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1.
Neural Comput ; 36(5): 759-780, 2024 Apr 23.
Article in English | MEDLINE | ID: mdl-38658025

ABSTRACT

Central pattern generators are circuits generating rhythmic movements, such as walking. The majority of existing computational models of these circuits produce antagonistic output where all neurons within a population spike with a broad burst at about the same neuronal phase with respect to network output. However, experimental recordings reveal that many neurons within these circuits fire sparsely, sometimes as rarely as once within a cycle. Here we address the sparse neuronal firing and develop a model to replicate the behavior of individual neurons within rhythm-generating populations to increase biological plausibility and facilitate new insights into the underlying mechanisms of rhythm generation. The developed network architecture is able to produce sparse firing of individual neurons, creating a novel implementation for exploring the contribution of network architecture on rhythmic output. Furthermore, the introduction of sparse firing of individual neurons within the rhythm-generating circuits is one of the factors that allows for a broad neuronal phase representation of firing at the population level. This moves the model toward recent experimental findings of evenly distributed neuronal firing across phases among individual spinal neurons. The network is tested by methodically iterating select parameters to gain an understanding of how connectivity and the interplay of excitation and inhibition influence the output. This knowledge can be applied in future studies to implement a biologically plausible rhythm-generating circuit for testing biological hypotheses.


Subject(s)
Action Potentials , Central Pattern Generators , Models, Neurological , Spinal Cord , Action Potentials/physiology , Central Pattern Generators/physiology , Animals , Spinal Cord/physiology , Neurons/physiology , Computer Simulation , Neural Networks, Computer , Periodicity , Nerve Net/physiology , Humans
2.
Commun Biol ; 5(1): 1247, 2022 11 14.
Article in English | MEDLINE | ID: mdl-36376446

ABSTRACT

Distinguishing animate from inanimate things is of great behavioural importance. Despite distinct brain and behavioural responses to animate and inanimate things, it remains unclear which object properties drive these responses. Here, we investigate the importance of five object dimensions related to animacy ("being alive", "looking like an animal", "having agency", "having mobility", and "being unpredictable") in brain (fMRI, EEG) and behaviour (property and similarity judgements) of 19 participants. We used a stimulus set of 128 images, optimized by a genetic algorithm to disentangle these five dimensions. The five dimensions explained much variance in the similarity judgments. Each dimension explained significant variance in the brain representations (except, surprisingly, "being alive"), however, to a lesser extent than in behaviour. Different brain regions sensitive to animacy may represent distinct dimensions, either as accessible perceptual stepping stones toward detecting whether something is alive or because they are of behavioural importance in their own right.


Subject(s)
Brain , Pattern Recognition, Visual , Humans , Pattern Recognition, Visual/physiology , Brain/diagnostic imaging , Brain/physiology , Brain Mapping , Magnetic Resonance Imaging/methods , Judgment/physiology
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