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                    112                                     Biomimetics: Biologically Inspired Technologies

                    only active (or highly excited) neurons can launch such a process and while the transponder neurons
                    are excited, they are not active or highly excited (i.e., active, or highly excited, neurons — a rare
                    state that can only exist following a confabulation information processing operation — are the only
                    ones that can unconditionally excite other neurons) However, as with transponder neurons, if
                    a neuron receives a high-enough number of simultaneous inputs from active neurons — even
                    through unstrengthened synapses, and in the absence of any operation command input — it will
                    become excited. Finally, excited neurons can excite other neurons if those other neurons reside in
                    a lexicon which is simultaneously also receiving operation command signal input (this is what
                    happens when knowledge is used and when short-term memory learning takes place, as will be
                    discussed below).
                       The wiring of the symbol and transponder neuron axons is (largely) completed in childhood and
                    then remains (at least for our purposes here) essentially fixed for life. Again, the gross statistics of
                    this wiring are genetically determined; but the local details are random.
                       A relatively small number (say, 1 to 25% — a genetically controlled percentage that deliberately
                    varies across cortex) of the target region neurons representing symbol l will just happen to each
                    receive many synaptic inputs from a subset of the transponder neurons (Figure 3.A.5 illustrates the
                    axonal connections from c transponder neurons for only one of these few l neurons). These
                    particular l neurons complete the knowledge link. If all of the neurons representing symbol l are
                    already active at the moment these synaptic inputs arrive, then (in the event that they have not been
                    previously permanently strengthened) the transponder neuron synapses that land on this subset of
                    them will be temporarily strengthened (this is called short-term memory). During the next sleep
                    period, if this causal pairing of symbols c and l is again deliberately rehearsed, these temporarily
                    strengthened synapses may be more lastingly strengthened (this is medium-term memory). If this
                    link is subsequently rehearsed more over the next few days, these synapses may be permanently
                    strengthened (this is long-term memory). It is important to note that the synapses from the c neurons
                    to the c transponder neurons are generally not strengthened. This is because the transponder
                    neurons are not meaningfully active at the time when these inputs arrive. Only deliberate usage
                    of a link with immediately prior co-occurrence of both source symbol and target symbol
                    activity causes learning. This was, roughly, the learning hypothesis that Donald Hebb advanced 56
                    years ago (Hebb, 1949).
                       Note again that the transponder neurons that represent a symbol c will always be the same;
                    independent of which target lexicon(s) are to be linked to. Thus, c transponder neurons must send
                    a sufficiently large number of axons to all of the lexicons containing symbols to which symbol c
                    might need to connect. The theory posits that genetic control of the distribution of axons (nomin-
                    ally) ensures that all of the potentially necessary knowledge links can be formed. Obviously, this
                    postulated design could be analyzed, since the rough anatomy and statistics of cortical axon
                    fascicles are known. Such an analysis might well be able to support, or raise doubts, that this
                    hypothesis is capable of explaining cortical knowledge.
                       Cognitive functions where confabulations always yield zero or one winners, because at most one
                    symbol has anything close to enough knowledge links from the assumed facts, do not need precisely
                    weighted knowledge links. In cortical modules which only require such confabulations, knowledge
                    links terminating within that module are hypothesized by the theory to be essentially binary in
                    strength: either completely unstrengthened (i.e., as yet unused) or strong (strengthened to near
                    maximum). Such modules together probably encompass a majority of cortex.
                       However, other cognitive functions (e.g., language) do require each knowledge link to have a
                    strength that is directly related by some fixed function to p(cjl). The theory’s hypothesis as to how
                    these weightings arise is now sketched.
                       Although the mechanisms of synaptic modification are not yet well understood (particularly
                    those connected with medium-term and long-term memory), research has established that ‘‘Heb-
                    bian’’ synaptic strengthening does occur (Cowan et al., 2001). This presumably can yield a
                    transponder neuron to target symbol neuron synapse strength directly related to the joint probability
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