NEUROCOMPUTATIONAL MODELLING OF DISTRIBUTED LEARNING FROM VISUAL STIMULI
DOI:
https://doi.org/10.22159/ajpcr.2017.v10s1.19645Keywords:
Neurocomputational Modelling, Machine Vision, Artificial IntelligenceAbstract
Neurocomputational modeling of visual stimuli can lead not only to identify the neural substrates of attention but also to test cognitive theories of
attention with applications on several visual media, robotics, etc. However, there are many research works done in cognitive model for linguistics,
but the studies regarding cognitive modeling of learning mechanisms for visual stimuli are falling back. Based on principles of operation cognitive
functionalities in human vision processing, the study presents the development of a computational neurocomputational cognitive model for visual
perception with detailed algorithmic descriptions. Here, four essential questions of cognition and visual attention is considered for logically
compressing into one unified neurocomputational model: (i) Segregation of special classes of stimuli and attention modulation, (ii) relation between
gaze movements and visual perception, (iii) mechanism of selective stimulus processing and its encoding in neuronal cells, and (iv) mechanism of
visual perception through autonomous relation proofing.
Downloads
References
Horn B. Extended Guassian images. Proc. IEEE, 1984, 72: 1671–1686
Johnson A, Hebert M. Using spin images for efficient object recognition in cluttered 3D scenes. IEEE Trans. Pattern Analysis and Machine Intelligence, 1999, 21: 433–449
Elbaz A, Kimmel R. On bending invariant signatures for surfaces. IEEE Trans. Pattern Analysis and Machine Intelligence, 2003, 25: 1285–1295
Funkhouser T, Min P, Kazhdan M, Chen J, Halderman A, Dobkin D, Jacobs D. A search engine for 3D models. ACM Trans. Graphics, 2003, 22: 83–105
Liu Y, Chen Z, Tang K. Construction of iso-contours, bisectors, and Voronoi diagrams on triangulated surfaces. IEEE Trans. Pattern Analysis and Machine Intelligence, 2011, 33: 1502–1517
Goodale M, Milner A. Separate visual pathways for perception and action. Trends in Neurosciences, 1992, 15: 20–25
Fu X, Cai L, Liu Y, et al. A computational cognition model of perception, memory, and judgment. Sci China Ser F-Inf Sci, 2013, 56(5): , doi: 10.1007/s11432-009-0095-8.
McGill 3D Shape Benchmark, http://www.cim.mcgill.ca/∼shape/benchMark/
Gallistel C R, King A. Memory and the Computational Brain: Why Cognitive Science Will Transform Neuroscience. New York: Blackwell/Wiley, 2009. iiv–xvi
Hu S M, Chen T, Xu K, et al. Internet visual media processing: a survey with graphics and vision applications. Vis Comput, 2013, 29: 393–405
Hulusic V, Debattista K, Aggarwal V, et al. Maintaining frame rate perception in interactive environments by exploiting audio-visual cross-modal interaction. Vis Comput, 2011, 27: 57–66
Vazquez P-P, Marco J. Using normalized compression distance for image similarity measurement: an experimental study. Vis Comput, 2012, 28: 1063–1084
Eysenck M W, Keane M T. Cognitive Psychology: a Student’s Handbook. 6th ed. New York: Psychology Press, 2010. 1–50
National Institute on Drug Abuse. Computational neuroscience at the NIH. Nat Neurosci, 2000, 3: 1161–1164
Buschman T J, Miller E K. Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science, 2007, 315: 1860–1862
Navalpakkam V, Itti L. Search goal tunes visual features optimally. Neuron, 2007, 53: 605-617
Katsuki F, Constantinidis C. Early involvement of prefrontal cortex in visual bottom-up attention. Nat Neurosci, 2012, 15: 1160–1166
Corbetta M, Shulman G L. Control of goal-directed and stimulus-driven attention in the brain. Nat Rev Neurosci, 2002, 3: 201–215
Zanto T P, Rubens M T, Thangavel A, et al. Causal role of the prefrontal cortex in top down modulation of visual processing and working memory. Nat Neurosci, 2011, 14: 656–661
Tomita H M, Ohbayashi K, Nakahara I, et al. Top-down signal from prefrontal cortex in executive control of memory retrieval. Nature, 1999, 401: 699–703
Itti L, Koch C. Computational modelling of visual attention. Nat Rev Neurosci, 2001, 2: 194–203
Cox D, Meyers E, Sinha P. Contextually evoked object-specific responses in human visual cortex. Science, 2004, 303: 115–117
Kouh M, Poggio T. A canonical neural circuit for cortical nonlinear operations. Neural Comput, 2008, 20: 1427–1451
Poggio T, Bizzi E. Generalization in vision and motor control. Nature, 2004, 431: 768-774
Hung C P, Kreiman G, Poggio T, et al. Fast readout of object identity from macaque inferior temporal cortex. Science, 2005, 310: 863–866
A Rai, Computational Modeling Study of Synfire Chains from Multiple Plasticity Mechanisms for Model Development at Neural Level: Introducing an Evolving Digital Micro-Brain, Research & Reviews: Journal of Computational Biology 3 (2), 9-15
A Rai, Characterizing Face Encoding Mechanism by Selective Object Pattern in Brains Using Synthetic Intelligence & its Simultaneous replication of Visual System That Encode Faces, RESEARCH & REVIEWS : JOURNAL OF COMPUTATIONAL BIOLOGY 3 (2), 9-15
A Rai, Parsing of Sensory Perception in Oscillatory Networks Through Cross Frequency Coupling of Memory Synchronization: Revelation of Enhanced Learning by Autistic Brain, RESEARCH & REVIEWS: A JOURNAL OF NEUROSCIENCE 4 (2), 9-14
Pylyshyn Z W. Computation and Cognition: toward a Foundation for Cognitive Science. Cambridge: The MIT Press, 1984. 1–16.
Rai, Ankush. "Shell implementation of neural net over the UNIX environment for file management: A step towards automated operating system." Journal of Operating Systems Development & Trends 1.2 (2014): 10-14.
Rai, Ankush. "An Introduction of Smart Self-learning Shell Programming Interface." Journal of Advances in Shell Programming 1.2 (2015): 3-6.
Rai, Ankush. "Dynamic Pagination for Efficient Memory Management over Distributed Computational Architecture for Swarm Robotics." Journal of Advances in Shell Programming 1.2 (2014): 1-4.
Published
How to Cite
Issue
Section
The publication is licensed under CC By and is open access. Copyright is with author and allowed to retain publishing rights without restrictions.
