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Brain Organs

The WBA Product specification requires a WBA model to have correspondence with actual brain organs.
So this page refers to concrete brain organs to give an 'image' of WBA.
A WBA would have to incorporate at least the first three components (the perceptual system, the hippocampus, and the pre-frontal-cortex-basal-ganglia-thalamus loop).

Note that this page is under construction.

Two-Stream Perceptual System

It is hypothesized that the visual and auditory systems in the brain are separated into ventral and dorsal streams.
The feature-place separation by the two streams would be related to the binding problem (at least the binding of information on perceptual features and their locations).
At least the ventral stream consists of a cascade of cortical regions, forming a 'deep' network. A model also has to take into account the fact that the cascade is richly bi-directional with afferent and efferent connections.


The hippocampus, consisting of several sub-regions, is supposed to be responsible to the following cognitive functions among others.

As the place cells respond to the places the subject has visited, it is supposed to be related to long-term memory.
The circuitry of the hippocampus has been well studied.

Pre-frontal Cortex, Basal Ganglia and Thalamus

These organs, forming a circuit (loop), are supposed to be involved in (action) planning and execution.
The basal ganglia are hypothesized to use reinforcement learning principles.
For a computational model, see
O'Reilly et al.: Making Working Memory Work: A Computational Model of Learning in the Frontal Cortex and Basal Ganglia, Neural Computation, 18, pp.283-328 (2006)


The amygdala is supposed to be related to affect.
See Amygdala@Scholarpedia for detailed explanation.

'Language Areas'

If you make a human-level WBA model, you definitely have to take the 'language areas' into account.
Wernicke's area and Broca's area are two well known language areas, where the former is hypothesized to be involved in language comprehension and the latter speech production.
For a computational model, see
P. F. Dominey: Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing, Frontiers in Psychology, 4: 500 (2013).