Resting-State fMRI Functional Connectivity Strength Predicts Local Activity Change in the Dorsal Cingulate Cortex: A Multi-Target Focused rTMS Study

Utilizing fMRI to Guide TMS Targets: the Reliability and Sensitivity of fMRI Metrics at 3 T and 1.5 T

US Food and Drug Administration (FDA) cleared a Transcranial Magnetic Stimulation (TMS) system with functional Magnetic Resonance Imaging-guided (fMRI) individualized treatment protocol for major depressive disorder, which employs resting state-fMRI (RS-fMRI) functional connectivity (FC) to pinpoint the target individually to increase the accuracy and effeteness of the stimulation. Furthermore, task activation-guided TMS, as well as the use of RS-fMRI local metrics for targeted the specific abnormal brain regions, are considered a precise scheme for TMS targeting. Since 1.5 T MRI is more available in hospitals, systematic evaluation of the test-retest reliability and sensitivity of fMRI metrics on 1.5 T and 3 T MRI may provide reference for the application of fMRI-guided individualized-precise TMS stimulation. Twenty participants underwent three RS-fMRI scans and one scan of finger-tapping task fMRI with self-initiated (SI) and visual-guided (VG) conditions at both 3 T and 1.5 T. Then the location reliability derived by FC (with three seed regions) and peak activation were assessed by intra-individual distance. The test-retest reliability and sensitivity of five RS-fMRI local metrics were evaluated using intra-class correlation and effect size, separately. The intra-individual distance of peak activation location between 1.5 T and 3 T was 15.8 mm and 19 mm for two conditions, respectively. The intra-individual distance for the FC derived targets at 1.5 T was 9.6-31.2 mm, compared to that of 3 T (7.6-31.1 mm). The test-retest reliability and sensitivity of RS-fMRI local metrics showed similar trends on 1.5 T and 3 T. These findings hasten the application of fMRI-guided individualized TMS treatment in clinical practice.

Abnormal individualized peak functional connectivity toward potential repetitive transcranial magnetic stimulation treatment of autism spectrum disorder

Functional connectivity (FC) derived from resting-state functional magnetic resonance imaging has been widely applied to guide precise repetitive transcranial magnetic stimulation (rTMS). The left, right, and bilateral dorsolateral prefrontal cortices (DLPFC) have been used as rTMS treatment target regions for autism spectrum disorder (ASD), albeit with moderate efficacy. Thus, we aimed to develop an individualized localization method for rTMS treatment of ASD. We included 266 male ASDs and 297 male typically-developed controls (TDCs) from the Autism Brain Imaging Data Exchange Dataset. The nucleus accumbens (NAc) was regarded as a promising effective region, which was used as a seed and individualized peak FC strength in the DLPFC was compared between ASD and TDC. Correlation analysis was conducted between individualized peak FC strength and symptoms in ASD. We also investigated the spatial distribution of individualized peak FC locations in the DLPFC and conducted voxel-wise analysis to compare NAc-based FC between the two groups. ASD showed stronger peak FC in the right DLPFC related to TDC (Cohen's d = -.19, 95% CI: -0.36 to -0.03, t = -2.30, p = .02). Moreover, negative correlation was found between the peak FC strength in the right DLPFC and Autism Diagnostic Observation Schedule (ADOS) scores, which assessed both the social communication and interaction (r = -.147, p = .04, uncorrected significant), and stereotyped behaviors and restricted interests (r = -.198, p = .02, corrected significant). Peak FC locations varied substantially across participants. No significant differences in NAc-based FC in the DLPFC were found in the voxel-wise comparison. Our study supports the use of individualized peak FC-guided precise rTMS treatment of male ASD. Moreover, stimulating the right DLPFC might alleviate core symptoms of ASD.

Neuroimaging profiles of the negative affective network predict anxiety severity in patients with chronic insomnia disorder: A machine learning study

BACKGROUND

Sleep is instrumental in safeguarding emotional well-being. While the susceptibility to both insomnia and anxiety has been demonstrated to involve intricate brain systems, the neuroimaging profile of chronic insomnia disorder with comorbid anxiety symptoms (CID-A) remains unexplored. Employing machine learning methodologies, this study aims to elucidate the distinct neural substrates underlying CID-A and to investigate whether these cerebral markers can prognosticate anxiety symptoms in patients with insomnia.

METHODS

Functional magnetic resonance imaging (fMRI) data were procured from a relatively large cohort (dataset 1) comprised of 47 CID-A patients, 49 CID patients without anxiety (CID-NA), and 48 good sleeper controls (GSC). Aberrant cerebral functional alterations were assessed through functional connectivity strength (FCS) and resting-state functional connectivity (rsFC). Subsequently, Support Vector Regression (SVR) models were constructed to predict anxiety symptoms in CID patients based on neuroimaging features, which were validated utilizing an external cohort (dataset 2).

RESULTS

In comparison to CID-NA and GSC subjects, CID-A patients exhibited heightened FCS in the right dorsomedial prefrontal cortex (DMPFC), a central hub within the negative affective network. Moreover, the SVR models revealed that DMPFC-related rsFC/FCS features could be employed to predict anxiety symptoms in two independent cohorts of CID patients.

LIMITATION

Modifications in brain functionality might vary across insomnia subtypes.

CONCLUSION

The present findings suggest a potential negative affective network model for the neuropathophysiology of CID accompanied by anxiety. Importantly, the negative affective network pattern may serve as a predictor for anxiety symptoms in CID patients.

Emotion regulation of social pain: double dissociation of lateral prefrontal cortices supporting reappraisal and distraction

The dorsolateral prefrontal cortex (DLPFC) and ventrolateral prefrontal cortex (VLPFC) are both crucial regions involved in voluntary emotion regulation. However, it remains unclear whether the two regions show functional specificity for reappraisal and distraction. This study employed transcranial magnetic stimulation (TMS) to explore, in a real social interactive scenario, whether different lateral prefrontal regions play relatively specific roles in downregulating social pain via reappraisal and distraction. Participants initially took part in a social interactive game, followed by receiving either active (the DLPFC- or VLPFC-activated group, n = 100 per group) or control (the vertex-activated group, n = 100) TMS session. They were then instructed to use both distraction and reappraisal strategies to downregulate any negative emotions evoked by the social evaluation given by their peers who interacted with them previously. Results demonstrated that the TMS-activated DLPFC has a greater beneficial effect during distraction, whereas the activated VLPFC has a greater beneficial effect during reappraisal. This result investigated the direct experience of social pain and extended previous findings on empathy-related responses to affective pictures while also controlling for confounding factors such as empathic concern. Therefore, we are now confident in the double dissociation proposal of the DLPFC and VLPFC in distraction and reappraisal.

Short-term effect of coil handle orientations on fMRI-guided rTMS on insomnia: A case report

Introduction

The coil handle orientation plays a pivotal role in the therapeutic efficacy of repetitive transcranial magnetic stimulation (rTMS). However, there is currently no consensus on the optimal individualized coil handle orientation, especially for non-motor areas.

Case presentation

The present case reported a short-term effect of functional connectivity (FC)-guided rTMS with coil handle posterior-anterior 45° (PA45°) and posterior-anterior 135° (PA135°) on a patient with insomnia. Notably, in this case, the PA45° orientation was nearly perpendicular to the adjacent sulcus, while the PA135° orientation was almost parallel to it. Local brain activity and functional connectivity were assessed using resting-state functional magnetic resonance imaging (RS-fMRI). Additionally, motor evoked potentials (MEPs) were captured both pre and post-rTMS sessions.

Findings

The coil handle orientation PA45° outperformed the PA135° in both RS-fMRI and MEP outcomes. Moreover, a 9-day rTMS treatment led to discernible improvements in symptoms of depression and anxiety, complemented by a modest enhancement in sleep quality.

Multisite rTMS combined with cognitive training modulates effective connectivity in patients with Alzheimer's disease

Purpose

To investigate the effective connectivity (EC) changes after multisite repetitive transcranial magnetic stimulation (rTMS) combined with cognitive training (COG).

Method

We selected 51 patients with mild or moderate Alzheimer's disease (AD) and delivered 10 Hz rTMS over the left dorsal lateral prefrontal cortex (DLPFC) and the lateral temporal lobe (LTL) combined with COG or sham stimulation for 4 weeks. The selected AD patients were divided into real (real rTMS+COG, n = 11) or sham (sham rTMS+COG, n = 8) groups to undergo neuropsychological assessment, resting-state fMRI, and 3D brain structural imaging before (T0), immediately at the end of treatment (T4), and 4 weeks after treatment (T8). A 2 × 3 factorial design with "time" as the within-subjects factor (three levels: T0, T4, and T8) and "group" as the between-subjects factor (two levels: real and sham) was used to investigate the EC changes related to the stimulation targets in the rest of the brain, as well as the causal interactions among seven resting-state networks based on Granger causality analysis (GCA).

Results

At the voxel level, the EC changes from the left DLPFC out to the left inferior parietal lobe and the left superior frontal gyrus, as well as from the left LTL out to the left orbital frontal cortex, had a significant group × time interaction effect. At the network level, a significant interaction effect was identified in the increase in EC from the limbic network out to the default mode network. The decrease in EC at the voxel level and the increase in EC at the network level were both associated with the improved ability to perform activities of daily living and cognitive function.

Conclusion

Multisite rTMS combined with cognitive training can modulate effective connectivity in patients with AD, resulting in improved ability to perform activities of daily living and cognitive function.

The role of ventrolateral prefrontal cortex on voluntary emotion regulation of social pain

The right ventrolateral prefrontal cortex (rVLPFC) is highly engaged in emotion regulation of social pain. However, there is still lack of both inhibition and excitement evidence to prove the causal relationship between this brain region and voluntary emotion regulation. This study used high-frequency (10 Hz) and low-frequency (1 Hz) repetitive transcranial magnetic stimulation (rTMS) to separately activate or inhibit the rVLPFC in two groups of participants. We recorded participants' emotion ratings as well as their social attitude and prosocial behaviors following emotion regulation. Also, we used eye tracker to record the changes of pupil diameter to measure emotional feelings objectively. A total of 108 healthy participants were randomly assigned to the activated, inhibitory or sham rTMS groups. They were required to accomplish three sequential tasks: the emotion regulation (cognitive reappraisal) task, the favorability rating task, and the donation task. Results show that the rVLPFC-inhibitory group reported more negative emotions and showed larger pupil diameter while the rVLPFC-activated group showed less negative emotions and reduced pupil diameter during emotion regulation (both compared with the sham rTMS group). In addition, the activated group gave more positive social evaluation to peers and donated more money to a public welfare activity than the rVLPFC-inhibitory group, among which the change of social attitude was mediated by regulated emotion. Taken together, these findings reveal that the rVLPFC plays a causal role in voluntary emotion regulation of social pain and can be a potential brain target in treating deficits of emotion regulation in psychiatric disorders.

Classify patients with Moyamoya disease according to their cognitive performance might be helpful in clinical and practical with support vector machine based on hypergraph

Moyamoya disease (MMD) patients were now classified according to their cerebrovascular manifestations, with cognition and emotion ignored, which attenuated the therapy. The present study tried to classify them based on their cognitive and emotional performance and explored the neural basis underlying this classification using resting-state fMRI (rs-fMRI). Thirty-nine MMD patients were recruited, assessed mental function and MRI scanned. We adopted hierarchical analysis of their mental performance for new subtypes. Next, a three-step analysis, with each step consisting of 10 random cross validation, was conducted for robust brain regions in classifying the three subtypes of patients in a support vector machine (SVM) model with hypergraph of rs-fMRI. We found three new subtypes including high depression-high anxiety-low cognition (HE-LC, 50%), low depression-low anxiety-high cognition (LE-HC, 14%), and low depression-low anxiety-low cognition (LE-LC, 36%), and no hemorrhagic MMD patients fell into the LE-HC group. The temporal and the bilateral superior frontal cortex, and so forth were included in all 10 randomized SVM modeling. The classification accuracy of the final three-way classification model was 67.5% in average of 10 random cross validation. In addition, the S value between the frontal cortex and the angular cortex was positively correlated with the anxiety score and backward digit span (p < .05). Our results might provide a new perspective for MMD classification concerning patients' mental status, guide timely surgery and suggest angular cortex, and so forth should be protected in surgery for cognitive consideration.

Higher reliability and validity of Wavelet-ALFF of resting-state fMRI: From multicenter database and application to rTMS modulation

Amplitude of low-frequency fluctuation (ALFF) has been widely used for localization of abnormal activity at the single-voxel level in resting-state fMRI (RS-fMRI) studies. However, previous ALFF studies were based on fast Fourier transform (FFT-ALFF). Our recent study found that ALFF based on wavelet transform (Wavelet-ALFF) showed better sensitivity and reproducibility than FFT-ALFF. The current study aimed to test the reliability and validity of Wavelet-ALFF, and apply Wavelet-ALFF to investigate the modulation effect of repetitive transcranial magnetic stimulation (rTMS). The reliability and validity were assessed on multicenter RS-fMRI datasets under eyes closed (EC) and eyes open (EO) conditions (248 healthy participants in total). We then detected the sensitivity of Wavelet-ALFF using a rTMS modulation dataset (24 healthy participants). For each dataset, Wavelet-ALFF based on five mother wavelets (i.e., db2, bior4.4, morl, meyr and sym3) and FFT-ALFF were calculated in the conventional band and five frequency sub-bands. The results showed that the reliability of both inter-scanner and intra-scanner was higher with Wavelet-ALFF than with FFT-ALFF across multiple frequency bands, especially db2-ALFF in the higher frequency band slow-2 (0.1992-0.25 Hz). In terms of validity, the multicenter ECEO datasets showed that the effect sizes of Wavelet-ALFF with all mother wavelets (especially for db2-ALFF) were larger than those of FFT-ALFF across multiple frequency bands. Furthermore, Wavelet-ALFF detected a larger modulation effect than FFT-ALFF. Collectively, Wavelet db2-ALFF showed the best reliability and validity, suggesting that db2-ALFF may offer a powerful metric for inspecting regional spontaneous brain activities in future studies.

Test-retest reliability of peak location in the sensorimotor network of resting state fMRI for potential rTMS targets

Most stroke repetitive transcranial magnetic stimulation (rTMS) studies have used hand motor hotspots as rTMS stimulation targets; in addition, recent studies demonstrated that functional magnetic resonance imaging (fMRI) task activation could be used to determine suitable targets due to its ability to reveal individualized precise and stronger functional connectivity with motor-related brain regions. However, rTMS is unlikely to elicit motor evoked potentials in the affected hemisphere, nor would activity be detected when stroke patients with severe hemiplegia perform an fMRI motor task using the affected limbs. The current study proposed that the peak voxel in the resting-state fMRI (RS-fMRI) motor network determined by independent component analysis (ICA) could be a potential stimulation target. Twenty-one healthy young subjects underwent RS-fMRI at three visits (V1 and V2 on a GE MR750 scanner and V3 on a Siemens Prisma) under eyes-open (EO) and eyes-closed (EC) conditions. Single-subject ICA with different total number of components (20, 30, and 40) were evaluated, and then the locations of peak voxels on the left and right sides of the sensorimotor network (SMN) were identified. While most ICA RS-fMRI studies have been carried out on the group level, that is, Group-ICA, the current study performed individual ICA because only the individual analysis could guide the individual target of rTMS. The intra- (test-retest) and inter-scanner reliabilities of the peak location were calculated. The use of 40 components resulted in the highest test-retest reliability of the peak location in both the left and right SMN compared with that determined when 20 and 30 components were used for both EC and EO conditions. ICA with 40 components might be another way to define a potential target in the SMN for poststroke rTMS treatment.