This title appears in the Scientific Report :
2019
Please use the identifier:
http://hdl.handle.net/2128/24253 in citations.
Please use the identifier: http://dx.doi.org/10.31234/osf.io/zk2dy in citations.
Neuronal Causes and Behavioural Effects: a Review on Logical, Methodological, and Technical Issues With Respect to Causal Explanations of Behaviour in Neuroscience
Neuronal Causes and Behavioural Effects: a Review on Logical, Methodological, and Technical Issues With Respect to Causal Explanations of Behaviour in Neuroscience
Elucidating causal, neurobiological underpinnings of behaviour is an ultimate goal of every neuroscientific study. However, due to the complexity of the brain as well as the complexity of the human environment, finding a~causal architecture that underlies behaviour remains a~formidable challenge. In...
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Personal Name(s): | Fakhar, Kayson (Corresponding author) |
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Gonschorek, Dominic / Schmors, Lisa / Bielczyk, Natalia Z | |
Contributing Institute: |
Computational and Systems Neuroscience; INM-6 Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 |
Imprint: |
2019
|
DOI: |
10.31234/osf.io/zk2dy |
Document Type: |
Preprint |
Research Program: |
SMARTSTART Training Program in Computational Neuroscience Theory, modelling and simulation |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.31234/osf.io/zk2dy in citations.
Elucidating causal, neurobiological underpinnings of behaviour is an ultimate goal of every neuroscientific study. However, due to the complexity of the brain as well as the complexity of the human environment, finding a~causal architecture that underlies behaviour remains a~formidable challenge. In this manuscript, we review the logical and conceptual issues with respect to causal research in neuroscience.First, we review the state of the art interventional and computational approaches to infer causal brain-behaviour relationships. We provide an~overview of potential issues, flaws, and confounds in these studies. We conclude that studies on the causal structure underlying behaviour should be performed by accumulating evidence coming from several lines of experimental and modelling studies. Lastly, we also propose computational models including artificial neuronal networks and simulated animats as a~potential breakthrough to causal brain-behaviour investigations. |