Next: Retrieval
Up: Recognition, retrieval and dynamical
Previous: Recognition, retrieval and dynamical
In this first example, we have learned one period-3 elementary
sequence (
). We then run the spontaneous
dynamics (1), and present different input signals, some
of them corresponding to the learned sequence, and others being
unknown (Fig.4). The point is to check that the
feedback signal (i) is stimulus-dependent and (ii) can adapt
dynamically to its inputs.
Figure:
Activation dynamics, after learning the elementary
sequence
, while presenting different stimuli.
Input changes take place at
(Input shift) and
(reverse temporal order).
,
, other
parameters are in Tab.1. - a - Neuronal
activity on secondary layer. 20 individual signals are
represented, with their mean activity. - b - Input signal
(I) and Feedback reinforcement (F). Only the values corresponding
to the three first primary neurons are represented between
and
(some time steps have been discarded for readability).
|
During the 30 first steps, the input stimulus corresponds to the
learned one. After 10-12 transient steps, the system reaches its
attractor, and the feedback signal is activated.
At time
, a phase shift occurs on the input signal. The
misfit between input and feedback signals leads to a transitory
decrease of the feedback signal, which allows the inner dynamics
to adapt to the input. After this new transient time, the feedback
signal is again in synchrony with the input signal. Last, at time
, we reverse the time order of the input signal. In that
case, the feedback signal fades out.
So, one can remark that the activation of the feedback
reinforcement is very sensitive to the spatio-temporal structure
of the input signal, i.e. is stimulus specific. It grounds
on a coincidence detection principle, i.e. to the detection
of a specific sequence of activations in the secondary layer. This
secondary layer organization is also stimulus-specific, and is in
particular highly sensitive to the time order of the input signal.
For that reason, a change in the time order of the spatial inputs
modifies the inner organization and thus deactivates the feedback
reinforcement. The system has thus learned to discriminate between
one relevant stimulus and other non-relevant (non-learned) stimuli
(spatial and/or temporal mismatch - we have verified that a
spatial mismatch deactivates the feedback signal in the same
fashion).
When can we say that a system ``recognizes'' the input pattern?
Most models that rely on resonant principles have to use a global
attentional threshold which determines whether a new input pattern
is coherent with previously learned patterns or not
[5]. In our system, we define the recognition
as the dynamic process which corresponds to the activation of a
specific feedback signal. Recognition thus takes place without
global control. It relies on the emergence of a specific dynamical
configuration. It is thus more simple (or more ``natural'') in its
principle: the gating function grounds on the coherent behavior of
the whole population of neurons. The ``decision'' to recognize (or
to ignore) a given stimulus comes from the collective activity of
all the neurons belonging to the perceptual system.
Next: Retrieval
Up: Recognition, retrieval and dynamical
Previous: Recognition, retrieval and dynamical
Dauce Emmanuel
2003-04-08