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potentials as “mismatch negativities” and are modelled as adaptive resonances (Car-
penter and Grossberg
2003
, Grossberg
1988
,Rose
2006
).
As successive neural populations respond to the stabilised perceptual images of
lower loops, higher semantic resonances are created as objects are recognised and
other sets of neural assemblies that are sensitive to their implications are activated.
As ensembles of neural assemblies that function as semantic “cognitive nodes” are
concurrently excited, evaluative and steering circuits are also being activated and
signals associated with hedonic valences become added to the circulating mixture
of signals. Both short term and long term memory processes play modulatory roles
in the pattern amplifications that go on in the loops, either facilitating or retarding
the amplification and buildup of particular circulating patterns. In this conception,
some sets of signals are limited to only one or two circuits that reciprocally con-
nect pairs of brain regions, while others of more general relevance are circulated
more broadly, through a global workspace. Sets of circuits related to evaluation of
the various consequences of action and its planning are activated and finally motor
execution programs and pattern generators are engaged to move muscles that act on
the external world.
15.5.4 Multidimensional Signals
Although modern neuroscience has identified specific neuronal populations and cir-
cuits that subserve all these diverse functions, there is much poorer understanding
of how these different kinds of informational considerations might be coherently
integrated. Although, most information processing appears to be carried out in local
brain regions by neural populations, a given region might integrate several different
kinds of signals. Traditional theories of neural networks assume very specific neu-
ronal interconnectivities and synaptic weightings, both for local and long-distance
connections. However, flexibly combining different kinds of information from dif-
ferent brain regions poses enormous implementational problems. On the other hand,
if different types of information can have their own recognisable signal types, then
this coordination problem is drastically simplified. If different signal types can be
nondestructively combined to form multidimensional vectors, then combinatorial
representation systems are much easier to implement. Communications problems
are further simplified if the multiple types of information can be sent concurrently
over the same transmission lines without a great deal of destructive interference.
15.5.5 Temporal Coding and Signal Multiplexing
Multiplexing of signals permits them to be combined nondestructively, broadcast,
and then demultiplexed by local assemblies that are tuned to receive them. Tempo-
ral coding of information in patterns of spikes lends itself to multidimensional sig-
nalling, multiplexed transmission, and broadcast strategies for long-distance neural
