A spatial model of the plant circadian clock reveals design principles for coordinated timing

Individual plant cells possess a genetic network, the circadian clock, that times internal processes to the day‐night cycle. Mathematical models of the clock are typically either “whole‐plant” that ignore tissue or cell type‐specific clock behavior, or “phase‐only” that do not include molecular components. To address the complex spatial coordination observed in experiments, here we implemented a clock network model on a template of a seedling. In our model, the sensitivity to light varies across the plant, and cells communicate their timing via local or long‐distance sharing of clock components, causing their rhythms to couple. We found that both varied light sensitivity and long‐distance coupling could generate period differences between organs, while local coupling was required to generate the spatial waves of clock gene expression observed experimentally. We then examined our model under noisy light‐dark cycles and found that local coupling minimized timing errors caused by the noise while allowing each plant region to maintain a different clock phase. Thus, local sensitivity to environmental inputs combined with local coupling enables flexible yet robust circadian timing.     

Functional Brain Connectivity as a New Feature for P300 Speller

The brain is a large-scale complex network often referred to as the “connectome”. Cognitive functions and information processing are mainly based on the interactions between distant brain regions. However, most of the ‘feature extraction’ methods used in the context of Brain Computer Interface (BCI) ignored the possible functional relationships between different signals recorded from distinct brain areas. In this paper, the functional connectivity quantified by the phase locking value (PLV) was introduced to characterize the evoked responses (ERPs) obtained in the case of target and non-targets visual stimuli. We also tested the possibility of using the functional connectivity in the context of ‘P300 speller’. The proposed approach was compared to the well-known methods proposed in the state of the art of “P300 Speller”, mainly the peak picking, the area, time/frequency based features, the xDAWN spatial filtering and the stepwise linear discriminant analysis (SWLDA). The electroencephalographic (EEG) signals recorded from ten subjects were analyzed offline. The results indicated that phase synchrony offers relevant information for the classification in a P300 speller. High synchronization between the brain regions was clearly observed during target trials, although no significant synchronization was detected for a non-target trial. The results showed also that phase synchrony provides higher performance than some existing methods for letter classification in a P300 speller principally when large number of trials is available. Finally, we tested the possible combination of both approaches (classical features and phase synchrony). Our findings showed an overall improvement of the performance of the P300-speller when using Peak picking, the area and frequency based features. Similar performances were obtained compared to xDAWN and SWLDA when using large number of trials.     

Functional Brain Networks Develop from a “Local to Distributed” Organization

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward ‘segregation’ (a general decrease in correlation strength) between regions close in anatomical space and ‘integration’ (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more “distributed” architecture in young adults. We argue that this “local to distributed” developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing “small-world”-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways.     

Functional Brain Networks Develop from a “Local to Distributed” Organization

The mature human brain is organized into a collection of specialized functional networks that flexibly interact to support various cognitive functions. Studies of development often attempt to identify the organizing principles that guide the maturation of these functional networks. In this report, we combine resting state functional connectivity MRI (rs-fcMRI), graph analysis, community detection, and spring-embedding visualization techniques to analyze four separate networks defined in earlier studies. As we have previously reported, we find, across development, a trend toward ‘segregation’ (a general decrease in correlation strength) between regions close in anatomical space and ‘integration’ (an increased correlation strength) between selected regions distant in space. The generalization of these earlier trends across multiple networks suggests that this is a general developmental principle for changes in functional connectivity that would extend to large-scale graph theoretic analyses of large-scale brain networks. Communities in children are predominantly arranged by anatomical proximity, while communities in adults predominantly reflect functional relationships, as defined from adult fMRI studies. In sum, over development, the organization of multiple functional networks shifts from a local anatomical emphasis in children to a more “distributed” architecture in young adults. We argue that this “local to distributed” developmental characterization has important implications for understanding the development of neural systems underlying cognition. Further, graph metrics (e.g., clustering coefficients and average path lengths) are similar in child and adult graphs, with both showing “small-world”-like properties, while community detection by modularity optimization reveals stable communities within the graphs that are clearly different between young children and young adults. These observations suggest that early school age children and adults both have relatively efficient systems that may solve similar information processing problems in divergent ways.     

The cell adhesion molecule EphA4 is involved in circadian clock functions

Circadian (～24 h) rhythms of cellular network plasticity in the central circadian clock, the suprachiasmatic nucleus (SCN), have been described. The neuronal network in the SCN regulates photic resetting of the circadian clock as well as stability of the circadian system during both entrained and constant conditions. EphA4, a cell adhesion molecule regulating synaptic plasticity by controlling connections of neurons and astrocytes, is expressed in the SCN. To address whether EphA4 plays a role in circadian photoreception and influences the neuronal network of the SCN, we have analyzed circadian wheel‐running behavior of EphA4 knockout (EphA4^?/?) mice under different light conditions and upon photic resetting, as well as their light‐induced protein response in the SCN. EphA4^?/? mice exhibited reduced wheel‐running activity, longer endogenous periods under constant darkness and shorter periods under constant light conditions, suggesting an effect of EphA4 on SCN function. Moreover, EphA4^?/? mice exhibited suppressed phase delays of their wheel‐running activity following a light pulse during the beginning of the subjective night (CT15). Accordingly, light‐induced c‐FOS (FBJ murine osteosarcoma viral oncogene homolog) expression was diminished. Our results suggest a circadian role for EphA4 in the SCN neuronal network, affecting the circadian system and contributing to the circadian response to light.     

Quantitative analysis of phase wave of gene expression in the mammalian central circadian clock network

Background

The suprachiasmatic nucleus (SCN), the master circadian clock, is a heterogeneous oscillator network, yet displays a robust synchronization dynamics. Recent single-cell bioluminescent imaging revealed temporal gradients in circadian clock gene expression in the SCN ex vivo. However, due to technical difficulty in biological approaches to elucidate the entire network structure of the SCN, characteristics of the gradient, which we refer to as phase wave, remain unknown.

Methodology/Principal Findings

We implemented new approaches, i.e., quantitative analysis and model simulation to characterize the phase waves in Per2::Luciferase clock reporter gene expression of the rat SCN slice. Our quantitative study demonstrated not only a high degree of synchronization between the neurons and regular occurrence of the phase wave propagation, but also a significant amount of phase fluctuations contained in the wave. In addition, our simulations based on local coupling model suggest that the intercellular coupling strength estimated by the model simulations is significantly higher than the critical value for generating the phase waves. Model simulations also suggest that heterogeneity of the SCN neurons is one of the main factors causing the phase wave fluctuations. Furthermore, robustness of the SCN network against dynamical noise and variation of the natural frequencies inherent in these neurons was quantitatively assessed.

Conclusions/Significance

To our knowledge, this is the first quantitative evaluation of the phase wave and further characterization of the SCN neuronal network features generating the wave i.e., intercellular synchrony, phase fluctuation, strong local coupling, heterogeneous periodicity and robustness. Our present study provides an approach, which will lead to a comprehensive understanding of mechanistic and/or biological significance of the phase wave in the central circadian oscillatory system.     

Beyond a Dichotomous View of the Concepts of ‘Sex’ and ‘Gender’ Focus Group Discussions among Gender Researchers at a Medical Faculty

Introduction

The concepts of ‘sex’ and ‘gender’ are both of vital importance in medicine and health sciences. However, the meaning of these concepts has seldom been discussed in the medical literature. The aim of this study was to explore what the concepts of ‘sex’ and ‘gender’ meant for gender researchers based in a medical faculty.

Methods

Sixteen researchers took part in focus group discussions. The analysis was performed in several steps. The participating researchers read the text and discussed ideas for analysis in national and international workshops. The data were analysed using qualitative content analysis. The authors performed independent preliminary analyses, which were further developed and intensively discussed between the authors.

Results

The analysis of meanings of the concepts of ‘sex’ and ‘gender’ for gender researchers based in a medical faculty resulted in three categories; “Sex as more than biology”, with the subcategories ‘sex’ is not simply biological, ‘sex’ as classification, and ‘sex’ as fluid and changeable; ”Gender as a multiplicity of power-related constructions”, with the subcategories: ‘gender’ as constructions, ‘gender’ power dimensions, and ‘gender’ as doing femininities and masculinities; “Sex and gender as interwoven”, with the subcategories: ‘sex’ and ‘gender’ as inseparable and embodying ‘sex’ and ‘gender’.

Conclusions

Gender researchers within medicine pointed out the importance of looking beyond a dichotomous view of the concepts of ‘sex’ and ‘gender’. The perception of the concepts was that ‘sex’ and ‘gender’ were intertwined. Further research is needed to explore how ‘sex’ and ‘gender’ interact.     

Temporal Characteristics of Online Syntactic Sentence Planning: An Event-Related Potential Study

During sentence production, linguistic information (semantics, syntax, phonology) of words is retrieved and assembled into a meaningful utterance. There is still debate on how we assemble single words into more complex syntactic structures such as noun phrases or sentences. In the present study, event-related potentials (ERPs) were used to investigate the time course of syntactic planning. Thirty-three volunteers described visually animated scenes using naming formats varying in syntactic complexity: from simple words (‘W’, e.g., “triangle”, “red”, “square”, “green”, “to fly towards”), to noun phrases (‘NP’, e.g., “the red triangle”, “the green square”, “to fly towards”), to a sentence (‘S’, e.g., “The red triangle flies towards the green square.”). Behaviourally, we observed an increase in errors and corrections with increasing syntactic complexity, indicating a successful experimental manipulation. In the ERPs following scene onset, syntactic complexity variations were found in a P300-like component (‘S’/‘NP’>‘W’) and a fronto-central negativity (linear increase with syntactic complexity). In addition, the scene could display two actions - unpredictable for the participant, as the disambiguation occurred only later in the animation. Time-locked to the moment of visual disambiguation of the action and thus the verb, we observed another P300 component (‘S’>‘NP’/‘W’). The data show for the first time evidence of sensitivity to syntactic planning within the P300 time window, time-locked to visual events critical of syntactic planning. We discuss the findings in the light of current syntactic planning views.     

Signaling in the mammalian circadian clock: the NO/cGMP pathway

Mammalian circadian rhythms are generated by a hypothalamic suprachiasmatic nuclei (SCN) clock. Light pulses synchronize body rhythms by inducing phase delays during the early night and phase advances during the late night. Phosphorylation events are known to be involved in circadian phase shifting, both for delays and advances. Pharmacological inhibition of the cGMP-dependent kinase (cGK) or Ca2+/calmodulin-dependent kinase (CaMK), or of neuronal nitric oxide synthase (nNOS) blocks the circadian responses to light in vivo. Light pulses administered during the subjective night, but not during the day, induce rapid phosphorylation of both p-CAMKII and p-nNOS (specifically phosphorylated by CaMKII). CaMKII inhibitors block light-induced nNOS activity and phosphorylation, suggesting a direct pathway between both enzymes. Furthermore, SCN cGMP exhibits diurnal and circadian rhythms with maximal values during the day or subjective day. This variation of cGMP levels appears to be related to temporal changes in phosphodiesterase (PDE) activity and not to guanylyl cyclase (GC) activity. Light pulses increase SCN cGMP levels at circadian time (CT) 18 (when light causes phase advances of rhythms) but not at CT 14 (the time for light-induced phase delays). cGK II is expressed in the hamster SCN and also exhibits circadian changes in its levels, peaking during the day. Light pulses increase cGK activity at CT 18 but not at CT 14. In addition, cGK and GC inhibition by KT-5823 and ODQ significantly attenuated light-induced phase shifts at CT 18. This inhibition did not change c-Fos expression SCN but affected the expression of the clock gene per in the SCN. These results suggest a signal transduction pathway responsible for light-induced phase advances of the circadian clock which could be summarized as follows: Glu-Ca2+-CaMKII-nNOS-GC-cGMP-cGK-->-->clock genes. This pathway offers a signaling window that allows peering into the circadian clock machinery in order to decipher its temporal cogs and wheels.     

On the persistence of memory: Soft clocks and terrestrial biosphere-atmosphere interactions

The circadian clock is considered a central “orchestrator” of gene expression and metabolism. Concomitantly, the circadian clock is considered of negligible influence in the field and beyond leaf levels, where direct physiological responses to environmental cues are considered the main drivers of diel fluctuations. I propose to bridge the gap across scales by examining current evidence on whether circadian rhythmicity in gas exchange is relevant for field settings and at the ecosystem scale. Nocturnal stomatal conductance and water fluxes appear to be influenced by a “hard” clock that may override the direct physiological responses to the environment. Tests on potential clock controls over photosynthetic carbon assimilation and daytime transpiration are scant yet, if present, could have a large impact on our current understanding and modeling of the exchanges of carbon dioxide and water between terrestrial ecosystems and the atmosphere.     

Establishment of cell lines derived from the rat suprachiasmatic nucleus

Physiological and behavioral circadian rhythms in mammals are orchestrated by a central circadian clock located in the suprachiasmatic nucleus (SCN) of the hypothalamus. Photic input entrains the phase of the central clock, and many peripheral clocks are regulated by neural or hormonal output from the SCN. We established cell lines derived from the rat embryonic SCN to examine the molecular network of the central clock. An established cell line exhibited the stable circadian expression of clock genes. The circadian oscillation was abruptly phase-shifted by forskolin, and abolished by siBmal1. These results are compatible with in vivo studies of the SCN.     

Circadian Regulation of Food-Anticipatory Activity in Molecular Clock–Deficient Mice

In the mammalian brain, the suprachiasmatic nucleus (SCN) of the anterior hypothalamus is considered to be the principal circadian pacemaker, keeping the rhythm of most physiological and behavioral processes on the basis of light/dark cycles. Because restriction of food availability to a certain time of day elicits anticipatory behavior even after ablation of the SCN, such behavior has been assumed to be under the control of another circadian oscillator. According to recent studies, however, mutant mice lacking circadian clock function exhibit normal food-anticipatory activity (FAA), a daily increase in locomotor activity preceding periodic feeding, suggesting that FAA is independent of the known circadian oscillator. To investigate the molecular basis of FAA, we examined oscillatory properties in mice lacking molecular clock components. Mice with SCN lesions or with mutant circadian periods were exposed to restricted feeding schedules at periods within and outside circadian range. Periodic feeding led to the entrainment of FAA rhythms only within a limited circadian range. Cry1^−/− mice, which are known to be a “short-period mutant,” entrained to a shorter period of feeding cycles than did Cry2^−/− mice. This result indicated that the intrinsic periods of FAA rhythms are also affected by Cry deficiency. Bmal1 ^−/− mice, deficient in another essential element of the molecular clock machinery, exhibited a pre-feeding increase of activity far from circadian range, indicating a deficit in circadian oscillation. We propose that mice possess a food-entrainable pacemaker outside the SCN in which canonical clock genes such as Cry1, Cry2 and Bmal1 play essential roles in regulating FAA in a circadian oscillatory manner.     

Evolutionary and Topological Properties of Genes and Community Structures in Human Gene Regulatory Networks

The diverse, specialized genes present in today’s lifeforms evolved from a common core of ancient, elementary genes. However, these genes did not evolve individually: gene expression is controlled by a complex network of interactions, and alterations in one gene may drive reciprocal changes in its proteins’ binding partners. Like many complex networks, these gene regulatory networks (GRNs) are composed of communities, or clusters of genes with relatively high connectivity. A deep understanding of the relationship between the evolutionary history of single genes and the topological properties of the underlying GRN is integral to evolutionary genetics. Here, we show that the topological properties of an acute myeloid leukemia GRN and a general human GRN are strongly coupled with its genes’ evolutionary properties. Slowly evolving (“cold”), old genes tend to interact with each other, as do rapidly evolving (“hot”), young genes. This naturally causes genes to segregate into community structures with relatively homogeneous evolutionary histories. We argue that gene duplication placed old, cold genes and communities at the center of the networks, and young, hot genes and communities at the periphery. We demonstrate this with single-node centrality measures and two new measures of efficiency, the set efficiency and the interset efficiency. We conclude that these methods for studying the relationships between a GRN’s community structures and its genes’ evolutionary properties provide new perspectives for understanding evolutionary genetics.     

Development of SCN Connectivity and the Circadian Control of Arousal: A Diminishing Role for Humoral Factors?

The suprachiasmatic nucleus (SCN) is part of a wake-promoting circuit comprising the dorsomedial hypothalamus (DMH) and locus coeruleus (LC). Although widely considered a “master clock,” the SCN of adult rats is also sensitive to feedback regarding an animal''s behavioral state. Interestingly, in rats at postnatal day (P)2, repeated arousing stimulation does not increase neural activation in the SCN, despite doing so in the LC and DMH. Here we show that, by P8, the SCN is activated by arousing stimulation and that selective destruction of LC terminals with DSP-4 blocks this activational effect. We next show that bidirectional projections among the SCN, DMH, and LC are nearly absent at P2 but present at P8. Despite the relative lack of SCN connectivity with downstream structures at P2, day-night differences in sleep-wake activity are observed, suggesting that the SCN modulates behavior at this age via humoral factors. To test this hypothesis, we lesioned the SCN at P1 and recorded sleep-wake behavior at P2: Day-night differences in sleep and wake were eliminated. We next performed precollicular transections at P2 and P8 that isolate the SCN and DMH from the brainstem and found that day-night differences in sleep-wake behavior were retained at P2 but eliminated at P8. Finally, the SCN or DMH was lesioned at P8: When recorded at P21, rats with either lesion exhibited similarly fragmented wake bouts and no evidence of circadian modulation of wakefulness. These results suggest an age-related decline in the SCN''s humoral influence on sleep-wake behavior that coincides with the emergence of bidirectional connectivity among the SCN, DMH, and LC.     

Control of Neuronal Network in Caenorhabditis elegans

Caenorhabditis elegans, a soil dwelling nematode, is evolutionarily rudimentary and contains only ∼ 300 neurons which are connected to each other via chemical synapses and gap junctions. This structural connectivity can be perceived as nodes and edges of a graph. Controlling complex networked systems (such as nervous system) has been an area of excitement for mankind. Various methods have been developed to identify specific brain regions, which when controlled by external input can lead to achievement of control over the state of the system. But in case of neuronal connectivity network the properties of neurons identified as driver nodes is of much importance because nervous system can produce a variety of states (behaviour of the animal). Hence to gain insight on the type of control achieved in nervous system we implemented the notion of structural control from graph theory to C. elegans neuronal network. We identified ‘driver neurons’ which can provide full control over the network. We studied phenotypic properties of these neurons which are referred to as ‘phenoframe’ as well as the ‘genoframe’ which represents their genetic correlates. We find that the driver neurons are primarily motor neurons located in the ventral nerve cord and contribute to biological reproduction of the animal. Identification of driver neurons and its characterization adds a new dimension in controllability of C. elegans neuronal network. This study suggests the importance of driver neurons and their utility to control the behaviour of the organism.     

GABA synchronizes clock cells within the suprachiasmatic circadian clock

The master clock in the suprachiasmatic nuclei (SCN) is composed of multiple, single-cell circadian clocks. We test the postulate that these individual "clock cells" can be synchronized to each other by the inhibitory transmitter gamma-aminobutyric acid (GABA). For these experiments, we monitored the firing rate rhythm of individual clock cells on fixed multielectrode plates in culture and tested the effects of GABA. The results show that the daily variation in responsiveness of the SCN to phase-shifting agents is manifested at the level of individual neurons. Moreover, GABA, acting through A-type receptors, can both phase shift and synchronize clock cells. We propose that GABA is an important synchronizer of SCN neurons in vivo.     

Intrinsic connectivity reveals functionally distinct cortico-hippocampal networks in the human brain

Episodic memory depends on interactions between the hippocampus and interconnected neocortical regions. Here, using data-driven analyses of resting-state functional magnetic resonance imaging (fMRI) data, we identified the networks that interact with the hippocampus—the default mode network (DMN) and a “medial temporal network” (MTN) that included regions in the medial temporal lobe (MTL) and precuneus. We observed that the MTN plays a critical role in connecting the visual network to the DMN and hippocampus. The DMN could be further divided into 3 subnetworks: a “posterior medial” (PM) subnetwork comprised of posterior cingulate and lateral parietal cortices; an “anterior temporal” (AT) subnetwork comprised of regions in the temporopolar and dorsomedial prefrontal cortex; and a “medial prefrontal” (MP) subnetwork comprised of regions primarily in the medial prefrontal cortex (mPFC). These networks vary in their functional connectivity (FC) along the hippocampal long axis and represent different kinds of information during memory-guided decision-making. Finally, a Neurosynth meta-analysis of fMRI studies suggests new hypotheses regarding the functions of the MTN and DMN subnetworks, providing a framework to guide future research on the neural architecture of episodic memory.

Episodic memory depends on interactions between the hippocampus and interconnected neocortical regions. This study uses network analyses of intrinsic brain networks at rest to identify and characterize brain networks that interact with the hippocampus and have distinct functions during memory-guided decision making.