Transcranial direct current stimulation for auditory verbal hallucinations: a systematic review of clinical trials

Estimation of complete mutual information exploiting nonlinear magnitude-phase dependence: Application to spatial FNC for complex-valued fMRI data

BACKGROUND

Real-valued mutual information (MI) has been used in spatial functional network connectivity (FNC) to measure high-order and nonlinear dependence between spatial maps extracted from magnitude-only functional magnetic resonance imaging (fMRI). However, real-valued MI cannot fully capture the group differences in spatial FNC from complex-valued fMRI data with magnitude and phase dependence.

METHODS

We propose a complete complex-valued MI method according to the chain rule of MI. We fully exploit the dependence among magnitudes and phases of two complex-valued signals using second and fourth-order joint entropies, and propose to use a Gaussian copula transformation with a lower bound property to avoid inaccurate estimation of joint probability density function when computing the joint entropies.

RESULTS

The proposed method achieves more accurate MI estimates than the two histogram-based (normal and symbolic approaches) and kernel density estimation methods for simulated signals, and enhances group differences in spatial functional network connectivity for experimental complex-valued fMRI data.

COMPARISON WITH EXISTING METHODS

Compared with the simplified complex-valued MI and real-valued MI, the proposed method yields higher MI estimation accuracy, leading to 17.4 % and 145.5 % wider MI ranges, and more significant connectivity differences between healthy controls and schizophrenia patients. A unique connection between executive control network (EC) and right frontal parietal areas, and three additional connections mainly related to EC are detected than the simplified complex-valued MI.

CONCLUSIONS

With capability in quantifying MI fully and accurately, the proposed complex-valued MI is promising in providing qualified FNC biomarkers for identifying mental disorders such as schizophrenia.

A new transfer entropy method for measuring directed connectivity from complex-valued fMRI data

Background

Inferring directional connectivity of brain regions from functional magnetic resonance imaging (fMRI) data has been shown to provide additional insights into predicting mental disorders such as schizophrenia. However, existing research has focused on the magnitude data from complex-valued fMRI data without considering the informative phase data, thus ignoring potentially important information.

Methods

We propose a new complex-valued transfer entropy (CTE) method to measure causal links among brain regions in complex-valued fMRI data. We use the transfer entropy to model a general non-linear magnitude-magnitude and phase-phase directed connectivity and utilize partial transfer entropy to measure the complementary phase and magnitude effects on magnitude-phase and phase-magnitude causality. We also define the significance of the causality based on a statistical test and the shuffling strategy of the two complex-valued signals.

Results

Simulated results verified higher accuracy of CTE than four causal analysis methods, including a simplified complex-valued approach and three real-valued approaches. Using experimental fMRI data from schizophrenia and controls, CTE yields results consistent with previous findings but with more significant group differences. The proposed method detects new directed connectivity related to the right frontal parietal regions and achieves 10.2-20.9% higher SVM classification accuracy when inferring directed connectivity using anatomical automatic labeling (AAL) regions as features.

Conclusion

The proposed CTE provides a new general method for fully detecting highly predictive directed connectivity from complex-valued fMRI data, with magnitude-only fMRI data as a specific case.

Dynamic functional network connectivity based on spatial source phase maps of complex-valued fMRI data: Application to schizophrenia

BACKGROUND

Dynamic spatial functional network connectivity (dsFNC) has shown advantages in detecting functional alterations impacted by mental disorders using magnitude-only fMRI data. However, complete fMRI data are complex-valued with unique and useful phase information.

METHODS

We propose dsFNC of spatial source phase (SSP) maps, derived from complex-valued fMRI data (named SSP-dsFNC), to capture the dynamics elicited by the phase. We compute mutual information for connectivity quantification, employ statistical analysis and Markov chains to assess dynamics, ultimately classifying schizophrenia patients (SZs) and healthy controls (HCs) based on connectivity variance and Markov chain state transitions across windows.

RESULTS

SSP-dsFNC yielded greater dynamics and more significant HC-SZ differences, due to the use of complete brain information from complex-valued fMRI data.

COMPARISON WITH EXISTING METHODS

Compared with magnitude-dsFNC, SSP-dsFNC detected additional and meaningful connections across windows (e.g., for right frontal parietal) and achieved 14.6% higher accuracy for classifying HCs and SZs.

CONCLUSIONS

This work provides new evidence about how SSP-dsFNC could be impacted by schizophrenia, and this information could be used to identify potential imaging biomarkers for psychotic diagnosis.

Preconditioning prefrontal connectivity using transcranial direct current stimulation and transcranial magnetic stimulation

Transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS) have been shown to modulate functional connectivity. Their specific effects seem to be dependent on the pre-existing neuronal state. We aimed to precondition frontal networks using tDCS and subsequently stimulate the left dorsolateral prefrontal cortex (lDLPFC) using TMS. Thirty healthy participants underwent excitatory, inhibitory, or sham tDCS for 10 min, as well as an excitatory intermittent theta-burst (iTBS) protocol (600 pulses, 190 s, 20 × 2-s trains), applied over the lDLPFC at 90% of the individual resting motor threshold. Functional connectivity was measured in three task-free resting state fMRI sessions, immediately before and after tDCS, as well as after iTBS. Testing the whole design did not yield any significant results. Analysis of the connectivity between the stimulation site and all other brain voxels, contrasting only the interaction effect between the experimental groups (excitatory vs. inhibitory) and the repeated measure (post-tDCS vs. post-TMS), revealed significantly affected voxels bilaterally in the anterior cingulate and paracingulate gyri, the caudate nuclei, the insula and operculum cortices, as well as the Heschl’s gyrus. Post-hoc ROI-to-ROI analyses between the significant clusters and the striatum showed post-tDCS, temporo-parietal-to-striatal and temporo-parietal-to-fronto-cingulate differences between the anodal and cathodal tDCSgroup, as well as post-TMS, striatal-to-temporo-parietal differences between the anodal and cathodal groups and frontostriatal and interhemispheric temporo-parietal cathodal-sham group differences. Excitatory iTBS to a tDCS-inhibited lDLPFC thus yielded more robust functional connectivity to various areas as compared to excitatory iTBS to a tDCS-enhanced DLPFC. Even considering reduced statistical power due to low subject numbers, results demonstrate complex, whole-brain stimulation effects. They are possibly facilitated by cortical homeostatic control mechanisms and show the feasibility of using tDCS to modulate subsequent TMS effects. This proof-of-principle study might stimulate further research into the principle of preconditioning that might be useful in the development of protocols using DLPFC as a stimulation site for the treatment of depression.

Adjunctive tDCS for treatment-refractory auditory hallucinations in schizophrenia: A meta-analysis of randomized, double-blinded, sham-controlled studies

OBJECTIVE

Treatment-refractory auditory hallucinations (TRAH) in schizophrenia often do not improve with pharmacotherapy. We performed a meta-analysis of randomized, double-blind, sham-controlled clinical trials (RCTs) that systematically examined the therapeutic effects and tolerability of adjunctive active versus sham active transcranial direct current stimulation (tDCS) for auditory hallucinations as measured by the Auditory Hallucination Rating Scale (AHRS) in schizophrenia patients with TRAH.

METHODS

Relevant data were extracted, checked and analyzed using the Review Manager, Version 5.3 by three independent investigators.

RESULTS

Eight double-blind RCTs covering 329 schizophrenia patients (168 in active tDCS group, 161 in sham tDCS group) were included. Although no advantage of active tDCS on auditory hallucinations [7 RCTs, n = 224; standardized mean difference (SMD): - 0.33 (95% confidence interval (CI): - 0.71, 0.05), P = 0.09; I² = 46%] was found compared to sham, subgroup analyses revealed that active tDCS with twice-daily stimulation [6 RCTs, n = 198; SMD: - 0.42 (95%CI: -0.82, -0.02), P = 0.04; I² = 44%] and active tDCS with ≥ 10 stimulation sessions [6 RCTs, n = 198; SMD: - 0.42 (95%CI: -0.82, -0.02), P = 0.04; I² = 44%] showed a significantly better therapeutic effect than sham in improving auditory hallucinations symptoms. Meta-analyses of total psychopathology and discontinuation due to any reason were not significantly different between the active and sham tDCS groups.

CONCLUSION

This meta-analysis demonstrated that the effects of tDCS for auditory hallucinations symptoms were influenced by the tDCS parameters. Twice-daily stimulation and ≥ 10 stimulation sessions may be needed to improve auditory hallucinations symptoms in schizophrenia with TRAH.

Cerebellar stimulation in schizophrenia: A systematic review of the evidence and an overview of the methods

BACKGROUND

Cerebellar structural and functional abnormalities underlie widespread deficits in clinical, cognitive, and motor functioning that are observed in schizophrenia. Consequently, the cerebellum is a promising target for novel schizophrenia treatments. Here we conducted an updated systematic review examining the literature on cerebellar stimulation efficacy and tolerability for mitigating symptoms of schizophrenia. We discuss the purported mechanisms of cerebellar stimulation, current methods for implementing stimulation, and future directions of cerebellar stimulation for intervention development with this population.

METHODS

Two independent authors identified 20 published studies (7 randomized controlled trials, 7 open-label studies, 1 pilot study, 4 case reports, 1 preclinical study) that describe the effects of cerebellar circuitry modulation in patients with schizophrenia or animal models of psychosis. Published studies up to October 11, 2022 were identified from a search within PubMed, Scopus, and PsycInfo.

RESULTS

Most studies stimulating the cerebellum used transcranial magnetic stimulation or transcranial direct-current stimulation, specifically targeting the cerebellar vermis/midline. Accounting for levels of methodological rigor across studies, these studies detected post-cerebellar modulation in schizophrenia as indicated by the alleviation of certain clinical symptoms (mainly negative and depressive symptoms), as well as increased frontal-cerebellar connectivity and augmentation of canonical neuro-oscillations known to be abnormal in schizophrenia. In contrast to a prior review, we did not find consistent evidence for cognitive improvements following cerebellar modulation stimulation. Modern cerebellar stimulation methods appear tolerable for individuals with schizophrenia, with only mild and temporary side effects.

CONCLUSION

Cerebellar stimulation is a promising intervention for individuals with schizophrenia that may be more relevant to some symptom domains than others. Initial results highlight the need for continued research using more methodologically rigorous designs, such as additional longitudinal and randomized controlled trials.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42022346667].