Differences

This shows you the differences between two versions of the page.

--- brain_organs [2016/01/03 21:20] – created n.arakawa
+++ brain_organs [2021/12/11 10:36] (current) – [References] n.arakawa
@@ Line 1: / Line 1: @@
 ==== Brain Organs ====
-The [[WBA Product]] specification requires a WBA model to have correspondence with actual brain organs.\\
+As 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).
+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.
+//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 model also has to take into account the fact that the cascade is richly bi-directional with afferent and efferent connections.
+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 hippocampus, consisting of several sub-regions, is supposed to be responsible to the following cognitive functions among others.
+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 the places the subject has visited, it is supposed to be related to long-term memory.\\
+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 ===
@@ Line 18: / Line 19: @@
 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)
+  * 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)
+  * [[https://grey.colorado.edu/CompCogNeuro/index.php/CCNBook/Motor|CCNBook Motor]] ([[CCNBook-Motor summary|summary]])
+  * [[https://grey.colorado.edu/CompCogNeuro/index.php/CCNBook/Executive|CCNBook Executive]] ([[CCNBook-Executive summary|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 make a human-level WBA model, you definitely have to take the 'language areas' into account.\\
+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]]
+  * [[https://compcogneuro.org/|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]]
+  * [[List of Models]]