Now showing 1 - 10 of 110
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    A phase dynamic model of systematic error in simple copying tasks
    (01-09-2009)
    Dubey, Saguna
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    Sambaraju, Sandeep
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    Cautha, Sarat Chandra
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    Arya, Vednath
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    A crucial insight into handwriting dynamics is embodied in the idea that stable, robust handwriting movements correspond to attractors of an oscillatory dynamical system. We present a phase dynamic model of visuomotor performance involved in copying simple oriented lines. Our studies on human performance in copying oriented lines revealed a systematic error pattern in orientation of drawn lines, i.e., lines at certain orientation are drawn more accurately than at other values. Furthermore, human subjects exhibit "flips" in direction at certain characteristic orientations. It is argued that this flipping behavior has its roots in the fact that copying process is inherently ambiguous-a line of given orientation may be drawn in two different (mutually opposite) directions producing the same end result. The systematic error patterns seen in human copying performance is probably a result of the attempt of our visuomotor system to cope with this ambiguity and still be able to produce accurate copying movements. The proposed nonlinear phase-dynamic model explains the experimentally observed copying error pattern and also the flipping behavior with remarkable accuracy. © 2009 Springer-Verlag.
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    A comparative study of complexity of handwritten Bharati characters with that of major Indian scripts
    (30-06-2017)
    Naik, Manali
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    We present Bharati, a simple, novel script that can represent the characters of a majority of contemporary Indian scripts. The shapes/motifs of Bharati characters are drawn from some of the simplest characters of existing Indian scripts. Bharati characters are designed such that they strictly reflect the underlying phonetic organization, thereby attributing to the script qualities of simplicity, familiarity, ease of acquisition and use. Thus, employing Bharati script as a common script for a majority of Indian languages can ameliorate several existing communication bottlenecks in India. We perform a complexity analysis of handwritten Bharati script and compare its complexity with that of nine major Indian scripts. The measures of complexity are derived from a theory of handwritten characters based on Catastrophe theory. Bharati script is shown to be simpler than the nine major Indian scripts in most measures of complexity. Self-organizing maps (SOM) are generated by training data for handwritten characters of Bharati and Indian scripts. Phonetically similar characters are clustered together on SOM for Bharati, supporting the proposition that the shapes of Bharati script follow the underlying phonetic organization.
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    A computational neuromotor model of the role of basal ganglia and hippocampus in spatial navigation
    (08-11-2010)
    Sukumar, Deepika
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    A computational model of the Basal Ganglia and the Hippocampus as key players in solving a navigation task is presented. The roles played by the above-mentioned neural substrates in navigation are demonstrated by an exploration task performed by a model rat in a simulated Morris Water Maze. To highlight the role of hippocampus in navigation, the agent is made to adopt a context-based navigation strategy. To demonstrate the role of BG in navigation, the agent is made to adopt a visual cue-based navigation strategy. The models are developed based on "actor-critic" architecture and trained using reinforcement learning. The above two models are integrated into a complete model which incorporates the above two forms of navigation. © 2010 Springer-Verlag Berlin Heidelberg.
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    A hierarchical anti-Hebbian network model for the formation of spatial cells in three-dimensional space
    (01-12-2018)
    Soman, Karthik
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    Yartsev, Michael M.
    Three-dimensional (3D) spatial cells in the mammalian hippocampal formation are believed to support the existence of 3D cognitive maps. Modeling studies are crucial to comprehend the neural principles governing the formation of these maps, yet to date very few have addressed this topic in 3D space. Here we present a hierarchical network model for the formation of 3D spatial cells using anti-Hebbian network. Built on empirical data, the model accounts for the natural emergence of 3D place, border, and grid cells, as well as a new type of previously undescribed spatial cell type which we call plane cells. It further explains the plausible reason behind the place and grid-cell anisotropic coding that has been observed in rodents and the potential discrepancy with the predicted periodic coding during 3D volumetric navigation. Lastly, it provides evidence for the importance of unsupervised learning rules in guiding the formation of higher-dimensional cognitive maps.
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    Bistable dynamics of cardiac cell models coupled by dynamic gap junctions linked to Cardiac Memory
    (01-02-2010)
    Sachdeva, Gairik
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    Kalyanasundaram, Kanakapriya
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    Krishnan, J.
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    In an earlier study, we suggested that adaptive gap junctions (GJs) might be a basis of cardiac memory, a phenomenon which refers to persistent electrophysiological response of the heart to external pacing. Later, it was also shown that the proposed mechanism of adaptation of GJs is consistent with known electrophysiology of GJs. In the present article, we show that a pair of cardiac cell models coupled by dynamic, voltage-sensitive GJs exhibits bistable behavior under certain conditions. Three kinds of cell pairs are considered: (1) a Noble-Noble cell pair that represents adjacent cells in Purkinje network, (2) a pair of DiFranceso-Noble cells that represents adjacent SA nodal cells, and (3) a model of Noble cell coupled to Luo-Rudy cell model, which represents an interacting pair of a Purkinje fiber and a ventricular myocyte. Bistability is demonstrated in all the three cases. We suggest that this bistability might be an underlying factor behind cardiac memory. Focused analysis of a pair of Noble cell models showed that bistability is obtained only when the properties of GJs "match" with the properties of the pair of cells that is coupled by the GJs. This novel notion of match between GJs and cardiac cell types might give an insight into specialized distributions of various connexin proteins in cardiac tissue. © 2009 Springer-Verlag.
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    A computational basal ganglia model to assess the role of STN-DBS on Impulsivity in Parkinson's disease
    (28-09-2015)
    Alekhya, Mandali
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    Deep Brain Stimulation (DBS) of Sub Thalamic Nucleus (STN) is the most sought out therapeutic technique for the treatment of motor symptoms in advanced parkinsonian conditions. But the effect of STN-DBS on cognition was observed to be contrary with Impulsivity being observed as the most common side effect. Among the numerous behavioral tasks, Iowa Gambling Task (IGT) captures one of the impulsivity features (premeditation) and the task resembles real life decision making scenario. A 2D spiking network of basal ganglia (BG) was modeled to study the cognitive aspects of Parkinson's disease (PD) during medication and DBS. The model consist of key BG nuclei such as the Globus Pallidus externus (GPe) and Globus Pallidus internus (GPi) and STN modeled as Izhikevich 2D spiking neurons and striatal output as Poisson process. The concept of dopamine being the reward prediction error was utilized to update the cortico-striatal weights. The model was then tested on 3 conditions i.e., healthy controls, PD 'ON' and STN-DBS. The effect of DBS on decision making (in terms of IGT score) was studied by changing the electrode position (in STN) in the model. Our results indicate that changing the electrode's position and current spread independently leads to a critical change in performance levels. The model also shows that simulated PD 'ON' medication performed poorly compared to healthy controls as observed in experiments. The simulated results suggest that electrode position or current spread might be the probable reason for the observed controversial outcomes in STN-DBS patients. This is one of the first models to use spiking neurons to test the effects of dopamine medications and STN DBS on complex decision making.
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    Motor symptoms in Parkinson's disease: A unified framework
    (01-09-2016)
    Moustafa, Ahmed A.
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    Phillips, Joseph R.
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    Gupta, Ankur
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    Keri, Szabolcs
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    Polner, Bertalan
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    Frank, Michael J.
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    Jahanshahi, Marjan
    Parkinson's disease (PD) is characterized by a range of motor symptoms. Besides the cardinal symptoms (akinesia and bradykinesia, tremor and rigidity), PD patients show additional motor deficits, including: gait disturbance, impaired handwriting, grip force and speech deficits, among others. Some of these motor symptoms (e.g., deficits of gait, speech, and handwriting) have similar clinical profiles, neural substrates, and respond similarly to dopaminergic medication and deep brain stimulation (DBS). Here, we provide an extensive review of the clinical characteristics and neural substrates of each of these motor symptoms, to highlight precisely how PD and its medical and surgical treatments impact motor symptoms. In conclusion, we offer a unified framework for understanding the range of motor symptoms in PD. We argue that various motor symptoms in PD reflect dysfunction of neural structures responsible for action selection, motor sequencing, and coordination and execution of movement.
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    A Computational Model of Neuro-Glio-Vascular Loop Interactions
    (27-11-2012)
    Chander, Bankim Subhash
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    We present a computational, biophysical model of neuron-astrocyte-vessel interaction. Unlike other cells, neurons convey "hunger" signals to the vascular network via an intervening layer of glial cells (astrocytes); vessels dilate and release glucose which fuels neuronal firing. Existing computational models focus on only parts of this loop (neuron→astrocyte→vessel→neuron), whereas the proposed model describes the entire loop. Neuronal firing causes release of a neurotransmitter like glutamate which triggers release of vasodilator by astrocytes via a cascade of biochemical events. Vasodilators released from astrocytic endfeet cause blood vessels to dilate and release glucose into the interstitium, part of which is taken up by the astrocyticendfeet. Glucose is converted into lactate in the astrocyte and transported into the neuron. Glucose from the interstitium and lactate (produced from glucose) influx from astrocyte are converted into ATP in the neuron. Neuronal ATP is used to drive the Na+/K+ATPase pumps, which maintain ionic gradients necessary for neuronal firing. When placed in the metabolic loop, the neuron exhibits sustained firing only when the stimulation current is more than a minimum threshold. For various combinations of initial neuronal [ATP] and external current, the neuron exhibits a variety of firing patterns including sustained firing, firing after an initial pause, burst firing etc. Neurovascular interactions under conditions of constricted vessels are also studied. Most models of cerebral circulation describe neurovascular interactions exclusively in the "forward" neuron→vessel direction. The proposed model indicates possibility of "reverse" influence also, with vasomotion rhythms influencing neural firing patterns. Another idea that emerges out of the proposed work is that brain's computations may be more comprehensively understood in terms of neuro-glial-vascular dynamics and not in terms of neural firing alone. © 2012 Chander, Chakravarthy.
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    Systems biological approach on neurological disorders: A novel molecular connectivity to aging and psychiatric diseases
    (12-01-2011)
    Ahmed, Shiek S.S.J.
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    Ahameethunisa, Abdul R.
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    Santosh, Winkins
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    Kumar, Suresh
    Background: Systems biological approach of molecular connectivity map has reached to a great interest to understand the gene functional similarities between the diseases. In this study, we developed a computational framework to build molecular connectivity maps by integrating mutated and differentially expressed genes of neurological and psychiatric diseases to determine its relationship with aging.Results: The systematic large-scale analyses of 124 human diseases create three classes of molecular connectivity maps. First, molecular interaction of disease protein network generates 3632 proteins with 6172 interactions, which determines the common genes/proteins between diseases. Second, Disease-disease network includes 4845 positively scored disease-disease relationships. The comparison of these disease-disease pairs with Medical Subject Headings (MeSH) classification tree suggests 25% of the disease-disease pairs were in same disease area. The remaining can be a novel disease-disease relationship based on gene/protein similarity. Inclusion of aging genes set showed 79 neurological and 20 psychiatric diseases have the strong association with aging. Third and lastly, a curated disease biomarker network was created by relating the proteins/genes in specific disease contexts, such analysis showed 73 markers for 24 diseases. Further, the overall quality of the results was achieved by a series of statistical methods, to avoid insignificant data in biological networks.Conclusions: This study improves the understanding of the complex interactions that occur between neurological and psychiatric diseases with aging, which lead to determine the diagnostic markers. Also, the disease-disease association results could be helpful to determine the symptom relationships between neurological and psychiatric diseases. Together, our study presents many research opportunities in post-genomic biomarkers development. © 2011 Ahmed et al; licensee BioMed Central Ltd.
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    A computational model of planarian regeneration
    (04-07-2017)
    De, Abhishek
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    Levin, Michael
    Regeneration of complex anatomical structures is an emergent phenomenon arising from complex interplay between various underlying cellular components and processes. It is still largely unclear how coordination among cells leads to accurate regeneration of the organism, preserving the location, shape, and composition of the parts with respect to the whole. Here, we examine at the global interaction of cells in a computational model of planarian regeneration. A key feature of our model is the integration of multiple organizational levels of an organism–from cells, to network, to global shape. The computational model is able to replicate most of the experimental observations thereby facilitating study of the putative mechanisms. We observe that a hierarchical interplay between local and long range signaling acts as a positional map that guides the cellular fate at any position. Furthermore, we have quantified the quality of regeneration using a metric that provides a sense of how well the regenerated organism resembles its original shape.