Biology subjects

Wenderoth, N.

Publications and source records attributed to Wenderoth, N..

8 recordsLinked to original sources

bioRxiv2018

A different state of mind: neural activity related to volitionally up- versus downregulating cortical excitability

To date there exists no reliable method to non-invasively upregulate or downregulate the state of the resting motor system over a large dynamic range. Here we show that an operant conditioning paradigm which provides neurofeedback of the size of motor evoked potentials (MEPs) in response to transcranial magnetic stimulation (TMS), enables participants to self-modulate their own brain state. Following training, participants were able to robustly increase (by 83.8%) and decrease (by 30.6%) their MEP amplitudes. This volitional up-versus down-regulation of corticomotor excitability caused an increase of late-cortical disinhibition (LCD), a TMS derived read-out of presynaptic GABAB disinhibition, which was accompanied by an increase of gamma and a decrease of alpha oscillations in the trained hemisphere. This approach paves the way for future investigations into how altered brain state influences motor neurophysiology and recovery of function in a neurorehabilitation context.

neuroscience↗

bioRxiv2018

Motor resonance in primary motor cortex reflects the integration of kinematic and contextual information in accordance to a Bayesian predictive coding framework

Contextual information accompanying others actions modulates \"motor resonance\", i.e. neural activity within motor areas that is elicited by movement observation. One possibility is that we weight and combine such information in a Bayesian manner according to their relative uncertainty. Therefore, contextual information becomes particularly useful when others actions are ambiguous. It is unclear, however, whether this uncertainty modulates the neural activity in primary motor cortex (M1) during movement observation. Here we applied single-pulse transcranial magnetic stimulation (TMS) while subjects watched different grasping actions. We operationalized motor resonance as grip specific modulation of corticomotor excitability measured in the index (FDI) versus the little finger abductor (ADM). We experimentally modulated either the availability of kinematic information (Exp. 1) or the reliability of contextual cues (Exp. 2). Our results indicate that even in the absence of movement kinematics, reliable contextual information is enough to trigger significant muscle-specific corticomotor excitability changes in M1 (p<.0001) which are strongest when both kinematics and contextual information are available (p<.005). These findings suggest that bottom-up mechanisms that activate motor representations as a function of the observed kinematics, and top-down mechanisms which activate motor representations associated with arbitrary cues converge in M1 in a statistically optimal manner.

neuroscience↗

bioRxiv2017

Altering brain dynamics with transcranial random noise stimulation

Random noise can enhance the detectability of weak signals in nonlinear threshold systems, a phenomenon known as stochastic resonance (SR). This concept is not only applicable to single threshold systems but can also be applied to dynamical systems with multiple attractor states, such as observed during the phenomenon of binocular rivalry. Binocular rivalry can be characterized by marginally stable attractor states between which the brain switches in a spontaneous, stochastic manner. The switches are thought to be driven by a combination of neuronal adaptation and noise. Here we used a computational model to predict the effect of noise on perceptual dominance durations when either low-contrast or high-contrast stimuli are presented. Subsequently we compared the model prediction to a series of three experiments where we measured binocular rivalry dynamics when noise (zero-mean Gaussian white noise) was added either to the visual stimulus (Exp. 1) or directly to the visual cortex (Exp. 2 and Exp. 3) by applying transcranial Random Noise Stimulation (tRNS 1mA, 100-640 Hz zero mean Gaussian white noise). We found that adding noise significantly reduced the mixed percept duration (Exp. 1 and Exp. 2). This effect was only present for low-contrast but not for high-contrast visual stimuli which is in line with the model predictions. Our results demonstrate that both central and peripheral noise can influence state-switching dynamics of binocular rivalry under specific conditions (e.g. low visual contrast stimuli), in line with a SR-mechanism.

neuroscience↗

bioRxiv2017

Heart-brain interactions in the MR environment: characterization of the ballistocardiogram in EEG signals collected during simultaneous fMRI

The ballistocardiographic (BCG) artifact is linked to cardiac activity and occurs in electroencephalographic (EEG) recordings acquired inside the magnetic resonance (MR) environment. Its variability in terms of amplitude, waveform shape and spatial distribution over subjects scalp makes its attenuation a challenging task. In this study, we aimed to provide a detailed characterization of the BCG properties, including its temporal dependency on cardiac events and its spatio-temporal dynamics. To this end, we used high-density EEG data acquired during simultaneous functional MR imaging in six healthy volunteers. First, we investigated the relationship between cardiac activity and BCG occurrences in the EEG recordings. We observed large variability in the delay between ECG and subsequent BCG events (ECG-BCG delay) across subjects and non-negligible epoch-by-epoch variations at the single subject level. Also, we found positive correlations between heart rate variability and ECG-BCG delay. The inspection of spatial-temporal variations revealed a prominent non-stationarity of the BCG signal. We identified five main BCG waves, which were common across subjects. Principal component analysis revealed two spatially distinct patterns to explain most of the variance (85% in total). These components are possibly related to head rotation and pulse-driven scalp expansion, respectively. Our results may inspire the development of novel, more effective methods for the removal of the BCG, capable of isolating and attenuating artifact occurrences while preserving true neuronal activity.

neuroscience↗

bioRxiv2017

Making up your mind: Enhanced perceptual decision-making induced by stochastic resonance during non-invasive brain stimulation

Perceptual decision-making relies on the gradual accumulation of noisy sensory evidence until a specified boundary is reached and an appropriate response is made. It might be assumed that adding noise to a stimulus, or to the neural systems involved in its processing, would interfere with the decision process. But it has been suggested that adding an optimal amount of noise can, under appropriate conditions, enhance the quality of subthreshold signals in nonlinear systems, a phenomenon known as stochastic-resonance. Here we asked whether perceptual decisions obey these stochastic resonance principles by adding noise directly to the visual cortex using transcranial-random-noise stimulation (tRNS) while participants judged the direction of motion in foveally presented random-dot motion arrays. Consistent with the stochastic resonance account, we found that adding tRNS bilaterally to visual cortex enhanced decision-making when stimuli were below, but not above, perceptual threshold. We modelled the data under a drift diffusion framework to isolate the specific components of the multi-stage decision process that were influenced by the addition of neural noise. This modelling showed that tRNS increased drift rate, which indexes the rate of evidence accumulation, but had no effect on bound separation or non-decision time. These results were specific to bilateral stimulation of visual cortex; control experiments involving unilateral stimulation of left and right visual areas showed no influence of random noise stimulation. Our study is the first to provide causal evidence that perceptual decision-making is susceptible to a stochastic resonance effect induced by tRNS, and that this effect arises from selective enhancement of the rate of evidence accumulation for sub-threshold sensory events.

neuroscience↗

bioRxiv2017

Improving the quality of combined EEG-TMS neural recordings: Introducing the ‘Coil Spacer’

BackgroundIn the last decade, interest in combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) approaches has grown substantially. Aside from the obvious artifacts induced by the magnetic pulses themselves, separate and more sinister signal disturbances arise as a result of contact between the TMS coil and EEG electrodes.\n\nNew methodHere we profile the characteristics of these artifacts and introduce a simple device - the coil spacer - to provide a platform allowing physical separation between the coil and electrodes during stimulation.\n\nResultsEEG data revealed high amplitude signal disturbances when the TMS coil was in direct contact with the EEG electrodes, well within the physiological range of viable EEG signals. The largest artifacts were located in the Delta and Theta frequency range, and standard data cleanup using independent components analysis (ICA) was ineffective due to the artifacts similarity to real brain oscillations.\n\nComparison with Existing MethodWhile the current best practice is to use a large coil holding apparatus to fixate the coil hovering over the head with an air gap, the spacer provides a simpler solution that ensures this distance is kept constant throughout testing.\n\nConclusionsThe results strongly suggest that data collected from combined TMS-EEG studies with the coil in direct contact with the EEG cap are polluted with low frequency artifacts that are indiscernible from physiological brain signals. The coil spacer provides a cheap and simple solution to this problem and is recommended for use in future simultaneous TMS-EEG recordings.

neuroscience↗

bioRxiv2017

Concurrent tACS-fMRI Reveals Causal Influence Of Power Synchronized Neural Activity On Resting State fMRI Connectivity

Resting state fMRI (rs-fMRI) is commonly used to study the brains intrinsic neural coupling, which reveals specific spatiotemporal patterns in the form of resting state networks (RSN). It has been hypothesized that slow rs-fMRI oscillations (<0.1 Hz) are driven by underlying electrophysiological rhythms that typically occur at much faster timescales (>5 Hz); however, causal evidence for this relationship is currently lacking. Here we measured rs-fMRI in humans while applying transcranial alternating current stimulation (tACS) to entrain brain rhythms in left and right sensorimotor cortices.\n\nThe two driving tACS signals were tailored to the individuals alpha rhythm (8-12 Hz) and fluctuated in amplitude according to a 1 Hz power envelope. We entrained the left versus right hemisphere in accordance to two different coupling modes where either alpha oscillations were synchronized between hemispheres (phase-synchronized tACS) or the slower oscillating power envelopes (power-synchronized tACS).\n\nPower-synchronized tACS significantly increased rs-fMRI connectivity within the stimulated RSN compared to phase-synchronized or no tACS. This effect outlasted the stimulation period and tended to be more effective in individuals who exhibited a naturally weak interhemispheric coupling. Using this novel approach, our data provide causal evidence that synchronized power fluctuations contribute to the formation of fMRI-based RSNs. Moreover, our findings demonstrate that the brains intrinsic coupling at rest can be selectively modulated by choosing appropriate tACS signals, which could lead to new interventions for patients with altered rs-fMRI connectivity.\n\nSignificance StatementResting state fMRI has become an important tool to estimate brain connectivity. However, relatively little is known about how slow hemodynamic oscillations measured with fMRI relate to electrophysiological processes.\n\nIt was suggested that slowly fluctuating power envelopes of electrophysiological signals synchronize across brain areas and that the topography of this activity is spatially correlated to resting state networks derived from rs-fMRI. Here we take a novel approach to address this problem and establish a causal link between the power fluctuations of electrophysiological signals and rs-fMRI via a new neuromodulation paradigm, which exploits these power-synchronization mechanisms.\n\nThese novel mechanistic insights bridge different scientific domains and are of broad interest to researchers in the fields of Medical Imaging, Neuroscience, Physiology and Psychology.

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bioRxiv2016

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain

Brain dynamics are thought to unfold on a network determined by the pattern of axonal connections linking pairs of neuronal populations; the so-called connectome. Prior work has indicated that structural brain connectivity constrains pairwise correlations in brain dynamics (also called functional connectivity), but it is not known whether inter-regional axonal connectivity is related to the intrinsic dynamics of individual brain areas. Here we investigate this relationship using a weighted, directed mesoscale mouse connectome from the Allen Mouse Brain Connectivity Atlas and resting state functional MRI (rs-fMRI) time-series data measured in 184 brain regions in eighteen anesthetized mice. For each brain region, we measured degree, betweenness, and clustering coefficient from weighted and unweighted, and directed and undirected versions of the connectome. We then characterized the univariate rs-fMRI dynamics at each brain region by computing 6 930 time-series properties using the time-series analysis toolbox, hctsa. After correcting for regional volume variations, strong and robust correlations between structural connectivity properties and rs-fMRI dynamics were found only when edge weights were accounted for, and were associated with variations in the autocorrelation properties of the rs-fMRI signal. The strongest relationships were found for weighted in-degree, which was positively correlated to the autocorrelation of fMRI time series at time lag{tau} = 34s (partial Spearman correlation{rho} = 0.58), as well as a range of related measures such as relative high frequency power (f > 0.4 Hz:{rho} = -0.43). Our results indicate that the topology of inter-regional axonal connections of the mouse brain is closely related to intrinsic, spontaneous dynamics such that regions with a greater aggregate strength of incoming projections display longer timescales of activity fluctuations.

neuroscience↗