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Berger, T.

Publications and source records attributed to Berger, T..

3 recordsLinked to original sources

Abnormal mu rhythm state-related cortical and corticospinal responses in chronic stroke

The motor cortexs activity is state-dependent. Specifically, the sensorimotor mu rhythm phase relates to fluctuating levels of primary motor cortex (M1) excitability, previously demonstrated in young and healthy volunteers. However, it is unknown whether this observation is generalizable to individuals with brain lesions after a stroke. We investigated the phase relationship between the mu rhythm and cortical excitability by combining real-time processing of electroencephalography (EEG) signals and transcranial magnetic stimulation (TMS) of M1. In 11 chronic subcortical stroke survivors and 12 similar-aged healthy volunteers, we applied TMS to M1 at the peak, falling, trough, and rising phase of the sensorimotor mu oscillation. As outcome measures, we investigated the M1-to-muscle excitability by measuring motor-evoked potentials (MEPs) and local cortical activation by measuring TMS-evoked potentials (TEPs). We found that M1-to-muscle excitability in stroke survivors and older volunteers shows a phase-dependency similar to that in young healthy adults. That is, MEPs were increased and decreased at the trough and peak of the mu rhythm, respectively. However, individuals with stronger stroke-related motor symptoms showed a decreased phase preference. Further, phase-dependency was abolished in the local cortical activity, as measured with EEG, in the stroke-affected hemisphere, in contrast to the non-affected hemisphere as well as either hemisphere in healthy volunteers. Altogether, these results shed light on the state-dependency of motor cortex excitability after stroke. Our results indicate that the strength of phase preference of TMS motor responses could indicate the severity of motor impairment. These results could enable the development of improved TMS paradigms for recovery of motor impairment after stroke.

neuroscience↗

Systematic cross-species comparison of prefrontal cortex functional networks targeted via Transcranial Magnetic Stimulation

Transcranial Magnetic Stimulation (TMS) is a non-invasive brain stimulation method that safely modulates neural activity in vivo. Its precision in targeting specific brain networks makes TMS invaluable in diverse clinical applications. For example, TMS is used to treat depression by targeting prefrontal brain networks and their connection to other brain regions. However, despite its widespread use, the underlying neural mechanisms of TMS are not completely understood. Non-human primates (NHPs) offer an ideal model to study TMS mechanisms through invasive electrophysiological recordings. As such, bridging the gap between NHP experiments and human applications is imperative to ensure translational relevance. Here, we systematically compare the TMS-targeted functional networks in the prefrontal cortex in humans and NHPs. To conduct this comparison, we combine TMS electric field modeling in humans and macaques with resting-state functional magnetic resonance imaging (fMRI) data to compare the functional networks targeted via TMS across species. We identified distinct stimulation zones in macaque and human models, each exhibiting variations in the impacted networks (macaque: Frontoparietal Network, Somatomotor Network; human: Frontoparietal Network, Default Network). We identified differences in brain gyrification and functional organization across species as the underlying cause of found network differences. The TMS-network profiles we identified will allow researchers to establish consistency in network activation across species, aiding in the translational efforts to develop improved TMS functional network targeting approaches.

neuroscience↗

Resolving spatiotemporal electrical signaling within the islet via CMOS microelectrode arrays

Glucose-stimulated beta-cells synchronize calcium waves across the islet to recruit more beta-cells for insulin secretion. Compared to calcium dynamics, the formation and cell-to-cell propagation of electrical signals within the islet are poorly characterized. To determine factors that influence the propagation of electrical activity across the islet underlying calcium oscillations and beta-cell synchronization, we used high-resolution CMOS multielectrode arrays (MEA) to measure voltage changes associated with the membrane potential of individual cells within intact mouse islets. We measured both fast (milliseconds, spikes) and slow (seconds, waves) voltage changes and analyzed the spatiotemporal voltage dynamics. Treatment of islets from C57BL6 mice with increasing glucose concentrations revealed that single spike activity and wave signal velocity were both glucose-dependent. A repeated glucose stimulus involved a highly active subset of cells in terms of spike activity. When islets were pretreated for 72 hours with glucolipotoxic medium, the wave velocity was significantly reduced. Network analysis confirmed that the synchrony of islet cells was affected due to slower propagating electrical waves and not due to altered spike activity. In summary, this approach provided novel insight regarding the propagation of electrical activity and opens a wide field for further studies on signal transduction in the islet cell network. Article HighlightsThis study presents a new method for characterizing islet spatiotemporal electrical dynamics and subpopulations of beta-cells. We asked whether a high-resolution CMOS-MEA is suited to detect electrical signals on a level close to single cells, and whether we can track the propagation of electrical activity through the islet on a cellular scale. A highly active subpopulation of islet cells was identified by action potential-like spike activity, whereas slower waves were a measure for synchronized electrical activity. Further, propagating waves were slowed by glucolipotoxicity. The technique is a useful tool for exploring the pancreatic islet network in health and disease.

physiology↗