The Experts below are selected from a list of 444 Experts worldwide ranked by ideXlab platform
Charles G Gross - One of the best experts on this subject based on the ideXlab platform.
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genealogy of the Grandmother Cell
The Neuroscientist, 2002Co-Authors: Charles G GrossAbstract:A “Grandmother Cell” is a hypothetical neuron that responds only to a highly complex, specific, and meaningful stimulus, such as the image of one’s Grandmother. The term originated in a parable Jerry Lettvin told in 1967. A similar concept had been systematically developed a few years earlier by Jerzy Konorski who called such Cells “gnostic” units. This essay discusses the origin, influence, and current status of these terms and of the alternative view that complex stimuli are represented by the pattern of firing across ensembles of neurons.
Itzhak Fried - One of the best experts on this subject based on the ideXlab platform.
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sparse but not Grandmother Cell coding in the medial temporal lobe
Trends in Cognitive Sciences, 2008Co-Authors: Quian R Quiroga, Gabriel Kreiman, Christof Koch, Itzhak FriedAbstract:Although a large number of neuropsychological and imaging studies have demonstrated that the medial temporal lobe (MTL) plays an important role in human memory, there are few data regarding the activity of neurons involved in this process. The MTL receives massive inputs from visual cortical areas, and evidence over the last decade has consistently shown that MTL neurons respond selectively to complex visual stimuli. Here, we focus on how the activity patterns of these Cells might reflect the transformation of visual percepts into long-term memories. Given the very sparse and abstract representation of visual information by these neurons, they could in principle be considered as ‘Grandmother Cells’. However, we give several arguments that make such an extreme interpretation unlikely.
Quian R Quiroga - One of the best experts on this subject based on the ideXlab platform.
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sparse but not Grandmother Cell coding in the medial temporal lobe
Trends in Cognitive Sciences, 2008Co-Authors: Quian R Quiroga, Gabriel Kreiman, Christof Koch, Itzhak FriedAbstract:Although a large number of neuropsychological and imaging studies have demonstrated that the medial temporal lobe (MTL) plays an important role in human memory, there are few data regarding the activity of neurons involved in this process. The MTL receives massive inputs from visual cortical areas, and evidence over the last decade has consistently shown that MTL neurons respond selectively to complex visual stimuli. Here, we focus on how the activity patterns of these Cells might reflect the transformation of visual percepts into long-term memories. Given the very sparse and abstract representation of visual information by these neurons, they could in principle be considered as ‘Grandmother Cells’. However, we give several arguments that make such an extreme interpretation unlikely.
Jeffrey S. Bowers - One of the best experts on this subject based on the ideXlab platform.
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On the Biological Plausibility of Grandmother Cells: Implications for Neural Network Theories in Psychology and Neuroscience
Psychological Review, 2009Co-Authors: Jeffrey S. BowersAbstract:A fundamental claim associated with parallel distributed processing (PDP) theories of cognition is that knowledge is coded in a distributed manner in mind and brain. This approach rejects the claim that knowledge is coded in a localist fashion, with words, objects, and simple concepts (e.g. "dog"), that is, coded with their own dedicated representations. One of the putative advantages of this approach is that the theories are biologically plausible. Indeed, advocates of the PDP approach often highlight the close parallels between distributed representations learned in connectionist models and neural coding in brain and often dismiss localist (Grandmother Cell) theories as biologically implausible. The author reviews a range a data that strongly challenge this claim and shows that localist models provide a better account of single-Cell recording studies. The author also contrast local and alternative distributed coding schemes (sparse and coarse coding) and argues that common rejection of Grandmother Cell theories in neuroscience is due to a misunderstanding about how localist models behave. The author concludes that the localist representations embedded in theories of perception and cognition are consistent with neuroscience; biology only calls into question the distributed representations often learned in PDP models.
Wang Ting - One of the best experts on this subject based on the ideXlab platform.
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Motor Learning Mechanism on the Neuron Scale
2014Co-Authors: Liu, Mr. Peilei, Wang TingAbstract:Based on existing data, we wish to put forward a biological model of motor system on the neuron scale. Then we indicate its implications in statistics and learning. Specifically, neuron firing frequency and synaptic strength are probability estimates in essence. And the lateral inhibition also has statistical implications. From the standpoint of learning, dendritic competition through retrograde messengers is the foundation of conditional reflex and Grandmother Cell coding. And they are the kernel mechanisms of motor learning and sensory motor integration respectively. Finally, we compare motor system with sensory system. In short, we would like to bridge the gap between molecule evidences and computational models.Comment: 8 pages, 4 figure
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A Quantitative Neural Coding Model of Sensory Memory
2014Co-Authors: Liu Peilei, Wang TingAbstract:The coding mechanism of sensory memory on the neuron scale is one of the most important questions in neuroscience. We have put forward a quantitative neural network model, which is self organized, self similar, and self adaptive, just like an ecosystem following Darwin theory. According to this model, neural coding is a mult to one mapping from objects to neurons. And the whole cerebrum is a real-time statistical Turing Machine, with powerful representing and learning ability. This model can reconcile some important disputations, such as: temporal coding versus rate based coding, Grandmother Cell versus population coding, and decay theory versus interference theory. And it has also provided explanations for some key questions such as memory consolidation, episodic memory, consciousness, and sentiment. Philosophical significance is indicated at last.Comment: 9 pages, 3 figure
