Above are papers related to the following paper: [Paper_ID] Paper #1136110. 	[Title] A Theory of Visual Relative Motion Perception: Grouping, Binding, and Gestalt Organization [Abstract] The human visual system is more sensitive to the relative motion of objects than to their absolute motion. An understanding of motion perception requires an understanding of how neural circuits can group moving visual elements relative to one another, based upon hierarchical reference frames. We have modeled visual relative motion perception using a neural network architecture that groups visual elements according to Gestalt common-fate principles and exploits information about the behavior of each group to predict the behavior of individual elements. A simple competitive neural circuit binds visual elements together into a representation of a visual object. Information about the spiking pattern of neurons allows transfer of the bindings of an object representation from location to location in the neural circuit as the object moves. The model exhibits characteristics of human object grouping and solves some key neural circuit design problems in visual relative motion perception. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #756061. 	[Title] In  Unsmearing Visual Motion: Development of Long-Range Horizontal Intrinsic Connections [Abstract] Human vision systems integrate information nonlocally, across long spatial ranges. For example, a moving stimulus appears smeared when viewed briefly (30 ms), yet sharp when viewed for a longer exposure (100 ms) (Burr, 1980). This suggests that visual systems combine information along a trajectory that matches the motion of the stimulus. Our self-organizing neural network model shows how developmental exposure to moving stimuli can direct the formation of horizontal trajectory-specific motion integration pathways that unsmear representations of moving stimuli. These results account for Burr's data and can potentially also model other phenomena, such as visual inertia. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #1136446. 	[Title] The role of afferent excitatory and lateral inhibitory synaptic plasticity in visual cortical ocular dominance [Abstract]  Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #1136447. 	[Title] Plasticity in cortical neuron properties: Modeling the effects of an NMDA antagonist and a GABA [Abstract] Infusion of a GABA agonist (Reiter & Stryker, 1988) and infusion of an NMDA receptor antagonist (Bear et al., 1990), in the primary visual cortex of kittens during monocular deprivation, shifts ocular dominance toward the closed eye, in the cortical region near the infusion site. This reverse ocular dominance shift has been previously modeled by variants of a covariance synaptic plasticity rule (Bear et al., 1990; Clothiaux et al., 1991; Miller et al., 1989; Reiter & Stryker, 1988). Kasamatsu et al. (1997, 1998) showed that infusion of an NMDA receptor antagonist in adult cat primary visual cortex changes ocular dominance distribution, reduces binocularity, and reduces orientation and direction selectivity. This paper presents a novel account of the effects of these pharmacological treatments, based on the EXIN synaptic plasticity rules (Marshall, 1995), which include both an instar afferent excitatory and an outstar lateral inhibitory rule. Functionally, the EXIN plasticity rules enhance the efficiency, discrimination, and context-sensitivity of a neural network's representation of perceptual patterns (Marshall, 1995; Marshall & Gupta, 1998). The EXIN model decreases lateral inhibition from neurons outside the infusion site (control regions) to neurons inside the infusion region, during monocular deprivation. In the model, plasticity in afferent pathways to neurons affected by the pharmacological treatments is assumed to be blocked , as opposed to previous models (Bear et al., 1990; Miller et al., 1989; Reiter & Stryker, 1988), in which afferent pathways from the open eye to neurons in the infusion region are weakened . The proposed model is consistent with results suggesting that long-term plasticity can be blocked by NMDA antagonists or by postsynaptic hyperpolarization (Bear et al., 1990; Dudek & Bear, 1992; Goda & Stevens, 1996; Kirkwood et al., 1993). Since the role of plasticity in lateral inhibitory pathways in producing cortical plasticity has not received much attention, several predictions are made based on the EXIN lateral inhibitory plasticity rule. Please summarise all the given information.

Paper #1136110 has the title `A Theory of Visual Relative Motion Perception: Grouping, Binding, and Gestalt Organization  
` and the abstract `The human visual system is more sensitive to the relative motion of objects than to their absolute motion. An understanding of motion perception requires an understanding of how neural circuits can group moving visual elements relative to one another, based upon hierarchical reference frames. We have modeled visual relative motion perception using a neural network architecture that groups visual elements according to Gestalt common-fate principles and exploits information about the behavior of each group to predict the behavior of individual elements. A simple competitive neural circuit binds visual elements together into a representation of a visual object. Information about the spiking pattern of neurons allows transfer of the bindings of an object representation from location to location in the neural circuit as the object moves. The model exhibits characteristics of human object grouping and solves some key neural circuit design problems in visual relative motion perception. 
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Question: Which category should Paper #1136110 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #1136110 has the title `A Theory of Visual Relative Motion Perception: Grouping, Binding, and Gestalt Organization  
` and the abstract `The human visual system is more sensitive to the relative motion of objects than to their absolute motion. An understanding of motion perception requires an understanding of how neural circuits can group moving visual elements relative to one another, based upon hierarchical reference frames. We have modeled visual relative motion perception using a neural network architecture that groups visual elements according to Gestalt common-fate principles and exploits information about the behavior of each group to predict the behavior of individual elements. A simple competitive neural circuit binds visual elements together into a representation of a visual object. Information about the spiking pattern of neurons allows transfer of the bindings of an object representation from location to location in the neural circuit as the object moves. The model exhibits characteristics of human object grouping and solves some key neural circuit design problems in visual relative motion perception. 
`.
Question: Which category should Paper #1136110 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].

This paper should be classified into: Neural_Networks