Matching Items (5)

Modeling Biological and Optical Tools Towards Achieving Deeper Levels of Brain Stimulation using OLEDs

Description

Optogenetics presents the ability to control membrane dynamics through the usage of transfected proteins (opsins) and light stimulation. However, as the field continues to grow, the original biological and stimulation

Optogenetics presents the ability to control membrane dynamics through the usage of transfected proteins (opsins) and light stimulation. However, as the field continues to grow, the original biological and stimulation tools used have become dated or limited in their uses. The usage of Organic Light Emitting Diodes (OLEDs) in optical stimulation offers greater resolution, finer control of pixel arrays, and the increased functionality of a flexible display at the cost of lower irradiance power density. This study was done to simulate methods using genetic and optical tools towards decreasing the threshold irradiance needed to initiate an action potential in a ChR2 expressing neuron. Simulations show that pulsatile stimulation can decrease threshold irradiances by increasing the overall duration of stimulus while keeping individual pulse durations below 5 ms. Furthermore, the redistribution of Channelrhodopsin-2 (ChR2) to the apical dendrites and a change in wavelength to 625 nm both result in lower threshold irradiances. However, the model used has many discrepancies and has room for improvement in areas such as the light distribution model and ChR2 dynamics. The simulations run with this model however still present valuable insight and knowledge towards the usage of new stimulation methods and revisions on existing protocols.

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Date Created
  • 2016-05

Intracortical microstimulation of somatosensory cortex: functional encoding and localization of neuronal recruitment

Description

Intracortical microstimulation (ICMS) within somatosensory cortex can produce artificial sensations including touch, pressure, and vibration. There is significant interest in using ICMS to provide sensory feedback for a prosthetic limb.

Intracortical microstimulation (ICMS) within somatosensory cortex can produce artificial sensations including touch, pressure, and vibration. There is significant interest in using ICMS to provide sensory feedback for a prosthetic limb. In such a system, information recorded from sensors on the prosthetic would be translated into electrical stimulation and delivered directly to the brain, providing feedback about features of objects in contact with the prosthetic. To achieve this goal, multiple simultaneous streams of information will need to be encoded by ICMS in a manner that produces robust, reliable, and discriminable sensations. The first segment of this work focuses on the discriminability of sensations elicited by ICMS within somatosensory cortex. Stimulation on multiple single electrodes and near-simultaneous stimulation across multiple electrodes, driven by a multimodal tactile sensor, were both used in these experiments. A SynTouch BioTac sensor was moved across a flat surface in several directions, and a subset of the sensor's electrode impedance channels were used to drive multichannel ICMS in the somatosensory cortex of a non-human primate. The animal performed a behavioral task during this stimulation to indicate the discriminability of sensations evoked by the electrical stimulation. The animal's responses to ICMS were somewhat inconsistent across experimental sessions but indicated that discriminable sensations were evoked by both single and multichannel ICMS. The factors that affect the discriminability of stimulation-induced sensations are not well understood, in part because the relationship between ICMS and the neural activity it induces is poorly defined. The second component of this work was to develop computational models that describe the populations of neurons likely to be activated by ICMS. Models of several neurons were constructed, and their responses to ICMS were calculated. A three-dimensional cortical model was constructed using these cell models and used to identify the populations of neurons likely to be recruited by ICMS. Stimulation activated neurons in a sparse and discontinuous fashion; additionally, the type, number, and location of neurons likely to be activated by stimulation varied with electrode depth.

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Date Created
  • 2013

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Reliable arithmetic circuit design inspired by SNP systems

Description

ABSTRACT Developing new non-traditional device models is gaining popularity as the silicon-based electrical device approaches its limitation when it scales down. Membrane systems, also called P systems, are a new

ABSTRACT Developing new non-traditional device models is gaining popularity as the silicon-based electrical device approaches its limitation when it scales down. Membrane systems, also called P systems, are a new class of biological computation model inspired by the way cells process chemical signals. Spiking Neural P systems (SNP systems), a certain kind of membrane systems, is inspired by the way the neurons in brain interact using electrical spikes. Compared to the traditional Boolean logic, SNP systems not only perform similar functions but also provide a more promising solution for reliable computation. Two basic neuron types, Low Pass (LP) neurons and High Pass (HP) neurons, are introduced. These two basic types of neurons are capable to build an arbitrary SNP neuron. This leads to the conclusion that these two basic neuron types are Turing complete since SNP systems has been proved Turing complete. These two basic types of neurons are further used as the elements to construct general-purpose arithmetic circuits, such as adder, subtractor and comparator. In this thesis, erroneous behaviors of neurons are discussed. Transmission error (spike loss) is proved to be equivalent to threshold error, which makes threshold error discussion more universal. To improve the reliability, a new structure called motif is proposed. Compared to Triple Modular Redundancy improvement, motif design presents its efficiency and effectiveness in both single neuron and arithmetic circuit analysis. DRAM-based CMOS circuits are used to implement the two basic types of neurons. Functionality of basic type neurons is proved using the SPICE simulations. The motif improved adder and the comparator, as compared to conventional Boolean logic design, are much more reliable with lower leakage, and smaller silicon area. This leads to the conclusion that SNP system could provide a more promising solution for reliable computation than the conventional Boolean logic.

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Date Created
  • 2013

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The role of motor cortical neuron subpopulations in the adaptation of locomotion through complex environments

Description

Locomotion in natural environments requires coordinated movements from multiple body parts, and precise adaptations when changes in the environment occur. The contributions of the neurons of the motor cortex

Locomotion in natural environments requires coordinated movements from multiple body parts, and precise adaptations when changes in the environment occur. The contributions of the neurons of the motor cortex underlying these behaviors are poorly understood, and especially little is known about how such contributions may differ based on the anatomical and physiological characteristics of neurons. To elucidate the contributions of motor cortical subpopulations to movements, the activity of motor cortical neurons, muscle activity, and kinematics were studied in the cat during a variety of locomotion tasks requiring accurate foot placement, including some tasks involving both expected and unexpected perturbations of the movement environment. The roles of neurons with two types of neuronal characteristics were studied: the existence of somatosensory receptive fields located at the shoulder, elbow, or wrist of the contralateral forelimb; and the existence projections through the pyramidal tract, including fast- and slow-conducting subtypes.

Distinct neuronal adaptations between simple and complex locomotion tasks were observed for neurons with different receptive field properties and fast- and slow-conducting pyramidal tract neurons. Feedforward and feedback-driven kinematic control strategies were observed for adaptations to expected and unexpected perturbations, respectively, during complex locomotion tasks. These kinematic differences were reflected in the response characteristics of motor cortical neurons receptive to somatosensory information from different parts of the forelimb, elucidating roles for the various neuronal populations in accommodating disturbances in the environment during behaviors. The results show that anatomical and physiological characteristics of motor cortical neurons are important for determining if and how neurons are involved in precise control of locomotion during natural behaviors.

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Date Created
  • 2015

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Towards brains in the cloud: a biophysically realistic computational model of olfactory bulb

Description

The increasing availability of experimental data and computational power have resulted in increasingly detailed and sophisticated models of brain structures. Biophysically realistic models allow detailed investigations of the mechanisms that

The increasing availability of experimental data and computational power have resulted in increasingly detailed and sophisticated models of brain structures. Biophysically realistic models allow detailed investigations of the mechanisms that operate within those structures. In this work, published mouse experimental data were synthesized to develop an extensible, open-source platform for modeling the mouse main olfactory bulb and other brain regions. A “virtual slice” model of a main olfactory bulb glomerular column that includes detailed models of tufted, mitral, and granule cells was created to investigate the underlying mechanisms of a gamma frequency oscillation pattern (“gamma fingerprint”) often observed in rodent bulbar local field potential recordings. The gamma fingerprint was reproduced by the model and a mechanistic hypothesis to explain aspects of the fingerprint was developed. A series of computational experiments tested the hypothesis. The results demonstrate the importance of interactions between electrical synapses, principal cell synaptic input strength differences, and granule cell inhibition in the formation of the gamma fingerprint. The model, data, results, and reproduction materials are accessible at https://github.com/justasb/olfactorybulb. The discussion includes a detailed description of mechanisms underlying the gamma fingerprint and how the model predictions can be tested experimentally. In summary, the modeling platform can be extended to include other types of cells, mechanisms and brain regions and can be used to investigate a wide range of experimentally testable hypotheses.

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Date Created
  • 2019