Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence

1. Front Matter

   Pages I-XXVII

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2. Foundations of Connectionism and Biophysical Models of Neurons

   1. Dendrites: The Last-Generation Computers

      • O. Herreras, J. M. Ibarz, L. López-Aguado, P. Varona

      Pages 1-13

   2. Homogeneity in the Electrical Activity Pattern as a Function of Intercellular Coupling in Cell Networks

      • E. Andreu, R. Pomares, B. Soria, J. V. Sanchez-Andres

      Pages 14-20

   3. A Realistic Computational Model of the Local Circuitry of the Cuneate Nucleus

      • Eduardo Sroseanchez, Senrosesen Barro, Jorge Mariño, Antonio Canedo

      Pages 21-29

   4. Algorithmic Extraction of Morphological Statistics from Electronic Archives of Neuroanatomy

      • Ruggero Scorcioni, Giorgio A. Ascoli

      Pages 30-37

   5. What Can We Compute with Lateral Inhibition Circuits?

      • Josrosee Mira, Ana E. Delgado

      Pages 38-46

   6. Neuronal Models with Current Inputs

      • Jianfeng Fent

      Pages 47-54

   7. Decoding the Population Responses of Retinal Ganglions Cells Using Information Theory

      • J. M. Ferrández, M. Bongard, F. García de Quiros, J. A. Bolea, J. Ammermü, R. A. Normann et al.

      Pages 55-62

   8. Numerical Study of Effects of Co-transmission by Substance P and Acetylcholine on Synaptic Plasticity in Myenteric Neurons

      • Roustem Miftakov, James Christensen

      Pages 63-71

   9. Neurobiological Modeling of Bursting Response During Visual Attention

      • Reza Rajimehr, Leila Montaser Kouhsari

      Pages 72-80

   10. Sensitivity of Simulated Striate Neurons to Cross-Like Stimuli Based on Disinhibitory Mechanism

       • Konstantin A. Saltykov, Igor A. Shevelev

       Pages 81-86

   11. Synchronisation Mechanisms in Neuronal Networks

       • Santi Chillemi, Michele Barbi, Angelo Di Garbo

       Pages 87-94

   12. Detection of Oriented Repetitive Alternating Patterns in color Images

       • Tino Lourens, Hiroshi G. Okuno, Hiroaki Kitano

       Pages 95-107

   13. Synchronization in Brain — Assessment by Electroencephalographic Signals

       • Ernesto Pereda, Joydeep Bhattacharya

       Pages 108-116

   14. Strategies for the Optimization of Large Scale Networks of Integrate and Fire Neurons

       • Manuel A. Sánchez-Montañás

       Pages 117-125

3. Structural and Functional Models of Neurons

   1. A Neural Network Model of Working Memory (Processing of “What” and “Where” Information)

      • Tetsuto Minami, Toshio Inui

      Pages 126-133

   2. Orientation Selectivity of Intracortical Inhibitory Cells in the Striate Visual Cortex: A Computational Theory and a Neural Circuitry

      • Medhi N. Shirazi

      Pages 134-141

   3. Interpreting Neural Networks in the Frame of the Logic of Lukasiewicz

      • Claudio Moraga, Luis Salinas

      Pages 142-149

   4. Time-Dispersive Effects in the J. Gonzalo’s Research on Cerebral Dynamics

      • Isabel Gonzalo, Miguel A. Porras

      Pages 150-157

   5. Verifying Properties of Neural Networks

      • Pedro Rodrigues, J. Félix Costa, Hava T. Siegelmann

      Pages 158-165

Underlying most of the IWANN calls for papers is the aim to reassume some of the motivations of the groundwork stages of biocybernetics and the later bionics formulations and to try to reconsider the present value of two basic questions. The?rstoneis:“Whatdoesneurosciencebringintocomputation(thenew bionics)?” That is to say, how can we seek inspiration in biology? Titles such as “computational intelligence”, “arti?cial neural nets”, “genetic algorithms”, “evolutionary hardware”, “evolutive architectures”, “embryonics”, “sensory n- romorphic systems”, and “emotional robotics” are representatives of the present interest in “biological electronics” (bionics). Thesecondquestionis:“Whatcanreturncomputationtoneuroscience(the new neurocybernetics)?” That is to say, how can mathematics, electronics, c- puter science, and arti?cial intelligence help the neurobiologists to improve their experimental data modeling and to move a step forward towards the understa- ing of the nervous system? Relevant here are the general philosophy of the IWANN conferences, the sustained interdisciplinary approach, and the global strategy, again and again to bring together physiologists and computer experts to consider the common and pertinent questions and the shared methods to answer these questions.

• Connectionism
• Simulation
• algorithmic learning
• artificial neural networks
• biocomputing
• brain-like computations
• evolutionary algorithms
• genetic algorithms
• heuristics
• knowledge
• multi-objective optimization
• neurons
• reinforcement learning
• robot
• statistics
• algorithm analysis and problem complexity

• Departamento de Inteligencia Artificial Sanda del Rey, Universidad Nacional de Educación a Distancia, Madrid, Spain

  José Mira

• Departamento de Arquitectura y Tecnología de Computadores, Universidad de Granada, Granada, Spain

  Alberto Prieto

Policies and ethics