Back

The Cerebellar Engine: Multiscale Digital Brain Co-simulations Reveal How Cerebellar Spiking Architecture Shapes Cortical Coherence

Geminiani, A.; Meier, J. M.; Perdikis, D.; Ouertani, S.; Casellato, C.; Ritter, P.; D'Angelo, E. U.

2026-04-04 neuroscience
10.64898/2026.04.02.715849 bioRxiv
Show abstract

The impact of cellular activities on large-scale brain dynamics is thought to determine brain functioning and disease, yet the causal relationships of neural mechanisms across scales remain unclear. Recently, the cerebellum has been reported to affect whole-brain dynamics during sensorimotor integration. To disclose the underlying mechanisms, we have developed a multiscale digital brain co-simulator, in which a spiking neural network of the olivo-cerebellar microcircuit is embedded in a mouse virtual brain and wired with other nodes using an atlas-based long-range connectome. Parameters and bi-directional interfaces between the spiking olivo-cerebellar network and other rate-coded modules were tuned to match experimental data of primary sensory and motor cortex (M1 and S1) power spectral densities and neuronal spiking rates. Then, the role of the cerebellar circuitry on sensorimotor integration was analyzed by lesioning critical circuit connections in silico. Simulations showed that spike processing within the cerebellar circuit is key to explaining the gamma-band coherence between M1 and S1 during sensorimotor integration. These results provide a mechanistic explanation of how the cerebellum promotes the formation of sensorimotor contingencies in relevant cortical modules as the basis of its critical role in sensorimotor prediction. On a broader perspective, this modelling approach opens new perspectives for the multiscale investigation of brain physiological and pathological states in relation to specific cellular and microcircuit properties.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Frontiers in Computational Neuroscience
53 papers in training set
Top 0.1%
14.8%
2
PLOS Computational Biology
1633 papers in training set
Top 2%
12.4%
3
Advanced Science
249 papers in training set
Top 2%
7.2%
4
National Science Review
22 papers in training set
Top 0.1%
7.2%
5
eLife
5422 papers in training set
Top 11%
6.8%
6
Nature Communications
4913 papers in training set
Top 35%
4.3%
50% of probability mass above
7
Cell Reports
1338 papers in training set
Top 13%
4.0%
8
NeuroImage
813 papers in training set
Top 2%
4.0%
9
Communications Biology
886 papers in training set
Top 2%
3.6%
10
iScience
1063 papers in training set
Top 10%
2.1%
11
Neurocomputing
13 papers in training set
Top 0.2%
1.7%
12
Neuroscience Bulletin
11 papers in training set
Top 0.3%
1.7%
13
Science Advances
1098 papers in training set
Top 17%
1.7%
14
Science Bulletin
22 papers in training set
Top 0.3%
1.7%
15
Neural Networks
32 papers in training set
Top 0.4%
1.7%
16
Communications Physics
12 papers in training set
Top 0.2%
1.5%
17
Progress in Neurobiology
41 papers in training set
Top 1%
1.3%
18
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 36%
1.3%
19
Scientific Reports
3102 papers in training set
Top 66%
1.2%
20
PNAS Nexus
147 papers in training set
Top 0.6%
1.2%
21
Network Neuroscience
116 papers in training set
Top 0.9%
1.0%
22
Science China Life Sciences
26 papers in training set
Top 2%
0.8%
23
Human Brain Mapping
295 papers in training set
Top 4%
0.8%
24
Frontiers in Systems Neuroscience
19 papers in training set
Top 0.4%
0.8%
25
Physical Review Research
46 papers in training set
Top 1%
0.6%
26
Neuron
282 papers in training set
Top 9%
0.6%
27
Chaos, Solitons & Fractals
32 papers in training set
Top 2%
0.6%
28
Cerebral Cortex
357 papers in training set
Top 2%
0.6%