Learning from large scale neural simulations

TY - CHAP

T1 - Learning from large scale neural simulations

AU - Serban, Maria

PY - 2017

Y1 - 2017

N2 - Large-scale neural simulations have the marks of a distinct methodology which can be fruitfully deployed in neuroscience. I distinguish between two types of applications of the simulation methodology in neuroscientific research. Model-oriented applications aim to use the simulation outputs to derive new hypotheses about brain organization and functioning and thus to extend current theoretical knowledge and understanding in the field. Data-oriented applications of the simulation methodology target the collection and analysis of data relevant for neuroscientific research that is inaccessible via more traditional experimental methods. I argue for a two-stage evaluation schema which helps clarify the differences and similarities between three current large-scale simulation projects pursued in neuroscience.

AB - Large-scale neural simulations have the marks of a distinct methodology which can be fruitfully deployed in neuroscience. I distinguish between two types of applications of the simulation methodology in neuroscientific research. Model-oriented applications aim to use the simulation outputs to derive new hypotheses about brain organization and functioning and thus to extend current theoretical knowledge and understanding in the field. Data-oriented applications of the simulation methodology target the collection and analysis of data relevant for neuroscientific research that is inaccessible via more traditional experimental methods. I argue for a two-stage evaluation schema which helps clarify the differences and similarities between three current large-scale simulation projects pursued in neuroscience.

KW - Faculty of Humanities

KW - computer simulations

KW - brain science

M3 - Book chapter

SN - 9780128042151

SP - 129

EP - 148

BT - Modeling brains: The making and use of models in neuroscience and psychiatry

PB - Elsevier

CY - Amsterdam

ER -