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Can the causal role of brain oscillations be studied through rhythmic brain stimulation?

ABSTRACT: Many studies have investigated the causal relevance of brain oscillations using rhythmic stimulation, either through direct-brain or sensory stimulation. Yet, how intrinsic rhythms interact with the externally generated rhythm is largely unknown. We presented a flickered (60 Hz) visual grating or its correspondent unflickered stimulus in a psychophysical change detection task during simultaneous magnetoencephalography recordings to humans to test the effect of visual entrainment on induced gamma oscillations. Notably, we generally observed the coexistence of the broadband induced gamma rhythm with the entrained flicker rhythm (reliably measured in each participant), with the peak frequency of the induced response remaining unaltered in approximately half of participants—relatively independently of their native frequency. However, flicker increased broadband induced gamma power, and this was stronger in participants with a native frequency closer to the flicker frequency (resonance) and led to strong phase entrainment. Presence of flicker did not change behavior itself but profoundly altered brain behavior correlates across the sample: While broadband induced gamma oscillations correlated with reaction times for unflickered stimuli (as known previously), for the flicker, the amplitude of the entrained flicker rhythm (but no more the induced oscillation) correlated with reaction times. This, however, strongly depended on whether a participant's peak frequency shifted to the entrained rhythm. Our results suggests that rhythmic brain stimulation leads to a coexistence of two partially independent oscillations with heterogeneous effects across participants on the downstream relevance of these rhythms for behavior. This may explain the inconsistency of findings related to external entrainment of brain oscillations and poses further questions toward causal manipulations of brain oscillations in general.

SUBMITTER: Lobo T

PROVIDER: S-EPMC8572434 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Circadian and other physiological rhythms play a key role in both normal homeostasis and disease processes. Such is the case of circadian and infradian seizure patterns observed in epilepsy. However, these rhythms are not fully exploited in the design of active implantable medical devices. In this paper we explore a new implantable stimulator that implements chronotherapy as a feedforward input to supplement both open-loop and closed-loop methods. This integrated algorithm allows for stimulation to be adjusted to the ultradian, circadian and infradian patterns observed in patients through slowly-varying temporal adjustments of stimulation and algorithm sub-components, while also enabling adaption of stimulation based on immediate physiological needs such as a breakthrough seizure or change of posture. Embedded physiological sensors in the stimulator can be used to refine the baseline stimulation circadian pattern as a "digital zeitgeber," i.e., a source of stimulus that entrains or synchronizes the subject's natural rhythms. This algorithmic approach is tested on a canine with severe drug-resistant idiopathic generalized epilepsy exhibiting a characteristic diurnal pattern correlated with sleep-wake cycles. Prior to implantation, the canine's cluster seizures evolved to status epilepticus (SE) and required emergency pharmacological intervention. The cranially-mounted system was fully-implanted bilaterally into the centromedian nucleus of the thalamus. Using combinations of time-based modulation, thalamocortical rhythm-specific tuning of frequency parameters as well as fast-adaptive modes based on activity, the canine experienced no further SE events post-implant as of the time of writing (7 months). Importantly, no significant cluster seizures have been observed either, allowing the reduction of rescue medication. The use of digitally-enabled chronotherapy as a feedforward signal to augment adaptive neurostimulators could prove a useful algorithmic method in conditions where sensitivity to temporal patterns are characteristics of the disease state, providing a novel mechanism for tailoring a more patient-specific therapy approach.

Project description: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.

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Can the causal role of brain oscillations be studied through rhythmic brain stimulation?

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