Assessing uncertainty in dynamic functional connectivity

Functional connectivity (FC) - the study of the statistical association between time series from anatomically distinct regions (Friston, 1994, 2011) - has become one of the primary areas of research in the field surrounding resting state functional magnetic resonance imaging (rs-fMRI). Although for many years researchers have implicitly assumed that FC was stationary across time in rs-fMRI, it has recently become increasingly clear that this is not the case and the ability to assess dynamic changes in FC is critical for better understanding of the inner workings of the human brain (Hutchison et al., 2013; Chang and Glover, 2010). Currently, the most common strategy for estimating these dynamic changes is to use the sliding-window technique. However, its greatest shortcoming is the inherent variation present in the estimate, even for null data, which is easily confused with true time-varying changes in connectivity (Lindquist et al., 2014). This can have serious consequences as even spurious fluctuations caused by noise can easily be confused with an important signal. For these reasons, assessment of uncertainty in the sliding-window correlation estimates is of critical importance. Here we propose a new approach that combines the multivariate linear process bootstrap (MLPB) method and a sliding-window technique to assess the uncertainty in a dynamic FC estimate by providing its confidence bands. Both numerical results and an application to rs-fMRI study are presented, showing the efficacy of the proposed method

Semiparametric Estimation of Task-Based Dynamic Functional Connectivity on the Population Level

Dynamic functional connectivity (dFC) estimates time-dependent associations between pairs of brain region time series as typically acquired during functional MRI. dFC changes are most commonly quantified by pairwise correlation coefficients between the time series within a sliding window. Here, we applied a recently developed bootstrap-based technique (Kudela et al., 2017) to robustly estimate subject-level dFC and its confidence intervals in a task-based fMRI study (24 subjects who tasted their most frequently consumed beer and Gatorade as an appetitive control). We then combined information across subjects and scans utilizing semiparametric mixed models to obtain a group-level dFC estimate for each pair of brain regions, flavor, and the difference between flavors. The proposed approach relies on the estimated group-level dFC accounting for complex correlation structures of the fMRI data, multiple repeated observations per subject, experimental design, and subject-specific variability. It also provides condition-specific dFC and confidence intervals for the whole brain at the group level. As a summary dFC metric, we used the proportion of time when the estimated associations were either significantly positive or negative. For both flavors, our fully-data driven approach yielded regional associations that reflected known, biologically meaningful brain organization as shown in prior work, as well as closely resembled resting state networks (RSNs). Specifically, beer flavor-potentiated associations were detected between several reward-related regions, including the right ventral striatum (VST), lateral orbitofrontal cortex, and ventral anterior insular cortex (vAIC). The enhancement of right VST-vAIC association by a taste of beer independently validated the main activation-based finding (Oberlin et al., 2016). Most notably, our novel dFC methodology uncovered numerous associations undetected by the traditional static FC analysis. The data-driven, novel dFC methodology presented here can be used for a wide range of task-based fMRI designs to estimate the dFC at multiple levels-group-, individual-, and task-specific, utilizing a combination of well-established statistical methods

Corticostriatal and dopaminergic response to beer flavor with both fMRI and [11C]raclopride Positron Emission Tomography

Background Cue-evoked drug seeking behavior likely depends on interactions between frontal activity and ventral striatal (VST) dopamine transmission. Using [11C]raclopride (RAC) positron emission tomography (PET), we previously demonstrated that beer flavor (absent intoxication) elicited VST dopamine (DA) release in beer drinkers, inferred by RAC displacement. Here, a subset of subjects from this previous RAC-PET study underwent a similar paradigm during functional magnetic resonance imaging (fMRI) to test how orbitofrontal cortex (OFC) and VST BOLD responses to beer flavor are related to VST DA release and motivation to drink. Methods Male beer drinkers (n=28, age=24±2, drinks/week=16±10) from our previous PET study participated in a similar fMRI paradigm wherein subjects tasted their most frequently consumed brand of beer and Gatorade® (appetitive control). We tested for correlations between blood oxygenation level dependent (BOLD) activation in fMRI and VST DA responses in PET, and drinking-related variables. Results Compared to Gatorade, beer flavor increased wanting and desire to drink, and induced BOLD responses in bilateral OFC and right VST. Wanting and desire to drink correlated with both right VST and medial OFC BOLD activation to beer flavor. Like the BOLD findings, beer flavor (relative to Gatorade) again induced right VST DA release in this fMRI subject subset, but there was no correlation between DA release and the magnitude of BOLD responses in frontal regions of interest. Conclusions Both imaging modalities showed a right lateralized VST response (BOLD and DA release) to a drug-paired conditioned stimulus, whereas fMRI BOLD responses in the VST and medial OFC also reflected wanting and desire to drink. The data suggest the possibility that responses to drug-paired cues may be rightward biased in the VST (at least in right-handed males), and that VST and OFC responses in this gustatory paradigm reflect stimulus wanting

Phytoplankton dynamics in relation to seasonal variability and upwelling and relaxation patterns at the mouth of Ria de Aveiro (West Iberian Margin) over a four-year period

From June 2004 to December 2007, samples were weekly collected at a fixed station located at the mouth of Ria de Aveiro (West Iberian Margin). We examined the seasonal and inter-annual fluctuations in composition and community structure of the phytoplankton in relation to the main environmental drivers and assessed the influence of the oceano-graphic regime, namely changes in frequency and intensity of upwelling events, over the dynamics of the phytoplankton assemblage. The samples were consistently handled and a final subset of 136 OTUs (taxa with relative abundance > 0.01%) was subsequently submitted to various multivariate analyses. The phytoplankton assemblage showed significant changes at all temporal scales but with an overriding importance of seasonality over longer-(inter-annual) or shorter-term fluctuations (upwelling-related). Sea-surface temperature, salinity and maximum upwelling index were retrieved as the main driver of seasonal change. Seasonal signal was most evident in the fluctuations of chlorophyll a concentration and in the high turnover from the winter to spring phytoplankton assemblage. The seasonal cycle of production and succession was disturbed by upwelling events known to disrupt thermal stratification and induce changes in the phytoplankton assemblage. Our results indicate that both the frequency and intensity of physical forcing were important drivers of such variability, but the outcome in terms of species composition was highly dependent on the available local pool of species and the timing of those events in relation to the seasonal cycle. We conclude that duration, frequency and intensity of upwelling events, which vary seasonally and inter-annually, are paramount for maintaining long-term phytoplankton diversity likely by allowing unstable coexistence and incorporating species turnover at different scales. Our results contribute to the understanding of the complex mechanisms of coastal phytoplankton dynamics in relation to changing physical forcing which is fundamental to improve predictability of future prospects under climate change.Portuguese Foundation for Science and Technology (FCT, Portugal) [SFRH/BPD/ 94562/2013]; FEDER funds; national funds; CESAM [UID/AMB/50017]; FCT/MEC through national funds; FEDERinfo:eu-repo/semantics/publishedVersio

Small conductance calcium-activated potassium current and the mechanism of atrial arrhythmia in mice with dysfunctional melanocyte-like cells

BACKGROUND: The melanin synthesis enzyme dopachrome tautomerase (Dct) regulates intracellular Ca(2+) in melanocytes. Homozygous Dct knockout (Dct(-/-)) adult mice are vulnerable to atrial arrhythmias (AA). OBJECTIVE: The purpose of this study was to determine whether apamin-sensitive small conductance Ca(2+)-activated K(+) (SK) currents are upregulated in Dct(-/-) mice and contribute to AA. METHODS: Optical mapping was used to study the membrane potential of the right atrium in Langendorff perfused Dct(-/-) (n = 9) and Dct(+/-) (n = 9) mice. RESULTS: Apamin prolonged action potential duration (APD) by 18.8 ms (95% confidence interval [CI] 13.4-24.1 ms) in Dct(-/-) mice and by 11.5 ms (95% CI 5.4-17.6 ms) in Dct(+/-) mice at a pacing cycle length of 150 ms (P = .047). The pacing cycle length threshold to induce APD alternans was 48 ms (95% CI 34-62 ms) for Dct(-/-) mice and 21 ms (95% CI 12-29 ms) for Dct(+/-) mice (P = .002) at baseline, and it was 35 ms (95% CI 21-49 ms) for Dct(-/-) mice and 22 ms (95% CI 11-32 ms) for Dct(+/-) mice (P = .025) after apamin administration. Apamin prolonged post-burst pacing APD by 8.9 ms (95% CI 3.9-14.0 ms) in Dct(-/-) mice and by 1.5 ms (95% CI 0.7-2.3 ms) in Dct(+/-) mice (P = .005). Immunoblot and quantitative polymerase chain reaction analyses showed that protein and transcripts levels of SK1 and SK3 were increased in the right atrium of Dct(-/-) mice. AA inducibility (89% vs 11%; P = .003) and duration (281 seconds vs 66 seconds; P = .008) were greater in Dct(-/-) mice than in Dct(+/-) mice at baseline, but not different (22% vs 11%; P = 1.00) after apamin administration. Five of 8 (63%) induced atrial fibrillation episodes in Dct(-/-) mice had focal drivers. CONCLUSION: Apamin-sensitive SK current upregulation in Dct(-/-) mice plays an important role in the mechanism of AA

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Applications 28 (2018): 749-760, doi: 10.1002/eap.1682.The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite‐based sensors can repeatedly record the visible and near‐infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100‐m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short‐wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14‐bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3‐d repeat low‐Earth orbit could sample 30‐km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.National Center for Ecological Analysis and Synthesis (NCEAS); National Aeronautics and Space Administration (NASA) Grant Numbers: NNX16AQ34G, NNX14AR62A; National Ocean Partnership Program; NOAA US Integrated Ocean Observing System/IOOS Program Office; Bureau of Ocean and Energy Management Ecosystem Studies program (BOEM) Grant Number: MC15AC0000

Satellite Sensor Requirements for Monitoring Essential Biodiversity Variables of Coastal Ecosystems

The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibratio

On the Dynamics of the Spontaneous Activity in Neuronal Networks

Most neuronal networks, even in the absence of external stimuli, produce spontaneous bursts of spikes separated by periods of reduced activity. The origin and functional role of these neuronal events are still unclear. The present work shows that the spontaneous activity of two very different networks, intact leech ganglia and dissociated cultures of rat hippocampal neurons, share several features. Indeed, in both networks: i) the inter-spike intervals distribution of the spontaneous firing of single neurons is either regular or periodic or bursting, with the fraction of bursting neurons depending on the network activity; ii) bursts of spontaneous spikes have the same broad distributions of size and duration; iii) the degree of correlated activity increases with the bin width, and the power spectrum of the network firing rate has a 1/f behavior at low frequencies, indicating the existence of long-range temporal correlations; iv) the activity of excitatory synaptic pathways mediated by NMDA receptors is necessary for the onset of the long-range correlations and for the presence of large bursts; v) blockage of inhibitory synaptic pathways mediated by GABA(A) receptors causes instead an increase in the correlation among neurons and leads to a burst distribution composed only of very small and very large bursts. These results suggest that the spontaneous electrical activity in neuronal networks with different architectures and functions can have very similar properties and common dynamics

Cosmic ray oriented performance studies for the JEM-EUSO first level trigger

JEM-EUSO is a space mission designed to investigate Ultra-High Energy Cosmic Rays and Neutrinos (E > 5 ⋅ 1019 eV) from the International Space Station (ISS). Looking down from above its wide angle telescope is able to observe their air showers and collect such data from a very wide area. Highly specific trigger algorithms are needed to drastically reduce the data load in the presence of both atmospheric and human activity related background light, yet retain the rare cosmic ray events recorded in the telescope. We report the performance in offline testing of the first level trigger algorithm on data from JEM-EUSO prototypes and laboratory measurements observing different light sources: data taken during a high altitude balloon flight over Canada, laser pulses observed from the ground traversing the real atmosphere, and model landscapes reproducing realistic aspect ratios and light conditions as would be seen from the ISS itself. The first level trigger logic successfully kept the trigger rate within the permissible bounds when challenged with artificially produced as well as naturally encountered night sky background fluctuations and while retaining events with general air-shower characteristics

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)