Difference in distribution of microtubule-associated proteins 5a and 5b during the development of cerebral cortex and corpus callosum in cats: dependence on phosphorylation.

MAP5, a microtubule-associated protein characteristic of differentiating neurons, was studied in the developing visual cortex and corpus callosum of the cat. In juvenile cortical tissue, during the first month after birth, MAP5 is present as a protein doublet of molecular weights of 320 and 300 kDa, defined as MAP5a and MAP5b, respectively. MAP5a is the phosphorylated form. MAP5a decreases two weeks after birth and is no longer detectable at the beginning of the second postnatal month; MAP5b also decreases after the second postnatal week but more slowly and it is still present in the adult. In the corpus callosum only MAP5a is present between birth and the end of the first postnatal month. Afterwards only MAP5b is present but decreases in concentration more than 3-fold towards adulthood. Our immunocytochemical studies show MAP5 in somata, dendrites and axonal processes of cortical neurons. In adult tissue it is very prominent in pyramidal cells of layer V. In the corpus callosum MAP5 is present in axons at all ages. There is strong evidence that MAP5a is located in axons while MAP5b seems restricted to somata and dendrites until P28, but is found in callosal axons from P39 onwards. Biochemical experiments indicate that the state of phosphorylation of MAP5 influences its association with structural components. After high speed centrifugation of early postnatal brain tissue, MAP5a remains with pellet fractions while most MAP5b is soluble. In conclusion, phosphorylation of MAP5 may regulate (1) its intracellular distribution within axons and dendrites, and (2) its ability to interact with other subcellular components.

The auditory pathway in cat corpus callosum.

The cortical auditory fields of the two hemispheres are interconnected via the corpus callosum. We have investigated the topographical arrangement of auditory callosal axons in the cat. Following circumscribed biocytin injections in the primary (AI), secondary (AII), anterior (AAF) and posterior (PAF) auditory fields, labelled axons have been found in the posterior two-thirds of the corpus callosum. Callosal axons labelled by small individual cortical injections did not form a tight bundle at the callosal midsagittal plane but spread over as much as one-third of the corpus callosum. Axons originating from different auditory fields were roughly topographically ordered, reflecting to some extent the rostro-caudal position of the field of origin. Axons from AAF crossed on average more rostrally than axons from AI; the latter crossed more rostrally than axons from PAF and AII. Callosal axons originating in a discrete part of the cortex travelled first in a relatively tight bundle to the telo-diencephalic junction and then dispersed progressively. In conclusion, the cat corpus callosum does not contain a sector reserved for auditory axons, nor a strictly topographically ordered auditory pathway. This observation is of relevance to neuropsychological and neuropathological observations in man.

Apprentissage automatique de la morphologie : le cas des structures racine-schème

RÉSUMÉ Cette thèse porte sur le développement de méthodes algorithmiques pour découvrir automatiquement la structure morphologique des mots d'un corpus. On considère en particulier le cas des langues s'approchant du type introflexionnel, comme l'arabe ou l'hébreu. La tradition linguistique décrit la morphologie de ces langues en termes d'unités discontinues : les racines consonantiques et les schèmes vocaliques. Ce genre de structure constitue un défi pour les systèmes actuels d'apprentissage automatique, qui opèrent généralement avec des unités continues. La stratégie adoptée ici consiste à traiter le problème comme une séquence de deux sous-problèmes. Le premier est d'ordre phonologique : il s'agit de diviser les symboles (phonèmes, lettres) du corpus en deux groupes correspondant autant que possible aux consonnes et voyelles phonétiques. Le second est de nature morphologique et repose sur les résultats du premier : il s'agit d'établir l'inventaire des racines et schèmes du corpus et de déterminer leurs règles de combinaison. On examine la portée et les limites d'une approche basée sur deux hypothèses : (i) la distinction entre consonnes et voyelles peut être inférée sur la base de leur tendance à alterner dans la chaîne parlée; (ii) les racines et les schèmes peuvent être identifiés respectivement aux séquences de consonnes et voyelles découvertes précédemment. L'algorithme proposé utilise une méthode purement distributionnelle pour partitionner les symboles du corpus. Puis il applique des principes analogiques pour identifier un ensemble de candidats sérieux au titre de racine ou de schème, et pour élargir progressivement cet ensemble. Cette extension est soumise à une procédure d'évaluation basée sur le principe de la longueur de description minimale, dans- l'esprit de LINGUISTICA (Goldsmith, 2001). L'algorithme est implémenté sous la forme d'un programme informatique nommé ARABICA, et évalué sur un corpus de noms arabes, du point de vue de sa capacité à décrire le système du pluriel. Cette étude montre que des structures linguistiques complexes peuvent être découvertes en ne faisant qu'un minimum d'hypothèses a priori sur les phénomènes considérés. Elle illustre la synergie possible entre des mécanismes d'apprentissage portant sur des niveaux de description linguistique distincts, et cherche à déterminer quand et pourquoi cette coopération échoue. Elle conclut que la tension entre l'universalité de la distinction consonnes-voyelles et la spécificité de la structuration racine-schème est cruciale pour expliquer les forces et les faiblesses d'une telle approche. ABSTRACT This dissertation is concerned with the development of algorithmic methods for the unsupervised learning of natural language morphology, using a symbolically transcribed wordlist. It focuses on the case of languages approaching the introflectional type, such as Arabic or Hebrew. The morphology of such languages is traditionally described in terms of discontinuous units: consonantal roots and vocalic patterns. Inferring this kind of structure is a challenging task for current unsupervised learning systems, which generally operate with continuous units. In this study, the problem of learning root-and-pattern morphology is divided into a phonological and a morphological subproblem. The phonological component of the analysis seeks to partition the symbols of a corpus (phonemes, letters) into two subsets that correspond well with the phonetic definition of consonants and vowels; building around this result, the morphological component attempts to establish the list of roots and patterns in the corpus, and to infer the rules that govern their combinations. We assess the extent to which this can be done on the basis of two hypotheses: (i) the distinction between consonants and vowels can be learned by observing their tendency to alternate in speech; (ii) roots and patterns can be identified as sequences of the previously discovered consonants and vowels respectively. The proposed algorithm uses a purely distributional method for partitioning symbols. Then it applies analogical principles to identify a preliminary set of reliable roots and patterns, and gradually enlarge it. This extension process is guided by an evaluation procedure based on the minimum description length principle, in line with the approach to morphological learning embodied in LINGUISTICA (Goldsmith, 2001). The algorithm is implemented as a computer program named ARABICA; it is evaluated with regard to its ability to account for the system of plural formation in a corpus of Arabic nouns. This thesis shows that complex linguistic structures can be discovered without recourse to a rich set of a priori hypotheses about the phenomena under consideration. It illustrates the possible synergy between learning mechanisms operating at distinct levels of linguistic description, and attempts to determine where and why such a cooperation fails. It concludes that the tension between the universality of the consonant-vowel distinction and the specificity of root-and-pattern structure is crucial for understanding the advantages and weaknesses of this approach.

Splenium of corpus callosum: patterns of interhemispheric interaction in children and adults.

The splenium of the corpus callosum connects the posterior cortices with fibers varying in size from thin late-myelinating axons in the anterior part, predominantly connecting parietal and temporal areas, to thick early-myelinating fibers in the posterior part, linking primary and secondary visual areas. In the adult human brain, the function of the splenium in a given area is defined by the specialization of the area and implemented via excitation and/or suppression of the contralateral homotopic and heterotopic areas at the same or different level of visual hierarchy. These mechanisms are facilitated by interhemispheric synchronization of oscillatory activity, also supported by the splenium. In postnatal ontogenesis, structural MRI reveals a protracted formation of the splenium during the first two decades of human life. In doing so, the slow myelination of the splenium correlates with the formation of interhemispheric excitatory influences in the extrastriate areas and the EEG synchronization, while the gradual increase of inhibitory effects in the striate cortex is linked to the local inhibitory circuitry. Reshaping interactions between interhemispherically distributed networks under various perceptual contexts allows sparsification of responses to superfluous information from the visual environment, leading to a reduction of metabolic and structural redundancy in a child's brain.

Neurons in the corpus callosum of the cat during postnatal development.

The corpus callosum (CC) is a major telencephalic commissure containing mainly cortico-cortical axons and glial cells. We have identified neurons in the CC of the cat and quantified their number at different postnatal ages. An antibody against microtubule-associated protein 2 was used as a marker of neurons. Immunocytochemical double-labelling with neuron-specific enolase or gamma-aminobutyric acid antibodies in the absence of glial fibrillary acidic protein positivity confirmed the neuronal phenotype of these cells. CC neurons were also stained with anti-calbindin and anti-calretinin antibodies, typical for interneurons, and with an anti-neurofilament antibody, which in neocortex detects pyramidal neurons. Together, these findings suggest that the CC contains a mixed population of neuronal types. The quantification was corrected for double counting of adjacent sections and volume changes during CC development. Our data show that CC neurons are numerous early postnatally, and their number decreases with age. At birth, about 570 neurons are found within the CC boundaries and their number drops to about 200 in the adult. The distribution of the neurons within the CC also changes in development. Initially, many neurons are found throughout the CC, while at later ages they become restricted to the boundaries of the CC, and in the adult to the rostrum of the CC close to the septum pellucidum or to the indusium griseum. Although origin and function of transient CC neurons in development and in adulthood remain unknown, they are likely to be interstitial neurons. Some of them have well-developed and differentiated processes and resemble pyramidal cells or interneurons. An axon-guiding function during the early postnatal period can not be excluded.