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Liu S, Duan M, Sun Y, Wang L, An L, Ming D. Neural responses to social decision-making in suicide attempters with mental disorders. BMC Psychiatry 2023; 23:19. [PMID: 36624426 PMCID: PMC9830736 DOI: 10.1186/s12888-022-04422-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 11/24/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Decision-making deficits have been reported in suicide attempters and may be a neuropsychological trait of vulnerability to suicidal behavior. However, little is known about how neural activity is altered in decision-making. This study aimed to investigate the neural responses in suicide attempters with mental disorders during social decision-making. Electroencephalography (EEG) were recorded from 52 patients with mental disorders with past suicide attempts (SAs = 26) and without past suicide attempts (NSAs = 26), as well as from 22 age- and sex- matched healthy controls (HCs) during the Ultimatum Game (UG), which is a typical paradigm to investigate the responses to fair and unfair decision-making. METHODS MINI 5.0 interview and self report questionnaire were used to make mental diagnosis and suicide behavior assessment for individuals. Event-related potential (ERP) and phase-amplitude coupling (PAC) were extracted to quantify the neural activity. Furthermore, Spearman correlation and logistic regression analyses were conducted to identify the risk factors of suicidal behavior. RESULTS ERP analysis demonstrated that SA patients had decreased P2 amplitude and prolonged P2 latency when receiving unfair offers. Moreover, SA patients exhibited greater negative-going feedback-related negativity (FRN) to unfair offers compared to fair ones, whereas such a phenomenon was absent in NSA and HC groups. These results revealed that SA patients had a stronger fairness principle and a disregard toward the cost of punishment in social decision-making. Furthermore, theta-gamma and beta-gamma PAC were involved in decision-making, with compromised neural coordination in the frontal, central, and temporal regions in SA patients, suggesting cognitive dysfunction during social interaction. Statistically significant variables were used in logistic regression analysis. The area under receiver operating characteristic curve in the logistic regression model was 0.91 for SA/HC and 0.84 for SA/NSA. CONCLUSIONS Our findings emphasize that suicide attempts in patients with mental disorders are associated with abnormal decision-making. P2, theta-gamma PAC, and beta-gamma PAC may be neuro-electrophysiological biomarkers associated with decision-making. These results provide neurophysiological signatures of suicidal behavior.
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Affiliation(s)
- Shuang Liu
- grid.33763.320000 0004 1761 2484Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072 China
| | - Moxin Duan
- grid.33763.320000 0004 1761 2484Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072 China
| | - Yiwei Sun
- grid.33763.320000 0004 1761 2484Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072 China
| | - Lingling Wang
- grid.33763.320000 0004 1761 2484School of Education, Tianjin University, Tianjin, China
| | - Li An
- School of Education, Tianjin University, Tianjin, China.
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China. .,School of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China.
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2
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Treu S, Gonzalez-Rosa JJ, Soto-Leon V, Lozano-Soldevilla D, Oliviero A, Lopez-Sosa F, Reneses-Prieto B, Barcia JA, Strange BA. A ventromedial prefrontal dysrhythmia in obsessive-compulsive disorder is attenuated by nucleus accumbens deep brain stimulation. Brain Stimul 2021; 14:761-770. [PMID: 33984535 DOI: 10.1016/j.brs.2021.04.028] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 04/23/2021] [Accepted: 04/30/2021] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Obsessive-compulsive disorder (OCD) has consistently been linked to abnormal frontostriatal activity. The electrophysiological disruption in this circuit, however, remains to be characterized. OBJECTIVE/HYPOTHESIS The primary goal of this study was to investigate the neuronal synchronization in OCD patients. We predicted aberrant oscillatory activity in frontal regions compared to healthy control subjects, which would be alleviated by deep brain stimulation (DBS) of the nucleus accumbens (NAc). METHODS We compared scalp EEG recordings from nine patients with OCD treated with NAc-DBS with recordings from healthy controls, matched for age and gender. Within the patient group, EEG activity was compared with DBS turned off vs. stimulation at typical clinical settings (3.5 V, frequency of stimulation 130 Hz, pulse width 60 μs). In addition, intracranial EEG was recorded directly from depth macroelectrodes in the NAc in four OCD patients. RESULTS Cross-frequency coupling between the phase of alpha/low beta oscillations and amplitude of high gamma was significantly increased over midline frontal and parietal electrodes in patients when stimulation was turned off, compared to controls. Critically, in patients, beta (16-25 Hz) -gamma (110-166 Hz) phase amplitude coupling source localized to the ventromedial prefrontal cortex, and was reduced when NAc-DBS was active. In contrast, intracranial EEG recordings showed no beta-gamma phase amplitude coupling. The contribution of non-sinusoidal beta waveforms to this coupling are reported. CONCLUSION We reveal an increased beta-gamma phase amplitude coupling in fronto-central scalp sensors in patients suffering from OCD, compared to healthy controls, which may derive from ventromedial prefrontal regions implicated in OCD and is normalized by DBS of the nucleus accumbens. This aberrant cross-frequency coupling could represent a biomarker of OCD, as well as a target for novel therapeutic approaches.
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Affiliation(s)
- Svenja Treu
- Laboratory for Clinical Neuroscience, Centre for Biomedical Technology, Universidad Politécnica de Madrid, Spain.
| | - Javier J Gonzalez-Rosa
- Laboratory for Clinical Neuroscience, Centre for Biomedical Technology, Universidad Politécnica de Madrid, Spain; University of Cadiz, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Vanesa Soto-Leon
- Hospital Nacional de Parapléjicos, FENNSI Group, Hospital Nacional de Parapléjicos, Toledo, Spain
| | - Diego Lozano-Soldevilla
- Laboratory for Clinical Neuroscience, Centre for Biomedical Technology, Universidad Politécnica de Madrid, Spain
| | - Antonio Oliviero
- Hospital Nacional de Parapléjicos, FENNSI Group, Hospital Nacional de Parapléjicos, Toledo, Spain
| | - Fernando Lopez-Sosa
- Laboratory for Clinical Neuroscience, Centre for Biomedical Technology, Universidad Politécnica de Madrid, Spain; University of Cadiz, Institute of Biomedical Research Cadiz (INiBICA), Cádiz, Spain
| | - Blanca Reneses-Prieto
- Department of Psychiatry, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San Carlos, Universidad Complutense de Madrid, Spain
| | - Juan A Barcia
- Department of Neurosurgery, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria San Carlos, Universidad Complutense de Madrid, Spain
| | - Bryan A Strange
- Laboratory for Clinical Neuroscience, Centre for Biomedical Technology, Universidad Politécnica de Madrid, Spain
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Deep brain stimulation of the internal capsule enhances human cognitive control and prefrontal cortex function. Nat Commun 2019; 10:1536. [PMID: 30948727 PMCID: PMC6449385 DOI: 10.1038/s41467-019-09557-4] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 03/19/2019] [Indexed: 01/11/2023] Open
Abstract
Deep brain stimulation (DBS) is a circuit-oriented treatment for mental disorders. Unfortunately, even well-conducted psychiatric DBS clinical trials have yielded inconsistent symptom relief, in part because DBS’ mechanism(s) of action are unclear. One clue to those mechanisms may lie in the efficacy of ventral internal capsule/ventral striatum (VCVS) DBS in both major depression (MDD) and obsessive-compulsive disorder (OCD). MDD and OCD both involve deficits in cognitive control. Cognitive control depends on prefrontal cortex (PFC) regions that project into the VCVS. Here, we show that VCVS DBS’ effect is explained in part by enhancement of PFC-driven cognitive control. DBS improves human subjects’ performance on a cognitive control task and increases theta (5–8Hz) oscillations in both medial and lateral PFC. The theta increase predicts subjects’ clinical outcomes. Our results suggest a possible mechanistic approach to DBS therapy, based on tuning stimulation to optimize these neurophysiologic phenomena. Deep brain stimulation (DBS) is a promising treatment for psychiatric disorders, but its mechanism in relieving symptoms is unclear. Here, the authors show that DBS of ventral internal capsule/ventral striatum (VCVS) may act by enhancing prefrontal cortex oscillations that in turn enhance cognitive control.
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Salimpour Y, Anderson WS. Cross-Frequency Coupling Based Neuromodulation for Treating Neurological Disorders. Front Neurosci 2019; 13:125. [PMID: 30846925 PMCID: PMC6393401 DOI: 10.3389/fnins.2019.00125] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2018] [Accepted: 02/04/2019] [Indexed: 11/22/2022] Open
Abstract
Synchronous, rhythmic changes in the membrane polarization of neurons form oscillations in local field potentials. It is hypothesized that high-frequency brain oscillations reflect local cortical information processing, and low-frequency brain oscillations project information flow across larger cortical networks. This provides complex forms of information transmission due to interactions between oscillations at different frequency bands, which can be rendered with cross-frequency coupling (CFC) metrics. Phase-amplitude coupling (PAC) is one of the most common representations of the CFC. PAC reflects the coupling of the phase of oscillations in a specific frequency band to the amplitude of oscillations in another frequency band. In a normal brain, PAC accompanies multi-item working memory in the hippocampus, and changes in PAC have been associated with diseases such as schizophrenia, obsessive-compulsive disorder (OCD), Alzheimer disease (AD), epilepsy, and Parkinson’s disease (PD). The purpose of this article is to explore CFC across the central nervous system and demonstrate its correlation to neurological disorders. Results from previously published studies are reviewed to explore the significant role of CFC in large neuronal network communication and its abnormal behavior in neurological disease. Specifically, the association of effective treatment in PD such as dopaminergic medication and deep brain stimulation with PAC changes is described. Lastly, CFC analysis of the electrocorticographic (ECoG) signals recorded from the motor cortex of a Parkinson’s disease patient and the parahippocampal gyrus of an epilepsy patient are demonstrated. This information taken together illuminates possible roles of CFC in the nervous system and its potential as a therapeutic target in disease states. This will require new neural interface technologies such as phase-dependent stimulation triggered by PAC changes, for the accurate recording, monitoring, and modulation of the CFC signal.
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Affiliation(s)
- Yousef Salimpour
- Functional Neurosurgery Laboratory, Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - William S Anderson
- Functional Neurosurgery Laboratory, Department of Neurosurgery, Johns Hopkins School of Medicine, Baltimore, MD, United States
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Widge AS, Bilge MT, Montana R, Chang W, Rodriguez CI, Deckersbach T, Carpenter LL, Kalin NH, Nemeroff CB. Electroencephalographic Biomarkers for Treatment Response Prediction in Major Depressive Illness: A Meta-Analysis. Am J Psychiatry 2019; 176:44-56. [PMID: 30278789 PMCID: PMC6312739 DOI: 10.1176/appi.ajp.2018.17121358] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Reducing unsuccessful treatment trials could improve depression treatment. Quantitative EEG (QEEG) may predict treatment response and is being commercially marketed for this purpose. The authors sought to quantify the reliability of QEEG for response prediction in depressive illness and to identify methodological limitations of the available evidence. METHOD The authors conducted a meta-analysis of diagnostic accuracy for QEEG in depressive illness, based on articles published between January 2000 and November 2017. The review included all articles that used QEEG to predict response during a major depressive episode, regardless of patient population, treatment, or QEEG marker. The primary meta-analytic outcome was the accuracy for predicting response to depression treatment, expressed as sensitivity, specificity, and the logarithm of the diagnostic odds ratio. Raters also judged each article on indicators of good research practice. RESULTS In 76 articles reporting 81 biomarkers, the meta-analytic estimates showed a sensitivity of 0.72 (95% CI=0.67-0.76) and a specificity of 0.68 (95% CI=0.63-0.73). The logarithm of the diagnostic odds ratio was 1.89 (95% CI=1.56-2.21), and the area under the receiver operator curve was 0.76 (95% CI=0.71-0.80). No specific QEEG biomarker or specific treatment showed greater predictive power than the all-studies estimate in a meta-regression. Funnel plot analysis suggested substantial publication bias. Most studies did not use ideal practices. CONCLUSIONS QEEG does not appear to be clinically reliable for predicting depression treatment response, as the literature is limited by underreporting of negative results, a lack of out-of-sample validation, and insufficient direct replication of previous findings. Until these limitations are remedied, QEEG is not recommended for guiding selection of psychiatric treatment.
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Affiliation(s)
- Alik S. Widge
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA,Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA,Correspondence to Alik S Widge, MD, PhD, 149 13th St, Room 2627, Charlestown, MA 02129, , 617-643-2580
| | - M. Taha Bilge
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Rebecca Montana
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Weilynn Chang
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | | | - Thilo Deckersbach
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Linda L. Carpenter
- Butler Hospital and Warren Alpert Medical School of Brown University, Providence, RI
| | - Ned H. Kalin
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, WI
| | - Charles B. Nemeroff
- Department of Psychiatry, University of Miami Miller School of Medicine, Miami, FL
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6
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Widge AS, Boggess M, Rockhill AP, Mullen A, Sheopory S, Loonis R, Freeman DK, Miller EK. Altering alpha-frequency brain oscillations with rapid analog feedback-driven neurostimulation. PLoS One 2018; 13:e0207781. [PMID: 30517149 PMCID: PMC6281199 DOI: 10.1371/journal.pone.0207781] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 11/06/2018] [Indexed: 01/11/2023] Open
Abstract
Oscillations of the brain's local field potential (LFP) may coordinate neural ensembles and brain networks. It has been difficult to causally test this model or to translate its implications into treatments, because there are few reliable ways to alter LFP oscillations. We developed a closed-loop analog circuit to enhance brain oscillations by feeding them back into cortex through phase-locked transcranial electrical stimulation. We tested the system in a rhesus macaque with chronically implanted electrode arrays, targeting 8-15 Hz (alpha) oscillations. Ten seconds of stimulation increased alpha oscillatory power for up to 1 second after stimulation offset. In contrast, open-loop stimulation decreased alpha power. There was no effect in the neighboring 15-30 Hz (beta) LFP rhythm or on a neighboring array that did not participate in closed-loop feedback. Analog closed-loop neurostimulation might thus be a useful strategy for altering brain oscillations, both for basic research and the treatment of neuro-psychiatric disease.
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Affiliation(s)
- Alik S. Widge
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Matthew Boggess
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Alexander P. Rockhill
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America
| | - Andrew Mullen
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Shivani Sheopory
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
- College of Engineering, Boston University, Boston, Massachusetts, United States of America
| | - Roman Loonis
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Daniel K. Freeman
- The Charles Stark Draper Laboratory, Inc., Cambridge, Massachusetts, United States of America
| | - Earl K. Miller
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
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Bilge MT, Gosai AK, Widge AS. Deep Brain Stimulation in Psychiatry: Mechanisms, Models, and Next-Generation Therapies. Psychiatr Clin North Am 2018; 41:373-383. [PMID: 30098651 PMCID: PMC6092041 DOI: 10.1016/j.psc.2018.04.003] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Deep brain stimulation has preliminary evidence of clinical efficacy, but has been difficult to develop into a robust therapy, in part because its mechanisms are incompletely understood. We review evidence from movement and psychiatric disorder studies, with an emphasis on how deep brain stimulation changes brain networks. From this, we argue for a network-oriented approach to future deep brain stimulation studies. That network approach requires methods for identifying patients with specific circuit/network deficits. We describe how dimensional approaches to diagnoses may aid that identification. We discuss the use of network/circuit biomarkers to develop self-adjusting "closed loop" systems.
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Affiliation(s)
- Mustafa Taha Bilge
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Charlestown, Boston, MA 02129, USA
| | - Aishwarya K Gosai
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Charlestown, Boston, MA 02129, USA
| | - Alik S Widge
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 149 13th Street, Charlestown, Boston, MA 02129, USA; Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.
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8
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Widge AS, Malone DA, Dougherty DD. Closing the Loop on Deep Brain Stimulation for Treatment-Resistant Depression. Front Neurosci 2018; 12:175. [PMID: 29618967 PMCID: PMC5871707 DOI: 10.3389/fnins.2018.00175] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2018] [Accepted: 03/05/2018] [Indexed: 12/20/2022] Open
Abstract
Major depressive episodes are the largest cause of psychiatric disability, and can often resist treatment with medication and psychotherapy. Advances in the understanding of the neural circuit basis of depression, combined with the success of deep brain stimulation (DBS) in movement disorders, spurred several groups to test DBS for treatment-resistant depression. Multiple brain sites have now been stimulated in open-label and blinded studies. Initial open-label results were dramatic, but follow-on controlled/blinded clinical trials produced inconsistent results, with both successes and failures to meet endpoints. Data from follow-on studies suggest that this is because DBS in these trials was not targeted to achieve physiologic responses. We review these results within a technology-lifecycle framework, in which these early trial “failures” are a natural consequence of over-enthusiasm for an immature technology. That framework predicts that from this “valley of disillusionment,” DBS may be nearing a “slope of enlightenment.” Specifically, by combining recent mechanistic insights and the maturing technology of brain-computer interfaces (BCI), the next generation of trials will be better able to target pathophysiology. Key to that will be the development of closed-loop systems that semi-autonomously alter stimulation strategies based on a patient's individual phenotype. Such next-generation DBS approaches hold great promise for improving psychiatric care.
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Affiliation(s)
- Alik S Widge
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Donald A Malone
- Department of Psychiatry, Cleveland Clinic, Cleveland, OH, United States
| | - Darin D Dougherty
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
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9
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Deep Brain Stimulation for Highly Refractory Depression. Neuromodulation 2018. [DOI: 10.1016/b978-0-12-805353-9.00087-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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10
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Lo MC, Widge AS. Closed-loop neuromodulation systems: next-generation treatments for psychiatric illness. Int Rev Psychiatry 2017; 29:191-204. [PMID: 28523978 PMCID: PMC5461950 DOI: 10.1080/09540261.2017.1282438] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2016] [Accepted: 01/10/2017] [Indexed: 01/19/2023]
Abstract
Despite deep brain stimulation's positive early results in psychiatric disorders, well-designed clinical trials have yielded inconsistent clinical outcomes. One path to more reliable benefit is closed-loop therapy: stimulation that is automatically adjusted by a device or algorithm in response to changes in the patient's electrical brain activity. These interventions may provide more precise and patient-specific treatments. This article first introduces the available closed-loop neuromodulation platforms, which have shown clinical efficacy in epilepsy and strong early results in movement disorders. It discusses the strengths and limitations of these devices in the context of psychiatric illness. It then describes emerging technologies to address these limitations, including pre-clinical developments such as wireless deep neurostimulation and genetically targeted neuromodulation. Finally, ongoing challenges and limitations for closed-loop psychiatric brain stimulation development, most notably the difficulty of identifying meaningful biomarkers for titration, are discussed. This is considered in the recently-released Research Domain Criteria (RDoC) framework, and how neuromodulation and RDoC are jointly very well suited to address the problem of treatment-resistant illness is described.
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Affiliation(s)
- Meng-Chen Lo
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA
| | - Alik S. Widge
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA
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Mazaheri A, Bahramisharif A. Reply to: Ventral Capsule/Ventral Striatum Deep Brain Stimulation Does Not Consistently Diminish Occipital Cross-Frequency Coupling. Biol Psychiatry 2016; 80:e61-2. [PMID: 26852072 DOI: 10.1016/j.biopsych.2015.12.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2015] [Revised: 12/14/2015] [Accepted: 12/14/2015] [Indexed: 10/22/2022]
Affiliation(s)
- Ali Mazaheri
- School of Psychology, University of Birmingham, Edgbaston, Birmingham, United Kingdom.
| | - Ali Bahramisharif
- Academic Medical Centre, University of Amsterdam, Amsterdam, Netherlands
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