulation for weighted cortical pattern targeting from realistic modeling of electric fields

Recently, multifocal transcranial current stimulation (tCS) devices using several relatively small electrodes have been used to achieve more focal stimulation of specific cortical targets. However, it is becoming increasingly recognized that many behavioral manifestations of neurological and psychiatric disease are not solely the result of abnormality in one isolated brain region but represent alterations in brain networks. In this paper we describe a method for optimizing the configuration of multifocal tCS for stimulation of brain networks, represented by spatially extended cortical targets. We show how, based on fMRI, PET, EEG or other data specifying a target map on the cortical surface for excitatory, inhibitory or neutral stimulation and a constraint on the maximal number of electrodes, a solution can be produced with the optimal currents and locations of the electrodes. The method described here relies on a fast calculation of multifocal tCS electric fields (including components normal and tangential to the cortical boundaries) using a five layer finite element model of a realistic head. Based on the hypothesis that the effects of current stimulation are to first order due to the interaction of electric fields with populations of elongated cortical neurons, it is argued that the optimization problem for tCS stimulation can be defined in terms of the component of the electric field normal to the cortical surface. Solutions are found using constrained least squares to optimize current intensities, while electrode number and their locations are selected using a genetic algorithm. For direct current tCS (tDCS) applications, we provide some examples of this technique using an available tCS system providing 8 small Ag/AgCl stimulation electrodes. We demonstrate the approach both for localized and spatially extended targets defined using rs-fcMRI and PET data, with clinical applications in stroke and depression. Finally, we extend these ideas to more general stimulation protocols, such as alternating current tCS (tACS).