SFBs

Collaborative Research Centre SFB 936: Multi-site communication in the brain

URL: http://sfb936.net

Coordinators: Andreas K. Engel (Dept. of Neurophysiology, UKE) and Christian Gerloff (Dept. of Neurology, UKE)

Principal investigators from the Dept. of Neurophysiology: Andreas Engel, Tobias Donner, Christian Moll, Guido Nolte, Till Schneider

This CRC has been established by the DFG in 2011, has been extended into its third funding period in 2019 and will now run until June 2023.

Cognitive processes, such as perception, memory, attentional control, emotion, decision making, action planning, or conscious awareness, are based on the activation of highly distributed networks involving numerous interacting neuronal assemblies in multiple regions of the central nervous system. The essence of a normally functioning brain is proper connectivity. Neurological and psychiatric disorders causing disturbances in any of these cognitive domains, accordingly, involve malfunctions in distributed networks. Current concepts of brain function are still largely based on the notion of local processing and specialization of brain areas. The overarching hypothesis pursued by the SFB 936 is that the crucial determinant of behavior is neuronal network interaction and not local processing. Research of the SFB is structured in three thematic areas:

A. Multi-site communication as a basis of cognition;
B. Multi-site interactions during development, plasticity and learning;
C. Altered multi-site communication in brain disorders.

In the first funding period, the SFB has successfully applied a multi-level approach for the analysis of large-scale networks, combining different methods such as psychophysics, electro-/magnetoencephalography, functional and structural magnetic resonance imaging, multi-site microelectrode recordings, morphological-structural analyses and computational modeling. In the second funding period, the SFB 936 has extended its activities by complementing network investigation and analysis with approaches for modulation of networks, such as optogenetics, electrical stimulation, magnetic stimulation, pharmacology, and behavioral training interventions. Furthermore, computational modeling of networks has been strengthened in the second funding period. While pursuing the same overarching theme, the SFB 936 moves in the third funding period from analyzing, modulating and modeling networks towards functional and behavioral relevance of distinct network components and their spatiotemporal dynamics in health, development, and disease. Moreover, the SFB now consolidates its integrated perspective on large-scale brain networks by working towards closing gaps that have been identified, such as bridging between different scales of network investigation and integrating results across different subnetworks that have been studied.

Collaborative Research Centre SFB TRR 169: Cross-modal learning – Adaptivity, prediction and interaction

URL: https://www.crossmodal-learning.org

Coordinator: Jianwei Zhang (Dept. of Computer Science, University of Hamburg)

Principal investigators from the Dept. of Neurophysiology: Andreas Engel, Guido Nolte

This CRC has been established by the DFG in 2015, has been extended into its second funding period in 2019, which will run from 2020-2023.

The term “crossmodal learning” refers to the adaptive, synergistic integration of complex perceptions from multiple sensory modalities, such that the learning that occurs within any individual sensory modality can be enhanced with information from one or more other modalities. Crossmodal learning is crucial for human understanding of the world, and examples are ubiquitous, such as learning to grasp and manipulate objects, learning to read and write, learning to understand language, etc. In all these examples, visual, auditory, somatosensory, or other modalities have to be integrated. The long-term goal of the research in the CRC is to develop an interdisciplinary understanding of the neural, cognitive, and computational mechanisms of crossmodal learning. This understanding will allow us to pursue the following primary sub-goals of the research programme:

(1) to enrich our current understanding of the multisensory processes underlying the human mind and brain,
(2) to create detailed formal models that describe crossmodal learning in both humans and machines, and
(3) to build artificial systems for tasks requiring a crossmodal conception of the world.

This CRC continues and expands an interdisciplinary cooperation between the existing fields of computer science, psychology, and neuroscience, focused on strengthening the newly established discipline of crossmodal learning. Based on a successful first funding period and extensive groundwork of collaborative research between Germany and China, the second phase of the CRC is jointly funded by the DFG and the NSFC (Natural Science Foundation of China) as an international collaboration between the University of Hamburg, the University Medical Center Hamburg Eppendorf and the three top universities in China (Tsinghua, Beijing Normal, and Peking University) as well as the Institute of Psychology of the Chinese Academy of Sciences, all located in Beijing, China.