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| Open AccessA multi-demand operating system underlying diverse cognitive tasks
A consistent set of brain areas is engaged across diverse cognitive tasks. Here, the authors reveal a unifying latent brain state that predicts performance across seven tasks, linking a core control network to cognitive flexibility and adaptive behaviors.
- Weidong Cai
- , Jalil Taghia
- & Vinod Menon
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Article
| Open AccessLocal orchestration of distributed functional patterns supporting loss and restoration of consciousness in the primate brain
The brain’s role in supporting consciousness is unclear. Here, authors show that global markers of consciousness in macaque cortex are suppressed by many anaesthetics, and restored by local stimulation of a thalamic nucleus that also induces awakening.
- Andrea I. Luppi
- , Lynn Uhrig
- & Rodrigo Cofre
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Article
| Open AccessNeonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment
Neonatal brain dynamics are not well understood. Here, the authors characterise brain transient states in neonates, and show that preterm infants display altered whole brain dynamics and an atypical repertoire of regional transient states, which are associated with behavioural outcomes at 18 months of age.
- Lucas G. S. França
- , Judit Ciarrusta
- & Dafnis Batalle
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| Open AccessConnectome-based reservoir computing with the
conn2res toolboxBrain connectivity patterns shape computational capacity of biological neural networks, however mapping empirically measured connectivity to artificial networks remains challenging. The authors present a toolbox for implementing biological neural networks as artificial reservoir networks. The toolbox allows for a variety of empirical/measured connectomes and is equipped with various dynamical systems, and cognitive tasks.
- Laura E. Suárez
- , Agoston Mihalik
- & Bratislav Misic
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Article
| Open AccessCompetition and evolutionary selection among core regulatory motifs in gene expression control
Regulators represent a bioenergetic cost in gene expression control. Here, the author shows how functionally equivalent regulatory motifs have fundamentally different impacts on population structure, growth dynamics, and evolutionary outcomes.
- Andras Gyorgy
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Article
| Open AccessAutoencoder neural networks enable low dimensional structure analyses of microbial growth dynamics
Here, the authors apply autoencoder neural networks to show that microbial growth dynamics can be compressed into low-dimensional representations and reconstructed with high fidelity, facilitating quantitative predictions and deduction of potential mechanisms.
- Yasa Baig
- , Helena R. Ma
- & Lingchong You
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Article
| Open AccessInternal states as a source of subject-dependent movement variability are represented by large-scale brain networks
How internal states such as confidence and motivation influence motor performance remains unclear. Here, the authors explore brain networks associated with these internal states, finding that the Dorsal Attention Network encodes error states and the Default Network reflects perceived uncertainty.
- Macauley Smith Breault
- , Pierre Sacré
- & Sridevi V. Sarma
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Article
| Open AccessOptogenetic control of YAP reveals a dynamic communication code for stem cell fate and proliferation
The transcriptional regulator YAP controls cellular decisions such as proliferation, differentiation, and pluripotency. Here, the authors show a concentration-dependent and temporal communication code for YAP that enables cells to choose between these programs.
- Kirstin Meyer
- , Nicholas C. Lammers
- & Orion D. Weiner
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Article
| Open AccessInitial conditions combine with sensory evidence to induce decision-related dynamics in premotor cortex
It remains unclear why some decisions take longer than others even when the sensory inputs are similar. Here, the authors show that both initial neural state and sensory input combine in the premotor cortex to influence the speed and geometry of neural population activity during decisions.
- Pierre O. Boucher
- , Tian Wang
- & Chandramouli Chandrasekaran
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Article
| Open AccessCritical dynamics arise during structured information presentation within embodied in vitro neuronal networks
The conditions under which networks of neurons exhibit critical dynamics remains unclear. Here, the authors investigate how simple neural cultures reorganize activity when embodied in a gameplay environment and find that network wide neural criticality arises in nuanced ways.
- Forough Habibollahi
- , Brett J. Kagan
- & Chris French
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Article
| Open AccessSequence anticipation and spike-timing-dependent plasticity emerge from a predictive learning rule
Prediction of future inputs is a key computational task for the brain. Here, the authors proposed a predictive learning rule in neurons that leads to anticipation and recall of inputs, and that reproduces experimentally observed STDP phenomena.
- Matteo Saponati
- & Martin Vinck
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Perspective
| Open AccessToward a formal theory for computing machines made out of whatever physics offers
Learning from human brains to build powerful computers is attractive, yet extremely challenging due to the lack of a guiding computing theory. Jaeger et al. give a perspective on a bottom-up approach to engineer unconventional computing systems, which is fundamentally different to the classical theory based on Turing machines.
- Herbert Jaeger
- , Beatriz Noheda
- & Wilfred G. van der Wiel
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Article
| Open AccessBrain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data
The brain has been proposed to operate near a critical transition between order and disorder, controlled by a balance between inhibition and excitation. Here, the authors show that individual variability in long-range synchronization between brain regions can be explained by an individual’s proximity to this phase transition.
- Marco Fuscà
- , Felix Siebenhühner
- & Satu Palva
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Article
| Open AccessThe default network dominates neural responses to evolving movie stories
How brain networks process dynamic naturalistic stimuli is not well understood. Here, the authors use machine learning algorithms to show that brain states in the default network capture the semantic aspects of an unfolding narrative during movie watching.
- Enning Yang
- , Filip Milisav
- & Danilo Bzdok
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Article
| Open AccessLearning perturbation-inducible cell states from observability analysis of transcriptome dynamics
A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, the authors develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery of analyte-responsive promoters.
- Aqib Hasnain
- , Shara Balakrishnan
- & Enoch Yeung
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Article
| Open AccessStress-induced metabolic exchanges between complementary bacterial types underly a dynamic mechanism of inter-species stress resistance
Microbes can cooperate and share resources via metabolic cross-feeding. Here, the authors show that excretion of key metabolites following acid stress provides a collaborative, inter-species mechanism of stress resistance.
- Kapil Amarnath
- , Avaneesh V. Narla
- & Terence Hwa
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Article
| Open AccessLearning how network structure shapes decision-making for bio-inspired computing
Better understanding of a trade-off between the speed and accuracy of decision-making is relevant for mapping biological intelligence to machines. The authors introduce a brain-inspired learning algorithm to uncover dependencies in individual fMRI networks with features of neural activity and predict inter-individual differences in decision-making.
- Michael Schirner
- , Gustavo Deco
- & Petra Ritter
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Article
| Open AccessDistributing task-related neural activity across a cortical network through task-independent connections
Large scale neural recordings show that task-related activity is observed across neural circuits. Here, the authors have identified a network mechanism that promotes distributed activity in the cortex during decision-making via task-independent synapses.
- Christopher M. Kim
- , Arseny Finkelstein
- & Ran Darshan
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Article
| Open AccessComplexity of cortical wave patterns of the wake mouse cortex
The cerebral cortex has ongoing electrical activities with rich and complex patterns in space and time. Here, the authors use optical voltage imaging in mice and computational methods, relating these complexities to different levels of wakefulness.
- Yuqi Liang
- , Junhao Liang
- & Changsong Zhou
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Article
| Open AccessOptogenetic stimulation of anterior insular cortex neurons in male rats reveals causal mechanisms underlying suppression of the default mode network by the salience network
The salience network has been hypothesised to modulate default mode network activity during stimulus-driven cognition. Here, the authors show that in rats, stimulation of the anterior insular cortex, a key node of the salience network, suppresses the default mode network and decouples these networks, providing in vivo evidence of a causal role of the anterior insular cortex in brain network switching.
- Vinod Menon
- , Domenic Cerri
- & Yen-Yu Ian Shih
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Article
| Open AccessIntrinsic macroscale oscillatory modes driving long range functional connectivity in female rat brains detected by ultrafast fMRI
The mechanisms which generate fMRI signal correlations across the brain are not fully understood. Here, the authors record ultrafast fMRI signals in anesthetized female rats to demonstrate intrinsic macroscale oscillatory modes which drive correlated activity between distant regions.
- Joana Cabral
- , Francisca F. Fernandes
- & Noam Shemesh
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Article
| Open AccessChoice selective inhibition drives stability and competition in decision circuits
In decision circuits, inhibitory neurons signal animal choices. Here, the authors show that choice-selective inhibition can stabilize the circuit dynamics or promote competition depending on inhibitory output connections, affecting choice behavior.
- James P. Roach
- , Anne K. Churchland
- & Tatiana A. Engel
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Article
| Open AccessIntrinsic brain dynamics in the Default Mode Network predict involuntary fluctuations of visual awareness
The default mode network (DMN) is known to be involved in consciousness. Here the authors show intrinsic EEG oscillations in default mode network can predict upcoming involuntarily perceptual transitions.
- Dian Lyu
- , Shruti Naik
- & Emmanuel A. Stamatakis
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Article
| Open AccessLayered feedback control overcomes performance trade-off in synthetic biomolecular networks
Layered feedback is an optimization strategy in feedback control designs widely used in engineering. Here, combining simulation and experimentation, the authors apply layered control - a powerful optimization strategy in engineering - to synthetic biomolecular networks in living bacteria to show layered control overcomes performance trade-offs in biology.
- Chelsea Y. Hu
- & Richard M. Murray
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Article
| Open AccessHuman acute inflammatory recovery is defined by co-regulatory dynamics of white blood cell and platelet populations
Inflammation is a protective response of the body. Here, authors show that healthy inflammation induces remarkably consistent changes in white cell and platelet populations, regardless of the underlying cause, including heart attack, infection and trauma.
- Brody H. Foy
- , Thoralf M. Sundt
- & John M. Higgins
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Article
| Open AccessModelling the medium-term dynamics of SARS-CoV-2 transmission in England in the Omicron era
This mathematical modelling study projects the dynamics of SARS-CoV-2 in England until the end of 2022 assuming that the Omicron BA.2 sublineage remains dominant. They show that booster vaccination was highly effective in mitigating severe outcomes and that future dynamics will depend greatly on assumptions about waning immunity.
- Rosanna C. Barnard
- , Nicholas G. Davies
- & W. John Edmunds
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Article
| Open AccessFractional neural sampling as a theory of spatiotemporal probabilistic computations in neural circuits
Dynamics of neural circuits mapping brain functions such as sensory processing and decision making, can be characterized by probabilistic representations and inference. The authors elaborate the role of spatiotemporal neural dynamics for more efficient performance of probabilistic computations.
- Yang Qi
- & Pulin Gong
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Article
| Open AccessTemperature elevations can induce switches to homoclinic action potentials that alter neural encoding and synchronization
The intrinsic dynamics of neurons, in particular the generation action potentials, can impact neural network states and processes of encoding information. The authors demonstrate how the elevation of temperature induces a type of action potential dynamics that favors synchronization patterns in neural networks.
- Janina Hesse
- , Jan-Hendrik Schleimer
- & Susanne Schreiber
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Article
| Open AccessThe neural coding framework for learning generative models
Brain-inspired neural generative models can be designed to learn complex probability distributions from data. Here the authors propose a neural generative computational framework, inspired by the theory of predictive processing in the brain, that facilitates parallel computing for complex tasks.
- Alexander Ororbia
- & Daniel Kifer
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Article
| Open AccessAngular and linear speed cells in the parahippocampal circuits
It remains unclear how the hippocampal region integrates position and self-motion information to update spatial representations. Here, the authors report grid and head direction cells as well as cells encoding self-motion parameters such as angular head velocity and speed, and find conjunctive representations of these different parameters.
- Davide Spalla
- , Alessandro Treves
- & Charlotte N. Boccara
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Article
| Open AccessFocal neural perturbations reshape low-dimensional trajectories of brain activity supporting cognitive performance
The study of the brain’s low-dimensional topology enables the dynamic tracking of changes in neural activity. Here authors show how the reshaping of low-dimensional trajectories of brain activity sustain cognition following focal neural perturbations.
- Kartik K. Iyer
- , Kai Hwang
- & Luca Cocchi
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Article
| Open AccessLong-term priors influence visual perception through recruitment of long-range feedback
Priors learnt from lifetime experiences influence perception. The authors show that when perception is congruent with a long-term prior, there is increased top-down input in the ventral visual stream, whereas bottom-up input is enhanced when perception is incongruent with prior.
- Richard Hardstone
- , Michael Zhu
- & Biyu J. He
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Article
| Open AccessA frequency-amplitude coordinator and its optimal energy consumption for biological oscillators
Calibrating both anomalous frequency and amplitude of biorhythm prevents physiological dysfunctions or diseases. Here, the authors propose a universal approach to design a frequency-amplitude coordinator rigorously via dynamical systems tools.
- Bo-Wei Qin
- , Lei Zhao
- & Wei Lin
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Article
| Open AccessDissecting transition cells from single-cell transcriptome data through multiscale stochastic dynamics
How to infer transient cells and cell-fate transitions from snap-shot single cell transcriptome dataset remains a major challenge. Here the authors present a multiscale approach to construct single-cell dynamical manifold, quantify cell stability, and compute transition trajectory and probability between cell states.
- Peijie Zhou
- , Shuxiong Wang
- & Qing Nie
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Article
| Open AccessSpatial localisation meets biomolecular networks
Complex biomolecular networks are fundamental to the functioning of living systems, both at the cellular level and beyond. In this paper, the authors develop a systems framework to elucidate the interplay of networks and the spatial localisation of network components.
- Govind Menon
- & J. Krishnan
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Article
| Open AccessLongitudinal analysis of blood markers reveals progressive loss of resilience and predicts human lifespan limit
Aging is associated with an increased risk of chronic diseases and functional decline. Here, the authors investigate the fluctuations of physiological indices along aging trajectories and observed a characteristic decrease in the organism state recovery rate.
- Timothy V. Pyrkov
- , Konstantin Avchaciov
- & Peter O. Fedichev
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Article
| Open AccessClone-structured graph representations enable flexible learning and vicarious evaluation of cognitive maps
Higher-order sequence learning using a structured graph representation - clone-structured cognitive graphs (CSCG) – can explain how the hippocampus learns cognitive maps. CSCG provides novel explanations for transferable schemas and transitive inference in the hippocampus, and for how place cells, splitter cells, lap-cells and a variety of phenomena emerge from the same set of fundamental principles.
- Dileep George
- , Rajeev V. Rikhye
- & Miguel Lázaro-Gredilla
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Article
| Open AccessNeuroimaging evidence for a network sampling theory of individual differences in human intelligence test performance
A defining human characteristic is the ability to perform diverse cognitively challenging tasks. The authors show that this adaptability relates to a network sampling mechanism, where brain-wide network states transiently blend the unique combinations of neural resources required by different tasks.
- Eyal Soreq
- , Ines R. Violante
- & Adam Hampshire
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Article
| Open AccessA self-organized synthetic morphogenic liposome responds with shape changes to local light cues
The authors generated a Synthetic Morphogenic Membrane System by encapsulating a dynamic microtubule aster and a light-inducible signaling system driven by GTP/ATP chemical potential into cell-sized liposomes. This reconstitution of artificial proto-cells reveals how non-equilibrium phenomena affect cellular information processing in morphogenesis.
- Konstantin Gavriljuk
- , Bruno Scocozza
- & Philippe I. H. Bastiaens
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Article
| Open AccessPredictive learning as a network mechanism for extracting low-dimensional latent space representations
Neural networks trained using predictive models generate representations that recover the underlying low-dimensional latent structure in the data. Here, the authors demonstrate that a network trained on a spatial navigation task generates place-related neural activations similar to those observed in the hippocampus and show that these are related to the latent structure.
- Stefano Recanatesi
- , Matthew Farrell
- & Eric Shea-Brown
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Article
| Open AccessMultiscale low-dimensional motor cortical state dynamics predict naturalistic reach-and-grasp behavior
Motor control involves neural dynamics at multiple spatiotemporal scales. Here the authors show that a multiscale, low-dimensional dynamical structure that is shared between scales and subjects reflects naturalistic reach-and-grasp movements in macaques.
- Hamidreza Abbaspourazad
- , Mahdi Choudhury
- & Maryam M. Shanechi
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Article
| Open AccessExploring the effect of network topology, mRNA and protein dynamics on gene regulatory network stability
Maintaining protein expression levels is essential to cellular homeostasis. Here, the authors investigate how transcription factors affect the stability of protein expression in a gene regulatory network, and highlight the importance of network topology.
- Yipei Guo
- & Ariel Amir
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Article
| Open AccessDiffuse neural coupling mediates complex network dynamics through the formation of quasi-critical brain states
A principle of neuroanatomy, namely diffuse connectivity, is modeled using a large-scale network of corticothalamic neural masses. We demonstrate that increases in diffuse coupling transition the system through a quasi-critical regime, which coincides with known signatures of complex adaptive brain dynamics, and model fits to human imaging data orient task states to higher levels of diffusivity, consistent with the influence of arousal systems.
- Eli J. Müller
- , Brandon R. Munn
- & James M. Shine
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Article
| Open AccessIntegration of time-series meta-omics data reveals how microbial ecosystems respond to disturbance
Herold et al. present an integrated meta-omics framework to investigate how mixed microbial communities, such as oleaginous bacterial populations in biological wastewater treatment plants, respond with distinct adaptation strategies to disturbances. They show that community resistance and resilience are a function of phenotypic plasticity and niche complementarity.
- Malte Herold
- , Susana Martínez Arbas
- & Paul Wilmes
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Article
| Open AccessMovie viewing elicits rich and reliable brain state dynamics
The transition from resting to perceiving one’s milieu requires a fundamental reorganization of brain activity. Here, the authors show how a fundamental reshaping of brain state dynamics supports perceptual engagement in naturalistic stimuli.
- Johan N. van der Meer
- , Michael Breakspear
- & Luca Cocchi
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Article
| Open AccessReconciling qualitative, abstract, and scalable modeling of biological networks
Boolean Networks are a well-established model of biological networks, but usual interpretations can preclude the prediction of behaviours observed in quantitative systems. The authors introduce Most Permissive Boolean Networks, which are shown not to miss any behaviour achievable by the corresponding quantitative model.
- Loïc Paulevé
- , Juri Kolčák
- & Stefan Haar
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Article
| Open AccessA neural circuit model for human sensorimotor timing
We can flexibly coordinate our movements with external stimuli, but no circuit-level model exists to explain this ability. Inspired by fundamental concepts in control theory, the authors construct a modular neural circuit that captures human behavior in a wide range of temporal coordination tasks.
- Seth W. Egger
- , Nhat M. Le
- & Mehrdad Jazayeri
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Article
| Open AccessGene regulatory network inference from sparsely sampled noisy data
Gene regulatory network inference is a topical problem in systems biology. Here, the authors presents BINGO, a powerful method for network inference from time series data.
- Atte Aalto
- , Lauri Viitasaari
- & Jorge Gonçalves
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Article
| Open AccessControl of criticality and computation in spiking neuromorphic networks with plasticity
Designing efficient artificial networks able to quickly converge to optimal performance for a given task remains a challenge. Here, the authors demonstrate a relation between criticality, task-performance and information theoretic fingerprint in a spiking neuromorphic network with synaptic plasticity.
- Benjamin Cramer
- , David Stöckel
- & Viola Priesemann