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The coupling of gamma oscillation (~ 40+ Hz) amplitude to the phase of ongoing theta (~ 6 Hz) oscillations has been proposed to be directly relevant for memory performance. Current theories suggest that memory capacity scales with number of gamma cycles that can be fitted into the preferred phase of a theta cycle. Following this logic, transcranial alternating current stimulation (tACS) may be used to adjust theta cycles (increasing/decreasing theta frequency) to decrease or increase memory performance during stimulation. Here, we used individualized EEG-informed theta tACS to (1) experimentally “slow down” individual theta frequency (ITF), (2) evaluate cognitive after effects on a battery of memory and learning tasks, and (3) link the cognitive performance changes to tACS-induced effects on theta-band oscillations as measured by post EEG. We found frequency- and task-specific tACS after effects demonstrating a specific enhancement in memory capacity. This tACS-induced cognitive enhancement was specific to the visual memory task performed immediately after tACS offset, and specific to the ITF-1 Hz (slowing) stimulation condition and thus following a protocol specifically designed to slow down theta frequency to enhance memory capacity. Follow-up correlation analyses in this group linked the enhanced memory performance to increased left frontal-parietal theta-band connectivity. Interestingly, resting-state theta power immediately after tACS offset revealed a theta power increase not for the ITF-1 Hz group, but only for the ITF group where the tACS frequency was ‘optimal’ for entrainment. These results suggest that while individually calibrated tACS at peak frequency maximally modulates resting-state oscillatory power, tACS stimulation slightly below this optimal peak theta frequency is better suited to enhance memory capacity performance. Importantly, our results further suggest that such cognitive enhancement effects can last beyond the period of stimulation and are linked to increased network connectivity, opening the door towards more clinical and applied relevance of using tACS in cognitive rehabilitation and/or neurocognitive enhancement.

The treatment of major depressive disorder (MDD) is hampered by low chances of treatment response in each treatment step, which is partly due to a lack of firmly established outcome-predictive biomarkers. Here, we hypothesize that polygenic-informed EEG signatures may help predict antidepressant treatment response. Using a polygenic-informed electroencephalography (EEG) data-driven, data-reduction approach, we identify a brain network in a large cohort (N=1,123), and discover it is sex-specifically (male patients, N=617) associated with polygenic risk score (PRS) of antidepressant response. Subsequently, we demonstrate in three independent datasets the utility of the network in predicting response to antidepressant medication (male, N=232) as well as repetitive transcranial magnetic stimulation (rTMS) and concurrent psychotherapy (male, N=95). This network significantly improves a treatment response prediction model with age and baseline severity data (area under the curve, AUC=0.623 for medicaton; AUC=0.719 for rTMS). A predictive model for MDD patients, aimed at increasing the likelihood of being a responder to antidepressants or rTMS and concurrent psychotherapy based on only this network, yields a positive predictive value (PPV) of 69% for medication and 77% for rTMS. Finally, blinded out-of-sample validation of the network as predictor for psychotherapy response in another independent dataset (male, N=50) results in a within-subsample response rate of 50% (improvement of 56%). Overall, the findings provide a first proof-of-concept of a combined genetic and neurophysiological approach in the search for clinically-relevant biomarkers in psychiatric disorders, and should encourage researchers to incorporate genetic information, such as PRS, in their search for clinically relevant neuroimaging biomarkers.

Repeated pairing of transcranial magnetic stimulation (TMS) over left and right primary motor cortex (M1), at intensities sufficient to generate descending volleys, produces sustained increases in corticospinal excitability. In other paired associative stimulation (PAS) protocols, in which peripheral afferent stimulation is the first element, changes in corticospinal excitability achieved when the second stimulus consists of brief bursts of transcranial alternating current stimulation (tACS), are comparable to those obtained if TMS is used instead (McNickle and Carson 2015). The present aim was to determine whether associative effects are induced when the first stimulus of a cortico-cortical pair is tACS, or alternatively subthreshold TMS. Bursts of tACS (500 ms; 140 Hz; 1 mA) were associated (180 stimulus pairs) with single magnetic stimuli (120% resting motor threshold rMT) delivered over the opposite (left) M1. The tACS ended 6 ms prior to the TMS. In a separate condition, TMS (55% rMT) was delivered to right M1 6 ms before (120% rMT) TMS was applied over left M1. In a sham condition, TMS (120% rMT) was delivered to left M1 only. The limitations of null hypothesis significance testing are well documented. We therefore employed Bayes factors to assess evidence in support of experimental hypotheses—defined precisely in terms of predicted effect sizes, that these two novel variants of PAS increase corticospinal excitability. Although both interventions induced sustained (~ 20–30 min) increases in corticospinal excitability, the evidence in support of the experimental hypotheses (over specified alternatives) was generally greater for the paired TMS-TMS than the tACS-TMS conditions.

Antidepressants are widely prescribed, but their efficacy relative to placebo is modest, in part because the clinical diagnosis of major depression encompasses biologically heterogeneous conditions. Here, we sought to identify a neurobiological signature of response to antidepressant treatment as compared to placebo. We designed a latent-space machine-learning algorithm tailored for resting-state electroencephalography (EEG) and applied it to data from the largest imaging-coupled, placebo-controlled antidepressant study (n = 309). Symptom improvement was robustly predicted in a manner both specific for the antidepressant sertraline (versus placebo) and generalizable across different study sites and EEG equipment. This sertraline-predictive EEG signature generalized to two depression samples, wherein it reflected general antidepressant medication responsivity and related differentially to a repetitive transcranial magnetic stimulation treatment outcome. Furthermore, we found that the sertraline resting-state EEG signature indexed prefrontal neural responsivity, as measured by concurrent transcranial magnetic stimulation and EEG. Our findings advance the neurobiological understanding of antidepressant treatment through an EEG-tailored computational model and provide a clinical avenue for personalized treatment of depression.

The study of the physiological effects underlying brain response to transcranial magnetic stimulation is important to understand its impact on neurorehabilitation. We aim to analyze the impact of a transcranial magnetic stimulation protocol, the continuous theta burst (cTBS), on human neurophysiology, particularly on contralateral motor rhythms. cTBS was applied in 20 subjects over the primary motor cortex. We recorded brain electrical activity pre- and post-cTBS with electroencephalography both at rest and while performing motor tasks, to evaluate changes in brain oscillatory patterns such as mu and beta rhythms. Moreover, we measured motor-evoked potentials before and after cTBS to assess its impact on brain's excitability. On the hemisphere contralateral to the protocol, we did observe a significant increase in mu (p = 0.027) and beta (p = 0.006) rhythms from pre- to post-cTBS, at the beginning of arm elevation. The topology of action planning and motor execution suggests that cTBS produced an inhibitory effect that propagated to the contralateral hemisphere, thereby precluding the expected/desired excitation for therapy purposes. This novel approach provides support for the notion that this protocol induces inhibitory changes in contralateral motor rhythms, by decreasing desynchronization, contradicting the ipsilateral inhibition vs. contralateral disinhibition hypothesis. Our results have implications for personalized cTBS usage as a rehabilitation intervention, suggesting that an unexpected propagation of inhibition can occur.

Linguistic phrases are tracked in sentences even though there is no one-to-one acoustic phrase marker in the physical signal. This phenomenon suggests an automatic tracking of abstract linguistic structure that is endogenously generated by the brain. However, all studies investigating linguistic tracking compare conditions where either relevant information at linguistic timescales is available, or where this information is absent altogether (e.g., sentences versus word lists during passive listening). It is therefore unclear whether tracking at phrasal timescales is related to the content of language, or rather, results as a consequence of attending to the timescales that happen to match behaviourally relevant information. To investigate this question, we presented participants with sentences and word lists while recording their brain activity with magnetoencephalography (MEG). Participants performed passive, syllable, word, and word-combination tasks corresponding to attending to four different rates: one they would naturally attend to, syllable-rates, word-rates, and phrasal-rates, respectively. We replicated overall findings of stronger phrasal-rate tracking measured with mutual information for sentences compared to word lists across the classical language network. However, in the inferior frontal gyrus (IFG) we found a task effect suggesting stronger phrasal-rate tracking during the word-combination task independent of the presence of linguistic structure, as well as stronger delta-band connectivity during this task. These results suggest that extracting linguistic information at phrasal rates occurs automatically with or without the presence of an additional task, but also that IFG might be important for temporal integration across various perceptual domains.

Depression is a common mental disorder that affects many people worldwide, while a significant proportion of patients remain non-responsive to antidepressant medications. Alternative treatment options such as ketamine therapy and repetitive transcranial magnetic stimulation (rTMS) therapy are offered nowadays. This study aims to describe and compare the acute antidepressive efficacy of both, intramuscular ketamine and rTMS in depression patients seeking help in a naturalistic clinical mental health setting. The clinical records of 24 patients with treatment resistant depression were collected from the clinical base of a real life clinic. Twelve patients were treated with intramuscular ketamine, twice weekly for 8 sessions, and twelve patients were treated with 30 sessions of left dorsolateral prefrontal cortex – intermittent theta-burst stimulation (DLPFC-iTBS). Using three clinical assessments (HDRS, HAM-A, BDI-II), our data reveal that both therapies led to significant improvement in symptoms from pre- to post- treatment, as well as that the two experimental groups did not differ significantly with respect to pre- to post- depressive and anxiety symptoms, indicating that the effect of both experimental groups in our sample was equally effective. Furthermore, our results showed high remission and response rates in both groups, with no statistical differences between the patients of ketamine group and rTMS group in remission and response rates. We show a significant pre- to post- treatment reduction in depressive and anxiety symptoms, with no significant differences between the two experimental groups, indicating that the effect of both therapies was equally effective in our limited sample.

Transcranial alternating current stimulation (tACS) can be used to study causal contributions of oscillatory brain mechanisms to cognition and behavior. For instance, individual alpha frequency (IAF) tACS was reported to enhance alpha power and impact visuospatial attention performance. Unfortunately, such results have been inconsistent and difficult to replicate. In tACS, stimulation generally involves one frequency, sometimes individually calibrated to a peak value observed in an M/EEG power spectrum. Yet, the 'peak' actually observed in such power spectra often contains a broader range of frequencies, raising the question whether a biologically calibrated tACS protocol containing this fuller range of alpha-band frequencies might be more effective. Here, we introduce 'Broadband-alpha-tACS', a complex individually calibrated electrical stimulation protocol. We band-pass filtered left posterior resting-state EEG data around the IAF (± 2 Hz), and converted that time series into an electrical waveform for tACS stimulation of that same left posterior parietal cortex location. In other words, we stimulated a brain region with a 'replay' of its own alpha-band frequency content, based on spontaneous activity. Within-subjects (N = 24), we compared to a sham tACS session the effects of broadband-alpha tACS, power-matched spectral inverse ('alpha-removed') control tACS, and individual alpha frequency (IAF) tACS, on EEG alpha power and performance in an endogenous attention task previously reported to be affected by alpha tACS. Broadband-alpha-tACS significantly modulated attention task performance (i.e., reduced the rightward visuospatial attention bias in trials without distractors, and reduced attention benefits). Alpha-removed tACS also reduced the rightward visuospatial attention bias. IAF-tACS did not significantly modulate attention task performance compared to sham tACS, but also did not statistically significantly differ from broadband-alpha-tACS. This new broadband-alpha-tACS approach seems promising, but should be further explored and validated in future studies.

Background: The prefrontal cortex can be partialized in various anatomical and functional sub regions. Among those regions, both right dorsolateral prefrontal cortex (rDLPFC) and ventromedial prefrontal cortex (VMPFC) have been associated with risk-taking behavior based on neuroimaging studies. Noninvasive brain stimulation (NIBS) studies aiming at demonstrating the functional relevance of neural activity in these areas almost exclusively focused on the rDLPFC, where its experimental stimulation with a (generally) inhibitory protocol lead to a measurable increase in risk-taking behavior due to reduced cognitive control. The functional relevance of VMPFC in risk-taking behavior has not yet been addressed using NIBS, although multiple neuroimaging studies correlate this area’s activity with valuation. Objective/Hypothesis: Here, we used NIBS to investigate the functional relevance of both, the rDLPFC and VMPFC in risk-taking behavior. We hypothesized that, compared to sham stimulation, VMPFC suppression leads to a reduction in risk-taking behavior by reducing the appeal to higher value options and consequently the attractiveness of riskier options, whereas rDLPFC suppression leads to an increase in risk taking, replicating previous findings. Methods: We applied continuous theta burst stimulation (cTBS), a generally inhibitory protocol, to stimulate either VMPFC or DLPFC before the execution of the computerized Maastricht Gambling Task (MGT) in a within-subject design with 30 participants. The MGT allowed the analysis of potential brain region-specific effects of cTBS on risk-taking behavior such as participants’ choices of average values, probabilities, and response time. Results: cTBS applied to either rDLPFC or VMPFC both led to an increase in risk-taking behavior and in the average value chosen as compared to sham TMS. No effect on the choice of probabilities was found. A significant increase in response time was observed exclusively after suppressing rDLPFC. We speculate that these similar behavioral consequences following cTBS over DLPFC and VMPFC are likely due to the strong anatomical and functional interconnection between both brain regions. Keywords: Risk-taking behavior, TMS, cTBS, rDLPFC, VMPFC

OBJECTIVES: Most anesthetic drugs used for electroconvulsive therapy (ECT) have dose-dependent anticonvulsive effects, counter-acting seizure induction, lowering seizure quality. However, a consummate drug for ECT anesthesia has not yet been established. Therefore, in this study, we aimed to investigate the effects of etomidate, thiopental, propofol and co-administration of ketamine-propofol (ketofol) on seizure quality and hemodynamic safety.METHODS: Registries of 121 patients (1077 sessions) were retrospectively evaluated. The effects of anesthetics on ECT-related parameters (stimulation charge, central seizure duration, number of failed stimulation trials, mean arterial pressure, and peak heart rate) were analyzed via linear mixed-effects models.RESULTS: Overall, the seizure duration decreased, and the stimulation charge increased in time with continuing sessions within a course of ECT. The decrease in seizure duration and the increase in required stimulation charge was significantly lower with etomidate and ketofol. Additionally, ketofol was significantly related to a lower number of failed stimulation trials compared to propofol. Ketofol and propofol use was associated with a significantly lower postictal mean arterial pressure.CONCLUSION: Ketofol and etomidate were equivalently superior in the rate of decrease in seizure duration and the required elevation in stimulus charge, which would interpret into valuable clinical guidance, especially for "seizure resistant" patients, and their use may potentially lower ECT related cognitive side effects.

The ability to control sexual urges and impulses is essential to achieve individual and social harmony. Failing to regulate sexual behavior can lead to the interference with daily life goals, sexual diseases transmission and moral violations, among others. The dual control model of sexual response proposes that an imbalance between sexual excitation and sexual inhibition mechanisms may lead to sexual dysregulation, thereby explaining problematic sexual behavior. Interindividual differences in self-control and testosterone levels are likely to modulate sexual regulation mechanisms, but these individual features have scarcely been studied in the context of compulsive sexual behavior. This study investigated the role of sexual excitation and inhibition, self-control and testosterone levels in predicting individuals' proneness to display compulsive sexual behavior. Seventy healthy young males provided a saliva sample for testosterone measurements and filled in questionnaires on self-control, sexual excitation, sexual inhibition, sexual compulsivity and sexual behavior. High testosterone levels and low self-control were associated with higher sexual compulsivity scores. Additionally, testosterone levels and sexual inhibition negatively predicted the frequency of sexual behavior with a partner. The results of our study highlight the joint role of psychological traits and testosterone levels in compulsive sexual behavior proneness, providing implications regarding the prevention and treatment of this condition in young males. ispartof: FRONTIERS IN PSYCHOLOGY vol:12 ispartof: location:Switzerland status: published

This Viewpoint discusses 3 areas in which the mental health care sector can play an active role to mitigate climate change: clinical practice, educational sessions, and research.

Successful forgetting of unwanted memories is crucial for goal-directed behavior and mental wellbeing. While memory retention strengthens memory traces, it is unclear what happens to memory traces of events that are actively forgotten. Using intracranial EEG recordings from lateral temporal cortex, we find that memory traces for actively forgotten information are partially preserved and exhibit unique neural signatures. Memory traces of successfully remembered items show stronger encoding-retrieval similarity in gamma frequency patterns. By contrast, encoding-retrieval similarity of item-specific memory traces of actively forgotten items depend on activity at alpha/beta frequencies commonly associated with functional inhibition. Additional analyses revealed selective modification of item-specific patterns of connectivity and top-down information flow from dorsolateral prefrontal cortex to lateral temporal cortex in memory traces of intentionally forgotten items. These results suggest that intentional forgetting relies more on inhibitory top-down connections than intentional remembering, resulting in inhibitory memory traces with unique neural signatures and representational formats., The authors used intracranial EEG recordings from patients with epilepsy to show that successful intentional forgetting is due to a selective modification of item-specific top-down connections and not simply a degradation of the memory traces.

Objectives: Transcranial magnetic stimulation, in particular continuous theta burst (cTBS), has been proposed for stroke rehabilitation, based on the concept that inhibition of the healthy hemisphere helps promote the recovery of the lesioned one. We aimed to study its effects on cortical excitability, oscillatory patterns, and motor function, the main aim being to identify potentially beneficial neurophysiological effects.Materials and Methods: We applied randomized real or placebo stimulation over the unaffected primary motor cortex of 10 subacute (7 ± 3 days) post-stroke patients. Neurophysiological measurements were performed using electroencephalography and electromyography. Motor function was assessed with the Wolf Motor Function Test. We performed a repeated measure study with the recordings taken pre-, post-cTBS, and at 3 months' follow-up.Results: We investigated changes in motor rhythms during arm elevation and thumb opposition tasks and found significant changes in beta power of the affected thumb's opposition, specifically after real cTBS. Our results are consistent with an excitatory response (increase in event-related desynchronization) in the sensorimotor cortical areas of the affected hemisphere, after stimulation. Neither peak-to-peak amplitude of motor-evoked potentials nor motor performance were significantly altered.Conclusions: Consistently with the theoretical prediction, this contralateral inhibitory stimulation paradigm changes neurophysiology, leading to a significant excitatory impact on the cortical oscillatory patterns of the contralateral hemisphere. These proof-of-concept results provide evidence for the potential role of continuous TBS in the neurorehabilitation of post-stroke patients. We suggest that these changes in ERS/ERD patterns should be further explored in future phase IIb/phase III clinical trials, in larger samples of poststroke patients.

Cognitive abilities are impaired in patients with pituitary adenoma. However, studies on attention processing impairment in preoperative patients and attention processing recovery after transsphenoidal adenomectomy are lacking. The study aims to identify the electrophysiological change that relates to attention processing in pituitary patients before and after treatment. Twenty five preoperative pituitary patients and 25 follow-up postoperative patients were recruited. 27 healthy controls (HCs) were matched to the patients with age, gender, and education. Event-related potentials were used to investigate the attention processing in the preoperative patients, postoperative patients, and HCs. Across three groups, all emotional stimuli evoked P200 components. Compared with the HCs or postoperative patients, the amplitudes of P200 in the preoperative patients were higher. Moreover, The amplitudes of P200 decreased in the postoperative patients, which were similar to that in the HCs. The attention processing was improved after surgery, but no significant differences were detected between the postoperative patients and HCs. Abnormal hormone levels may be relevant to the factor that impair attention processing. Compared with that of the HCs and postoperative patients, the P200 component elicited by negative stimuli is higher in preoperative patients, which may illustrate compensatory activity after attention impairments. Furthermore, these data indicate that improvements in attention processing may be attributed to the amelioration of endocrine disorders. This study shows that the P200 component may be used to diagnose attention processing in preoperative pituitary patients and prove the improvement of attention processing in postoperative patients.

To investigate whether beta oscillations are causally related to motor inhibition, thirty-six participants underwent two concurrent transcranial alternating current stimulation (tACS) and electroencephalography (EEG) sessions during which either beta (20 Hz) or gamma (70 Hz) stimulation was applied while participants performed a stop-signal task. In addition, we acquired magnetic resonance images to simulate the electric field during tACS. 20 Hz stimulation targeted at the pre-supplementary motor area enhanced inhibition and increased beta oscillatory power around the time of the stop-signal in trials directly following stimulation. The increase in inhibition on stop trials followed a dose-response relationship with the strength of the individually simulated electric field. Computational modeling revealed that 20 and 70 Hz stimulation had opposite effects on the braking process. These results highlight that the effects of tACS are state-dependent and demonstrate that fronto-central beta activity is causally related to successful motor inhibition, supporting its use as a functional biomarker. ispartof: iScience vol:25 issue:5 pages:104338- ispartof: location:United States status: Published online

The evaluation of transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEPs) promises valuable information about fundamental brain related mechanisms and may serve as a diagnostic tool for clinical monitoring of therapeutic progress or surgery procedures. However, reports about spontaneous fluctuations of MEP amplitudes causing high intra-individual variability have led to increased concerns about the reliability of this measure. One possible cause for high variability of MEPs could be neuronal oscillatory activity, which reflects fluctuations of membrane potentials that systematically increase and decrease the excitability of neuronal networks. Here, we investigate the dependence of MEP amplitude on oscillation power and phase by combining the application of single pulse TMS over the primary motor cortex with concurrent recordings of electromyography and electroencephalography. Our results show that MEP amplitude is correlated to alpha phase, alpha power as well as beta phase. These findings may help explain corticospinal excitability fluctuations by highlighting the modulatory effect of alpha and beta phase on MEPs. In the future, controlling for such a causal relationship may allow for the development of new protocols, improve this method as a (diagnostic) tool and increase the specificity and efficacy of general TMS applications.

Transcranial alternating current stimulation (tACS) at 10Hz has been shown to modulate spatial attention. However, the frequency-specificity and the oscillatory changes underlying this tACS effect are still largely unclear. Here, we applied high-definition tACS at individual alpha frequency (IAF), two control frequencies (IAF+/-2Hz) and sham to the left posterior parietal cortex and measured its effects on visuospatial attention performance and offline alpha power (using electroencephalography, EEG). We revealed a behavioural and electrophysiological stimulation effect relative to sham for IAF but not control frequency stimulation conditions: there was a leftward lateralization of alpha power for IAF tACS, which differed from sham for the first out of three minutes following tACS. At a high value of this EEG effect (moderation effect), we observed a leftward attention bias relative to sham. This effect was task-specific, i.e. it could be found in an endogenous attention but not in a detection task. Only in the IAF tACS condition, we also found a correlation between the magnitude of the alpha lateralization and the attentional bias effect. Our results support a functional role of alpha oscillations in visuospatial attention and the potential of tACS to modulate it. The frequency-specificity of the effects suggests that an individualization of the stimulation frequency is necessary in heterogeneous target groups with a large variation in IAF.

The human brain has limited storage capacity often challenging the encoding and recall of a long series of multiple items. Different encoding strategies are therefore employed to optimize performance in memory processes such as chunking where particular items are ‘grouped’ to reduce the number of items to store artificially. Additionally, related to the position of an item within a series, there is a tendency to remember the first and last items on the list better than the middle ones, which calls the “serial position effect”. Although relatively well-established in behavioral research, the neuronal mechanisms underlying such encoding strategies and memory effects remain poorly understood. Here, we used event-related EEG oscillation analyses to unravel the neuronal substrates of serial encoding strategies and effects during the behaviorally controlled execution of the digit span task. We recorded EEG in forty-four healthy young-adult participants during a backward digit span (ds) task with two difficulty levels (i.e., 3-ds and 5-ds). Participants were asked to recall the digits in reverse order after the presentation of each set. We analyzed the pattern of event-related delta and theta oscillatory power in the time-frequency domain over fronto-central and parieto-occipital areas during the item (digit) list encoding, focusing on how these oscillatory responses changed with each subsequent digit being encoded in the series. Results showed that the development of event-related delta power evoked by digits in each series matched the ‘serial position curve’, with higher delta power being present during the first, and especially last, digits as compared to digits presented in the middle of a set, for both difficulty levels. Event-related theta power, in contrast, rather resembled a neural correlate of a chunking pattern where, during the 5-ds encoding, a clear change in event-related theta occurred around the third/fourth positions, with decreasing power values for later digits. This suggests that different oscillatory mechanisms linked to different frequency bands may code for the different encoding strategies and effects in serial item presentation. Furthermore, recall-EEG correlations suggested that participants with higher fronto-central delta responses during digit encoding showed also higher recall scores. The here presented findings contribute to our understanding of the neural oscillatory mechanisms underlying multiple item encoding, directly informing recent efforts towards memory enhancement through targeted oscillation-based neuromodulation. Türkiye Bilimsel ve Teknolojik Araştırma Kurumu

BACKGROUND: Bipolar spectrum disorders (BSD) are highly disabling, with rapid cycling being treatment resistant. High-dose levothyroxine (HDT) has been reported to be effective. Diagnosis is associated with mutations in thyroid-activating enzymes and cerebral transporter protein carrier. Repetitive transcranial magnetic stimulation (rTMS) has neuroplastic effects.METHODS: We report data on 55 severely symptomatic patients with rapid-cycling BSD treated with a combination protocol of HDT and rTMS. Of the patients, 31 patients (56.4%) were female and 40 (72.7%) had at least one additional diagnosis.RESULTS: Patients were evaluated at three monthly intervals after acute treatment. Remission was measured using the Sheehan Disability Scale (SDS). The average number of medications prescribed was 1.8, with 32 patients (58.2%) needing only levothyroxine. The average dose of levothyroxine was 303.7 mcg (50 mcg-1000 mcg). A total of 53 patients were in remission (96.4%), with an average duration of 2.0 years. The SDS scores decreased significantly (Cohen's d = 2.61 (95% C.I. 1.81 to 2.83, p < 0.001). One patient had reversible side effects. A total of 52 (94.3%) patients had Deiodinase 1 and 2 (DiO1/DiO2) or SLCO1C1 protein carrier gene mutations.CONCLUSION: The data support the safety and acceptability of combined HDT/rTMS. Patients achieved long remissions with substantial improvements in quality of life.

In this open-label naturalistic study, we assess the feasibility, tolerability, and effectiveness of a repetitive transcranial magnetic stimulation protocol with a reduced total pulse number for treating patients suffering from bipolar disorder type II. All patients received one rTMS treatment session of 1000 pulses for 20 consecutive working days, accumulating to 20.000 rTMS pulses applied over 4 weeks. We measured the patients’ symptoms before the start, halfway through, directly after, and one month after treatment. We quantified the depression symptoms using both the Beck depression inventory scale and the symptom checklist-90 depression subscale. Patients showed a significant reduction in depression symptoms directly after treatment and an even further reduction one month after treatment. The remission rates were at 26% halfway through treatment (after the 10th session), 61% directly after treatment (after the 20th session), and increased to 78% at the 1-month follow-up. Importantly, the protocol proved to be feasible and highly tolerable in this patient population, with no adverse effects being reported. Considering these positive results, further research should focus on replicating these findings in larger clinical samples with control groups and longer follow-up periods, while potentially adding maintenance sessions to optimize the treatment effect and stability for bipolar disorder type II patients.

Neuronal oscillations putatively track speech in order to optimize sensory processing. However, it is unclear how isochronous brain oscillations can track pseudo-rhythmic speech input. Here we propose that oscillations can track pseudo-rhythmic speech when considering that speech time is dependent on content-based predictions flowing from internal language models. We show that temporal dynamics of speech are dependent on the predictability of words in a sentence. A computational model including oscillations, feedback, and inhibition is able to track pseudo-rhythmic speech input. As the model processes, it generates temporal phase codes, which are a candidate mechanism for carrying information forward in time. The model is optimally sensitive to the natural temporal speech dynamics and can explain empirical data on temporal speech illusions. Our results suggest that speech tracking does not have to rely only on the acoustics but could also exploit ongoing interactions between oscillations and constraints flowing from internal language models.

Background: Electroconvulsive therapy (ECT) is the most effective treatment for severe major depressive episodes (MDEs). Nonetheless, firmly established associations between ECT outcomes and biological variables are currently lacking. Polygenic risk scores (PRSs) carry clinical potential, but associations with treatment response in psychiatry are seldom reported. Here, we examined whether PRSs for major depressive disorder, schizophrenia (SCZ), cross-disorder, and pharmacological antidepressant response are associated with ECT effectiveness.Methods: A total of 288 patients with MDE from 3 countries were included. The main outcome was a change in the 17-item Hamilton Depression Rating Scale scores from before to after ECT treatment. Secondary outcomes were response and remission. Regression analyses with PRSs as independent variables and several covariates were performed. Explained variance (R2) at the optimal p-value threshold is reported.Results: In the 266 subjects passing quality control, the PRS-SCZ was positively associated with a larger Hamilton Depression Rating Scale decrease in linear regression (optimal p-value threshold = .05, R2 = 6.94%, p < .0001), which was consistent across countries: Ireland (R2 = 8.18%, p = .0013), Belgium (R2 = 6.83%, p = .016), and the Netherlands (R2 = 7.92%, p = .0077). The PRS-SCZ was also positively associated with remission (R2 = 4.63%, p = .0018). Sensitivity and subgroup analyses, including in MDE without psychotic features (R2 = 4.42%, p = .0024) and unipolar MDE only (R2 = 9.08%, p < .0001), confirmed the results. The other PRSs were not associated with a change in the Hamilton Depression Rating Scale score at the predefined Bonferroni-corrected significance threshold.Conclusions: A linear association between PRS-SCZ and ECT outcome was uncovered. Although it is too early to adopt PRSs in ECT clinical decision making, these findings strengthen the positioning of PRS-SCZ as relevant to treatment response in psychiatry.

Neural oscillations in the theta range (4–8 Hz) are thought to underlie associative memory function in the hippocampal-cortical network. While there is ample evidence supporting a role of theta oscillations in animal and human memory, most evidence is correlational. Non-invasive brain stimulation (NIBS) can be employed to modulate cortical oscillatory activity to influence brain activity, and possibly modulate deeper brain regions, such as hippocampus, through strong and reliable cortico-hippocampal functional connections. We applied focal transcranial alternating current stimulation (tACS) at 6 Hz over left parietal cortex to modulate brain activity in the putative cortico-hippocampal network to influence associative memory encoding. After encoding and brain stimulation, participants completed an associative memory and a perceptual recognition task. Results showed that theta tACS significantly decreased associative memory performance but did not affect perceptual memory performance. These results show that parietal theta tACS modulates associative processing separately from perceptual processing, and further substantiate the hypothesis that theta oscillations are implicated in the cortico-hippocampal network and associative encoding.

Rhythmic stimulation can be applied to modulate neuronal oscillations. Such ‘entrainment’ is optimized when stimulation frequency is individually calibrated based on magneto/encephalography markers. It remains unknown how consistent such individual markers are across days/sessions, within a session, or across cognitive states, hemispheres and estimation methods, especially in a realistic, practical, lab setting. We here estimated individual alpha frequency (IAF) repeatedly from short electroencephalography (EEG) measurements at rest or during an attention task (cognitive state), using single parieto-occipital electrodes in 24 participants on 4 days (between-sessions), with multiple measurements over an hour on 1 day (within-session). First, we introduce an algorithm to automatically reject power spectra without a sufficiently clear peak to ensure unbiased IAF estimations. Then we estimated IAF via the traditional ‘maximum’ method and a ‘Gaussian fit’ method. IAF was reliable within- and between-sessions for both cognitive states and hemispheres, though task-IAF estimates tended to be more variable. Overall, the ‘Gaussian fit’ method was more reliable than the ‘maximum’ method. Furthermore, we evaluated how far from an approximated ‘true’ task-related IAF the selected ‘stimulation frequency’ was, when calibrating this frequency based on a short rest-EEG, a short task-EEG, or simply selecting 10 Hz for all participants. For the ‘maximum’ method, rest-EEG calibration was best, followed by task-EEG, and then 10 Hz. For the ‘Gaussian fit’ method, rest-EEG and task-EEG-based calibration were similarly accurate, and better than 10 Hz. These results lead to concrete recommendations about valid, and automated, estimation of individual oscillation markers in experimental and clinical settings.

Background In contrast to cisgender persons, transgender persons identify with a different gender than the one assigned at birth. Although research on the underlying neurobiology of transgender persons has been accumulating over the years, neuroimaging studies in this relatively rare population are often based on very small samples resulting in discrepant findings. Aim To examine the neurobiology of transgender persons in a large sample. Methods Using a mega-analytic approach, structural MRI data of 803 non-hormonally treated transgender men (TM, n = 214, female assigned at birth with male gender identity), transgender women (TW, n = 172, male assigned at birth with female gender identity), cisgender men (CM, n = 221, male assigned at birth with male gender identity) and cisgender women (CW, n = 196, female assigned at birth with female gender identity) were analyzed. Outcomes Structural brain measures, including grey matter volume, cortical surface area, and cortical thickness. RESULTS Transgender persons differed significantly from cisgender persons with respect to (sub)cortical brain volumes and surface area, but not cortical thickness. Contrasting the 4 groups (TM, TW, CM, and CW), we observed a variety of patterns that not only depended on the direction of gender identity (towards male or towards female) but also on the brain measure as well as the brain region examined. Clinical Translation The outcomes of this large-scale study may provide a normative framework that may become useful in clinical studies. Strengths and Limitations While this is the largest study of MRI data in transgender persons to date, the analyses conducted were governed (and restricted) by the type of data collected across all participating sites. CONCLUSION Rather than being merely shifted towards either end of the male-female spectrum, transgender persons seem to present with their own unique brain phenotype.

Coarse-to-fine theories of vision propose that the coarse information carried by the low spatial frequencies (LSF) of visual input guides the integration of finer, high spatial frequency (HSF) detail. Whether and how LSF modulates HSF processing in naturalistic broad-band stimuli is still unclear. Here we used multivariate decoding of EEG signals to separate the respective contribution of LSF and HSF to the neural response evoked by broad-band images. Participants viewed images of human faces, monkey faces and phase-scrambled versions that were either broad-band or filtered to contain LSF or HSF. We trained classifiers on EEG scalp-patterns evoked by filtered scrambled stimuli and evaluated the derived models on broad-band scrambled and intact trials. We found reduced HSF contribution when LSF was informative towards image content, indicating that coarse information does guide the processing of fine detail, in line with coarse-to-fine theories. We discuss the potential cortical mechanisms underlying such coarse-to-fine feedback.

Sentences contain structure that determines their meaning beyond that of individual words. An influential study by Ding and colleagues (2016) used frequency tagging of phrases and sentences to show that the human brain is sensitive to structure by finding peaks of neural power at the rate at which structures were presented. Since then, there has been a rich debate on how to best explain this pattern of results with profound impact on the language sciences. Models that use hierarchical structure building, as well as models based on associative sequence processing, can predict the neural response, creating an inferential impasse as to which class of models explains the nature of the linguistic computations reflected in the neural readout. In the current manuscript, we discuss pitfalls and common fallacies seen in the conclusions drawn in the literature illustrated by various simulations. We conclude that inferring the neural operations of sentence processing based on these neural data, and any like it, alone, is insufficient. We discuss how to best evaluate models and how to approach the modeling of neural readouts to sentence processing in a manner that remains faithful to cognitive, neural, and linguistic principles.

Introduction Rapid cycling Bipolar disorder and mixed affective states are treatment resistant conditions. Standard treatments are ineffective. Homozygous polymorphism of DIO2 gene is associated 3.75-fold risk of bipolar disorder. Objectives High Dose Levothyroxine combined with repetitive transcranial magnetic stimulation (rTMS) in Rapid cycling Bipolar disorder: Is it thyroid disease? Methods 20 RCBPD with ICD-10criteria for bipolar disorder. All were severely symptomatic. TFTs and ECGs were monitored weekly with cardiology and endocrinology backup. Genetic testing was undertaken for DiO1/DiO2 status. Results 17 were female, average age 32.4 yrs. 19/20 had Single nucleotide polymorphisms (SNP) of either DIO1, DIO2 or both. All but two patients were treated with rTMS to induce cerebral neuroplasticity. Average pre-treatment fT4 was 17.0 pmol/L , and fT3 4.5 pmol/L Average post-treatment, fT4 was 59.7 pmol/L and fT3 5.3 pmol/L. Average fT4:fT3 ratio pre-treatment was 4:1, and post-treatment was 5:1. HDL range was 200-800 mcg daily for remission. Average dose 472 mcg daily. Discontinuation rate was 0%. All patients had ECG and cardiac review One patient required a dose reduction because of minimal side effects 12 patients needed one mood stabiliser All were in remission for a minimum of 6 months. Conclusions We speculate that BPD may be a form of cerebral hypothyroidism and that HDL helps to overcome the deficit while robust inactivating deiodinases in the periphery protect from systemic thyrotoxicosis. This is evidenced by findings of normal clinical examination and elevated rT3. rTMS exercises its well established neuroplastic effect, helping to achieve and maintain remission as an adjunct to HDL. Disclosure The London Psychiatry Centre (TLPC) has pending patents for the combined protocol of rTMS and/or Thyroid hormones depending on the territory: - Pending US Patent application: (and/or) US20200384279 - Pending European patent appl

BackgroundMost of our decisions involve a certain degree of risk regarding the outcomes of our choices. People vary in the way they make decisions, resulting in different levels of risk-taking behavior. These differences have been linked to prefrontal theta band activity. However, a direct functional relationship between prefrontal theta band activity and risk-taking has not yet been demonstrated.ObjectiveWe used noninvasive brain stimulation to test the functional relevance of prefrontal oscillatory theta activity for the regulatory control of risk-taking behavior.MethodsIn a within-subject experiment, 31 healthy participants received theta (6.5 Hertz [Hz]), gamma (40 Hz), and sham transcranial alternating current stimulation (tACS) over the left prefrontal cortex (lPFC). During stimulation, participants completed a task assessing their risk-taking behavior as well as response times and sensitivity to value and outcome probabilities. Electroencephalography (EEG) was recorded before and immediately after stimulation to investigate possible long-lasting stimulation effects.ResultsTheta band, but not gamma band or sham, tACS led to a significant reduction in risk-taking behavior, indicating a frequency-specific effect of prefrontal brain stimulation on the modulation of risk-taking behavior. Moreover, theta band stimulation led to increased response times and decreased sensitivity to reward values. EEG data analyses did not show an offline increase in power in the stimulated frequencies after the stimulation protocol.ConclusionThese findings provide direct empirical evidence for the effects of prefrontal theta band stimulation on behavioral risk-taking regulation.

Background Recognition of facial expressions (FEs) plays a crucial role in social interactions. Most studies on FE recognition use static (image) stimuli, even though real-life FEs are dynamic. FE processing is complex and multifaceted, and its neural correlates remain unclear. Transitioning from static to dynamic FE stimuli might help disentangle the neural oscillatory mechanisms underlying face processing and recognition of emotion expression. To our knowledge, we here present the first time–frequency exploration of oscillatory brain mechanisms underlying the processing of dynamic FEs. Results Videos of joyful, fearful, and neutral dynamic facial expressions were presented to 18 included healthy young adults. We analyzed event-related activity in electroencephalography (EEG) data, focusing on the delta, theta, and alpha-band oscillations. Since the videos involved a transition from neutral to emotional expressions (onset around 500 ms), we identified time windows that might correspond to face perception initially (time window 1; first TW), and emotion expression recognition subsequently (around 1000 ms; second TW). First TW showed increased power and phase-locking values for all frequency bands. In the first TW, power and phase-locking values were higher in the delta and theta bands for emotional FEs as compared to neutral FEs, thus potentially serving as a marker for emotion recognition in dynamic face processing. Conclusions Our time–frequency exploration revealed consistent oscillatory responses to complex, dynamic, ecologically meaningful FE stimuli. We conclude that while dynamic FE processing involves complex network dynamics, dynamic FEs were successfully used to reveal temporally separate oscillation responses related to face processing and subsequently emotion expression recognition.

Prolactinomas have been reported for the failure of cognitive functions. However, the electrophysiological mechanisms of attention processing in prolactinomas remain unclear. In a visual mission, we monitored the scalp electroencephalography (EEG) of the participants. Compared with the healthy controls (HCs), larger frontoparietal theta and alpha coherence were found in the patients, especially in the right-lateralized hemisphere, which indicated a deficit in attention processing. Moreover, the frontoparietal coherence was positively correlated with altered prolactin (PRL) levels, implying the significance of PRL for adaptive brain compensation in prolactinomas. Taken together, this research showed the variations in attention processing between the HCs and prolactinomas. The coherence between frontal and parietal regions may be one of the possible electrophysiological biomarkers for detecting deficient attention processing in prolactinomas.

Although effective in major depressive disorder (MDD), repetitive transcranial magnetic stimulation (rTMS) is costly and complex, limiting accessibility. To address this, we tested the feasibility of novel rTMS techniques with cost-saving opportunities, such as an open-room setting, large non-focal parabolic coils, and custom-built coil arms. We employed a low-frequency (LF) 1 Hz stimulation protocol (360 pulses per session), delivered on the most affordable FDA-approved device. MDD participants received an initial accelerated rTMS course (arTMS) of 6 sessions/day over 5 days (30 total), followed by a tapering course of daily sessions (up to 25) to decrease the odds of relapse. The self-reported Beck Depression Inventory II (BDI-II) was used to measure severity of depression. Forty-eight (48) patients completed the arTMS course. No serious adverse events occurred, and all patients reported manageable pain levels. Response and remission rates were 35.4% and 27.1% on the BDI-II, respectively, at the end of the tapering course. Repeated measures ANOVA showed significant changes of BDI-II scores over time. Even though our protocol will require further improvements, some of the concepts we introduced here could help guide the design of future trials aiming at increasing accessibility to rTMS.

Repetitive Transcranial Magnetic Stimulation (rTMS) is an innovative, non-invasive and well tolerated method that could be usedas a treatment option for a variety of neuropsychiatric disorders. A large number of studies, for more than 30 years, have demonstrated that is a powerful neuroscience tool for diagnostic and therapeutic purposes. rTMS is based on the phenomenon of electromagnetic mutual induction, that firstly reported by Michael Faraday in 1831. Later, in 1985, Anthony Barker and his colleaguesdeveloped the first modern transcranial magnetic stimulation (TMS) device. rTMS uses brief electromagnetic pulses generatedby an insulated coil, placed over the scalp. This technique has the ability to modulate the cortical activity of the brain. DailyrTMS stimulation for several weeks has been shown to be effective in reducing symptoms of many neuropsychiatric disorders.Moreover, studies have shown that dorsolateral prefrontal cortex (DLPFC) has a crucial role in improving cognitive performanceand, as a result, is a commonly used target area for the treatment of many neuropsychiatric disorders such as depression. 2008was a significant year for TMS history, as FDA approved for first time a TMS therapy device for the clinical treatment of depression.This approval as well as the National Institute for Health and Care Excellence (NICE) recommendation on TMS for the treatmentof depression in 2015 lead to the establishment of rTMS as a first-line treatment for patients that failed in at least one prior antidepressant medication, followed by FDA approvals for the treatment of migraines and OCD. This paper aims to enhance further some of the clinical usefulness of rTMS.

OBJECTIVE: Our previous research showed high predictive accuracy at differentiating responders from non-responders to repetitive transcranial magnetic stimulation (rTMS) for depression using resting electroencephalography (EEG) and clinical data from baseline and one-week following treatment onset using a machine learning algorithm. In particular, theta (4-8 Hz) connectivity and alpha power (8-13 Hz) significantly differed between responders and non-responders. Independent replication is a necessary step before the application of potential predictors in clinical practice. This study attempted to replicate the results in an independent dataset.METHODS: We submitted baseline resting EEG data from an independent sample of participants who underwent rTMS treatment for depression (N = 193, 128 responders) (Krepel et al., 2018) to the same between group comparisons as our previous research (Bailey et al., 2019).RESULTS: Our previous results were not replicated, with no difference between responders and non-responders in theta connectivity (p = 0.250, Cohen's d = 0.1786) nor alpha power (p = 0.357, ηp2 = 0.005).CONCLUSIONS: These results suggest that baseline resting EEG theta connectivity or alpha power are unlikely to be generalisable predictors of response to rTMS treatment for depression.SIGNIFICANCE: These results highlight the importance of independent replication, data sharing and using large datasets in the prediction of response research.

Visual images contain redundant information across spatial scales where low spatial frequency contrast is informative towards the location and likely content of high spatial frequency detail. Previous research suggests that the visual system makes use of those redundancies to facilitate efficient processing. In this framework, a fast, initial analysis of low-spatial frequency (LSF) information guides the slower and later processing of high spatial frequency (HSF) detail. Here, we used multivariate classification as well as time-frequency analysis of MEG responses to the viewing of intact and phase scrambled images of human faces to demonstrate that the availability of redundant LSF information, as found in broadband intact images, correlates with a reduction in HSF representational dominance in both early and higher-level visual areas as well as a reduction of gamma-band power in early visual cortex. Our results indicate that the cross spatial frequency information redundancy that can be found in all natural images might be a driving factor in the efficient integration of fine image details.

Risk-taking behavior and intertemporal choices are common sources of inconsistences in decision-making. Although both phenomena have high economic and societal impacts, little is known about their underlying neurological processes. This knowledge is essential to understand its mechanisms and correlations. Since this remains an open question in economics and neuroscience, we explore such underlying mechanisms, aiming to clarify if these processes are correlated and how they are processed. Risk-taking behavior was chosen as our topic based on the positive correlation between a rich gut microbiota and risk-taking behavior with rodents (Chumney & Robinson, 2006). Considering the promising results presented by studies replicating such experiments with humans (Dinan et al., 2013), we believe we can prove the influence of the gut-brain axis on risk-taking behavior. Moreover, based on the possible common neural mechanisms underlying risk and time preferences (Bechara & Damasio, 2005), we also investigate the gut-brain influence on intertemporal choices. To explore such neurological processes we manipulate the gut microbiota, employing our most innovative contribution, which is the use of probiotics to investigate how the gut-brain axis is involved in decision-making. Our experiment uses a mixed design with two sessions (28 days gap), and different economic games to elicit risk-taking behavior and intertemporal choice. The preliminary results indicate that risk-taking and intertemporal choices are only correlated in specific scenarios. This correlation was present when participants faced risk-choices with low contrast between the options' expected values, and with intertemporal choices involving longer intervals. The probiotics intervention did not affect participants' stress response or intertemporal choices. However, a decrease in risk-taking behavior was observed after probiotics administration, which suggests an effect of the microbiota-gut-brain axis on decision-making under risk.

Several studies have established specific relationships between White Matter (WM) and behaviour. However, these studies have typically focussed on fractional anisotropy (FA), a neuroimaging metric that is sensitive to multiple tissue properties, making it difficult to identify what biological aspects of WM may drive such relationships. Here, we carry out a pre-registered assessment of WM-behaviour relationships in 50 healthy individuals across multiple behavioural and anatomical domains, and complementing FA with myelin-sensitive quantitative MR modalities (MT, R1, R2*).Surprisingly, we only find support for predicted relationships between FA and behaviour in one of three pre-registered tests. For one behavioural domain, where we failed to detect an FA-behaviour correlation, we instead find evidence for a correlation between behaviour and R1. This hints that multimodal approaches are able to identify a wider range of WM-behaviour relationships than focusing on FA alone.To test whether a common biological substrate such as myelin underlies WM-behaviour relationships, we then ran joint multimodal analyses, combining across all MRI parameters considered. No significant multimodal signatures were found and power analyses suggested that sample sizes of 40 to 200 may be required to detect such joint multimodal effects, depending on the task being considered.These results demonstrate that FA-behaviour relationships from the literature can be replicated, but may not be easily generalisable across domains. Instead, multimodal microstructural imaging may be best placed to detect a wider range of WM-behaviour relationships, as different MRI modalities provide distinct biological sensitivities. Our findings highlight a broad heterogeneity in WM’s relationship with behaviour, suggesting that variable biological effects may be shaping their interaction.HighlightsPre-registered testing of microstructural imaging across modalities (FA, MT, R1, R2*) to test WM-behaviour relationships.Partial support for FA-behaviour relationships hypothesised based on previous literature.Multimodal approaches can help detect WM-behaviour relationships that are not detected with FA alone.Sample sizes of 40 to 200 may be needed to detect myelin-behaviour relationships in joint multimodal analyses.Variable biological effects may be shaping WM-behaviour relationships.

The understanding and treatment of psychiatric disorders with neurobiological and clinical heterogeneity could benefit from the identification of disease subtypes on the basis of data acquired with established neuroimaging technologies. Here, we report the identification of two clinically relevant subtypes of post-traumatic stress disorder (PTSD) and major depressive disorder (MDD) on the basis of robust and distinct functional-connectivity patterns, prominently within the frontoparietal-control and default-mode networks. We identified the disease subtypes by analysing, via unsupervised and supervised machine learning, the power-envelope-based connectivity of signals reconstructed from high-density resting-state electroencephalography in four datasets from patients with PTSD and MDD, and show that the subtypes are transferable across independent datasets recorded under different conditions. The subtype whose functional connectivity differed most from those of healthy controls was less responsive to psychotherapy treatment for PTSD and failed to respond to an antidepressant medication for MDD. By contrast, both subtypes responded equally well to two different forms of repetitive transcranial magnetic stimulation therapy for MDD. Our data-driven approach may constitute a generalizable solution for connectome-based diagnosis., One-sentence editorial summary The analysis of functional-connectivity patterns in resting-state electroencephalography data via machine learning led to the identification of two clinically relevant subtypes of post-traumatic stress disorder and major depressive disorder.

This PhD research investigated the underlying mechanisms of transcranial magnetic stimulation (TMS). TMS is a form of non-invasive brain stimulation, which is used both in research to alter brain activity and in the clinic where it is a treatment option for many neuropsychiatric disorders such as major depression. However, not a lot is known about how TMS actually works. This research took an interdisciplinary approach to better understand the mechanisms of TMS. On the microscopic level, it used human neurons which were grown in the lab and stimulated with TMS to look for changes in plasticity such as neuronal firing, gene expression, and morphology. On the macroscopic level, the researcher stimulated human participants and measured indirect outcomes of plasticity, using multimodal setups such as combined TMS-EEG and TMS-EEG-fMRI. Better understanding the mechanisms of TMS is very important. If we fully understand how TMS works, we can optimize stimulation protocols, promoting increased responsiveness and better treatment outcomes in the clinic.