Harilal Parasuram

Computational Modeling of Single Neuron Extracellular Electric Potentials and Network Local Field Potentials using LFPsim

Local Field Potentials (LFPs) are population signals generated by complex spatiotemporal interaction of current sources and dipoles. Mathematical computations of LFPs allow the study of circuit functions and dysfunctions via simulations. This paper introduces LFPsim, a NEURON-based tool for computing population LFP activity and single neuron extracellular potentials. LFPsim was developed to be used on existing cable compartmental neuron and network models. Point source, line source, and RC based filter approximations can be used to compute extracellular activity. As a demonstration of efficient implementation, we showcase LFPs from mathematical models of electrotonically compact cerebellum granule neurons and morphologically complex neurons of the neocortical column. LFPsim reproduced neocortical LFP at 8, 32, and 56 Hz via current injection, in vitro post-synaptic N2a, N2b waves and in vivo T-C waves in cerebellum granular layer. LFPsim also includes a simulation of multi-electrode array of LFPs in network populations to aid computational inference between biophysical activity in neural networks and corresponding multi-unit activity resulting in extracellular and evoked LFP signals.

Exploiting point source approximation on detailed neuronal models to reconstruct single neuron electric field and population LFP

Extracellular electrodes record local field potential as an average response from the neurons within the vicinity of the electrode. Here, we used neuronal models and point source approximation techniques to study the compartmental contribution of single neuron LFP and the attenuation properties of extracellular medium. Cable compartmental contribution of single neuron LFP was estimated by computing electric potential generated by localized ion channels. We simulated the electric potential generated from axon-hillock region contributed significantly to the single neuron extracellular field. Models of cerebellar granule neuron and L5 pyramidal neuron were used to study single neuron extracellular field potentials. Attenuation properties of the extracellular medium were studied via the granule cell model. A computational model of a rat Crus-IIa cerebellar granular layer, built with detailed anatomical and physiological properties allowed reconstructing population LFP. As with single neurons, the same technique was able to reconstruct the T and C waves of evoked postsynaptic in vivo LFP trace. In addition to role of attenuation on the width of signals, plasticity was simulated via modifications of intrinsic properties of underlying neurons and population LFP validated experimental data correlating network function to underlying single neuron activity.

Computational Neuroscience of Timing, Plasticity and Function in Cerebellum Microcircuits

Cerebellum has been known to show homogeneity in circuit organization and hence the “modules” or various circuits in the cerebellum are attributed to the diversity of functions such as timing, pattern recognition, movement planning and dysfunctions such as ataxia related to the cerebellum. Ataxia-like conditions, induced by intrinsic excitability changes, disable spiking or bursts and thereby limit the quanta of downstream information. Understanding timing, plasticity and functional roles of cerebellum involve large-scale and microcircuit reconstructions validating molecular mechanisms in population activity. Using mathematical modelling, we attempted to reconstruct information transmission at the granular layer of the cerebellum, a circuit whose role in dysfunctions remain yet to be fully explored. We have employed spiking models to reconstruct timing roles and detailed biophysical models for extracellular activity and local field population response. The roles of inhibition, induced plasticity and their implications in information transmission were evaluated. Modulatory roles of Golgi inhibition and pattern abstraction via optimal storage were estimated. An abstraction of the granular and Purkinje layer circuit for neurorobotic roles such as pattern recognition and spike encoding via two new methods was developed. Simulations suggest plasticity at cerebellar relays may be an important element of tremendous storage capacity reliable in the learning of coordination of actions, sensorimotor or cognitive, in which the cerebellum participates.

Computing LFP from biophysical models of neurons and neural microcircuits

Local Field Potentials (LFP) allow interpretations of patterns of information generated by neuronal populations. LFPs are Low frequency (<;300 Hz) population signals recorded with glass or metal electrodes and are known to be generated by complex spatiotemporal interactions of synaptic stimuli in combination with sink-source behavior in the circuit. Computational reconstruction of local field potentials allows to constrain detailed neuronal models and network microcircuits and study the function and dysfunctions via simulations. In this paper, we present a comparison of various methods and tools available for LFP computations in single neurons and populations of cells. We compare our LFPsim and ReConv methods to LFPy, VERTEX while mathematically computing local field potentials in single neurons and network models made with detailed multi-compartmental models and available through databases like ModelDB.

Understanding Cerebellum Granular Layer Network Computations through Mathematical Reconstructions of Evoked Local Field Potentials

Background: The cerebellar granular layer input stage of cerebellum receives information from tactile and sensory regions of the body. The somatosensory activity in the cerebellar granular layer corresponds to sensory and tactile input has been observed by recording Local Field Potential (LFP) from the Crus-IIa regions of cerebellum in brain slices and in anesthetized animals. Purpose: In this paper, a detailed biophysical model of Wistar rat cerebellum granular layer network model and LFP modelling schemas were used to simulate circuit’s evoked response. Methods: Point Source Approximation and Line Source Approximation were used to reconstruct the network LFP. The LFP mechanism in in vitro was validated in network model and generated the in vivo LFP using the same mechanism. Results: The network simulations distinctly displayed the Trigeminal and Cortical (TC) wave components generated by 2 independent bursts implicating the generation of TC waves by 2 independent granule neuron populations. Induced plasticity was simulated to estimate granule neuron activation related population responses. As a prediction, cerebellar dysfunction (ataxia) was also studied using the model. Dysfunction at individual neurons in the network was affected by the population response. Conclusion: Our present study utilizes available knowledge on known mechanisms in a single cell and associates network function to population responses.

Taking Project Tiger to the Classroom: A Virtual Lab Case Study

Understanding how population dynamics change over time is critical to many practical problems as pest control, endangered species protection etc. Teaching population ecology is not easy since data is usually collected over a very long period. This paper discusses a specific tiger population case study relating to growth rate predictions using an online virtual lab. Studying tiger populations and introduction of such data in classrooms help in creating awareness and support new pedagogies to estimate animal population dynamics. We have used online virtual labs which are ready-made tools to perform simple experiments and analysis. An important and usually complex case of population analysis as in tiger populations in India is studied in this paper. Although some major parameters like food, transient movement, and ecosystem details have been ignored, predicted data for tiger population follows closely to actual data for previous years and even predicts the growth rate with a small standard deviation of 10%. Our results with tiger populations come close to the actual census values. We propose the use of simple mathematical models to make assessment of transient animal populations such as tigers, and sharks. Also use of such ready-made pro-academic online tools encourages new studies and an enhanced pedagogy to population ecology for mathematicians, biotechnologists, wildlife institute personnel among many other crossdisciplinary scientists.