Biology subjects

Faller, J.

Publications and source records attributed to Faller, J..

3 recordsLinked to original sources

bioRxiv2022

Functional and effective connectivity between dorsolateral prefrontal and subgenual anterior cingulate cortex depends on the timing of transcranial magnetic stimulation relative to the phase of prefrontal alpha EEG

BACKGROUNDThe communication through coherence model posits that brain rhythms are synchronized across different frequency bands and that effective connectivity strength between interacting regions depends on their phase relation. Evidence to support the model comes mostly from electrophysiological recordings in animals while evidence from human data is limited. METHODSHere, an fMRI-EEG-TMS (fET) instrument capable of acquiring simultaneous fMRI and EEG during noninvasive single pulse TMS applied to dorsolateral prefrontal cortex (DLPFC) was used to test whether prefrontal EEG alpha phase moderates TMS-evoked top-down influences on subgenual, rostral and dorsal anterior cingulate cortex (ACC). Results in healthy volunteers (n=11) were compared to those from patients with major depressive disorder (MDD) (n=17) collected as part of a ongoing clinical trial investigation. RESULTSIn both groups, TMS-evoked functional connectivity between DLPFC and subgenual ACC (sgACC) depended on the EEG alpha phase. TMS-evoked DLPFC to sgACC effective connectivity (EC) was moderated by EEG alpha phase in healthy volunteers, but not in the MDD patients. Top-down EC was inhibitory for TMS onsets during the upward slope of the alpha wave relative to TMS timed to the downward slope of the alpha wave. Prefrontal EEG alpha phase dependent effects on TMS-evoked fMRI BOLD activation of the rostral anterior cingulate cortex were detected in the MDD patient group, but not in the healthy volunteer group. DISCUSSIONResults demonstrate that TMS-evoked top-down influences vary as a function of the prefrontal alpha rhythm, and suggest clinical applications whereby TMS is synchronized to the brains internal rhythms in order to more efficiently engage deep therapeutic targets.

neuroscience↗

bioRxiv2021

Spatiospectral brain networks reflective of improvisational experience

Musical improvisers are trained to categorize certain musical structures into functional classes, which is thought to facilitate improvisation. Using a novel auditory oddball paradigm (Goldman et al., 2020) which enables us to disassociate a deviant (i.e. musical cord inversion) from a consistent functional class, we recorded scalp EEG from a group of musicians who spanned a range of improvisational and classically trained experience. Using a spatiospectral based inter and intra network connectivity analysis, we found that improvisers showed a variety of differences in connectivity within and between large-scale cortical networks compared to classically trained musicians, as a function of deviant type. Inter-network connectivity in the alpha band, for a time window leading up to the behavioural response, was strongly linked to improvisation experience, with the default mode network acting as a hub. Spatiospectral networks post response were substantially different between improvisers and classically trained musicians, with greater inter-network connectivity (specific to the alpha and beta bands) seen in improvisers whereas those with more classical training had largely reduced inter-network activity (mostly in the gamma band). More generally, we interpret our findings in the context of network-level correlates of expectation violation as a function of subject expertise, and we discuss how these may generalize to other and more ecologically valid scenarios.

neuroscience↗

bioRxiv2018

Regulation of arousal via on-line neurofeedback improves human performance in a demanding sensory-motor task

Our state of arousal can significantly affect our ability to make optimal decisions, judgments, and actions in real-world dynamic environments. The Yerkes-Dodson law, which posits an inverse-U relationship between arousal and task performance, suggests that there is a state of arousal that is optimal for behavioral performance in a given task. Here we show that we can use on-line neurofeedback to shift an individuals arousal toward this optimal state. Specifically, we use a brain computer interface (BCI) that uses information in the electroencephalogram (EEG) to generate a neurofeedback signal that dynamically adjusts an individuals arousal state when they are engaged in a boundary avoidance task (BAT). The BAT is a demanding sensory-motor task paradigm that we implement as an aerial navigation task in virtual reality (VR), and which creates cognitive conditions that escalate arousal and quickly results in task failure -- e.g. missing or crashing into the boundary. We demonstrate that task performance, measured as time and distance over which the subject can navigate before failure, is significantly increased when veridical neurofeedback is provided. Simultaneous measurements of pupil dilation and heart rate variability show that the neurofeedback indeed reduces arousal. Our work is the first demonstration of a BCI system that uses on-line neurofeedback to shift arousal state and increase task performance in accordance with the Yerkes-Dodson law.

neuroscience↗