Synchronous modifications in the cortical and pulvinar unit activity during slow wave sleep.
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Biomedical subjects
Publications and source records attributed to Y Burnod.
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Various physiological parameters (EEG, EKG, EOG, EMG), and behavioural activities were measured during 8 working hours in 40 subjects divided into 4 groups according to their age and occupation (35 and 50 years, specially skilled workmen and university workers). Several moments of synchronization between the different parameters were defined; they were characterized by reduction or suppression of the theta index, an increase in the alpha index, an increase in number of blinkings, a drop in muscle tone, and variations in heart rate, accompanied by modifications in work activity. The variation observed during these synchronized moments is an overall change in all the parameters and is not systematically related to just one of them. The synchronized moments last for about 8 minutes and are more frequent and better individualized in university personnel than in workmen. The average interval between them is 93 minutes with large intra and inter-variability between individuals. They are longer in 50-year-old subjects whatever the type of activity. The authors compare these moments of synchronization with ultradian rhythms described by other authors.
We analyzed the cellular short-term memory effects induced by a slowly inactivating potassium (Ks) conductance using a biophysical model of a neuron. We first described latency-to-first-spike and temporal changes in firing frequency as a function of parameters of the model, injected current and prior history of the neuron (deinactivation level) under current clamp. This provided a complete set of properties describing the Ks conductance in a neuron. We then showed that the action of the Ks conductance is not generally appropriate for controlling latency-to-first-spike under random synaptic stimulation. However, reliable latencies were found when neuronal population computation was used. Ks inactivation was found to control the rate of convergence to steady-state discharge behavior and to allow frequency to increase at variable rates in sets of synaptically connected neurons. These results suggest that inactivation of the Ks conductance can have a reliable influence on the behavior of neuronal populations under real physiological conditions.
The principles underlying the organization and operation of the prefrontal cortex have been addressed by neural network modeling. The involvement of the prefrontal cortex in the temporal organization of behavior can be defined by processing units that switch between two stable states of activity (bistable behavior) in response to synaptic inputs. Long-term representation of programs requiring short-term memory can result from activity-dependent modifications of the synaptic transmission controlling the bistable behavior. After learning, the sustained activity of a given neuron represents the selective memorization of a past event, the selective anticipation of a future event, and the predictability of reinforcement. A simulated neural network illustrates the abilities of the model (1) to learn, via a natural step-by-step training protocol, the paradigmatic task (delayed response) used for testing prefrontal neurons in primates, (2) to display the same categories of neuronal activities, and (3) to predict how they change during learning. In agreement with experimental data, two main types of activity contribute to the adaptive properties of the network. The first is transient activity time-locked to events of the task and its profile remains constant during successive training stages. The second is sustained activity that undergoes nonmonotonic changes with changes in reward contingency that occur during the transition between stages.