Abnormalities in the evoked frontal oscillatory activity of first-episode psychosis: A TMS/EEG study

Increase in beta frequency phase synchronization and power after a session of high frequency repetitive transcranial magnetic stimulation to the primary motor cortex

High-frequency repetitive transcranial magnetic stimulation (rTMS) to the primary motor cortex (M1) is used to treat several neuropsychiatric disorders, but the detailed temporal dynamics of its effects on cortical connectivity remain unclear. Here, we stimulated four cortical targets used for rTMS (M1; dorsolateral-prefrontal cortex, DLPFC; anterior cingulate cortex, ACC; posterosuperior insula, PSI) with TMS coupled with high-density electroencephalography (TMS-EEG) to measure cortical excitability and oscillatory dynamics before and after active- and sham-M1-rTMS. Before and immediately after active or sham M1-rTMS (15 ​min, 3000 pulses at 10 ​Hz), single-pulse TMS-evoked EEG was recorded at the four targets in 20 healthy individuals. Cortical excitability and oscillatory measures were extracted at the main frequency bands (α [8-13 ​Hz], low-β [14-24 ​Hz], high-β [25-35 ​Hz]). Active-M1-rTMS increased high-β synchronization in electrodes near the stimulation area and remotely, in the contralateral hemisphere (p ​= ​0.026). Increased high-β synchronization (48-83 ​ms after TMS-EEG stimulation) was succeeded by enhancement in low-β power (86-144 ​ms after TMS-EEG stimulation) both locally and in the contralateral hemisphere (p ​= ​0.006). No significant differences were observed in stimulating the DLPFC, ACC, or PSI by TMS-EEG. M1-rTMS engaged a sequence of enhanced phase synchronization, followed by an increase in power occurring within M1, which spread to remote areas and persisted after the end of the stimulation session. These results are relevant to understanding the M1 neuroplastic effects of rTMS in health and may help in the development of informed rTMS therapies in disease.

Methodological Choices Matter: A Systematic Comparison of TMS-EEG Studies Targeting the Primary Motor Cortex

Transcranial magnetic stimulation (TMS) triggers time-locked cortical activity that can be recorded with electroencephalography (EEG). Transcranial evoked potentials (TEPs) are widely used to probe brain responses to TMS. Here, we systematically reviewed 137 published experiments that studied TEPs elicited from TMS to the human primary motor cortex (M1) in healthy individuals to investigate the impact of methodological choices. We scrutinized prevalent methodological choices and assessed how consistently they were reported in published papers. We extracted amplitudes and latencies from reported TEPs and compared specific TEP peaks and components between studies using distinct methods. Reporting of methodological details was overall sufficient, but some relevant information regarding the TMS settings and the recording and preprocessing of EEG data were missing in more than 25% of the included experiments. The published TEP latencies and amplitudes confirm the "prototypical" TEP waveform following stimulation of M1, comprising distinct N15, P30, N45, P60, N100, and P180 peaks. However, variations in amplitude were evident across studies. Higher stimulation intensities were associated with overall larger TEP amplitudes. Active noise masking during TMS generally resulted in lower TEP amplitudes compared to no or passive masking but did not specifically impact those TEP peaks linked to long-latency sensory processing. Studies implementing independent component analysis (ICA) for artifact removal generally reported lower TEP magnitudes. In summary, some aspects of reporting practices could be improved in future TEP studies to enable replication. Methodological choices, including TMS intensity and the use of noise masking or ICA, introduce systematic differences in reported TEP amplitudes. Further investigation into the significance of these and other methodological factors and their interactions is warranted.

Prefrontal Oscillatory Slowing in Early-Course Schizophrenia Is Associated With Worse Cognitive Performance and Negative Symptoms: A Transcranial Magnetic Stimulation-Electroencephalography Study

BACKGROUND

Abnormalities in dorsolateral prefrontal cortex (DLPFC) oscillations are neurophysiological signatures of schizophrenia thought to underlie its cognitive deficits. Transcranial magnetic stimulation with electroencephalography (TMS-EEG) provides a measure of cortical oscillations unaffected by sensory relay functionality and/or patients' level of engagement, which are important confounding factors in schizophrenia. Previous TMS-EEG work showed reduced fast, gamma-range oscillations and a slowing of the main DLPFC oscillatory frequency, or natural frequency, in chronic schizophrenia. However, it is unclear whether this DLPFC natural frequency slowing is present in early-course schizophrenia (EC-SCZ) and is associated with symptom severity and cognitive dysfunction.

METHODS

We applied TMS-EEG to the left DLPFC in 30 individuals with EC-SCZ and 28 healthy control participants. Goal-directed working memory performance was assessed using the AX-Continuous Performance Task. The EEG frequency with the highest cumulative power at the stimulation site, or natural frequency, was extracted. We also calculated the local relative spectral power as the average power in each frequency band divided by the broadband power.

RESULTS

Compared with the healthy control group, the EC-SCZ group had reduced DLPFC natural frequency (p = .0000002, Cohen's d = -2.32) and higher DLPFC beta-range relative spectral power (p = .0003, Cohen's d = 0.77). In the EC-SCZ group, the DLPFC natural frequency was inversely associated with negative symptoms. Across all participants, the beta band relative spectral power negatively correlated with AX-Continuous Performance Task performance.

CONCLUSIONS

DLPFC oscillatory slowing is an early pathophysiological biomarker of schizophrenia that is associated with its symptom severity and cognitive impairments. Future work should assess whether noninvasive neurostimulation, including repetitive TMS, can ameliorate prefrontal oscillatory deficits and related clinical functions in patients with EC-SCZ.

Investigating cortical excitability and inhibition in patients with schizophrenia: A TMS-EEG study

BACKGROUND

Transcranial magnetic stimulation (TMS) combined with electromyography (EMG) has widely been used as a non-invasive brain stimulation tool to assess excitation/inhibition (E/I) balance. E/I imbalance is a putative mechanism underlying symptoms in patients with schizophrenia. Combined TMS-electroencephalography (TMS-EEG) provides a detailed examination of cortical excitability to assess the pathophysiology of schizophrenia. This study aimed to investigate differences in TMS-evoked potentials (TEPs), TMS-related spectral perturbations (TRSP) and intertrial coherence (ITC) between patients with schizophrenia and healthy controls.

MATERIALS AND METHODS

TMS was applied over the motor cortex during EEG recording. Differences in TEPs, TRSP and ITC between the patient and healthy subjects were analysed for all electrodes at each time point, by applying multiple independent sample t-tests with a cluster-based permutation analysis to correct for multiple comparisons.

RESULTS

Patients demonstrated significantly reduced amplitudes of early and late TEP components compared to healthy controls. Patients also showed a significant reduction of early delta (50-160 ms) and theta TRSP (30-250ms),followed by a reduction in alpha and beta suppression (220-560 ms; 190-420 ms). Patients showed a reduction of both early (50-110 ms) gamma increase and later (180-230 ms) gamma suppression. Finally, the ITC was significantly lower in patients in the alpha band, from 30 to 260 ms.

CONCLUSION

Our findings support the putative role of impaired GABA-receptor mediated inhibition in schizophrenia impacting excitatory neurotransmission. Further studies can usefully elucidate mechanisms underlying specific symptoms clusters using TMS-EEG biometrics.

Transcranial Magnetic Stimulation-Electroencephalography for Biomarker Discovery in Psychiatry

Current diagnosis and treatment of psychiatric illnesses are still based on behavioral observations and self-reports, commonly leading to prolonged untreated illness. Biological markers (biomarkers) may offer an opportunity to revolutionize clinical psychiatry practice by helping provide faster and potentially more effective therapies. Transcranial magnetic stimulation concurrent with electroencephalography (TMS-EEG) is a noninvasive brain mapping methodology that can assess the functions and dynamics of specific brain circuitries in awake humans and aid in biomarker discovery. This article provides an overview of TMS-EEG-based biomarkers that may hold potential in psychiatry. The methodological readiness of the TMS-EEG approach and steps in the validation of TMS-EEG biomarkers for clinical utility are discussed. Biomarker discovery with TMS-EEG is in the early stages, and several validation steps are still required before clinical implementations are realized. Thus far, TMS-EEG predictors of response to magnetic brain stimulation treatments in particular have shown promise for translation to clinical practice. Larger-scale studies can confirm validation followed by biomarker-informed trials to assess added value compared to existing practice.

Classification of First-Episode Psychosis with EEG Signals: ciSSA and Machine Learning Approach

First-episode psychosis (FEP) typically marks the onset of severe psychiatric disorders and represents a critical period in the field of mental health. The early diagnosis of this condition is essential for timely intervention and improved clinical outcomes. In this study, the classification of FEP was investigated using the analysis of electroencephalography (EEG) signals and circulant spectrum analysis (ciSSA) sub-band signals. FEP poses a significant diagnostic challenge in the realm of mental health, and it is aimed at introducing a novel and effective approach for early diagnosis. To achieve this, the LASSO method was utilized to select the most significant features derived from entropy, frequency, and statistical-based characteristics obtained from ciSSA sub-band signals, as well as their hybrid combinations. Subsequently, a high-performance classification model has been developed using machine learning techniques, including ensemble, support vector machine (SVM), and artificial neural network (ANN) methods. The results of this study demonstrated that the hybrid features extracted from EEG signals' ciSSA sub-bands, in combination with the SVM method, achieved a high level of performance, with an area under curve (AUC) of 0.9893, an accuracy of 96.23%, a sensitivity of 0.966, a specificity of 0.956, a precision of 0.9667, and an F1 score of 0.9666. This has revealed the effectiveness of the ciSSA-based method for classifying FEP from EEG signals.

Effects of transcranial magnetic stimulation (TMS) current direction and pulse waveform on cortico-cortical connectivity: A registered report TMS-EEG study

Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) are a promising proxy for measuring effective connectivity, that is, the directed transmission of physiological signals along cortico-cortical tracts, and for developing connectivity-based biomarkers. A crucial point is how stimulation parameters may affect TEPs, as they may contribute to the general variability of findings across studies. Here, we manipulated two TMS parameters (i.e. current direction and pulse waveform) while measuring (a) an early TEP component reflecting contralateral inhibition of motor areas, namely, M1-P15, as an operative model of interhemispheric cortico-cortical connectivity, and (b) motor-evoked potentials (MEP) for the corticospinal pathway. Our results showed that these two TMS parameters are crucial to evoke the M1-P15, influencing its amplitude, latency, and replicability. Specifically, (a) M1-P15 amplitude was strongly affected by current direction in monophasic stimulation; (b) M1-P15 latency was significantly modulated by current direction for monophasic and biphasic pulses. The replicability of M1-P15 was substantial for the same stimulation condition. At the same time, it was poor when stimulation parameters were changed, suggesting that these factors must be controlled to obtain stable single-subject measures. Finally, MEP latency was modulated by current direction, whereas non-statistically significant changes were evident for amplitude. Overall, our study highlights the importance of TMS parameters for early TEP responses recording and suggests controlling their impact in developing connectivity biomarkers from TEPs. Moreover, these results point out that the excitability of the corticospinal tract, which is commonly used as a reference to set TMS intensity, may not correspond to the excitability of cortico-cortical pathways.

The role of neuronavigation in TMS-EEG studies: current applications and future perspectives

Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) allows measuring non-invasively the electrical response of the human cerebral cortex to a direct perturbation. Complementing TMS-EEG with a structural neuronavigation tool (nTMS-EEG) is key for accurately selecting cortical areas, targeting them, and adjusting the stimulation parameters based on some relevant anatomical priors. This step, together with the employment of visualization tools designed to perform a quality check of TMS-evoked potentials (TEPs) in real-time during acquisition, is key for maximizing the impact of the TMS pulse on the cortex and in ensuring highly reproducible measurements within sessions and across subjects. Moreover, storing stimulation parameters in the neuronavigation system can help in reproducing the stimulation parameters within and across experimental sessions and sharing them across research centers. Finally, the systematic employment of neuronavigation in TMS-EEG studies is also key to standardize measurements in clinical populations in search for reliable diagnostic and prognostic TMS-EEG-based biomarkers for neurological and psychiatric disorders.

Application of fast perturbational complexity index to the diagnosis and prognosis for disorders of consciousness

OBJECTIVE

Diagnosis and prognosis of patients with disorders of consciousness (DOC) is a challenge for neuroscience and clinical practice. Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) is an effective tool to measure the level of consciousness. However, a scientific and accurate method to quantify TMS-evoked activity is still lacking. This study applied fast perturbational complexity index (PCIst) to the diagnosis and prognosis of DOC patients.

METHODS

TMS-EEG data of 30 normal healthy participants (NOR) and 181 DOC patients were collected. The PCIst was used to assess the time-space complexity of TMS-evoked potentials (TEP). We selected parameters of PCIst in terms of data length, data delay, sampling rate and frequency band. In addition, we collected Coma Recovery Scale-Revised (CRS-R) values for 114 DOC patients after one year. Finally, we trained the classification and regression model.

RESULTS

1) PCIst shows the differences among NOR, minimally consciousness state (MCS) and unresponsive wakefulness syndrome (UWS) and has low computational cost. 2) Optimal parameters of data length and delay after TMS are 300ms and 101-300ms. Significant differences of PCIst at 5-8Hz and 9-12Hz bands are found among NOR, MCS and UWS groups. PCIst still works when TEP is down-sampled to 250 Hz. 3) PCIst at 9-12Hz shows the highest performance in diagnosis and prognosis of DOC.

CONCLUSIONS

This study confirms that PCIst can quantify the level of consciousness. PCIst is a potential measure for the diagnosis and prognosis of DOC patients.

A systematic review of TMS and neurophysiological biometrics in patients with schizophrenia

BACKGROUND

Transcranial magnetic stimulation can be combined with electromyography (TMS-EMG) and electroencephalography (TMS-EEG) to evaluate the excitatory and inhibitory functions of the cerebral cortex in a standardized manner. It has been postulated that schizophrenia is a disorder of functional neural connectivity underpinned by a relative imbalance of excitation and inhibition. The aim of this review was to provide a comprehensive overview of TMS-EMG and TMS-EEG research in schizophrenia, focused on excitation or inhibition, connectivity, motor cortical plasticity and the effect of antipsychotic medications, symptom severity and illness duration on TMS-EMG and TMS-EEG indices.

METHODS

We searched PsycINFO, Embase and Medline, from database inception to April 2020, for studies that included TMS outcomes in patients with schizophrenia. We used the following combination of search terms: transcranial magnetic stimulation OR tms AND interneurons OR glutamic acid OR gamma aminobutyric acid OR neural inhibition OR pyramidal neurons OR excita* OR inhibit* OR GABA* OR glutam* OR E-I balance OR excitation-inhibition balance AND schizoaffective disorder* OR Schizophrenia OR schizophreni*.

RESULTS

TMS-EMG and TMS-EEG measurements revealed deficits in excitation or inhibition, functional connectivity and motor cortical plasticity in patients with schizophrenia. Increased duration of the cortical silent period (a TMS-EMG marker of γ-aminobutyric acid B receptor activity) with clozapine was a relatively consistent finding.

LIMITATIONS

Most of the studies used patients with chronic schizophrenia and medicated patients, employed cross-sectional group comparisons and had small sample sizes.

CONCLUSION

TMS-EMG and TMS-EEG offer an opportunity to develop a novel and improved understanding of the physiologic processes that underlie schizophrenia and to assess the therapeutic effect of antipsychotic medications. In the future, these techniques may also help predict disease progression and further our understanding of the excitatory/inhibitory balance and its implications for mechanisms that underlie treatment-resistant schizophrenia.

Reduced TMS-evoked fast oscillations in the motor cortex predict the severity of positive symptoms in first-episode psychosis

Accumulating evidence points to neurophysiological abnormalities of the motor cortex in Schizophrenia (SCZ). However, whether these abnormalities represent a core biological feature of psychosis rather than a superimposed neurodegenerative process is yet to be defined, as it is their putative relationship with clinical symptoms. in this study, we used Transcranial Magnetic Stimulation coupled with electroencephalography (TMS-EEG) to probe the intrinsic oscillatory properties of motor (Brodmann Area 4, BA4) and non-motor (posterior parietal, BA7) cortical areas in twenty-three first-episode psychosis (FEP) patients and thirteen age and gender-matched healthy comparison (HC) subjects. Patients underwent clinical evaluation at baseline and six-months after the TMS-EEG session. We found that FEP patients had reduced EEG activity evoked by TMS of the motor cortex in the beta-2 (25-34 Hz) frequency band in a cluster of electrodes overlying BA4, relative to HC participants. Beta-2 deficits in the TMS-evoked EEG response correlated with worse positive psychotic symptoms at baseline and also predicted positive symptoms severity at six-month follow-up assessments. Altogether, these findings indicate that reduced TMS-evoked fast oscillatory activity in the motor cortex is an early neural abnormality that: 1) is present at illness onset; 2) may represent a state marker of psychosis; and 3) could play a role in the development of new tools of outcome prediction in psychotic patients.

TMS-EEG Biomarkers of Amnestic Mild Cognitive Impairment Due to Alzheimer's Disease: A Proof-of-Concept Six Years Prospective Study

Background: Early and affordable identification of subjects with amnestic mild cognitive impairment (aMCI) who will convert to Alzheimer's disease (AD) is a major scientific challenge. Objective: To investigate the neurophysiological hallmarks of sensorimotor cortex function in aMCI under the hypothesis that some may represent the plastic rearrangements induced by neurodegeneration, hence predictors of future conversion to AD. We sought to determine (1) whether the sensorimotor network shows peculiar alterations in patients with aMCI and (2) if sensorimotor network alterations predict long-term disease progression at the individual level. Methods: We studied several transcranial magnetic stimulation (TMS)-electroencephalogram (EEG) parameters of the sensorimotor cortex in a group of patients with aMCI and followed them for 6 years. We then identified aMCI who clinically converted to AD [prodromal to AD-MCI (pAD-MCI)] and those who remained cognitively stable [non-prodromal to AD-MCI (npAD-MCI)]. Results: Patients with aMCI showed reduced motor cortex (M1) excitability and disrupted EEG synchronization [decreased intertrial coherence (ITC)] in alpha, beta and gamma frequency bands compared to the control subjects. The degree of alteration in M1 excitability and alpha ITC was comparable between pAD-MCI and npAD-MCI. Importantly, beta and gamma ITC impairment in the stimulated M1 was greater in pAD-MCI than npAD-MCI. Furthermore, an additional parameter related to the waveform shape of scalp signals, reflecting time-specific alterations in global TMS-induced activity [stability of the dipolar activity (sDA)], discriminated npAD-MCI from MCI who will convert to AD. Discussion: The above mentioned specific cortical changes, reflecting deficit of synchronization within the cortico-basal ganglia-thalamo-cortical loop in aMCI, may reflect the pathological processes underlying AD. These changes could be tested in larger cohorts as neurophysiological biomarkers of AD.

Assessment of Cortical Plasticity in Schizophrenia by Transcranial Magnetic Stimulation

Neural plasticity refers to the capability of the brain to modify its structure and/or function and organization in response to a changing environment. Evidence shows that disruption of neuronal plasticity and altered functional connectivity between distinct brain networks contribute significantly to the pathophysiological mechanisms of schizophrenia. Transcranial magnetic stimulation has emerged as a noninvasive brain stimulation tool that can be utilized to investigate cortical excitability with the aim of probing neural plasticity mechanisms. In particular, in pathological disorders, such as schizophrenia, cortical dysfunction, such as an aberrant excitatory-inhibitory balance in cortical networks, altered cortical connectivity, and impairment of critical period timing are very important to be studied using different TMS paradigms. Studying such neurophysiological characteristics and plastic changes would help in elucidating different aspects of the pathophysiological mechanisms underlying schizophrenia. This review attempts to summarize the findings of available TMS studies with diagnostic and characterization aims, but not with therapeutic purposes, in schizophrenia. Findings provide further evidence of aberrant excitatory-inhibitory balance in cortical networks, mediated by neurotransmitter pathways such as the glutamate and GABA systems. Future studies with combining techniques, for instance, TMS with brain imaging or molecular genetic typing, would shed light on the characteristics and predictors of schizophrenia.

TMS-induced brain connectivity modulation in Genetic Generalized Epilepsy

OBJECTIVE

In epilepsy patients, Transcranial Magnetic Stimulation (TMS) may result in the induction and modulation of epileptiform discharges (EDs). We hereby investigate the modulatory effects of TMS on brain connectivity in Genetic Generalized Epilepsy (GGE) and explore their potential as a diagnostic biomarker in GGE.

METHODS

Patients with GGE (n=18) and healthy controls (n=11) were investigated with a paired-pulse TMS-EEG protocol. The brain network was studied at local and at global levels using Coherence as an EEG connectivity measure. Comparison of patients vs controls was performed in a time-resolved manner by analyzing comparatively pre- vs post-TMS brain networks.

RESULTS

There was statistically significant TMS-induced modulation of connectivity at specific frequency bands within groups and difference in TMS-induced modulation between the two groups. The most significant difference between patients and controls related to connectivity modulation in the γ band at 1-3 sec post-TMS (p=0.004).

CONCLUSIONS

TMS modulates the healthy and epileptic brain connectivity in different ways. Our results indicate that TMS-EEG connectivity analysis can be a basis for a diagnostic biomarker of GGE.

SIGNIFICANCE

The analysis identifies specific time periods and frequency bands of interest of TMS-induced connectivity modulation and elucidates the effect of TMS on the healthy and epileptic brain connectivity.

Investigating neurophysiological markers of impaired cognition in schizophrenia

Cognitive impairment is highly prevalent in schizophrenia and treatment options are severely limited. A greater understanding of the pathophysiology of impaired cognition would have broad implications, including for the development of effective treatments. In the current study we used a multimodal approach to identify neurophysiological markers of cognitive impairment in schizophrenia. Fifty-seven participants (30 schizophrenia, 27 controls) underwent neurobiological assessment (electroencephalography [EEG] and Transcranial Magnetic Stimulation combined with EEG [TMS-EEG]) and assessment of cognitive functioning using an n-back task and the MATRICS Consensus Cognitive Battery. Neurobiological outcome measures included oscillatory power during a 2-back task, TMS-related oscillations and TMS-evoked potentials (TEPs). Cognitive outcome measures were d prime and accurate reaction time on the 2-back and MATRICS domain scores. Compared to healthy controls, participants with schizophrenia showed significantly reduced theta oscillations in response to TMS, and trend level decreases in task-related theta and cortical reactivity (i.e. reduced N100 and N40 TEPs). Participants with schizophrenia also showed significantly impaired cognitive performance across all measures. Correlational analysis identified significant associations between cortical reactivity and TMS-related oscillations in both groups; and trend level associations between task-related oscillations and impaired cognition in schizophrenia. The current study provides experimental support for possible neurophysiological markers of cognitive impairment in schizophrenia. The potential implications of these findings, including for treatment development, are discussed.

TMS-EEG Research to Elucidate the Pathophysiological Neural Bases in Patients with Schizophrenia: A Systematic Review

Schizophrenia (SCZ) is a serious mental disorder, and its pathogenesis is complex. Recently, the glutamate hypothesis and the excitatory/inhibitory (E/I) imbalance hypothesis have been proposed as new pathological hypotheses for SCZ. Combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) is a non-invasive novel method that enables us to investigate the cortical activity in humans, and this modality is a suitable approach to evaluate these hypotheses. In this study, we systematically reviewed TMS-EEG studies that investigated the cortical dysfunction of SCZ to examine the emerging hypotheses for SCZ. The following search terms were set in this systematic review: (TMS or ‘transcranial magnetic stimulation’) and (EEG or electroencephalog*) and (schizophrenia). We inspected the articles written in English that examined humans and were published by March 2020 via MEDLINE, Embase, PsycINFO, and PubMed. The initial search generated 379 studies, and 14 articles were finally identified. The current review noted that patients with SCZ demonstrated the E/I deficits in the prefrontal cortex, whose dysfunctions were also associated with cognitive impairment and clinical severity. Moreover, TMS-induced gamma activity in the prefrontal cortex was related to positive symptoms, while theta/delta band activities were associated with negative symptoms in SCZ. Thus, this systematic review discusses aspects of the pathophysiological neural basis of SCZ that are not explained by the traditional dopamine hypothesis exclusively, based on the findings of previous TMS-EEG research, mainly in terms of the E/I imbalance hypothesis. In conclusion, TMS-EEG neurophysiology can be applied to establish objective biomarkers for better diagnosis as well as to develop new therapeutic strategies for patients with SCZ.

Examining and Modulating Neural Circuits in Psychiatric Disorders With Transcranial Magnetic Stimulation and Electroencephalography: Present Practices and Future Developments

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation technique uniquely equipped to both examine and modulate neural systems and related cognitive and behavioral functions in humans. As an examination tool, TMS can be used in combination with EEG (TMS-EEG) to elucidate directly, objectively, and noninvasively the intrinsic properties of a specific cortical region, including excitation, inhibition, reactivity, and oscillatory activity, irrespective of the individual's conscious effort. Additionally, when applied in repetitive patterns, TMS has been shown to modulate brain networks in healthy individuals, as well as ameliorate symptoms in individuals with psychiatric disorders. The key role of TMS in assessing and modulating neural dysfunctions and associated clinical and cognitive deficits in psychiatric populations is therefore becoming increasingly evident. In this article, the authors review TMS-EEG studies in schizophrenia and mood disorders, as most TMS-EEG studies to date have focused on individuals with these disorders. The authors present the evidence on the efficacy of repetitive TMS (rTMS) and theta burst stimulation (TBS), when targeting specific cortical areas, in modulating neural circuits and ameliorating symptoms and abnormal behaviors in individuals with psychiatric disorders, especially when informed by resting-state and task-related neuroimaging measures. Examples of how the combination of TMS-EEG assessments and rTMS and TBS paradigms can be utilized to both characterize and modulate neural circuit alterations in individuals with psychiatric disorders are also provided. This approach, along with the evaluation of the behavioral effects of TMS-related neuromodulation, has the potential to lead to the development of more effective and personalized interventions for individuals with psychiatric disorders.

TMS-EEG: An emerging tool to study the neurophysiologic biomarkers of psychiatric disorders

The etiology of psychiatric disorders remains largely unknown. The exploration of the neurobiological mechanisms of mental illness helps improve diagnostic efficacy and develop new therapies. This review focuses on the application of concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG) in various mental diseases, including major depressive disorder, bipolar disorder, schizophrenia, autism spectrum disorder, attention-deficit/hyperactivity disorder, substance use disorder, and insomnia. First, we summarize the commonly used protocols and output measures of TMS-EEG; then, we review the literature exploring the alterations in neural patterns, particularly cortical excitability, plasticity, and connectivity alterations, and studies that predict treatment responses and clinical states in mental disorders using TMS-EEG. Finally, we discuss the potential mechanisms underlying TMS-EEG in establishing biomarkers for psychiatric disorders and future research directions.

Understanding Cortical Dysfunction in Schizophrenia With TMS/EEG

In schizophrenia and related disorders, a deeper mechanistic understanding of neocortical dysfunction will be essential to developing new diagnostic and therapeutic techniques. To this end, combined transcranial magnetic stimulation and electroencephalography (TMS/EEG) provides a non-invasive tool to simultaneously perturb and measure neurophysiological correlates of cortical function, including oscillatory activity, cortical inhibition, connectivity, and synchronization. In this review, we summarize the findings from a variety of studies that apply TMS/EEG to understand the fundamental features of cortical dysfunction in schizophrenia. These results lend to future applications of TMS/EEG in understanding the pathophysiological mechanisms underlying cognitive deficits in schizophrenia.

Phase-Amplitude Markers of Synchrony and Noise: A Resting-State and TMS-EEG Study of Schizophrenia

The electroencephalogram (EEG) of schizophrenia patients is known to exhibit a reduction of signal-to-noise ratio and of phase locking, as well as a facilitation of excitability, in response to a variety of external stimuli. Here, we demonstrate these effects in transcranial magnetic stimulation (TMS)-evoked potentials and in the resting-state EEG. To ensure veracity, we used 3 weekly sessions and analyzed both resting-state and TMS-EEG data. For the TMS responses, our analysis verifies known results. For the resting state, we introduce the methodology of mean-normalized variation to the EEG analysis (quartile-based coefficient of variation), which allows for a comparison of narrow-band EEG amplitude fluctuations to narrow-band Gaussian noise. This reveals that amplitude fluctuations in the delta, alpha, and beta bands of healthy controls are different from those in schizophrenia patients, on time scales of tens of seconds. We conclude that the EEG-measured cortical activity patterns of schizophrenia patients are more similar to noise, both in alpha- and beta-resting state and in TMS responses. Our results suggest that the ability of neuronal populations to form stable, locally, and temporally correlated activity is reduced in schizophrenia, a conclusion, that is, in accord with previous experiments on TMS-EEG and on resting-state EEG.

Investigational and Therapeutic Applications of Transcranial Magnetic Stimulation in Schizophrenia

PURPOSE OF REVIEW

This current review summarizes the investigational and therapeutic applications of transcranial magnetic stimulation (TMS) in schizophrenia.

RECENT FINDINGS

Fairly consistent findings of an impaired cortical excitation-inhibition balance, cortical plasticity, and motor resonance have been reported in schizophrenia. Cortical connectivity impairments have also been demonstrated in motor and prefrontal brain regions. In terms of treatment, the best support is for 1-Hz TMS to the left temporoparietal cortex for the short-term treatment of persistent auditory hallucinations. High-frequency TMS to the left prefrontal cortex improves negative and cognitive symptoms, but with inconsistent and small effects. TMS combined with diverse brain mapping techniques and clinical evaluation can unravel critical brain-behavior relationships relevant to schizophrenia. These provide critical support to the conceptualization of schizophrenia as a connectopathy with anomalous cortical plasticity. Adaptive modulation of these aberrant brain networks in a neuroscience-informed manner drives short-term therapeutic gains in difficult-to-treat symptoms of schizophrenia.