Search results for "Neural"
showing 10 items of 2783 documents
Defective Postnatal Neurogenesis and Disorganization of the Rostral Migratory Stream in Absence of theVax1Homeobox Gene
2004
The subventricular zone (SVZ) is one of the sources of adult neural stem cells (ANSCs) in the mouse brain. Precursor cells proliferate in the SVZ and migrate through the rostral migratory stream (RMS) to the olfactory bulb (OB), where they differentiate into granule and periglomerular cells. Few transcription factors are known to be responsible for regulating NSC proliferation, migration, and differentiation processes; even fewer have been found to be responsible for the organization of the SVZ and RMS. For this reason, we studied the ventral anterior homeobox (Vax1) gene in NSC proliferation and in SVZ organization. We found thatVax1is strongly expressed in the SVZ and in the RMS and that,…
Subventricular zone in motor neuron disease with frontotemporal dementia.
2011
Investigate how the subventricular proliferation and organisation is modified in a patient with FTLD-ALS. We studied the subventricular zone (SVZ) of a patient with FTLD-ALS immunohistochemical and histologically. We found an increase of Ki-67 positive cells and neuroblast in the subventricular zone, suggesting an activation of proliferating activity in response to FTD-ALS. This proliferation can act as a compensatory mechanism for rapid neuronal death and its modulation could provide a new therapeutic pathway in ALS. These results suggest a modification of neurogenesis in FTD-ALS. (C) 2011 Elsevier Ireland Ltd. All rights reserved.
Sustained activation of mTOR pathway in embryonic neural stem cells leads to development of tuberous sclerosis complex-associated lesions
2011
SummaryTuberous Sclerosis Complex (TSC) is a multisystem genetic disorder characterized by hamartomatous neurological lesions that exhibit abnormal cell proliferation and differentiation. Hyperactivation of mTOR pathway by mutations in either the Tsc1 or Tsc2 gene underlies TSC pathogenesis, but involvement of specific neural cell populations in the formation of TSC-associated neurological lesions remains unclear. We deleted Tsc1 in Emx1-expressing embryonic telencephalic neural stem cells (NSCs) and found that mutant mice faithfully recapitulated TSC neuropathological lesions, such as cortical lamination defects and subependymal nodules (SENs). These alterations were caused by enhanced gen…
Telomere shortening and chromosomal instability abrogates proliferation of adult but not embryonic neural stem cells.
2004
Chromosome integrity is essential for cell viability and, therefore, highly proliferative cell types require active telomere elongation mechanisms to grow indefinitely. Consistently, deletion of telomerase activity in a genetically modified mouse strain results in growth impairments in all highly proliferative cell populations analyzed so far. We show that telomere attrition dramatically impairs the in vitro proliferation of adult neural stem cells (NSCs) isolated from the subventricular zone (SVZ) of telomerase-deficient adult mice. Reduced proliferation of postnatal neurogenic progenitors was also observed in vivo, in the absence of exogenous mitogenic stimulation. Strikingly, severe telo…
Distribution of PSA-NCAM expression in the amygdala of the adult rat.
2002
Synaptic plasticity in the amygdala appears to be necessary for the generation of emotional memories. However, the molecular bases of this plasticity are not fully understood. Because the polysialylated form of the neural cell adhesion molecule (PSA-NCAM) has been implicated in memory consolidation in the hippocampus and temporal cortex, we have studied in detail the expression of this molecule in the adult rat amygdala with an antibody against PSA-NCAM. Our results demonstrate for the first time the presence of PSA-NCAM in the adult rat amygdala. Immunoreactive somata and processes are abundant in the amygdalo-hippocampal transition area, central nucleus, intra-amygdaloid bed nucleus of th…
Review of Non-English Corpora Annotated for Emotion Classification in Text
2020
In this paper we try to systematize the information about the available corpora for emotion classification in text for languages other than English with the goal to find what approaches could be used for low-resource languages with close to no existing works in the field. We analyze the corresponding volume, emotion classification schema, language of each corresponding corpus and methods employed for data preparation and annotation automation. We’ve systematized twenty-four papers representing the corpora and found that corpora were mostly for the most spoken world languages: Hindi, Chinese, Turkish, Arabic, Japanese etc. A typical corpus contained several thousand of manually-annotated ent…
A Controllable Text Simplification System for the Italian Language
2021
Text simplification is a non-trivial task that aims at reducing the linguistic complexity of written texts. Researchers have studied the problem by proposing new methodologies for addressing the English language, but other languages, like the Italian one, are almost unexplored. In this paper, we give a contribution to the enhancement of the Automated Text Simplification research by presenting a deep learning-based system, inspired by a state of the art system for the English language, capable of simplifying Italian texts. The system has been trained and tested by leveraging the Italian version of Newsela; it has shown promising results by achieving a SARI value of 30.17.
Movie Script Similarity Using Multilayer Network Portrait Divergence
2020
International audience; This paper addresses the question of movie similarity through multilayer graph similarity measures. Recent work has shown how to construct multilayer networks using movie scripts, and how they capture different aspects of the stories. Based on this modeling, we propose to rely on the multilayer structure and compute different similarities, so we may compare movies, not from their visual content, summary, or actors, but actually from their own storyboard. We propose to do so using “portrait divergence”, which has been recently introduced to compute graph distances from summarizing graph characteristics. We illustrate our approach on the series of six Star Wars movies.
Increasing the Inference and Learning Speed of Tsetlin Machines with Clause Indexing
2020
The Tsetlin Machine (TM) is a machine learning algorithm founded on the classical Tsetlin Automaton (TA) and game theory. It further leverages frequent pattern mining and resource allocation principles to extract common patterns in the data, rather than relying on minimizing output error, which is prone to overfitting. Unlike the intertwined nature of pattern representation in neural networks, a TM decomposes problems into self-contained patterns, represented as conjunctive clauses. The clause outputs, in turn, are combined into a classification decision through summation and thresholding, akin to a logistic regression function, however, with binary weights and a unit step output function. …
Diffusive neural network
2002
Abstract A non-connectionist model of a neuronal network based on passive diffusion of neurotransmitters is presented as an alternative to hard-wired artificial neural networks. Classic thermodynamical approach shows that the diffusive network is capable of exhibiting asymptotic stability and a dynamics resembling that of a chaotic system. Basic computational capabilities of the net are discussed based on the equivalence with a Turing machine. The model offers a way to represent mass-sustained brain functions in terms of recurrent behaviors in the phase space.