scholarly journals Editorial: Towards the Next Generation of Deep Brain Stimulation Therapies: Technological Advancements, Computational Methods, and New Targets

2021 ◽  
Vol 15 ◽  
Author(s):  
Sabato Santaniello ◽  
George C. McConnell ◽  
John T. Gale ◽  
Rose T. Faghih ◽  
Caleb Kemere ◽  
...  
2013 ◽  
Vol 23 ◽  
pp. S138
Author(s):  
J. Luigjes ◽  
W. Van den Brink ◽  
D. Denys

Author(s):  
Eran Klein

Deep brain stimulation (DBS) for psychiatric illness raises challenges for informed consent. Some of these are well recognized, such as vulnerability and unrealistic expectations, problems with capacity to consent, and scientific and safety uncertainties in implantable device research. The next generation of DBS for treatment of psychiatric illnesses may be closed-loop (or brain–computer interface-modulated) or volitionally controlled. That is, the activity of deep brain stimulating electrodes will be modulated with feedback from additional cortical or deep brain implanted recording electrodes. Six challenges for informed consent in next-generation psychiatric DBS are reviewed. These challenges are illustrated by expanding on results of a recently published qualitative study of individuals in research trials of DBS for depression and obsessive–compulsive disorder. An argument is offered that engaging with end users and potential end users of neural devices about ethical concerns is an important step in improving informed consent practices related to emerging neurotechnologies.


2021 ◽  
Vol 15 ◽  
Author(s):  
Witney Chen ◽  
Lowry Kirkby ◽  
Miro Kotzev ◽  
Patrick Song ◽  
Ro’ee Gilron ◽  
...  

Advances in neuromodulation technologies hold the promise of treating a patient’s unique brain network pathology using personalized stimulation patterns. In service of these goals, neuromodulation clinical trials using sensing-enabled devices are routinely generating large multi-modal datasets. However, with the expansion of data acquisition also comes an increasing difficulty to store, manage, and analyze the associated datasets, which integrate complex neural and wearable time-series data with dynamic assessments of patients’ symptomatic state. Here, we discuss a scalable cloud-based data platform that enables ingestion, aggregation, storage, query, and analysis of multi-modal neurotechnology datasets. This large-scale data infrastructure will accelerate translational neuromodulation research and enable the development and delivery of next-generation deep brain stimulation therapies.


2015 ◽  
Vol 8 (1) ◽  
pp. 21-26 ◽  
Author(s):  
Cameron C. McIntyre ◽  
Ashutosh Chaturvedi ◽  
Reuben R. Shamir ◽  
Scott F. Lempka

2009 ◽  
Vol 12 (2) ◽  
pp. 85-103 ◽  
Author(s):  
Kendall H. Lee ◽  
Charles D. Blaha ◽  
Paul A. Garris ◽  
Pedram Mohseni ◽  
April E. Horne ◽  
...  

Author(s):  
Laura B. Dunn ◽  
Paul E. Holtzheimer

As investigators look to “next-generation” deep brain stimulation (DBS) approaches, renewed enthusiasm is emerging for DBS for psychiatric disorders. This commentary on Chapter 13 (“Informed Consent for Next-Generation Deep Brain Stimulation Psychiatric Research: Engaging End Users to Understand Risks and Improve Practice”) provides additional insight into the challenges related to informed consent described by Klein. We argue that the sorts of vulnerability described by Klein warrant further attention, in particular, to help address the question of whether patients with psychiatric disorders are uniquely vulnerable, in ways that patients with other illnesses are not. Ethics research, such as that conducted by Klein, in which end users of brain-based devices are interviewed, is critical. It will also be important to compare brain-based intervention research with other forms of research; we do not want to end up engaging in ethics “exceptionalism” as a result of failure to conduct rigorous studies on ethics-related questions.


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