Coordinating brain-distributed network activities in memory resistant to extinction.

Certain memories resist extinction to continue invigorating maladaptive actions. The robustness of these memories could depend on their widely distributed implementation across populations of neurons in multiple brain regions. However, how dispersed neuronal activities are collectively organized to underpin a persistent memory-guided behavior remains unknown. To investigate this, we simultaneously monitored the prefrontal cortex, nucleus accumbens, amygdala, hippocampus, and ventral tegmental area (VTA) of the mouse brain from initial recall to post-extinction renewal of a memory involving cocaine experience. We uncover a higher-order pattern of short-lived beta-frequency (15-25 Hz) activities that are transiently coordinated across these networks during memory retrieval. The output of a divergent pathway from upstream VTA glutamatergic neurons, paced by a slower (4-Hz) oscillation, actuates this multi-network beta-band coactivation; its closed-loop phase-informed suppression prevents renewal of cocaine-biased behavior. Binding brain-distributed neural activities in this temporally structured manner may constitute an organizational principle of robust memory expression.

A programmable reaction-diffusion system for spatiotemporal cell signaling circuit design.

Cells self-organize molecules in space and time to generate complex behaviors, but we lack synthetic strategies for engineering spatiotemporal signaling. We present a programmable reaction-diffusion platform for designing protein oscillations, patterns, and circuits in mammalian cells using two bacterial proteins, MinD and MinE (MinDE). MinDE circuits act like "single-cell radios," emitting frequency-barcoded fluorescence signals that can be spectrally isolated and analyzed using digital signal processing tools. We define how to genetically program these signals and connect their spatiotemporal dynamics to cell biology using engineerable protein-protein interactions. This enabled us to construct sensitive reporter circuits that broadcast endogenous cell signaling dynamics on a frequency-barcoded imaging channel and to build control signal circuits that synthetically pattern activities in the cell, such as protein condensate assembly and actin filamentation. Our work establishes a paradigm for visualizing, probing, and engineering cellular activities at length and timescales critical for biological function.

Enhanced DNA repair through droplet formation and p53 oscillations.

Living organisms are constantly exposed to DNA damage, and optimal repair is therefore crucial. A characteristic hallmark of the response is the formation of sub-compartments around the site of damage, known as foci. Following multiple DNA breaks, the transcription factor p53 exhibits oscillations in its nuclear concentration, but how this dynamics can affect the repair remains unknown. Here, we formulate a theory for foci formation through droplet condensation and discover how oscillations in p53, with its specific periodicity and amplitude, optimize the repair process by preventing Ostwald ripening and distributing protein material in space and time. Based on the theory predictions, we reveal experimentally that the oscillatory dynamics of p53 does enhance the repair efficiency. These results connect the dynamical signaling of p53 with the microscopic repair process and create a new paradigm for the interplay of complex dynamics and phase transitions in biology.

Phase precession in the human hippocampus and entorhinal cortex.

Knowing where we are, where we have been, and where we are going is critical to many behaviors, including navigation and memory. One potential neuronal mechanism underlying this ability is phase precession, in which spatially tuned neurons represent sequences of positions by activating at progressively earlier phases of local network theta oscillations. Based on studies in rodents, researchers have hypothesized that phase precession may be a general neural pattern for representing sequential events for learning and memory. By recording human single-neuron activity during spatial navigation, we show that spatially tuned neurons in the human hippocampus and entorhinal cortex exhibit phase precession. Furthermore, beyond the neural representation of locations, we show evidence for phase precession related to specific goal states. Our findings thus extend theta phase precession to humans and suggest that this phenomenon has a broad functional role for the neural representation of both spatial and non-spatial information.

Mechanochemical Principles of Spatial and Temporal Patterns in Cells and Tissues.

Patterns are ubiquitous in living systems and underlie the dynamic organization of cells, tissues, and embryos. Mathematical frameworks have been devised to account for the self-organization of biological patterns, most famously the Turing framework. Patterns can be defined in space, for example, to form stripes; in time, such as during oscillations; or both, to form traveling waves. The formation of these patterns can have different origins: purely chemical, purely mechanical, or a combination of the two. Beyond the variety of molecular implementations of such patterns, we emphasize the unitary principles associated with them, across scales in space and time, within a general mechanochemical framework. We illustrate where such mechanisms of pattern formation arise in biological systems from cellular to tissue scales, with an emphasis on morphogenesis. Our goal is to convey a picture of pattern formation that draws attention to the principles rather than solely to specific molecular mechanisms.

Dynamics and Spatial Genomics of the Nascent Transcriptome by Intron seqFISH.

Visualization of the transcriptome and the nuclear organization in situ has been challenging for single-cell analysis. Here, we demonstrate a multiplexed single-molecule in situ method, intron seqFISH, that allows imaging of 10,421 genes at their nascent transcription active sites in single cells, followed by mRNA and lncRNA seqFISH and immunofluorescence. This nascent transcriptome-profiling method can identify different cell types and states with mouse embryonic stem cells and fibroblasts. The nascent sites of RNA synthesis tend to be localized on the surfaces of chromosome territories, and their organization in individual cells is highly variable. Surprisingly, the global nascent transcription oscillated asynchronously in individual cells with a period of 2 hr in mouse embryonic stem cells, as well as in fibroblasts. Together, spatial genomics of the nascent transcriptome by intron seqFISH reveals nuclear organizational principles and fast dynamics in single cells that are otherwise obscured.

Brain-wide Electrical Spatiotemporal Dynamics Encode Depression Vulnerability.

Brain-wide fluctuations in local field potential oscillations reflect emergent network-level signals that mediate behavior. Cracking the code whereby these oscillations coordinate in time and space (spatiotemporal dynamics) to represent complex behaviors would provide fundamental insights into how the brain signals emotional pathology. Using machine learning, we discover a spatiotemporal dynamic network that predicts the emergence of major depressive disorder (MDD)-related behavioral dysfunction in mice subjected to chronic social defeat stress. Activity patterns in this network originate in prefrontal cortex and ventral striatum, relay through amygdala and ventral tegmental area, and converge in ventral hippocampus. This network is increased by acute threat, and it is also enhanced in three independent models of MDD vulnerability. Finally, we demonstrate that this vulnerability network is biologically distinct from the networks that encode dysfunction after stress. Thus, these findings reveal a convergent mechanism through which MDD vulnerability is mediated in the brain.

Modulation of Phase Shift between Wnt and Notch Signaling Oscillations Controls Mesoderm Segmentation.

How signaling dynamics encode information is a central question in biology. During vertebrate development, dynamic Notch signaling oscillations control segmentation of the presomitic mesoderm (PSM). In mouse embryos, this molecular clock comprises signaling oscillations of several pathways, i.e., Notch, Wnt, and FGF signaling. Here, we directly address the role of the relative timing between Wnt and Notch signaling oscillations during PSM patterning. To this end, we developed a new experimental strategy using microfluidics-based entrainment that enables specific control of the rhythm of segmentation clock oscillations. Using this approach, we find that Wnt and Notch signaling are coupled at the level of their oscillation dynamics. Furthermore, we provide functional evidence that the oscillation phase shift between Wnt and Notch signaling is critical for PSM segmentation. Our work hence reveals that dynamic signaling, i.e., the relative timing between oscillatory signals, encodes essential information during multicellular development.

Excitable Dynamics and Yap-Dependent Mechanical Cues Drive the Segmentation Clock.

The periodic segmentation of the vertebrate body axis into somites, and later vertebrae, relies on a genetic oscillator (the segmentation clock) driving the rhythmic activity of signaling pathways in the presomitic mesoderm (PSM). To understand whether oscillations are an intrinsic property of individual cells or represent a population-level phenomenon, we established culture conditions for stable oscillations at the cellular level. This system was used to demonstrate that oscillations are a collective property of PSM cells that can be actively triggered in vitro by a dynamical quorum sensing signal involving Yap and Notch signaling. Manipulation of Yap-dependent mechanical cues is sufficient to predictably switch isolated PSM cells from a quiescent to an oscillatory state in vitro, a behavior reminiscent of excitability in other systems. Together, our work argues that the segmentation clock behaves as an excitable system, introducing a broader paradigm to study such dynamics in vertebrate morphogenesis.

Excitable Signal Transduction Networks in Directed Cell Migration.

Although directed migration of eukaryotic cells may have evolved to escape nutrient depletion, it has been adopted for an extensive range of physiological events during development and in the adult organism. The subversion of these movements results in disease, such as cancer. Mechanisms of propulsion and sensing are extremely diverse, but most eukaryotic cells move by extending actin-filled protrusions termed macropinosomes, pseudopodia, or lamellipodia or by extension of blebs. In addition to motility, directed migration involves polarity and directional sensing. The hundreds of gene products involved in these processes are organized into networks of parallel and interconnected pathways. Many of these components are activated or inhibited coordinately with stimulation and on each spontaneously extended protrusion. Moreover, these networks display hallmarks of excitability, including all-or-nothing responsiveness and wave propagation. Cellular protrusions result from signal transduction waves that propagate outwardly from an origin and drive cytoskeletal activity. The range of the propagating waves and hence the size of the protrusions can be altered by lowering or raising the threshold for network activation, with larger and wider protrusions favoring gliding or oscillatory behavior over amoeboid migration. Here, we evaluate the variety of models of excitable networks controlling directed migration and outline critical tests. We also discuss the utility of this emerging view in producing cell migration and in integrating the various extrinsic cues that direct migration.

NALCN-mediated sodium influx confers metastatic prostate cancer cell invasiveness.

There is growing evidence that ion channels are critically involved in cancer cell invasiveness and metastasis. However, the molecular mechanisms of ion signaling promoting cancer behavior are poorly understood and the complexity of the underlying remodeling during metastasis remains to be explored. Here, using a variety of in vitro and in vivo techniques, we show that metastatic prostate cancer cells acquire a specific Na+ /Ca2+ signature required for persistent invasion. We identify the Na+ leak channel, NALCN, which is overexpressed in metastatic prostate cancer, as a major initiator and regulator of Ca2+ oscillations required for invadopodia formation. Indeed, NALCN-mediated Na+ influx into cancer cells maintains intracellular Ca2+ oscillations via a specific chain of ion transport proteins including plasmalemmal and mitochondrial Na+ /Ca2+ exchangers, SERCA and store-operated channels. This signaling cascade promotes activity of the NACLN-colocalized proto-oncogene Src kinase, actin remodeling and secretion of proteolytic enzymes, thus increasing cancer cell invasive potential and metastatic lesions in vivo. Overall, our findings provide new insights into an ion signaling pathway specific for metastatic cells where NALCN acts as persistent invasion controller.

Cell coupling compensates for changes in single-cell Her6 dynamics and provides phenotypic robustness.

This paper investigates the effect of altering the protein expression dynamics of the bHLH transcription factor Her6 at the single-cell level in the embryonic zebrafish telencephalon. Using a homozygote endogenous Her6:Venus reporter and 4D single-cell tracking, we show that Her6 oscillates in neural telencephalic progenitors and that the fusion of protein destabilisation (PEST) domain alters its expression dynamics, causing most cells to downregulate Her6 prematurely. However, counterintuitively, oscillatory cells increase, with some expressing Her6 at high levels, resulting in increased heterogeneity of Her6 expression in the population. These tissue-level changes appear to be an emergent property of coupling between single-cells, as revealed by experimentally disrupting Notch signalling and by computationally modelling alterations in Her6 protein stability. Despite the profound differences in the single-cell Her6 dynamics, the size of the telencephalon is only transiently altered and differentiation markers do not exhibit significant differences early on; however, a small increase is observed at later developmental stages. Our study suggests that cell coupling provides a compensation strategy, whereby an almost normal phenotype is maintained even though single-cell gene expression dynamics are abnormal, granting phenotypic robustness.

Ketamine can produce oscillatory dynamics by engaging mechanisms dependent on the kinetics of NMDA receptors.

Ketamine is an N-methyl-D-aspartate (NMDA)-receptor antagonist that produces sedation, analgesia, and dissociation at low doses and profound unconsciousness with antinociception at high doses. At high and low doses, ketamine can generate gamma oscillations (>25 Hz) in the electroencephalogram (EEG). The gamma oscillations are interrupted by slow-delta oscillations (0.1 to 4 Hz) at high doses. Ketamine's primary molecular targets and its oscillatory dynamics have been characterized. However, how the actions of ketamine at the subcellular level give rise to the oscillatory dynamics observed at the network level remains unknown. By developing a biophysical model of cortical circuits, we demonstrate how NMDA-receptor antagonism by ketamine can produce the oscillatory dynamics observed in human EEG recordings and nonhuman primate local field potential recordings. We have identified how impaired NMDA-receptor kinetics can cause disinhibition in neuronal circuits and how a disinhibited interaction between NMDA-receptor-mediated excitation and GABA-receptor-mediated inhibition can produce gamma oscillations at high and low doses, and slow-delta oscillations at high doses. Our work uncovers general mechanisms for generating oscillatory brain dynamics that differs from ones previously reported and provides important insights into ketamine's mechanisms of action as an anesthetic and as a therapy for treatment-resistant depression.

Dynamic brain communication underwriting face pareidolia.

Face pareidolia is a tendency to seeing faces in nonface images that reflects high tuning to a face scheme. Yet, studies of the brain networks underwriting face pareidolia are scarce. Here, we examined the time course and dynamic topography of gamma oscillatory neuromagnetic activity while administering a task with nonface images resembling a face. Images were presented either with canonical orientation or with display inversion that heavily impedes face pareidolia. At early processing stages, the peaks in gamma activity (40 to 45 Hz) to images either triggering or not face pareidolia originate mainly from the right medioventral and lateral occipital cortices, rostral and caudal cuneus gyri, and medial superior occipital gyrus. Yet, the difference occurred at later processing stages in the high-frequency range of 80 to 85 Hz over a set of the areas constituting the social brain. The findings speak rather for a relatively late neural network playing a key role in face pareidolia. Strikingly, a cutting-edge analysis of brain connectivity unfolding over time reveals mutual feedforward and feedback intra- and interhemispheric communication not only within the social brain but also within the extended large-scale network of down- and upstream regions. In particular, the superior temporal sulcus and insula strongly engage in communication with other brain regions either as signal transmitters or recipients throughout the whole processing of face-pareidolia images.

Bloch oscillations, Landau-Zener transition, and topological phase evolution in an array of coupled pendula.

We experimentally and theoretically study the dynamics of a one-dimensional array of pendula with a mild spatial gradient in their self-frequency and where neighboring pendula are connected with weak and alternating coupling. We map their dynamics to the topological Su-Schrieffer-Heeger model of charged quantum particles on a lattice with alternating hopping rates in an external electric field. By directly tracking the dynamics of a wave-packet in the bulk of the lattice, we observe Bloch oscillations, Landau-Zener transitions, and coupling between the isospin (i.e., the inner wave function distribution within the unit cell) and the spatial degrees of freedom (the distribution between unit cells). We then use Bloch oscillations in the bulk to directly measure the nontrivial global topological phase winding and local geometric phase of the band. We measure an overall evolution of 3.1 [Formula: see text] 0.2 radians for the geometrical phase during the Bloch period, consistent with the expected Zak phase of [Formula: see text]. Our results demonstrate the power of classical analogs of quantum models to directly observe the topological properties of the band structure and shed light on the similarities and the differences between quantum and classical topological effects.

Phase-dependent word perception emerges from region-specific sensitivity to the statistics of language.

Neural oscillations reflect fluctuations in excitability, which biases the percept of ambiguous sensory input. Why this bias occurs is still not fully understood. We hypothesized that neural populations representing likely events are more sensitive, and thereby become active on earlier oscillatory phases, when the ensemble itself is less excitable. Perception of ambiguous input presented during less-excitable phases should therefore be biased toward frequent or predictable stimuli that have lower activation thresholds. Here, we show such a frequency bias in spoken word recognition using psychophysics, magnetoencephalography (MEG), and computational modelling. With MEG, we found a double dissociation, where the phase of oscillations in the superior temporal gyrus and medial temporal gyrus biased word-identification behavior based on phoneme and lexical frequencies, respectively. This finding was reproduced in a computational model. These results demonstrate that oscillations provide a temporal ordering of neural activity based on the sensitivity of separable neural populations.

Dynamic electrical synapses rewire brain networks for persistent oscillations and epileptogenesis.

One of the very fundamental attributes for telencephalic neural computation in mammals involves network activities oscillating beyond the initial trigger. The continuing and automated processing of transient inputs shall constitute the basis of cognition and intelligence but may lead to neuropsychiatric disorders such as epileptic seizures if carried so far as to engross part of or the whole telencephalic system. From a conventional view of the basic design of the telencephalic local circuitry, the GABAergic interneurons (INs) and glutamatergic pyramidal neurons (PNs) make negative feedback loops which would regulate the neural activities back to the original state. The drive for the most intriguing self-perpetuating telencephalic activities, then, has not been posed and characterized. We found activity-dependent deployment and delineated functional consequences of the electrical synapses directly linking INs and PNs in the amygdala, a prototypical telencephalic circuitry. These electrical synapses endow INs dual (a faster excitatory and a slower inhibitory) actions on PNs, providing a network-intrinsic excitatory drive that fuels the IN-PN interconnected circuitries and enables persistent oscillations with preservation of GABAergic negative feedback. Moreover, the entities of electrical synapses between INs and PNs are engaged in and disengaged from functioning in a highly dynamic way according to neural activities, which then determine the spatiotemporal scale of recruited oscillating networks. This study uncovers a special wide-range and context-dependent plasticity for wiring/rewiring of brain networks. Epileptogenesis or a wide spectrum of clinical disorders may ensue, however, from different scales of pathological extension of this unique form of telencephalic plasticity.

Quantum interference in superposed lattices.

Charge transport in solids at low temperature reveals a material's mesoscopic properties and structure. Under a magnetic field, Shubnikov-de Haas (SdH) oscillations inform complex quantum transport phenomena that are not limited by the ground state characteristics and have facilitated extensive explorations of quantum and topological interest in two- and three-dimensional materials. Here, in elemental metal Cr with two incommensurately superposed lattices of ions and a spin-density-wave ground state, we reveal that the phases of several low-frequency SdH oscillations in [Formula: see text] and [Formula: see text] are no longer identical but opposite. These relationships contrast with the SdH oscillations from normal cyclotron orbits that maintain identical phases between [Formula: see text] and [Formula: see text] . We trace the origin of the low-frequency SdH oscillations to quantum interference effects arising from the incommensurate orbits of Cr's superposed reciprocal lattices and explain the observed [Formula: see text]-phase shift by the reconnection of anisotropic joint open and closed orbits.

Large Fermi surface in pristine kagome metal CsV3Sb5 and enhanced quasiparticle effective masses.

The kagome metal CsV[Formula: see text]Sb[Formula: see text] is an ideal platform to study the interplay between topology and electron correlation. To understand the fermiology of CsV[Formula: see text]Sb[Formula: see text], intensive quantum oscillation (QO) studies at ambient pressure have been conducted. However, due to the Fermi surface reconstruction by the complicated charge density wave (CDW) order, the QO spectrum is exceedingly complex, hindering a complete understanding of the fermiology. Here, we directly map the Fermi surface of the pristine CsV[Formula: see text]Sb[Formula: see text] by measuring Shubnikov-de Haas QOs up to 29 T under pressure, where the CDW order is completely suppressed. The QO spectrum of the pristine CsV[Formula: see text]Sb[Formula: see text] is significantly simpler than the one in the CDW phase, and the detected oscillation frequencies agree well with our density functional theory calculations. In particular, a frequency as large as 8,200 T is detected. Pressure-dependent QO studies further reveal a weak but noticeable enhancement of the quasiparticle effective masses on approaching the critical pressure where the CDW order disappears, hinting at the presence of quantum fluctuations. Our high-pressure QO results reveal the large, unreconstructed Fermi surface of CsV[Formula: see text]Sb[Formula: see text], paving the way to understanding the parent state of this intriguing metal in which the electrons can be organized into different ordered states.

What Happens with the Circuit in Alzheimer's Disease in Mice and Humans?

A major mystery of many types of neurological and psychiatric disorders, such as Alzheimer's disease (AD), remains the underlying, disease-specific neuronal damage. Because of the strong interconnectivity of neurons in the brain, neuronal dysfunction necessarily disrupts neuronal circuits. In this article, we review evidence for the disruption of large-scale networks from imaging studies of humans and relate it to studies of cellular dysfunction in mouse models of AD. The emerging picture is that some forms of early network dysfunctions can be explained by excessively increased levels of neuronal activity. The notion of such neuronal hyperactivity receives strong support from in vivo and in vitro cellular imaging and electrophysiological recordings in the mouse, which provide mechanistic insights underlying the change in neuronal excitability. Overall, some key aspects of AD-related neuronal dysfunctions in humans and mice are strikingly similar and support the continuation of such a translational strategy.