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 "Dyslexic and Category-Specific Aphasic Impairments in a Self-Organizing Feature Map Model of the Lexicon"):
  Abstract: DISLEX is an artificial neural network model of the mental lexicon. It was built to test com-putationally whether the lexicon could consist of separate feature maps for the different lexical modalities and the lexical semantics, connected with ordered pathways. In the model, the orthographic, phonological, and semantic feature maps and the associations between them are formed in an unsupervised process, based on cooccurrence of the lexical symbol and its meaning. After the model is organized, various damage to the lexical system can be simulated, resulting in dyslexic and category-specific aphasic impairments similar to those observed in human patients.

Includes members:
  Member "Cholinergic suppression of transmission may allow combined associative memory function and self-organization in the neocortex.":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "LEARNING TO AVOID COLLISIONS: A REINFORCEMENT LEARNING PARADIGM FOR MOBILE ROBOT NAVIGATION")
  Member "Book Review  Introduction to the Theory of Neural Computation Reviewed by: 2":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "Induction of Multiscale Temporal Structure")
  Member "SCRIPT RECOGNITION WITH HIERARCHICAL FEATURE MAPS":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "SELF-ORGANIZING PROCESS BASED ON LATERAL INHIBITION AND SYNAPTIC RESOURCE REDISTRIBUTION")
  Member "SELF-ORGANIZING PROCESS BASED ON LATERAL INHIBITION AND SYNAPTIC RESOURCE REDISTRIBUTION":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "How Lateral Interaction Develops in a Self-Organizing Feature Map")

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