Biology subjects

Haslacher, D.

Publications and source records attributed to Haslacher, D..

6 recordsLinked to original sources

bioRxiv2024

Working memory enhancement using real-time phase-tuned transcranial alternating current stimulation

BackgroundPrior work has shown that transcranial alternating current stimulation (tACS) of parietooccipital alpha oscillations (8 - 14 Hz) can modulate working memory (WM) performance as a function of the phase lag to endogenous oscillations. However, leveraging this effect using real-time phase-tuned tACS was not feasible so far due to stimulation artifacts. Objectives/HypothesisWe aimed to develop a system that tracks and adapts the phase lag between tACS and ongoing parietooccipital alpha oscillations in real-time. We hypothesized that such real-time phase-tuned tACS enhances working memory performance, depending on the phase lag. MethodsWe developed real-time phase-tuned closed-loop amplitude-modulated tACS (CLAM-tACS) targeting parietooccipital alpha oscillations. CLAM-tACS was applied at six different phase lags relative to ongoing alpha oscillations while participants (N = 21) performed a working memory task. To exclude that behavioral effects of CLAM-tACS were mediated by other factors such as sensory co-stimulation, a second group of participants (N = 25) received equivalent stimulation of the forehead. ResultsWM accuracy improved in a phase lag dependent manner (p < 0.05) in the group receiving parietooccipital stimulation, with the strongest enhancement observed at 330{degrees} phase lag between tACS and ongoing alpha oscillations (p < 0.01, d = 0.976). Moreover, across participants, modulation of frontoparietal alpha oscillations correlated both in amplitude (p < 0.05) and phase (p < 0.05) with the modulation of WM accuracy. No such effects were observed in the control group receiving frontal stimulation. ConclusionsOur results demonstrate the feasibility and efficacy of real-time phase-tuned CLAM-tACS in modulating both brain activity and behavior, thereby paving the way for further investigation into brain-behavior relationships and the exploration of innovative therapeutic applications.

neuroscience↗

bioRxiv2024

Heartbeat perception is causally linked to frontal delta oscillations

The ability to accurately perceive ones own bodily signals, such as the heartbeat, plays a vital role in physical and mental health. However, the neurophysiological mechanisms underlying this ability, termed interoception, are not fully understood. Converging evidence suggests that cardiac rhythms are linked to frontal brain activity, particularly oscillations in the delta (0.5 - 4 Hz) band, but their causal relationship remained elusive. Using amplitude-modulated transcranial alternating current stimulation (AM-tACS), a method to enhance or suppress brain oscillations in a phase-specific manner, we investigated whether frontal delta oscillations are causally linked to heartbeat perception. We found that enhancement of delta phase synchrony suppressed heartbeat detection accuracy, while suppression of delta phase synchrony enhanced heartbeat detection accuracy. These findings suggest that frontal delta oscillations play a critical role in heartbeat perception, paving the way for causal investigations of interoception and potential clinical applications. SignificanceAlthough bodily signals are known to influence perception and behavior, little is known about the underlying neurophysiological mechanisms. Here, we show that perception of the heartbeat is anticorrelated with phase synchrony of frontal delta oscillations, and that modulating these oscillations with transcranial electric stimulation influences heartbeat perception. Our results suggest that delta oscillations play a key role in processing bodily signals, with potential implications for theories of emotions and clinical neuroscience.

neuroscience↗

bioRxiv2022

In-vivo phase-dependent enhancement and suppression of brain oscillations by transcranial alternating current stimulation (tACS)

Transcranial alternating current stimulation (tACS) can influence human perception and behavior, with recent evidence also suggesting its potential impact in clinical settings, but the underlying mechanisms are poorly understood. Behavioral and indirect physiological evidence indicates that phase-dependent constructive and destructive interference between the tACS electric field and ongoing brain oscillations may play an important role, but direct in-vivo validation was infeasible because stimulation artifacts impeded such assessment. Using stimulation artifact source separation (SASS), a real-time compatible artifact suppression approach, we overcame this limitation and provide direct evidence for millisecond-by-millisecond phase-dependent enhancement and suppression of ongoing brain oscillations during amplitude-modulated tACS (AM-tACS) across 29 healthy human volunteers. We found that AM-tACS enhanced and suppressed targeted brain oscillations by 11.7 {+/-} 5.14% and 10.1 {+/-} 4.07% respectively. Millisecond-precise modulation of oscillations predicted modulation of behavior (r = 0.65, p < 0.001). These results not only provide direct evidence for constructive and destructive interference as a key mechanism of AM-tACS but suggest superiority of phase-locked (closed-loop) AM-tACS over conventional (open-loop) AM-tACS to purposefully enhance or suppress brain oscillations. SignificanceThe presented data provide direct evidence for a key mechanism underlying neurophysiological and behavioral effects of transcranial alternating current stimulation (tACS), a broadly used neuromodulation approach that yields promising clinical results but also raised controversies because of its variable effects. Our findings not only elucidate the underlying mechanisms of tACS, but also provide the rationale for closed-loop tACS protocols that will enable targeted enhancement and suppression of brain oscillations related to various brain functions such perception, memory or cognition. Towards this end, we introduce the technical prerequisites to establish millisecond-to-millisecond precise closed-loop tACS protocols that will be important to advance tACS as a neuroscientific and clinical tool, for example in the treatment of neuropsychiatric disorders.

neuroscience↗

bioRxiv2021

Heart rate variability predicts decline in sensorimotor rhythm control

Voluntary control of sensorimotor rhythms (SMR, 8-12 Hz) can be used for brain-computer interface (BCI)-based operation of an assistive hand exoskeleton, e.g., in finger paralysis after stroke. To gain SMR control, stroke survivors are usually instructed to engage in motor imagery (MI) or to attempt moving the paralyzed fingers resulting in task- or event-related desynchronization (ERD) of SMR (SMR-ERD). However, as these tasks are cognitively demanding, especially for stroke survivors suffering from cognitive impairments, BCI control performance can deteriorate considerably over time. It would thus be important to identify biomarkers that predict decline in BCI control performance within an ongoing session in order to optimize the man-machine interaction scheme. Here we determine the link between BCI control performance over time and heart rate variability (HRV). Specifically, we investigated whether HRV can be used as a biomarker to predict decline during voluntary control of SMR-ERD across 17 healthy participants using Granger causality. SMR-ERD was visually displayed on a screen. Participants were instructed to engage in MI-based SMR-ERD control over two consecutive runs of 8.5 minutes each. During the second run, task difficulty was gradually increased. While control performance (p = .18) and HRV (p = .16) remained unchanged across participants during the first run, during the second run, both measures declined over time at high correlation (performance: -0.61%/10s, p = 0; HRV: -0.007ms/10s, p < .001). We found that HRV Granger-caused BCI control performance (p < .001) exhibited predictive characteristics of HRV on an individual participant level. These results suggest that HRV can predict decline in BCI performance paving the way for adaptive BCI control paradigms, e.g., to individualize and optimize assistive BCI systems in stroke.

neuroscience↗

bioRxiv2020

Stimulation Artifact Source Separation (SASS) for assessing electric brain oscillations during transcranial alternating current stimulation (tACS)

Brain oscillations, e.g. measured by electro- or magnetoencephalography (EEG/MEG), are causally linked to brain functions that are fundamental for perception, cognition and learning. Recent advances in neurotechnology provide means to non-invasively target these oscillations using frequency-tuned amplitude-modulated transcranial alternating current stimulation (AM-tACS). However, online adaptation of stimulation parameters to ongoing brain oscillations remains an unsolved problem due to stimulation artifacts that impede such adaptation, particularly at the target frequency. Here, we introduce a real-time compatible artifact rejection algorithm (Stimulation Artifact Source Separation, SASS) that overcomes this limitation. SASS is a spatial filter (linear projection) removing EEG signal components that are maximally different in the presence versus absence of stimulation. This enables the reliable removal of stimulation-specific signal components, while leaving physiological signal components unaffected. For validation of SASS, we evoked brain activity with known phase and amplitude using 10 Hz visual flickers across 7 healthy human volunteers. 64-channel EEG was recorded during and in absence of 10 Hz AM-tACS targeting the visual cortex. Phase differences between AM-tACS and the visual stimuli were randomized, so that steady-state visually evoked potentials (SSVEPs) were phase-locked to the visual stimuli but not to the AM-tACS signal. For validation, distributions of single-trial amplitude and phase of EEG signals recorded during and in absence of AM-tACS were compared for each participant. When no artifact rejection method was applied, AM-tACS stimulation artifacts impeded assessment of single-trial SSVEP amplitude and phase. Using SASS, amplitude and phase of single trials recorded during and in absence of AM-tACS were comparable. These results indicate that SASS can be used to establish adaptive (closed-loop) AM-tACS, a potentially powerful tool to target various brain functions, and to investigate how AM-tACS interacts with electric brain oscillations. Highlights- Stimulation Artifact Source Separation (SASS), a real-time compatible signal decomposition algorithm for separating electric brain activity and stimulation signal artifacts related to amplitude-modulated transcranial alternating current stimulation (AM-tACS), is introduced - Employing SASS, phase and amplitude of single-trial steady state visual evoked potentials (SSVEPs) were reliably recovered from electroencephalography (EEG) recordings at the frequency targeted with AM-tACS - SASS enables assessment of single-trial oscillatory brain activity at the target frequency during stimulation and paves the way for online adaptation of stimulation parameters to ongoing brain oscillations

neuroscience↗

bioRxiv2020

Minimizing biosignal recording sites for hybrid noninvasive brain/neural robot control

Noninvasive brain/neural controlled robots are promising tools to improve autonomy and quality of life in severe paralysis, but require biosignal recordings, such as electroencephalography (EEG) and electrooculography (EOG), from various sites distributed over the users head. This limits the applicability and practicality of noninvasive brain/neural robot control on an everyday basis. It would thus be very desirable to minimize the number of necessary recording sites paving the way for miniaturized, headset-like EEG/EOG systems that users with hemiplegia can mount by themselves. Here, we introduce a novel EEG/EOG brain/neural robot control strategy using only scalp electrodes placed near cortical sensorimotor areas. The strategy was tested across 16 healthy volunteers engaging in an EEG/EOG brain/neural control task. Classification accuracies were compared using scalp electrodes only vs. the conventional electrode placements across the scalp and face. To evaluate whether cranial muscle artifacts impede classification accuracy, participants were asked to chew during the task. We found that brain/neural classification accuracy was comparable and that chewing did not impact classification accuracies when using scalp electrodes only. Our results suggest that the proposed new strategy allows for reliable EEG/EOG-based brain/neural robot control, a critical prerequisite to broaden the use of noninvasive brain/neural assistive and rehabilitative technologies.

neuroscience↗