Above are papers related to the following paper: [Paper_ID] Paper #7296. 	[Title] Modeling Cortical Plasticity Based on Adapting Lateral Interaction [Abstract] A neural network model called LISSOM for the cooperative self-organization of afferent and lateral connections in cortical maps is applied to modeling cortical plasticity. After self-organization, the LISSOM maps are in a dynamic equilibrium with the input, and reorganize like the cortex in response to simulated cortical lesions and intracortical microstimulation. The model predicts that adapting lateral interactions are fundamental to cortical reorganization, and suggests techniques to hasten recovery following sensory cortical surgery. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #7297. 	[Title] Self-Organization and Functional Role of Lateral Connections and Multisize Receptive Fields in the Primary Visual Cortex [Abstract] Cells in the visual cortex are selective not only to ocular dominance and orientation of the input, but also to its size and spatial frequency. The simulations reported in this paper show how size selectivity could develop through Hebbian self-organization, and how receptive fields of different sizes could organize into columns like those for orientation and ocular dominance. The lateral connections in the network self-organize cooperatively and simultaneously with the receptive field sizes, and produce patterns of lateral connectivity that closely follow the receptive field organization. Together with our previous work on ocular dominance and orientation selectivity, these results suggest that a single Hebbian self-organizing process can give rise to all the major receptive field properties in the visual cortex, and also to structured patterns of lateral interactions, some of which have been verified experimentally and others predicted by the model. The model also suggests a functional role for the self-organized structures: The afferent receptive fields develop a sparse coding of the visual input, and the recurrent lateral interactions eliminate redundancies in cortical activity patterns, allowing the cortex to efficiently process massive amounts of visual information. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #7272. 	[Title] Tilt Aftereffects in a Self-Organizing Model of the Primary Visual Cortex [Abstract]  Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #7276. 	[Title] Self-Organization and Segmentation in a Laterally Connected Orientation Map of Spiking Neurons [Abstract] The RF-SLISSOM model integrates two separate lines of research on computational modeling of the visual cortex. Laterally connected self-organizing maps have been used to model how afferent structures such as orientation columns and patterned lateral connections can simultaneously self-organize through input-driven Hebbian adaptation. Spiking neurons with leaky integrator synapses have been used to model image segmentation and binding by synchronization and desynchronization of neuronal group activity. Although these approaches differ in how they model the neuron and what they explain, they share the same overall layout of a laterally connected two-dimensional network. This paper shows how both self-organization and segmentation can be achieved in such an integrated network, thus presenting a unified model of development and functional dynamics in the primary visual cortex. Please summarise all the given information.

Above are papers related to the following paper: [Paper_ID] Paper #763181. 	[Title] A Neural Network Model of Visual Tilt Aftereffects [Abstract] RF-LISSOM, a self-organizing model of laterally connected orientation maps in the primary visual cortex, was used to study the psychological phenomenon known as the tilt aftereffect. The same self-organizing processes that are responsible for the long-term development of the map and its lateral connections are shown to result in tilt aftereffects over short time scales in the adult. The model allows observing large numbers of neurons and connections simultaneously, making it possible to relate higher-level phenomena to low-level events, which is difficult to do experimentally. The results give computational support for the idea that direct tilt aftereffects arise from adaptive lateral interactions between feature detectors, as has long been surmised. They also suggest that indirect effects could result from the conservation of synaptic resources during this process. The model thus provides a unified computational explanation of self-organization and both direct and indirect tilt aftereffects in the primary visual cortex. Please summarise all the given information.

Paper #7296 has the title `Modeling Cortical Plasticity Based on Adapting Lateral Interaction  
` and the abstract `A neural network model called LISSOM for the cooperative self-organization of afferent and lateral connections in cortical maps is applied to modeling cortical plasticity. After self-organization, the LISSOM maps are in a dynamic equilibrium with the input, and reorganize like the cortex in response to simulated cortical lesions and intracortical microstimulation. The model predicts that adapting lateral interactions are fundamental to cortical reorganization, and suggests techniques to hasten recovery following sensory cortical surgery. 
`.
Question: Which category should Paper #7296 be classified as ?
You can select one from ['Neural_Networks', 'Case_Based', 'Theory', 'Reinforcement_Learning', 'Probabilistic_Methods', 'Rule_Learning', 'Genetic_Algorithms'].


Paper #7296 has the title `Modeling Cortical Plasticity Based on Adapting Lateral Interaction  
` and the abstract `A neural network model called LISSOM for the cooperative self-organization of afferent and lateral connections in cortical maps is applied to modeling cortical plasticity. After self-organization, the LISSOM maps are in a dynamic equilibrium with the input, and reorganize like the cortex in response to simulated cortical lesions and intracortical microstimulation. The model predicts that adapting lateral interactions are fundamental to cortical reorganization, and suggests techniques to hasten recovery following sensory cortical surgery. 
`.
Question: Which category should Paper #7296 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