FEIT Research Project Database

Transcranial magnetic brain stimulation for depression


Project Leader: Andrew Zalesky
Staff: Dr Robin Cash
Collaborators: Dr Luca Cocchi (QIMR)
Primary Contact: Andrew Zalesky (azalesky@unimelb.edu.au)
Keywords: neural engineering; neuroengineering; neuroimaging
Disciplines: Biomedical Engineering,Electrical & Electronic Engineering
Domains:

Develop innovative brain stimulation therapies for depression and other psychiatric disorders based on new knowledge of aberrant brain circuits and systems.

While many individuals with mental health conditions respond to medication, other individuals do not or find the side-effects intolerable. For these individuals, therapeutic brain stimulation can potentially be life-changing. Brain stimulation (Transcranial Magnetic Stimulation) can be used to target and modify specific brain circuits that are abnormal in mental health disorders in order to bring about clinical improvements. Brain stimulation is a gentle non-invasive approach that can gradually alleviate symptoms over the course of 4-6 weeks of daily treatment.

However, while brain stimulation is effective for some individuals, not all will benefit. Our group focusses on establishing a better understanding the relations between specific brain circuits and clinical symptoms and on translating these findings to the clinic to more effectively treat mental health conditions.

Our work has helped to delineate brain circuits and regions that are critical to the effective treatment of Major Depressive Disorder (MDD). We have developed new computational methodology that enables these circuits to be accurately targeted by therapeutic brain stimulation. And because no two individuals are the same, and no two brains are identical (not even for twins, we checked), we have developed new techniques which enable personalised optimal stimulation targets to be precisely located based on an individual’s brain network architecture. Our research to date indicates that this specific approach provides the capacity to improve clinical treatment outcomes.

Other things that we have focussed on is reducing the cost of depression treatment by developing accelerated (faster) protocols that demonstrate equivalent clinical efficacy. These protocols include a number of adjustments that enable the same number of pulses to be delivered in a fraction of the time. This accelerated approach requires as little as 3 minutes rather than the typical 25+ minutes of stimulation has shown equivalent clinical efficacy in MDD and in stroke rehabilitation.

Given that it can take several weeks of treatment to establish who will and will not respond to therapeutic brain stimulation, we have also developed methodology to assist in predicting treatment response. This approach utilises patterns of brain communication to identify responders and non-responders to treatment. This can potentially spare individuals the time and expense of treatment.

Further research and key questions

  • Expanding personalised treatment to other psychiatric disorders based on disease-relevant brain circuits
  • Implementation of personalised brain stimulation in the clinic
  • Investigations of the response of specific brain circuits and symptoms to brain stimulation

Further reading: reviews

Further reading: papers

  • Cash et al. Biological Psychiatry. 2019. Subgenual Functional Connectivity Predicts Antidepressant Treatment Response to TMS: Independent Validation and Evaluation of Personalization. This paper provides strong evidence on the relation between brain connectivity and TMS antidepressant response.
  • Cash et al. Human Brain Mapping. 2020. Personalized connectivity-guided DLPFC-TMS for depression: advancing computational feasibility, precision and reproducibility. We provide the first demonstration, validated across 1000 adults, that brain connectivity-based personalised TMS targets can be reliably and robustly pinpointed, with unprecedented millimetre precision.
  • Cash et al. JAMA Psychiatry. 2020. Functional Magnetic Resonance Imaging-Guided Personalization of Transcranial Magnetic Stimulation for Depression. We demonstrate that TMS antidepressant response is better when patients are treated closer in proximity to their personalised connectivity-based brain target.
  • Cash et al. Biological Psychiatry. 2020. Using brain imaging to improve spatial targeting of TMS for depression. A review of the contribution of neuroimaging to advancing therapeutic TMS for depression.
  • Cash et al. Human Brain Mapping. 2019. A multivariate neuroimaging biomarker of individual outcome to TMS in depression. We developed a machine learning approach to predict antidepressant treatment response based on brain connectivity.
  • Rastogi, Cash et al., Neuroimage 2017. Modulation of cognitive cerebello-cerebral functional connectivity by lateral cerebellar continuous theta burst stimulation. This is one of the first studies to directly demonstrate the causal modulation of distributed neural networks using brain stimulation. It is now widely accepted that TMS similarly exerts its clinical effects by normalising aberrant network connectivity. Our study additionally illustrated the fact that conventional TMS targeting approaches, based on fiducial landmarks, are inaccurate and may even categorically target and modulate unintended brain networks.

Further information: Check out our lab website for further details: www.sysneuro.org

Evolution of brain stimulation targeting practices over time. From Cash et al, 2020.
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