A5002519820- Neural dynamics and brain function
- Neuroscience and Neuropharmacology Research
- Photoreceptor and optogenetics research
- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
- Neuroscience and Neural Engineering
- Cell Image Analysis Techniques
- stochastic dynamics and bifurcation
- Epilepsy research and treatment
- Advanced Memory and Neural Computing
- Ionosphere and magnetosphere dynamics
- Solar and Space Plasma Dynamics
- Image and Signal Denoising Methods
- Protein Structure and Dynamics
- Pulsars and Gravitational Waves Research
- Neuroscience and Music Perception
- Blind Source Separation Techniques
- Chaos control and synchronization
- Neural Networks and Applications
- Neurobiology and Insect Physiology Research
- Nonlinear Dynamics and Pattern Formation
- Speech and Audio Processing
- Lipid Membrane Structure and Behavior
- Scientific Computing and Data Management
- Analog and Mixed-Signal Circuit Design
University of Chicago
2003-2013
Google (United States)
2012
Office of Science
2010
Argonne National Laboratory
2010
University of Memphis
2010
Northwestern University
2001
Most types of electrographic epileptiform activity can be characterized by isolated or repetitive bursts in brain electrical activity. This observation is our motivation to determine mechanisms that underlie bursting behavior neuronal networks. Here we show the persistent sodium (Na P ) current mouse neocortical slices associated with cellular and data suggest these cells are capable driving networks into a state. conclusion supported following observations. 1) Both low concentrations...
Detection and analysis of epileptic seizures is clinical research interest. We propose a novel seizure detection scheme based on the phase-slope index (PSI) directed influence applied to multichannel electrocorticogram data. The PSI metric identifies increases in spatio-temporal interactions between channels that clearly distinguish from interictal activity. form global interaction compare this threshold detect presence seizures. chosen moving average recent activity accommodate differences...
Seizures in pediatric epilepsy are often associated with spreading, repetitive bursting activity neocortex. The authors examined onset and propagation of seizure-like using a computational model cortical circuitry. includes two pyramidal cell types four inhibitory interneurons. Each neuron is represented by multicompartmental biophysically realistic ion channels. determined the role neurons found that their capability driving network oscillations most prominent networks either weak or...
An empirical Compton up-scattering model is described which reproduces both the fractional amplitude (RMS) vs. energy and soft time lags in 830 Hz QPO observed 4U1608-52 on Mar. 3, 1996. A combination of two coherent variations coronal photon temperatures (with their relative contributions determined by enforcing conservation) gives rise to QPO's dependent characteristics. All input parameters model, save a characteristic plasma size fraction Comptonized photons impinging source, are derived...
Two models of the neocortex are developed to study normal and pathologic neuronal activity. One model contains a detailed description neocortical microcolumn represented by 656 neurons, including superficial deep pyramidal cells, four types inhibitory realistic synaptic contacts. Simulations show that neurons given type exhibit similar, synchronized behavior in this model. This observation is captured population describes activity large populations with two differential equations delays....
Robust, automated seizure detection has long been an important goal in epilepsy research because of both the possibilities for portable intervention devices and potential to provide prompter, more efficient treatment while clinic. The authors present results on how well four algorithms (based principal eigenvalue [EI], total power, Kolmogorov entropy [KE], correlation dimension) discriminated between ictal interictal EEG electrocorticoencephalography (ECoG) from patients (aged 13 months 21...
Our limited understanding of the relationship between behavior individual neurons and large neuronal networks is an important limitation in current epilepsy research may be one main causes our inadequate ability to treat it. Addressing this problem directly via experiments impossibly complex; thus, we have been developing studying medium-large-scale simulations detailed guide us. Flexibility connection schemas a complete description cortical tissue seem necessary for purpose. In paper...
Two existing models of brain dynamics in epilepsy, one detailed (i.e., realistic) and abstract simplified) are compared terms behavioral range match to vitro mouse recordings. A new method is introduced for comparing across computational that may have very different forms. First, high-level metrics were extracted from model output time series. principal components analysis was then performed over these obtain a reduced set derived features. These features define low-dimensional behavior...
Background Large neural network simulations are becoming more complex to set up. They require modeling at multiple scales, include the effects of many interacting physical processes, encompass greater detail, and consume computational resources. The drive solve problems that rely on increasingly codes will soon land us in realm petascale computing. How we manage such simulations, configure them, accurately aim them we're trying solve? Simulation is an expensive process, with each run...
Background Automated parameter search algorithms, such as simulated annealing, seek to tune a model's parameters reproduce important features of target data set. A match function compares the model and generate goodness fit is crucial because it reflects which are considered interest. Previous work has shown effectiveness combining annealing with time-domain functions (e.g., spike timing least mean square (LMS) membrane potentials) compartmental cortical pyramidal cell [1].