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2.
Commun Biol ; 5(1): 1240, 2022 11 14.
Article in English | MEDLINE | ID: mdl-36376444

ABSTRACT

The cerebellar network is renowned for its regular architecture that has inspired foundational computational theories. However, the relationship between circuit structure, function and dynamics remains elusive. To tackle the issue, we developed an advanced computational modeling framework that allows us to reconstruct and simulate the structure and function of the mouse cerebellar cortex using morphologically realistic multi-compartmental neuron models. The cerebellar connectome is generated through appropriate connection rules, unifying a collection of scattered experimental data into a coherent construct and providing a new model-based ground-truth about circuit organization. Naturalistic background and sensory-burst stimulation are used for functional validation against recordings in vivo, monitoring the impact of cellular mechanisms on signal propagation, inhibitory control, and long-term synaptic plasticity. Our simulations show how mossy fibers entrain the local neuronal microcircuit, boosting the formation of columns of activity travelling from the granular to the molecular layer providing a new resource for the investigation of local microcircuit computation and of the neural correlates of behavior.


Subject(s)
Cerebellar Cortex , Models, Neurological , Mice , Animals , Cerebellar Cortex/physiology , Cerebellum/physiology , Neuronal Plasticity/physiology , Neurons/physiology
3.
Sci Rep ; 12(1): 13864, 2022 08 16.
Article in English | MEDLINE | ID: mdl-35974119

ABSTRACT

The modeling of extended microcircuits is emerging as an effective tool to simulate the neurophysiological correlates of brain activity and to investigate brain dysfunctions. However, for specific networks, a realistic modeling approach based on the combination of available physiological, morphological and anatomical data is still an open issue. One of the main problems in the generation of realistic networks lies in the strategy adopted to build network connectivity. Here we propose a method to implement a neuronal network at single cell resolution by using the geometrical probability volumes associated with pre- and postsynaptic neurites. This allows us to build a network with plausible connectivity properties without the explicit use of computationally intensive touch detection algorithms using full 3D neuron reconstructions. The method has been benchmarked for the mouse hippocampus CA1 area, and the results show that this approach is able to generate full-scale brain networks at single cell resolution that are in good agreement with experimental findings. This geometric reconstruction of axonal and dendritic occupancy, by effectively reflecting morphological and anatomical constraints, could be integrated into structured simulators generating entire circuits of different brain areas facilitating the simulation of different brain regions with realistic models.


Subject(s)
Models, Neurological , Neurons , Algorithms , Animals , Axons , Computer Simulation , Mice , Neurons/physiology
4.
Mech Ageing Dev ; 184: 111150, 2019 12.
Article in English | MEDLINE | ID: mdl-31574270

ABSTRACT

In most species, females live longer than males. An understanding of this female longevity advantage will likely uncover novel anti-aging therapeutic targets. Here we investigated the transcriptomic responses in the hypothalamus - a key organ for somatic aging control - to the introduction of a simple aging-related molecular perturbation, i.e. GIT2 heterozygosity. Our previous work has demonstrated that GIT2 acts as a network controller of aging. A similar number of both total (1079-female, 1006-male) and gender-unique (577-female, 527-male) transcripts were significantly altered in response to GIT2 heterozygosity in early life-stage (2 month-old) mice. Despite a similar volume of transcriptomic disruption in females and males, a considerably stronger dataset coherency and functional annotation representation was observed for females. It was also evident that female mice possessed a greater resilience to pro-aging signaling pathways compared to males. Using a highly data-dependent natural language processing informatics pipeline, we identified novel functional data clusters that were connected by a coherent group of multifunctional transcripts. From these it was clear that females prioritized metabolic activity preservation compared to males to mitigate this pro-aging perturbation. These findings were corroborated by somatic metabolism analyses of living animals, demonstrating the efficacy of our new informatics pipeline.


Subject(s)
Aging/genetics , Aging/physiology , GTPase-Activating Proteins/genetics , GTPase-Activating Proteins/physiology , Hypothalamus/metabolism , Animals , Cluster Analysis , Computational Biology , Female , Longevity/genetics , Longevity/physiology , Male , Mice , Mice, Inbred C57BL , RNA/biosynthesis , RNA/genetics , Sex Characteristics , Signal Transduction/genetics , Signal Transduction/physiology , Transcriptome
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