Learning to classify complex patterns using a VLSI network of
... power consumption. Understanding how to accomplish this in VLSI networks of spiking neurons can not only contribute to an insight into the fundamental mechanisms of computation used in the brain, but could also lead to efficient hardware implementations for a wide range of applications, from autonom ...
... power consumption. Understanding how to accomplish this in VLSI networks of spiking neurons can not only contribute to an insight into the fundamental mechanisms of computation used in the brain, but could also lead to efficient hardware implementations for a wide range of applications, from autonom ...
Bursting Neurons Signal Input Slope
... firing patterns. For instance, intrinsic conductances can generate brief, high-frequency bursts of action potentials that are commonly observed in recordings from a variety of brain regions (Kandel and Spencer, 1961; Barker and Gainer, 1975; King et al., 1976; Cattaneo et al., 1981a; Eisen and Marde ...
... firing patterns. For instance, intrinsic conductances can generate brief, high-frequency bursts of action potentials that are commonly observed in recordings from a variety of brain regions (Kandel and Spencer, 1961; Barker and Gainer, 1975; King et al., 1976; Cattaneo et al., 1981a; Eisen and Marde ...
What is the other 85% of V1 doing?
... of interaction may be crucial to the operation of the system, and so cutting them out—either in theories or experiments—may give a misleading picture of how the system actually works. Obviously, if one knew in advance what the important modes of interaction were then one could choose to reduce appro ...
... of interaction may be crucial to the operation of the system, and so cutting them out—either in theories or experiments—may give a misleading picture of how the system actually works. Obviously, if one knew in advance what the important modes of interaction were then one could choose to reduce appro ...
Synchrony Unbound: Review A Critical Evaluation of
... It seems that the object binding problem cannot be solved in primary visual cortex, and that the computations involved cannot be completed until a fairly high level in the visual cortical hierarchy. The neurological literature supports the idea that binding is a high-level process. Visual binding de ...
... It seems that the object binding problem cannot be solved in primary visual cortex, and that the computations involved cannot be completed until a fairly high level in the visual cortical hierarchy. The neurological literature supports the idea that binding is a high-level process. Visual binding de ...
Investigating circadian rhythmicity in pain sensitivity using
... pain, was developed in 1965 by Ronald Melzack and Charles Patrick Wall [20]. These researchers revolutionized the understanding of the pain pathway by scrutinizing previous conceptual models of pain processing and developing a model that accounts for the experimental evidence seen thus far. The gate ...
... pain, was developed in 1965 by Ronald Melzack and Charles Patrick Wall [20]. These researchers revolutionized the understanding of the pain pathway by scrutinizing previous conceptual models of pain processing and developing a model that accounts for the experimental evidence seen thus far. The gate ...
Perception of three-dimensional structure from motion
... of motion gradient information. This 3-D surface computation may operate within MT, or may utilize the cells in MST which have been previously shown to be selective to various gradients and patterns of motion26–30. By using transparent motions, we have been able to establish that area MT is intimate ...
... of motion gradient information. This 3-D surface computation may operate within MT, or may utilize the cells in MST which have been previously shown to be selective to various gradients and patterns of motion26–30. By using transparent motions, we have been able to establish that area MT is intimate ...
Curriculum Vitae - People.csail.mit.edu
... Dec. 2007Structured Learning. To develop methods to learn models of and to mine structured data such as graphs and relational interpretations. Postdoctoral Associate, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, USA Feb. - Nov. 2007 ...
... Dec. 2007Structured Learning. To develop methods to learn models of and to mine structured data such as graphs and relational interpretations. Postdoctoral Associate, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, USA Feb. - Nov. 2007 ...
The hippocampal–striatal axis in learning, prediction and
... reinforcing effects of drugs or rewards. Animals undergo conditioning sessions in different environments (or spatial compartments), only one of which is associated with the drug or reward. The acquisition of a spatial– reward association is indicated by the animal’s preference for the environment pr ...
... reinforcing effects of drugs or rewards. Animals undergo conditioning sessions in different environments (or spatial compartments), only one of which is associated with the drug or reward. The acquisition of a spatial– reward association is indicated by the animal’s preference for the environment pr ...
Applied Mathematics and Computation 215
... mathematically aware that have clarified difficult problems and vague intuitions. We look very selectively in the space available at how people have tried to isolate and clarify what is difficult about the reduction of computation, particularly in nature, to the basic Turing model. Fuzziness, Contin ...
... mathematically aware that have clarified difficult problems and vague intuitions. We look very selectively in the space available at how people have tried to isolate and clarify what is difficult about the reduction of computation, particularly in nature, to the basic Turing model. Fuzziness, Contin ...
Neural Networks and Its Application in Engineering
... A neural network could be also be described as a system composed of many simple processing elements operating in parallel whose function is determined by network structure, connection strengths, and the processing performed at computing elements or nodes (DARPA Neural Network Study, 1988). It resemb ...
... A neural network could be also be described as a system composed of many simple processing elements operating in parallel whose function is determined by network structure, connection strengths, and the processing performed at computing elements or nodes (DARPA Neural Network Study, 1988). It resemb ...
rene-witte.net - Semantic Scholar
... Fig. 1: PAS Extractor ) as basis for further processing. Our focus lies thereby on the analysis of the extracted PASs of the reported speech utterance and the gener- ...
... Fig. 1: PAS Extractor ) as basis for further processing. Our focus lies thereby on the analysis of the extracted PASs of the reported speech utterance and the gener- ...
Word - Egodeath.com
... The Workspace — Copycat’s Locus of Perceptual Activity The Constant Fight for Probabilistic Attention The Parallel Emergence of Multi-Level Perceptual Structures The Drive Towards Global Coherence and Towards Deep Concepts The Coderack — Source of Emergent Pressures in Copycat Pressures Determine th ...
... The Workspace — Copycat’s Locus of Perceptual Activity The Constant Fight for Probabilistic Attention The Parallel Emergence of Multi-Level Perceptual Structures The Drive Towards Global Coherence and Towards Deep Concepts The Coderack — Source of Emergent Pressures in Copycat Pressures Determine th ...
Mirror Proposal 8-01 - USC - University of Southern California
... The modeling environment will include a primatoid hand-arm avatar for generating actions (to provide output in studies of learning to grasp, and input stimuli for studies of action recognition); preprocessing routines for visual input; and tools for modeling adaptive networks of biologically plausib ...
... The modeling environment will include a primatoid hand-arm avatar for generating actions (to provide output in studies of learning to grasp, and input stimuli for studies of action recognition); preprocessing routines for visual input; and tools for modeling adaptive networks of biologically plausib ...