A taxonomy of neuroscientific strategies based on interaction orders
- Matteo Neri,
- Andrea Brovelli,
- Samy Castro,
- Fausto Fraisopi,
- Marilyn Gatica,
- Ruben Herzog,
- Ivan Mindlin,
- Pedro Mediano,
- Giovanni Petri,
- Daniel Bor,
- Fernando Rosas,
- Antonella Tramacere ,
- Mar Estarellas
Abstract
In recent decades, neuroscience has advanced with increasingly
sophisticated strategies for recording and analyzing brain activity,
enabling detailed investigations into the roles of functional units,
such as individual neurons, brain regions, and their interactions.
Recently, new strategies for the investigation of cognitive functions
regard the study of higher-order interactions---that is, the
interactions involving more than two brain regions or neurons. While
methods focusing on individual units and their interactions at various
levels offer valuable and often complementary insights, each approach
comes with its own set of limitations. In this context, a conceptual map
to categorize and locate diverse strategies could be crucial to orient
researchers and guide future research directions. To this end, we define
the spectrum of orders of interaction, namely a framework that
categorizes the interactions among neurons or brain regions based on the
number of elements involved in these interactions. We use a simulation
of a toy model and a few case studies to demonstrate the utility and the
challenges of the exploration of the spectrum. We conclude by proposing
future research directions aimed at enhancing our understanding of brain
function and cognition through a more nuanced methodological framework.19 Aug 2024Submitted to European Journal of Neuroscience 21 Aug 2024Submission Checks Completed
21 Aug 2024Assigned to Editor
25 Aug 2024Review(s) Completed, Editorial Evaluation Pending
30 Aug 2024Reviewer(s) Assigned
18 Oct 2024Editorial Decision: Revise Minor
15 Nov 20241st Revision Received
18 Nov 2024Review(s) Completed, Editorial Evaluation Pending
18 Nov 2024Submission Checks Completed
18 Nov 2024Assigned to Editor
18 Nov 2024Reviewer(s) Assigned