Slow Time Scale Research Articles

Is the Madden‐Julian Oscillation a Moisture Mode?

AbstractThe governing thermodynamics of the Madden‐Julian Oscillation (MJO) is examined using sounding and reanalysis data. On the basis of four objective criteria, results suggest that the MJO behaves like a moisture mode–a system whose thermodynamics is governed by moisture–only over the Indian Ocean. Over this basin, the MJO shows a slow convective adjustment timescale, its zonal scale is smaller, and it exhibits slow propagation, allowing moisture modes to exist. Elsewhere, the faster‐propagating wavenumber 1–2 components are more prominent preventing weak temperature gradient (WTG) balance to be established. As a result, temperature and moisture play similar roles in the MJO's thermodynamics outside the Indian Ocean.

GABA tone regulation and its cognitive functions in the brain.

γ-Aminobutyric acid (GABA) is the major inhibitory neurotransmitter released at GABAergic synapses, mediating fast-acting phasic inhibition. Emerging lines of evidence unequivocally indicate that a small amount of extracellular GABA - GABA tone - exists in the brain and induces a tonic GABA current that controls neuronal activity on a slow timescale relative to that of phasic inhibition. Surprisingly, studies indicate that glial cells that synthesize GABA, such as astrocytes, release GABA through non-vesicular mechanisms, such as channel-mediated release, and thereby act as the source of GABA tone in the brain. In this Review, we first provide an overview of major advances in our understanding of the cell-specific molecular and cellular mechanisms of GABA synthesis, release and clearance that regulate GABA tone in various brain regions. We next examine the diverse ways in which the tonic GABA current regulates synaptic transmission and synaptic plasticity through extrasynaptic GABAA-receptor-mediated mechanisms. Last, we discuss the physiological mechanisms through which tonic inhibition modulates cognitive function on a slow timescale. In this Review, we emphasize that the cognitive functions of tonic GABA current extend beyond mere inhibition, laying a foundation for future research on the physiological and pathophysiological roles of GABA tone regulation in normal and abnormal psychiatric conditions.

Increased intracellular crowding during hyperosmotic stress

Hyperosmotic stress activates in live cells numerous processes and also promotes intracellular protein/RNA aggregation and phase separation. However, the time course and the extent of these changes remain largely uncharacterized. To investigate dynamic changes in intracellular macromolecular crowding (MMC) induced by hyperosmotic stress in live cells, we used fluorescence lifetime imaging microscopy and fluorescence correlation spectroscopy (FCS) to quantify changes in the local environment by measuring the fluorescence lifetime and the diffusion of the monomeric enhanced green fluorescent protein (eGFP), respectively. Real-time monitoring of eGFP fluorescence lifetime showed that a faster response to environmental changes due to MMC is observed than when measuring the acceptor/donor emission ratio using the MMC-sensitive Förster resonance energy transfer sensor (GimRET). This suggests that eGFP molecular electronic states and/or collision frequency are affected by changes in the immediate surroundings due to MMC without requiring conformational changes as is the case for the GimRET sensor. Furthermore, eGFP diffusion assessed by FCS indicated higher intracellular viscosity due to increased MMC during hyperosmotic stress. Our findings reveal that changes in eGFP fluorescence lifetime and diffusion are early indicators of elevated intracellular MMC. Our approach can therefore be used to reveal in live cells short-lived transient states through which MMC builds over time, which could not be observed when measuring changes in other physical properties that occur at slower time scales.

Structural basis of TFIIIC-dependent RNA polymerase III transcription initiation

RNA polymerase III (Pol III) is responsible for transcribing 5S ribosomal RNA (5S rRNA), tRNAs, and other short non-coding RNAs. Its recruitment to the 5S rRNA promoter requires transcription factors TFIIIA, TFIIIC, and TFIIIB. Here, we use cryoelectron microscopy (cryo-EM) to visualize the S.cerevisiae complex of TFIIIA and TFIIIC bound to the promoter. Gene-specific factor TFIIIA interacts with DNA and acts as an adaptor for TFIIIC-promoter interactions. We also visualize DNA binding of TFIIIB subunits, Brf1 and TBP (TATA-box binding protein), which results in the full-length 5S rRNA gene wrapping around the complex. Our smFRET study reveals that the DNA within the complex undergoes both sharp bending and partial dissociation on a slow timescale, consistent with the model predicted from our cryo-EM results. Our findings provide new insights into the transcription initiation complex assembly on the 5S rRNA promoter and allow us to directly compare Pol III and Pol II transcription adaptations.

Multifaceted luminance gain control beyond photoreceptors in Drosophila

Animals navigating in natural environments must handle vast changes in their sensory input. Visual systems, for example, handle changes in luminance at many timescales, from slow changes across the day to rapid changes during active behavior. To maintain luminance-invariant perception, visual systems must adapt their sensitivity to changing luminance at different timescales. We demonstrate that luminance gain control in photoreceptors alone is insufficient to explain luminance invariance at both fast and slow timescales and reveal the algorithms that adjust gain past photoreceptors in the fly eye. We combined imaging and behavioral experiments with computational modeling to show that downstream of photoreceptors, circuitry taking input from the single luminance-sensitive neuron type L3 implements gain control at fast and slow timescales. This computation is bidirectional in that it prevents the underestimation of contrasts in low luminance and overestimation in high luminance. An algorithmic model disentangles these multifaceted contributions and shows that the bidirectional gain control occurs at both timescales. The model implements a nonlinear interaction of luminance and contrast to achieve gain correction at fast timescales and a dark-sensitive channel to improve the detection of dim stimuli at slow timescales. Together, our work demonstrates how a single neuronal channel performs diverse computations to implement gain control at multiple timescales that are together important for navigation in natural environments.

0060 A Classification Based Generative Approach to Selective Targeting of Global Slow Oscillations during Sleep

Abstract Introduction Interacting with sleep slow oscillations (0.5,15 Hz) is essential to understanding the mechanisms underlying their role in sleep functions, including homeostasis, synaptic reorganization, and memory consolidation. Current approaches to SO-based non-invasive closed loop alternate current stimulation (cl-tACs) focus on timing, and do not differentiate among oscillations based on their space-time profiles. In this study, we leverage machine learning and global optimization to introduce a generative model of brain stimulation protocols targeting Global SOs. Methods We identify a stimulation protocol that matches a Global SO in two stages: first focusing on the electrode montage, and then on the stimulation waveform. Using the sleep night of 22 volunteers acquired in the lab with high density EEG (175 electrodes), we labeled the SOs as Global/non-Global SOs based on their co-detection on the scalp at a small delay (0.4s). We used the current density (CSD) profile of each SO in cortical and subcortical regions to develop a well-trained classifier (based on weighted k-nearest neighbors). We identify as optimal the electrode montage that resulted in CSDs labeled as Global with highest likelihood by the classifier. We then parameterized a sinusoidal waveform and identified optimum parameters with a genetic algorithm that used feature ranking to establish a weighted distance metric to target Global SO profile built from sleep data. We repeat this approach focusing on Global SO dynamics at a slow time scale and a faster time scale (200ms vs 20ms resolution). Results We identified optimal stimulation profiles matching Global SOs at both time scales. At slow time scale, montage selection relied only on CSD near the SO trough and in the reward network and the brainstem. Linear waveforms over-performed sinusoidal waveforms for fit at low time scales. At fast time scale, CSD at both trough and 500ms before the trough were strongly selective for Global vs. non-Global SO. Conclusion Global SOs are a gating mechanism for large-scale neural communication, a necessary substrate for systems consolidation and long-term memory formation. This data-driven method builds on natural sleep data to shape a stimulation protocol that imitates Global SO dynamics and is generalizable to other SO types. Support (if any)

Perspective: How Fast Dynamics Affect Slow Function in Protein Machines.

Internal motions in proteins take place on a broad range of time- and space-scales. The potential roles of these dynamics in the biochemical functions of proteins have intrigued biophysicists for many years, and multiple mechanisms to couple motions to function have been proposed. Some of these mechanisms have relied on equilibrium concepts. For example, the modulation of dynamics was proposed to change the entropy of a protein, hence affecting processes such as binding. This so-called dynamic allostery scenario has been demonstrated in several recent experiments. Perhaps even more intriguing may be models that involve out-of-equilibrium operation, which by necessity require the input of energy. We discuss several recent experimental studies that expose such potential mechanisms for coupling dynamics and function. In Brownian ratchets, for example, directional motion is promoted by switching a protein between two free energy surfaces. An additional example involves the effect of microsecond domain-closure dynamics of an enzyme on its much slower chemical cycle. These observations lead us to propose a novel two-time-scale paradigm for the activity of protein machines: fast equilibrium fluctuations take place on the microsecond-millisecond time scale, while on a slower time scale, free energy is invested in order to push the system out of equilibrium and drive functional transitions. Motions on the two time scales affect each other and are essential for the overall function of these machines.

Low-Mach number asymptotic analysis of fluid–structure-interaction (FSI) pressure waves inside an elastic tube

We consider the pressure wave having velocity cp inside an elastic tube of internal radius R0, thickness e, length L, shear modulus G and density ρs0, filled with a fluid with kinematic viscosity νf. We theoretically analyze the fluid–structure coupling between: (i) the elastic sheath, (ii) the fluid boundary layer, and (iii) the core acoustic pressure and velocity fields. Our analysis provides an asymptotic derivation of the fluid–structure-interactions (FSI) model that recovers known pulse-wave velocities and provides a new theoretical prediction for the exponential time decay of the wave longitudinal attenuation envelope. Taking advantage of highly distinct time-scales between the viscous radial diffusion τd=R02/νf compared with wave-convective time τc=L/cp as well as the elastic relaxation time τe=eρs/G, such that τe∼τc≪τd we perform a two time-scale asymptotic analysis based on a small parameter δ=τc/τd. Said parameter is obtained by balancing the momentum acceleration and the viscous damping rate in the inner unsteady boundary layer, the thickness of which being δR0. The resulting asymptotic sequence provides a unique consistent scaling for solid deformation and velocity fields, with the secularity condition associated with the leading-order slow-time scale envelope attenuation obtained by extending the analysis to investigate the first-order corrections.On the one hand our approach reconciles both predictions for the precursive elastic wave and the pulse velocities obtained when considering solid deformation only, and, on the other hand, predictions for the longitudinal attenuation resulting from the effect of boundary layers only. Our analysis also permits the derivation of a new convoluted model for the wall shear stress, which is (FSI)–consistent. The theoretical results are successfully compared with experimental measurements.

Selecting Features for Markov Modeling: A Case Study on HP35.

Markov state models represent a popular means to interpret molecular dynamics trajectories in terms of memoryless transitions between metastable conformational states. To provide a mechanistic understanding of the considered biomolecular process, these states should reflect structurally distinct conformations and ensure a time scale separation between fast intrastate and slow interstate dynamics. Adopting the folding of villin headpiece (HP35) as a well-established model problem, here we discuss the selection of suitable input coordinates or "features", such as backbone dihedral angles and interresidue distances. We show that dihedral angles account accurately for the structure of the native energy basin of HP35, while the unfolded region of the free energy landscape and the folding process are best described by tertiary contacts of the protein. To construct a contact-based model, we consider various ways to define and select contact distances and introduce a low-pass filtering of the feature trajectory as well as a correlation-based characterization of states. Relying on input data that faithfully account for the mechanistic origin of the studied process, the states of the resulting Markov model are clearly discriminated by the features, describe consistently the hierarchical structure of the free energy landscape, and─as a consequence─correctly reproduce the slow time scales of the process.

Timescale separation in the coordinated switching of bacterial flagellar motors

The output of the bacterial chemotaxis signaling pathway, the level of the intracellular regulator CheY-P, modulates the rotation direction of the flagellar motor, thereby regulating bacterial run-and-tumble behavior. The multiple flagellar motors on an E. coli cell are controlled by a common cytoplasmic pool of CheY-P. Fluctuation of the CheY-P level was thought to be able to coordinate the switching of multiple motors. Here, we measured the correlation of rotation directions between two motors on a cell, finding that it surprisingly exhibits two well separated timescales. We found that the slow timescale (∼6 s) can be explained by the slow fluctuation of the CheY-P level due to stochastic activity of the chemotactic adaptation enzymes, whereas the fast timescale (∼0.3 s) can be explained by the random pulse-like fluctuation of the CheY-P level, due probably to the activity of the chemoreceptor clusters. We extracted information on the properties of the fast CheY-P pulses based on the correlation measurements. The two well-separated timescales in the fluctuation of CheY-P level help to coordinate multiple motors on a cell and to enhance bacterial chemotactic performance.

Two-timescale coordinated operation of wind-advanced adiabatic compressed air energy storage system: A bilevel stochastic dynamic programming method

Renewable energy is a promising solution to address the energy crisis and environmental issues, but it comes with challenges due to its inherent volatility and limited dispatchability. Advanced adiabatic compressed air energy storage (AA-CAES) is a favorable partner for centralized renewable integration, due to its numerous benefits, such as large capacity, long lifetime, fast response capability, and zero carbon emissions. For the economic management of a wind-AACAES system, a battery-like AA-CAES dispatch model is proposed, where the charging/discharging efficiencies and capacities are dependent on the operating power and state-of-charge (SoC) to capture the part-load characteristics. A hybrid control strategy is proposed to enhance the flexibility and efficiency of the compression side under off-design conditions caused by simultaneous changes in back pressure and load. To provide dispatch and control strategies of AA-CAES, a multi-timescale optimization problem is established. The slow timescale determines the baseline output scheduling on an hourly basis to maximize total revenue, while the fast timescale updates the real-time adjustment every five minutes to minimize the penalty of tracking error. A bi-level stochastic dynamic programming (SDP) framework is formulated to incorporate the wind uncertainties and multi timescale coordination, where terminal SoCs and value functions are essential to integrate decisions across slow and fast timescales. A non-iterative parametric programming-based method is proposed to solve the slow-timescale SDP, and a simulation-based rollout algorithm is applied to extract the fast-timescale actions, which yields evident improvement over any heuristic base policy that is sequentially consistent. The numerical results demonstrate that the proposed method has a performance gap of approximately 7.1%, which outperforms the rule-based method by 32.6%. The installation of AA-CAES improves the total revenue by 11.9%. Additionally, the hybrid control strategy enhances the charging flexibility and efficiency by 30.7% and 4.3%, respectively, resulting in a 3.9% reduction in tracking deviation penalty.

Thermal-Comfort Aware Online Co-Scheduling Framework for HVAC, Battery Systems, and Appliances in Smart Buildings

Energy management in buildings is vital for reducing electricity costs and maximizing the comfort of occupants. Excess solar generation can be used by combining a battery storage system and a heating, ventilation, and air-conditioning (HVAC) system so that occupants feel comfortable. Despite several studies on the scheduling of appliances, batteries, and HVAC, comprehensive and time scalable approaches are required that integrate such predictive information as renewable generation and thermal comfort. In this paper, we propose an thermal-comfort aware online coscheduling framework that incorporates optimal energy scheduling and a prediction model of PV generation and thermal comfort with the model predictive control (MPC) approach. We introduce a photovoltaic (PV) energy nowcasting and thermal-comfort-estimation model that provides useful information for optimization. The energy management problem is formulated as three coordinated optimization problems that cover fast and slow time-scales by considering predicted information. This approach reduces the time complexity without a significant negative impact on the result's global nature and its quality. Experimental results show that our proposed framework achieves optimal energy management that takes into account the trade-off between electricity expenses and thermal comfort. Our sensitivity analysis indicates that introducing a battery significantly improves the trade-off relationship.

Deep Neural Network-Based Approximate Optimal Tracking for Unknown Nonlinear Systems

The infinite horizon optimal tracking problem is solved for a deterministic, control-affine, unknown nonlinear dynamical system. A deep neural network (DNN) is updated in real-time to approximate the unknown nonlinear system dynamics. The developed framework uses a multi-timescale concurrent learning-based weight update policy, with which the output-layer DNN weights are updated in real-time, but the internal DNN features are updated discretely and at a slower timescale (i.e., with batch-like updates). The design of the output-layer weight update policy is motivated by a Lyapunov-based analysis, and the inner features are updated according to existing DNN optimization algorithms. Simulation results demonstrate the efficacy of the developed technique and compare its performance to existing techniques.

Synchronization of inspiratory burst onset along the ventral respiratory column in the neonate mouse is mediated by electrotonic coupling

Breathing is a singularly robust behavior, yet this motor pattern is continuously modulated at slow and fast timescales to maintain blood-gas homeostasis, while intercalating orofacial behaviors. This functional multiplexing goes beyond the rhythmogenic function that is typically ascribed to medullary respiration-modulated networks and may explain lack of progress in identifying the mechanism and constituents of the respiratory rhythm generator. By recording optically along the ventral respiratory column in medulla, we found convergent evidence that rhythmogenic function is distributed over a dispersed and heterogeneous network that is synchronized by electrotonic coupling across a neuronal syncytium. First, high-speed recordings revealed that inspiratory onset occurred synchronously along the column and did not emanate from a rhythmogenic core. Second, following synaptic isolation, synchronized stationary rhythmic activity was detected along the column. This activity was attenuated following gap junction blockade and was silenced by tetrodotoxin. The layering of syncytial and synaptic coupling complicates identification of rhythmogenic mechanism, while enabling functional multiplexing.

Driving Force of the Initial Step in Electrochemical Pt(111) Oxidation

The first step of electrochemical surface oxidation is extraction of a metal atom from its lattice site to a location in a growing oxide. Here we show by fast simultaneous electrochemical and in situ high-energy surface X-ray diffraction measurements that the initial extraction of Pt atoms from Pt(111) is a fast, potential-driven process, whereas charge transfer for the related formation of adsorbed oxygen-containing species occurs on a much slower time scale and is evidently uncoupled from the extraction process. It is concluded that potential plays a key independent role in electrochemical surface oxidation.

Slow spectral diffusion of the NO stretching mode of [RuCl5(NO)]2- in D2O studied by 2D-IR spectroscopy and molecular dynamics simulations.

The vibrational dynamics of the NO stretching mode of [RuCl5(NO)]2- in D2O were investigated by nonlinear infrared (IR) spectroscopy. We performed IR pump-probe measurements to obtain the vibrational lifetime of this molecule. The lifetime is 31ps, which is sufficiently long enough to study the vibrational frequency fluctuation on a slower time scale with high precision. By two-dimensional IR spectroscopy, the frequency-frequency time correlation function (FFTCF) of the NO stretching mode was characterized with a delta function plus a double-exponential function. The time constant of the slower component was ∼10ps. We also found that the time constant does not strongly depend on temperature. In order to investigate the microscopic origin of this component, we performed classical molecular dynamics simulations. It was found that the hydration structure around the NO group was influenced by the negatively charged Cl ligands. To calculate the FFTCF decay, we employed an approximate theoretical model based on the vibrational solvatochromism theory. It was demonstrated that water fluctuations around the Cl ligands projected on the NO group correspond to the 10ps decay component in the FFTCF. The fluctuation is related to the orientational dynamics of the water molecules attracted by the Cl ligands. By comparing the FFTCF parameters of the present solute with those of previously reported metal complexes and SCN- in D2O, we conclude that the presence of different electrostatic environments around the vibrational probe and the other interaction sites of the solute is important for understanding the slow decay component in the FFTCFs.

Intrinsic timescales in the visual cortex change with selective attention and reflect spatial connectivity

Intrinsic timescales characterize dynamics of endogenous fluctuations in neural activity. Variation of intrinsic timescales across the neocortex reflects functional specialization of cortical areas, but less is known about how intrinsic timescales change during cognitive tasks. We measured intrinsic timescales of local spiking activity within columns of area V4 in male monkeys performing spatial attention tasks. The ongoing spiking activity unfolded across at least two distinct timescales, fast and slow. The slow timescale increased when monkeys attended to the receptive fields location and correlated with reaction times. By evaluating predictions of several network models, we found that spatiotemporal correlations in V4 activity were best explained by the model in which multiple timescales arise from recurrent interactions shaped by spatially arranged connectivity, and attentional modulation of timescales results from an increase in the efficacy of recurrent interactions. Our results suggest that multiple timescales may arise from the spatial connectivity in the visual cortex and flexibly change with the cognitive state due to dynamic effective interactions between neurons.

Investigating the Dominant Environmental Quenching Process in UVCANDELS/COSMOS Groups

We explore how the fraction of quenched galaxies changes in groups of galaxies with respect to the distance to the center of the group, redshift, and stellar mass to determine the dominant process of environmental quenching in 0.2 < z < 0.8 groups. We use new UV data from the UVCANDELS project in addition to existing multiband photometry to derive new galaxy physical properties of the group galaxies from the zCOSMOS 20 k group catalog. Limiting our analysis to a complete sample of log (M */M ⊙) > 10.56 group galaxies, we find that the probability of being quenched increases slowly with decreasing redshift, diverging from the stagnant field galaxy population. A corresponding analysis on how the probability of being quenched increases with time within groups suggests that the dominant environmental quenching process is characterized by slow (∼Gyr) timescales. We find a quenching time of approximately Gyr, consistent with the slow processes of strangulation and delayed-then-rapid quenching although more data are needed to confirm this result.

Adaptive global coordination of local routing policies for communication networks

We consider optimal routing of data packets in communication networks featuring time-variable flow rates and bandwidth limitations. Taking into account recent programmability developments in communication systems, we propose a two-level control scheme: routers with a programmable data plane implement local proportional control policies that forward the incoming data to different available output interfaces at line rate. The local controllers’ parameters are adapted periodically on a slower time scale by a logically centralized (software-defined) network controller running a global coordination algorithm that keeps the routing feasible and optimal with respect to a network metric, such as the average packet delay. A robust optimization approach is selected to handle traffic variations in-between global adaptation steps. The outcome is a non-convex Quadratically Constrained Quadratic Program (QCQP), for which we present an iterative solution approach that is computationally suitable for realistically-sized backbone communication networks. With simulation experiments, we demonstrate the advantages of adaptive, global routing coordination compared to fixed, globally or locally-determined policies, especially concerning packet loss.

Two-Dimensional Electronic Spectroscopy Reveals Vibrational Modes Coupled to Charge Transfer in a Julolidine-BODIPY Dyad.

Understanding charge transfer (CT) dynamics in molecular donor-acceptor (D-A) dyads can provide insight into developing efficient D-A molecules for capturing solar energy. Here, we characterize the excited-state evolution of a julolidine-BODIPY (Jul-BD) D-A system with an emissive CT state using time-resolved fluorescence, femtosecond transient absorption, and two-dimensional electronic spectroscopies. Comparison of these results with those from phenyl-BODIPY (Ph-BD) allows us to identify the dynamics at play during CT state formation and its subsequent conversion to either a fully charge-separated or triplet state. Photoexcitation of Jul-BD in tetrahydrofuran results in the formation of an initial emissive CT state that relaxes before fully charge-separating. In contrast, Jul-BD in toluene exhibits similar CT state dynamics, albeit at slower timescales, before decaying to a terminal triplet species. Quantum beat analysis at early times in both solvents shows several vibronic modes, which are corroborated using density functional theory (DFT) calculations. For Ph-BD, a single 220 cm-1 compression mode about the single bond linking the phenyl to BODIPY modulates their orbital overlap. Three active vibronic modes, 147, 174, and 214 cm-1, are found in Jul-BD, regardless of the dielectric constant of the medium. These motions correspond to compression and torsional motions along the single bond joining Jul to BD and are responsible for the evolution of the spontaneous and stimulated emission features in the time-resolved spectroscopic data, which is further supported by time-dependent DFT calculations of the steady-state absorption spectrum of the Jul-BD as a function of increasing D-A dihedral core angle. These findings show how torsional and compression motions can play a pivotal role in intramolecular CT between a D and an A linked by a single bond.