NEST Conference 2022

Unified Descriptions and Depictions of Network Connectivity

T-6

24 Jun 2022, 11:15

25m

Virtual

Talk & (optional) poster Main track Talks

Speaker

Sacha J. van Albada (Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institut Brain Structure-Function Relationships (INM-10), Jülich Research Centre, Jülich, Germany; Institute of Zoology, University of Cologne, Cologne, Germany)

Description

Computational neuroscientists have not yet agreed on a common way to describe high-level connectivity patterns in neuronal network models. Furthermore, different studies use different symbols to represent connectivity in network diagrams. This diversity of connectivity descriptions and depictions makes it more difficult to understand and reproduce modeling results. This issue is compounded by the fact that certain aspects of the connectivity that would be necessary for its unambiguous interpretation, such as whether self-connections are allowed, are sometimes omitted from descriptions. A review of published models from the databases ModelDB [1] and Open Source Brain [2] reveals that, despite models mostly still having simple connectivity, ambiguities in their description and depiction are not uncommon. From the use of connectivity in existing models, along with a review of simulation software (e.g., NEST [3]) and specification languages (e.g., CSA [4]), we derive a set of connectivity concepts for which we propose unified terminology with precise mathematical meanings [5]. We further propose a graphical notation to represent connectivity in network diagrams. These standardized descriptions and depictions enable modelers to specify connectivity concisely and unambiguously. Moreover, the derived concepts may serve to guide the implementation and naming of high-level connection routines in simulators like NEST.

References

1. ModelDB [https://senselab.med.yale.edu/modeldb]
   1. Gleeson P, Cantarelli M, Marin B, . . . van Albada SJ, van Geit W, R Silver RA (2019) Open Source Brain: a collaborative resource for visualizing, analyzing, simulating and developing standardized models of neurons and circuits. Neuron 3:395-411.
   2. Gewaltig M-O and Diesmann M (2007). NEST (NEural Simulation Tool). Scholarpedia. 2(4):1430, doi:10.4249/scholarpedia.1430
   3. Djurfeldt M (2012) The connection-set algebra—a novel formalism for the representation of connectivity structure in neuronal network models. Neuroinform. 10:287–304. doi:10.1007/s12021-012-9146-1
   4. Senk J, Kriener B, Djurfeldt M, Voges N, Jiang H-J, Schüttler L, Gramelsberger G, Diesmann M, Plesser HE, van Albada SJ (in press) Connectivity concepts in neuronal network modeling. PLoS Comput Biol.

Acknowledgements

This project received funding from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under grant agreements 785907 (HBP SGA2), 945539 (HBP SGA3), and 754304 (DEEP-EST); Deutsche Forschungsgemeinschaft grants 368482240/GRK2416: ‘‘RTG 2416 Multi-senses Multi-scales’’ and AL 2041/1-1 of Priority Program 2041; the Helmholtz Association Initiative and Networking Fund SO-092 (ACA); the Excellence Initiative of the German federal and state governments (neuroIC001): “ERS: disziplinärer Paketantrag NeuroIC: NeuroModelingTalk (NMT) Approaching the complexity barrier in neuroscientific modeling”; and the Helmholtz Metadata Collaboration (HMC) under grant ZT-I-PF-3-026.