Time reproduction, bisection and doubling: a novel paradigm to investigate the effect of the internal clock on time estimation.

Time perception is not always veridical, but it can be modulated by changes in internal and external context. The most-acknowledged theory in this regard hypothesises the existence of an internal clock allowing us to subjectively estimate time intervals. The aim of the present study is to investigate the possible effect of such an internal clock, measured as the ability to reproduce a target duration, in the mental manipulation of time: 63 healthy participants were asked to Bisect and to Double reference time intervals, besides Reproducing them. Moreover, to investigate whether time processing might be predicted by individual differences, handedness, anxiety, and personality traits were also assessed by means of standardized questionnaires. Results show that participants correctly Reproduce time intervals (internal clock), but they overestimate time intervals during Bisection and underestimate them during Doubling. We explain this unexpected pattern of results as a kind of aftereffect, due to the short-term retention (adaptation) to the subjective representation of shorter (Bisection) vs longer (Doubling) intervals, respectively. Moreover, hierarchic regression models reveal that some personality traits can predict Bisection accuracy, but they clearly show that the best predictor for both Bisection and Doubling is the accuracy in Reproducing time intervals, confirming the fundamental role of the internal clock in time estimation. We conclude that time estimation is a unique skill, mostly independent from inter-individual differences, and the new paradigms introduced here (bisection vs doubling) reveal that the correct functioning of the internal clock also explains the ability to mentally manipulate the time.

Individualized perturbation of the human connectome reveals reproducible biomarkers of network dynamics relevant to cognition.

Large-scale brain networks are often described using resting-state functional magnetic resonance imaging (fMRI). However, the blood oxygenation level-dependent (BOLD) signal provides an indirect measure of neuronal firing and reflects slow-evolving hemodynamic activity that fails to capture the faster timescale of normal physiological function. Here we used fMRI-guided transcranial magnetic stimulation (TMS) and simultaneous electroencephalography (EEG) to characterize individual brain dynamics within discrete brain networks at high temporal resolution. TMS was used to induce controlled perturbations to individually defined nodes of the default mode network (DMN) and the dorsal attention network (DAN). Source-level EEG propagation patterns were network-specific and highly reproducible across sessions 1 month apart. Additionally, individual differences in high-order cognitive abilities were significantly correlated with the specificity of TMS propagation patterns across DAN and DMN, but not with resting-state EEG dynamics. Findings illustrate the potential of TMS-EEG perturbation-based biomarkers to characterize network-level individual brain dynamics at high temporal resolution, and potentially provide further insight on their behavioral significance.

Phase-dependent local brain states determine the impact of image-guided transcranial magnetic stimulation on motor network electroencephalographic synchronization.

Recent studies have synchronized transcranial magnetic stimulation (TMS) application with pre-defined brain oscillatory phases showing how brain response to perturbation depends on the brain state. However, none have investigated whether phase-dependent TMS can possibly modulate connectivity with homologous distant brain regions belonging to the same network. In the framework of network-targeted TMS, we investigated whether stimulation delivered at a specific phase of ongoing brain oscillations might favour stronger cortico-cortical (c-c) synchronization of distant network nodes connected to the stimulation target. Neuronavigated TMS pulses were delivered over the primary motor cortex (M1) during ongoing electroencephalography recording in 24 healthy individuals over two repeated sessions 1 month apart. Stimulation effects were analysed considering whether the TMS pulse was delivered at the time of a positive (peak) or negative (trough) phase of µ-frequency oscillation, which determines c-c synchrony within homologous areas of the sensorimotor network. Diffusion weighted imaging was used to study c-c connectivity within the sensorimotor network and identify contralateral regions connected with the stimulation spot. Depending on when during the µ-activity the TMS-pulse was applied (peak or trough), its impact on inter-hemispheric network synchrony varied significantly. Higher M1-M1 phase-lock synchronization after the TMS-pulse (0-200 ms) in the µ-frequency band was found for trough compared to peak stimulation trials in both study visits. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase the magnitude and reliability of the response to the external perturbation, with implications for interventions aimed at engaging more distributed functional brain networks. KEY POINTS: Synchronized transcranial magnetic stimulation (TMS) pulses with pre-defined brain oscillatory phases allow evaluation of the impact of brain states on TMS effects. TMS pulses over M1 at the negative peak of the µ-frequency band induce higher phase-lock synchronization with interconnected contralateral homologous regions. Cortico-cortical synchronization changes are linearly predicted by the fibre density and cross-section of the white matter tract that connects the two brain regions. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase the magnitude and reliability of within-network synchronization.

Effect of group-based vs individualized stimulation site selection on reliability of network-targeted TMS.

BACKGROUND: Transcranial magnetic stimulation (TMS) is a widely used technique for the noninvasive assessment and manipulation of brain activity and behavior. Although extensively used for research and clinical purposes, recent studies have questioned the reliability of TMS findings because of the high inter-individual variability that has been observed. OBJECTIVE: In this study, we compared the efficacy and reliability of different targeting scenarios on the TMS-evoked response. METHODS: 24 subjects underwent a single pulse stimulation protocol over two parietal nodes belonging to the Dorsal Attention (DAN) and Default Mode (DMN) Networks respectively. Across visits, the stimulated target for both networks was chosen either based on group-derived networks' maps or personalized network topography based on individual anatomy and functional profile. All stimulation visits were conducted twice, one month apart, during concomitant electroencephalography recording. RESULTS: At the network level, we did not observe significant differences in the TMS-evoked response between targeting conditions. However, reliable patterns of activity were observed- for both networks tested- following the individualized targeting approach. When the same analyses were carried out at the electrode space level, evidence of reliable patterns was observed following the individualized stimulation of the DAN, but not of the DMN. CONCLUSIONS: Our findings suggest that individualization of stimulation sites might ensure reliability of the evoked TMS-response across visits. Furthermore, individualized stimulation sites appear to be of foremost importance in highly variable, high order task-positive networks, such as the DAN.

"When did you see it?" The effect of emotional valence on temporal source memory in aging.

Previous studies consistently showed age-related differences in temporal judgment and temporal memory. Importantly, emotional valence plays a crucial role in older adults' information processing. In this study, we examined the effects of emotions at the intersection between time and memory, analysing age-related differences in a temporal source memory task. Twenty-five younger adults (age range 18-35), 25 old adults (age range 65-74), and 25 old-old adults (age range 75-84) saw a series of emotional pictures in three sessions separated by a one-day rest period. In the fourth session, participants were asked to indicate in which session (1, 2, or 3) they saw each picture. Results showed that old-old adults tended to collocate negative pictures distant in time, while positive stimuli were remembered as more recent than real, compared to neutral pictures. To a lower extent, people over 65 showed the same pattern of results. In contrast, emotional valence did not affect younger adults' temporal positioning of stimuli. Current findings fit well with the Socio-Emotional Selectivity Theory's assumptions and extended the literature on the positivity effect to temporal source memory.

Network-level macroscale structural connectivity predicts propagation of transcranial magnetic stimulation.

Information processing in the brain is mediated by structural white matter pathways and is highly dependent on topological brain properties. Here we combined transcranial magnetic stimulation (TMS) with high-density electroencephalography (EEG) and Diffusion Weighted Imaging (DWI), specifically looking at macroscale connectivity to understand whether regional, network-level or whole-brain structural properties are more responsible for stimulus propagation. Neuronavigated TMS pulses were delivered over two individually defined nodes of the default mode (DMN) and dorsal attention (DAN) networks in a group of healthy subjects, with test-retest reliability assessed 1-month apart. TMS-evoked activity was predicted by the modularity and structural integrity of the stimulated network rather than the targeted region(s) or the whole-brain connectivity, suggesting network-level structural connectivity as more relevant than local and global brain properties in shaping TMS signal propagation. The importance of network structural connectome was unveiled only by evoked activity, but not resting-state data. Future clinicals interventions might enhance target engagement by adopting DWI-guided, network-focused TMS.

Overlapping and dissociable brain activations for fluid intelligence and executive functions.

Cognitive enhancement interventions aimed at boosting human fluid intelligence (gf) have targeted executive functions (EFs), such as updating, inhibition, and switching, in the context of transfer-inducing cognitive training. However, even though the link between EFs and gf has been demonstrated at the psychometric level, their neurofunctional overlap has not been quantitatively investigated. Identifying whether and how EFs and gf might share neural activation patterns could provide important insights into the overall hierarchical organization of human higher-order cognition, as well as suggest specific targets for interventions aimed at maximizing cognitive transfer. We present the results of a quantitative meta-analysis of the available fMRI and PET literature on EFs and gf in humans, showing the similarity between gf and (i) the overall global EF network, as well as (ii) specific maps for updating, switching, and inhibition. Results highlight a higher degree of similarity between gf and updating (80% overlap) compared with gf and inhibition (34%), and gf and switching (17%). Moreover, three brain regions activated for both gf and each of the three EFs also were identified, located in the left middle frontal gyrus, left inferior parietal lobule, and anterior cingulate cortex. Finally, resting-state functional connectivity analysis on two independent fMRI datasets showed the preferential behavioural correlation and anatomical overlap between updating and gf. These findings confirm a close link between gf and EFs, with implications for brain stimulation and cognitive training interventions.

Impact of network-targeted multichannel transcranial direct current stimulation on intrinsic and network-to-network functional connectivity.

Dynamics within and between functional resting-state networks have a crucial role in determining both healthy and pathological brain functioning in humans. The possibility to noninvasively interact and selectively modulate the activity of networks would open to relevant applications in neuroscience. Here we tested a novel approach for multichannel, network-targeted transcranial direct current stimulation (net-tDCS), optimized to increase excitability of the sensorimotor network (SMN) while inducing cathodal inhibitory modulation over prefrontal and parietal brain regions negatively correlated with the SMN. Using an MRI-compatible multichannel transcranial electrical stimulation (tES) device, 20 healthy participants underwent real and sham tDCS while at rest in the MRI scanner. Changes in functional connectivity (FC) during and after stimulation were evaluated, looking at the intrinsic FC of the SMN and the strength of the negative connectivity between SMN and the rest of the brain. Standard, bifocal tDCS targeting left motor cortex (electrode ~C3) and right frontopolar (~Fp2) regions was tested as a control condition in a separate sample of healthy subjects to investigate network specificity of multichannel stimulation effects. Net-tDCS induced greater FC increase over the SMN compared to bifocal tDCS, during and after stimulation. Moreover, exploratory analysis of the impact of net-tDCS on negatively correlated networks showed an increase in the negative connectivity between SMN and prefrontal/parietal areas targeted by cathodal stimulation both during and after real net-tDCS. Results suggest preliminary evidence of the possibility of manipulating distributed network connectivity patterns through net-tDCS, with potential relevance for the development of cognitive enhancement and therapeutic tES solutions.

Thalamic morphometric changes induced by first-person action videogame training.

Cross-sectional data suggest videogaming as promoting modifications in perceptual and cognitive skills of players, as well as inducing structural brain changes. However, whether such changes are both possible after a systematic gaming exposure, and last beyond the training period, is not known. Here, we originally quantified immediate and long-lasting cognitive and morphometric impact of a systematic gaming experience on a first-person shooter (FPS) game. Thirty-five healthy participants, assigned to a videogaming and a control group, underwent a cognitive assessment and structural magnetic resonance imaging at baseline (T0), immediately post-gaming (T1) and after  3 months (T2). Enhancements of cognitive performance were found on perceptual and attentional measures at both T1 and T2. Morphometric analysis revealed immediate structural changes involving bilateral medial and posterior thalamic nuclei, as well as bilateral superior temporal gyrus, right precentral gyrus, and left middle occipital gyrus. Notably, significant changes in pulvinar volume were still present at T2, while a voxel-wise regression analysis also linked baseline pulvinar volume and individual changes in gaming performance. Present findings extend over the notion that videogame playing might impact cognitive and brain functioning in a beneficial way, originally showing long-term brain structural changes even months after gaming practice. The involvement of posterior thalamic structures highlights a potential link between FPS games and thalamo-cortical networks related to attention mechanisms and multisensory integration processing.

Stimuli, presentation modality, and load-specific brain activity patterns during n-back task.

Working memory (WM) refers to a set of cognitive processes that allows for the temporary storage and manipulation of information, crucial for everyday life skills. WM deficits are present in several neurological, psychiatric, and neurodevelopmental disorders, thus making the full understanding of its neural correlates a key aspect for the implementation of cognitive training interventions. Here, we present a quantitative meta-analysis focusing on the underlying neural substrates upon which the n-back, one of the most commonly used tasks for WM assessment, is believed to rely on, as highlighted by functional magnetic resonance imaging and positron emission tomography findings. Relevant published work was scrutinized through the activation likelihood estimate (ALE) statistical framework in order to generate a set of task-specific activation maps, according to n-back difficulty. Our results confirm the known involvement of frontoparietal areas across different types of n-back tasks, as well as the recruitment of subcortical structures, cerebellum and precuneus. Specific activations maps for four stimuli types, six presentation modalities, three WM loads and their combination are provided and discussed. Moreover, functional overlap with resting-state networks highlighted a strong similarity between n-back nodes and the Dorsal Attention Network, with less overlap with other networks like Salience, Language, and Sensorimotor ones. Additionally, neural deactivations during n-back tasks and their functional connectivity profile were examined. Clinical and functional implications are discussed in the context of potential noninvasive brain stimulation and cognitive enhancement/rehabilitation programs.

Modulation of network-to-network connectivity via spike-timing-dependent noninvasive brain stimulation.

Human cognitive abilities and behavior are linked to functional coupling of many brain regions organized in distinct networks. Gaining insights on the role those networks' dynamics play in cognition and pathology requires their selective, reliable, and reversible manipulation. Here we document the possibility to manipulate the interplay between two brain networks in a controlled manner, by means of a Transcranial Magnetic Stimulation (TMS) protocol inducing spike timing dependent plasticity (STDP). Pairs of TMS pulses at specific inter-stimulus intervals, repeatedly delivered over two negatively correlated nodes of the default mode network (DMN) and the task-positive network (TPN) defined on the basis of individual functional magnetic resonance imaging (fMRI) data, induced a modulation of network-to-network connectivity, even reversing correlation from negative to slightly positive in 30% of cases. Results also suggest a baseline-dependent effect, with a greater connectivity modulation observed in participants with weaker between-networks connectivity strength right before TMS. Finally, modulation of task-evoked fMRI activity patterns during a sustained attention task was also observed after stimulation, with a faster or slower switch between rest and task blocks according to the timing of TMS pulses. The present findings promote paired associative TMS as a promising technique for controlled manipulation of fMRI connectivity dynamics in humans, as well as the causal investigation of brain-behavior relations.

Brain functional connectivity correlates of coping styles.

Coping abilities represent the individual set of mental and behavioral strategies adopted when facing stress or traumatic experiences. Coping styles related to avoidance have been linked to a disposition to develop psychiatric disorders such as PTSD, anxiety, and major depression, whereas problem-oriented coping skills have been positively correlated with well-being and high quality of life. Even though coping styles constitute an important determinant of resilience and can impact many aspects of everyday living, no study has investigated their brain functional connectivity underpinnings in humans. Here we analyzed both psychometric scores of coping and resting-state fMRI data from 102 healthy adult participants. Controlling for personality and problem-solving abilities, we identified significant links between the propensity to adopt different coping styles and the functional connectivity profiles of regions belonging to the default mode (DMN) and anterior salience (AS) networks-namely, the anterior cingulate cortex, left frontopolar cortex, and left angular gyrus. Also, a reduced negative correlation between AS and DMN nodes explained variability in one specific coping style, related to avoiding problems while focusing on the emotional component of the stressor at hand, instead of relying on cognitive resources. These results might be integrated with current neurophysiological models of resilience and individual responses to stress, in order to understand the propensity to develop clinical conditions (e.g., PTSD) and predict the outcomes of psychotherapeutic interventions.

Age of Insomnia Onset Correlates with a Reversal of Default Mode Network and Supplementary Motor Cortex Connectivity.

Insomnia might occur as result of increased cognitive and physiological arousal caused by acute or long acting stressors and associated cognitive rumination. This might lead to alterations in brain connectivity patterns as those captured by functional connectivity fMRI analysis, leading to potential insight about primary insomnia (PI) pathophysiology as well as the impact of long-term exposure to sleep deprivation. We investigated changes of voxel-wise connectivity patterns in a sample of 17 drug-naïve PI patients and 17 age-gender matched healthy controls, as well as the relationship between brain connectivity and age of onset, illness duration, and severity. Results showed a significant increase in resting-state functional connectivity of the bilateral visual cortex in PI patients, associated with decreased connectivity between the visual cortex and bilateral temporal pole. Regression with clinical scores originally unveiled a pattern of increased local connectivity as measured by intrinsic connectivity contrast (ICC), specifically resembling the default mode network (DMN). Additionally, age of onset was found to be correlated with the connectivity of supplementary motor area (SMA), and the strength of DMN←→SMA connectivity was significantly correlated with both age of onset (R2 = 41%) and disease duration (R2 = 21%). Chronic sleep deprivation, but most importantly early insomnia onset, seems to have a significant disruptive effect over the physiological negative correlation between DMN and SMA, a well-known fMRI marker of attention performance in humans. This suggests the need for more in-depth investigations on the prevention and treatment of connectivity changes and associated cognitive and psychological deficits in PI patients.

Computational modeling of whole-brain dynamics: a review of neurosurgical applications.

A major goal of modern neurosurgery is the personalization of treatment to optimize or predict individual outcomes. One strategy in this regard has been to create whole-brain models of individual patients. Whole-brain modeling is a subfield of computational neuroscience that focuses on simulations of large-scale neural activity patterns across distributed brain networks. Recent advances allow for the personalization of these models by incorporating distinct connectivity architecture obtained from noninvasive neuroimaging of individual patients. Local dynamics of each brain region are simulated with neural mass models and subsequently coupled together, considering the subject's empirical structural connectome. The parameters of the model can be optimized by comparing model-generated and empirical data. The resulting personalized whole-brain models have translational potential in neurosurgery, allowing investigators to simulate the effects of virtual therapies (such as resections or brain stimulations), assess the effect of brain pathology on network dynamics, or discern epileptic networks and predict seizure propagation in silico. The information gained from these simulations can be used as clinical decision support, guiding patient-specific treatment plans. Here the authors provide an overview of the rapidly advancing field of whole-brain modeling and review the literature on neurosurgical applications of this technology.

N100 as a response prediction biomarker for accelerated 1 Hz right DLPFC-rTMS in major depression.

BACKGROUND AND OBJECTIVE: Repetitive transcranial magnetic stimulation (rTMS) is a safe and effective treatment for major depressive disorder (MDD); however, this treatment currently lacks reliable biomarkers of treatment response. TMS-evoked potentials (TEPs), measured using TMS-electroencephalography (TMS-EEG), have been suggested as potential biomarker candidates, with the N100 peak being one of the most promising. This study investigated the association between baseline N100 amplitude and 1 Hz right dorsolateral prefrontal cortex (R-DLPFC) accelerated rTMS (arTMS) treatment in MDD. METHODS: Baseline TMS-EEG sessions were performed for 23 MDD patients. All patients then underwent 40 sessions of 1 Hz R-DLPFC (F4) arTMS over 5 days and a follow-up TMS-EEG session one week after the end of theses arTMS sessions. RESULTS: Baseline N100 amplitude at F4 showed a strong positive association (p < .001) with treatment outcome. The association between the change in N100 amplitude (baseline to follow-up) and treatment outcome did not remain significant after Bonferroni correction (p = .06, corrected; p = .03, uncorrected). Furthermore, treatment responders had a significantly larger mean baseline F4 TEP amplitude during the N100 time frame compared to non-responders (p < .001). Topographically, after Bonferroni correction, F4 is the only electrode at which its baseline N100 amplitude showed a significant positive association (p < .001) with treatment outcome. LIMITATIONS: Lack of control group and auditory masking. CONCLUSION: Baseline N100 amplitude showed a strong association with treatment outcome and thus demonstrated great potential to be utilized as a cost-effective and widely adoptable biomarker of rTMS treatment in MDD.

TMS-evoked responses are driven by recurrent large-scale network dynamics.

A compelling way to disentangle the complexity of the brain is to measure the effects of spatially and temporally synchronized systematic perturbations. In humans, this can be non-invasively achieved by combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG). Spatiotemporally complex and long-lasting TMS-EEG evoked potential (TEP) waveforms are believed to result from recurrent, re-entrant activity that propagates broadly across multiple cortical and subcortical regions, dispersing from and later re-converging on, the primary stimulation site. However, if we loosely understand the TEP of a TMS-stimulated region as the impulse response function of a noisy underdamped harmonic oscillator, then multiple later activity components (waveform peaks) should be expected even for an isolated network node in the complete absence of recurrent inputs. Thus emerges a critically important question for basic and clinical research on human brain dynamics: what parts of the TEP are due to purely local dynamics, what parts are due to reverberant, re-entrant network activity, and how can we distinguish between the two? To disentangle this, we used source-localized TMS-EEG analyses and whole-brain connectome-based computational modelling. Results indicated that recurrent network feedback begins to drive TEP responses from 100 ms post-stimulation, with earlier TEP components being attributable to local reverberatory activity within the stimulated region. Subject-specific estimation of neurophysiological parameters additionally indicated an important role for inhibitory GABAergic neural populations in scaling cortical excitability levels, as reflected in TEP waveform characteristics. The novel discoveries and new software technologies introduced here should be of broad utility in basic and clinical neuroscience research.

Identifying Neurophysiological Markers of Intermittent Theta Burst Stimulation in Treatment-Resistant Depression Using Transcranial Magnetic Stimulation-Electroencephalography.

BACKGROUND: Intermittent theta burst stimulation (iTBS) targeting the left dorsolateral prefrontal cortex is effective for treatment-resistant depression, but the effects of iTBS on neurophysiological markers remain unclear. Here, we indexed transcranial magnetic stimulation-electroencephalography (TMS-EEG) markers, specifically, the N45 and N100 amplitudes, at baseline and post-iTBS, comparing separated and contiguous iTBS schedules. TMS-EEG markers were also compared between iTBS responders and nonresponders. METHODS: TMS-EEG was analyzed from a triple-blind 1:1 randomized trial for treatment-resistant depression, comparing a separated (54-minute interval) and contiguous (0-minute interval) schedule of 2 × 600-pulse iTBS for 30 treatments. Participants underwent TMS-EEG over the left dorsolateral prefrontal cortex at baseline and posttreatment. One hundred fourteen participants had usable TMS-EEG at baseline, and 98 at posttreatment. TMS-evoked potential components (N45, N100) were examined via global mean field analysis. RESULTS: The N100 amplitude decreased from baseline to posttreatment, regardless of the treatment group (F1,106 = 5.20, p = .02). There were no changes in N45 amplitude in either treatment group. In responders, the N100 amplitude decreased after iTBS (F1,102 = 11.30, p = .001, pcorrected = .0004). Responders showed higher posttreatment N45 amplitude than nonresponders (F1,94 = 4.11, p = .045, pcorrected = .016). Higher baseline N100 amplitude predicted lower post-iTBS depression scores (F4,106 = 6.28, p = .00014). CONCLUSIONS: These results provide further evidence for an association between the neurophysiological effects of iTBS and treatment efficacy in treatment-resistant depression. Future studies are needed to test the predictive potential for clinical applications of TMS-EEG markers.

Reliability of resting-state EEG modulation by continuous and intermittent theta burst stimulation of the primary motor cortex: a sham-controlled study.

Theta burst stimulation (TBS) is a form of repetitive transcranial magnetic stimulation designed to induce changes of cortical excitability that outlast the period of TBS application. In this study, we explored the effects of continuous TBS (cTBS) and intermittent TBS (iTBS) versus sham TBS stimulation, applied to the left primary motor cortex, on modulation of resting state electroencephalography (rsEEG) power. We first conducted hypothesis-driven region-of-interest (ROI) analyses examining changes in alpha (8-12 Hz) and beta (13-21 Hz) bands over the left and right motor cortex. Additionally, we performed data-driven whole-brain analyses across a wide range of frequencies (1-50 Hz) and all electrodes. Finally, we assessed the reliability of TBS effects across two sessions approximately 1 month apart. None of the protocols produced significant group-level effects in the ROI. Whole-brain analysis revealed that cTBS significantly enhanced relative power between 19 and 43 Hz over multiple sites in both hemispheres. However, these results were not reliable across visits. There were no significant differences between EEG modulation by active and sham TBS protocols. Between-visit reliability of TBS-induced neuromodulatory effects was generally low-to-moderate. We discuss confounding factors and potential approaches for improving the reliability of TBS-induced rsEEG modulation.

Reliability of resting-state EEG modulation by continuous and intermittent theta burst stimulation of the primary motor cortex: A sham-controlled study.

Theta burst stimulation (TBS) is a form of repetitive transcranial magnetic stimulation designed to induce changes of cortical excitability that outlast the period of TBS application. In this study, we explored the effects of continuous TBS (cTBS) and intermittent TBS (iTBS) versus sham TBS stimulation, applied to the primary motor cortex, on modulation of resting state electroencephalography (rsEEG) power. We first conducted hypothesis-driven region-of-interest (ROI) analyses examining changes in alpha (8-12 Hz) and beta (13-21 Hz) bands over the left and right motor cortex. Additionally, we performed data-driven whole-brain analyses across a wide range of frequencies (1-50 Hz) and all electrodes. Finally, we assessed the reliability of TBS effects across two sessions approximately 1 month apart. None of the protocols produced significant group-level effects in the ROI. Whole-brain analysis revealed that cTBS significantly enhanced relative power between 19-43 Hz over multiple sites in both hemispheres. However, these results were not reliable across visits. There were no significant differences between EEG modulation by active and sham TBS protocols. Between-visit reliability of TBS-induced neuromodulatory effects was generally low-to-moderate. We discuss confounding factors and potential approaches for improving the reliability of TBS-induced rsEEG modulation.

Mapping Inter-individual Functional Connectivity Variability in TMS Targets for Major Depressive Disorder.

Transcranial magnetic stimulation (TMS) is an emerging alternative to existing treatments for major depressive disorder (MDD). The effects of TMS on both brain physiology and therapeutic outcomes are known to be highly variable from subject to subject, however. Proposed reasons for this variability include individual differences in neurophysiology, in cortical geometry, and in brain connectivity. Standard approaches to TMS target site definition tend to focus on coordinates or landmarks within the individual brain regions implicated in MDD, such as the dorsolateral prefrontal cortex (dlPFC) and orbitofrontal cortex (OFC). Additionally considering the network connectivity of these sites (i.e., the wider set of brain regions that may be mono- or poly-synaptically activated by TMS stimulation) has the potential to improve subject-specificity of TMS targeting and, in turn, improve treatment outcomes. In this study, we looked at the functional connectivity (FC) of dlPFC and OFC TMS targets, based on induced electrical field (E-field) maps, estimated using the SimNIBS library. We hypothesized that individual differences in spontaneous functional brain dynamics would contribute more to downstream network engagement than individual differences in cortical geometry (i.e., E-field variability). We generated individualized E-field maps on the cortical surface for 121 subjects (67 female) from the Human Connectome Project database using tetrahedral head models generated from T1- and T2-weighted MR images. F3 and Fp1 electrode positions were used to target the left dlPFC and left OFC, respectively. We analyzed inter-subject variability in the shape and location of these TMS target E-field patterns, their FC, and the major functional networks to which they belong. Our results revealed the key differences in TMS target FC between the dlPFC and OFC, and also how this connectivity varies across subjects. Three major functional networks were targeted across the dlPFC and OFC: the ventral attention, fronto-parietal and default-mode networks in the dlPFC, and the fronto-parietal and default mode networks in the OFC. Inter-subject variability in cortical geometry and in FC was high. Our analyses showed that the use of normative neuroimaging reference data (group-average or representative FC and subject E-field) allows prediction of which networks are targeted, but fails to accurately quantify the relative loading of TMS targeting on each of the principal networks. Our results characterize the FC patterns of canonical therapeutic TMS targets, and the key dimensions of their variability across subjects. The high inter-individual variability in cortical geometry and FC, leading to high variability in distributions of targeted brain networks, may account for the high levels of variability in physiological and therapeutic TMS outcomes. These insights should, we hope, prove useful as part of the broader effort by the psychiatry, neurology, and neuroimaging communities to help improve and refine TMS therapy, through a better understanding of the technology and its neurophysiological effects.