γ neuromodulations: unraveling biomarkers for neurological and psychiatric disorders

Abstract

γ neuromodulation has emerged as a promising strategy for addressing neurological and psychiatric disorders, particularly in regulating executive and cognitive functions. This review explores the latest neuromodulation techniques, focusing on the critical role of γ oscillations in various brain disorders. Direct γ neuromodulation induces γ-frequency oscillations to synchronize disrupted brain networks, while indirect methods influence γ oscillations by modulating cortical excitability. We investigate how monitoring dynamic features of γ oscillations allows for detailed evaluations of neuromodulation effectiveness. By targeting γ oscillatory patterns and restoring healthy cross-frequency coupling, interventions may alleviate cognitive and behavioral symptoms linked to disrupted communication. This review examines clinical applications of γ neuromodulations, including enhancing cognitive function through 40 Hz multisensory stimulation in Alzheimer's disease, improving motor function in Parkinson's disease, controlling seizures in epilepsy, and modulating emotional dysfunctions in depression. Additionally, these neuromodulation strategies aim to regulate excitatory-inhibitory imbalances and restore γ synchrony across neurological and psychiatric disorders. The review highlights the potential of γ oscillations as biomarkers to boost restorative results in clinical applications of neuromodulation. Future studies might focus on integrating multimodal personalized protocols, artificial intelligence (AI) driven frameworks for neural decoding, and global multicenter collaborations to standardize and scale precision treatments across diverse disorders.

Keywords: Cross frequency coupling; Deep brain stimulation (DBS); Neurological disorders; Neuromodulation; Psychiatric disorders; Transcranial magnetic stimulation (TMS); γ oscillations.

Fig. 1

Strategies for collecting and analyzing neuronal oscillations. a Data collection procedure using EEG/MEG. b Data presentation and reduce artifacts. c ICA for extracting clean data. d Preprocessed clean data in sensors (visual α oscillations). e Source reconstructions. f Source power (visual α oscillations). g The presentation for neuronal oscillations. h ERP analysis. i Time–frequency analysis. j Frequency-specific functional connectivity, including connectivity matrices and brain connectivity maps. k Brain dynamic models (Hidden Markov Model). l Brain dynamic patterns describing the power spectra of different brain states. m Brain dynamic features including fractional occupancy and transition probability of each brain state. EEG electroencephalogram, MEG magnetoencephalography, ICA independent component analysis, ERP event-related potential

Fig. 2

Schematic representation of neuromodulation technologies. Schematic representation of non-invasive neuromodulations rTMS (a), tACS (b), tDCS (c), Neurofeedback (d), and invasive neuromodulation DBS (e). f Neuromodulation treatments enhance cognitive and executive functions, which in turn leads to the rehabilitation of clinical symptoms. g Key features for non-invasive and invasive neuromodulation. rTMS repetitive transcranial magnetic stimulation, tACS transcranial alternating current stimulation, tDCS transcranial direct current stimulation, DBS deep brain stimulation

Fig. 3

CFC mechanisms and neuromodulation. a Phase-amplitude coupling, where the phase of a lower-frequency oscillation modulates the amplitude of a higher-frequency oscillation. b Neuromodulation alters neurotransmitter release and brain network synchronization. The noradrenergic system (c), the dopaminergic system (d), and the cholinergic system (e) modulate cross-frequency coupling. f, g Simulation of phase-amplitude coupling illustrating changes before, during, and after neuromodulation. The neuromodulation intervention effectively restores cross-frequency coupling patterns. CFC cross-frequency coupling

Fig. 4

Diverse impacts of γ modulations in neurological and psychiatric disorders. a The 40 Hz multisensory stimulation contributing to the clearance of amyloid-β in Alzheimer’s disease mouse models. b The 40 Hz multisensory stimulation showed improvements in diverse clinical symptoms in patients with Alzheimer’s disease. c Localization of seizure onset zones and prediction of seizure outcomes in epilepsy with γ oscillations. d The cortico-striatal-thalamic-cortical (CSTC) circuit shows the role of γ oscillations in obsessive–compulsive disorder during reward-based tasks. e Increased γ oscillations of occipital regions in patients with depression and schizophrenia. f The biological network mechanisms underlying γ oscillations. g Depiction of excitatory-inhibitory imbalance. AD Alzheimer’s disease, CSTC cortico-striatal-thalamic-cortical, PYR pyramidal neurons, PV parvalbumin, GABA γ-aminobutyric acid

Fig. 5

Limitations and future directions in utilizing γ neuromodulations. a Individualized differences for γ neuromodulations. b Understanding of the neurobiological mechanisms. c Side effects and tolerability. Future directions: d Multicenter collaborations to enhance treatment efficiency. e AI-driven analysis for customized interventions. f multimodal individualized methods. rTMS repetitive transcranial magnetic stimulation, tDCS transcranial direct current stimulation, tACS transcranial alternating current stimulation, NFB Neurofeedback, DBS Deep brain stimulation, AI Artificial intelligence