Article

Predicting and phase targeting brain oscillations in real-time

2024-10-12

Abstract excerpt

<h4>Objective: </h4> Closed-loop neurostimulation (CLNS) procedures, aligning stimuli with electrical brain activity, are quickly gaining popularity in neuroscience. They have been employed to reveal causal links between neural activity patterns and function, and to explore therapeutic effects of electroencephalography (EEG-)guided stimulations during sleep. Most CLNS procedures are developed for a single purpose,...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 4739ceba-ebbb-5786-aa3a-d6d10d88572f
DOI: 10.1101/2024.10.12.617974

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Predicting and phase targeting brain oscillations in real-timeDOI 10.1101/2024.10.12.617974Read

A Classification-Based Generative Approach to Selective Targeting of Global Slow Oscillations during SleepSemantic proximity Read

Predicting the effects of deep brain stimulation using a reduced coupled oscillator modelSemantic proximity Read

Scalp EEG predicts intracranial brain activity in humansSemantic proximity Read

Corticothalamic modelling of sleep neurophysiology with applications to mobile EEGSemantic proximity Read

Predictive Modeling of Evoked Intracranial EEG Response to Medial Temporal Lobe Stimulation in Patients with EpilepsySemantic proximity Read

Deep brain stimulation pulse sequences to optimally modulate frequency-specific neural activitySemantic proximity Read

A connectome-based, corticothalamic model of state- and stimulation-dependent modulation of rhythmic neural activity and connectivitySemantic proximity Read

Modulation of large-scale cortical coupling by transcranial alternating current stimulationSemantic proximity Read

Closed-loop optimization of a high-dimensional generative latent space for rhythmic visual responseSemantic proximity Read

Decoding Motor Excitability in TMS using EEG-Features: An Exploratory Machine Learning ApproachSemantic proximity Read

Non-linear Auto-Regressive Models for Cross-Frequency Coupling in Neural Time SeriesSemantic proximity Read

Personalized, EEG-controlled intermittent theta burst stimulationSemantic proximity Read