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King
of the Cortex:
Anterior PFC
By Chris Chatham
As enigmatic as prefrontal function seems to be, the anterior portions
of prefrontal cortex (aPFC) are even more mysterious. This results
partly from the fact that aPFC is particularly difficult to access
and study electrophysiologically in nonhuman primates, as Ramnani
and Owen note in their 2004 Nature Reviews Neuroscience
article,
and so detailed neuroanatomical investigations of aPFC have been
conducted only recently. The authors report how this work has led
to a breakthrough in the understanding of aPFC's computations. Ramnani and Owen review Brodmann's
early analysis of aPFC, also known as Brodmann's area 10 (BA10).
This region occupies most of
the frontal pole and shows distinct cytoarchitecture from surrounding
regions. Unfortunately there are several problems with this straightforward
association of aPFC with BA10. First, this association makes
BA10 an impractically large region, so some have argued for the
distinction
between subregions of BA10. Second, in monkeys, this area is
not occupied by BA10, but by BA12. Considering these difficulties,
Ramnani & Owen restrict their analysis of aPFC to BA10p, the
area of aPFC that lies directly on the frontal pole and includes
the most anterior regions of the frontal gyri.
The dendrites of PFC neurons have
more spines that neurons found elsewhere in cortex, suggesting
that PFC is particularly involved
in "integrating" multiple inputs. This interesting fact
is even more true of aPFC, which Ramnani & Owen claim has a
higher spine density than even other regions of PFC despite having
a lower overall number of neurons. Unlike all other PFC areas,
which are interconnected with low-level association areas, aPFC
is reciprocally interconnected only with an "executive network" of
purely multi-modal regions. Tellingly, this includes anterior temporal
cortex (thought to be involved in object identity processing),
cingulate cortex (thought to be involved in conflict monitoring/detection),
and other regions of PFC (broadly involved in the active maintenance
of information).
Based on this knowledge of aPFC
neuroanatomy Ramnani and Owen analyze several theories of aPFC
function, reviewed in turn
below.
Internal State Model
This theory suggests that aPFC is
important for introspection, which often results in spontaneous,
stimulus-indepepdent
neural activity. This theory can account for the greater
activation
of aPFC during baseline fMRI tasks (such as when subjects
are simply
asked to stare at a screen) relative to tasks that seem
to involve more cognitive demands. Likewise, this theory
accounts
for higher
aPFC activity during tasks involving episodic memory
relative to recognition only. Ramnani & Owen conclude that while this model
may accurately describe some functions of aPFC, other PFC regions
are also likely involved in similar processes.
Memory Retrieval Models
The authors also review "memory retrieval" models of
aPFC function, which suggest that aPFC generates ("gates")
or evaluates memory search strategies, such as those that are particularly
active for source memory (memory for where or under what circumstances
a particular item was experienced). Ramnani & Owen conclude
that this theory is useful for explaining aPFC activation in some
tasks, but is probably too specific to be a good model for the
general functions of aPFC.
Prospective Memory Model
Others have suggested that aPFC
is important for prospective memory, which is "memory for the future" (i.e., I need to pick
up milk on the way home from work today.) Note the similarities
between this account and the temporal cascade model of Koechlin
et al. described yesterday, in which increasingly anterior regions
maintain information for increasingly long periods of time. Unfortunately,
Ramnani & Owen conclude that this theory also seems too specific,
since tasks that do not clearly utilize prospective memory also
activate aPFC.
Cognitive Branching Model
Yet others have suggested that aPFC
is important for maintenance of meta-level goals while subgoals
are
being specified
and manipulated. Ramnani & Owen note that this model is very vague, in that
every cognitive task can be thought to involve almost any number
of subgoals.
Relational Integration Model
This theory holds that aPFC is important
for considering how two distinct things
relate to one another;
Ramnani & Owen review
some work that has been successful in distinguishing this from
general mental effort. The authors suggest this theory is "off
the mark" in that it is both too specific (it cannot explain
activation in other tasks that do not seem to involve relational
integration) and too broad (dlPFC seems to show a similar response
profile).
"Operation Coordination" Model
Finally, Ramnani & Owen propose their own model of aPFC function,
which is essentially a reinterpretation of each of the above models
according to information processing demand rather than task-specific
demands. This "operation coordination" model proposes
that aPFC is utilized when a goal requires the use of two or more
distinct cognitive operations in order to monitor and integrate
their outcomes.
Conclusions
Ramnani & Owen's "operation coordination" model
of aPFC function provided number of predictions that have subsequently been supported in areas as diverse as exploratory behavior, brain-computer
interfaces, and traditional n-back working memory tasks. aPFC may
also contribute to the "mixing cost" often observed in
task-switching paradigms.
Most importantly, this view of
aPFC function falls neatly
in line with
an emerging
view about the
functional architecture
of PFC.
PFC can be viewed as a cascading
hierarchy of supramodal processors,
each recursively connected
with lower regions and biasing their
representations.
aPFC
appears to
sit at the top
of this hierarchy.
As with all theories of PFC
function, however, this one
can seem a
little too fuzzy. For
example, how
does one
distinguish
between "cognitve
operations"? Is aPFC activity always increased when a task
involves 2 relative to 1 cognitive processes (however we might
define them), or does PFC perform more dynamic load balancing?
Finally, how might non-human primates manifest mixing costs or
other putative effects of "operation coordination," given
that their frontal pole contains BA12 rather than BA10?
Chris
Chatham is a graduate student at the University of Colorado,
Boulder, and author of the Developing
Intelligence weblog.
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