Generative models of the human connectome

The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan.Comment: 38 pages, 5 figures + 19 supplemental figures, 1 tabl

Molecular crowding and RNA synergize to promote phase separation, microtubule interaction, and seeding of Tau condensates

Biomolecular condensation of the neuronal microtubule-associated protein Tau (MAPT) can be induced by coacervation with polyanions like RNA, or by molecular crowding. Tau condensates have been linked to both functional microtubule binding and pathological aggregation in neurodegenerative diseases. We find that molecular crowding and coacervation with RNA, two conditions likely coexisting in the cytosol, synergize to enable Tau condensation at physiological buffer conditions and to produce condensates with a strong affinity to charged surfaces. During condensate-mediated microtubule polymerization, their synergy enhances bundling and spatial arrangement of microtubules. We further show that different Tau condensates efficiently induce pathological Tau aggregates in cells, including accumulations at the nuclear envelope that correlate with nucleocytoplasmic transport deficits. Fluorescent lifetime imaging reveals different molecular packing densities of Tau in cellular accumulations and a condensate-like density for nuclear-envelope Tau. These findings suggest that a complex interplay between interaction partners, post-translational modifications, and molecular crowding regulates the formation and function of Tau condensates. Conditions leading to prolonged existence of Tau condensates may induce the formation of seeding-competent Tau and lead to distinct cellular Tau accumulations

Mapping structural diversity in networks sharing a given degree distribution and global clustering: Adaptive resolution grid search evolution with Diophantine equation-based mutations

Methods that generate networks sharing a given degree distribution and global clustering can induce changes in structural properties other than that controlled for. Diversity in structural properties, in turn, can affect the outcomes of dynamical processes operating on those networks. Since exhaustive sampling is not possible, we propose a novel evolutionary framework for mapping this structural diversity. The three main features of this framework are: (a) subgraph-based encoding of networks, (b) exact mutations based on solving systems of Diophantine equations, and (c) heuristic diversity-driven mechanism to drive resolution changes in the MapElite algorithm.We show that our framework can elicit networks with diversity in their higher-order structure and that this diversity affects the behaviour of the complex contagion model. Through a comparison with state of the art clustered network generation methods, we demonstrate that our approach can uncover a comparably diverse range of networks without needing computationally unfeasible mixing times. Further, we suggest that the subgraph-based encoding provides greater confidence in the diversity of higher-order network structure for low numbers of samples and is the basis for explaining our results with complex contagion model. We believe that this framework could be applied to other complex landscapes that cannot be practically mapped via exhaustive sampling

Electronic damage in S atoms in a native protein crystal induced by an intense X-ray free-electron laser pulse

Current hard X-ray free-electron laser (XFEL) sources can deliver doses to biological macromolecules well exceeding 1 GGy, in timescales of a few tens of femtoseconds. During the pulse, photoionization can reach the point of saturation in which certain atomic species in the sample lose most of their electrons. This electronic radiation damage causes the atomic scattering factors to change, affecting, in particular, the heavy atoms, due to their higher photoabsorption cross sections. Here, it is shown that experimental serial femtosecond crystallography data collected with an extremely bright XFEL source exhibit a reduction of the effective scattering power of the sulfur atoms in a native protein. Quantitative methods are developed to retrieve information on the effective ionization of the damaged atomic species from experimental data, and the implications of utilizing new phasing methods which can take advantage of this localized radiation damage are discussed

The Dynamics of Functional Brain Networks:Integrated Network States during Cognitive Task Performance

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions, however it is unclear how this mechanism manifests over time. In this study, we use time-resolved network analysis of functional magnetic resonance imaging data to demonstrate that the human brain traverses between two functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. The integrated state enables faster and more accurate performance on a cognitive task, and is associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Our data confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.Comment: 38 pages, 4 figure

Frustrated hierarchical synchronization and emergent complexity in the human connectome network

The spontaneous emergence of coherent behavior through synchronization plays a key role in neural function, and its anomalies often lie at the basis of pathologies. Here we employ a parsimonious (mesoscopic) approach to study analytically and computationally the synchronization (Kuramoto) dynamics on the actual human-brain connectome network. We elucidate the existence of a so-far-uncovered intermediate phase, placed between the standard synchronous and asynchronous phases, i.e. between order and disorder. This novel phase stems from the hierarchical modular organization of the connectome. Where one would expect a hierarchical synchronization process, we show that the interplay between structural bottlenecks and quenched intrinsic frequency heterogeneities at many different scales, gives rise to frustrated synchronization, metastability, and chimera-like states, resulting in a very rich and complex phenomenology. We uncover the origin of the dynamic freezing behind these features by using spectral graph theory and discuss how the emerging complex synchronization patterns relate to the need for the brain to access –in a robust though flexible way– a large variety of functional attractors and dynamical repertoires without ad hoc fine-tuning to a critical pointWe acknowledge financial support from J. de Andalucía, grant P09-FQM-4682 and we thank O. Sporns for providing us access to the human connectome data

Monitoring and Scoring Counter-Diffusion Protein Crystallization Experiments in Capillaries by in situ Dynamic Light Scattering

In this paper, we demonstrate the feasibility of using in situ Dynamic Light Scattering (DLS) to monitor counter-diffusion crystallization experiments in capillaries. Firstly, we have validated the quality of the DLS signal in thin capillaries, which is comparable to that obtained in standard quartz cuvettes. Then, we have carried out DLS measurements of a counter-diffusion crystallization experiment of glucose isomerase in capillaries of different diameters (0.1, 0.2 and 0.3 mm) in order to follow the temporal evolution of protein supersaturation. Finally, we have compared DLS data with optical recordings of the progression of the crystallization front and with a simulation model of counter-diffusion in 1D

Dynamic Assessment of Baroreflex Control of Heart Rate During Induction of Propofol Anesthesia Using a Point Process Method

In this article, we present a point process method to assess dynamic baroreflex sensitivity (BRS) by estimating the baroreflex gain as focal component of a simplified closed-loop model of the cardiovascular system. Specifically, an inverse Gaussian probability distribution is used to model the heartbeat interval, whereas the instantaneous mean is identified by linear and bilinear bivariate regressions on both the previous R−R intervals (RR) and blood pressure (BP) beat-to-beat measures. The instantaneous baroreflex gain is estimated as the feedback branch of the loop with a point-process filter, while the RRBP feedforward transfer function representing heart contractility and vasculature effects is simultaneously estimated by a recursive least-squares filter. These two closed-loop gains provide a direct assessment of baroreflex control of heart rate (HR). In addition, the dynamic coherence, cross bispectrum, and their power ratio can also be estimated. All statistical indices provide a valuable quantitative assessment of the interaction between heartbeat dynamics and hemodynamics. To illustrate the application, we have applied the proposed point process model to experimental recordings from 11 healthy subjects in order to monitor cardiovascular regulation under propofol anesthesia. We present quantitative results during transient periods, as well as statistical analyses on steady-state epochs before and after propofol administration. Our findings validate the ability of the algorithm to provide a reliable and fast-tracking assessment of BRS, and show a clear overall reduction in baroreflex gain from the baseline period to the start of propofol anesthesia, confirming that instantaneous evaluation of arterial baroreflex control of HR may yield important implications in clinical practice, particularly during anesthesia and in postoperative care.National Institutes of Health (U.S.) (Grant R01-HL084502)National Institutes of Health (U.S.) (Grant K25-NS05758)National Institutes of Health (U.S.) (Grant DP2- OD006454)National Institutes of Health (U.S.) (Grant T32NS048005)National Institutes of Health (U.S.) (Grant T32NS048005)National Institutes of Health (U.S.) (Grant R01-DA015644)Massachusetts General Hospital (Clinical Research Center, UL1 Grant RR025758