Effects of Subcallosal Cingulate Deep Brain Stimulation on Negative Self-bias in Patients With Treatment-resistant Depression

Hilimire, Matthew R.; Mayberg, Helen S.; Holtzheimer, Paul E.; Broadway, James M.; Parks, Nathan A.; DeVylder, Jordan; Corballis, Paul M.

doi:10.1016/j.brs.2014.11.010

Cited by 43 publications

(35 citation statements)

References 49 publications

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“…74 Deep-brain stimulation of the subcallosal cingulate has been associated with a persistent normalisation of hyper-responsivity to negative emotion stimuli that might characterise negative bias biotypes (figure 3). 75 Investigation of new lines of evidence implicating additional neural circuits in treatments for depression and anxiety is also important. For example, connectivity of visual circuits could distinguish treatment-resistant patients from treatment-sensitive patients.…”

Section: Future Directionsmentioning

confidence: 99%

Precision psychiatry: a neural circuit taxonomy for depression and anxiety

Williams

2016

The Lancet Psychiatry

507

375

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Although there have been tremendous advances in the understanding of human dysfunctions in the brain circuitry for self-reflection, emotion, and cognitive control, a brain-based taxonomy for mental disease is still lacking. As a result, these advances have not been translated into actionable clinical tools, and the language of brain circuits has not been incorporated into training programmes. To address this gap, I present this synthesis of published work, with a focus on functional imaging of circuit dysfunctions across the spectrum of mood and anxiety disorders. This synthesis provides the foundation for a taxonomy of putative types of dysfunction, which cuts across traditional diagnostic boundaries for depression and anxiety and includes instead distinct types of neural circuit dysfunction that together reflect the heterogeneity of depression and anxiety. This taxonomy is suited to specifying symptoms in terms of underlying neural dysfunction at the individual level and is intended as the foundation for building mechanistic research and ultimately guiding clinical practice.

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Section: Future Directionsmentioning

confidence: 99%

Precision psychiatry: a neural circuit taxonomy for depression and anxiety

Williams

2016

The Lancet Psychiatry

507

375

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“…Further, different targets may optimally impact specific depressive symptoms: inhibiting negative mood may be best achieved with stimulation of the SCC white matter, while motivation and learning may be optimally induced using stimulation of the ventral striatum/ventral anterior internal capsule or medial forebrain bundle. A target comparison strategy addressing the time course of stimulation-induced changes in distinct symptoms or behaviors may also be required to fully delineate DBS effects in MDD toward optimizing the selection of a procedure most likely to result in clinical remission for a given patient (130–132). …”

Section: Integrated Multimodal Framework Using Dbs For Trdmentioning

confidence: 99%

Multimodal Approaches to Define Network Oscillations in Depression

Smart

Tiruvadi

Mayberg

2015

Biological Psychiatry

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The renaissance in the use of encephalography-based research methods to probe the pathophysiology of neuropsychiatric disorders is well afoot and continues to advance. Building on the platform of neuroimaging evidence on brain circuit models, magnetoencephalography, scalp electroencephalography, and even invasive electroencephalography are now being used to characterize brain network dysfunctions that underlie major depressive disorder using brain oscillation measurements and associated treatment responses. Such multiple encephalography modalities provide avenues to study pathologic network dynamics with high temporal resolution and over long time courses, opportunities to complement neuroimaging methods and findings, and new approaches to identify quantitative biomarkers that indicate critical targets for brain therapy. Such goals have been facilitated by the ongoing testing of novel invasive neuromodulation therapies, notably, deep brain stimulation, where clinically relevant treatment effects can be monitored at multiple brain sites in a time-locked causal manner. We review key brain rhythms identified in major depressive disorder as foundation for development of putative biomarkers for objectively evaluating neuromodulation success and for guiding deep brain stimulation or other target-based neuromodulation strategies for treatment-resistant depression patients.

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“…A number of studies are based on the automated classification of normal and depression-related EEG signals. This proposed automatic classification system could serve as a useful diagnostic and monitoring tool for the detection of depression [20,79,133,135,226,228,231].…”

Section: Othermentioning

confidence: 99%

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

et al. 2017

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Abstract:Recent developments and studies in brain-computer interface (BCI) technologies have facilitated emotion detection and classification. Many BCI studies have sought to investigate, detect, and recognize participants' emotional affective states. The applied domains for these studies are varied, and include such fields as communication, education, entertainment, and medicine. To understand trends in electroencephalography (EEG)-based emotion recognition system research and to provide practitioners and researchers with insights into and future directions for emotion recognition systems, this study set out to review published articles on emotion detection, recognition, and classification. The study also reviews current and future trends and discusses how these trends may impact researchers and practitioners alike. We reviewed 285 articles, of which 160 were refereed journal articles that were published since the inception of affective computing research. The articles were classified based on a scheme consisting of two categories: research orientation and domains/applications. Our results show considerable growth of EEG-based emotion detection journal publications. This growth reflects an increased research interest in EEG-based emotion detection as a salient and legitimate research area. Such factors as the proliferation of wireless EEG devices, advances in computational intelligence techniques, and machine learning spurred this growth.

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Effects of Subcallosal Cingulate Deep Brain Stimulation on Negative Self-bias in Patients With Treatment-resistant Depression

Cited by 43 publications

References 49 publications

Precision psychiatry: a neural circuit taxonomy for depression and anxiety

Precision psychiatry: a neural circuit taxonomy for depression and anxiety

Multimodal Approaches to Define Network Oscillations in Depression

Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review

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