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dynamic neural field

Anish A Sarma, Britni Crocker, Sydney S Cash, Wilson Truccolo, Anish A Sarma, Britni Crocker, Sydney S Cash, Wilson Truccolo, Sydney S Cash, Wilson Truccolo, Anish A Sarma, Britni Crocker
Neuromodulation systems based on electrical stimulation can be used to investigate, probe, and potentially treat a range of neurological disorders. The effects of ongoing neural state and dynamics on stimulation response, and of stimulation parameters on neural state, have broad implications for the development of closed-loop neuro-modulation approaches. We describe the development of a modular, low-latency platform for pre-clinical, closed-loop neuromodulation studies with human participants. We illustrate the uses of the platform in a stimulation case study with a person with epilepsy undergoing neuro-monitoring prior to resective surgery...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Maria Sole Morelli, Gaetano Valenza, Alberto Greco, Alberto Giannoni, Claudio Passino, Michele Emdin, Enzo Pasquale Scilingo, Nicola Vanello, Maria Sole Morelli, Gaetano Valenza, Alberto Greco, Alberto Giannoni, Claudio Passino, Michele Emdin, Enzo Pasquale Scilingo, Nicola Vanello, Maria Sole Morelli, Claudio Passino, Alberto Greco, Nicola Vanello, Gaetano Valenza, Alberto Giannoni, Michele Emdin, Enzo Pasquale Scilingo
Brain activations underlying control of breathing are not completely known. Furthermore, the coupling between neural and respiratory dynamics is usually estimated through linear correlation measures, thus totally disregarding possible underlying nonlinear interactions. To overcome these limitations, in this preliminary study we propose a nonlinear coupling analysis of simultaneous recordings of electroencephalographic (EEG) and respiratory signals at rest and after variation of carbon dioxide (CO2) level. Specifically, a CO2 increase was induced by a voluntary breath hold task...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Sofia D Karamintziou, Ana Luísa Custódio, Brigitte Piallat, Mircea Polosan, Stéphan Chabardès, Pantelis G Stathis, George A Tagaris, Damianos E Sakas, Georgia E Polychronaki, George L Tsirogiannis, Olivier David, Konstantina S Nikita
Advances in the field of closed-loop neuromodulation call for analysis and modeling approaches capable of confronting challenges related to the complex neuronal response to stimulation and the presence of strong internal and measurement noise in neural recordings. Here we elaborate on the algorithmic aspects of a noise-resistant closed-loop subthalamic nucleus deep brain stimulation system for advanced Parkinson's disease and treatment-refractory obsessive-compulsive disorder, ensuring remarkable performance in terms of both efficiency and selectivity of stimulation, as well as in terms of computational speed...
2017: PloS One
Yongmin Cho, Charles L Zhao, Hang Lu
The nervous system of Caenorhabditis elegans is an important model system for understanding the development and function of larger, more complex nervous systems. It is prized for its ease of handling, rapid life cycle, and stereotyped, well-cataloged development, with the development of all 302 neurons mapped all the way from zygote to adult. The combination of easy genetic manipulation and optical transparency of the worm allows for the direct imaging of its interior with fluorescent microscopy, without physically compromising the normal physiology of the animal itself...
February 21, 2017: Wiley Interdisciplinary Reviews. Systems Biology and Medicine
Kate L Parent, Daniel F Hill, Lindsey M Crown, Jean-Paul Wiegand, Kathleen F Gies, Michael A Miller, Christopher W Atcherley, Michael L Heien, Stephen L Cowen
Complex behaviors depend on the coordination of the activities of ensembles of neurons and the release of neuromodulators such as dopamine. The mechanisms underlying such coordination are not well-understood due to a lack of instrumentation for combined and real-time monitoring of neuromodulator release and the activities of large ensembles of neurons. Here we describe a measurement platform that allows for the combined monitoring of electrophysiology from a high-density electrode array and dopamine dynamics from a carbon-fiber microelectrode...
February 17, 2017: Analytical Chemistry
Elena Bertolotti, Raffaella Burioni, Matteo di Volo, Alessandro Vezzani
We investigate the dynamical role of inhibitory and highly connected nodes (hub) in synchronization and input processing of leaky-integrate-and-fire neural networks with short term synaptic plasticity. We take advantage of a heterogeneous mean-field approximation to encode the role of network structure and we tune the fraction of inhibitory neurons f_{I} and their connectivity level to investigate the cooperation between hub features and inhibition. We show that, depending on f_{I}, highly connected inhibitory nodes strongly drive the synchronization properties of the overall network through dynamical transitions from synchronous to asynchronous regimes...
January 2017: Physical Review. E
Stephanie J Temme, Brady J Maher, Kimberly M Christian
PURPOSE OF REVIEW: Induced pluripotent stem cells (iPSCs) can be generated from human patient tissue samples, differentiated into any somatic cell type, and studied under controlled culture conditions. We review how iPSCs are used to investigate genetic factors and biological mechanisms underlying psychiatric disorders, and considerations for synthesizing data across studies. RECENT FINDINGS: Results from patient specific-iPSC studies often reveal cellular phenotypes consistent with postmortem and brain imaging studies...
December 2016: Current Behavioral Neuroscience Reports
Christoph Fretter, Annick Lesne, Claus C Hilgetag, Marc-Thorsten Hütt
Simple models of excitable dynamics on graphs are an efficient framework for studying the interplay between network topology and dynamics. This topic is of practical relevance to diverse fields, ranging from neuroscience to engineering. Here we analyze how a single excitation propagates through a random network as a function of the excitation threshold, that is, the relative amount of activity in the neighborhood required for the excitation of a node. We observe that two sharp transitions delineate a region of sustained activity...
February 10, 2017: Scientific Reports
Egidio Falotico, Lorenzo Vannucci, Alessandro Ambrosano, Ugo Albanese, Stefan Ulbrich, Juan Camilo Vasquez Tieck, Georg Hinkel, Jacques Kaiser, Igor Peric, Oliver Denninger, Nino Cauli, Murat Kirtay, Arne Roennau, Gudrun Klinker, Axel Von Arnim, Luc Guyot, Daniel Peppicelli, Pablo Martínez-Cañada, Eduardo Ros, Patrick Maier, Sandro Weber, Manuel Huber, David Plecher, Florian Röhrbein, Stefan Deser, Alina Roitberg, Patrick van der Smagt, Rüdiger Dillman, Paul Levi, Cecilia Laschi, Alois C Knoll, Marc-Oliver Gewaltig
Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task...
2017: Frontiers in Neurorobotics
Yihong Wang, Rubin Wang, Yating Zhu
Rodent animal can accomplish self-locating and path-finding task by forming a cognitive map in the hippocampus representing the environment. In the classical model of the cognitive map, the system (artificial animal) needs large amounts of physical exploration to study spatial environment to solve path-finding problems, which costs too much time and energy. Although Hopfield's mental exploration model makes up for the deficiency mentioned above, the path is still not efficient enough. Moreover, his model mainly focused on the artificial neural network, and clear physiological meanings has not been addressed...
February 2017: Cognitive Neurodynamics
Daniele Avitable, Kyle C A Wedgwood
We study coarse pattern formation in a cellular automaton modelling a spatially-extended stochastic neural network. The model, originally proposed by Gong and Robinson (Phys Rev E 85(5):055,101(R), 2012), is known to support stationary and travelling bumps of localised activity. We pose the model on a ring and study the existence and stability of these patterns in various limits using a combination of analytical and numerical techniques. In a purely deterministic version of the model, posed on a continuum, we construct bumps and travelling waves analytically using standard interface methods from neural field theory...
February 1, 2017: Journal of Mathematical Biology
R Magalhães, J Bourgin, F Boumezbeur, P Marques, M Bottlaender, C Poupon, B Djemaï, E Duchesnay, S Mériaux, N Sousa, T M Jay, A Cachia
In today's society, every individual is subjected to stressful stimuli with different intensities and duration. This exposure can be a key trigger in several mental illnesses greatly affecting one's quality of life. Yet not all subjects respond equally to the same stimulus and some are able to better adapt to them delaying the onset of its negative consequences. The neural specificities of this adaptation can be essential to understand the true dynamics of stress as well as to design new approaches to reduce its consequences...
January 24, 2017: Translational Psychiatry
Andrew Erwin, Marcia O'Malley, David Ress, Fabrizio Sergi
We demonstrate the interaction control capabilities of the MR-SoftWrist, a novel MR-compatible robot capable of applying accurate kinesthetic feedback to wrist pointing movements executed during fMRI. The MR-SoftWrist, based on a novel design that combines parallel piezoelectric actuation with compliant force feedback, is capable of delivering 1.5 N·m of torque to the wrist of an interacting subject about the flexion/extension and radial/ulnar axes. The robot workspace, defined by admissible wrist rotation angles, fully includes a circle with a 20 deg radius...
December 1, 2016: IEEE Transactions on Neural Systems and Rehabilitation Engineering
Milos Jordanski, Milos Radovic, Zarko Milosevic, Nenad Filipovic, Zoran Obradovic
Computer simulations based on the finite element method (FEM) represent powerful tools for modeling blood flow through arteries. However, due to its computational complexity, this approach may be inappropriate when results are needed quickly. In order to reduce computational time, in this paper we proposed an alternative machine learning based approach for calculation of wall shear stress (WSS) distribution, which may play an important role in mechanisms related to initiation and development of atherosclerosis...
December 14, 2016: IEEE Journal of Biomedical and Health Informatics
Wei-Long Zheng, Bao-Liang Lu
OBJECTIVE: Covert aspects of ongoing user mental states provide key context information for user-aware human computer interactions. In this paper, we focus on the problem of estimating the vigilance of users using EEG and EOG signals. APPROACH: The PERCLOS index as vigilance annotation is obtained from eye tracking glasses. To improve the feasibility and wearability of vigilance estimation devices for real-world applications, we adopt a novel electrode placement for forehead EOG and extract various eye movement features, which contain the principal information of traditional EOG...
January 19, 2017: Journal of Neural Engineering
Ben W Dulken, Dena S Leeman, Stéphane C Boutet, Katja Hebestreit, Anne Brunet
Neural stem cells (NSCs) in the adult mammalian brain serve as a reservoir for the generation of new neurons, oligodendrocytes, and astrocytes. Here, we use single-cell RNA sequencing to characterize adult NSC populations and examine the molecular identities and heterogeneity of in vivo NSC populations. We find that cells in the NSC lineage exist on a continuum through the processes of activation and differentiation. Interestingly, rare intermediate states with distinct molecular profiles can be identified and experimentally validated, and our analysis identifies putative surface markers and key intracellular regulators for these subpopulations of NSCs...
January 17, 2017: Cell Reports
Christian Donner, Klaus Obermayer, Hideaki Shimazaki
The models in statistical physics such as an Ising model offer a convenient way to characterize stationary activity of neural populations. Such stationary activity of neurons may be expected for recordings from in vitro slices or anesthetized animals. However, modeling activity of cortical circuitries of awake animals has been more challenging because both spike-rates and interactions can change according to sensory stimulation, behavior, or an internal state of the brain. Previous approaches modeling the dynamics of neural interactions suffer from computational cost; therefore, its application was limited to only a dozen neurons...
January 2017: PLoS Computational Biology
Daniel E Winkowski, Daniel A Nagode, Kevin J Donaldson, Pingbo Yin, Shihab A Shamma, Jonathan B Fritz, Patrick O Kanold
Sensory environments change over a wide dynamic range and sensory processing can change rapidly to facilitate stable perception. While rapid changes may occur throughout the sensory processing pathway, cortical changes are believed to profoundly influence perception. Prior stimulation studies showed that orbitofrontal cortex (OFC) can modify receptive fields and sensory coding in A1, but the engagement of OFC during listening and the pathways mediating OFC influences on A1 are unknown. We show in mice that OFC neurons respond to sounds consistent with a role of OFC in audition...
January 8, 2017: Cerebral Cortex
Shuangming Yang, Bin Deng, Jiang Wang, Huiyan Li, Chen Liu, Chris Fietkiewicz, Kenneth A Loparo
Real-time estimation of dynamical characteristics of thalamocortical cells, such as dynamics of ion channels and membrane potentials, is useful and essential in the study of the thalamus in Parkinsonian state. However, measuring the dynamical properties of ion channels is extremely challenging experimentally and even impossible in clinical applications. This paper presents and evaluates a real-time estimation system for thalamocortical hidden properties. For the sake of efficiency, we use a field programmable gate array for strictly hardware-based computation and algorithm optimization...
January 9, 2017: Scientific Reports
Qihe Shan, Huaguang Zhang, Zhanshan Wang, Zhao Zhang
Neural networks (NNs) in the stochastic environment were widely modeled as stochastic differential equations, which were driven by white noise, such as Brown or Wiener process in the existing papers. However, they are not necessarily the best models to describe dynamic characters of NNs disturbed by nonwhite noise in some specific situations. In this paper, general noise disturbance, which may be nonwhite, is introduced to NNs. Since NNs with nonwhite noise cannot be described by Itô integral equation, a novel modeling method of stochastic NNs is utilized...
December 29, 2016: IEEE Transactions on Neural Networks and Learning Systems
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