Information Technology Reference
In-Depth Information
Table 9.1: Server name, major function, and brain structure
Server
Brain structure
Major function (Processing logic)
Eye
Eye, LGN, SC, Visual pathway
Visual sampling and signal
transmission
VSen
Distributed parallel area, superior
frontal sulcus, dorsal and ventral
system
Visual sensory memory and
perception
Pho
Left posterior parietal cortex,
inferior parietal lobe
Phonological loop to store
auditoria
and textual information
CE
Dorsal lateral prefrontal cortex and
ACC
Mental process and response
inhibition and selection
BG
Basal ganglia
Motor program retrieval
LTPM
Striatal and cerebellar systems
Long-term procedural knowledge
storage
SMA
Supplementary motor area and
pre-SMA
Motor program assembly, error
detection, and bimanual
coordination
M1
Primary motor cortex
Addressing spinal motorneourons
S1
Somatosensory cortex
Sending the sensory information to
other areas
Hand
-
Execution of motor movement
functions but others may not (see Table 9.1). Because the routes of the queuing net-
work are composed of different brain areas (servers), different routes chosen by the
entities may lead to different information processing speeds or errors. If the entities
try to maximize response time performance, they may choose an optimal route that
maximizes speed, but may not minimize error. Some routes, however, may maxi-
mize both performance measures. Therefore, in different situations, different routes
may be chosen by the entities which activate different brain areas (servers). This
ability to have different routes becoming active forms the dynamic, self-organization
aspect of the queuing network. Consequently, there are two levels of learning within
the queuing network: (1) learning processes at the individual server level and (2)
self-organization or routes of the queuing network that change depending on the
stages of learning or the type of stimuli presented.
Learning Processes of the Individual Servers
In the motor learning process, the basal ganglia, striatal, and cerebellar systems
(BG and LTPM servers) play a major role in procedural knowledge acquisition [2].
Therefore, the current model focuses on the BG and the LTPM servers in quantifying
the learning processes of individual servers. It is assumed that the time for the BG
server to retrieve a motor program from the LTPM decreases exponentially as a
function of the number of practice trials (see Equation 9.1). Because the exponential
function fits learning processes of memory search, motor learning, visual search,
