Functional Sub-Types

The paper argues that a functional reduction of ordinary psychology to neuropsychology is possible by means of constructing fine-grained functional, mental sub-types that are coextensive with neuropsychological types. We establish this claim by means of considering as examples the cases of the disconnection syndrome and schizophrenia. We point out that the result is a conservative reduction, vindicating the scientific quality of the mental types of ordinary psychology by systematically linking them with neuroscience. That procedure of conservative reduction by means of functional sub-types is in principle repeatable down to molecular neuroscience.

Prediction of functional outcome 18 months after a first psychotic episode: a proton magnetic resonance spectroscopy study.

CONTEXT: Recent magnetic resonance imaging studies have attempted to relate volumetric brain measurements in early schizophrenia to clinical and functional outcome some years later. These studies have generally been negative, perhaps because gray and white matter volumes inaccurately assess the underlying dysfunction that might be predictive of outcome. OBJECTIVE: To investigate the predictive value of frontal and temporal spectroscopy measures for outcome in patients with first-episode psychoses. DESIGN: Left prefrontal cortex and left mediotemporal lobe voxels were assessed using proton magnetic resonance spectroscopy to provide the ratio of N-acetylaspartate (NAA) and choline-containing compounds to creatine and phosphocreatine (Cr) (NAA/Cr ratio). These data were used to predict outcome at 18 months after admission, as assessed by a systematic medical record audit. SETTING: Early psychosis clinic. PARTICIPANTS: Forty-six patients with first-episode psychosis. MAIN OUTCOME MEASURES: We used regression models that included age at imaging and duration of untreated psychosis to predict outcome scores on the Global Assessment of Functioning Scale, Clinical Global Impression scales, and Social and Occupational Functional Assessment Scale, as well as the number of admissions during the treatment period. We then further considered the contributions of premorbid function and baseline level of negative symptoms. RESULTS: The only spectroscopic predictor of outcome was the NAA/Cr ratio in the prefrontal cortex. Low scores on this variable were related to poorer outcome on all measures. In addition, the frontal NAA/Cr ratio explained 17% to 30% of the variance in outcome. CONCLUSIONS: Prefrontal neuronal dysfunction is an inconsistent feature of early psychosis; rather, it is an early marker of poor prognosis across the first years of illness. The extent to which this can be used to guide treatment and whether it predicts outcome some years after first presentation are questions for further research.

Traité général de science économique / par Christian Cornélissen. T. 3, Théorie du capital et du profit

Collection : Bibliothèque internationale d'économie politique ; 87-88

Genetic and environmental effects on the covariation betweencolour polymorphism and a life history trait

Variation in coloration with a strong underlying genetic basis is frequently found within animal populations but little is known about its function. Covariation between colour polymorphism and life-history traits can arise because morphs perform differently among environments or because they possess alternative alleles coding for key life-history traits. To test these two hypotheses, we studied a population of tawny owls Strix aluco, a bird displaying red, brown and grey morphs. We assessed the colour morph of breeding females, swapped eggs or hatchlings between pairs of nests, and examined how body condition in 3-week-old nestlings covaries with coloration of foster and genetic mothers. Redder foster and genetic mothers produced young in better condition. Because in two other years we observed that greyish females produced offspring in better condition than those of red females, the present study suggests that colour polymorphism signals genetic and phenotypic adaptations to cope with a fluctuating environment.

Identification of optimal structural connectivity using functional connectivity and neural modeling.

The complex network dynamics that arise from the interaction of the brain's structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure-function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure-function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.