Biomedical subjects

J L Valdés

Publications and source records attributed to J L Valdés.

3 recordsLinked to original sources

PubMed2005

Differential effects of infralimbic cortical lesions on temperature and locomotor activity responses to feeding in rats.

The time of food availability induces important behavioral and metabolic adaptations. Animals subjected to feeding restricted to a few daytime hours show increased locomotor activity and body temperature in anticipation of mealtime. In addition, animals under ad libitum feeding show a marked postprandial raise in body temperature and in thermogenesis. The areas of the brain commanding these responses to food are partially known. We investigated in the rat the role of the infralimbic area, located in the medial prefrontal cortex, and considered a visceral-autonomic motor area, in the responses to ad libitum or restricted feeding schedule. We performed infralimbic cortex excitotoxic lesions using injections of ibotenic acid, and measured body temperature and locomotor activity by telemetry in rats under ad libitum and restricted feeding conditions. We found that bilateral infralimbic area lesions prevented both the anticipatory and the postprandial increases in core temperature, decreased mean temperature by nearly 0.3 degrees C during both light/dark phases, and increased daily temperature variability. In contrast, the lesion caused a rapid induction of the anticipatory locomotor activity. These results show that behavioral and metabolic responses to the time of food availability are commanded separately and that the infralimbic area is a key structure to adjust the body temperature to an upcoming meal.

Animals↗

PubMed2005

Arousal and differential Fos expression in histaminergic neurons of the ascending arousal system during a feeding-related motivated behaviour.

Arousal depends on the concerted activity of the ascending arousal system (AAS) but specific stimuli may primarily activate some nuclei of this system. Motivated behaviours are characterized by behavioural arousal, although it is not known which AAS nuclei are active during a motivated behaviour. To address this issue, rats were rendered motivated for food by fasting them for 1 day and then were enticed with food that they could not obtain for varying periods of time. We studied the level of arousal by polysomnography or radiotelemetry, and Fos-ir in the AAS, during food enticing. We found a strong arousal and an early increase in Fos-ir in the histaminergic neurons from the tuberomammillary nucleus, after 30 min of enticing, followed by increased Fos-ir in the whole AAS if food enticing was prolonged to 1 or 2 hours. In contrast, food presentation to non-motivated rats did not increase arousal or Fos-ir in the tuberomammillary nucleus. As opposed to the active arousal of the motivated rats, passive arousal induced by sensory stimulation was associated with increased Fos-ir in the locus coeruleus and the orexin neurons, but not with increased Fos-ir in the tuberomammillary nucleus or in the other nuclei of the AAS. We conclude that the arousal during feeding-related motivated behaviour is associated primarily with the activation of the tuberomammillary nucleus, while the other arousal-related nuclei become active later on.

Afferent Pathways↗

PubMed1995

EEG predictability: adequacy of non-linear forecasting methods.

The predictive properties of EEG segments were analyzed. The sample included alpha, delta as well as spike and wave EEG activity recordings. Most of these segments are better described with non-linear autoregressive models, and a non-linear forecasting algorithm is routinely required. In terms of their predictive properties, segments can be divided into unpredictable, predictable and very predictable, these three groups being similarly represented among the alpha activity EEG segments. In EEG segments with alpha activity, poor predictability is associated with poor organization of the rhythmic pattern. Concerning dynamic properties, it was found that cyclic skeletons were highly represented among the very predictable segments, which reflect a contribution of the deterministic component of the autoregressive model to the predictability of the segments. Notable contributions of the noise component may explain the properties of unpredictable segments. These results point to a great diversity of predictive patterns among EEG recordings. Other factors besides the existence of chaotic dynamics must be regarded.

Algorithms↗