2020

  • Journal of Molecular Biology 432:3722-3737 (2020)

    Authors:
    Ananthasubramaniam, B., Schmal, C., & Herzel, H.

    Abstract:

    Mathematical models of varying complexity have helped shed light on different aspects of circadian clock function. In this work, we question whether minimal clock models (Goodwin models) are sufficient to reproduce essential phenotypes of the clock: a small phase response curve (PRC), fast jet lag, and seasonal phase shifts. Instead of building a single best model, we take an approach where we study the properties of a set of models satisfying certain constraints; here, a 1h-pulse PRC with a range of 3h and clock periods between 22h and 26h is designed. Surprisingly, almost all these randomly parameterized models showed a 4h change in phase of entrainment between long and short days and jet lag durations of three to seven days in advance and delay. Moreover, intrinsic clock period influenced jet lag duration and entrainment amplitude and phase. Fast jet lag was realized in this model by means of an interesting amplitude effect: the association between clock amplitude and clock period termed “twist.” This twist allows amplitude changes to speed up and slow down clocks enabling faster shifts. These findings were robust to the addition of positive feedback to the model. In summary, the known design principles of rhythm generation – negative feedback, long delay, and switch-like inhibition (we review these in detail) – are sufficient to reproduce the essential clock phenotypes. Furthermore, amplitudes play a role in determining clock properties and must be always considered, although they are difficult to measure.

    Link

  • Journal of Comparative Neurology, 528(10), 1754-1774 (2020)

    Authors:
    Arnold, T., Korek, S., Massah, A., Eschstruth, D., & Stengl, M.

    Abstract:

    Circadian clocks control rhythms in physiology and behavior entrained to 24 h light – dark cycles. Despite of conserved general schemes, molecular circadian clockworks differ between insect species. With RNA interference (RNAi) we examined an ancient circadian clockwork in a basic insect, the hemimetabolous Madeira cockroach Rhyparobia maderae. With injections of double-stranded RNA (dsRNA) of cockroach period (Rm´per), timeless 1 (Rm´tim1), or cryptochrome 2 (Rm´cry2) we searched for essential components of the clock´s core feedback loop. A single injection of dsRNA of each clock gene into adult cockroaches successfully and permanently knocked down respective mRNA levels within ~two weeks, deleting daytime-dependent mRNA rhythms for all three clock genes tested. Rm´perRNAi or Rm´cry2RNAi affected both genes, while Rm´tim1 was independent of both. Unexpectedly, circadian locomotor rhythms always remained. They expressed normal periods for Rm´perRNAi and shorter periods for Rm´tim1RNAi and Rm´cry2RNAi. As a hypothesis of the cockroach´s molecular clockwork, a network of switched differential equations was developed to model the oscillatory behavior of clock cells expressing the clock genes. Data were consistent with coupled oscillator cells expressing different periods based on core feedback loops with either PER, TIM1, or CRY2/PER complexes as negative feedback of the clockwork.

    Link

  • bioRxiv (2020)

    Authors:
    Baum, D., Lindow, N., Brünig, F. N., Dercksen, V. J., Fabig, G., Kiewisz, R., … & Prohaska, S.

    Abstract:

    We present a software-assisted workflow for the alignment and matching of filamentous structures across a 3D stack of serial images. This is achieved by combining automatic methods, visual validation, and interactive correction. After an initial alignment, the user can continuously improve the result by interactively correcting landmarks or matches of filaments. Supported by a visual quality assessment of regions that have been already inspected, this allows a trade-off between quality and manual labor. The software tool was developed to investigate cell division by quantitative 3D analysis of microtubules (MTs) in both mitotic and meiotic spindles. For this, each spindle is cut into a series of semi-thick physical sections, of which electron tomograms are acquired. The serial tomograms are then stitched and non-rigidly aligned to allow tracing and connecting of MTs across tomogram boundaries. In practice, automatic stitching alone provides only an incomplete solution, because large physical distortions and a low signal-to-noise ratio often cause experimental difficulties. To derive 3D models of spindles despite the problems related to sample preparation and subsequent data collection, semi-automatic validation and correction is required to remove stitching mistakes. However, due to the large number of MTs in spindles (up to 30k) and their resulting dense spatial arrangement, a naive inspection of each MT is too time consuming. Furthermore, an interactive visualization of the full image stack is hampered by the size of the data (up to 100 GB). Here, we present a specialized, interactive, semi-automatic solution that considers all requirements for large-scale stitching of filamentous structures in serial-section image stacks. The key to our solution is careful design of the visualization and interaction tools for each processing step to guarantee real-time response, and an optimized workflow that efficiently guides the user through datasets.

    Link

  • eLIFE 9:e53148 (2020)

    Authors:
    Braganza, O., Müller-Komorovska, D., Kelly, T., Beck, H

    Abstract:

    Feedback inhibitory motifs are thought to be important for pattern separation across species. How feedback circuits may implement pattern separation of biologically plausible, temporally structured input in mammals is, however, poorly understood. We have quantitatively determined key properties of netfeedback inhibition in the mouse dentate gyrus, a region critically involved in pattern separation. Feedback inhibition is recruited steeply with a low dynamic range (0% to 4% of active GCs), and with a non-uniform spatial profile. Additionally, net feedback inhibition shows frequency-dependent facilitation, driven by strongly facilitating mossy fiber inputs. Computational analyses show a significant contribution of the feedback circuit to pattern separation of theta modulated inputs, even within individual theta cycles. Moreover, pattern separation was selectively boosted at gamma frequencies, in particular for highly similar inputs. This effect was highly robust, suggesting that frequency-dependent pattern separation is a key feature of the feedback inhibitory microcircuit.

    Link

  • abstract submitted (2020)

    Authors:
    N. Chinichian, I. Veer, J. Kuruschwitz, A. A. Heinz, Meyer-Lindenberg, H. Walter

    Abstract:

    Recently, the use of network-based methods on brain imaging data has received a lot of traction in the neuroscience community. Collaboration between brain regions in this paradigm to perform every cognitive task has been studied using a wide variance of methods. While some of these methods allow elegant mathematical interpretations of our data, others can easily become computationally expensive or difficult to interpret and compare between subjects or groups. Here, we suggest an intuitive and computationally efficient method to measure the reconfiguration of brain regions in relation to a template modular structure over time. This method uses a single a-priori modular structure as a reference and therefore does not rely on a stochastic data-driven estimation of modules. We calculate the deformation of a-prior modules over time and use the outcome as a source of tracking the activity patterns. Our proposed method thus has the benefit of using the same (biologically relevant) modular framework across samples and studies, which also allows for better interpretation of brain regions switching their modular alliance. In the Application section, we demonstrate that our newly proposed method yields highly similar results of whole-brain flexibility as in another study that uses one of the current well-established methods of calculating dynamic network reconfiguration.

    Link

  • Science 368(6495):1057-1058 (2020)

    Authors:
    Franke K., Vlasits A.

    Abstract:

    Many cases of blindness result from progressive loss of photoreceptors, which are the light-sensing cells in the eye. For individuals with such progressive blindness, potential therapies aim at restoring vision by making the retina light-sensitive again while minimally interfering with any healthy photoreceptors—goals that are usually contradictory. Many current therapeutic strategies interfere with remaining vision, making them primarily suitable for patients who have lost all light sensitivity. On page 1108 of this issue, Nelidova et al. (1) present a potential solution to this conundrum: making the retina sensitive to infrared light, which is largely undetectable by human photoreceptors. They use engineered nanoparticle sensors and gene therapy to induce infrared light sensitivity in mice with inherited degenerative blindness and in postmortem human retinas. This approach might avoid damage to functional photoreceptors by preventing saturation or hyperactivation while inducing light sensitivity in patients with partial retinal degeneration.

    Link

  • bioRxiv (2020)

    Authors:
    Gallardo G., Wassermann D., Anwander A.

    Abstract:

    Despite recent advances in tractography, the gap remains wide between the descriptions of white-matter pathways in the literature and the methods to reconstruct and study them from dMRI images. Here, we tackle this challenge by proposing a language to define white matter tracts, namely WMQLT, and a tool to automatically reconstruct pathways from their WMQLT queries. Our method is performant, flexible enough to allow defining tracts using multiple modalities, and allows to extend ROI-based reconstruction methods. Leveraging our language, we define 19 major brain tracts, alongside their subdivisions, and reconstruct them in a large population. We show that the shape of the reconstructed pathways, as well as their connectivity and lateralizations are in accordance with the current neuroanatomical literature. Finally, we showcase our technique in two scenarios: computing the functional subdivisions of a tract, and assessing the role of handedness and gender in the lateralization of language-related tracts.

    Link

  • bioRxiv, 838383 (2020)

    Authors:
    Gonçalves, P. J., Lueckmann, J. M., Deistler, M., Nonnenmacher, M., Öcal, K., Bassetto, G., … & Greenberg, D. S.

    Abstract:

    Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of underlying causes. However, determining which model parameters agree with complex and stochastic neural data presents a significant challenge. We address this challenge with a machine learning tool which uses deep neural density estimators – trained using model simulations – to carry out Bayesian inference and retrieve the full space of parameters compatible with raw data or selected data features. Our method is scalable in parameters and data features, and can rapidly analyze new data after initial training. We demonstrate the power and flexibility of our approach on receptive fields, ion channels, and Hodgkin–Huxley models. We also characterize the space of circuit configurations giving rise to rhythmic activity in the crustacean stomatogastric ganglion, and use these results to derive hypotheses for underlying compensation mechanisms. Our approach will help close the gap between data-driven and theory-driven models of neural dynamics.

    Link

  • Philosophical Transactions of the Royal Society B, 375(1796), 20190319 (2020)

    Authors:
    Hilgetag, C. C., & Goulas, A.

    Abstract:

    Concepts shape the interpretation of facts. One of the most popular concepts in systems neuroscience is that of 'hierarchy'. However, this concept has been interpreted in many different ways, which are not well aligned. This observation suggests that the concept is ill defined. Using the example of the organization of the primate visual cortical system, we explore several contexts in which 'hierarchy' is currently used in the description of brain networks. We distinguish at least four different uses, specifically, 'hierarchy' as a topological sequence of projections, as a gradient of features, as a progression of scales, or as a sorting of laminar projection patterns. We discuss the interpretation and functional implications of the different notions of 'hierarchy' in these contexts and suggest that more specific terms than 'hierarchy' should be used for a deeper understanding of the different dimensions of the organization of brain networks.

    Link

  • Annals of Neurology, 87(6), 962-975 (2020)

    Authors:
    Irmen, F., Horn, A., Mosley, P., Perry, A., Petry‐Schmelzer, J. N., Dafsari, H. S., … & Kübler, D.

    Abstract:

    Objective: Subthalamic nucleus deep brain stimulation (STN‐DBS) in Parkinson's disease (PD) not only stimulates focal target structures but also affects distributed brain networks. The impact this network modulation has on non‐motor DBS effects is not well‐characterized. By focusing on the affective domain, we systematically investigate the impact of electrode placement and associated structural connectivity on changes in depressive symptoms following STN‐DBS, which have been reported to improve, worsen, or remain unchanged.
    Methods: Depressive symptoms before and after STN‐DBS surgery were documented in 116 patients with PD from 3 DBS centers (Berlin, Queensland, and Cologne). Based on individual electrode reconstructions, the volumes of tissue activated (VTAs) were estimated and combined with normative connectome data to identify structural connections passing through VTAs. Berlin and Queensland cohorts formed a training and cross‐validation dataset used to identify structural connectivity explaining change in depressive symptoms. The Cologne data served as the test‐set for which depressive symptom change was predicted.
    Results: Structural connectivity was linked to depressive symptom change under STN‐DBS. An optimal connectivity map trained on the Berlin cohort could predict changes in depressive symptoms in Queensland patients and vice versa. Furthermore, the joint training‐set map predicted changes in depressive symptoms in the independent test‐set. Worsening of depressive symptoms was associated with left prefrontal connectivity.
    Interpretation: Fibers connecting the electrode with left prefrontal areas were associated with worsening of depressive symptoms. Our results suggest that for the left STN‐DBS lead, placement impacting fibers to left prefrontal areas should be avoided to maximize improvement of depressive symptoms.

    Link

  • Science Advances, 6(41), eaaz9281 (2020)

    Authors:
    Kirilina, E., Helbling, S., Morawski, M., Pine, K., Reimann, K., Jankuhn, S., Dinse, J., Deistung, A., Reichenbach, J.R., Trampel, R., Geyer, S., Müller, L., Jakubowski, N., Arendt, T., Bazin, P.L., Weiskopf, N. (2020)

    Abstract:

    Superficial white matter (SWM) contains the most cortico-cortical white matter connections in the human brain encompassing the short U-shaped association fibers. Despite its importance for brain connectivity, very little is known about SWM in humans, mainly due to the lack of noninvasive imaging methods. Here, we lay the groundwork for systematic in vivo SWM mapping using ultrahigh resolution 7 T magnetic resonance imaging. Using biophysical modeling informed by quantitative ion beam microscopy on postmortem brain tissue, we demonstrate that MR contrast in SWM is driven by iron and can be linked to the microscopic iron distribution. Higher SWM iron concentrations were observed in U-fiber–rich frontal, temporal, and parietal areas, potentially reflecting high fiber density or late myelination in these areas. Our SWM mapping approach provides the foundation for systematic studies of interindividual differences, plasticity, and pathologies of this crucial structure for cortico-cortical connectivity in humans.

    Link

  • Network Neuroscience, (Just Accepted), 1-32 (2020)

    Authors:
    Luboeinski J., Tchumatchenko T.

    Abstract:

    n.a.

    Link

  • European Journal of Neuroscience (2020)

    Authors:
    Maith, O., Villagrasa Escudero, F., Dinkelbach, H. Ü., Baladron, J., Horn, A., Irmen, F., … & Hamker, F. H.

    Abstract:

    Previous computational model‐based approaches for understanding the dynamic changes related to Parkinson’s disease made particular assumptions about Parkinson’s disease related activity changes or specified dopamine‐dependent activation or learning rules. Inspired by recent model‐based analysis of resting‐state fMRI, we have taken a data‐driven approach. We fit the free parameters of a spiking neuro‐computational model to match correlations of blood‐oxygen‐level‐dependent signals between different basal ganglia nuclei and obtain subject‐specific neurocomputational models of two subject groups: Parkinson patients and matched controls. When comparing mean firing rates at rest and connectivity strengths between the control and Parkinsonian model groups, several significant differences were found that are consistent with previous experimental observations. We discuss the implications of our approach and compare its results also with the popular “rate model” of the basal ganglia. Our study suggests that a model‐based analysis of imaging data from healthy and Parkinsonian subjects is a promising approach for the future to better understand Parkinson related changes in the basal ganglia and corresponding treatments.

    Link

  • Frontiers in Neuroscience 14: 16 (2020)

    Authors:
    Müller-Komorowska, D., Opitz, T., Elzoheiry, S., Schweizer, M., Beck, H

    Abstract:

    Transgenic Cre-recombinase expressing mouse lines are widely used to express fluorescent proteins and opto-/chemogenetic actuators, making them a cornerstone of modern neuroscience. The investigation of interneurons in particular has benefitted from the ability to genetically target specific cell types. However, the specificity of some Cre driver lines has been called into question. Here, we show that nonspecific expression in a subset of hippocampal neurons can have substantial nonspecific functional effects in a somatostatin-Cre (SST-Cre) mouse line. Nonspecific targeting of CA3 pyramidal cells caused large optogenetically evoked excitatory currents in remote brain regions. Similar, but less severe patterns of nonspecific expression were observed in a widely used SST-IRES-Cre line, when crossed with a reporter mouse line. Viral transduction on the other hand yielded more specific expression but still resulted in nonspecific expression in a minority of pyramidal layer cells. These results suggest that a careful analysis of specificity is mandatory before the use of Cre driver lines for opto- or chemogenetic manipulation approaches.

    Link

  • Biorxiv (2020)

    Authors:
    Pofahl, M., Nikbakht, N., Haubrich, A.N., Nguyen, T., Masala, N., Braganza, O., Macke, J.H., Ewell, L.A., Golcuk, K., Beck, H

    Abstract:

    All vertebrates are capable of generating dissimilar patterns of neuronal activity from similar sensory-driven input patterns, a phenomenon called pattern separation. It is unclear, however, how these separated patterns are transformed into lasting memories that retain the initial discrimination. Using dual-color in-vivo two-photon Ca2+ imaging, we show that the dentate gyrus, a region implicated in pattern separation, generates in immobile mice sparse, synchronized activity patterns driven by entorhinal cortex activity. These population events are structured and modified by changes in the environment; they incorporate place- and speed cells and are similar to population patterns evoked during self-motion. Inhibiting only granule cells in immobile mice impairs formation of pattern-separated memories. These patterns, thus, support the creation of precise memories by replaying the population codes of the current environment on a short time scale.

    Link

  • Frontiers Physiol. 11, 272 (2020)

    Authors:
    Schmal C., Herzel H., Myung J.

    Abstract:

    Entrainment denotes a process of coordinating the internal circadian clock to external rhythmic time-cues (Zeitgeber), mainly light. It is facilitated by stronger Zeitgeber signals and smaller period differences between the internal clock and the external Zeitgeber. The phase of entrainment ψ is a result of this process on the side of the circadian clock. On Earth, the period of the day-night cycle is fixed to 24 h, while the periods of circadian clocks distribute widely due to natural variation within and between species. The strength and duration of light depend locally on season and geographic latitude. Therefore, entrainment characteristics of a circadian clock vary under a local light environment and distribute along geoecological settings. Using conceptual models of circadian clocks, we investigate how local conditions of natural light shape global patterning of entrainment through seasons. This clock-side entrainment paradigm enables us to predict systematic changes in the global distribution of chronotypes.

    Link

  • bioRxiv (2020)

    Authors:
    Schröder, C., Klindt, D., Strauss, S., Franke, K., Bethge, M., Euler, T. & Berens, P.

    Abstract:

    Visual processing in the retina has been studied in great detail at all levels such that a comprehensive picture of the retina’s cell types and the many neural circuits they form is emerging. However, the currently best performing models of retinal function are black-box CNN models which are agnostic to such biological knowledge. In particular, these models typically neglect the role of the many inhibitory circuits involving amacrine cells and the biophysical mechanisms underlying synaptic release. Here, we present a computational model of temporal processing in the inner retina, including inhibitory feedback circuits and realistic synaptic release mechanisms. Fit to the responses of bipolar cells, the model generalized well to new stimuli including natural movie sequences, performing on par with or better than a benchmark black-box model. In pharmacology experiments, the model replicated in silico the effect of blocking specific amacrine cell populations with high fidelity, indicating that it had learned key circuit functions. Also, more in depth comparisons showed that connectivity patterns learned by the model were well matched to connectivity patterns extracted from connectomics data. Thus, our model provides a biologically interpretable data-driven account of temporal processing in the inner retina, filling the gap between purely black-box and detailed biophysical modeling.

    Link

  • Optics Express, 28(10), 15587-15600 (2020)

    Authors:
    Stockhausen, A., Bürgers, J., Rodriguez-Gatica, J. E., Schweihoff, J., Merkel, R., Prigge, J. M., … & Kubitscheck, U.

    Abstract:

    Light-sheet fluorescence microscopy (LSFM) helps investigate small structures in developing cells and tissue for three-dimensional localization microscopy and large-field brain imaging in neuroscience. Lattice light-sheet microscopy is a recent development with great potential to improve axial resolution and usable field sizes, thus improving imaging speed. In contrast to the commonly employed Gaussian beams for light-sheet generation in conventional LSFM, in lattice light-sheet microscopy an array of low diverging Bessel beams with a suppressed side lobe structure is used. We developed a facile elementary lattice light-sheet microscope using a micro-fabricated fixed ring mask for lattice light-sheet generation. In our setup, optical hardware elements enable a stable and simple illumination path without the need for spatial light modulators. This setup, in combination with long-working distance objectives and the possibility for simultaneous dual-color imaging, provides optimal conditions for imaging extended optically cleared tissue samples. We here present experimental data of fluorescently stained neurons and neurites from mouse hippocampus following tissue expansion and demonstrate the high homogeneous resolution throughout the entire imaged volume. Utilizing our purpose-built lattice light-sheet microscope, we reached a homogeneous excitation and an axial resolution of 1.2 µm over a field of view of (333 µm)^2.

    Link

  • Frontiers in Physiology, 11, 334 (2020)

    Authors:
    Tokuda, I. T., Schmal, C., Ananthasubramaniam, B., & Herzel, H.

    Abstract:

    Understanding entrainment of circadian rhythms is a central goal of chronobiology. Many factors, such as period, amplitude, Zeitgeber strength, and daylength, govern entrainment ranges and phases of entrainment. We have tested whether simple amplitude-phase models can provide insight into the control of entrainment phases. Using global optimization, we derived conceptual models with just three free parameters (period, amplitude, and relaxation rate) that reproduce known phenotypic features of vertebrate clocks: phase response curves (PRCs) with relatively small phase shifts, fast re-entrainment after jet lag, and seasonal variability to track light onset or offset. Since optimization found multiple sets of model parameters, we could study this model ensemble to gain insight into the underlying design principles. We found complex associations between model parameters and entrainment features. Arnold onions of representative models visualize strong dependencies of entrainment on periods, relative Zeitgeber strength, and photoperiods. Our results support the use of oscillator theory as a framework for understanding the entrainment of circadian clocks.

    Link

  • PLOS ONE, prel. accepted (2020)

    Authors:
    Werckenthin A., Huber J., Arnold T., Koziarek S., Plath M.J.A. , J.A. Plath, Stursberg O. ,Herzel H.P. , Stengl M.

    Abstract:

    Circadian clocks control rhythms in physiology and behavior entrained to 24 h light – dark cycles. Despite of conserved general schemes, molecular circadian clockworks differ between insect species. With RNA interference (RNAi) we examined an ancient circadian clockwork in a basic insect, the hemimetabolous Madeira cockroach Rhyparobia maderae. With injections of double-stranded RNA (dsRNA) of cockroach period (Rm´per), timeless 1 (Rm´tim1), or cryptochrome 2 (Rm´cry2) we searched for essential components of the clock´s core negative feedback loop. Single injections of dsRNA of each clock gene into adult cockroaches successfully and permanently knocked down respective mRNA levels within ~two weeks deleting daytime-dependent mRNA rhythms for Rm´per and Rm´cry2. Rm´perRNAi or Rm´cry2RNAi affected total mRNA levels of both genes, while Rm´tim1 transcription was independent of both, also keeping rhythmic expression. Unexpectedly, circadian locomotor activity of most cockroaches remained rhythmic for each clock gene knockdown employed. It expressed weakened rhythms and unchanged periods for Rm´perRNAi and shorter periods for Rm´tim1RNAi and Rm´cry2RNAi. As a hypothesis of the cockroach´s molecular clockwork, a basic network of switched differential equations was developed to model the oscillatory behavior of clock cells expressing respective clock genes. Data were consistent with two synchronized main groups of coupled oscillator cells, a leading (morning) oscillator, or a lagging (evening) oscillator that couple via mutual inhibition. The morning oscillators express shorter, the evening oscillators longer endogenous periods based on core feedback loops with either PER, TIM1, or CRY2/PER complexes as dominant negative feedback of the clockwork. We hypothesize that dominant morning oscillator cells with shorter periods express PER, but not CRY2, or TIM1 as suppressor of clock gene expression, while two groups of evening oscillator cells with longer periods either comprise TIM1 or CRY2/PER suppressing complexes. Modelling suggests that there is an additional negative feedback next to Rm´PER in cockroach morning oscillator cells.

    Link

  • Scientific Reports volume 10, Article number: 4399 (2020)

    Authors:
    Zhao, Z., Klindt, D. A., Chagas, A. M., Szatko, K. P., Rogerson, L., Protti, D. A., Bethge, M., Franke, K., Berens, P., Ecker, A. S., & Euler, T.

    Abstract:

    The retina decomposes visual stimuli into parallel channels that encode different features of the visual environment. Central to this computation is the synaptic processing in a dense layer of neuropil, the so-called inner plexiform layer (IPL). Here, different types of bipolar cells stratifying at distinct depths relay the excitatory feedforward drive from photoreceptors to amacrine and ganglion cells. Current experimental techniques for studying processing in the IPL do not allow imaging the entire IPL simultaneously in the intact tissue. Here, we extend a two-photon microscope with an electrically tunable lens allowing us to obtain optical vertical slices of the IPL, which provide a complete picture of the response diversity of bipolar cells at a “single glance”. The nature of these axial recordings additionally allowed us to isolate and investigate batch effects, i.e. inter-experimental variations resulting in systematic differences in response speed. As a proof of principle, we developed a simple model that disentangles biological from experimental causes of variability and allowed us to recover the characteristic gradient of response speeds across the IPL with higher precision than before. Our new framework will make it possible to study the computations performed in the central synaptic layer of the retina more efficiently.

    Link

  • BioRxiv, 780031 (2019)

    Authors:
    Behrens, C., Zhang, Y., Yadav, S. C., Haverkamp, S., Irsen, S., Korympidou, M. M., … & Berens, P.

    Abstract:

    In the outer plexiform layer (OPL) of the mouse retina, two types of cone photoreceptors (cones) provide input to more than a dozen types of cone bipolar cells (CBCs). This transmission is modulated by a single horizontal cell (HC) type, the only interneuron in the outer retina. Horizontal cells form feedback synapses with cones and feedforward synapses with CBCs. However, the exact computational role of HCs is still debated. Along with performing global signaling within their laterally coupled network, HCs also provide local, cone-specific feedback. Specifically, it has not been clear which synaptic structures HCs use to provide local feedback to cones and global forward signaling to CBCs.

    Here, we reconstructed in a serial block-face electron microscopy volume the dendritic trees of five HCs as well as cone axon terminals and CBC dendrites to quantitatively analyze their connectivity. In addition to the fine HC dendritic tips invaginating cone axon terminals, we also identified “bulbs”, short segments of increased dendritic diameter on the primary dendrites of HCs. These bulbs are located well below the cone axon terminal base and make contact to other cells mostly identified as other HCs or CBCs. Using immunolabeling we show that HC bulbs express vesicular gamma-aminobutyric acid transporters and co-localize with GABA receptor γ2 subunits. Together, this suggests the existence of two synaptic strata in the mouse OPL, spatially separating cone-specific feedback and feedforward signaling to CBCs. A biophysics-based computational model of a HC dendritic branch supports the hypothesis that the spatial arrangement of synaptic contacts allows simultaneous local feedback and global feedforward signaling.

    Link

  • Brain. 142(9):2558-2571 (2019)

    Authors:
    Betts, M. J., Kirilina, E., Otaduy, M. C., Ivanov, D., Acosta-Cabronero, J., Callaghan, M. F., … & Loane, C.

    Abstract:

    Pathological alterations to the locus coeruleus, the major source of noradrenaline in the brain, are histologically evident in early stages of neurodegenerative diseases. Novel MRI approaches now provide an opportunity to quantify structural features of the locus coeruleus in vivo during disease progression. In combination with neuropathological biomarkers, in vivo locus coeruleus imaging could help to understand the contribution of locus coeruleus neurodegeneration to clinical and pathological manifestations in Alzheimer’s disease, atypical neurodegenerative dementias and Parkinson’s disease. Moreover, as the functional sensitivity of the noradrenergic system is likely to change with disease progression, in vivo measures of locus coeruleus integrity could provide new pathophysiological insights into cognitive and behavioural symptoms. Locus coeruleus imaging also holds the promise to stratify patients into clinical trials according to noradrenergic dysfunction. In this article, we present a consensus on how non-invasive in vivo assessment of locus coeruleus integrity can be used for clinical research in neurodegenerative diseases. We outline the next steps for in vivo, post-mortem and clinical studies that can lay the groundwork to evaluate the potential of locus coeruleus imaging as a biomarker for neurodegenerative diseases.

    Link

  • NeuroImage, 189, 777-792 (2019)

    Authors:
    Beul, S. F., & Hilgetag, C. C.

    Abstract:

    Studies of structural brain connectivity have revealed many intriguing features of complex cortical networks. To advance integrative theories of cortical organization, an understanding is required of how connectivity interrelates with other aspects of brain structure. Recent studies have suggested that interareal connectivity may be related to a variety of macroscopic as well as microscopic architectonic features of cortical areas. However, it is unclear how these features are inter-dependent and which of them most strongly and fundamentally relate to structural corticocortical connectivity. Here, we systematically investigated the relation of a range of microscopic and macroscopic architectonic features of cortical organization, namely layer III pyramidal cell soma cross section, dendritic synapse count, dendritic synapse density and dendritic tree size as well as area neuron density, to multiple properties of cortical connectivity, using a comprehensive, up-to-date structural connectome of the primate brain. Importantly, relationships were investigated by multi-variate analyses to account for the interrelations of features. Of all considered factors, the classical architectonic parameter of neuron density most strongly and consistently related to essential features of cortical connectivity (existence and laminar patterns of projections, area degree), and in conjoint analyses largely abolished effects of cellular morphological features. These results confirm neuron density as a central architectonic indicator of the primate cerebral cortex that is closely related to essential aspects of brain connectivity and is also highly indicative of further features of the architectonic organization of cortical areas, such as the considered cellular morphological measures. Our findings integrate several aspects of cortical micro- and macroscopic organization, with implications for cortical development and function.

    Link

  • Neurophotonics, 6(1), 015005 (2019)

    Authors:
    Bürgers, J., Pavlova, I., Rodriguez-Gatica, J. E., Henneberger, C., Oeller, M., Ruland, J. A., … & Schwarz, M. K.

    Abstract:

    The goal of understanding the architecture of neural circuits at the synapse level with a brain-wide perspective has powered the interest in high-speed and large field-of view volumetric imaging at subcellular resolution. Here we developed a method combining tissue expansion and light sheet fluorescence microscopy to allow extended volumetric super resolution high-speed imaging of large mouse brain samples. We demonstrate the capabilities of this method by performing two color fast volumetric super resolution imaging of mouse CA1 and dentate gyrus molecular-, granule cell- and polymorphic layers. Our method enables an exact evaluation of granule cell and neurite morphology within the context of large cell ensembles spanning several orders of magnitude in resolution. We found that imaging a brain region of 1 mm3 in super resolution using light sheet fluorescence expansion microscopy is about 17-fold faster than imaging the same region by a current state of the art high resolution confocal laser scanning microscope.

    Link

  • Data in Brief 25:104132 (2019)

    Authors:
    Callaghan, M. F., Lutti, A., Ashburner, J., Balteau, E., Corbin, N., Draganski, B., … & Phillips, C.

    Abstract:

    The hMRI toolbox is an open-source toolbox for the calculation of quantitative MRI parameter maps from a series of weighted imaging data, and optionally additional calibration data. The multi- parameter mapping (MPM) protocol, incorporating calibration data to correct for spatial variation in the scanner’s transmit and receive fields, is the most complete protocol that can be handled by the toolbox. Here we present a dataset acquired with such a full MPM protocol, which is made freely available to be used as a tutorial by following instructions provided on the associated toolbox wiki pages, which can be found at http://hMRI.info, and following the theory described in: hMRI e A toolbox for quantitative MRI in neuroscience and clinical research.

    Link

  • Biol Cybern Dec;113(5-6):475-494 (2019)

    Authors:
    Chien, V. S., Maess, B., & Knösche, T. R.

    Abstract:

    Neural responses to sudden changes can be observed in many parts of the sensory pathways at different organizational levels. For example, deviants that violate regularity at various levels of abstraction can be observed as simple On/Off responses of individual neurons or as cumulative responses of neural populations. The cortical deviance-related responses supporting different functionalities (e.g., gap detection, chunking, etc.) seem unlikely to arise from different function-specific neural circuits, given the relatively uniform and self-similar wiring patterns across cortical areas and spatial scales. Additionally, reciprocal wiring patterns (with heterogeneous combinations of excitatory and inhibitory connections) in the cortex naturally speak in favor of a generic deviance detection principle. Based on this concept, we propose a network model consisting of reciprocally coupled neural masses as a blueprint of a universal change detector. Simulation examples reproduce properties of cortical deviance-related responses including the On/Off responses, the omitted-stimulus response (OSR), and the mismatch negativity (MMN). We propose that the emergence of change detectors relies on the involvement of disinhibition. An analysis of network connection settings further suggests a supportive effect of synaptic adaptation and a destructive effect of N-methyl-D-aspartate receptor (NMDA-r) antagonists on change detection. We conclude that the nature of cortical reciprocal wiring gives rise to a whole range of local change detectors supporting the notion of a generic deviance detection principle. Several testable predictions are provided based on the network model. Notably, we predict that the NMDA-r antagonists would generally dampen the cortical Off response, the cortical OSR, and the MMN.

    Link

  • Network Neuroscience, 3(4), 1038-1050 (2019)

    Authors:
    Delettre, C., Messé, A., Dell, L. A., Foubet, O., Heuer, K., Larrat, B., … & Borrell, V.

    Abstract:

    The anatomical wiring of the brain is a central focus in network neuroscience. Diffusion MRI tractography offers the unique opportunity to investigate the brain fiber architecture in vivo and noninvasively. However, its reliability is still highly debated. Here, we explored the ability of diffusion MRI tractography to match invasive anatomical tract-tracing connectivity data of the ferret brain. We also investigated the influence of several state-of-the-art tractography algorithms on this match to ground truth connectivity data. Tract-tracing connectivity data were obtained from retrograde tracer injections into the occipital, parietal, and temporal cortices of adult ferrets. We found that the relative densities of projections identified from the anatomical experiments were highly correlated with the estimates from all the studied diffusion tractography algorithms (Spearman’s rho ranging from 0.67 to 0.91), while only small, nonsignificant variations appeared across the tractography algorithms. These results are comparable to findings reported in mouse and monkey, increasing the confidence in diffusion MRI tractography results. Moreover, our results provide insights into the variations of sensitivity and specificity of the tractography algorithms, and hence into the influence of choosing one algorithm over another.

    Link

2019

  • Journal of Comparative Neurology, 527(8), 1293-1314 (2019)

    Authors:
    Dell, L. A., Innocenti, G. M., Hilgetag, C. C., & Manger, P. R.

    Abstract:

    The present study describes the ipsilateral and contralateral corticocortical and corticothalamic connectivity of the occipital visual areas 17, 18, 19, and 21 in the ferret using standard anatomical tract-tracing methods. In line with previous studies of mammalian visual cortex connectivity, substantially more anterograde and retrograde label was present in the hemisphere ipsilateral to the injection site compared to the contralateral hemisphere. Ipsilateral reciprocal connectivity was the strongest within the occipital visual areas, while weaker connectivity strength was observed in the temporal, suprasylvian, and parietal visual areas. Callosal connectivity tended to be strongest in the homotopic cortical areas, and revealed a similar areal distribution to that observed in the ipsilateral hemisphere, although often less widespread across cortical areas. Ipsilateral reciprocal connectivity was observed throughout the visual nuclei of the dorsal thalamus, with no contralateral connections to the visual thalamus being observed. The current study, along with previous studies of connectivity in the cat, identified the posteromedial lateral suprasylvian visual area (PMLS) as a distinct network hub external to the occipital visual areas in carnivores, implicating PMLS as a potential gateway to the parietal cortex for dorsal stream processing. These data will also contribute to a macro connectome database of the ferret brain, providing essential data for connectomics analyses and cross-species analyses of connectomes and brain connectivity matrices, as well as providing data relevant to additional studies of cortical connectivity across mammals and the evolution of cortical connectivity variation.

    Link

  • Journal of Comparative Neurology, 527(8), 1315-1332 (2019)

    Authors:
    Dell, L. A., Innocenti, G. M., Hilgetag, C. C., & Manger, P. R.

    Abstract:

    The present study describes the ipsilateral and contralateral cortico‐cortical and cortico‐thalamic connectivity of the parietal visual areas, posterior parietal caudal cortical area (PPc) and posterior parietal rostral cortical area (PPr), in the ferret using standard anatomical tract‐tracing methods. The two divisions of posterior parietal cortex of the ferret are strongly interconnected, however area PPc shows stronger connectivity with the occipital and suprasylvian visual cortex, while area PPr shows stronger connectivity with the somatomotor cortex, reflecting the functional specificity of these two areas. This pattern of connectivity is mirrored in the contralateral callosal connections. In addition, PPc and PPr are connected with the visual and somatomotor nuclei of the dorsal thalamus. Numerous connectional similarities exist between the posterior parietal cortex of the ferret (PPc and PPr) and the cat (area 7 and 5), indicative of the homology of these areas within the Carnivora. These findings highlight the existence of a frontoparietal network as a shared feature of the organization of parietal cortex across Euarchontoglires and Laurasiatherians, with the degree of expression varying in relation to the expansion and areal complexity of the posterior parietal cortex. This observation indicates that the ferret is a potentially valuable experimental model animal for understanding the evolution and function of the posterior parietal cortex and the frontoparietal network across mammals. The data generated will also contribute to a connectomics database, to further cross‐species analyses of connectomes and illuminate wiring principles of cortical connectivity across mammals.

    Link

  • Journal of Comparative Neurology, 527(8), 1333-1347 (2019)

    Authors:
    Dell, L. A., Innocenti, G. M., Hilgetag, C. C., & Manger, P. R.

    Abstract:

    The present study describes the ipsilateral and contralateral corticocortical and corticothalamic connectivity of the temporal visual areas 20a and 20b in the ferret using standard anatomical tract‐tracing methods. The two temporal visual areas are strongly interconnected, but area 20a is primarily connected to the occipital visual areas, whereas area 20b maintains more widespread connections with the occipital, parietal and suprasylvian visual areas and the secondary auditory cortex. The callosal connectivity, although homotopic, consists mainly of very weak anterograde labeling which was more widespread in area 20a than area 20b. Although areas 20a and 20b are well connected with the visual dorsal thalamus, the injection into area 20a resulted in more anterograde label, whereas more retrograde label was observed in the visual thalamus following the injection into area 20b. Most interestingly, comparisons to previous connectional studies of cat areas 20a and 20b reveal a common pattern of connectivity of the temporal visual cortex in carnivores, where the posterior parietal cortex and the central temporal region (PMLS) provide network points required for dorsal and ventral stream interaction enroute to integration in the prefrontal cortex. This pattern of network connectivity is not dissimilar to that observed in primates, which highlights the ferret as a useful animal model to understand visual sensory integration between the dorsal and ventral streams. The data generated will also contribute to a connectomics database, to facilitate cross species analysis of brain connectomes and wiring principles of the brain.

    Link

  • Future Trends of HPC in a Disruptive Scenario, 34, 223 (2019)

    Authors:
    Dickscheid, T., Haas, S., Bludau, S., Glock, P., Huysegoms, M., & Amunts, K.

    Abstract:

    Mapping the microscopical organization of the human cerebral cortex provides a basis for multimodal brain atlases, and is indispensable for allocating functional imaging, physiological, connectivity, molecular, or genetic data to anatomically well specified structural entities of human brain organization at micrometer resolution. The analysis of histological sections is still considered a “gold standard” in brain mapping, and compared with other maps, e.g. from neuroimaging studies [1]. But while the spatial patterns of neuronal cells are inherently three-dimensional, such microscopic analysis is usually performed in individual 2D sections. Here we propose an HPC-based workflow that aims to recover the three-dimensional context from a stack of histological sections stained for neuronal cell bodies, imaged under a light microscope. Our aim is to align image data in consecutive sections at the micrometer resolution, where the texture is dominated by small objects like cell bodies, that often do not extend across sections. Therefore we cannot apply classical intensity-based image registration, where similarity of neighboring images is optimized at the pixel level. Our main contribution is a procedure to explicitly detect and match vessel-like structures in the brain tissue, guiding a feature-based image registration algorithm to 3D reconstruct regions of interest in the brain and recover the distribution of neuronal cells. To replace erroneous information in corrupted tissue areas, we further propose a simple predictive algorithm which generates realistic cell detections by learning from intact tissue parts in the local surroundings.

    Link

  • Science advances, 5(4), eaar7633. (2019)

    Authors:
    Galindo-Leon, E. E., Stitt, I., Pieper, F., Stieglitz, T., Engler, G., & Engel, A. K.

    Abstract:

    Intrinsically generated patterns of coupled neuronal activity are associated with the dynamics of specific brain states. Sensory inputs are extrinsic factors that can perturb these intrinsic coupling modes, creating a complex scenario in which forthcoming stimuli are processed. Studying this intrinsic-extrinsic interplay is necessary to better understand perceptual integration and selection. Here, we show that this interplay leads to a reconfiguration of functional cortical connectivity that acts as a mechanism to facilitate stimulus processing. Using audiovisual stimulation in anesthetized ferrets, we found that this reconfiguration of coupling modes is context specific, depending on long-term modulation by repetitive sensory inputs. These reconfigured coupling modes lead to changes in latencies and power of local field potential responses that support multisensory integration. Our study demonstrates that this interplay extends across multiple time scales and involves different types of intrinsic coupling. These results suggest a previously unknown large-scale mechanism that facilitates multisensory integration.

    Link

  • Magn Reson Med. 9 81:1265-1279 (2019)

    Authors:
    Georgi J, Metere R, Jäger C, Morawski M, Möller HE

    Abstract:

    Abstract
    Purpose
    Water mobility in tissues is related to the microstructure that modulates diffusion and spin relaxation. Previous work has shown that the extracellular matrix (ECM) impacts water diffusion in cartilage. To investigate if similar contributions to image contrast exist for brain, which is characterized by a substantially lower ECM content, diffusion and relaxation were studied in fixed samples from goat and human thalamus before and after enzymatic digestion of ECM compounds. Selected experiments in human corpus callosum were included for comparing subcortical gray matter and white matter.

    Methods
    Digestion of matrix components was achieved by treatment with hyaluronidase. Nonlocalized pulsed field gradient measurements were performed with urn:x-wiley:07403194:media:mrm27459:mrm27459-math-0001 values between 0.6 and 18,000 s/mm2 at 3T and temperatures between 0°C and 20°C, in addition to T1 and T2 relaxation measurements. The data were fitted to multiexponential models to account for different water compartments. After the measurements, the samples were sliced and stained for ECM‐sensitive markers to verify efficient digestion.

    Results
    Microstructural alterations associated with hyaluronan digestion did not lead to measurable effects on water diffusion or urn:x-wiley:07403194:media:mrm27459:mrm27459-math-0002. However, T1 of the main relaxographic component, attributed to intra‐/extracellular water, decreased by 7%.

    Conclusion
    Investigations with very strong gradients did not reveal a detectable effect on water diffusion or urn:x-wiley:07403194:media:mrm27459:mrm27459-math-0003 after hyaluronan removal, indicating that the brain ECM content is too low to produce a detectable effect. The subtle alteration of T1 upon hyaluronidase treatment might reflect a modulation of intercompartmental water exchange properties.

    Link

  • PLoS biology, 17(3), e2005346 (2019)

    Authors:
    Goulas, A., Majka, P., Rosa, M. G., & Hilgetag, C. C.

    Abstract:

    The cerebral cortex of mammals exhibits intricate interareal wiring. Moreover, mammalian cortices differ vastly in size, cytological composition, and phylogenetic distance. Given such complexity and pronounced species differences, it is a considerable challenge to decipher organizational principles of mammalian connectomes. Here, we demonstrate species-specific and species-general unifying principles linking the physical, cytological, and connectional dimensions of architecture in the mouse, cat, marmoset, and macaque monkey. The existence of connections is related to the cytology of cortical areas, in addition to the role of physical distance, but this relation is attenuated in mice and marmoset monkeys. The cytoarchitectonic cortical gradients, and not the rostrocaudal axis of the cortex, are closely linked to the laminar origin of connections, a principle that allows the extrapolation of this connectional feature to humans. Lastly, a network core, with a central role under different modes of network communication, characterizes all cortical connectomes. We observe a displacement of the network core in mammals, with a shift of the core of cats and macaque monkeys toward the less neuronally dense areas of the cerebral cortex. This displacement has functional ramifications but also entails a potential increased degree of vulnerability to pathology. In sum, our results sketch out a blueprint of mammalian connectomes consisting of species-specific and species-general links between the connectional, physical, and cytological dimensions of the cerebral cortex, possibly reflecting variations and persistence of evolutionarily conserved mechanisms and cellular phenomena. Our framework elucidates organizational principles that encompass but also extend beyond the wiring economy principle imposed by the physical embedding of the cerebral cortex.

    Link

  • Science advances, 5(6), eaav9694 (2019)

    Authors:
    Goulas, A., Betzel, R. F., & Hilgetag, C. C.

    Abstract:

    The wiring of vertebrate and invertebrate brains provides the anatomical skeleton for cognition and behavior. Connections among brain regions are characterized by heterogeneous strength that is parsimoniously described by the wiring cost and homophily principles. Moreover, brains exhibit a characteristic global network topology, including modules and hubs. However, the mechanisms resulting in the observed interregional wiring principles and network topology of brains are unknown. Here, with the aid of computational modeling, we demonstrate that a mechanism based on heterochronous and spatially ordered neurodevelopmental gradients, without the involvement of activity-dependent plasticity or axonal guidance cues, can reconstruct a large part of the wiring principles (on average, 83%) and global network topology (on average, 80%) of diverse adult brain connectomes, including fly and human connectomes. In sum, space and time are key components of a parsimonious, plausible neurodevelopmental mechanism of brain wiring with a potential universal scope, encompassing vertebrate and invertebrate brains.

    Link

  • arXiv:1905.07488 (2019)

    Authors:
    Greenberg, D. S., Nonnenmacher, M., & Macke, J. H.

    Abstract:

    How can one perform Bayesian inference on stochastic simulators with intractable likelihoods? A recent approach is to learn the posterior from adaptively proposed simulations using neural network-based conditional density estimators. However, existing methods are limited to a narrow range of proposal distributions or require importance weighting that can limit performance in practice. Here we present automatic posterior transformation (APT), a new sequential neural posterior estimation method for simulation-based inference. APT can modify the posterior estimate using arbitrary, dynamically updated proposals, and is compatible with powerful flow-based density estimators. It is more flexible, scalable and efficient than previous simulation-based inference techniques. APT can operate directly on high-dimensional time series and image data, opening up new applications for likelihood-free inference.

    Link

  • Network Neuroscience, 3(4), 905-923 (2019)

    Authors:
    Hilgetag, C. C., Beul, S. F., van Albada, S. J., & Goulas, A.

    Abstract:

    The connections linking neurons within and between cerebral cortical areas form a multiscale network for communication. We review recent work relating essential features of cortico-cortical connections, such as their existence and laminar origins and terminations, to fundamental structural parameters of cortical areas, such as their distance, similarity in cytoarchitecture, defined by lamination or neuronal density, and other macroscopic and microscopic structural features. These analyses demonstrate the presence of an architectonic type principle. Across species and cortices, the essential features of cortico-cortical connections vary consistently and strongly with the cytoarchitectonic similarity of cortical areas. By contrast, in multivariate analyses such relations were not found consistently for distance, similarity of cortical thickness, or cellular morphology. Gradients of laminar cortical differentiation, as reflected in overall neuronal density, also correspond to regional variations of cellular features, forming a spatially ordered natural axis of concerted architectonic and connectional changes across the cortical sheet. The robustness of findings across mammalian brains allows cross-species predictions of the existence and laminar patterns of projections, including estimates for the human brain that are not yet available experimentally. The architectonic type principle integrates cortical connectivity and architecture across scales, with implications for computational explorations of cortical physiology and developmental mechanisms.

    Link

  • Brain, 142(10), 3129–3143 (2019)

    Authors:
    Horn, A., Wenzel, G., Irmen, F., Huebl, J., Li, N., Neumann, W. J., … & Kühn, A. A.

    Abstract:

    Neuroimaging has seen a paradigm shift away from a formal description of local activity patterns towards studying distributed brain networks. The recently defined framework of the ‘human connectome’ enables global analysis of parts of the brain and their interconnections. Deep brain stimulation (DBS) is an invasive therapy for patients with severe movement disorders aiming to retune abnormal brain network activity by local high frequency stimulation of the basal ganglia. Beyond clinical utility, DBS represents a powerful research platform to study functional connectomics and the modulation of distributed brain networks in the human brain. We acquired resting-state functional MRI in 20 patients with Parkinson’s disease with subthalamic DBS switched on and off. An age-matched control cohort of 15 subjects was acquired from an open data repository. DBS lead placement in the subthalamic nucleus was localized using a state-of-the art pipeline that involved brain shift correction, multispectral image registration and use of a precise subcortical atlas. Based on a realistic 3D model of the electrode and surrounding anatomy, the amount of local impact of DBS was estimated using a finite element method approach. On a global level, average connectivity increases and decreases throughout the brain were estimated by contrasting on and off DBS scans on a voxel-wise graph comprising eight thousand nodes. Local impact of DBS on the motor subthalamic nucleus explained half the variance in global connectivity increases within the motor network (R = 0.711, P < 0.001). Moreover, local impact of DBS on the motor subthalamic nucleus could explain the degree to how much voxel-wise average brain connectivity normalized towards healthy controls (R = 0.713, P < 0.001). Finally, a network-based statistics analysis revealed that DBS attenuated specific couplings known to be pathological in Parkinson’s disease. Namely, coupling between motor thalamus and motor cortex was increased while striatal coupling with cerebellum, external pallidum and subthalamic nucleus was decreased by DBS. Our results show that resting state functional MRI may be acquired in DBS on and off conditions on clinical MRI hardware and that data are useful to gain additional insight into how DBS modulates the functional connectome of the human brain. We demonstrate that effective DBS increases overall connectivity in the motor network, normalizes the network profile towards healthy controls and specifically strengthens thalamo-cortical connectivity while reducing striatal control over basal ganglia and cerebellar structures.

    Link

  • Neuron 103, 118-132 (2019)

    Authors:
    Kramer, A., Wu, Y., Baier, H., & Kubo, F.

    Abstract:

    Animals use global image motion cues to actively stabilize their position by compensatory movements. Neurons in the zebrafish pretectum distinguish different optic flow patterns, e.g., rotation and translation, to drive appropriate behaviors. Combining functional imaging and morphological reconstruction of single cells, we revealed critical neuroanatomical features of this sensorimotor transformation. Terminals of direction-selective retinal ganglion cells (DS-RGCs) are located within the pretectal retinal arborization field 5 (AF5), where they meet dendrites of pretectal neurons with simple tuning to monocular optic flow. Translation-selective neurons, which respond selectively to optic flow in the same direction for both eyes, are intermingled with these simple cells but do not receive inputs from DS-RGCs. Mutually exclusive populations of pretectal projection neurons innervate either the reticular formation or the cerebellum, which in turn control motor responses. We posit that local computations in a defined pretectal circuit transform optic flow signals into neural commands driving optomotor behavior.

    Link

  • Scientific reports 9.1 (2019): 1-16 (2019)

    Authors:
    Li, D., Zavaglia, M., Wang, G., Xie, H., Hu, Y., Werner, R., … & Hilgetag, C. C.

    Abstract:

    The laminar organization of the cerebral cortex is a fundamental characteristic of the brain, with essential implications for cortical function. Due to the rapidly growing amount of high-resolution brain imaging data, a great demand arises for automated and flexible methods for discriminating the laminar texture of the cortex. Here, we propose a combined approach of unsupervised and supervised machine learning to discriminate the hierarchical cortical laminar organization in high-resolution 2-photon microscopic neural image data of mouse brain without observer bias, that is, without the prerequisite of manually labeled training data. For local cortical foci, we modify an unsupervised clustering approach to identify and represent the laminar cortical structure. Subsequently, supervised machine learning is applied to transfer the resulting layer labels across different locations and image data, to ensure the existence of a consistent layer label system. By using neurobiologically meaningful features, the discrimination results are shown to be consistent with the layer classification of the classical Brodmann scheme, and provide additional insight into the structure of the cerebral cortex and its hierarchical organization. Thus, our work paves a new way for studying the anatomical organization of the cerebral cortex, and potentially its functional organization.

    Link

  • Frontiers in Integrative Neuroscience, 13, 54 (2019)

    Authors:
    Li, D., Wang, G., Xie, H., Hu, Y., Guan, J. S., & Hilgetag, C. C.

    Abstract:

    Activity patterns of cerebral cortical regions represent the current environment in which animals receive multi-modal inputs. These patterns are also shaped by the history of activity that reflects learned information on past multimodal exposures. We studied the long-term dynamics of cortical activity patterns during the formation of multimodal memories by analyzing in vivo high-resolution 2-photon mouse brain imaging data of Immediate Early Gene (IEG) expression, resolved by cortical layers. Strikingly, in superficial layers II/III, the patterns showed similar dynamics across structurally and functionally distinct cortical areas and the consistency of dynamic patterns lasted for one to several days. By contrast, in deep layer V, the activity dynamics varied across different areas, and the current activities were sensitive to the previous activities at different time points, depending on the cortical locations, indicating that the information stored in the cortex at different time points was distributed across different cortical areas. These results suggest different roles of superficial and deep layer neurons in the long-term multimodal representation of the environment.

    Link

  • In Symposium on Advances in Approximate Bayesian Inference (pp. 32-53) (2019)

    Authors:
    Lueckmann, J. M., Bassetto, G., Karaletsos, T., & Macke, J. H.

    Abstract:

    Approximate Bayesian Computation (ABC) provides methods for Bayesian inference in simulation-based models which do not permit tractable likelihoods. We present a new ABC method which uses probabilistic neural emulator networks to learn synthetic likelihoods on simulated data – both ’local’ emulators which approximate the likelihood for specific observed data, as well as ’global’ ones which are applicable to a range of data. Simulations are chosen adaptively using an acquisition function which takes into account uncertainty about either the posterior distribution of interest, or the parameters of the emulator. Our approach does not rely on user-defined rejection thresholds or distance functions. We illustrate inference with emulator networks on synthetic examples and on a biophysical neuron model, and show that emulators allow accurate and efficient inference even on problems which are challenging for conventional ABC approaches.

    Link

  • arXiv preprint arXiv:1909.01908 (2019)

    Authors:
    van Meegen, A., & van Albada, S. J.

    Abstract:

    A complex interplay of single-neuron properties and the recurrent network structure shapes the activity of individual cortical neurons, which differs in general from the respective population activity. We develop a theory that makes it possible to investigate the influence of both network structure and single-neuron properties on the single-neuron statistics in block-structured sparse random networks of spiking neurons. In particular, the theory predicts the neuron-level autocorrelation times, also known as intrinsic timescales, of the neuronal activity. The theory is based on a postulated extension of dynamic mean-field theory from rate networks to spiking networks, which is validated via simulations. It accounts for both static variability, e.g. due to a distributed number of incoming synapses per neuron, and dynamical fluctuations of the input. To illustrate the theory, we apply it to a balanced random network of leaky integrate-and-fire neurons, a balanced random network of generalized linear model neurons, and a biologically constrained network of leaky integrate-and-fire neurons. For the generalized linear model network, an analytical solution to the colored noise problem allows us to obtain self-consistent firing rate distributions, single-neuron power spectra, and intrinsic timescales. For the leaky integrate-and-fire networks, we obtain the same quantities by means of a novel analytical approximation of the colored noise problem that is valid in the fluctuation-driven regime. Our results provide a further step towards an understanding of the dynamics in recurrent spiking cortical networks.

    Link

  • Magnetic resonance in medicine, 82(5), 1804-1811 (2019)

    Authors:
    Papazoglou, S., Streubel, T., Ashtarayeh, M., Pine, K. J., Edwards, L. J., Brammerloh, M., … & Callaghan, M. F.

    Abstract:

    Purpose: To propose and validate an efficient method, based on a biophysically motivated signal model, for removing the orientation‐dependent part of R*2 using a single gradient‐recalled echo (GRE) measurement.

    Methods: The proposed method utilized a temporal second‐order approximation of the hollow‐cylinder‐fiber model, in which the parameter describing the linear signal decay corresponded to the orientation‐independent part of R*2. The estimated parameters were compared to the classical, mono‐exponential decay model for R*2 in a sample of an ex vivo human optic chiasm (OC). The OC was measured at 16 distinct orientations relative to the external magnetic field using GRE at 7T. To show that the proposed signal model can remove the orientation dependence of R*2, it was compared to the established phenomenological method for separating R*2 into orientation-dependent and independent parts.

    Results: Using the phenomenological method on the classical signal model, the well‐known separation of R*2 into orientation‐dependent and ‐independent parts was verified. For the proposed model, no significant orientation dependence in the linear signal decay parameter was observed.

    Conclusions: Since the proposed second‐order model features orientation‐dependent and ‐independent components at distinct temporal orders, it can be used to remove the orientation dependence of R*2 using only a single GRE measurement.

    Link

  • Computational Brain & Behavior volume 2, pages229–232 (2019)

    Authors:
    Poldrack, R. A., Feingold, F., Frank, M. J., Gleeson, P., de Hollander, G., Huys, Q. J., … & Rogers, T. T.

    Abstract:

    The Target Article by Lee et al. (2019) highlights the ways in which ongoing concerns about research reproducibility extend to model-based approaches in cognitive science. Whereas Lee et al. focus primarily on the importance of research practices to improve model robustness, we propose that the transparent sharing of model specifications, including their inputs and outputs, is also essential to improving the reproducibility of model-based analyses. We outline an ongoing effort (within the context of the Brain Imaging Data Structure community) to develop standards for the sharing of the structure of computational models and their outputs.

    Link

  • Bernstein Conference 2019 (2019)

    Authors:
    Renner, S., Kraynyukova, N, Kotkat, A.H., Bauer, Y., Born, G., Spacek, M., Tchumatchenko, T., Busse, L.

    Abstract:

    n.a.

    Link

  • Network Neuroscience, 3(4), 944-968 (2019)

    Authors:
    Rojas, P., Plath, J. A., Gestrich, J., Ananthasubramaniam, B., Garcia, M. E., Herzel, H., & Stengl, M.

    Abstract:

    The circadian clock of the nocturnal Madeira cockroach is located in the accessory medulla, a small non-retinotopic neuropil in the brain's visual system. The clock comprises about 240 neurons that control rhythms in physiology and behaviour such as sleep-wake cycles. The clock neurons contain an abundant number of partly co-localized neuropeptides, among them pigment-dispersing factor (PDF), the insects' most important circadian coupling signal that controls sleep-wake rhythms. We performed long-term loose patch clamp recordings under 12:12 h light-dark cycles in the cockroach clock in vivo. A wide range of timescales, from milliseconds to seconds, was found in spike and field potential patterns. We developed a framework of wavelet transform based methods to detect these multiscale electrical events. We analysed frequencies and patterns of events with interesting dynamic features, such as mixed-mode oscillations reminiscent of sharp-wave ripples. Oscillations in the beta/gamma frequency range (20 – 40 Hz) were observed to rise at dawn, when PDF is released, peaking just before the onset of locomotor activity of the nocturnal cockroach. We expect, that in vivo electrophysiological recordings combined with neuropeptide/antagonist applications and behavioural analysis will determine whether specific patterns of electrical activity recorded in the network of the cockroach circadian clock are causally related to with neuropeptide-dependent control of behaviour.

    Link

  • PLOS Computational Biology, 15(10), e1007004 (2019)

    Authors:
    Schmidt, H., & Knösche, T. R.

    Abstract:

    With the advent of advanced MRI techniques it has become possible to study axonal white matter non-invasively and in great detail. Measuring the various parameters of the long-range connections of the brain opens up the possibility to build and refine detailed models of large-scale neuronal activity. One particular challenge is to find a mathematical description of action potential propagation that is sufficiently simple, yet still biologically plausible to model signal transmission across entire axonal fibre bundles. We develop a mathematical framework in which we replace the Hodgkin-Huxley dynamics by a spike-diffuse-spike model with passive sub-threshold dynamics and explicit, threshold-activated ion channel currents. This allows us to study in detail the influence of the various model parameters on the action potential velocity and on the entrainment of action potentials between ephaptically coupled fibres without having to recur to numerical simulations. Specifically, we recover known results regarding the influence of axon diameter, node of Ranvier length and internode length on the velocity of action potentials. Additionally, we find that the velocity depends more strongly on the thickness of the myelin sheath than was suggested by previous theoretical studies. We further explain the slowing down and synchronisation of action potentials in ephaptically coupled fibres by their dynamic interaction. In summary, this study presents a solution to incorporate detailed axonal parameters into a whole-brain modelling framework.

    Link

  • Scientific data, 6(1), 1-12 (2019)

    Authors:
    Shen, K., Bezgin, G., Schirner, M., Ritter, P., Everling, S., & McIntosh, A. R.

    Abstract:

    Models of large-scale brain networks that are informed by the underlying anatomical connectivity contribute to our understanding of the mapping between the structure of the brain and its dynamical function. Connectome-based modelling is a promising approach to a more comprehensive understanding of brain function across spatial and temporal scales, but it must be constrained by multi-scale empirical data from animal models. Here we describe the construction of a macaque (Macaca mulatta and Macaca fascicularis) connectome for whole-cortex simulations in TheVirtualBrain, an open-source simulation platform. We take advantage of available axonal tract-tracing datasets and enhance the existing connectome data using diffusion-based tractography in macaques. We illustrate the utility of the connectome as an extension of TheVirtualBrain by simulating resting-state BOLD-fMRI data and fitting it to empirical resting-state data.

    Link

  • Frontiers in computational neuroscience, 13, 54 (2019)

    Authors:
    Stefanovski, L., Triebkorn, J. P., Spiegler, A., Diaz-Cortes, M. A., Solodkin, A., Jirsa, V., … & Ritter, P.

    Abstract:

    Introduction: While the prevalence of neurodegenerative diseases associated with dementia such as Alzheimer’s disease (AD) increases, our knowledge on the underlying mechanisms, outcome predictors, or therapeutic targets is limited. In this work, we demonstrate how computational multi-scale brain modeling links phenomena of different scales and therefore identifies potential disease mechanisms leading the way to improved diagnostics and treatment. Methods: The Virtual Brain (TVB; thevirtualbrain.org) neuroinformatics platform allows standardized large-scale structural connectivity-based simulations of whole brain dynamics. We provide proof of concept for a novel approach that quantitatively links the effects of altered molecular pathways onto neuronal population dynamics. As a novelty, we connect chemical compounds measured with positron emission tomography (PET) with neural function in TVB addressing the phenomenon of hyperexcitability in AD related to the protein amyloid beta (Abeta). We construct personalized virtual brains based on an averaged healthy connectome and individual PET derived distributions of Abeta in patients with mild cognitive impairment (MCI, N = 8) and Alzheimer’s Disease (AD, N = 10) and in age-matched healthy controls (HC, N = 15) using data from ADNI-3 data base (http://adni.loni.usc.edu). In the personalized virtual brains, individual Abeta burden modulates regional Excitation-Inhibition balance, leading to local hyperexcitation with high Abeta loads. We analyze simulated regional neural activity and electroencephalograms (EEG). Results: Known empirical alterations of EEG in patients with AD compared to HCs were reproduced by simulations. The virtual AD group showed slower frequencies in simulated local field potentials and EEG compared to MCI and HC groups. The heterogeneity Stefanovski et al. The Virtual Neurodegenerative Brain of the Abeta load is crucial for the virtual EEG slowing which is absent for control models with homogeneous Abeta distributions. Slowing phenomena primarily affect the network hubs, independent of the spatial distribution of Abeta. Modeling the N-methyl-D-aspartate (NMDA) receptor antagonism of memantine in local population models, reveals potential functional reversibility of the observed large-scale alterations (reflected by EEG slowing) in virtual AD brains. Discussion: We demonstrate how TVB enables the simulation of systems effects caused by pathogenetic molecular candidate mechanisms in human virtual brains.

    Link

  • Neuroimage, 194, 191-210 (2019)

    Authors:
    Tabelow, K., Balteau, E., Ashburner, J., Callaghan, M. F., Draganski, B., Helms, G., … & Reimer, E.

    Abstract:

    Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R⋆2 , proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g- ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user’s perspective, the hMRI-toolbox is an effi- cient, robust and simple framework for investigating qMRI data in neuroscience and clinical research.

    Link

  • Current Biology, 29(19), R933-R935 (2019)

    Authors:
    Vlasits A., Baden T.

    Abstract:

    In animal eyes, the detection of slow global image motion is crucial to preventing blurry vision. A new study reveals how a mammalian global motion detector achieves this through ‘space–time wiring’ at its dendrites.

    Link

  • Network Neuroscience Volume 3 | Issue 1 | 2019 (2019)

    Authors:
    Zimmermann, J., Griffiths, J., Schirner, M., Ritter, P., & McIntosh, A. R.

    Abstract:

    Structural connectivity (SC), the physical pathways connecting regions in the brain, and functional connectivity (FC), the temporal coactivations, are known to be tightly linked. However, the nature of this relationship is still not understood. In the present study, we examined this relation more closely in six separate human neuroimaging datasets with different acquisition and preprocessing methods. We show that using simple linear associations, the relation between an individual’s SC and FC is not subject specific for five of the datasets. Subject specificity of SC-FC fit is achieved only for one of the six datasets, the multimodal Glasser Human Connectome Project (HCP) parcellated dataset. We show that subject specificity of SC-FC correspondence is limited across datasets due to relatively small variability between subjects in SC compared with the larger variability in FC.

    Link

2018

  • European Journal of Neuroscience, 51(1), 282-299 (2018b)

    Authors:
    Giese, M., Wei, H., & Stengl, M.

    Abstract:

    GABA is the most abundant neurotransmitter in the circadian pacemaker circuits of mammals and insects. In the Madeira cockroach the accessory medulla (AME) in the brain´s optic lobes is the circadian clock that orchestrates rest-activity rhythms in synchrony with light dark cycles. Three prominent GABAergic tracts connect the AME to termination sites of compound eye photoreceptors in the lamina and medulla. Parallel GABAergic light entrainment pathways were suggested to either advance or delay the clock for adjustment to changing photoperiods. In agreement with this hypothesis GABA activated or inhibited AME clock neurons, allowing for distinction of three different GABA response types. Here, we examined which GABA receptors are responsible for these response types. We found that both ionotropic GABAA receptors and metabotropic GABAB receptors were expressed in AME clock cells. Via different signaling pathways, either one of them could account for all three GABA response types. The muscimol-dependently activated GABAA receptor formed a chloride channel, while the SKF 97541-dependently activated GABAB receptor signaled via G-proteins, apparently targeting potassium channels. Expression of chloride exporters or –importers determined whether GABAA receptor activation hyper- or depolarized AME neurons. For GABAB receptor responses second messenger gated channels present in the clock cells appeared to decide about the polarity of the GABA response. In summary, circadian clock neurons co-expressed inhibitory and/or excitatory GABAA and GABAB receptors in various combinations, while cotransporter expression and the set of second messenger gated ion channels present allowed for distinct signaling in different clock neurons.

    Link

  • Eneuro, 5(3) (2018)

    Authors:
    Aerts, H., Schirner, M., Jeurissen, B., Van Roost, D., Achten, E., Ritter, P., & Marinazzo, D.

    Abstract:

    Presurgical planning for brain tumor resection aims at delineating eloquent tissue in the vicinity of the lesion to spare during surgery. To this end, noninvasive neuroimaging techniques such as functional MRI and diffusion-weighted imaging fiber tracking are currently employed. However, taking into account this information is often still insufficient, as the complex nonlinear dynamics of the brain impede straightforward prediction of functional outcome after surgical intervention. Large-scale brain network modeling carries the potential to bridge this gap by integrating neuroimaging data with biophysically based models to predict collective brain dynamics. As a first step in this direction, an appropriate computational model has to be selected, after which suitable model parameter values have to be determined. To this end, we simulated large-scale brain dynamics in 25 human brain tumor patients and 11 human control participants using The Virtual Brain, an open-source neuroinformatics platform. Local and global model parameters of the Reduced Wong–Wang model were individually optimized and compared between brain tumor patients and control subjects. In addition, the relationship between model parameters and structural network topology and cognitive performance was assessed. Results showed (1) significantly improved prediction accuracy of individual functional connectivity when using individually optimized model parameters; (2) local model parameters that can differentiate between regions directly affected by a tumor, regions distant from a tumor, and regions in a healthy brain; and (3) interesting associations between individually optimized model parameters and structural network topology and cognitive performance.

    Link

  • PLoS computational biology, 14(11), e1006550 (2018)

    Authors:
    Beul, S. F., Goulas, A., & Hilgetag, C. C.

    Abstract:

    The architectonic type principle relates patterns of cortico-cortical connectivity to the relative architectonic differentiation of cortical regions. One mechanism through which the observed close relation between cortical architecture and connectivity may be established is the joint development of cortical areas and their connections in developmental time windows. Here, we describe a theoretical exploration of the possible mechanistic underpinnings of the architectonic type principle, by performing systematic computational simulations of cortical development. The main component of our in silico model was a developing two-dimensional cortical sheet, which was gradually populated by neurons that formed cortico-cortical connections. To assess different explanatory mechanisms, we varied the spatiotemporal trajectory of the simulated neurogenesis. By keeping the rules governing axon outgrowth and connection formation constant across all variants of simulated development, we were able to create model variants which differed exclusively by the specifics of when and where neurons were generated. Thus, all differences in the resulting connectivity were due to the variations in spatiotemporal growth trajectories. Our results demonstrated that a prescribed targeting of interareal connection sites was not necessary for obtaining a realistic replication of the experimentally observed relation between connection patterns and architectonic differentiation. Instead, we found that spatiotemporal interactions within the forming cortical sheet were sufficient if a small number of empirically well-grounded assumptions were met, namely planar, expansive growth of the cortical sheet around two points of origin as neurogenesis progressed, stronger architectonic differentiation of cortical areas for later neurogenetic time windows, and stochastic connection formation. Thus, our study highlights a potential mechanism of how relative architectonic differentiation and cortical connectivity become linked during development. We successfully predicted connectivity in two species, cat and macaque, from simulated cortico-cortical connection networks, which further underscored the general applicability of mechanisms through which the architectonic type principle can explain cortical connectivity in terms of the relative architectonic differentiation of cortical regions.

    Link

  • European Journal of Neuroscience, 48(12), 3583-3596 (2018)

    Authors:
    Bockhorst, T., Pieper, F., Engler, G., Stieglitz, T., Galindo‐Leon, E., & Engel, A. K.

    Abstract:

    Synchronous spiking of multiple neurons is a key phenomenon in normal brain function and pathologies. Recently, approaches to record spikes from the intact cortical surface using small high-density arrays of microelectrodes have been reported. It remained unaddressed how epicortical spiking relates to intracortical unit activity. We introduced a mesoscale approach using an array of 64 electrodes with intermediate diameter (250 μm) and combined large-coverage epicortical recordings in ferrets with intracortical recordings via laminar probes. Empirical data and modelling strongly suggest that our epicortical electrodes selectively captured synchronized spiking of neurons in the cortex beneath. As a result, responses to sensory stimulation were more robust and less noisy compared to intracortical activity, and receptive field properties were well preserved in epicortical recordings. This should promote insights into assembly-coding beyond the informative value of subdural EEG or single-unit spiking, and be advantageous to real-time applications in brain-machine interfacing.

    Link

  • Cerebral Cortex, 28(8), 2991-3003 (2018)

    Authors:
    Fischer, F., Pieper, F., Galindo-Leon, E., Engler, G., Hilgetag, C. C., & Engel, A. K.

    Abstract:

    Cortical single neuron activity and local field potential patterns change at different depths of general anesthesia. Here, we investigate the associated network level changes of functional connectivity. We recorded ongoing electrocorticographic (ECoG) activity from temporo-parieto-occipital cortex of 6 ferrets at various levels of isoflurane/nitrous oxide anesthesia and determined functional connectivity by computing amplitude envelope correlations. Through hierarchical clustering, we derived typical connectivity patterns corresponding to light, intermediate and deep anesthesia. Generally, amplitude correlation strength increased strongly with depth of anesthesia across all cortical areas and frequency bands. This was accompanied, at the deepest level, by the emergence of burst-suppression activity in the ECoG signal and a change of the spectrum of the amplitude envelope. Normalization of functional connectivity to the distribution of correlation coefficients showed that the topographical patterns remained similar across depths of anesthesia, reflecting the functional association of the underlying cortical areas. Thus, while strength and temporal properties of amplitude co-modulation vary depending on the activity of local neural circuits, their network-level interaction pattern is presumably most strongly determined by the underlying structural connectivity.

    Link

  • Methods, 50, 42-48 (2018)

    Authors:
    Förster D., Kramer A., Baier H., Kubo F.

    Abstract:

    All-optical methods enable the control and monitoring of neuronal activity with minimal perturbation of the system. Although imaging and optogenetic manipulations can be performed at cellular resolution, the morphology of single cells in a dense neuronal population has often remained unresolvable. Here we describe in detail two recently established optogenetic protocols for systematic description of function and morphology of single neurons in zebrafish. First, the Optobow toolbox allows unbiased mapping of excitatory functional connectivity. Second, the FuGIMA technique enables selective labeling and anatomical tracing of neurons that are responsive to a given sensory stimulus or correlated with a specific behavior. Both strategies can be genetically targeted to a neuronal population of choice using the Gal4/UAS system. As these in vivo approaches are non-invasive, we envision useful applications for the study of neuronal structure, function and connectivity during development and behavior.

    Link

  • Journal of biological rhythms, 33(1), 35-51 (2018)

    Authors:
    Gestrich, J., Giese, M., Shen, W., Zhang, Y., Voss, A., Popov, C., … & Wei, H.

    Abstract:

    In the Madeira cockroach lesion and transplantation studies located the circadian clock in the accessory medulla (AME). The AME is innervated by ~240 adjacent neuropeptidergic pacemaker neurons that are spontaneously active in the circadian- as well as in the gamma frequency range of 20-70 Hz. Best studied are the pigment-dispersing factor neurons anterior to the AME (aPDFMEs) that control locomotor activity rhythms and couple both clocks. Here, we analyzed responses of AME neurons to PDF, GABA, and acetylcholine. Using calcium imaging and immunocytochemistry with primary cell cultures, we characterized for the first time PDF autoreceptors in the cockroach and found cell type-specific PDF signaling. While contralaterally projecting AME cells such as medium-sized aPDFMEs were inhibited by PDF, ipsilaterally remaining AME cells such as small aPDFMEs were activated. Only the largest aPDFME did not express PDF autoreceptors. Using in vivo intracellular recordings we demonstrated that the largest aPDFME generates regular action potential bursts, which were not light-dependent during the day. Furthermore, all PDF-sensitive neurons recorded received cholinergic excitatory- and GABAergic inhibitory synaptic inputs. We hypothesize that PDF-signaling activates ipsilateral clock outputs while suppressing outputs of the contralateral clock. Furthermore, we suggest that the largest aPDFME controls rest-arousal rhythms of the cockroach.

    Link

  • European Journal of Neuroscience, 47(9), 1067-1080 (2018)

    Authors:
    Giese, M., Gestrich, J., Massah, A., Peterle, J., Wei, H., & Stengl, M.

    Abstract:

    In the Madeira cockroach pigment-dispersing factor-immunoreactive (PDF-ir) neurons innervating the circadian clock, the accessory medulla (AME) in the brain´s optic lobes, control circadian behavior. Circadian activity rhythms are entrained to daily light-dark cycles only by compound eye photoreceptors terminating in the lamina and medulla. Still, it is unknown which neurons connect the photoreceptors to the clock to allow for light-entrainment. Here, we characterized by multiple-label immunocytochemistry the serotonin (5-HT)-ir anterior fiber fan and GABA-ir pathways connecting the AME- and optic lobe neuropils. Colocalization of 5-HT with PDF was confirmed in PDF-ir lamina neurons (PDFLAs). Double-labeled fibers were traced to the AME originating from colabeled PDFLAs branching in accessory laminae and proximal lamina. The newly discovered GABA-ir medial layer fiber tract connected the AME to the medulla´s medial layer fiber system and the distal tract fibers connected the AME to the medulla. With Ca2+-imaging on primary cell cultures of the AME and with loose patch clamp recordings in vivo we showed that both neurotransmitters either excite or inhibit AME clock neurons. Because we found no colocalization of GABA and 5-HT in any optic lobe neuron, GABA- and 5-HT-neurons form separate clock input circuits. Among others, both pathways converged also on AME neurons that coexpressed mostly inhibitory GABA- and excitatory 5-HT-receptors. Our physiological and immunocytochemical studies demonstrate that GABA- and 5-HT-immunoreactive neurons constitute parallel excitatory or inhibitory pathways connecting the circadian clock either to the lamina and/or medulla where photic information from the compound eye is processed.

    Link

  • PLoS computational biology, 14(4), e1006084 (2018)

    Authors:
    Messé, A., Hütt, M. T., & Hilgetag, C. C.

    Abstract:

    The relationship between the structural connectivity (SC) and functional connectivity (FC) of neural systems is of central importance in brain network science. It is an open question, however, how the SC-FC relationship depends on specific topological features of brain networks or the models used for describing neural dynamics. Using a basic but general model of discrete excitable units that follow a susceptible—excited—refractory activity cycle (SER model), we here analyze how the network activity patterns underlying functional connectivity are shaped by the characteristic topological features of the network. We develop an analytical framework for describing the contribution of essential topological elements, such as common inputs and pacemakers, to the coactivation of nodes, and demonstrate the validity of the approach by comparison of the analytical predictions with numerical simulations of various exemplar networks. The present analytic framework may serve as an initial step for the mechanistic understanding of the contributions of brain network topology to brain dynamics.

    Link

  • Neuroimage 182:417-428 (2018)

    Authors:
    Morawski, M., Kirilina, E., Scherf, N., Jäger, C., Reimann, K., Trampel, R., … & Weiskopf, N.

    Abstract:

    Recent breakthroughs in magnetic resonance imaging (MRI) enabled quantitative relaxometry and diffusion-weighted imaging with sub-millimeter resolution. Combined with biophysical models of MR contrast the emerging methods promise in vivo mapping of cyto- and myelo-architectonics, i.e., in vivo histology using MRI (hMRI) in humans. The hMRI methods require histological reference data for model building and validation. This is currently provided by MRI on post mortem human brain tissue in combination with classical histology on sections. However, this well established approach is limited to qualitative 2D information, while a systematic validation of hMRI requires quantitative 3D information on macroscopic voxels. We present a promising histological method based on optical 3D imaging combined with a tissue clearing method, Clear Lipid-exchanged Acrylamide-hybridized Rigid Imaging compatible Tissue hYdrogel (CLARITY), adapted for hMRI validation. Adapting CLARITY to the needs of hMRI is challenging due to poor antibody penetration into large sample volumes and high opacity of aged post mortem human brain tissue. In a pilot experiment we achieved transparency of up to 8 mm-thick and immunohistochemical staining of up to 5 mm-thick post mortem brain tissue by a combination of active and passive clearing, prolonged clearing and staining times. We combined 3D optical imaging of the cleared samples with tailored image processing methods. We demonstrated the feasibility for quantification of neuron density, fiber orientation distribution and cell type classification within a volume with size similar to a typical MRI voxel. The presented combination of MRI, 3D optical microscopy and image processing is a promising tool for validation of MRI-based microstructure estimates.

    Link

  • eLife 7:e28927 (2018)

    Authors:
    Schirner, M., McIntosh, A. R., Jirsa, V., Deco, G., & Ritter, P.

    Abstract:

    The neurophysiological processes underlying non-invasive brain activity measurements are incompletely understood. Here, we developed a connectome-based brain network model that integrates individual structural and functional data with neural population dynamics to support multi-scale neurophysiological inference. Simulated populations were linked by structural connectivity and, as a novelty, driven by electroencephalography (EEG) source activity. Simulations not only predicted subjects' individual resting-state functional magnetic resonance imaging (fMRI) time series and spatial network topologies over 20 minutes of activity, but more importantly, they also revealed precise neurophysiological mechanisms that underlie and link six empirical observations from different scales and modalities: (1) resting-state fMRI oscillations, (2) functional connectivity networks, (3) excitation-inhibition balance, (4, 5) inverse relationships between α-rhythms, spike-firing and fMRI on short and long time scales, and (6) fMRI power-law scaling. These findings underscore the potential of this new modelling framework for general inference and integration of neurophysiological knowledge to complement empirical studies.

    Link

  • PLoS computational biology, 14(10), e1006359 (2018)

    Authors:
    Schmidt, M., Bakker, R., Shen, K., Bezgin, G., Diesmann, M., & van Albada, S. J.

    Abstract:

    Cortical activity has distinct features across scales, from the spiking statistics of individual cells to global resting-state networks. We here describe the first full-density multi-area spiking network model of cortex, using macaque visual cortex as a test system. The model represents each area by a microcircuit with area-specific architecture and features layer- and population-resolved connectivity between areas. Simulations reveal a structured asynchronous irregular ground state. In a metastable regime, the network reproduces spiking statistics from electrophysiological recordings and cortico-cortical interaction patterns in fMRI functional connectivity under resting-state conditions. Stable inter-area propagation is supported by cortico-cortical synapses that are moderately strong onto excitatory neurons and stronger onto inhibitory neurons. Causal interactions depend on both cortical structure and the dynamical state of populations. Activity propagates mainly in the feedback direction, similar to experimental results associated with visual imagery and sleep. The model unifies local and large-scale accounts of cortex, and clarifies how the detailed connectivity of cortex shapes its dynamics on multiple scales. Based on our simulations, we hypothesize that in the spontaneous condition the brain operates in a metastable regime where cortico-cortical projections target excitatory and inhibitory populations in a balanced manner that produces substantial inter-area interactions while maintaining global stability.

    Link

  • Current Opinion in Neurobiology, Volume 56 (2018)

    Authors:
    Vlasits, A. L., Euler, T., & Franke, K.

    Abstract:

    Cell type classification has been a major part of retina research for over one hundred years. In recent years, the ability to sample large populations of retinal cells has accelerated cell type classification based on different criteria like genetics, morphology, function, and circuitry. For example, recent work includes bipolar and retinal ganglion cell classifications based on single-cell transcriptomes, large-scale electron microscopy reconstruction, and population-level functional imaging. With comprehensive descriptions of several retinal cell classes now within reach, it is important to reflect on the priority of these different criteria to create an accurate and useful classification. Here, we argue that functional information about retinal cells should be prioritized over other criteria when addressing questions of visual function because this criterion provides the most meaningful information about how the retina works.

    Link

  • NeuroImage: Clinical, Volume 19, Pages 240-251 (2018)

    Authors:
    Zimmermann, J., Perry, A., Breakspear, M., Schirner, M., Sachdev, P., Wen, W., … & Solodkin, A.

    Abstract:

    Alzheimer's disease (AD) is marked by cognitive dysfunction emerging from neuropathological processes impacting brain function. AD affects brain dynamics at the local level, such as changes in the balance of inhibitory and excitatory neuronal populations, as well as long-range changes to the global network. Individual differences in these changes as they relate to behaviour are poorly understood. Here, we use a multi-scale neurophysiological model, “The Virtual Brain (TVB)”, based on empirical multi-modal neuroimaging data, to study how local and global dynamics correlate with individual differences in cognition. In particular, we modeled individual resting-state functional activity of 124 individuals across the behavioural spectrum from healthy aging, to amnesic Mild Cognitive Impairment (MCI), to AD. The model parameters required to accurately simulate empirical functional brain imaging data correlated significantly with cognition, and exceeded the predictive capacity of empirical connectomes.

    Link