Gustatory processing
changes within sessions, dependent on attention
By Donald B. Katz
Gustatory cortical networks
reliably transition through taste-specific states
By Lauren M. Jones
Distinct states of
firing patterns in the primary visual cortex of awake ferrets
By József Fiser
In a series of three talks, we
will present a coherent view of brains functioning as a dynamic network
processing complex multi-dimensional input. The specifics of this
approach include a) large scale multi-electrode recordings as the
appropriate tool for data collection, b) performance of behavioral
tasks as the appropriate preparation, c) data analysis methods based on
the principle that processing in such networks depends on the prior
state of the networks and involves complex coherent patterns of
activity in neural ensembles, and d) the use of multiple modalities and
species for validation of the generality of results. In the first
talk, we show that the processing of tastes in gustatory cortex varies
across a recording session dependent on mass action in cortical
networks, such that as the rat switches from being attentive
(desynchronized EEG) to being inattentive (oscillatory EEG) the nature
of taste coding changes; in inattentive rats, neural and behavioral
responses to a battery of experimenter-administered tastes are coded
more simply in relation to palatability—pleasing tastes are more
distinct from noxious tastes, and noxious tastes are more similar to
each other. In the second talk, we show that taste responses vary from
trial to trial, dependent on coherent ensemble processes. Ensembles of
taste cortex neurons go through a series of coherent states—defined as
a period of time in which each neuron has a particular firing rate—with
minimal switching time between states; a particular series of 2-3
states is specific for a particular taste stimulus, but the time spent
in each state varies widely across trials. A given state series is a
more effective predictor of taste identity than PSTH-based methods.
Finally, in the third talk we switch to a new modality (vision), a more
unconstrained task (passive viewing), and a different species (ferret).
While the visual system that is thought to work very differently from
taste, and the passive viewing task does not require stimulus
processing and response (ferrets sat in complete darkness or watched
either a natural scene or a random noise movie), cortical functioning
still exhibits similar hallmarks of dynamic state-dependent
functioning. We suggest that rather than attempting to reproduce simple
output or trial-averaged responses of single neurons, analyses that
capture the underlying structure of the dynamic behavior may provide
useful information for theoretical/computational attempts to unravel
the function of cortical networks.