Transcranial pulse stimulation (TPS) improves depression in AD patients on state‐of‐the‐art treatment

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Abstract

Introduction

Ultrasound‐based brain stimulation is a novel, non‐invasive therapeutic approach to precisely target regions of interest. Data from a first clinical trial of patients with Alzheimer's disease (AD) receiving 2‐4 weeks transcranial pulse stimulation (TPS) have shown memory and cognitive improvements for up to 3 months, despite ongoing state‐of‐the‐art treatment. Importantly, depressive symptoms also improved.

Methods

We analyzed changes in Beck Depression Inventory (BDI‐II) and functional connectivity (FC) changes with functional magnetic resonance imaging in 18 AD patients.

Results

We found significant improvement in BDI‐II after TPS therapy. FC analysis showed a normalization of the FC between the salience network (right anterior insula) and the ventromedial network (left frontal orbital cortex).

Discussion

Stimulation of areas related to depression (including extended dorsolateral prefrontal cortex) appears to alleviate depressive symptoms and induces FC changes in AD patients. TPS may be a novel add‐on therapy for depression in AD and as a neuropsychiatric diagnosis.

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Most cited references 17

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Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks.

Susan Whitfield-Gabrieli, Alfonso Nieto-Castañón (2012)

Resting state functional connectivity reveals intrinsic, spontaneous networks that elucidate the functional architecture of the human brain. However, valid statistical analysis used to identify such networks must address sources of noise in order to avoid possible confounds such as spurious correlations based on non-neuronal sources. We have developed a functional connectivity toolbox Conn ( www.nitrc.org/projects/conn ) that implements the component-based noise correction method (CompCor) strategy for physiological and other noise source reduction, additional removal of movement, and temporal covariates, temporal filtering and windowing of the residual blood oxygen level-dependent (BOLD) contrast signal, first-level estimation of multiple standard functional connectivity magnetic resonance imaging (fcMRI) measures, and second-level random-effect analysis for resting state as well as task-related data. Compared to methods that rely on global signal regression, the CompCor noise reduction method allows for interpretation of anticorrelations as there is no regression of the global signal. The toolbox implements fcMRI measures, such as estimation of seed-to-voxel and region of interest (ROI)-to-ROI functional correlations, as well as semipartial correlation and bivariate/multivariate regression analysis for multiple ROI sources, graph theoretical analysis, and novel voxel-to-voxel analysis of functional connectivity. We describe the methods implemented in the Conn toolbox for the analysis of fcMRI data, together with examples of use and interscan reliability estimates of all the implemented fcMRI measures. The results indicate that the CompCor method increases the sensitivity and selectivity of fcMRI analysis, and show a high degree of interscan reliability for many fcMRI measures.

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A component based noise correction method (CompCor) for BOLD and perfusion based fMRI.

Yashar Behzadi, Khaled Restom, Joy Liau … (2007)

A component based method (CompCor) for the reduction of noise in both blood oxygenation level-dependent (BOLD) and perfusion-based functional magnetic resonance imaging (fMRI) data is presented. In the proposed method, significant principal components are derived from noise regions-of-interest (ROI) in which the time series data are unlikely to be modulated by neural activity. These components are then included as nuisance parameters within general linear models for BOLD and perfusion-based fMRI time series data. Two approaches for the determination of the noise ROI are considered. The first method uses high-resolution anatomical data to define a region of interest composed primarily of white matter and cerebrospinal fluid, while the second method defines a region based upon the temporal standard deviation of the time series data. With the application of CompCor, the temporal standard deviation of resting-state perfusion and BOLD data in gray matter regions was significantly reduced as compared to either no correction or the application of a previously described retrospective image based correction scheme (RETROICOR). For both functional perfusion and BOLD data, the application of CompCor significantly increased the number of activated voxels as compared to no correction. In addition, for functional BOLD data, there were significantly more activated voxels detected with CompCor as compared to RETROICOR. In comparison to RETROICOR, CompCor has the advantage of not requiring external monitoring of physiological fluctuations.

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Large-scale automated synthesis of human functional neuroimaging data

Tal Yarkoni, Russell Poldrack, Thomas Nichols … (2011)

The explosive growth of the human neuroimaging literature has led to major advances in understanding of human brain function, but has also made aggregation and synthesis of neuroimaging findings increasingly difficult. Here we describe and validate an automated brain mapping framework that uses text mining, meta-analysis and machine learning techniques to generate a large database of mappings between neural and cognitive states. We demonstrate the capacity of our approach to automatically conduct large-scale, high-quality neuroimaging meta-analyses, address long-standing inferential problems in the neuroimaging literature, and support accurate ‘decoding’ of broad cognitive states from brain activity in both entire studies and individual human subjects. Collectively, our results validate a powerful and generative framework for synthesizing human neuroimaging data on an unprecedented scale.

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Author and article information

Contributors

Roland Beisteiner: roland.beisteiner@meduniwien.ac.at

Journal

Journal ID (nlm-ta): Alzheimers Dement (N Y)

Journal ID (iso-abbrev): Alzheimers Dement (N Y)

Journal ID (doi): 10.1002/(ISSN)2352-8737

Journal ID (publisher-id): TRC2

Title: Alzheimer's & Dementia : Translational Research & Clinical Interventions

Publisher: John Wiley and Sons Inc. (Hoboken )

ISSN (Electronic): 2352-8737

Publication date (Electronic): 10 February 2022

Publication date Collection: 2022

Volume: 8

Issue: 1 ( doiID: 10.1002/trc2.v8.1 )

Electronic Location Identifier: e12245

Affiliations

[ ¹ ] Department of Neurology Medical University of Vienna Vienna Austria

Author notes

[*] [* ] Correspondence

Roland Beisteiner, Department of Neurology, Medical University of Vienna, Spitalgasse 23, A‐1090 Vienna, Austria.

Email: roland.beisteiner@ 123456meduniwien.ac.at

Author information

Eva Matt https://orcid.org/0000-0003-2343-2191

Article

Publisher ID: TRC212245

DOI: 10.1002/trc2.12245

PMC ID: 8829892

PubMed ID: 35169611

SO-VID: 975b3234-c797-4cc5-87e3-4403b979ca15

License:

This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

History

Date revision received : 29 November 2021

Date received : 01 October 2021

Date accepted : 15 December 2021

Page count

Figures: 2, Tables: 0, Pages: 5, Words: 2796

Funding

Funded by: Medical University of Vienna and University of Vienna

Award ID: SO10300020

Funded by: STORZ Medical

Funded by: Austrian Science Fund , doi 10.13039/501100002428;

Award ID: KLIF455

Custom metadata

source-schema-version-number 2.0

cover-date 2022

details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.1 mode:remove_FC converted:10.02.2022

Keywords: alzheimer's disease,brain stimulation,depression,functional connectivity,functional magnetic resonance imaging,transcranial pulse stimulation,ultrasound

Data availability:

Keywords: alzheimer's disease, brain stimulation, depression, functional connectivity, functional magnetic resonance imaging, transcranial pulse stimulation, ultrasound

Transcranial pulse stimulation (TPS) improves depression in AD patients on state‐of‐the‐art treatment

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Abstract

Introduction

Methods

Results

Discussion

Related collections

Alternative approaches to Alzheimer's Disease

Most cited references 17

Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks.

A component based noise correction method (CompCor) for BOLD and perfusion based fMRI.

Large-scale automated synthesis of human functional neuroimaging data

Author and article information

Contributors

Journal

Affiliations

Author notes

Author information

Article

History

Page count

Funding

Categories

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