WBA en

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==== Brain Organs ====
As the [[WBA Product]] specification requires a WBA model to have correspondence with actual brain organs, 
this page refers to them to give an 'image' of WBA.\\  A WBA model would have to incorporate at least the first three components (the perceptual system, the hippocampus, and the pre-frontal-cortex-basal-ganglia-thalamus loop).\\
Here, it is important that a WBA model is constructed so that it can perform more than one generic class of tasks (as WBA aims for AGI).

//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 [[https://en.wikipedia.org/wiki/Two-streams_hypothesis|ventral and dorsal streams]].\\  The feature-place separation by the two streams would be related to [[https://en.wikipedia.org/wiki/Binding_problem|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 WBA model would also have to take into account the fact that the cascade is richly bi-directional with afferent and efferent connections.
=== Hippocampus ===
The [[http://www.scholarpedia.org/article/Models_of_hippocampus|hippocampus]], consisting of several sub-regions, is supposed to be responsible to the following cognitive functions among others.
  * Transferring mid-term memory into long-term memory
  * Navigation (at least in rodents; see [[http://www.scholarpedia.org/article/Grid_cells|the grid cells and place cells]])
As the place cells respond to places where the subject has visited, they are supposed to be related also 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.: [[http://psych.colorado.edu/~oreilly/papers/OReillyFrank06_pbwm.pdf|Making Working Memory Work: A Computational Model of Learning in the Frontal Cortex and Basal Ganglia]], Neural Computation, 18, pp.283-328 (2006)
[[CCNBook-Motor summary]]
=== Amygdala ===
The amygdala is supposed to be related to affect.\\
See [[http://www.scholarpedia.org/article/Amygdala|Amygdala@Scholarpedia]] for detailed explanation.
=== 'Language Areas' ===
If you are to make a human-level WBA model, you definitely have to take the 'language areas' into account.\\
[[https://en.wikipedia.org/wiki/Wernicke%27s_area|Wernicke's area]] and [[https://en.wikipedia.org/wiki/Broca%27s_area|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: [[http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3733003/|Recurrent temporal networks and language acquisition—from corticostriatal neurophysiology to reservoir computing]], Frontiers in Psychology, 4: 500 (2013).
==== References ====
  * [[https://grey.colorado.edu/CompCogNeuro/index.php/CCNBook/Main|The Computational Cognitive Neuroscience Book]]
  * [[http://blog.agi.io/2015/12/how-to-build-general-intelligence.html|How to build a General Intelligence: Circuits and Pathways]]
  * [[http://www.reservoir-computing.org|Reservoir-Computing.org]]