Optimal deep brain stimulation sites and networks for stimulation of the fornix in Alzheimer's disease

Romer-EPTI: Rotating-view motion-robust super-resolution EPTI for SNR-efficient distortion-free in-vivo mesoscale diffusion MRI and microstructure imaging

PURPOSE

To overcome the major challenges in diffusion MRI (dMRI) acquisition, including limited SNR, distortion/blurring, and susceptibility to motion artifacts.

THEORY AND METHODS

A novel Romer-EPTI technique is developed to achieve SNR-efficient acquisition while providing distortion-free imaging, minimal spatial blurring, high motion robustness, and simultaneous multi-TE imaging. It introduces a ROtating-view Motion-robust supEr-Resolution technique (Romer) combined with a distortion/blurring-free Echo Planar Time-resolved Imaging (EPTI) readout. Romer enhances SNR through simultaneous multi-thick-slice acquisition with rotating-view encoding, while providing high motion-robustness via a high-fidelity, motion-aware super-resolution reconstruction. Instead of EPI, the in-plane encoding is performed using EPTI readout to prevent geometric distortion, T2/T2*-blurring, and importantly, dynamic distortions that could introduce additional blurring/artifacts after super-resolution reconstruction due to combining volumes with inconsistent geometries. This further improves effective spatial resolution and motion robustness. Additional developments include strategies to address slab-boundary artifacts, achieve minimized TE and optimized readout for additional SNR gain, and increase robustness to strong phase variations at high b-values.

RESULTS

Using Romer-EPTI, we demonstrated distortion-free whole-brain mesoscale in-vivo dMRI at both 3T (500-μm isotropic [iso] resolution) and 7T (485-μm iso resolution) for the first time. Motion experiments demonstrated the technique's motion robustness and its ability to obtain high-resolution diffusion images in the presence of subject motion. Romer-EPTI also demonstrated high SNR gain and robustness in high b-value (b = 5000 s/mm2) and time-dependent dMRI.

CONCLUSION

The high SNR efficiency, improved image quality, and motion robustness of Romer-EPTI make it a highly efficient acquisition for high-resolution dMRI and microstructure imaging.

Pathogenesis, diagnostics, and therapeutics for Alzheimer's disease: Breaking the memory barrier

Alzheimer's disease (AD) is the most common cause of dementia and accounts for 60-70 % of all cases. It affects millions of people worldwide. AD poses a substantial economic burden on societies and healthcare systems. AD is a progressive neurodegenerative disorder characterized by cognitive decline, memory loss, and impaired daily functioning. As the prevalence of AD continues to increase, understanding its pathogenesis, improving diagnostic methods, and developing effective therapeutics have become paramount. This comprehensive review delves into the intricate mechanisms underlying AD, explores the current state of diagnostic techniques, and examines emerging therapeutic strategies. By revealing the complexities of AD, this review aims to contribute to the growing body of knowledge surrounding this devastating disease.

Linking Invasive and Noninvasive Brain Stimulation in Parkinson's Disease: A Randomized Trial

BACKGROUND

Recent imaging studies identified a brain network associated with clinical improvement following deep brain stimulation (DBS) in Parkinson's disease (PD), the PD response network.

OBJECTIVES

This study aimed to assess the impact of neuromodulation on PD motor symptoms by targeting this network noninvasively using multifocal transcranial direct current stimulation (tDCS).

METHODS

In a prospective, randomized, double-blinded, crossover trial, 21 PD patients (mean age 59.7 years, mean Hoehn & Yahr [H&Y] 2.4) received multifocal tDCS targeting the a-priori network. Twenty-minute sessions of tDCS and sham were administered on 2 days in randomized order. Movement Disorder Society-Unified Parkinson's Disease Rating Scale-Part III (MDS-UPDRS-III) scores were assessed.

RESULTS

Before intervention, MDS-UPDRS-III scores were comparable in both conditions (stimulation days: 37.38 (standard deviation [SD] = 12.50, confidence interval [CI] = 32.04, 42.73) vs. sham days: 36.95 (SD = 13.94, CI = 30.99, 42.91), P = 0.63). Active stimulation resulted in a reduction by 3.6 points (9.7%) to 33.76 (SD = 11.19, CI = 28.98, 38.55) points, whereas no relevant change was observed after sham stimulation (36.43 [SD = 14.15, CI = 30.38, 42.48], average improvement: 0.5 [1.4%]). Repeated-measures analysis of variance (ANOVA) confirmed significance (main effect of time: F(1,20)=4.35, P < 0.05). Tukey's post hoc tests indicated MDS-UPDRS-III improvement after active stimulation (t [20] = 2.9, P = 0.03) but not after sham (t [20] = 0.42, P > 0.05). In a subset of patients that underwent DBS surgery later, their DBS response correlated with tDCS effects (R = 0.55, P(1) = 0.04).

CONCLUSION

Noninvasive, multifocal tDCS targeting a DBS-derived network significantly improved PD motor symptoms. Despite a small effect size, this study provides proof of principle for the successful noninvasive neuromodulation of an invasively identified network. Future studies should investigate repeated tDCS sessions and their utility for screening before DBS surgery. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Evaluating a motor progression connectivity model across Parkinson's disease stages

BACKGROUND

Stimulation of a specific site in the dorsolateral subthalamic nucleus (STN) was recently associated with slower motor progression in Parkinson's Disease (PD), based on the deep brain stimulation (DBS) in early-stage PD pilot clinical trial. Here, subject-level visualizations are presented of this early-stage PD dataset to further describe the relationship between active contacts and motor progression. This study also evaluates whether stimulation of the sweet spot and connectivity model associated with slower motor progression is also associated with improvements in long-term motor outcomes in patients with advanced-stage PD.

METHODS

Active contacts of the early-stage PD cohort (N = 14) were analyzed alongside the degree of two-year motor progression. Sweet spot and connectivity models derived from the early-stage PD cohort were then used to determine how well they can estimate the variance in long-term motor outcomes in an independent STN-DBS cohort of advanced-stage PD patients (N = 29).

RESULTS

In early-stage PD, proximity of stimulation to the dorsolateral STN was associated with slower motor progression. In advanced-stage PD, stimulation proximity to the early PD connectivity model and sweet spot were associated with better long-term motor outcomes (R = 0.60, P < 0.001; R = 0.37, P = 0.046, respectively).

CONCLUSIONS

Results suggest stimulation of a specific site in the dorsolateral STN is associated with both slower motor progression and long-term motor improvements in PD.

A human brain network linked to restoration of consciousness after deep brain stimulation

Disorders of consciousness (DoC) are states of impaired arousal or awareness. Deep brain stimulation (DBS) is a potential treatment, but outcomes vary, possibly due to differences in patient characteristics, electrode placement, or stimulation of specific brain networks. We studied 40 patients with DoC who underwent DBS targeting the thalamic centromedian-parafascicular complex. Better-preserved gray matter, especially in the striatum, correlated with consciousness improvement. Stimulation was most effective when electric fields extended into parafascicular and subparafascicular nuclei-ventral to the centromedian nucleus, near the midbrain-and when it engaged projection pathways of the ascending arousal network, including the hypothalamus, brainstem, and frontal lobe. Moreover, effective DBS sites were connected to networks similar to those underlying impaired consciousness due to generalized absence seizures and acquired lesions. These findings support the therapeutic potential of DBS for DoC, emphasizing the importance of precise targeting and revealing a broader link between effective DoC treatment and mechanisms underlying other conscciousness-impairing conditions.

Neurometabolic topography and associations with cognition in Alzheimer's disease: A whole-brain high-resolution 3D MRSI study

INTRODUCTION

Altered neurometabolism, detectable via proton magnetic resonance spectroscopic imaging (1H-MRSI), is spatially heterogeneous and underpins cognitive impairments in Alzheimer's disease (AD). However, the spatial relationships between neurometabolic topography and cognitive impairment in AD remain unexplored due to technical limitations.

METHODS

We used a novel whole-brain high-resolution 1H-MRSI technique, with simultaneously acquired 18F-florbetapir positron emission tomography (PET) imaging, to investigate the relationship between neurometabolic topography and cognitive functions in 117 participants, including 22 prodromal AD, 51 AD dementia, and 44 controls.

RESULTS

Prodromal AD and AD dementia patients exhibited spatially distinct reductions in N-acetylaspartate, and increases in myo-inositol. Reduced N-acetylaspartate and increased myo-inositol were associated with worse global cognitive performance, and N-acetylaspartate correlated with five specific cognitive scores. Neurometabolic topography provides biological insights into diverse cognitive dysfunctions.

DISCUSSION

Whole-brain high-resolution 1H-MRSI revealed spatially distinct neurometabolic topographies associated with cognitive decline in AD, suggesting potential for noninvasive brain metabolic imaging to track AD progression.

HIGHLIGHTS

Whole-brain high-resolution 1H-MRSI unveils neurometabolic topography in AD. Spatially distinct reductions in NAA, and increases in mI, are demonstrated. NAA and mI topography correlates with global cognitive performance. NAA topography correlates with specific cognitive performance.

One side effect: two networks? Lateral and posteromedial stimulation spreads induce dysarthria in subthalamic deep brain stimulation for Parkinson's disease

BACKGROUND

Stimulation-induced dysarthria (SID) is a troublesome and potentially therapy-limiting side effect of deep brain stimulation of the subthalamic nucleus (STN-DBS) in patients with Parkinson's disease (PD). To date, the origin of SID, and especially whether there is an involvement of cerebellar pathways as well as the pyramidal tract, remains a matter of debate. Therefore, this study aims to shed light on structural networks associated with SID and to derive a data-driven model to predict SID in patients with PD and STN-DBS.

METHODS

Randomised, double-blinded monopolar reviews determining SID thresholds were conducted in 25 patients with PD and STN-DBS. A fibre-based mapping approach, implementing the calculation of fibr-wise ORs for SID, was employed to identify the distributional pattern of SID in the STN's vicinity. The ability of the data-driven model to classify stimulation volumes as 'causing SID' or 'not causing SID' was validated by calculating receiver operating characteristics (ROC) in an independent out-of-sample cohort comprising 14 patients with PD and STN-DBS.

RESULTS

Local fibre-based stimulation maps showed an involvement of fibres running lateral and posteromedial to the STN in the pathogenesis of SID, independent of the investigated hemisphere. ROC analysis in the independent out-of-sample cohort resulted in a good fit of the data-driven model for both hemispheres (area under the curve (AUC)left=0.88, AUCright=0.88).

CONCLUSIONS

This study reveals an involvement of both, cerebello-thalamic fibres, as well as the pyramidal tract, in the pathogenesis of SID in STN-DBS. The results may impact future postoperative programming strategies to avoid SID in patients with PD and STN-DBS TRIAL REGISTRATION NUMBER: DRKS00023221; German Clinical Trials Register (DRKS) Number.

BLA-involved circuits in neuropsychiatric disorders

The basolateral amygdala (BLA) is the subregion of the amygdala located in the medial of the temporal lobe, which is connected with a wide range of brain regions to achieve diverse functions. Recently, an increasing number of studies have focused on the participation of the BLA in many neuropsychiatric disorders from the neural circuit perspective, aided by the rapid development of viral tracing methods and increasingly specific neural modulation technologies. However, how to translate this circuit-level preclinical intervention into clinical treatment using noninvasive or minor invasive manipulations to benefit patients struggling with neuropsychiatric disorders is still an inevitable question to be considered. In this review, we summarized the role of BLA-involved circuits in neuropsychiatric disorders including Alzheimer's disease, perioperative neurocognitive disorders, schizophrenia, anxiety disorders, depressive disorders, posttraumatic stress disorders, autism spectrum disorders, and pain-associative affective states and cognitive dysfunctions. Additionally, we provide insights into future directions and challenges for clinical translation.

Deep Brain Stimulation for Obsessive-Compulsive Disorder: Optimal Stimulation Sites

BACKGROUND

Deep brain stimulation (DBS) is a promising treatment option for treatment-refractory obsessive-compulsive disorder (OCD). Several stimulation targets have been used, mostly in and around the anterior limb of the internal capsule and ventral striatum. However, the precise target within this region remains a matter of debate.

METHODS

Here, we retrospectively studied a multicenter cohort of 82 patients with OCD who underwent DBS of the ventral capsule/ventral striatum and mapped optimal stimulation sites in this region.

RESULTS

DBS sweet-spot mapping performed on a discovery set of 58 patients revealed 2 optimal stimulation sites associated with improvements on the Yale-Brown Obsessive Compulsive Scale, one in the anterior limb of the internal capsule that overlapped with a previously identified OCD-DBS response tract and one in the region of the inferior thalamic peduncle and bed nucleus of the stria terminalis. Critically, the nucleus accumbens proper and anterior commissure were associated with beneficial but suboptimal clinical improvements. Moreover, overlap with the resulting sweet- and sour-spots significantly estimated variance in outcomes in an independent cohort of 22 patients from 2 additional DBS centers. Finally, beyond obsessive-compulsive symptoms, stimulation of the anterior site was associated with optimal outcomes for both depression and anxiety, while the posterior site was only associated with improvements in depression.

CONCLUSIONS

Our results suggest how to refine targeting of DBS in OCD and may be helpful in guiding DBS programming in existing patients.

Deep brain stimulation induces white matter remodeling and functional changes to brain-wide networks

Deep brain stimulation (DBS) is an emerging therapeutic option for treatment resistant neurological and psychiatric disorders, most notably depression. Despite this, little is known about the anatomical and functional mechanisms that underlie this therapy. Here we targeted stimulation to the white matter adjacent to the subcallosal anterior cingulate cortex (SCC-DBS) in macaques, modeling the location in the brain proven effective for depression. We demonstrate that SCC-DBS has a selective effect on white matter macro- and micro-structure in the cingulum bundle distant to where stimulation was delivered. SCC-DBS also decreased functional connectivity between subcallosal and posterior cingulate cortex, two areas linked by the cingulum bundle and implicated in depression. Our data reveal that white matter remodeling as well as functional effects contribute to DBS's therapeutic efficacy.

Multi-shell diffusion MRI of the fornix as a biomarker for cognition in Alzheimer's disease

BACKGROUND AND PURPOSE

A substantial fraction of those who had Alzheimer's Disease (AD) pathology on autopsy did not have dementia in life. While biomarkers for AD pathology are well-developed, biomarkers specific to cognitive domains affected by early AD are lagging. Diffusion MRI (dMRI) of the fornix is a candidate biomarker for early AD-related cognitive changes but is susceptible to bias due to partial volume averaging (PVA) with cerebrospinal fluid. The purpose of this work is to leverage multi-shell dMRI to correct for PVA and to evaluate PVA-corrected dMRI measures in fornix as a biomarker for cognition in AD.

METHODS

Thirty-three participants in the Cleveland Alzheimer's Disease Research Center (CADRC) (19 with normal cognition (NC), 10 with mild cognitive impairment (MCI), 4 with dementia due to AD) were enrolled in this study. Multi-shell dMRI was acquired, and voxelwise fits were performed with two models: 1) diffusion tensor imaging (DTI) that was corrected for PVA and 2) neurite orientation dispersion and density imaging (NODDI). Values of tissue integrity in fornix were correlated with neuropsychological scores taken from the Uniform Data Set (UDS), including the UDS Global Composite 5 score (UDSGC5).

RESULTS

Statistically significant correlations were found between the UDSGC5 and PVA-corrected measure of mean diffusivity (MDc, r = -0.35, p < 0.05) from DTI and the intracelluar volume fraction (ficvf, r = 0.37, p < 0.04) from NODDI. A sensitivity analysis showed that the relationship to MDc was driven by episodic memory, which is often affected early in AD, and language.

CONCLUSION

This cross-sectional study suggests that multi-shell dMRI of the fornix that has been corrected for PVA is a potential biomarker for early cognitive domain changes in AD. A longitudinal study will be necessary to determine if the imaging measure can predict cognitive decline.

Engaging dystonia networks with subthalamic stimulation

Deep brain stimulation is a viable and efficacious treatment option for dystonia. While the internal pallidum serves as the primary target, more recently, stimulation of the subthalamic nucleus (STN) has been investigated. However, optimal targeting within this structure and its complex surroundings have not been studied in depth. Indeed, multiple historical targets that have been used for surgical treatment of dystonia are directly adjacent to the STN. Further, multiple types of dystonia exist, and outcomes are variable, suggesting that not all types would profit maximally from the exact same target. Therefore, a thorough investigation of the neural substrates underlying effects on dystonia symptoms is warranted. Here, we analyze a multi-center cohort of isolated dystonia patients with subthalamic implantations (N = 58) and relate their stimulation sites to improvement of appendicular and cervical symptoms as well as blepharospasm. Stimulation of the ventral oral posterior nucleus of thalamus and surrounding regions was associated with improvement in cervical dystonia, while stimulation of the dorsolateral STN was associated with improvement in limb dystonia and blepharospasm. This dissociation was also evident for structural connectivity, where the cerebellothalamic, corticospinal and pallidosubthalamic tracts were associated with improvement of cervical dystonia, while hyperdirect and subthalamopallidal pathways were associated with alleviation of limb dystonia and blepharospasm. Importantly, a single well-placed electrode may reach the three optimal target sites. On the level of functional networks, improvement of limb dystonia was correlated with connectivity to the corresponding somatotopic regions in primary motor cortex, while alleviation of cervical dystonia was correlated with connectivity to the recently described 'action-mode' network that involves supplementary motor and premotor cortex. Our findings suggest that different types of dystonia symptoms are modulated via distinct networks. Namely, appendicular dystonia and blepharospasm are improved with modulation of the basal ganglia, and, in particular, the subthalamic circuitry, including projections from the primary motor cortex. In contrast, cervical dystonia was more responsive when engaging the cerebello-thalamo-cortical circuit, including direct stimulation of ventral thalamic nuclei. These findings may inform DBS targeting and image-based programming strategies for patient-specific treatment of dystonia.

Targeting papez circuit for cognitive dysfunction- insights into deep brain stimulation for Alzheimer's disease

Hippocampus is the most widely studied brain area coupled with impairment of memory in a variety of neurological diseases and Alzheimer's disease (AD). The limbic structures within the Papez circuit have been linked to various aspects of cognition. Unfortunately, the brain regions that include this memory circuit are often ignored in terms of understanding cognitive decline in these diseases. To properly comprehend where cognition problems originate, it is crucial to clarify any aberrant contributions from all components of a specific circuit -on both a local and a global level. The pharmacological treatments currently available are not long lasting. Deep Brain Stimulation (DBS) emerged as a new powerful therapeutic approach for alleviation of the cognitive dysfunctions. Metabolic, functional, electrophysiological, and imaging studies helped to find out the crucial nodes that can be accessible for DBS. Targeting these nodes within the memory circuit produced significant improvement in learning and memory by disrupting abnormal circuit activity and restoring the physiological network. Here, we provide an overview of the neuroanatomy of the circuit of Papez along with the mechanisms and various deep brain stimulation targets of the circuit structures which could be significant for improving cognitive dysfunctions in AD.

U-shaped convolutional transformer GAN with multi-resolution consistency loss for restoring brain functional time-series and dementia diagnosis

Introduction

The blood oxygen level-dependent (BOLD) signal derived from functional neuroimaging is commonly used in brain network analysis and dementia diagnosis. Missing the BOLD signal may lead to bad performance and misinterpretation of findings when analyzing neurological disease. Few studies have focused on the restoration of brain functional time-series data.

Methods

In this paper, a novel U-shaped convolutional transformer GAN (UCT-GAN) model is proposed to restore the missing brain functional time-series data. The proposed model leverages the power of generative adversarial networks (GANs) while incorporating a U-shaped architecture to effectively capture hierarchical features in the restoration process. Besides, the multi-level temporal-correlated attention and the convolutional sampling in the transformer-based generator are devised to capture the global and local temporal features for the missing time series and associate their long-range relationship with the other brain regions. Furthermore, by introducing multi-resolution consistency loss, the proposed model can promote the learning of diverse temporal patterns and maintain consistency across different temporal resolutions, thus effectively restoring complex brain functional dynamics.

Results

We theoretically tested our model on the public Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and our experiments demonstrate that the proposed model outperforms existing methods in terms of both quantitative metrics and qualitative assessments. The model's ability to preserve the underlying topological structure of the brain functional networks during restoration is a particularly notable achievement.

Conclusion

Overall, the proposed model offers a promising solution for restoring brain functional time-series and contributes to the advancement of neuroscience research by providing enhanced tools for disease analysis and interpretation.

Electrocardiographic approach strategies in patients with Parkinson disease treated with deep brain stimulation

Deep brain stimulation (DBS) is an interdisciplinary and reversible therapy that uses high-frequency electrical stimulation to correct aberrant neural pathways in motor and cognitive neurological disorders. However, the high frequency of the waves used in DBS can interfere with electrical recording devices (e.g., electrocardiogram, electroencephalogram, cardiac monitor), creating artifacts that hinder their interpretation. The compatibility of DBS with these devices varies and depends on factors such as the underlying disease and the configuration of the neurostimulator. In emergencies where obtaining an electrocardiogram is crucial, the need for more consensus on reducing electrical artifacts in patients with DBS becomes a significant challenge. Various strategies have been proposed to attenuate the artifact generated by DBS, such as changing the DBS configuration from monopolar to bipolar, temporarily deactivating DBS during electrocardiographic recording, applying frequency filters both lower and higher than those used by DBS, and using non-standard leads. However, the inexperience of medical personnel, variability in DBS models, or the lack of a controller at the time of approach limit the application of these strategies. Current evidence on their reproducibility and efficacy is limited. Due to the growing elderly population and the rising utilization of DBS, it is imperative to create electrocardiographic methods that are easily accessible and reproducible for general physicians and emergency services.

The subcortical default mode network and Alzheimer's disease: a systematic review and meta-analysis

The default mode network is a central cortical brain network suggested to play a major role in several disorders and to be particularly vulnerable to the neuropathological hallmarks of Alzheimer's disease. Subcortical involvement in the default mode network and its alteration in Alzheimer's disease remains largely unknown. We performed a systematic review, meta-analysis and empirical validation of the subcortical default mode network in healthy adults, combined with a systematic review, meta-analysis and network analysis of the involvement of subcortical default mode areas in Alzheimer's disease. Our results show that, besides the well-known cortical default mode network brain regions, the default mode network consistently includes subcortical regions, namely the thalamus, lobule and vermis IX and right Crus I/II of the cerebellum and the amygdala. Network analysis also suggests the involvement of the caudate nucleus. In Alzheimer's disease, we observed a left-lateralized cluster of decrease in functional connectivity which covered the medial temporal lobe and amygdala and showed overlap with the default mode network in a portion covering parts of the left anterior hippocampus and left amygdala. We also found an increase in functional connectivity in the right anterior insula. These results confirm the consistency of subcortical contributions to the default mode network in healthy adults and highlight the relevance of the subcortical default mode network alteration in Alzheimer's disease.

Romer-EPTI: rotating-view motion-robust super-resolution EPTI for SNR-efficient distortion-free in-vivo mesoscale dMRI and microstructure imaging

Purpose

To overcome the major challenges in dMRI acquisition, including low SNR, distortion/blurring, and motion vulnerability.

Methods

A novel Romer-EPTI technique is developed to provide distortion-free dMRI with significant SNR gain, high motion-robustness, sharp spatial resolution, and simultaneous multi-TE imaging. It introduces a ROtating-view Motion-robust supEr-Resolution technique (Romer) combined with a distortion/blurring-free EPTI encoding. Romer enhances SNR by a simultaneous multi-thick-slice acquisition with rotating-view encoding, while providing high motion-robustness through a motion-aware super-resolution reconstruction, which also incorporates slice-profile and real-value diffusion, to resolve high-isotropic-resolution volumes. The in-plane encoding is performed using distortion/blurring-free EPTI, which further improves effective spatial resolution and motion robustness by preventing not only T2/T2*-blurring but also additional blurring resulting from combining encoded volumes with inconsistent geometries caused by dynamic distortions. Self-navigation was incorporated to enable efficient phase correction. Additional developments include strategies to address slab-boundary artifacts, achieve minimal TE for SNR gain at 7T, and achieve high robustness to strong phase variations at high b-values.

Results

Using Romer-EPTI, we demonstrate distortion-free whole-brain mesoscale in-vivo dMRI at both 3T (500-μm-iso) and 7T (485-μm-iso) for the first time, with high SNR efficiency (e.g., 25 × ), and high image quality free from distortion and slab-boundary artifacts with minimal blurring. Motion experiments demonstrate Romer-EPTI's high motion-robustness and ability to recover sharp images in the presence of motion. Romer-EPTI also demonstrates significant SNR gain and robustness in high b-value (b=5000s/mm2) and time-dependent dMRI.

Conclusion

Romer-EPTI significantly improves SNR, motion-robustness, and image quality, providing a highly efficient acquisition for high-resolution dMRI and microstructure imaging.

Biophysical Principles and Computational Modeling of Deep Brain Stimulation

BACKGROUND

Deep brain stimulation (DBS) has revolutionized the treatment of neurological disorders, yet the mechanisms of DBS are still under investigation. Computational models are important in silico tools for elucidating these underlying principles and potentially for personalizing DBS therapy to individual patients. The basic principles underlying neurostimulation computational models, however, are not well known in the clinical neuromodulation community.

OBJECTIVE

In this study, we present a tutorial on the derivation of computational models of DBS and outline the biophysical contributions of electrodes, stimulation parameters, and tissue substrates to the effects of DBS.

RESULTS

Given that many aspects of DBS are difficult to characterize experimentally, computational models have played an important role in understanding how material, size, shape, and contact segmentation influence device biocompatibility, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Neural activation is dictated by stimulation parameters including frequency, current vs voltage control, amplitude, pulse width, polarity configurations, and waveform. These parameters also affect the potential for tissue damage, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Activation of the neural substrate also is influenced by the encapsulation layer surrounding the electrode, the conductivity of the surrounding tissue, and the size and orientation of white matter fibers. These properties modulate the effects of the electric field and determine the ultimate therapeutic response.

CONCLUSION

This article describes biophysical principles that are useful for understanding the mechanisms of neurostimulation.

A Multiscale Closed-Loop Neurotoxicity Model of Alzheimer's Disease Progression Explains Functional Connectivity Alterations

The accumulation of amyloid-β (Aβ) and hyperphosphorylated-tau (hp-tau) are two classical histopathological biomarkers in Alzheimer's disease (AD). However, their detailed interactions with the electrophysiological changes at the meso- and macroscale are not yet fully understood. We developed a mechanistic multiscale model of AD progression, linking proteinopathy to its effects on neural activity and vice-versa. We integrated a heterodimer model of prion-like protein propagation and a brain network model of Jansen-Rit neural masses derived from human neuroimaging data whose parameters varied due to neurotoxicity. Results showed that changes in inhibition guided the electrophysiological alterations found in AD, and these changes were mainly attributed to Aβ effects. Additionally, we found a causal disconnection between cellular hyperactivity and interregional hypersynchrony contrary to previous beliefs. Finally, we demonstrated that early Aβ and hp-tau depositions' location determine the spatiotemporal profile of the proteinopathy. The presented model combines the molecular effects of both Aβ and hp-tau together with a mechanistic protein propagation model and network effects within a closed-loop model. This holds the potential to enlighten the interplay between AD mechanisms on various scales, aiming to develop and test novel hypotheses on the contribution of different AD-related variables to the disease evolution.

Deep brain stimulation for Alzheimer's disease - current status and next steps

INTRODUCTION

Alzheimer's disease (AD) requires novel therapeutic approaches due to limited efficacy of current treatments.

AREAS COVERED

This article explores AD as a manifestation of neurocircuit dysfunction and evaluates deep brain stimulation (DBS) as a potential intervention. Focusing on fornix-targeted stimulation (DBS-f), the article summarizes safety, feasibility, and outcomes observed in phase 1/2 trials, highlighting findings such as cognitive improvement, increased metabolism, and hippocampal growth. Topics for further study include optimization of electrode placement, and the role of stimulation-induced autobiographical-recall. Nucleus basalis of Meynert (DBS-NBM) DBS is also discussed and compared with DBS-f. Challenges with both DBS-f and DBS-NBM are identified, emphasizing the need for further research on optimal stimulation parameters. The article also reviews alternative DBS targets, including medial temporal lobe structures and the ventral capsule/ventral striatum.

EXPERT OPINION

Looking ahead, a phase-3 DBS-f trial, and the prospect of closed-loop stimulation using EEG-derived biomarkers or hippocampal theta activity are highlighted. Recent FDA-approved therapies and other neuromodulation techniques like temporal interference and low-intensity ultrasound are considered. The article concludes by underscoring the importance of imaging-based diagnosis and staging to allow for circuit-targeted therapies, given the heterogeneity of AD and varied stages of neurocircuit dysfunction.

Concept for intrathecal delivery of brain recording and stimulation device

Neurological disorders are common, yet many neurological diseases don't have efficacious treatments. The protected nature of the brain both anatomically and physiologically through the blood brain barrier (BBB) make it exceptionally hard to access. Recent advancements in interventional approaches, like the Stentrode™, have opened the possibility of using the cerebral vasculature as a highway for minimally invasive therapeutic delivery to the brain. Despite the immense success that the Stentrode™ has faced recently, it is limited to major cerebral vasculature and exists outside the BBB, making drug eluting configurations largely ineffective. The present study seeks to identify a separate anatomical pathway for therapeutic delivery to the deep brain using the ventricular system. The intrathecal route, in which drug pumps and spinal cord stimulators are delivered through a lumbar puncture, is a well-established route for delivering therapies to the spinal cord as high as C1. The present study identifies an extension of this anatomical pathway through the foramen of Magendie and into the brains ventricular system. To test this pathway, a narrow self-expanding electrical recording device was manufactured and its potential to navigate the ventricular system was assessed on human anatomical brain samples. While the results of this paper are largely preliminary and a substantial amount of safety and efficacy data is needed, this paper identifies an important anatomical pathway for delivery of therapeutic and diagnostics tools to the brain that is minimally invasive, can access limbic structures, and is within the BBB.

Changes in myelinated nerve fibers induced by pulsed electrical stimulation: A microstructural perspective on the causes of electrical stimulation side effects

Electrical brain stimulation technology is widely used in the clinic to treat brain neurological disorders. However, during treatment, patients may experience side effects such as pain, poor limb coordination, and skin rash. Previous reports have focused on the brilliant chapter on electrical brain stimulation technology and have not paid attention to patients' suffering caused by side effects during treatment. In this study, electrodes were arranged on the medulla oblongata. Pulsed electric fields of different frequencies were used to perform electrical stimulation to study the impact of electric fields on myelinated nerve fibers and reveal the possible microstructural origin of side effects. Transmission electron microscopy was used to analyze and quantify the changes in microstructure. The results illustrated that myelinated nerve fibers underwent atrophy under pulsed electric fields, with the mildest degree of atrophy under high-frequency (400 Hz) electric fields. Myelin sheaths experienced plate separation under pulsed electric fields, and a distinct laminar structure appeared. The microstructure changes may be related to the side effects of clinical electrical stimulation. This study can provide pathological possibilities for exploring the causes of the side effects of electrical stimulation and supply guidance for selecting electrical parameters for clinical electrical stimulation therapy from a distinctive perspective.

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.

WarpDrive: Improving spatial normalization using manual refinements

Spatial normalization-the process of mapping subject brain images to an average template brain-has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & modalities. While overall successful, sometimes, this automatic process yields suboptimal results, especially when dealing with brains with extensive neurodegeneration and atrophy patterns, or when high accuracy in specific regions is needed. Here we introduce WarpDrive, a novel tool for manual refinements of image alignment after automated registration. We show that the tool applied in a cohort of patients with Alzheimer's disease who underwent deep brain stimulation surgery helps create more accurate representations of the data as well as meaningful models to explain patient outcomes. The tool is built to handle any type of 3D imaging data, also allowing refinements in high-resolution imaging, including histology and multiple modalities to precisely aggregate multiple data sources together.

Artificial sharp-wave-ripples to support memory and counter neurodegeneration

Information processed in our sensory neocortical areas is transported to the hippocampus during memory encoding, and between hippocampus and neocortex during memory consolidation, and retrieval. Short bursts of high-frequency oscillations, so called sharp-wave-ripples, have been proposed as a potential mechanism for this information transfer: They can synchronize neural activity to support the formation of local neural networks to store information, and between distant cortical sites to act as a bridge to transfer information between sensory cortical areas and hippocampus. In neurodegenerative diseases like Alzheimer's Disease, different neuropathological processes impair normal neural functioning and neural synchronization as well as sharp-wave-ripples, which impairs consolidation and retrieval of information, and compromises memory. Here, we formulate a new hypothesis, that artificially inducing sharp-wave-ripples with noninvasive high-frequency visual stimulation could potentially support memory functioning, as well as target the neuropathological processes underlying neurodegenerative diseases. We also outline key challenges for empirical tests of the hypothesis.

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links

In recent years, deep learning approaches have gained significant attention in predicting brain disorders using neuroimaging data. However, conventional methods often rely on single-modality data and supervised models, which provide only a limited perspective of the intricacies of the highly complex brain. Moreover, the scarcity of accurate diagnostic labels in clinical settings hinders the applicability of the supervised models. To address these limitations, we propose a novel self-supervised framework for extracting multiple representations from multimodal neuroimaging data to enhance group inferences and enable analysis without resorting to labeled data during pre-training. Our approach leverages Deep InfoMax (DIM), a self-supervised methodology renowned for its efficacy in learning representations by estimating mutual information without the need for explicit labels. While DIM has shown promise in predicting brain disorders from single-modality MRI data, its potential for multimodal data remains untapped. This work extends DIM to multimodal neuroimaging data, allowing us to identify disorder-relevant brain regions and explore multimodal links. We present compelling evidence of the efficacy of our multimodal DIM analysis in uncovering disorder-relevant brain regions, including the hippocampus, caudate, insula, - and multimodal links with the thalamus, precuneus, and subthalamus hypothalamus. Our self-supervised representations demonstrate promising capabilities in predicting the presence of brain disorders across a spectrum of Alzheimer's phenotypes. Comparative evaluations against state-of-the-art unsupervised methods based on autoencoders, canonical correlation analysis, and supervised models highlight the superiority of our proposed method in achieving improved classification performance, capturing joint information, and interpretability capabilities. The computational efficiency of the decoder-free strategy enhances its practical utility, as it saves compute resources without compromising performance. This work offers a significant step forward in addressing the challenge of understanding multimodal links in complex brain disorders, with potential applications in neuroimaging research and clinical diagnosis.

Efficacy analysis of three brain stimulation techniques for Alzheimer's disease: a meta-analysis of repeated transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation

INTRODUCTION

This systematic review and meta-analysis study investigates the efficacy of repeated transcranial magnetic stimulation (rTMS), transcranial direct current stimulation (tDCS), and deep brain stimulation (DBS) using neuropsychological assessments as a potential treatment option for Alzheimer's disease (AD).

METHODS

PubMed, Embase, and the Cochrane Library were searched for studies on rTMS, tDCS, and DBS for the treatment of patients with AD between April 1970 and October 2022. The mini-Mental State Examination (MMSE) and AD Assessment Scale - Cognitive Subscale (ADAS-Cog) were adopted as the efficacy index.

RESULTS

The analysis yielded 17 eligible studies. rTMS greatly improved the cognition of patients with AD (immediate post-treatment WMD of MMSE score: 2.06, p < 0.00001; short-term follow-up WMD of MMSE score: 2.12, p = 0.006; WMD of ADAS-Cog score in single-arm studies: -4.97, p = 0.001). DBS did not reverse the progression of cognitive decline (WMD of ADAS-Cog score in single-arm studies: 7.40, p < 0.00001). Furthermore, tDCS demonstrated no significant efficacy in improving cognition in random clinical trials or single-arm studies.

CONCLUSION

rTMS is a promising non-medicinal alternative for cognitive improvement inpatients with AD.

If deprivation worsens dementia outcomes, stimulation should improve them

It is still not known what causes Alzheimer's Disease (AD). In this period of uncertainty, an emerging literature on risk factors suggests that the concept of "stimulation" is a useful pragmatic tool both before and after diagnosis to improve cognitive health. Before diagnosis of AD, stimulation of the brain through education, exercise, and social stimulation provides fortification against later cognitive decline. After diagnosis, specific electrical stimulation of brain circuits may protect cognitive function, and non-specific stimulation through different kinds of environmental enrichment may help to compensate for cognitive decline. Pragmatic guidelines are offered here to maximise enabling stimulation (physical, cognitive, and social activity) and minimise disabling stimulation across the lifetime (e.g. stress, pollution, and poor diet). However, much deeper structural changes in society are needed to struggle against socioeconomic and environmental deprivation and the inaccessibility of education for women across the globe.

Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight

Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.

Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation

BACKGROUND

Deep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome.

OBJECTIVE/HYPOTHESIS

We aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort.

METHODS

Volumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome ('discriminative' streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures.

RESULTS

PSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047).

CONCLUSION(S)

These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.

Publication Rates and Characteristics of Clinical Trials in Deep Brain and Responsive Neurostimulation

INTRODUCTION

Prompt dissemination of clinical trial results is essential for ensuring the safety and efficacy of intracranial neurostimulation treatments, including deep brain stimulation (DBS) and responsive neurostimulation (RNS). However, the frequency and completeness of results publication, and reasons for reporting delays, are unknown. Moreover, the patient populations, targeted anatomical locations, and stimulation parameters should be clearly reported for both reproducibility and to identify lacunae in trial design. Here, we examine DBS and RNS trials from 1997 to 2022, chart their characteristics, and examine rates and predictors of results reporting.

METHODS

Trials were identified using ClinicalTrials.gov. Associated publications were identified using ClinicalTrials.gov and PubMed.gov. Pearson's χ2 tests were used to assess differences in trial characteristics between published and unpublished trials.

RESULTS

Across 449 trials, representing a cumulative cohort of 42,769 patient interventions, there were 37 therapeutic indications and 44 stimulation targets. The most common indication and target were Parkinson's disease (40.55%) and the subthalamic nucleus (35.88%), respectively. Only 0.89% of trials were in pediatric patients (11.58% were mixed pediatric and adult). Explored targets represented 75% of potential basal ganglia targets but only 29% of potential thalamic targets. Allowing a 1-year grace period after trial completion, 34/169 (20.12%) had results reported on ClinicalTrials.gov, and 107/169 (63.31%) were published. ∼80% of published trials included details about stimulation parameters used. Published and unpublished trials did not significantly differ by trial characteristics.

CONCLUSION

We highlight key knowledge and performance gaps in DBS and RNS trial research. Over one-third of trials remain unpublished >1 year after completion; pediatric trials are scarce; most of the thalamus remains unexplored; about one-in-five trials fail to report stimulation parameters; and movement disorders comprise the most studied indications.

Alzheimer's Disease Treatment: The Search for a Breakthrough

As the search for modalities to cure Alzheimer's disease (AD) has made slow progress, research has now turned to innovative pathways involving neural and peripheral inflammation and neuro-regeneration. Widely used AD treatments provide only symptomatic relief without changing the disease course. The recently FDA-approved anti-amyloid drugs, aducanumab and lecanemab, have demonstrated unclear real-world efficacy with a substantial side effect profile. Interest is growing in targeting the early stages of AD before irreversible pathologic changes so that cognitive function and neuronal viability can be preserved. Neuroinflammation is a fundamental feature of AD that involves complex relationships among cerebral immune cells and pro-inflammatory cytokines, which could be altered pharmacologically by AD therapy. Here, we provide an overview of the manipulations attempted in pre-clinical experiments. These include inhibition of microglial receptors, attenuation of inflammation and enhancement of toxin-clearing autophagy. In addition, modulation of the microbiome-brain-gut axis, dietary changes, and increased mental and physical exercise are under evaluation as ways to optimize brain health. As the scientific and medical communities work together, new solutions may be on the horizon to slow or halt AD progression.

Innovative perspectives in limbic surgery using deep brain stimulation

Limbic surgery is one of the most attractive and retaken fields of functional neurosurgery in the last two decades. Psychiatric surgery emerged from the incipient work of Moniz and Lima lesioning the prefrontal cortex in agitated patients. Since the onset of stereotactic and functional neurosurgery with Spiegel and Wycis, the treatment of mental diseases gave attention to refractory illnesses mainly with the use of thalamotomies. Neurosis and some psychotic symptoms were treated by them. Several indications when lesioning the brain were included: obsessive-compulsive disorder, depression, and aggressiveness among others with a diversity of targets. The indiscriminately use of anatomical sites without enough scientific evidence, and uncertainly defined criteria for selecting patients merged with a deficiency in ethical aspects, brought a lack of procedures for a long time: only select clinics allowed this surgery around the world from 1950 to the 1990s. In 1999, Nuttin et al. began a new chapter in limbic surgery with the use of Deep Brain Stimulation, based on the experience of pain, Parkinson's disease, and epilepsy. The efforts were focused on different targets to treat depression and obsessive-compulsive disorders. Nevertheless, other diseases were added to use neuromodulation. The goal of this article is to show the new opportunities to treat neuropsychiatric diseases.

Insights and opportunities for deep brain stimulation as a brain circuit intervention

Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.