CFP: Multilayer networks and mechanisms in neuroscience and psychiatry (Synthese Topical Collection)

Final Call for Papers / Extended Deadline (30-04-2021)

Synthese Topical Collection on

Multilayer networks and mechanisms in neuroscience and psychiatry

Guest Editors

Leon de Bruin (Radboud University Nijmegen)

Beate Krickel (Technische Universität Berlin)

Linda Douw (Amsterdam UMC)

Description

The mechanistic explanatory strategy has had considerable success in various neuroscientific subdisciplines, including molecular, cognitive and computational neuroscience. Systems neuroscience, however, with its focus on the study of networks at various levels of brain organization, has proven to be a challenge. It is commonly accepted that mechanistic explanation involves structural and functional decomposition  - breaking down a system into concrete parts and activities in order to identify the causal relationships that realize the phenomenon. But systems neuroscientists seem to abstract away from concrete parts and activities and instead focus on general properties of neural networks, such as robustness and functional redundancy. Indeed, it has been suggested that systems neuroscientists provide topological explanations, which aim to explain how a system can resist or react to various perturbations. Some have argued that these explanations can still count as mechanistic, as long as we are willing to consider a less restrictive notion of mechanistic explanation that focuses primarily on the identification of causal relationships. By contrast, those who emphasize the importance of structural decomposition in neuroscientific research have claimed that topological explanations are not explanations at all.

The aim of this special issue is to address these questions about mechanistic, causal and topological explanation in the light of recent research on multilayer networks or ‘multiplexes’, in which variables (“nodes”) are connected to each other via multiple types of connections (“edges”). From a neuroscientific point of view, multiplexes are promising because they provide a unique opportunity to integrate and analyze information from various measurement techniques, such as diffusion-weighted magnetic resonance imaging (DWI), magnetoencephalography (MEG), electroencephalography (EEG), and functional magnetic resonance imaging (fMRI). For example, multiplexes can be used to study the interaction between structural/anatomical connectivity (obtained with DWI) and functional connectivity (obtained with fMRI), and in this way further our understanding of the interplay between brain structure and function. However, multiplexes can in principle also accommodate very different kinds of information – not just brain-based information, but also e.g., information from patient questionnaires, symptoms of mental disorders and social interaction patterns. This makes the multiplex a very promising model to bridge the gap between fundamental neuroscience and other scientific disciplines. Indeed, recent approaches in psychiatry have proposed to understand mental disorders in terms of symptom networks. Thus far, these approaches have mainly focused on how individual symptoms dynamically interact so as to sustain the other symptoms, but they could be extended into multilayer networks that can accommodate other kinds of information as well. 

We invite contributions that, among others:

·        investigate what kind of explanation multilayer networks provide. To what extent do they qualify as causal-mechanistic explanations? Are multilayer networks explanatory at all? Or are they primarily predictive?

·        determine the scope of multilayer network analysis (e.g., constraints on the kinds of information that can be included), and investigate the key concepts (e.g., the concept of level) and measurements (e.g., centrality measures) involved 

·        examine how multilayer networks can further our understanding of the interplay between different types of information (e.g., information about structural, functional and effective connectivity) and what kinds of connections can be included (e.g., it is possible to include intentional relations in a multilayer network account of mental disorder?)

·        discuss case studies in systems neuroscience, psychiatry and other scientific disciplines, in which the promises and pitfalls of multilayer networks and their explanatory/predictive role is highlighted

·        present new insights in how to integrate and analyze information from various measurement techniques in neuroscience, psychiatry and other scientific disciplines

·        investigate the connection between multilayer network analysis and more general topics in philosophy of science such as reductive explanation and explanatory depth

For any further information, please contact the Guest Editors:

·        Leon de Bruin, [email protected]

·        Beate Krickel, [email protected]

·        Linda Douw, [email protected]

Important dates and procedures

WHEN: The submissions portal will be open until April 30 2021.

WHERE: Submit your paper through the Synthese Editorial Manager under a dedicated heading entitled "T.C.: Multilayer networks and mechanisms in neuroscience and psychiatry".

Please visit Editorial Manager and select this heading when submitting the manuscript.

HOW: Submitted papers will be peer-reviewed as per usual journal practice. Typically, two reviewers will be assigned to each paper and final decisions will be taken by Synthese Editors in Chief, following the recommendation of the Guest Editors, which is based on the reviewers’ reports. Please prepare papers for anonymous reviews.