1,720,965 research outputs found
A neural model of sensory interactions in young neurotypical and ASD children
Full text linkThe brain at birth is characterized by a default state of competition among the senses [1], and integrative abilities are acquired only later in life, based on experience. Recently, Crosse and colleagues [2] in a bisensory reaction time task, with auditory (A) and visual (V) stimuli, presented alone or together (AV), in a random sequence, showed that children's reaction times (RTs) to congruent AV stimuli did not differ significantly from unisensory RTs, but differences emerged between ASD and neurotypical (NT) subjects. In this work, we implemented a neurocomputational model to simulate the RTs and analyse the behavioural responses of ASD children (6-7 years of age) and their NT counterpart. The model suggests that the comparable RTs found in unisensory and multisensory conditions could be interpreted by the default competition among the senses; this default state can be implemented via mutual inhibition between primary sensory areas; and the shift toward the classical multisensory facilitation, observed in adults, is the result of the inhibitory cross-modal connections becoming excitatory after an extended multisensory experience. Moreover, model results suggest that differences between ASD and NT children are due to a stronger cross-modal inhibition in 6-7 year-old ASD children. Finally, this neurocomputational model allowed investigation of the temporal profile of interactions among stimuli of different sensory modalities. These findings link the perceptual framework delineated by several empirical results to a plausible neural implementation
Atypical development of causal inference in autism inferred through a neurocomputational model
Full text linkIn everyday life, the brain processes a multitude of stimuli from the surrounding environment, requiring the integration of information from different sensory modalities to form a coherent perception. This process, known as multisensory integration, enhances the brain's response to redundant congruent sensory cues. However, it is equally important for the brain to segregate sensory inputs from distinct events, to interact with and correctly perceive the multisensory environment. This problem the brain must face, known as the causal inference problem, is strictly related to multisensory integration. It is widely recognized that the ability to integrate information from different senses emerges during the developmental period, as a function of our experience with multisensory stimuli. Consequently, multisensory integrative abilities are altered in individuals who have atypical experiences with cross-modal cues, such as those on the autistic spectrum. However, no research has been conducted on the developmental trajectories of causal inference and its relationship with experience thus far. Here, we used a neuro-computational model to simulate and investigate the development of causal inference in both typically developing children and those in the autistic spectrum. Our results indicate that higher exposure to cross-modal cues accelerates the acquisition of causal inference abilities, and a minimum level of experience with multisensory stimuli is required to develop fully mature behavior. We then simulated the altered developmental trajectory of causal inference in individuals with autism by assuming reduced multisensory experience during training. The results suggest that causal inference reaches complete maturity much later in these individuals compared to neurotypical individuals. Furthermore, we discuss the underlying neural mechanisms and network architecture involved in these processes, highlighting that the development of causal inference follows the evolution of the mechanisms subserving multisensory integration. Overall, this study provides a computational framework, unifying causal inference and multisensory integration, which allows us to suggest neural mechanisms and provide testable predictions about the development of such abilities in typically developed and autistic children
FGF2 modulates the voltage-dependent K+ current and changes excitability of rat dentate gyrus granule cells.
No full textFibroblast growth factor 2 (FGF2) is involved in hippocampus-dependent learning. In this study, the effects of FGF2 on the excitability were investigated in granule cells of rat dentate gyrus. Hippocampal slices were used to perform patch clamp recordings in granule cells. Extracellularly applied FGF2 early quenched the depolarization-induced repetitive firing, suggesting a decreased excitability under these conditions. Consistently, transient and sustained voltage-gated K(+) currents decreased in a dose-dependent manner, repolarization phase of action potential was slowed down, afterhyperpolarization was reduced, and membrane resistance was decreased. These effects were not mediated by tyrosine kinase FGF2 receptors. Moreover, an involvement of G protein signaling was ruled out, as well as an intracellular action of FGF2. Considering the relationship between FGF2 and hippocampal functions, the modulation of neuron excitability by activity-driven FGF2 release may be regarded as a part of a homeostatic mechanism of self-regulation of hippocampal activity
Explaining the effect of likelihood manipulation and prior through a neural network of the audiovisual perception of space
No full textResults in the recent literature suggest that multisensory integration in the brain follows the rules of Bayesian inference. However, how neural circuits can realize such inference and how it can be learned from experience is still the subject of active research. The aim of this work is to use a recent neurocomputational model to investigate how the likelihood and prior can be encoded in synapses, and how they affect audio-visual perception, in a variety of conditions characterized by different experience, different cue reliabilities and temporal asynchrony. The model considers two unisensory networks (auditory and visual) with plastic receptive fields and plastic crossmodal synapses, trained during a learning period. During training visual and auditory stimuli are more frequent and more tuned close to the fovea. Model simulations after training have been performed in crossmodal conditions to assess the auditory and visual perception bias: visual stimuli were positioned at different azimuth (±10° from the fovea) coupled with an auditory stimulus at various audio-visual distances (±20°). The cue reliability has been altered by using visual stimuli with two different contrast levels. Model predictions are compared with behavioral data. Results show that model predictions agree with behavioral data, in a variety of conditions characterized by a different role of prior and likelihood. Finally, the effect of a different unimodal or crossmodal prior, re-learning, temporal correlation among input stimuli, and visual damage (hemianopia) are tested, to reveal the possible use of the model in the clarification of important multisensory problems
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Cross-modal competition: The default computation for multisensory processing
No full textMature multisensory superior colliculus (SC) neurons integrate information across the senses to enhance their responses to spatiotem-porally congruent cross-modal stimuli. The development of this neurotypic feature of SC neurons requires experience with cross-modal cues. In the absence of such experience the response of an SC neuron to congruent cross-modal cues is no more robust than its response to the most effective component cue. This “default” or “naive” state is believed to be one in which cross-modal signals do not interact. The present results challenge this characterization by identifying interactions between visual-auditory signals in male and female cats reared without visual-auditory experience. By manipulating the relative effectiveness of the visual and auditory cross-modal cues that were presented to each of these naive neurons, an active competition between cross-modal signals was revealed. Although contrary to current expectations, this result is explained by a neuro-computational model in which the default interaction is mutual inhibition. These findings suggest that multisensory neurons at all maturational stages are capable of some form of multisensory integration, and use experience with cross-modal stimuli to transition from their initial state of competition to their mature state of cooperation. By doing so, they develop the ability to enhance the physiological salience of cross-modal events thereby increasing their impact on the sensorimotor circuitry of the SC, and the likelihood that biologically significant events will elicit SC-mediated overt behaviors
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