Biology subjects

Hinz, R.

Publications and source records attributed to Hinz, R..

5 recordsLinked to original sources

bioRxiv2021

An in-vivo digital atlas of the spatially reliable cerebral vasculature in mice

Cerebral vascular abnormalities can have a large impact on brain function and have been frequently detected as a comorbidity in various neuropathologies. The mouse is the most common pre-clinical animal model used to investigate neuropathologies and thus cerebral vascular atlases of this species are indispensable. In particular, an atlas derived from multiple animals and that can address inter-subject variability is still absent. The current study presents a mouse cerebral vascular atlas developed from MR 2D-TOF angiograms acquired from a relatively high number (N=21) of 12 weeks old male C57BL/6 mice. The vascular atlas we present depicts large arteries, veins and sinuses that are more spatially reliable across animals than smaller vessels. The atlas is available for download and contains multiple datasets: i) a cerebral vascular atlas; ii) a digital segmentation of large vessels (arteries and veins); iii) a high resolution T2 anatomical background aligned to the atlas; iv) a skeletonized vascular atlas; and v) a vascular graph model. We suggest that these components provide a very potent analysis tool for mouse fMRI data and that the atlas can be used as a template for multimodal brain imaging studies. To this end, we also demonstrate an explicit application of the atlas for the investigation of vascular influences in resting-state fMRI.

neuroscience↗

bioRxiv2019

Chemogenetic silencing of neurons in the mouse anterior cingulate area modulates neuronal activity and functional connectivity

The anterior cingulate area (ACA) is an integral part of the prefrontal cortex in mice and has been implicated in several cognitive functions. Previous anatomical and functional imaging studies demonstrated that the ACA is highly interconnected with numerous brain regions acting as a hub region in functional networks. However, the importance of the ACA in regulating functional network activity and connectivity remains to be elucidated. Recently developed neuromodulatory techniques, such as Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) allow for precise control of neuronal activity. In this study, we used an inhibitory kappa-opioid receptor DREADDs (KORD) to temporally inhibit neuronal firing in the right ACA of mice and assessed functional network activity and connectivity using non-invasive functional MRI. We demonstrated that KORD-induced inhibition of the right ACA induced blood oxygenation-level dependent (BOLD) signal decreases and increases in connected brain regions throughout of hemispheres. Furthermore, these modulations in neuronal activity were associated with decreased intra- and interhemispheric functional connectivity. These results demonstrate that the combination of the DREADD technology and non-invasive functional imaging methods is a valuable tool for unraveling the underlying mechanisms of network function and dysfunction.

neuroscience↗

bioRxiv2019

Resting brain fluctuations are intrinsically coupled to visual response dynamics

How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional (f)MRI to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) govern mouse resting brain dynamics. QPPs captured the temporal alignment of global brain fluctuations, anti-correlation of the Default Mode (DMN)- and Task Positive (TPN)-like networks, and activity in neuromodulatory nuclei of the reticular formation. While visual stimulation could trigger a transient spatiotemporal pattern highly similar to intrinsic QPPs, global signal fluctuations and QPPs during rest periods could explain variance in the following visual responses. QPPs and the global signal thus appeared to capture a common arousal-related brain-state fluctuation, orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.

neuroscience↗

bioRxiv2018

Bottom-up sensory processing can decrease activity and functional connectivity in the default mode like network in rats.

The default mode network is a large-scale brain network that is active during rest and internally focused states and deactivates as well as desynchronizes during externally oriented (top-down) attention demanding cognitive tasks. However, it is not sufficiently understood if unpredicted salient stimuli, able to trigger bottom-up attentional processes, could also result in similar reduction of activity and functional connectivity in the DMN. In this study, we investigated whether bottom-up sensory processing could influence the default mode like network (DMLN) in rats. DMLN activity was examined using block-design visual functional magnetic resonance imaging (fMRI) while its synchronization was investigated by comparing functional connectivity during a resting versus a continuously stimulated brain state by unpredicted light flashes. We demonstrated that activity in DMLN regions was decreased during visual stimulus blocks and increased during blanks. Furthermore, decreased inter-network functional connectivity between the DMLN and visual networks as well as decreased intra-network functional connectivity within the DMLN was observed during the continuous visual stimulation. These results suggest that triggering of bottom-up attention mechanisms in anesthetized rats can lead to a cascade similar to top-down orienting of attention in humans and is able to deactivate and desynchronize the DMLN.

neuroscience↗

bioRxiv2018

idtracker.ai: Tracking all individuals in large collectives of unmarked animals

Our understanding of collective animal behavior is limited by our ability to track each of the individuals. We describe an algorithm and software, idtracker.ai, that extracts from video all trajectories with correct identities at a high accuracy for collectives of up to 100 individuals. It uses two deep networks, one detecting when animals touch or cross and an-other one for animal identification, trained adaptively to conditions and difficulty of the video.

animal behavior and cognition↗