TY - JOUR
T1 - Realistic modeling of neurons and networks
T2 - Towards brain simulation
AU - D'Angelo, Egidio
AU - Solinas, Sergio
AU - Garrido, Jesus
AU - Casellato, Claudia
AU - Pedrocchi, Alessandra
AU - Mapelli, Jonathan
AU - Gandolfi, Daniela
AU - Prestori, Francesca
PY - 2013
Y1 - 2013
N2 - Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field.
AB - Realistic modeling is a new advanced methodology for investigating brain functions. Realistic modeling is based on a detailed biophysical description of neurons and synapses, which can be integrated into microcircuits. The latter can, in turn, be further integrated to form large-scale brain networks and eventually to reconstruct complex brain systems. Here we provide a review of the realistic simulation strategy and use the cerebellar network as an example. This network has been carefully investigated at molecular and cellular level and has been the object of intense theoretical investigation. The cerebellum is thought to lie at the core of the forward controller operations of the brain and to implement timing and sensory prediction functions. The cerebellum is well described and provides a challenging field in which one of the most advanced realistic microcircuit models has been generated. We illustrate how these models can be elaborated and embedded into robotic control systems to gain insight into how the cellular properties of cerebellar neurons emerge in integrated behaviors. Realistic network modeling opens up new perspectives for the investigation of brain pathologies and for the neurorobotic field.
KW - Computation
KW - Neuron models
KW - Plasticity
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U2 - 10.11138/FNeur/2013.28.3.153
DO - 10.11138/FNeur/2013.28.3.153
M3 - Article
C2 - 24139652
AN - SCOPUS:84886931814
VL - 28
SP - 153
EP - 166
JO - Functional Neurology
JF - Functional Neurology
SN - 0393-5264
IS - 3
ER -