Application of high-frequency repetitive transcranial magnetic stimulation to the DLPFC alters human prefrontal-hippocampal functional interaction.

Neural plasticity is crucial for understanding the experience-dependent reorganization of brain regulatory circuits and the pathophysiology of schizophrenia. An important circuit-level feature derived from functional magnetic resonance imaging (fMRI) is prefrontal-hippocampal seeded connectivity during working memory, the best established intermediate connectivity phenotype of schizophrenia risk to date. The phenotype is a promising marker for the effects of plasticity-enhancing interventions, such as high-frequency repetitive transcranial magnetic stimulation (rTMS), and can be studied in healthy volunteers in the absence of illness-related confounds, but the relationship to brain plasticity is unexplored. We recruited 39 healthy volunteers to investigate the effects of 5 Hz rTMS on prefrontal-hippocampal coupling during working memory and rest. In a randomized and sham-controlled experiment, neuronavigation-guided rTMS was applied to the right dorsolateral prefrontal cortex (DLPFC), and fMRI and functional connectivity analyses [seeded connectivity and psychophysiological interaction (PPI)] were used as readouts. Moreover, the test-retest reliability of working-memory related connectivity markers was evaluated. rTMS provoked a significant decrease in seeded functional connectivity of the right DLPFC and left hippocampus during working memory that proved to be relatively time-invariant and robust. PPI analyses provided evidence for a nominal effect of rTMS and poor test-retest reliability. No effects on n-back-related activation and DLPFC-hippocampus resting-state connectivity were observed. These data provide the first in vivo evidence for the effects of plasticity induction on human prefrontal-hippocampal network dynamics, offer insights into the biological mechanisms of a well established intermediate phenotype linked to schizophrenia, and underscores the importance of the choice of outcome measures in test-retest designs.

Simultaneous EEG and fMRI reveals a causally connected subcortical-cortical network during reward anticipation.

Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have been used to study the neural correlates of reward anticipation, but the interrelation of EEG and fMRI measures remains unknown. The goal of the present study was to investigate this relationship in response to a well established reward anticipation paradigm using simultaneous EEG-fMRI recording in healthy human subjects. Analysis of causal interactions between the thalamus (THAL), ventral-striatum (VS), and supplementary motor area (SMA), using both mediator analysis and dynamic causal modeling, revealed that (1) THAL fMRI blood oxygenation level-dependent (BOLD) activity is mediating intermodal correlations between the EEG contingent negative variation (CNV) signal and the fMRI BOLD signal in SMA and VS, (2) the underlying causal connectivity network consists of top-down regulation from SMA to VS and SMA to THAL along with an excitatory information flow through a THAL→VS→SMA route during reward anticipation, and (3) the EEG CNV signal is best predicted by a combination of THAL fMRI BOLD response and strength of top-down regulation from SMA to VS and SMA to THAL. Collectively, these findings represent a likely neurobiological mechanism mapping a primarily subcortical process, i.e., reward anticipation, onto a cortical signature.

Sequential inhibitory control processes assessed through simultaneous EEG-fMRI.

Inhibitory response control has been extensively investigated in both electrophysiological (ERP) and hemodynamic (fMRI) studies. However, very few multimodal results address the coupling of these inhibition markers. In fMRI, response inhibition has been most consistently linked to activation of the anterior insula and inferior frontal cortex (IFC), often also the anterior cingulate cortex (ACC). ERP work has established increased N2 and P3 amplitudes during NoGo compared to Go conditions in most studies. Previous simultaneous EEG-fMRI imaging reported association of the N2/P3 complex with activation of areas like the anterior midcingulate cortex (aMCC) and anterior insula. In this study we investigated inhibitory control in 23 healthy young adults (mean age=24.7, n=17 for EEG during fMRI) using a combined Flanker/NoGo task during simultaneous EEG and fMRI recording. Separate fMRI and ERP analysis yielded higher activation in the anterior insula, IFG and ACC as well as increased N2 and P3 amplitudes during NoGo trials in accordance with the literature. Combined analysis modelling sequential N2 and P3 effects through joint parametric modulation revealed correlation of higher N2 amplitude with deactivation in parts of the default mode network (DMN) and the cingulate motor area (CMA) as well as correlation of higher central P3 amplitude with activation of the left anterior insula, IFG and posterior cingulate. The EEG-fMRI results resolve the localizations of these sequential activations. They suggest a general role for allocation of attentional resources and motor inhibition for N2 and link memory recollection and internal reflection to P3 amplitude, in addition to previously described response inhibition as reflected by the anterior insula.

Novelty modulates human striatal activation and prefrontal-striatal effective connectivity during working memory encoding.

The functional role of the basal ganglia (BG) in the gating of suitable motor responses to the cortex is well established. Growing evidence supports an analogous role of the BG during working memory encoding, a task phase in which the "input-gating" of relevant materials (or filtering of irrelevant information) is an important mechanism supporting cognitive capacity and the updating of working memory buffers. One important aspect of stimulus relevance is the novelty of working memory items, a quality that is understudied with respect to its effects on corticostriatal function and connectivity. To this end, we used functional magnetic resonance imaging (fMRI) in 74 healthy volunteers performing an established Sternberg working memory task with different task phases (encoding vs. retrieval) and degrees of stimulus familiarity (novel vs. previously trained). Activation analyses demonstrated a highly significant engagement of the anterior striatum, in particular during the encoding of novel working memory items. Dynamic causal modeling (DCM) of corticostriatal circuit connectivity identified a selective positive modulatory influence of novelty encoding on the connection from the dorsolateral prefrontal cortex (DLPFC) to the anterior striatum. These data extend prior research by further underscoring the relevance of the BG for human cognitive function and provide a mechanistic account of the DLPFC as a plausible top-down regulatory element of striatal function that may facilitate the "input-gating" of novel working memory materials.

Resting-state brain network features associated with short-term skill learning ability in humans and the influence of N-methyl-d-aspartate receptor antagonism.

Graph theoretical functional magnetic resonance imaging (fMRI) studies have demonstrated that brain networks reorganize significantly during motor skill acquisition, yet the associations between motor learning ability, brain network features, and the underlying biological mechanisms remain unclear. In the current study, we applied a visually guided sequential pinch force learning task and graph theoretical analyses to investigate the associations between short-term motor learning ability and resting-state brain network metrics in 60 healthy subjects. We further probed the test-retest reliability (n = 26) and potential effects of the N-methyl-d-aspartate (NMDA) antagonist ketamine (n = 19) in independent healthy volunteers. Our results show that the improvement of motor performance after short-term training was positively correlated with small-worldness (p = 0.032) and global efficiency (p = 0.025), whereas negatively correlated with characteristic path length (p = 0.014) and transitivity (p = 0.025). In addition, using network-based statistics (NBS), we identified a learning ability-associated (p = 0.037) and ketamine-susceptible (p = 0.027) cerebellar-cortical network with fair to good reliability (intraclass correlation coefficient [ICC] > 0.7) and higher functional connectivity in better learners. Our results provide new evidence for the association of intrinsic brain network features with motor learning and suggest a role of NMDA-related glutamatergic processes in learning-associated subnetworks.