Personalized brain stimulation of memory networks

Effectiveness of Personalized Hippocampal Network-Targeted Stimulation in Alzheimer Disease: A Randomized Clinical Trial

Importance

Repetitive transcranial magnetic stimulation (rTMS) has emerged as a safe and promising intervention for Alzheimer disease (AD).

Objective

To investigate the effect of a 4-week personalized hippocampal network-targeted rTMS on cognitive and functional performance, as well as functional connectivity in AD.

Design, Setting, and Participants

This randomized clinical trial, which was sham-controlled and masked to participants and evaluators, was conducted between May 2020 and April 2022 at a single Korean memory clinic. Eligible participants were between ages 55 and 90 years and had confirmed early AD with evidence of an amyloid biomarker. Participants who met the inclusion criteria were randomly assigned to receive hippocampal network-targeted rTMS or sham stimulation. Participants received 4-week rTMS treatment, with assessment conducted at weeks 4 and 8. Data were analyzed between April 2022 and January 2024.

Interventions

Each patient received 20 sessions of personalized rTMS targeting the left parietal area, functionally connected to the hippocampus, based on fMRI connectivity analysis over 4 weeks. The sham group underwent the same procedure, excluding actual magnetic stimulation. A personalized 3-dimensional printed frame to fix the TMS coil to the optimal target site was produced.

Main Outcomes and Measures

The primary outcome was the change in the AD Assessment Scale-Cognitive Subscale test (ADAS-Cog) after 8 weeks from baseline. Secondary outcomes included changes in the Clinical Dementia Rating-Sum of Boxes (CDR-SOB) and Seoul-Instrumental Activity Daily Living (S-IADL) scales, as well as resting-state fMRI connectivity between the hippocampus and cortical areas.

Results

Among 30 participants (18 in the rTMS group; 12 in the sham group) who completed the 8-week trial, the mean (SD) age was 69.8 (9.1) years; 18 (60%) were female. As the primary outcome, the change in ADAS-Cog at the eighth week was significantly different between the rTMS and sham groups (coefficient [SE], -5.2 [1.6]; P = .002). The change in CDR-SOB (-4.5 [1.4]; P = .007) and S-IADL (1.7 [0.7]; P = .004) were significantly different between the groups favoring rTMS groups. The fMRI connectivity analysis revealed that rTMS increased the functional connectivity between the hippocampus and precuneus, with its changes associated with improvements in ADAS-Cog (r = -0.57; P = .005).

Conclusions and Relevance

This randomized clinical trial demonstrated the positive effects of rTMS on cognitive and functional performance, and the plastic changes in the hippocampal-cortical network. Our results support the consideration of rTMS as a potential treatment for AD.

Trial Registration

ClinicalTrials.gov Identifier: NCT04260724.

Targeting Symptom-Specific Networks With Transcranial Magnetic Stimulation

Increasing evidence suggests that the clinical effects of transcranial magnetic stimulation are target dependent. Within any given symptom, precise targeting of specific brain circuits may improve clinical outcomes. This principle can also be extended across symptoms-stimulation of different circuits may lead to different symptom-level outcomes. This may include targeting different symptoms within the same disorder (such as dysphoria vs. anxiety in patients with major depression) or targeting the same symptom across different disorders (such as primary major depression and depression secondary to stroke, traumatic brain injury, epilepsy, multiple sclerosis, or Parkinson's disease). Some of these symptom-specific changes may be desirable, while others may be undesirable. This review focuses on the conceptual framework through which symptom-specific target circuits may be identified, tested, and implemented.

Personalized and Circuit-Based Transcranial Magnetic Stimulation: Evidence, Controversies, and Opportunities

The development of neuroimaging methodologies to map brain connectivity has transformed our understanding of psychiatric disorders, the distributed effects of brain stimulation, and how transcranial magnetic stimulation can be best employed to target and ameliorate psychiatric symptoms. In parallel, neuroimaging research has revealed that higher-order brain regions such as the prefrontal cortex, which represent the most common therapeutic brain stimulation targets for psychiatric disorders, show some of the highest levels of interindividual variation in brain connectivity. These findings provide the rationale for personalized target site selection based on person-specific brain network architecture. Recent advances have made it possible to determine reproducible personalized targets with millimeter precision in clinically tractable acquisition times. These advances enable the potential advantages of spatially personalized transcranial magnetic stimulation targeting to be evaluated and translated to basic and clinical applications. In this review, we outline the motivation for target site personalization, preliminary support (mostly in depression), convergent evidence from other brain stimulation modalities, and generalizability beyond depression and the prefrontal cortex. We end by detailing methodological recommendations, controversies, and notable alternatives. Overall, while this research area appears highly promising, the value of personalized targeting remains unclear, and dedicated large prospective randomized clinical trials using validated methodology are critical.

Functional magnetic resonance imaging in schizophrenia: current evidence, methodological advances, limitations and future directions

Functional neuroimaging emerged with great promise and has provided fundamental insights into the neurobiology of schizophrenia. However, it has faced challenges and criticisms, most notably a lack of clinical translation. This paper provides a comprehensive review and critical summary of the literature on functional neuroimaging, in particular functional magnetic resonance imaging (fMRI), in schizophrenia. We begin by reviewing research on fMRI biomarkers in schizophrenia and the clinical high risk phase through a historical lens, moving from case-control regional brain activation to global connectivity and advanced analytical approaches, and more recent machine learning algorithms to identify predictive neuroimaging features. Findings from fMRI studies of negative symptoms as well as of neurocognitive and social cognitive deficits are then reviewed. Functional neural markers of these symptoms and deficits may represent promising treatment targets in schizophrenia. Next, we summarize fMRI research related to antipsychotic medication, psychotherapy and psychosocial interventions, and neurostimulation, including treatment response and resistance, therapeutic mechanisms, and treatment targeting. We also review the utility of fMRI and data-driven approaches to dissect the heterogeneity of schizophrenia, moving beyond case-control comparisons, as well as methodological considerations and advances, including consortia and precision fMRI. Lastly, limitations and future directions of research in the field are discussed. Our comprehensive review suggests that, in order for fMRI to be clinically useful in the care of patients with schizophrenia, research should address potentially actionable clinical decisions that are routine in schizophrenia treatment, such as which antipsychotic should be prescribed or whether a given patient is likely to have persistent functional impairment. The potential clinical utility of fMRI is influenced by and must be weighed against cost and accessibility factors. Future evaluations of the utility of fMRI in prognostic and treatment response studies may consider including a health economics analysis.

The future of brain circuit-targeted therapeutics

The principle of targeting brain circuits has drawn increasing attention with the growth of brain stimulation treatments such as transcranial magnetic stimulation (TMS), deep brain stimulation (DBS), and focused ultrasound (FUS). Each of these techniques can effectively treat different neuropsychiatric disorders, but treating any given disorder depends on choosing the right treatment target. Here, we propose a three-phase framework for identifying and modulating these targets. There are multiple approaches to identifying a target, including correlative neuroimaging, retrospective optimization based on existing stimulation sites, and lesion localization. These techniques can then be optimized using personalized neuroimaging, physiological monitoring, and engagement of a specific brain state using pharmacological or psychological interventions. Finally, a specific stimulation modality or combination of modalities can be chosen after considering the advantages and tradeoffs of each. While there is preliminary literature to support different components of this framework, there are still many unanswered questions. This presents an opportunity for the future growth of research and clinical care in brain circuit therapeutics.

Optimizing Individual Targeting of Fronto-Amygdala Network with Transcranial Magnetic Stimulation (TMS): Biophysical, Physiological and Behavioral Variations in People with Methamphetamine Use Disorder

Background

Previous studies in people with substance use disorders (SUDs) have implicated both the frontopolar cortex and amygdala in drug cue reactivity and craving, and amygdala-frontopolar coupling is considered a marker of early relapse risk. Accumulating data highlight that the frontopolar cortex can be considered a promising therapeutic target for transcranial magnetic stimulation (TMS) in SUDs. However, one-size-fits-all approaches to TMS targets resulted in substantial variation in both physiological and behavioral outcomes. Individualized TMS approaches to target cortico-subcortical circuits like amygdala-frontopolar have not yet been investigated in SUDs.

Objective

Here, we (1) defined individualized TMS target location based on functional connectivity of the amygdala-frontopolar circuit while people were exposed to drug-related cues, (2) optimized coil orientation based on maximizing electric field (EF) perpendicular to the individualized target, and (3) harmonized EF strength in targeted brain regions across a population.

Method

MRI data including structural, resting-state, and task-based fMRI data were collected from 60 participants with methamphetamine use disorders (MUDs). Craving scores based on a visual analog scale were collected immediately before and after the MRI session. We analyzed inter-subject variability in the location of TMS targets based on the maximum task-based connectivity between the left medial amygdala (with the highest functional activity among subcortical areas during drug cue exposure) and frontopolar cortex using psychophysiological interaction (PPI) analysis. Computational head models were generated for all participants and EF simulations were calculated for fixed vs. optimized coil location (Fp1/Fp2 vs. individualized maximal PPI location), orientation (AF7/AF8 vs. orientation optimization algorithm), and stimulation intensity (constant vs. adjusted intensity across the population).

Results

Left medial amygdala with the highest (mean ± SD: 0.31±0.29) functional activity during drug cue exposure was selected as the subcortical seed region. Amygdala-to-whole brain PPI analysis showed a significant cluster in the prefrontal cortex (cluster size: 2462 voxels, cluster peak in MNI space: [25 39 35]) that confirms cortico-subcortical connections. The location of the voxel with the most positive amygdala-frontopolar PPI connectivity in each participant was considered as the individualized TMS target (mean ± SD of the MNI coordinates: [12.6 64.23 -0.8] ± [13.64 3.50 11.01]). Individual amygdala-frontopolar PPI connectivity in each participant showed a significant correlation with VAS scores after cue exposure (R=0.27, p=0.03). Averaged EF strength in a sphere with r = 5mm around the individualized target location was significantly higher in the optimized (mean ± SD: 0.99 ± 0.21) compared to the fixed approach (Fp1: 0.56 ± 0.22, Fp2: 0.78 ± 0.25) with large effect sizes (Fp1: p = 1.1e-13, Hedges'g = 1.5, Fp2: p = 1.7e-5, Hedges'g = 1.26). Adjustment factor to have identical 1 V/m EF strength in a 5mm sphere around the individualized targets ranged from 0.72 to 2.3 (mean ± SD: 1.07 ± 0.29).

Conclusion

Our results show that optimizing coil orientation and stimulation intensity based on individualized TMS targets led to stronger electric fields in the targeted brain regions compared to a one-size-fits-all approach. These findings provide valuable insights for refining TMS therapy for SUDs by optimizing the modulation of cortico-subcortical circuits.