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Internal state dynamics shape brainwide activity and foraging behaviour 期刊论文
NATURE, 2020, 577 (7789) : 239-+
作者:  Marques, Joao C.;  Li, Meng;  Schaak, Diane;  Robson, Drew N.;  Li, Jennifer M.
收藏  |  浏览/下载:21/0  |  提交时间:2020/07/03

The brain has persistent internal states that can modulate every aspect of an animal'  s mental experience(1-4). In complex tasks such as foraging, the internal state is dynamic(5-8). Caenorhabditis elegans alternate between local search and global dispersal(5). Rodents and primates exhibit trade-offs between exploitation and exploration(6,7). However, fundamental questions remain about how persistent states are maintained in the brain, which upstream networks drive state transitions and how state-encoding neurons exert neuromodulatory effects on sensory perception and decision-making to govern appropriate behaviour. Here, using tracking microscopy to monitor whole-brain neuronal activity at cellular resolution in freely moving zebrafish larvae(9), we show that zebrafish spontaneously alternate between two persistent internal states during foraging for live prey (Paramecia). In the exploitation state, the animal inhibits locomotion and promotes hunting, generating small, localized trajectories. In the exploration state, the animal promotes locomotion and suppresses hunting, generating long-ranging trajectories that enhance spatial dispersion. We uncover a dorsal raphe subpopulation with persistent activity that robustly encodes the exploitation state. The exploitation-state-encoding neurons, together with a multimodal trigger network that is associated with state transitions, form a stochastically activated nonlinear dynamical system. The activity of this oscillatory network correlates with a global retuning of sensorimotor transformations during foraging that leads to marked changes in both the motivation to hunt for prey and the accuracy of motor sequences during hunting. This work reveals an important hidden variable that shapes the temporal structure of motivation and decision-making.


  
Construction of a human cell landscape at single-cell level 期刊论文
NATURE, 2020, 581 (7808) : 303-+
作者:  Han, Yan;  Reyes, Alexis A.;  Malik, Sara;  He, Yuan
收藏  |  浏览/下载:22/0  |  提交时间:2020/07/03

Single-cell analysis is a valuable tool for dissecting cellular heterogeneity in complex systems(1). However, a comprehensive single-cell atlas has not been achieved for humans. Here we use single-cell mRNA sequencing to determine the cell-type composition of all major human organs and construct a scheme for the human cell landscape (HCL). We have uncovered a single-cell hierarchy for many tissues that have not been well characterized. We established a '  single-cell HCL analysis'  pipeline that helps to define human cell identity. Finally, we performed a single-cell comparative analysis of landscapes from human and mouse to identify conserved genetic networks. We found that stem and progenitor cells exhibit strong transcriptomic stochasticity, whereas differentiated cells are more distinct. Our results provide a useful resource for the study of human biology.


Single-cell RNA sequencing is used to generate a dataset covering all major human organs in both adult and fetal stages, enabling comparison with similar datasets for mouse tissues.


  
Gene expression and cell identity controlled by anaphase-promoting complex 期刊论文
NATURE, 2020
作者:  Filacchione, Gianrico;  Capaccioni, Fabrizio;  Ciarniello, Mauro;  Raponi, Andrea;  Rinaldi, Giovanna;  De Sanctis, Maria Cristina;  Bockelee-Morvan, Dominique;  Erard, Stephane;  Arnold, Gabriele;  Mennella, Vito;  Formisano, Michelangelo;  Longobardo, Andrea;  Mottola, Stefano
收藏  |  浏览/下载:23/0  |  提交时间:2020/07/03

Metazoan development requires the robust proliferation of progenitor cells, the identities of which are established by tightly controlled transcriptional networks(1). As gene expression is globally inhibited during mitosis, the transcriptional programs that define cell identity must be restarted in each cell cycle(2-5) but how this is accomplished is poorly understood. Here we identify a ubiquitin-dependent mechanism that integrates gene expression with cell division to preserve cell identity. We found that WDR5 and TBP, which bind active interphase promoters(6,7), recruit the anaphase-promoting complex (APC/C) to specific transcription start sites during mitosis. This allows APC/C to decorate histones with ubiquitin chains branched at Lys11 and Lys48 (K11/K48-branched ubiquitin chains) that recruit p97 (also known as VCP) and the proteasome, which ensures the rapid expression of pluripotency genes in the next cell cycle. Mitotic exit and the re-initiation of transcription are thus controlled by a single regulator (APC/C), which provides a robust mechanism for maintaining cell identity throughout cell division.


WDR5 and TBP recruit anaphase-promoting complex to specific transcription start sites in mitosis, initiating a ubiquitin-dependent mechanism that preserves cell identity by linking gene expression and cell division.


  
Classification with a disordered dopantatom network in silicon 期刊论文
NATURE, 2020, 577 (7790) : 341-+
作者:  Vagnozzi, Ronald J.;  Maillet, Marjorie;  Sargent, Michelle A.;  Khalil, Hadi;  Johansen, Anne Katrine Z.;  Schwanekamp, Jennifer A.;  York, Allen J.;  Huang, Vincent;  Nahrendorf, Matthias;  Sadayappan, Sakthivel;  Molkentin, Jeffery D.
收藏  |  浏览/下载:32/0  |  提交时间:2020/07/03

Classification is an important task at which both biological and artificial neural networks excel(1,2). In machine learning, nonlinear projection into a high-dimensional feature space can make data linearly separable(3,4), simplifying the classification of complex features. Such nonlinear projections are computationally expensive in conventional computers. A promising approach is to exploit physical materials systems that perform this nonlinear projection intrinsically, because of their high computational density(5), inherent parallelism and energy efficiency(6,7). However, existing approaches either rely on the systems'  time dynamics, which requires sequential data processing and therefore hinders parallel computation(5,6,8), or employ large materials systems that are difficult to scale up(7). Here we use a parallel, nanoscale approach inspired by filters in the brain(1) and artificial neural networks(2) to perform nonlinear classification and feature extraction. We exploit the nonlinearity of hopping conduction(9-11) through an electrically tunable network of boron dopant atoms in silicon, reconfiguring the network through artificial evolution to realize different computational functions. We first solve the canonical two-input binary classification problem, realizing all Boolean logic gates(12) up to room temperature, demonstrating nonlinear classification with the nanomaterial system. We then evolve our dopant network to realize feature filters(2) that can perform four-input binary classification on the Modified National Institute of Standards and Technology handwritten digit database. Implementation of our material-based filters substantially improves the classification accuracy over that of a linear classifier directly applied to the original data(13). Our results establish a paradigm of silicon-based electronics for smallfootprint and energy-efficient computation(14).


  
A network-based comparative study of extreme tropical and frontal storm rainfall over Japan 期刊论文
CLIMATE DYNAMICS, 2019, 53: 521-532
作者:  Ozturk, Ugur;  Malik, Nishant;  Cheung, Kevin;  Marwan, Norbert;  Kurths, Juergen
收藏  |  浏览/下载:26/0  |  提交时间:2019/11/27
Extreme rainfall  Baiu  Tropical storms  Event synchronization  Complex networks  
The 'patchy' spread of renewables: A socio-territorial perspective on the energy transition process 期刊论文
ENERGY POLICY, 2019, 129: 684-692
作者:  Carrosio, Giovanni;  Scotti, Ivano
收藏  |  浏览/下载:12/0  |  提交时间:2019/11/26
Energy transition  Heating network systems  Social networks  Technical networks  Techno-institutional complex  Wind power facilities  
Tailoring Centrality Metrics for Water Distribution Networks 期刊论文
WATER RESOURCES RESEARCH, 2019, 55 (3) : 2348-2369
作者:  Giustolisi, Orazio;  Ridolfi, Luca;  Simone, Antonietta
收藏  |  浏览/下载:22/0  |  提交时间:2019/11/26
water distribution networks  complex network theory  centrality metrics  
Predictive analytics of tree growth based on complex networks of tree competition 期刊论文
FOREST ECOLOGY AND MANAGEMENT, 2018, 425: 164-176
作者:  Mongus, Domen;  Vilhar, Ursa;  Skudnik, Mitja;  Zalik, Borut;  Jesenko, David
收藏  |  浏览/下载:13/0  |  提交时间:2019/04/09
Tree competition  Predictive analytics  Knowledge discovery  Evolutionary algorithms  Complex networks  Topology  
Forest landscapes as social-ecological systems and implications for management 期刊论文
LANDSCAPE AND URBAN PLANNING, 2018, 177: 138-147
作者:  Fischer, Alexandra Paige
收藏  |  浏览/下载:15/0  |  提交时间:2019/04/09
Social-ecological systems  Complex adaptive systems  Forests  Landscapes  Scale mismatch  Governance networks  
Temporal evolution of the spatial covariability of rainfall in South America 期刊论文
CLIMATE DYNAMICS, 2018, 51: 371-382
作者:  Ciemer, Catrin;  Boers, Niklas;  Barbosa, Henrique M. J.;  Kurths, Jurgen;  Rammig, Anja
收藏  |  浏览/下载:18/0  |  提交时间:2019/04/09
South American monsoon  Complex networks  Rainfall  Teleconnections  Correlation measures