Igor Aleksander: Brain

Igor Aleksander is scientist. Explore interesting quotes on brain.
Igor Aleksander: 18 quotes0 likes

“The point of a brain is that it's not one huge neural network with feedback, it has up to 50 to 60 identified areas, all of which have feedback and all of which are capable of knowledge storage. We've got a complex system and, within this complex system, we can start discovering what the mechanisms that support deliberation are. Consciousness must come out of these interactions.”

Igor Aleksander

The simple things are hardest (2005)

“A neural network is a massively parallel distributed processor that has a natural propensity for storing experiential knowledge and making it available for use. It resembles the brain in two respects:
1. Knowledge is acquired by the network through a learning process.
2. Interneuron connection strengths known as synaptic weights are used to store the [[knowledge].”

Igor Aleksander

As cited in: Brian D. Ripley (2008) Pattern Recognition and Neural Networks. p.4
An introduction to neural computing (1990)

“Trying to understand the brain's abilities leads to philosophical difliculties. Penrose (1994) argues that the task is sterile and that science, including neural networks, has not yet advanced to the stage where it can explain conscious thought. At the other extreme there are philosophers such as Fodor (1975) who believed that thought has language-like properties and can be analysed in the same logical way as one can anlayse the structure of language.”

Igor Aleksander

Source: An introduction to neural computing (1990), p. 242

“Neural computing is the study of cellular networks that have a natural property for storing experimental knowledge. Such systems bear a resemblance to the brain in the sense that knowledge is acquired through training rather than programming and is retained due to changes in node functions. The knowledge takes the form of stable states or cycles of states in the operation of the et. A central property of such nets is to recall these states or cycles in response to the presentation of cues.”

Igor Aleksander

Aleksander & Morton (1989) Neural computing architectures: the design of brain-like machines. p.2 as cited in: M.A. Lovell et al. (1997) Developments in petrophysics. p.169