Deep brain stimulation (DBS) via implanted electrodes is used worldwide to treat patients with severe neurological and psychiatric disorders. However, its invasiveness precludes widespread clinical use and deployment in research. Temporal interference (TI) is a strategy for non-invasive steerable DBS using multiple kHz-range electric fields with a difference frequency within the range of neural activity. Here we report the validation of the non-invasive DBS concept in humans. We used electric field modeling and measurements in a human cadaver to verify that the locus of the transcranial TI stimulation can be steerably focused in the hippocampus with minimal exposure to the overlying cortex. We then used functional magnetic resonance imaging and behavioral experiments to show that TI stimulation can focally modulate hippocampal activity and enhance the accuracy of episodic memories in healthy humans. Our results demonstrate targeted, non-invasive electrical stimulation of deep structures in the human brain.

Aberrant neural oscillations hallmark numerous brain disorders. Here, we first report a method to track the phase of neural oscillations in real-time via endpoint-corrected Hilbert transform (ecHT) that mitigates the characteristic Gibbs distortion. We then used ecHT to show that the aberrant neural oscillation that hallmarks essential tremor (ET) syndrome, the most common adult movement disorder, can be transiently suppressed via transcranial electrical stimulation of the cerebellum phase-locked to the tremor. The tremor suppression is sustained shortly after the end of the stimulation and can be phenomenologically predicted. Finally, we use feature-based statistical-learning and neurophysiological-modelling to show that the suppression of ET is mechanistically attributed to a disruption of the temporal coherence of the aberrant oscillations in the olivocerebellar loop, thus establishing its causal role. The suppression of aberrant neural oscillation via phase-locked driven disruption of temporal coherence may in the future represent a powerful neuromodulatory strategy to treat brain disorders.

Modulations in motor cortical beta and alpha activity have been implicated in the preparation, execution, and termination of voluntary movements. The functional role of motor cortex beta activity is yet to be defined, though two opposing theories prevail. The idling cortex theory suggests that large-scale motor networks, in the absence of input, revert to an intrinsic oscillatory state. The alternative theory proposes that beta activity promotes postural tone at the expense of voluntary movement. These theories are primarily based on observations of event-related desynchronization associated with movement onset. Here, we explore the changes in alpha and beta oscillatory activity associated with the specific behavioral patterns during an established directional uncertainty paradigm. We demonstrate that, consistent with current proposals, alpha and beta desynchronization reflects a process of disengagement from existing networks to enable the creation of functional assemblies. We demonstrate that, following desynchronization, a novel signature of transient alpha synchrony underlies the recruitment of functional assemblies required for directional control. Although alpha and beta desynchronization are dependent upon the number of cues presented, they are not predictive of movement preparation. However, the transient alpha synchrony occurs only when participants have sufficient information to prepare for movement and shows a direct relationship with behavioral performance measures.

Sleep is a fundamental part of our lives; yet, how our brain falls asleep remains one of the most enduring mysteries of neuroscience. Here we report a new conceptual framework to analyze and model this phenomenon. The framework represents the changes in brain electroencephalogram activity during the transition into sleep as a trajectory in a normalized feature space. We use the framework to show that the brain’s wake-to-sleep transition follows bifurcation dynamics with a distinct tipping point preceded by a critical slowing down. We validate the bifurcation dynamics in two independent datasets, which include more than 1,000 human participants. Finally, we demonstrate the framework’s utility by predicting a person’s progression into sleep in real time with seconds temporal resolution and over 0.95 average accuracy.

Resting-state metrics, such as brain network activity and functional connectivity (FC), are influenced by preceding cognitive tasks, such as memory formation. Brain stimulation can modulate brain network activity and FC during the resting state. However, it is unknown whether it can acutely modulate activity or FC traces of preceding cognitive tasks. We evaluated whether non-invasive temporal interference (TI) stimulation of the hippocampus can modulate hippocampal resting-state FC traces induced by a preceding hippocampally-dependent task. We collected resting-state functional magnetic resonance imaging (rsfMRI) in twenty healthy participants before and after the performance of an associative memory task. Theta-band TI stimulation of the medial and anterior hippocampus, and sham stimulation were delivered during post-task resting state. We used permutation tests to assess differences in pairwise mutual information functional connectivity (miFC) between pre-task rsfMRI vs post-task sham. In edges with significantly different pre- vs post-task miFC, permutation tests assessed the effect of TI on post-task miFC. MiFC was significantly lower in several functional networks during post-task sham compared to pre-task baseline, including the hippocampal-connected and task-related Anterior Temporal (AT) and Posterior Medial (PM) networks. TI stimulation of the hippocampus during post-task resting state increased the miFC in the hippocampal AT and PM networks as well as other functional networks. Non-invasive TI stimulation of the hippocampus during the resting state acutely modulated FC traces related to preceding hippocampal-dependent memory tasks.

Background/Objectives: This study investigates the relationship between movement-related beta synchrony and primary motor cortex (M1) excitability, focusing on the time-dependent inhibition of movement. Voluntary movement induces beta frequency (13–30 Hz) event-related desynchronisation (B-ERD) in M1, followed by post-movement beta rebound (PMBR). Although PMBR is linked to cortical inhibition, its temporal relationship with motor cortical excitability is unclear. This study aims to determine whether PMBR acts as a marker for post-movement inhibition by assessing motor-evoked potentials (MEPs) during distinct phases of the beta synchrony profile. Methods: Twenty-five right-handed participants (mean age: 24 years) were recruited. EMG data were recorded from the first dorsal interosseous muscle, and TMS was applied to the M1 motor hotspot to evoke MEPs. A reaction time task was used to elicit beta oscillations, with TMS delivered at participant-specific time points based on EEG-derived beta power envelopes. MEP amplitudes were compared across four phases: B-ERD, early PMBR, peak PMBR, and late PMBR. Results: Our findings demonstrate that MEP amplitude significantly increased during B-ERD compared to rest, indicating heightened cortical excitability. In contrast, MEPs recorded during peak PMBR were significantly reduced, suggesting cortical inhibition. While all three PMBR phases exhibited reduced cortical excitability, a trend toward amplitude-dependent inhibition was observed. Conclusions: This study confirms that PMBR is linked to reduced cortical excitability, validating its role as a marker of motor cortical inhibition. These results enhance the understanding of beta oscillations in motor control and suggest that further research on altered PMBR could be crucial for understanding neurological and psychiatric disorders.