Low-frequency parietal repetitive transcranial magnetic stimulation reduces fear and anxiety

Threat of shock increases distractor susceptibility during the short-term maintenance of visual information

Elevated arousal in anxiety is thought to affect attention control. To test this, we designed a visual short-term memory (VSTM) task to examine distractor suppression during periods of threat and no-threat. We hypothesized that threat would impair performance when subjects had to filter out large numbers of distractors. The VSTM task required subjects to attend to one array of squares while ignoring a separate array. The number of target and distractor squares varied systematically, with high (four squares) and low (two squares) target and distractor conditions. This study comprised two separate experiments. Experiment 1 used startle responses and white noise as to directly measure threat-induced anxiety. Experiment 2 used BOLD to measure brain responses. For Experiment 1, subjects showed significantly larger startle responses during threat compared to safe period, supporting the validity of the threat manipulation. For Experiment 2, we found that accuracy was affected by threat, such that the distractor load negatively impacted accuracy only in the threat condition. We also found threat-related differences in parietal cortex activity. Overall, these findings suggest that threat affects distractor susceptibility, impairing filtering of distracting information. This effect is possibly mediated by hyperarousal of parietal cortex during threat.

Effects of repetitive transcranial magnetic stimulation on fear of cancer recurrence and its underlying neuromechanism

Introduction

Many breast cancer patients suffer from fear of cancer recurrence (FCR). However, effective physical intervention for FCR has been scarce. Previous studies have confirmed that repetitive transcranial magnetic stimulation (rTMS) can help improve patients' anxiety, depression, fear, and stress level. Therefore, this study aims to assess the efficacy of rTMS in the treatment of FCR in breast cancer patients and explore its underlying neural mechanism.

Methods and analysis

and analysis: Fifty breast cancer patients with high FCR (FCR total score >27), and fifty age- and gender-matched patients with low FCR (FCR total score <7) will be recruited to participate in this study. Patients in the high FCR group will be randomly assigned to receive 4-week low-frequency rTMS targeting the right dorsolateral prefrontal cortex (rDLPFC) + treatment as usual (TAU) (n = 25), or to receive sham stimulation + TAU (n = 25). Patients in the low FCR group will only receive TAU. All participants will take a baseline fMRI scan to examine the local activities and interactions of brain activity between the prefrontal cortex (DLPFC), amygdala and hippocampus. Fear of Cancer Recurrence Questionnaire (FCRQ7), Patient Health Questionnaire (PHQ9), Generalize Anxiety Disorder (GAD7), Numeric Rating Scale (NRS), and Insomnia Severity Index (ISI7) will be used to measure an individual's FCR, depression, anxiety, pain, and insomnia symptoms at week 0 (baseline), week 4 (the end of intervention), week 5 (1 week post-treatment), week 8 (1 month post-treatment), and week 16 (3 months post-treatment). Participants in the high FCR group will receive a post-treatment fMRI scan within 24 h after intervention to explore the neural mechanisms of rTMS treatment. The primary outcome of the study, whether the rTMS intervention is sufficient in relieving FCR in breast cancer patients, is measured by FCRQ7. Additionally, task activation, local activity and functional connectivity of the DLPFC, amygdala and hippocampus will be compared, between high and low FCR group, and before and after treatment.

Discussion

Studies have shown that low-frequency rTMS can be used to treat patient's FCR. However, there is a lack of relevant evidence to support the efficacy of rTMS on FCR in cancer patients, and the neural mechanisms underlying the effects of rTMS on FCR need to be further investigated.

Ethics and dissemination

Ethical approval for the study has been obtained from the Ethics Committee of Guangdong Provincial People's Hospital (reference number: KY-N-2022-136-01). The results of the investigation will be published in scientific papers. The data from the investigation will be made available online if necessary.

Trial registration

NCT05881889 (ClinicalTrials.gov). Date of registration: May 31, 2023.

Individualized prediction of anxiety and depressive symptoms using gray matter volume in a non-clinical population

Machine learning is an emerging tool in clinical psychology and neuroscience for the individualized prediction of psychiatric symptoms. However, its application in non-clinical populations is still in its infancy. Given the widespread morphological changes observed in psychiatric disorders, our study applies five supervised machine learning regression algorithms-ridge regression, support vector regression, partial least squares regression, least absolute shrinkage and selection operator regression, and Elastic-Net regression-to predict anxiety and depressive symptom scores. We base these predictions on the whole-brain gray matter volume in a large non-clinical sample (n = 425). Our results demonstrate that machine learning algorithms can effectively predict individual variability in anxiety and depressive symptoms, as measured by the Mood and Anxiety Symptoms Questionnaire. The most discriminative features contributing to the prediction models were primarily located in the prefrontal-parietal, temporal, visual, and sub-cortical regions (e.g. amygdala, hippocampus, and putamen). These regions showed distinct patterns for anxious arousal and high positive affect in three of the five models (partial least squares regression, support vector regression, and ridge regression). Importantly, these predictions were consistent across genders and robust to demographic variability (e.g. age, parental education, etc.). Our findings offer critical insights into the distinct brain morphological patterns underlying specific components of anxiety and depressive symptoms, supporting the existing tripartite theory from a neuroimaging perspective.

Threat of shock increases distractor susceptibility during the short-term maintenance of visual information

BACKGROUND

Work on anxiety related attention control deficits suggests that elevated arousal impacts the ability to filter out distractors. To test this, we designed a task to look at distractor suppression during periods of threat. We administered trials of a visual short-term memory (VSTM) task, during periods of unpredictable threat, and hypothesized that threat would impair performance during trials where subjects were required to filter out large numbers of distractors.

METHOD

Experiment 1 involved fifteen healthy participants who completed one study visit. They performed four runs of a VSTM task comprising 32 trials each. Participants were presented with an arrow indicating left or right, followed by an array of squares. They were instructed to remember the target side and disregard the distractors on the off-target side. A subsequent target square was shown, and participants indicated whether it matched one of the previously presented target squares. The trial conditions included 50% matches and 50% mismatches, with an equal distribution of left and right targets. The number of target and distractor squares varied systematically, with high (4 squares) and low (2 squares) target and distractor conditions. Trials alternated between periods of safety and threat, with startle responses recorded using electromyography (EMG) following white noise presentations. Experiment 2 involved twenty-seven healthy participants who completed the same VSTM task inside an MRI scanner during a single study visit. The procedure mirrored that of Experiment 1, except for the absence of white noise presentations.

RESULTS

For Experiment 1, subjects showed significantly larger startle responses during threat compared to safe period, supporting the validity of the threat manipulation. However, results suggested that the white noise probes interfered with performance. For Experiment 2, we found that both accuracy was affected by threat, such that distractor load negatively impacted accuracy only in the threat condition.

CONCLUSION

Overall, these findings suggest that threat affects distractor susceptibility during the short-term maintenance of visual information. The presence of threat makes it more difficult to filter out distracting information. We believe that this is related to hyperarousal of parietal cortex, which has been observed during unpredictable threat.

Interleaved TMS/fMRI shows that threat decreases dlPFC-mediated top-down regulation of emotion processing

Background

The right dorsolateral prefrontal cortex (dlPFC) has been indicated to be a key region in the cognitive regulation of emotion by many previous neuromodulation and neuroimaging studies. However, there is little direct causal evidence supporting this top-down regulation hypothesis. Furthermore, it is unclear whether contextual threat impacts this top-down regulation. By combining TMS/fMRI, this study aimed to uncover the impact of unpredictable threat on TMS-evoked BOLD response in dlPFC-regulated emotional networks. Based on the previous findings linking the dlPFC to the downregulation of emotional network activity, we hypothesized TMS pulses would deactivate activity in anxiety expression regions, and that threat would reduce this top-down regulation.

Methods

44 healthy controls (no current or history of psychiatric disorders) were recruited to take part in a broader study. Subjects completed the neutral, predictable, and unpredictable (NPU) threat task while receiving TMS pulses to either the right dlPFC or a control region. dlPFC targeting was based on data from a separate targeting session, where subjects completed the Sternberg working memory (WM) task inside the MRI scanner.

Results

When compared to safe conditions, subjects reported significantly higher levels of anxiety under threat conditions. Additionally, TMS-evoked responses in the left insula (LI), right sensory/motor cortex (RSM), and a region encompassing the bilateral SMA regions (BSMA) differed significantly between safe and threat conditions. There was a significant TMS-evoked deactivation in safe periods that was significantly attenuated in threat periods across all 3 regions.

Conclusions

These findings suggest that threat decreases dlPFC-regulated emotional processing by attenuating the top-down control of emotion, like the left insula. Critically, these findings provide support for the use of right dlPFC stimulation as a potential intervention in anxiety disorders.

Outcome measures for electric field modeling in tES and TMS: A systematic review and large-scale modeling study

BACKGROUND

Electric field (E-field) modeling is a potent tool to estimate the amount of transcranial magnetic and electrical stimulation (TMS and tES, respectively) that reaches the cortex and to address the variable behavioral effects observed in the field. However, outcome measures used to quantify E-fields vary considerably and a thorough comparison is missing.

OBJECTIVES

This two-part study aimed to examine the different outcome measures used to report on tES and TMS induced E-fields, including volume- and surface-level gray matter, region of interest (ROI), whole brain, geometrical, structural, and percentile-based approaches. The study aimed to guide future research in informed selection of appropriate outcome measures.

METHODS

Three electronic databases were searched for tES and/or TMS studies quantifying E-fields. The identified outcome measures were compared across volume- and surface-level E-field data in ten tES and TMS modalities targeting two common targets in 100 healthy individuals.

RESULTS

In the systematic review, we extracted 308 outcome measures from 202 studies that adopted either a gray matter volume-level (n = 197) or surface-level (n = 111) approach. Volume-level results focused on E-field magnitude, while surface-level data encompassed E-field magnitude (n = 64) and normal/tangential E-field components (n = 47). E-fields were extracted in ROIs, such as brain structures and shapes (spheres, hexahedra and cylinders), or the whole brain. Percentiles or mean values were mostly used to quantify E-fields. Our modeling study, which involved 1,000 E-field models and > 1,000,000 extracted E-field values, revealed that different outcome measures yielded distinct E-field values, analyzed different brain regions, and did not always exhibit strong correlations in the same within-subject E-field model.

CONCLUSIONS

Outcome measure selection significantly impacts the locations and intensities of extracted E-field data in both tES and TMS E-field models. The suitability of different outcome measures depends on the target region, TMS/tES modality, individual anatomy, the analyzed E-field component and the research question. To enhance the quality, rigor, and reproducibility in the E-field modeling domain, we suggest standard reporting practices across studies and provide four recommendations.

Role of the intraparietal sulcus (IPS) in anxiety and cognition: Opportunities for intervention for anxiety-related disorders

Our objective was to review the literature on the parietal cortex and intraparietal sulcus (IPS) in anxiety-related disorders, as well as opportunities for using neuromodulation to target this region and reduce anxiety. We provide an overview of prior research demonstrating: 1) the importance of the IPS in attention, vigilance, and anxious arousal, 2) the potential for neuromodulation of the IPS to reduce unnecessary attention toward threat and anxious arousal as demonstrated in healthy samples; and 3) limited data on the potential for neuromodulation of the IPS to reduce hyper-attention toward threat and anxious arousal among clinical samples with anxiety-related disorders. Future research should evaluate the efficacy of IPS neuromodulation in fully powered clinical trials, as well as the value in augmenting evidence-based treatments for anxiety with IPS neuromodulation.

Functional connectivity of the left inferior parietal lobule mediates the impact of anxiety and depression symptoms on sleep quality in healthy adults

Individuals with anxiety and depression symptoms are vulnerable to sleep disturbances. The current study aimed to explore the shared neuro-mechanisms underlying the effect of anxiety and depression symptoms on sleep quality. We recruited a cohort of 92 healthy adults who underwent functional magnetic resonance imaging scanning. We measured anxiety and depression symptoms using the Zung Self-rating Anxiety/Depression Scales and sleep quality using the Pittsburgh Sleep Quality Index. Independent component analysis was used to explore the functional connectivity (FC) of brain networks. Whole-brain linear regression analysis showed that poor sleep quality was associated with increased FC in the left inferior parietal lobule (IPL) within the anterior default mode network. Next, we extracted the covariance of anxiety and depression symptoms using principal component analysis to represent participants' emotional features. Mediation analysis revealed that the intra-network FC of the left IPL mediated the association between the covariance of anxiety and depression symptoms and sleep quality. To conclude, the FC of the left IPL may be a potential neural substrate in the association between the covariance of anxiety and depression symptoms and poor sleep quality, and may serve as a potential intervention target for the treatment of sleep disturbance in the future.

Alprazolam modulates persistence energy during emotion processing in first-degree relatives of individuals with schizophrenia: a network control study

Schizophrenia is marked by deficits in facial affect processing associated with abnormalities in GABAergic circuitry, deficits also found in first-degree relatives. Facial affect processing involves a distributed network of brain regions including limbic regions like amygdala and visual processing areas like fusiform cortex. Pharmacological modulation of GABAergic circuitry using benzodiazepines like alprazolam can be useful for studying this facial affect processing network and associated GABAergic abnormalities in schizophrenia. Here, we use pharmacological modulation and computational modeling to study the contribution of GABAergic abnormalities toward emotion processing deficits in schizophrenia. Specifically, we apply principles from network control theory to model persistence energy - the control energy required to maintain brain activation states - during emotion identification and recall tasks, with and without administration of alprazolam, in a sample of first-degree relatives and healthy controls. Here, persistence energy quantifies the magnitude of theoretical external inputs during the task. We find that alprazolam increases persistence energy in relatives but not in controls during threatening face processing, suggesting a compensatory mechanism given the relative absence of behavioral abnormalities in this sample of unaffected relatives. Further, we demonstrate that regions in the fusiform and occipital cortices are important for facilitating state transitions during facial affect processing. Finally, we uncover spatial relationships (i) between regional variation in differential control energy (alprazolam versus placebo) and (ii) both serotonin and dopamine neurotransmitter systems, indicating that alprazolam may exert its effects by altering neuromodulatory systems. Together, these findings provide a new perspective on the distributed emotion processing network and the effect of GABAergic modulation on this network, in addition to identifying an association between schizophrenia risk and abnormal GABAergic effects on persistence energy during threat processing.

Altered brain entropy and functional connectivity patterns in generalized anxiety disorder patients

BACKGROUND

Generalized anxiety disorder (GAD) is a highly prevalent disease characterized by chronic, pervasive, and intrusive worry. Previous resting-state functional MRI (fMRI) studies on GAD have mainly focused on conventional static linear features. Entropy analysis of resting-state functional magnetic resonance imaging (rs-fMRI) has recently been adopted to characterize brain temporal dynamics in some neuropsychological or psychiatric diseases. However, the nonlinear dynamic complexity of brain signals has been rarely explored in GAD.

METHODS

We measured the approximate entropy (ApEn) and sample entropy (SampEn) of the resting-state fMRI data from 38 GAD patients and 37 matched healthy controls (HCs). The brain regions with significantly different ApEn and SampEn values between the two groups were extracted. Using these brain regions as seed points, we also investigated whether there are differences in whole brain resting-state function connectivity (RSFC) pattern between GADs and HCs. Correlation analysis was subsequently conducted to investigate the association between brain entropy, RSFC and the severity of anxiety symptoms. A linear support vector machine (SVM) was used to assess the discriminative power of BEN and RSFC features among GAD patients and HCs.

RESULTS

Compared to the HCs, patients with GAD showed increased levels of ApEn in the right angular cortex (AG) and increased levels of SampEn in the right middle occipital gyrus (MOG) as well as the right inferior occipital gyrus (IOG). Contrarily, compared to the HCs, patients with GAD showed decreased RSFC between the right AG and the right inferior parietal gyrus (IPG). The SVM-based classification model achieved 85.33 % accuracy (sensitivity: 89.19 %; specificity: 81.58 %; and area under the receiver operating characteristic curve: 0.9018). The ApEn of the right AG and the SVM-based decision value was positively correlated with the Hamilton Anxiety Scale (HAMA).

LIMITATIONS

This study used cross-sectional data and sample size was small.

CONCLUSION

Patients with GAD showed increased level of nonlinear dynamical complexity of ApEn in the right AG and decreased linear features of RSFC in the right IPG. Combining the linear and nonlinear features of brain signals may be used to effectively diagnose psychiatric disorders.

Transcranial Magnetic Stimulation and its Imaging Features in Patients With Depression, Post-traumatic Stress Disorder, and Traumatic Brain Injury

Transcranial magnetic stimulation (TMS) is a type of noninvasive neurostimulation used increasingly often in clinical medicine. While most studies to date have focused on TMS's ability to treat major depressive disorder, it has shown promise in several other conditions including post-traumatic stress disorder (PTSD) and traumatic brain injury (TBI). As different treatment protocols are often used across studies, the ability to predict patient outcomes and evaluate immediate and long-term changes using imaging becomes increasingly important. Several imaging features, such as thickness, connectedness, and baseline activity of a variety of cortical and subcortical areas, have been found to be correlated with a greater response to TMS therapy. Intrastimulation imaging can reveal in real time how TMS applied to superficial areas activates or inhibits activity in deeper brain regions. Functional imaging performed weeks to months after treatment can offer an understanding of how long-term effects on brain activity relate to clinical improvement. Further work should be done to expand our knowledge of imaging features relevant to TMS therapy and how they vary across patients with different neurological and psychiatric conditions.

Sex-based variations of prefrontal structure and longitudinal symptoms in pediatric posttraumatic stress disorder

BACKGROUND

Pediatric posttraumatic stress disorder (pPTSD) is more than three times as likely to develop in trauma-exposed female youth than males. Despite the staggering sex differences in the prevalence rates of pPTSD and symptom expression, relatively little is known about the underlying biomarkers of these sex-based variations in pPTSD as compared to typically development.

METHODS

The Youth PTSD study recruited 97 youth, ages of 7 and 18, to undergo comprehensive clinical assessments and T1-weighted MRI to evaluate the extent to which sex can explain PTSD-related variations in brain structure. Whole-brain VBM as well as whole-brain estimates of cortical thickness and surface area were analyzed to identify group-by-sex interactions. Finally, we tested whether current or future symptom severity was predictive of regions exhibiting sex-based variations.

RESULTS

Clinically, females with PTSD were significantly more likely to report exposure to and higher severity of interpersonal violence and symptoms of hyperarousal. Sex and PTSD status were predictive of gray matter across the lateral prefrontal cortex (PFC), including the ventrolateral PFC and frontal pole, where increased volume and surface area was found in PTSD females as compared to PTSD males. Interestingly, the ventrolateral prefrontal cortex and frontal pole were negatively predictive of symptoms 1 year later in only males with PTSD.

CONCLUSIONS

Together, these results establish that youth with PTSD exhibit sex-based variations in clinical and trauma characteristics and prefrontal cortical structure relative to normative development. This work demonstrates the importance of examining the role that sex may play in the behavioral and neurobiological presentation of pPTSD.

Dual-targeted repetitive transcranial magnetic stimulation modulates brain functional network connectivity to improve cognition in mild cognitive impairment patients

Background: Mild cognitive impairment (MCI) is a condition between normal aging and dementia; nearly 10-15% of MCI patients develop dementia annually. There are no effective interventions for MCI progression. Repetitive transcranial magnetic stimulation (rTMS) is a non-invasive brain stimulation technique that has attempted to improve the overall cognitive function of MCI patients. However, it does not affect episodic memory improvement. Methods: In this study, we engaged 15 clinically diagnosed MCI patients and normal controls to explore the effect of dual-targeted rTMS on progressing cognitive function, particularly episodic memory in MCI patients. Resting-state EEG recordings and neuropsychological assessments were conducted before and after the intervention. EEG features were extracted using an adaptive algorithm to calculate functional connectivity alterations in relevant brain regions and the mechanisms of altered brain functional networks in response to dual-target rTMS. Results: The study revealed that the functional brain connectivity between the right posterior cingulate gyrus (PCC) and the right dorsal caudate nucleus (DC) was significantly reduced in MCI patients compared to normal controls (p < 0.001). Dual-target rTMS increased the strength of the reduced functional connectivity (p < 0.001), which was related to cognitive enhancement (p < 0.05). Conclusion: This study provides a new stimulation protocol for rTMS intervention. Improving the functional connectivity of the right PCC to the right DC is a possible mechanism by which rTMS improves overall cognitive and memory function in MCI patients.

Accelerated low-intensity rTMS does not rescue anxiety behaviour or abnormal connectivity in young adult rats following chronic restraint stress

Currently approved repetitive transcranial magnetic stimulation (rTMS) protocols for the treatment of major depressive disorder (MDD) involve once-daily (weekday) stimulation sessions, with 10 Hz or intermittent theta burst stimulation (iTBS) frequencies, over 4–6 weeks. Recently, accelerated treatment protocols (multiple daily stimulation sessions for 1–2 weeks) have been increasingly studied to optimize rTMS treatments. Accelerated protocols might confer unique advantages for adolescents and young adults but there are many knowledge gaps related to dosing in this age group. Off-label, clinical practice frequently outpaces solid evidence as rigorous clinical trials require substantial time and resources. Murine models present an opportunity for high throughput dose finding studies to focus subsequent clinical trials in humans. This project investigated the brain and behavioural effects of an accelerated low-intensity rTMS (LI-rTMS) protocol in a young adult rodent model of chronic restraint stress (CRS). Depression and anxiety-related behaviours were induced in young adult male Sprague Dawley rats using the CRS model, followed by the 3-times-daily delivery of 10 Hz LI-rTMS, for two weeks. Behaviour was assessed using the Elevated Plus Maze and Forced Swim Test, and functional, chemical, and structural brain changes measured using magnetic resonance imaging techniques. CRS induced an agitated depression-like phenotype but therapeutic effects from the accelerated protocol were not detected. Our findings suggest that the age of rodents may impact response to CRS and LI-rTMS. Future studies should also examine higher intensities of rTMS and accelerated theta burst protocols.

Frontoparietal paired associative stimulation versus single-site stimulation for generalized anxiety disorder: a pilot rTMS study

BACKGROUND

At present, the use of repetitive transcranial magnetic stimulation (rTMS) for generalized anxiety disorder (GAD) is limited to single-site interventions. We investigated whether dual-site frontoparietal stimulation delivered using cortical-cortical paired associative stimulation (ccPAS) had stronger clinical efficacy than single-site stimulation in patients with GAD.

METHODS

We randomized 50 patients with GAD to 1 Hz rTMS (10 sessions) using 1 of the following protocols: single-site stimulation over the right dorsolateral prefrontal cortex (dlPFC; 1500 pulses per session); single-site stimulation over the right posterior parietal cortex (PPC; 1500 pulses per session); repetitive dual-site ccPAS (rds-ccPAS) over the right dlPFC and right PPC with 1500 pulses per session (rd-ccPAS-1500); or rds-ccPAS over the right dlPFC and right PPC with 750 pulses per session (rd-ccPAS-750). Both rds-ccPAS treatments used a between-site interval of 100 ms.

RESULTS

Clinical scores for anxiety, depression and insomnia were reduced in all 4 groups after treatment. We found greater improvements in anxiety symptoms in the rds-ccPAS-1500 group compared to the rds-ccPAS-750 and single-site groups. We found greater improvements in depression symptoms and insomnia in the rds-PAS-1500 group compared to the single-site groups. The rds-ccPAS-1500 group also showed significant or trend-level improvements in anxiety symptoms and insomnia at 10-day and 1-month followup. More patients responded to treatment with rds-ccPAS-1500 than with single-site stimulation. The between-group differences in response rates persisted to the 3-month follow-up. Treatment using rds-ccPAS with a between-site interval of 100 ms induced a more significant improvement than the between-site interval of 50 ms we evaluated in a previous study.

LIMITATIONS

These results need to be replicated in a larger sample using sham control and equal-pulse single-site stimulation.

CONCLUSION

Frontoparietal rds-ccPAS may be a better treatment option for GAD.

From the Group to the Individual in Schizophrenia Spectrum Disorders: Biomarkers of Social Cognitive Impairments and Therapeutic Translation

People with schizophrenia spectrum disorders (SSDs) often experience persistent social cognitive impairments, associated with poor functional outcome. There are currently no approved treatment options for these debilitating symptoms, highlighting the need for novel therapeutic strategies. Work to date has elucidated differential social processes and underlying neural circuitry affected in SSDs, which may be amenable to modulation using neurostimulation. Further, advances in functional connectivity mapping and electric field modeling may be used to identify individualized treatment targets to maximize the impact of brain stimulation on social cognitive networks. Here, we review literature supporting a roadmap for translating functional connectivity biomarker discovery to individualized treatment development for social cognitive impairments in SSDs. First, we outline the relevance of social cognitive impairments in SSDs. We review machine learning approaches for dimensional brain-behavior biomarker discovery, emphasizing the importance of individual differences. We synthesize research showing that brain stimulation techniques, such as repetitive transcranial magnetic stimulation, can be used to target relevant networks. Further, functional connectivity-based individualized targeting may enhance treatment response. We then outline recent approaches to account for neuroanatomical variability and optimize coil positioning to individually maximize target engagement. Overall, the synthesized literature provides support for the utility and feasibility of this translational approach to precision treatment. The proposed roadmap to translate biomarkers of social cognitive impairments to individualized treatment is currently under evaluation in precision-guided trials. Such a translational approach may also be applicable across conditions and generalizable for the development of individualized neurostimulation targeting other behavioral deficits.

Effects of Neuromuscular Electrical Stimulation Combined with Repetitive Transcranial Magnetic Stimulation on Upper Limb Motor Function Rehabilitation in Stroke Patients with Hemiplegia

OBJECTIVE

To investigate the effect of neuromuscular electrical stimulation (NMES) combined with repetitive transcranial magnetic stimulation (rTMS) on upper limb motor dysfunction in stroke patients with hemiplegia.

METHODS

A total of 240 stroke patients with hemiplegia who met the inclusion criteria were selected and randomly divided into 4 groups (60 cases in each group): control group, NMES group, rTMS group, and NMES + rTMS group. Before treatment and 4 weeks after treatment, we evaluated and compared the results including Fugl-Meyer assessment of upper extremity (FMA-UE) motor function, modified Barthel index (MBI), modified Ashworth scale (MAS), and motor nerve electrophysiological results among the 4 groups.

RESULTS

Before treatment, there was no significant difference in the scores of FMA-UE, MBI, MAS, and motor nerve electrophysiological indexes among the four groups, with comparability. Compared with those before treatment, the scores of the four groups were significantly increased and improved after treatment. And the score of the NMES + rTMS group was notably higher than those in the other three groups.

CONCLUSION

NMES combined with rTMS can conspicuously improve the upper extremity motor function and activities of daily life of stroke patients with hemiplegia, which is worthy of clinical application and promotion.

Dynamic Tracking of State Anxiety via Multi-Modal Data and Machine Learning

Anxiety induction is widely used in the investigations of the mechanism and treatment of state anxiety. State anxiety is accompanied by immediate psychological and physiological responses. However, the existing state anxiety measurement, such as the commonly used state anxiety subscale of the State-Trait Anxiety Inventory, mainly relies on questionnaires with low temporal resolution. This study aims to develop a tracking model of state anxiety with high temporal resolution. To capture the dynamic changes of state anxiety levels, we induced the participants' state anxiety through exposure to aversive pictures or the risk of electric shocks and simultaneously recorded multi-modal data, including dimensional emotion ratings, electrocardiogram, and galvanic skin response. Using the paired self-reported state anxiety levels and multi-modal measures, we trained and validated machine learning models to predict state anxiety based on psychological and physiological features extracted from the multi-modal data. The prediction model achieved a high correlation between the predicted and self-reported state anxiety levels. This quantitative model provides fine-grained and sensitive measures of state anxiety levels for future affective brain-computer interaction and anxiety modulation studies.

Proof of concept study to develop a novel connectivity-based electric-field modelling approach for individualized targeting of transcranial magnetic stimulation treatment

Resting state functional connectivity (rsFC) offers promise for individualizing stimulation targets for transcranial magnetic stimulation (TMS) treatments. However, current targeting approaches do not account for non-focal TMS effects or large-scale connectivity patterns. To overcome these limitations, we propose a novel targeting optimization approach that combines whole-brain rsFC and electric-field (e-field) modelling to identify single-subject, symptom-specific TMS targets. In this proof of concept study, we recruited 91 anxious misery (AM) patients and 25 controls. We measured depression symptoms (MADRS/HAMD) and recorded rsFC. We used a PCA regression to predict symptoms from rsFC and estimate the parameter vector, for input into our e-field augmented model. We modeled 17 left dlPFC and 7 M1 sites using 24 equally spaced coil orientations. We computed single-subject predicted ΔMADRS/HAMD scores for each site/orientation using the e-field augmented model, which comprises a linear combination of the following elementwise products (1) the estimated connectivity/symptom coefficients, (2) a vectorized e-field model for site/orientation, (3) rsFC matrix, scaled by a proportionality constant. In AM patients, our connectivity-based model predicted a significant decrease depression for sites near BA9, but not M1 for coil orientations perpendicular to the cortical gyrus. In control subjects, no site/orientation combination showed a significant predicted change. These results corroborate previous work suggesting the efficacy of left dlPFC stimulation for depression treatment, and predict better outcomes with individualized targeting. They also suggest that our novel connectivity-based e-field modelling approach may effectively identify potential TMS treatment responders and individualize TMS targeting to maximize the therapeutic impact.

Neural correlates of extinguished threat recall underlying the commonality between pediatric anxiety and irritability

BACKGROUND

Anxiety and irritability frequently co-occur in youth and are mediated by aberrant threat responses. However, empirical evidence on neural mechanisms underlying this co-occurrence is limited. To address this, we apply data-driven latent phenotyping to data from a prior report of a well-validated threat extinction recall fMRI paradigm.

METHODS

Participants included 59 youth (28 anxiety disorder, 31 healthy volunteers; Mage=13.15 yrs) drawn from a transdiagnostic sample of 331 youth, in which bifactor analysis was conducted to derive latent factors representing shared vs. unique variance of dimensionally-assessed anxiety and irritability. Participants underwent threat conditioning and extinction. Approximately three weeks later, during extinction recall fMRI, participants made threat-safety discriminations under two task conditions: current threat appraisal and explicit recall of threat contingencies. Linear mixed-effects analyses examined associations of a "negative affectivity" factor reflecting shared anxiety and irritability variance with whole-brain activation and task-dependent amygdala connectivity.

RESULTS

During recall of threat-safety contingencies, higher negative affectivity was associated with greater prefrontal (ventrolateral/ventromedial, dorsolateral, orbitofrontal), motor, temporal, parietal, and occipital activation. During threat appraisal, higher negative affectivity was associated with greater amygdala-inferior parietal lobule connectivity to threat/safety ambiguity.

LIMITATIONS

Sample included only healthy youth and youth with anxiety disorders. Results may not generalize to other diagnoses for which anxiety and irritability are also common, and our negative affectivity factor should be interpreted as anxiety disorders with elevated irritability. Reliability of some subfactors was poor.

CONCLUSIONS

Aberrant amygdala-prefrontal-parietal circuitry during extinction recall of threat-safety stimuli may be a mechanism underlying the co-occurrence of pediatric anxiety and irritability.

Neurophysiological and clinical effects of the NMDA receptor antagonist lanicemine (BHV-5500) in PTSD: A randomized, double-blind, placebo-controlled trial

BACKGROUND

Posttraumatic stress disorder (PTSD) is associated with hyperarousal and stress reactivity, features consistent with behavioral sensitization. In this Phase 1b, parallel-arm, randomized, double-blind, placebo-controlled trial, we tested whether the selective low-trapping N-methyl-D-aspartate receptor (NMDAR) antagonist [Lanicemine (BHV-5500)] blocks expression of behavioral sensitization.

METHODS

Twenty-four participants with elevated anxiety potentiated startle (APS) and moderate-to-severe PTSD symptoms received three infusions of lanicemine 1.0 mg/ml (100 mg) or matching placebo (0.9% saline) (1:1 ratio), over a 5-day period. The primary outcome was change in APS from baseline to end of third infusion. We also examined changes in EEG gamma-band oscillatory activity as measures of NMDAR target engagement and explored Clinician-Administered PTSD Scale (CAPS-5) hyperarousal scores.

RESULTS

Lanicemine was safe and well-tolerated with no serious adverse events. Using Bayesian statistical inference, the posterior probability that lanicemine outperformed placebo on APS T-score after three infusions was 38%. However, after the first infusion, there was a 90% chance that lanicemine outperformed placebo in attenuating APS T-score by a standardized effect size more than 0.4.

CONCLUSION

We demonstrated successful occupancy of lanicemine on NMDAR using gamma-band EEG and effects on hyperarousal symptoms (Cohen's d = 0.75). While lanicemine strongly attenuated APS following a single infusion, differential changes from placebo after three infusions was likely obscured by habituation effects. To our knowledge, this is the first use of APS in the context of an experimental medicine trial of a NMDAR antagonist in PTSD. These findings support selective NMDAR antagonism as a viable pharmacological strategy for salient aspects of PTSD.

Functional connectivity of the visual cortex differentiates anxiety comorbidity from episodic migraineurs without aura

Background

Migraine is a common neurological disease that is often accompanied by psychiatric comorbidities. However, the relationship between abnormal brain function and psychiatric comorbidities in migraine patients remains largely unclear. Therefore, the present study sought to explore the correlations between the resting-state functional deficits and psychiatric comorbidities in migraine without aura (MwoA) patients.

Methods

Resting-state functional magnetic resonance images were obtained. In addition, the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) values were obtained. Thereafter regional abnormalities in MwoA patients with and without anxiety (MwoA-A and MwoA-OA) were chosen as seeds to conduct functional connectivity (FC) analysis.

Results

Compared to the healthy controls (HCs), the MwoA-A and MwoA-OA patients had abnormal ALFF and ReHo values in the right lingual gyrus (LG). They also had abnormal FC of the right LG with the ipsilateral superior frontal gyrus (SFG) and middle cingulate cortex (MCC). Additionally, the MwoA-A patients showed higher ReHo values in the left posterior intraparietal sulcus (pIPS) and abnormal FC of the right LG with ipsilateral pIPS and primary visual cortex, compared to the MwoA-OA patients. Moreover, the MwoA-OA patients showed an increase in the FC with the right posterior cingulate cortex/precuneus (PCC/PCUN), left middle frontal gyrus (MFG) and left inferior temporal gyrus (ITG) relative to the HCs. Furthermore, the ALFF values of the right LG positively were correlated with anxiety scores in MwoA-A patients. The abnormal LG-related FCs with the PCC/PCUN, MFG and ITG were negatively associated with the frequency of headaches in MwoA-OA patients.

Conclusions

This study identified abnormal visual FC along with other core networks differentiating anxiety comorbidity from MwoA. This may therefore enhance the understanding of the neuropsychological basis of psychiatric comorbidities and provide novel insights that may help in the discovery of new marks or even treatment targets.

The efficacy of repetitive transcranial magnetic stimulation on emotional processing in apathetic patients with Parkinson's disease: A Placebo-controlled ERP study

BACKGROUND

Few studies have examined the effect of rTMS on impaired emotional processing in apathetic Parkinson's disease (PD) patients, which impelled us to use a combination of repetitive transcranial magnetic stimulation (rTMS) with event-related potentials (ERPs) to gain insight into the underlying mechanisms.

METHODS

Apathetic and non-apathetic patients diagnosed with PD performed a facial emotion categorization task, and ERP data were collected before and after HF-rTMS or sham stimulation over the right dorsolateral prefrontal cortex (DLPFC). We observed the behavioural results and early components of P100 and N170.

RESULTS

After rTMS, accuracy (ACC) was higher for negative expressions, and reaction times (RTs) were shorter for all expressions in both apathetic and non-apathetic patients. P100 amplitudes significantly increased except for negative expressions in the right hemisphere, and hemisphere lateralization was reversed in apathetic patients. P100 amplitudes increased for all expressions bilaterally in non-apathetic patients. N170 amplitudes in apathetic patients increased, and hemisphere lateralization was normalized. Neither the apathetic sham group nor the non-apathetic cohort of patients showed changes in P100 or N170 lateralization.

LIMITATIONS

The effects of rTMS on PD patients relative to normal subjects should be compared and observed over a long period of time.

CONCLUSIONS

HF-rTMS over the right DLPFC is beneficial for emotional processing in both apathetic and non-apathetic PD patients but shows different sensitivities. The effect of rTMS on emotional processing impairments in apathetic PD patients is profound. Treatment with rTMS may be an important, novel nonpharmaceutical approach for apathy in PD patients.

A generalized workflow for conducting electric field-optimized, fMRI-guided, transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a noninvasive method to stimulate the cerebral cortex that has applications in psychiatry, such as in the treatment of depression and anxiety. Although many TMS targeting methods that use figure-8 coils exist, many do not account for individual differences in anatomy or are not generalizable across target sites. This protocol combines functional magnetic resonance imaging (fMRI) and iterative electric-field (E-field) modeling in a generalized approach to subject-specific TMS targeting that is capable of optimizing the stimulation site and TMS coil orientation. To apply this protocol, the user should (i) operationally define a region of interest (ROI), (ii) generate the head model from the structural MRI data, (iii) preprocess the functional MRI data, (iv) identify the single-subject stimulation site within the ROI, and (iv) conduct E-field modeling to identify the optimal coil orientation. In comparison with standard targeting methods, this approach demonstrates (i) reduced variability in the stimulation site across subjects, (ii) reduced scalp-to-cortical-target distance, and (iii) reduced variability in optimal coil orientation. Execution of this protocol requires intermediate-level skills in structural and functional MRI processing. This protocol takes ~24 h to complete and demonstrates how constrained fMRI targeting combined with iterative E-field modeling can be used as a general method to optimize both the TMS coil site and its orientation.

Correlation between executive function and quantitative EEG in patients with anxiety by the Research Domain Criteria (RDoC) framework

The Research Domain Criteria (RDoC) project was proposed by the National Institute of Mental Health in 2010 to create a new diagnostic system including symptoms and data from genetics, neuroscience, physiology, and self-reports. The purpose of this study was to determine the link between anxiety and executive functions through quantitative electroencephalography (qEEG) based on the RDoC system. Nineteen-channel EEGs were recorded at the psychiatric clinic from 41 patients with symptoms of anxiety. The EEG power spectra were analysed. The Executive Intelligence Test (EXIT) including the K-WAIS-IV, Stroop, controlled oral word association, and the design fluency tests were performed. A partial, inversed, and significant association was observed between executive intelligence quotient (EIQ) and the absolute delta power in the central region. Similarly, a partial, inversed, and significant association was observed between design fluency and the absolute delta power in the left parietal area. Our findings suggest that the increase in delta power in the central region and left P3 was negatively correlated with the decrease in executive function. It is expected that the absolute delta power plays a specific role in the task-negative default mode network in the relationship between anxiety and executive function.