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Mesoscale Brain Dynamics: Computing with Neuronal Pathways

Periodic Reporting for period 3 - BRAINCOMPATH (Mesoscale Brain Dynamics: Computing with Neuronal Pathways)

Reporting period: 2019-02-01 to 2020-07-31

In this project we address the fundamental question of how information processing takes place in the mammalian brain. The brain of mammals such as mice, rats, non-human primates and humans consists of a myriad of brain cells, which are interconnected to form a gigantic complex excitable network. To a large part signal flow through this distributed network is based on the electrical excitability of the neurons. Despite a wealth of previous neuroscientific studies, both on the anatomy and the function of neurons in various brain regions, we still poorly understand the principles of how signal flow is routed through neuronal networks to generate appropriate behavior. Brain dynamics on the 'mesoscopic' scale, the intermediate level where brain regions communicate via axonal pathways, has remained a particular blind spot of research as it has been difficult to access under relvenat conditions when the brain is performeing a particular task. Understanding how brains efficiently solve computational tasks is important and relevant for the society because (1) improved knowledge about the healthy brain's functioning will also open new opportunities to understand brain disorders and brain diseases, and (2) insights into the operating principles of the brain could inspire new types of information processing devices. The overall objective of the project is to tackle the mesoscopic level of brain dynamics both experimentally and theoretically, adopting a fresh perspective centered on neuronal pathway dynamics. Experimentally, we will utilize and further advance state-of-the-art genetic and optical techniques to create a toolbox for measuring and manipulating signal flow in pathway networks across a broad range of temporal scales. In particular, we will improve fiber-optic based methods for probing the activity of either individual or multiple neuronal pathways with high specificity. Using these tools we will set out to reveal mesoscopic brain dynamics across relevant cortical and subcortical regions in awake, behaving mice. Specifically, we will investigate sensorimotor learning for a reward-based texture discrimination task and rapid sensorimotor control during skilled locomotion. Moreover, by combining fiber-optic methods with two-photon microscopy and fMRI, respectively, we will start linking the meso-level to the micro- and macro-levels. Throughout the project, experiments will be complemented by computational approaches to analyse data, model pathway dynamics, and conceptualize a formal theory of mesoscopic dynamics. This project may transform the field by bridging the hierarchical brain levels and opening significant new avenues to assess physiological as well as pathological signal flow in the brain.
In the 4.5 years of the project, we made excellent progress towards the project's objectives. Specifically, the experimental approaches for investigations of brain dynamics on the mesoscale were largely advanced, including wide-field calcium imaging, multi-fiber photometry, and a novel light-sheet microscope for imaging large cleared tissue volumes, e.g. entire mouse brains. The development and application of these new methods resulted in 2 Nature Methods articles, 2 Neuron articles, and articles in Nature and Nature Communications. We addressed the scientific questions about the principles of behavior-related mesoscale brain dynamics by applying these methods in particular to mice performing sensory discrimination tasks. Thereby we gained important insights into the interactions between multiple brain regions during sensorimotor processing and during short-term memory. We identified the posterior parietal cortex (PPC) as a hub region for behavior-dependent routing of cortical signals towards either posterior association areas or frontal premotor cortex regions. In several studies, we performed chronic experiments over many weeks to investigate how brain activity patterns change during learning and adapt to altered task rules. Projections from the lateral orbitofrontal cortex (OFC) to the primary sensory area (S1) were found to implement a functional remapping of a subpopulation of neurons in S1 as basis of the adaptations after a rule switch. Several projects are still ongoing and will be completed in the remaining period of the project.
New scientific insights have already emerged from the experiments conducted in this project. For example, large-scale patterns of activity in the neocortex were identified, which relate to holding relevant information in short-term memory. The new experimental method of multi-fiber photometry moves beyond the current state-of-the-art by enabling simultaneous measurements of activity in many brain regions. This method opens entire new avenues to investigate mesoscale signal flow in the brain during specific behaviors. Until the end of the project we expect to have gained signifcant insight into the large-scale activity patterns as they occur in a sensory discrimination task and also how these activity patterns emerge during learning. We expect to have by the end of the project a general theoretical framework that describes mesoscale brain dynamics and a reduced specific model of the dynamics occuring during sensory discrimination.
Mesoscale brain dynamics during sensory discrimination (Gallero-Salas et al., 2021, Neuron 109:1).