Proceedings of the Seventh Annual Deep Brain Stimulation Think Tank: Advances in Neurophysiology, Adaptive DBS, Virtual Reality, Neuroethics and Technology.

The Seventh Annual Deep Brain Stimulation (DBS) Think Tank held on September 8th of 2019 addressed the most current: (1) use and utility of complex neurophysiological signals for development of adaptive neurostimulation to improve clinical outcomes; (2) Advancements in recent neuromodulation techniques to treat neuropsychiatric disorders; (3) New developments in optogenetics and DBS; (4) The use of augmented Virtual reality (VR) and neuromodulation; (5) commercially available technologies; and (6) ethical issues arising in and from research and use of DBS. These advances serve as both "markers of progress" and challenges and opportunities for ongoing address, engagement, and deliberation as we move to improve the functional capabilities and translational value of DBS. It is in this light that these proceedings are presented to inform the field and initiate ongoing discourse. As consistent with the intent, and spirit of this, and prior DBS Think Tanks, the overarching goal is to continue to develop multidisciplinary collaborations to rapidly advance the field and ultimately improve patient outcomes.

Public Regulatory Databases as a Source of Insight for Neuromodulation Devices Stimulation Parameters.

OBJECTIVE: The Shannon model is often used to define an expected boundary between non-damaging and damaging modes of electrical neurostimulation. Numerous preclinical studies have been performed by manufacturers of neuromodulation devices using different animal models and a broad range of stimulation parameters while developing devices for clinical use. These studies are mostly absent from peer-reviewed literature, which may lead to this information being overlooked by the scientific community. We aimed to locate summaries of these studies accessible via public regulatory databases and to add them to a body of knowledge available to a broad scientific community. METHODS: We employed web search terms describing device type, intended use, neural target, therapeutic application, company name, and submission number to identify summaries for premarket approval (PMA) devices and 510(k) devices. We filtered these records to a subset of entries that have sufficient technical information relevant to safety of neurostimulation. RESULTS: We identified 13 product codes for 8 types of neuromodulation devices. These led us to devices that have 22 PMAs and 154 510(k)s and six transcripts of public panel meetings. We found one PMA for a brain, peripheral nerve, and spinal cord stimulator and five 510(k) spinal cord stimulators with enough information to plot in Shannon coordinates of charge and charge density per phase. CONCLUSIONS: Analysis of relevant entries from public regulatory databases reveals use of pig, sheep, monkey, dog, and goat animal models with deep brain, peripheral nerve, muscle and spinal cord electrode placement with a variety of stimulation durations (hours to years); frequencies (10-10,000 Hz) and magnitudes (Shannon k from below zero to 4.47). Data from located entries indicate that a feline cortical model that employs acute stimulation might have limitations for assessing tissue damage in diverse anatomical locations, particularly for peripheral nerve and spinal cord simulation.

Proceedings of the Third Annual Deep Brain Stimulation Think Tank: A Review of Emerging Issues and Technologies.

The proceedings of the 3rd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, imaging, and computational work on DBS for the treatment of neurological and neuropsychiatric disease. Significant innovations of the past year are emphasized. The Think Tank's contributors represent a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers, and members of industry. Presentations and discussions covered a broad range of topics, including policy and advocacy considerations for the future of DBS, connectomic approaches to DBS targeting, developments in electrophysiology and related strides toward responsive DBS systems, and recent developments in sensor and device technologies.

Proceedings of the Second Annual Deep Brain Stimulation Think Tank: What's in the Pipeline.

The proceedings of the 2nd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, and computational work on DBS for the treatment of neurological and neuropsychiatric disease and represent the insights of a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers and members of industry. Presentations and discussions covered a broad range of topics, including advocacy for DBS, improving clinical outcomes, innovations in computational models of DBS, understanding of the neurophysiology of Parkinson's disease (PD) and Tourette syndrome (TS) and evolving sensor and device technologies.

Brain rhythms reveal a hierarchical network organization.

Recordings of ongoing neural activity with EEG and MEG exhibit oscillations of specific frequencies over a non-oscillatory background. The oscillations appear in the power spectrum as a collection of frequency bands that are evenly spaced on a logarithmic scale, thereby preventing mutual entrainment and cross-talk. Over the last few years, experimental, computational and theoretical studies have made substantial progress on our understanding of the biophysical mechanisms underlying the generation of network oscillations and their interactions, with emphasis on the role of neuronal synchronization. In this paper we ask a very different question. Rather than investigating how brain rhythms emerge, or whether they are necessary for neural function, we focus on what they tell us about functional brain connectivity. We hypothesized that if we were able to construct abstract networks, or "virtual brains", whose dynamics were similar to EEG/MEG recordings, those networks would share structural features among themselves, and also with real brains. Applying mathematical techniques for inverse problems, we have reverse-engineered network architectures that generate characteristic dynamics of actual brains, including spindles and sharp waves, which appear in the power spectrum as frequency bands superimposed on a non-oscillatory background dominated by low frequencies. We show that all reconstructed networks display similar topological features (e.g. structural motifs) and dynamics. We have also reverse-engineered putative diseased brains (epileptic and schizophrenic), in which the oscillatory activity is altered in different ways, as reported in clinical studies. These reconstructed networks show consistent alterations of functional connectivity and dynamics. In particular, we show that the complexity of the network, quantified as proposed by Tononi, Sporns and Edelman, is a good indicator of brain fitness, since virtual brains modeling diseased states display lower complexity than virtual brains modeling normal neural function. We finally discuss the implications of our results for the neurobiology of health and disease.

High-yield preparation of wax esters via lipase-catalyzed esterification using fatty acids and alcohols from crambe and camelina oils.

Fatty acids obtained from seed oils of crambe (Crambe abyssinica) and camelina (Camelina sativa) via alkaline saponification or steam splitting were esterified using lipases as biocatalysts with oleyl alcohol and the alcohols derived from crambe and camelina oils via hydrogenolysis of their methyl esters. Long-chain wax esters were thus obtained in high yields when Novozym 435 (immobilized lipase B from Candida antarctica) and papaya (Carica papaya) latex lipase were used as biocatalysts and vacuum was applied to remove the water formed. The highest conversions to wax esters were obtained with Novozym 435 (> or =95%) after 4-6 h of reaction, whereas with papaya latex lipase such a high degree of conversion was attained after 24 h. Products obtained from stoichiometric amounts of substrates were almost exclusively (>95%) composed of wax esters having compositions approaching that of jojoba (Simmondsia chinensis) oil, especially when crambe fatty acids in combination with camelina alcohols or camelina fatty acids in combination with crambe alcohols were used as substrates.

The development of computer ethics: contributions from business ethics and medical ethics.

In this essay, we demonstrate that the field of computer ethics shares many core similarities with two other areas of applied ethics. Academicians writing and teaching in the area of computer ethics, along with practitioners, must address ethical issues that are qualitatively similar in nature to those raised in medicine and business. In addition, as academic disciplines, these three fields also share some similar concerns. For example, all face the difficult challenge of maintaining a credible dialogue with diverse constituents such as academicians of various disciplines, professionals, policymakers, and the general public. Given these similarities, the fields of bioethics and business ethics can serve as useful models for the development of computer ethics.

Decision analysis and Alzheimer disease: three case studies.

Decision analysis may be useful to people facing Alzheimer disease (AD) decisions. The use of decision analysis in three such cases is reported. The first case involved a middle-aged person worried about early-onset AD and deciding whether to seek genetic testing. The analysis let the participant reject testing and consider innovative care options. The second case involved a middle-aged person concerned about later-onset AD. The analysis for her was more complex, and led to the assignment of some limited value on genetic testing for her. The third case revolved around a caregiver's treatment decisions for a patient with severe AD. It led her to recognize the importance of factors she had not previously considered. In each of the three cases, the intensive process of decision analysis appears to have improved the subject's decision.