Explaining synchrony in feed-forward networks: Are McCulloch-Pitts neurons good enough?

Biological Cybernetics

Volumn 89, Issue 4, 2003, Pages 237-241

  Nowotny, T ^a   Huerta, R ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL CELL CULTURE; FUNCTIONS; ITERATIVE METHODS; LIVING SYSTEMS STUDIES; MATHEMATICAL MODELS; MATRIX ALGEBRA; NEUROLOGY; NORMAL DISTRIBUTION;

GAUSSIAN DISTRIBUTION; HEAVISIDE FUNCTION; ITERATIVELY CONSTRUCTED NETWORKS; MCCULLOCH-PITTS NEURONS; SYNCHRONY; THEORETICAL NEUROSCIENCE;

FEEDFORWARD NEURAL NETWORKS;

ANIMALIA;

ACTION POTENTIAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; CORTICAL SYNCHRONIZATION; METHODOLOGY; NERVE CELL; PHYSIOLOGY;

ACTION POTENTIALS; CORTICAL SYNCHRONIZATION; NEURAL NETWORKS (COMPUTER); NEURONS;

EID: 0344585034     PISSN: 03401200     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00422-003-0431-9     Document Type: Letter

References (5)

1. Abeles M (1991) Corticonics: neural circuits of the cerebral cortex, 1st edn Cambridge University Press, New York
2. Cateau H, Fukai T (2001) Fokker-Planck approach to the pulse packet propagation in synfire chain. Neural Networks 14: 675-685
3. McCulloch WS, Pitts W (1943) Logical calculus of ideas immanent in nervous activity. Bull Math Biophys 5: 115-133
4. Reyes AD (2003) Synchrony-dependent propagation of firing rate in iteratively constructed networks in vitro. Nature Neurosci 6: 593-599
5. Segev I (2003) Synchrony is stubborn in feedforward cortical networks. Nature Neurosci 6: 543-544