12 research outputs found
Autism as a disorder of neural information processing: directions for research and targets for therapy
The broad variation in phenotypes and severities within autism spectrum disorders suggests the involvement of multiple predisposing factors, interacting in complex ways with normal developmental courses and gradients. Identification of these factors, and the common developmental path into which theyfeed, is hampered bythe large degrees of convergence from causal factors to altered brain development, and divergence from abnormal brain development into altered cognition and behaviour. Genetic, neurochemical, neuroimaging and behavioural findings on autism, as well as studies of normal development and of genetic syndromes that share symptoms with autism, offer hypotheses as to the nature of causal factors and their possible effects on the structure and dynamics of neural systems. Such alterations in neural properties may in turn perturb activity-dependent development, giving rise to a complex behavioural syndrome many steps removed from the root causes. Animal models based on genetic, neurochemical, neurophysiological, and behavioural manipulations offer the possibility of exploring these developmental processes in detail, as do human studies addressing endophenotypes beyond the diagnosis itself
Familiarization: A theory of repetition suppression predicts interference between overlapping cortical representations
Repetition suppression refers to a reduction in the cortical response to a novel stimulus that
results from repeated presentation of the stimulus. We demonstrate repetition suppression
in a well established computational model of cortical plasticity, according to which the relative
strengths of lateral inhibitory interactions are modified by Hebbian learning. We present
the model as an extension to the traditional account of repetition suppression offered by
sharpening theory, which emphasises the contribution of afferent plasticity, by instead
attributing the effect primarily to plasticity of intra-cortical circuitry. In support, repetition suppression
is shown to emerge in simulations with plasticity enabled only in intra-cortical connections.
We show in simulation how an extended ‘inhibitory sharpening theory’ can explain
the disruption of repetition suppression reported in studies that include an intermediate
phase of exposure to additional novel stimuli composed of features similar to those of the
original stimulus. The model suggests a re-interpretation of repetition suppression as a manifestation
of the process by which an initially distributed representation of a novel object
becomes a more localist representation. Thus, inhibitory sharpening may constitute a more
general process by which representation emerges from cortical re-organisation
Neuron-glial Interactions
Although lagging behind classical computational neuroscience, theoretical and computational approaches are beginning to emerge to characterize different aspects of neuron-glial interactions. This chapter aims to provide essential knowledge on neuron-glial interactions in the mammalian brain, leveraging on computational studies that focus on structure (anatomy) and function (physiology) of such interactions in the healthy brain. Although our understanding of the need of neuron-glial interactions in the brain is still at its infancy, being mostly based on predictions that await for experimental validation, simple general modeling arguments borrowed from control theory are introduced to support the importance of including such interactions in traditional neuron-based modeling paradigms.Junior Leader Fellowship Program by “la Caixa” Banking Foundation (LCF/BQ/LI18/11630006
Neuron-Glial Interactions
Although lagging behind classical computational neuroscience, theoretical and
computational approaches are beginning to emerge to characterize different
aspects of neuron-glial interactions. This chapter aims to provide essential
knowledge on neuron-glial interactions in the mammalian brain, leveraging on
computational studies that focus on structure (anatomy) and function
(physiology) of such interactions in the healthy brain. Although our
understanding of the need of neuron-glial interactions in the brain is still at
its infancy, being mostly based on predictions that await for experimental
validation, simple general modeling arguments borrowed from control theory are
introduced to support the importance of including such interactions in
traditional neuron-based modeling paradigms.Comment: 43 pages, 2 figures, 1 table. Accepted for publication in the
"Encyclopedia of Computational Neuroscience," D. Jaeger and R. Jung eds.,
Springer-Verlag New York, 2020 (2nd edition