Josette Pastor | PubMed Health

PubMed2005

Modulation of behavior and cortical motor activity in healthy subjects by a chronic administration of a serotonin enhancer.

UNLABELLED: SSRIs are postulated to modulate motor behavior. A single dose of selective serotoninergic reuptake inhibitors (SSRIs) like fluoxetine, paroxetine, or fluvoxamine, has been shown to improve motor performance and efficiency of information processing for simple sensorimotor tasks in healthy subjects. At a cortical level, a single dose of SSRI was shown to induce a hyperactivation of the primary sensorimotor cortex (S1M1) involved in the movement (Loubinoux, I., Boulanouar, K., Ranjeva, J. P., Carel, C., Berry, I., Rascol, O., Celsis, P., and Chollet, F., 1999. Cerebral functional magnetic resonance imaging activation modulated by a single dose of the monoamine neurotransmission enhancers fluoxetine and fenozolone during hand sensorimotor tasks. J. Cereb. Blood Flow Metab. 19 1365--1375, Loubinoux, I., Pariente, J., Boulanouar, K., Carel, C., Manelfe, C., Rascol, O., Celsis, P., and Chollet, F., 2002. A Single Dose of Serotonin Neurotransmission Agonist Paroxetine Enhances Motor Output. A double-blind, placebo-controlled, fMRI study in healthy subjects. NeuroImage 15 26--36). Since SSRIs are usually given for several weeks, we assessed the behavioral and cerebral effects of a one-month chronic administration of paroxetine on a larger group. In a double-blind, placebo controlled and crossover study, 19 subjects received daily 20 mg paroxetine or placebo, respectively, over a period of 30 days separated by a wash-out period of 3 months. After each period, the subjects underwent an fMRI (active or passive movement, dexterity task, sensory discrimination task) and a behavioral evaluation. Concurrently, a TMS (transcranial magnetic stimulation) study was conducted (Gerdelat-Mas, A., Loubinoux, I., Tombari, D., Rascol, O., Chollet, F., Simonetta-Moreau, M., 2005. Chronic administration of selective serotonin re-uptake inhibitor (SSRI) paroxetine modulates human motor cortex excitability in healthy subjects. NeuroImage 27,314--322). RESULTS: On the one hand, paroxetine improved motor performances at the finger tapping test (P=0.02) without affecting choice reaction time, strength and dexterity significantly. Subjects were also faster in processing the spatial incongruency between a stimulus and the motor response (P=0.04). In order to differentiate behavioral components, a principal component analysis was performed on all motor tests, and several characteristics were differentiated: strength, speed, skill, attention, and motor response coding. Paroxetine would improve the efficiency of motor response coding (MANOVA on the factors; factor 3, P=0.01). On the other hand, the chronic administration induced a significant hypoactivation of S1M1 whatever the task: motor or sensory, simple or complex (random effect analysis, P<0.05). The hypoactivation correlated with the improvement of performances at the finger tapping test (P<0.05) suggesting more efficiency in cerebral motor processing. CONCLUSIONS: Our results showed a clear modulation of sensory and motor cerebral activation after a chronic paroxetine administration. An improvement in both behavior and cerebral efficiency was suggested. It could be hypothesized that monoamines, by an unspecific effect, may tune the response of pyramidal neurons to optimize performances.

Adult↗

PubMed2004

Cerebral modeling and dynamic Bayesian networks.

The understanding and the prediction of the clinical outcomes of focal or degenerative cerebral lesions, as well as the assessment of rehabilitation procedures, necessitate knowing the cerebral substratum of cognitive or sensorimotor functions. This is achieved by activation studies, where subjects are asked to perform a specific task while data of their brain functioning are obtained through functional neuroimaging techniques. Such studies, as well as animal experiments, have shown that sensorimotor or cognitive functions are the offspring of the activity of large-scale networks of anatomically connected cerebral regions. However, no one-to-one correspondence between activated networks adn functions can be found. Our research aims at understanding how the activation of large-scale networks derives from cerebral information processing mechanisms, which can only explain apparently conflicting activation data. Our work falls at the crossroads of neuroimaging interpretation techniques and computational neuroscience. Since knowledge in cognitive neuroscience is permanently evolving, our research aims more precisely at defining a new modeling formalism and at building a flexible simulator, allowing a quick implementation of the models, for a better interpretation of cerebral functional images. It also aims at providing plausible models, at eht level of large-scale networks, of cerebral information processing mechanisms in humans. In this paper, we propose a formalism, based on dynamic Bayesian networks (DBNs), that respects the following constraints: an oriented, networks architecture, whose nodes (the cerebral structures) can all be different, the implementation of causality--the activation of the structure is caused by upstream nodes' activation--the explicit representation of different time scales (from 1 ms for the cerebral activity to many seconds for a PET scan image acquisition), the representation of cerebral information at the integrated level of neuronal populations, the imprecision of functional neuroimaging data, the nonlinearity and the uncertainty in cerebral mechanisms, and brain's plasticity (learning, reorganization, modulation). One of the main problems, nonlinearity, has been tackled thanks to new extensions of the Kalman filter. The capabilities of the formalism's current version are illustrated by the modeling of a phoneme categorization process, explaining the different cerebral activations in normal and dyslexic subjects.

Bayes Theorem↗