human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge groups papers that share a common citing paper.

Details of the hypergraph:
Center hyperedge (induced by source paper "Modeling dynamic receptive field changes in primary visual cortex using inhibitory learning"):
  Abstract: The position, size, and shape of the visual receptive field (RF) of some primary visual cortical neurons change dynamically, in response to artificial scotoma conditioning in cats (Pettet & Gilbert, 1992) and to retinal lesions in cats and monkeys (Darian-Smith & Gilbert, 1995). The "EXIN" learning rules (Marshall, 1995) are used to model dynamic RF changes. The EXIN model is compared with an adaptation model (Xing & Gerstein, 1994) and the LISSOM model (Sirosh & Miikkulainen, 1994; Sirosh et al., 1996). To emphasize the role of the lateral inhibitory learning rules, the EXIN and the LISSOM simulations were done with only lateral inhibitory learning. During scotoma conditioning, the EXIN model without feedforward learning produces centrifugal expansion of RFs initially inside the scotoma region, accompanied by increased responsiveness, without changes in spontaneous activation. The EXIN model without feedforward learning is more consistent with the neurophysiological data than are the adaptation model and the LISSOM model. The comparison between the EXIN and the LISSOM models suggests experiments to determine the role of feedforward excitatory and lateral inhibitory learning in producing dynamic RF changes during scotoma conditioning.

Includes members:
  Member "Self-Organization and Functional Role of Lateral Connections and Multisize Receptive Fields in the Primary Visual Cortex":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex.")
  Member "Plasticity in cortical neuron properties: Modeling the effects of an NMDA antagonist and a GABA":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Modeling dynamic receptive field changes produced by intracortical microstimulation")
  Member "Rearrangement of receptive field topography after intracortical and peripheral stimulation: The role of plasticity in":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "Generalization and Exclusive Allocation of Credit in Unsupervised Category Learning")
  Member "Modeling dynamic receptive field changes produced by intracortical microstimulation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "Plasticity in cortical neuron properties: Modeling the effects of an NMDA antagonist and a GABA")

Question: Please tell me which class the citing paper (i.e., the source paper of the center hyperedge) belongs to. The 7 classes are: Neural_Networks, Reinforcement_Learning, Probabilistic_Methods, Theory, Genetic_Algorithms, Case_Based, Rule_Learning. Directly output the class name.

gpt: Neural_Networks