Brain Rhythms Research Articles

Effective networks mediate right hemispheric dominance of human 40 Hz auditory steady-state response.

Auditory steady-state responses (ASSR) are induced from the brainstem to the neocortex when humans hear periodic amplitude-modulated tonal signals. ASSRs have been argued to be a key marker of auditory temporal processing and pathological reorganization of ASSR – a biomarker of neurodegenerative disorders. However, most of the earlier studies reporting the neural basis of ASSRs were focused on looking at individual brain regions. Here, we seek to characterize the large-scale directed information flow among cortical sources of ASSR entrained by 40 Hz external signals. Entrained brain rhythms with power peaking at 40 Hz were generated using both monaural and binaural tonal stimulation. First, we confirm the presence of ASSRs and their well-known right hemispheric dominance during binaural and both monaural conditions. Thereafter, reconstruction of source activity employing individual anatomy of the participant and subsequent network analysis revealed that while the sources are common among different stimulation conditions, differential levels of source activation and differential patterns of directed information flow among sources underlie processing of binaurally and monaurally presented tones. Particularly, we show bidirectional interactions involving the right superior temporal gyrus and inferior frontal gyrus underlie right hemispheric dominance of 40 Hz ASSR during both monaural and binaural conditions. On the other hand, for monaural conditions, the strength of inter-hemispheric flow from left primary auditory areas to right superior temporal areas followed a pattern that comply with the generally observed contralateral dominance of sensory signal processing.

Brain rhythms have come of age

Neuronal oscillations offer access to neuronal operations, bringing microscopic and macroscopic mechanisms, experimental methods, and explanations to a common platform. The field of brain rhythms has become the agora of discussions from temporal coordination of neuronal populations within and across brain regions to cognitive phenomena, including language and brain diseases.

Zuranolone, a Positive Allosteric Modulator of the GABAA Receptor: Hypothesized Mechanism of Action in Major Depressive Disorder

AbstractMajor depressive disorder (MDD) is a heterogeneous condition characterized by depressed mood and/or loss of interest/pleasure in activities, among other symptoms. Most currently available treatments for depression were developed on the hypothesis that depressive symptoms arise from a depletion of monoamines within the central nervous system (CNS). However, clinical understanding has advanced to identify brain network dysregulation as the primary driver of depression, with monoamines playing a lesser role. Prolonged inability to regulate brain networks may lead to the core symptoms and clinical presentation of MDD. Depression has been linked to impaired neuronal activity in brain networks (e.g., central executive network [CEN], default mode network [DMN], and salience network [SN]). It is hypothesized that improvement in depressive symptoms may result from restoring balance in brain networks governing mood.γ-aminobutyric acid (GABA) is critical for maintaining and restoring excitatory-inhibitory balance in the brain and regulating brain networks. Approximately one-third of neurons in the CNS are GABAergic, regulating network activity throughout the brain, including regions involved in mood, sleep, and cognition. GABA activates GABAA receptors (GABAAR), inhibiting neuronal activity through phasic (via synaptic GABAAR) and tonic (via extrasynaptic GABAAR) currents. Tonic GABA currents may play a particularly important role in regulating network activity, since they produce a large net inhibitory effect and are also involved in controlling the excitability of inhibitory interneurons, the key regulators of rhythmic brain network activity.Zuranolone is an investigational oral GABAAR positive allosteric modulator and neuroactive steroid. In clinical trials, treatment with zuranolone has shown significant improvement over placebo in depressive symptoms in adults with MDD or postpartum depression, with a generally well-tolerated and consistent safety profile.The hypothesized mechanism of zuranolone differs from monoamine-based antidepressants and from benzodiazepines. Unlike benzodiazepines, which bind to the α/γ subunit interface in synaptic GABAAR and enhance phasic inhibitory currents, zuranolone binds to the α/β subunit interface present in nearly all GABAAR, leading to enhanced phasic (synaptic) and tonic (extrasynaptic) inhibitory currents. Furthermore, in vitro evidence suggests that whereas benzodiazepines are associated with GABAAR downregulation, zuranolone upregulates the surface expression of GABAAR.In conclusion, by upregulating GABAAR expression and increasing phasic and tonic inhibitory GABAergic signaling, zuranolone may rapidly restore and maintain excitatory-inhibitory balance in brain networks, thus allowing the brain to potentially respond appropriately to internal and external stimuli.FundingSage Therapeutics, Inc., and Biogen Inc.

Neurophysiological isolation of individual rhythmic brain activity arising from auditory-speech load

Knowledge about the rhythmic activity of neural networks associated with the implementation of a particular brain function can be used to construct diagnostic systems for objective analyses of cognitive dysfunctions. The aim of this study was to identify specific frequency-based electroencephalogram phenomena associated with speech processing. The study included data from 40 clinically healthy volunteers aged 30 to 50 years (median 32.5 years), including 23 men and 17 women. While listening to a speech stimulus, changes in bioelectrical activity over the speech centers were recorded in 23 subjects (58%). During active speech production, similar changes were recorded in 12 subjects (30%). A pairwise comparison of electroencephalogram frequencies recorded during background recording and listening to the stimuli revealed statistically significant differences in changes in rhythmic activity over Broca’s area during listening and over Wernicke's area during active speech production, while changes in rhythmic activity over Broca’s area during active speech production and over Wernicke's area during listening were less significant. The most characteristic changes in the bioelectrical activity over the speech centers during listening and speaking were fluctuations with a frequency (on average) of 17.5–17.7 Hz. This may reflect a specific electroencephalogram rhythm associated with activity in the speech areas of the brain, which could allow these regions to be more accurately identified during auditory-verbal processing.

Timing to be precise? An overview of spike timing-dependent plasticity, brain rhythmicity, and glial cells interplay within neuronal circuits.

In the mammalian brain information processing and storage rely on the complex coding and decoding events performed by neuronal networks. These actions are based on the computational ability of neurons and their functional engagement in neuronal assemblies where precise timing of action potential firing is crucial. Neuronal circuits manage a myriad of spatially and temporally overlapping inputs to compute specific outputs that are proposed to underly memory traces formation, sensory perception, and cognitive behaviors. Spike-timing-dependent plasticity (STDP) and electrical brain rhythms are suggested to underlie such functions while the physiological evidence of assembly structures and mechanisms driving both processes continues to be scarce. Here, we review foundational and current evidence on timing precision and cooperative neuronal electrical activity driving STDP and brain rhythms, their interactions, and the emerging role of glial cells in such processes. We also provide an overview of their cognitive correlates and discuss current limitations and controversies, future perspectives on experimental approaches, and their application in humans.

Modulations of Cortical Power and Connectivity in Alpha and Beta Bands during the Preparation of Reaching Movements

Planning goal-directed movements towards different targets is at the basis of common daily activities (e.g., reaching), involving visual, visuomotor, and sensorimotor brain areas. Alpha (8-13 Hz) and beta (13-30 Hz) oscillations are modulated during movement preparation and are implicated in correct motor functioning. However, how brain regions activate and interact during reaching tasks and how brain rhythms are functionally involved in these interactions is still limitedly explored. Here, alpha and beta brain activity and connectivity during reaching preparation are investigated at EEG-source level, considering a network of task-related cortical areas. Sixty-channel EEG was recorded from 20 healthy participants during a delayed center-out reaching task and projected to the cortex to extract the activity of 8 cortical regions per hemisphere (2 occipital, 2 parietal, 3 peri-central, 1 frontal). Then, we analyzed event-related spectral perturbations and directed connectivity, computed via spectral Granger causality and summarized using graph theory centrality indices (in degree, out degree). Results suggest that alpha and beta oscillations are functionally involved in the preparation of reaching in different ways, with the former mediating the inhibition of the ipsilateral sensorimotor areas and disinhibition of visual areas, and the latter coordinating disinhibition of the contralateral sensorimotor and visuomotor areas.

Pattern dynamics and stochasticity of the brain rhythms

Our current understanding of brain rhythms is based on quantifying their instantaneous or time-averaged characteristics. What remains unexplored is the actual structure of the waves-their shapes and patterns over finite timescales. Here, we study brain wave patterning in different physiological contexts using two independent approaches: The first is based on quantifying stochasticity relative to the underlying mean behavior, and the second assesses "orderliness" of the waves' features. The corresponding measures capture the waves' characteristics and abnormal behaviors, such as atypical periodicity or excessive clustering, and demonstrate coupling between the patterns' dynamics and the animal's location, speed, and acceleration. Specifically, we studied patterns of θ, γ, and ripple waves recorded in mice hippocampi and observed speed-modulated changes of the wave's cadence, an antiphase relationship between orderliness and acceleration, as well as spatial selectiveness of patterns. Taken together, our results offer a complementary-mesoscale-perspective on brain wave structure, dynamics, and functionality.

Resting-State Activity in Children: Replicating and Extending Findings of Early Maturation of Alpha Rhythms in Autism Spectrum Disorder.

Resting-state alpha brain rhythms provide a foundation for basic as well as higher-order brain processes. Research suggests atypical maturation of the peak frequency of resting-state alpha activity (= PAF) in autism spectrum disorder (ASD). The present study examined resting-state alpha activity in young school-aged children, obtaining magnetoencephalographic (MEG) eyes-closed resting-state data from 47 typically developing (TD) males and 45 ASD males 6.0 to 9.3 years old. Results confirmed a higher PAF in ASD versus TD, and demonstrated that alpha power differences between groups were linked to the shift of PAF in ASD. Additionally, a higher PAF was associated with better cognitive performance in TD but not ASD. Finding thus suggested functional consequences of group differences in resting-state alpha activity.

Beta oscillations and waves in motor cortex can be accounted for by the interplay of spatially structured connectivity and fluctuating inputs.

The beta rhythm (13-30 Hz) is a prominent brain rhythm. Recordings in primates during instructed-delay reaching tasks have shown that different types of traveling waves of oscillatory activity are associated with episodes of beta oscillations in motor cortex during movement preparation. We propose here a simple model of motor cortex based on local excitatory-inhibitory neuronal populations coupled by long-range excitation, where additionally inputs to the motor cortex from other neural structures are represented by stochastic inputs on the different model populations. We show that the model accurately reproduces the statistics of recording data when these external inputs are correlated on a short time scale (25 ms) and have two different components, one that targets the motor cortex locally and another one that targets it in a global and synchronized way. The model reproduces the distribution of beta burst durations, the proportion of the different observed wave types, and wave speeds, which we show not to be linked to axonal propagation speed. When the long-range connectivity or the local input targets are anisotropic, traveling waves are found to preferentially propagate along the axis where connectivity decays the fastest. Different from previously proposed mechanistic explanations, the model suggests that traveling waves in motor cortex are the reflection of the dephasing by external inputs, putatively of thalamic origin, of an oscillatory activity that would otherwise be spatially synchronized by recurrent connectivity.

Hippocampal non-theta state: The "Janus face" of information processing.

The vast majority of studies on hippocampal rhythms have been conducted on animals or humans in situations where their attention was focused on external stimuli or solving cognitive tasks. These studies formed the basis for the idea that rhythmical activity coordinates the work of neurons during information processing. However, at rest, when attention is not directed to external stimuli, brain rhythms do not disappear, although the parameters of oscillatory activity change. What is the functional load of rhythmical activity at rest? Hippocampal oscillatory activity during rest is called the non-theta state, as opposed to the theta state, a characteristic activity during active behavior. We dedicate our review to discussing the present state of the art in the research of the non-theta state. The key provisions of the review are as follows: (1) the non-theta state has its own characteristics of oscillatory and neuronal activity; (2) hippocampal non-theta state is possibly caused and maintained by change of rhythmicity of medial septal input under the influence of raphe nuclei; (3) there is no consensus in the literature about cognitive functions of the non-theta-non-ripple state; and (4) the antagonistic relationship between theta and delta rhythms observed in rodents is not always observed in humans. Most attention is paid to the non-theta-non-ripple state, since this aspect of hippocampal activity has not been investigated properly and discussed in reviews.

How to entrain a selected neuronal rhythm but not others: open-loop dithered brain stimulation for selective entrainment

Objective. While brain stimulation therapies such as deep brain stimulation for Parkinson’s disease (PD) can be effective, they have yet to reach their full potential across neurological disorders. Entraining neuronal rhythms using rhythmic brain stimulation has been suggested as a new therapeutic mechanism to restore neurotypical behaviour in conditions such as chronic pain, depression, and Alzheimer’s disease. However, theoretical and experimental evidence indicate that brain stimulation can also entrain neuronal rhythms at sub- and super-harmonics, far from the stimulation frequency. Crucially, these counterintuitive effects could be harmful to patients, for example by triggering debilitating involuntary movements in PD. We therefore seek a principled approach to selectively promote rhythms close to the stimulation frequency, while avoiding potential harmful effects by preventing entrainment at sub- and super-harmonics. Approach. Our open-loop approach to selective entrainment, dithered stimulation, consists in adding white noise to the stimulation period. Main results. We theoretically establish the ability of dithered stimulation to selectively entrain a given brain rhythm, and verify its efficacy in simulations of uncoupled neural oscillators, and networks of coupled neural oscillators. Furthermore, we show that dithered stimulation can be implemented in neurostimulators with limited capabilities by toggling within a finite set of stimulation frequencies. Significance. Likely implementable across a variety of existing brain stimulation devices, dithering-based selective entrainment has potential to enable new brain stimulation therapies, as well as new neuroscientific research exploiting its ability to modulate higher-order entrainment.

Homeostatic normalization of alpha brain rhythms within the default-mode network and reduced symptoms in post-traumatic stress disorder following a randomized controlled trial of electroencephalogram neurofeedback.

Collective research has identified a key electroencephalogram signature in patients with post-traumatic stress disorder, consisting of abnormally reduced alpha (8-12 Hz) rhythms. We conducted a 20-session, double-blind, randomized controlled trial of alpha desynchronizing neurofeedback in patients with post-traumatic stress disorder over 20 weeks. Our objective was to provide mechanistic evidence underlying potential clinical improvements by examining changes in aberrant post-traumatic stress disorder brain rhythms (namely, alpha oscillations) as a function of neurofeedback treatment. We randomly assigned participants with a primary diagnosis of post-traumatic stress disorder (n = 38) to either an experimental group (n = 20) or a sham-control group (n = 18). A multichannel electroencephalogram cap was used to record whole-scalp resting-state activity pre- and post-neurofeedback treatment, for both the experimental and sham-control post-traumatic stress disorder groups. We first observed significantly reduced relative alpha source power at baseline in patients with post-traumatic stress disorder as compared to an age/sex-matched group of neurotypical healthy controls (n = 32), primarily within regions of the anterior default mode network. Post-treatment, we found that only post-traumatic stress disorder patients in the experimental neurofeedback group demonstrated significant alpha resynchronization within areas that displayed abnormally low alpha power at baseline. In parallel, we observed significantly decreased post-traumatic stress disorder severity scores in the experimental neurofeedback group only, when comparing baseline to post-treatment (Cohen's d = 0.77) and three-month follow-up scores (Cohen's d = 0.75), with a remission rate of 60.0% at the three-month follow-up. Overall, our results indicate that neurofeedback training can rescue pathologically reduced alpha rhythmicity, a functional biomarker that has repeatedly been linked to symptoms of hyperarousal and cortical disinhibition in post-traumatic stress disorder. This randomized controlled trial provides long-term evidence suggesting that the 'alpha rebound effect' (i.e. homeostatic alpha resynchronization) occurs within key regions of the default mode network previously implicated in post-traumatic stress disorder.

Stimulating olfactory epithelium mitigates mechanical ventilation-induced hippocampal inflammation and apoptosis.

Mechanical ventilation (MV), as a life-saving procedure in critical patients, is a risk factor to develop of neurocognitive dysfunction and triggers of inflammation and apoptosis in the brain. Since diversion of breathing route to the tracheal tube diminishes brain activity entrained by physiological nasal breathing, we hypothesized that simulating nasal breathing using rhythmic air-puff (AP) into the nasal cavity of mechanically ventilated rats can reduce hippocampal inflammation and apoptosis in association with restoring respiration-coupled oscillations. We found that stimulating olfactory epithelium through applying rhythmic nasal AP, in association with reviving respiration-coupled brain rhythm, mitigates MV-induced hippocampal apoptosis and inflammation involving microglia and astrocytes. The current translational study opens a window for a novel therapeutic approach to reduce neurological complications induced by MV.

Brain‐X: A new interdisciplinary journal for advancing neuroscience research

Despite significant advancements in brain research, the intricacies of the brain remain a mystery. The Human Brain Project (HBP) is an international research initiative modeled1-3 after the Human Genome Project (HGP), launched in both the United States and Europe,4, 5 that aims to unravel the complex structure and function of the human brain. HBP takes an interdisciplinary approach, incorporating fields such as biology, medicine, informatics, chemistry, materials, and physics. Such an approach is necessary for furthering our understanding of the brain and advancing neuroscience as a field. However, there is currently no professional journal that focuses specifically on interdisciplinary approaches to brain and neuroscience research. To fill this gap, we are proud to announce the launch of Brain-X. The “X” in the name represents the intersection of brain and neuroscience with a strong emphasis on interdisciplinary research. This international publication will showcase the latest discoveries and technological breakthroughs, providing novel insights into all aspects of brain, neuroscience, and neurology. Brain-X is dedicated to promoting interdisciplinarity and welcomes contributions from diverse fields. In particular, the journal strongly encourages studies that utilize mathematics, physics, chemistry, engineering, materials science, or information science to tackle issues in brain and neuroscience research across various disciplines. As a peer-reviewed and open-access journal, Brain-X partners with Wiley to enhance the visibility of interdisciplinary research in this field. The journal publishes a range of article types, including original research articles, data articles, methods articles, reviews, perspectives, research letters, commentaries, and correspondences. Brain-X will comprehensively cover a broad range of topics, including but not limited to aging and brain, brain-computer interface, brain injury and rehabilitation, brain-inspired computing and artificial intelligence (AI), brain-inspired 3D printing, brain rhythm and disease, brain-gut axis, cellular and molecular neuroscience, cerebral organoids, chemical neuroscience, clinical neurology, computational neuroscience, crosstalk between brain and other organs, nanoparticles for brain drug delivery, and nerve regeneration materials. The editorial board of Brain-X comprises influential scientists from around the world who enthusiastically encourage contributions from researchers. The journal guarantees a rapid review process with fair and prompt decisions. Upon acceptance, high-quality support from the editorial team ensures that the manuscript reaches its full potential in brain and neuroscience research. Brain-X aims to serve as a platform for students, scientists, and clinicians to share their discoveries and perspectives on brain, neuroscience, and neurology. The journal is committed to providing valuable and helpful information to the community in a timely and innovative manner. Kunlin Jin: Writing – original draft; Writing – review & editing. The author declares no conflicts of interest.

Local Dirac Synchronization on networks.

We propose Local Dirac Synchronization that uses the Dirac operator to capture the dynamics of coupled nodes and link signals on an arbitrary network. In Local Dirac Synchronization, the harmonic modes of the dynamics oscillate freely while the other modes are interacting non-linearly, leading to a collectively synchronized state when the coupling constant of the model is increased. Local Dirac Synchronization is characterized by discontinuous transitions and the emergence of a rhythmic coherent phase. In this rhythmic phase, one of the two complex order parameters oscillates in the complex plane at a slow frequency (called emergent frequency) in the frame in which the intrinsic frequencies have zero average. Our theoretical results obtained within the annealed approximation are validated by extensive numerical results on fully connected networks and sparse Poisson and scale-free networks. Local Dirac Synchronization on both random and real networks, such as the connectome of Caenorhabditis Elegans, reveals the interplay between topology (Betti numbers and harmonic modes) and non-linear dynamics. This unveils how topology might play a role in the onset of brain rhythms.

Next generation neural population models

Low-dimensional neural mass models are often invoked to model the coarse-grained activity of large populations of neurons and synapses and have been used to help understand the coordination of large scale brain rhythms. However, they are phenomenological in nature and, although motivated by neurobiological considerations, the absence of a direct link to an underlying biophysical reality is a weakness that means they may not be best suited to capturing some of the rich behaviors seen in real neuronal tissue. In this perspective article I discuss a simple spiking neuron network model that has recently been shown to admit to an exact mean-field description for synaptic interactions. This has many of the features of a neural mass model coupled to an additional dynamical equation that describes the evolution of population synchrony. Thisnext generationneural mass model is ideally suited to understanding the patterns of brain activity that are ubiquitously seen in neuroimaging recordings. Here I review the mean-field equations, the way in which population synchrony, firing rate, and average voltage are intertwined, together with their application in large scale brain modeling. As well as natural extensions of this new approach to modeling the dynamics of neuronal populations I discuss some of the open mathematical challenges in developing a statistical neurodynamics that can generalize the one discussed here.

The impact of selective and non-selective medial septum stimulation on hippocampal neuronal oscillations: A study based on modeling and experiments

Alzheimer's disease (AD) is a neurodegenerative disorder with a rising socioeconomic impact on societies. The hippocampus (HPC), which plays an important role in AD, is affected in the early stages. The medial septum (MS) in the forebrain provides major cholinergic input to the HPC and has been shown to play a significant role in generating oscillations in hippocampal neurons. Cholinergic neurons in the basal forebrain are particularly vulnerable to neurodegeneration in AD. To better understand the role of MS neurons including the cholinergic, glutamatergic, and GABAergic subpopulations in generating the well-known brain rhythms in HPC including delta, theta, slow gamma, and fast gamma oscillations, we designed a detailed computational model of the septohippocampal pathway. We validated the results of our model, using electrophysiological recordings in HPC with and without stimulation of the cholinergic neurons in MS using designer receptors exclusively activated by designer drugs (DREADDs) in healthy male ChAT-cre rats. Then, we eliminated 75% of the MS cholinergic neurons in the model to simulate degeneration in AD. A series of selective and non-selective stimulations of the remaining MS neurons were performed to understand the dynamics of oscillation regulation in the HPC during the degenerated state. In this way, appropriate stimulation strategies able to normalize the aberrant oscillations are proposed. We found that selectively stimulating the remaining healthy cholinergic neurons was sufficient for network recovery and compare this to stimulating other subpopulations and a non-selective stimulation of all MS neurons. Our data provide valuable information for the development of new therapeutic strategies in AD and a tool to test and predict the outcome of potential theranostic manipulations.

SARS-CoV-2 alters neural synchronies in the brain with more severe effects in younger individuals

Coronavirus disease secondary to infection by SARS-CoV-2 (COVID19 or C19) causes respiratory illness, as well as severe neurological symptoms that have not been fully characterized. In a previous study, we developed a computational pipeline for the automated, rapid, high-throughput and objective analysis of electroencephalography (EEG) rhythms. In this retrospective study, we used this pipeline to define the quantitative EEG changes in patients with a PCR-positive diagnosis of C19 (n = 31) in the intensive care unit (ICU) of Cleveland Clinic, compared to a group of age-matched PCR-negative (n = 38) control patients in the same ICU setting. Qualitative assessment of EEG by two independent teams of electroencephalographers confirmed prior reports with regards to the high prevalence of diffuse encephalopathy in C19 patients, although the diagnosis of encephalopathy was inconsistent between teams. Quantitative analysis of EEG showed distinct slowing of brain rhythms in C19 patients compared to control (enhanced delta power and attenuated alpha–beta power). Surprisingly, these C19-related changes in EEG power were more prominent in patients below age 70. Moreover, machine learning algorithms showed consistently higher accuracy in the binary classification of patients as C19 versus control using EEG power for subjects below age 70 compared to older ones, providing further evidence for the more severe impact of SARS-CoV-2 on brain rhythms in younger individuals irrespective of PCR diagnosis or symptomatology, and raising concerns over potential long-term effects of C19 on brain physiology in the adult population and the utility of EEG monitoring in C19 patients.

BrainWAVE: A Flexible Method for Noninvasive Stimulation of Brain Rhythms across Species.

Rhythmic neural activity, which coordinates brain regions and neurons to achieve multiple brain functions, is impaired in many diseases. Despite the therapeutic potential of driving brain rhythms, methods to noninvasively target deep brain regions are limited. Accordingly, we recently introduced a noninvasive stimulation approach using flickering lights and sounds ("flicker"). Flicker drives rhythmic activity in deep and superficial brain regions. Gamma flicker spurs immune function, clears pathogens, and rescues memory performance in mice with amyloid pathology. Here, we present substantial improvements to this approach that is flexible, user-friendly, and generalizable across multiple experimental settings and species. We present novel open-source methods for flicker stimulation across rodents and humans. We demonstrate rapid, cross-species induction of rhythmic activity without behavioral confounds in multiple settings from electrophysiology to neuroimaging. This flicker approach provides an exceptional opportunity to discover the therapeutic effects of brain rhythms across scales and species.

Neurocognitive, physiological, and biophysical effects of transcranial alternating current stimulation.

Transcranial alternating current stimulation (tACS) can modulate human neural activity and behavior. Accordingly, tACS has vast potential for cognitive research and brain disorder therapies. The stimulation generates oscillating electric fields in the brain that can bias neural spike timing, causing changes in local neural oscillatory power and cross-frequency and cross-area coherence. tACS affects cognitive performance by modulating underlying single or nested brain rhythms, local or distal synchronization, and metabolic activity. Clinically, stimulation tailored to abnormal neural oscillations shows promising results in alleviating psychiatric and neurological symptoms. We summarize the findings of tACS mechanisms, its use for cognitive applications, and novel developments for personalized stimulation.