David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Philosophical Explorations (1999)
In attempts to formulate a computational understanding of brain function, one of the fundamental concerns is the data structure by which the brain represents information. For many decades, a conceptual framework has dominated the thinking of both brain modelers and neurobiologists. That framework is referred to here as "classical neural networks." It is well supported by experimental data, although it may be incomplete. A characterization of this framework will be offered in the next section. Difficulties in modeling important functional aspects of the brain on the basis of classical neural networks alone have led to the recognition that another, general mechanism must be invoked to explain brain function. That mechanism I call "binding." Binding by neural signal synchrony had been mentioned several times in the liter ature (Lege´ndy, 1970; Milner, 1974) before it was fully formulated as a general phenomenon (von der Malsburg, 1981). Although experimental evidence for neural syn chrony was soon found, the idea was largely ignored for many years. Only recently has it become a topic of animated discussion. In what follows, I will summarize the nature and the roots of the idea of binding, especially of temporal binding, and will discuss some of the objec tions raised against it.
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Citations of this work BETA
Sharon Zmigrod & Bernhard Hommel (2011). The Relationship Between Feature Binding and Consciousness: Evidence From Asynchronous Multi-Modal Stimuli. Consciousness and Cognition 20 (3):586-593.
Cyriel M. A. Pennartz (2009). Identification and Integration of Sensory Modalities: Neural Basis and Relation to Consciousness. Consciousness and Cognition 18 (3):718-739.
Chrisantha Fernando (2013). From Blickets to Synapses: Inferring Temporal Causal Networks by Observation. Cognitive Science 37 (8):1426-1470.
Ken McRae Chris McNorgan, Jackie Reid (2011). Integrating Conceptual Knowledge Within and Across Representational Modalities. Cognition 118 (2):211.
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