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Understanding the Inflammatory Tissue Reaction to Brain Implants To Improve Neurochemical Sensing Performance.

ABSTRACT: Neurochemical sensing probes are a valuable diagnostic and therapeutic tool that can be used to study neurodegenerative diseases involving deficiencies in neurotransmitter signaling. However, implantation of these biosensors can elicit a harmful tissue response that alters the neurochemical environment within the brain. Transmission of chemical messengers via neurons is impeded by a barrier-forming glial scar that occurs within weeks after insertion followed by progressive neurodegeneration, attenuating signal sensitivity. Emerging research reveals that non-neuronal cells also influence the neurochemical milieu following injury both directly and indirectly. The reactivity of both microglia and astrocytes to inserted probes have been extensively studied in the past yet there remains other glial subtypes in the brain, such as oligodendrocytes and their precursors, the myelin structures they form, as well as vascular-bound pericytes, that have the potential to contribute significantly to the inflammation due to their responsibility to maintain tissue homeostasis. A brief overview of how tissue injury alters the neurochemical makeup followed by alternative potential targets of investigation and novel strategies to enhance the chemical sensing abilities of implantable probes will be discussed.

SUBMITTER: Wellman SM

PROVIDER: S-EPMC5944321 | biostudies-other | 2017 Dec

REPOSITORIES: biostudies-other

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Understanding the Inflammatory Tissue Reaction to Brain Implants To Improve Neurochemical Sensing Performance.

Wellman Steven M SM Kozai Takashi D Y TDY

ACS chemical neuroscience 20171109 12

Neurochemical sensing probes are a valuable diagnostic and therapeutic tool that can be used to study neurodegenerative diseases involving deficiencies in neurotransmitter signaling. However, implantation of these biosensors can elicit a harmful tissue response that alters the neurochemical environment within the brain. Transmission of chemical messengers via neurons is impeded by a barrier-forming glial scar that occurs within weeks after insertion followed by progressive neurodegeneration, att ...[more]

PMID: 29120167

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Project description:Computational modeling and simulation have become essential tools in the quest to better understand the brain's makeup and to decipher the causal interrelations of its components. The breadth of biochemical and biophysical processes and structures in the brain has led to the development of a large variety of model abstractions and specialized tools, often times requiring high performance computing resources for their timely execution. What has been missing so far was an in-depth analysis of the complexity of the computational kernels, hindering a systematic approach to identifying bottlenecks of algorithms and hardware. If whole brain models are to be achieved on emerging computer generations, models and simulation engines will have to be carefully co-designed for the intrinsic hardware tradeoffs. For the first time, we present a systematic exploration based on analytic performance modeling. We base our analysis on three in silico models, chosen as representative examples of the most widely employed modeling abstractions: current-based point neurons, conductance-based point neurons and conductance-based detailed neurons. We identify that the synaptic modeling formalism, i.e. current or conductance-based representation, and not the level of morphological detail, is the most significant factor in determining the properties of memory bandwidth saturation and shared-memory scaling of in silico models. Even though general purpose computing has, until now, largely been able to deliver high performance, we find that for all types of abstractions, network latency and memory bandwidth will become severe bottlenecks as the number of neurons to be simulated grows. By adapting and extending a performance modeling approach, we deliver a first characterization of the performance landscape of brain tissue simulations, allowing us to pinpoint current bottlenecks for state-of-the-art in silico models, and make projections for future hardware and software requirements.

Dataset Information

Understanding the Inflammatory Tissue Reaction to Brain Implants To Improve Neurochemical Sensing Performance.

Publications

Understanding the Inflammatory Tissue Reaction to Brain Implants To Improve Neurochemical Sensing Performance.

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