Analysis of co-occurrence rates of the modes.

<p>Cco-occurrence maps of frequency mode pairs. An entry (column <i>m</i>, row <i>n</i>)(1…50, 1…50) of a matrix at column <i>i</i> (1…4) and row <i>j</i> (1…4) of the figure shows cco-occurrence of frequency mode <i>i</i> in network <i>m</i>, given that frequency mode <i>j</i> is occurred at the same time-point in network <i>n</i>. Positive cc-occurrence (color coded as red) corresponds to <i>reinforcement effect</i> and negative cc-occurrence (color coded as blue) is corresponding to <i>suppression effect</i>.</p

Outline of our framework for capturing instantaneous spectra of ICA time-courses and its variation in time in the form of “frequency modes”.

<p>(A) First, fMRI time-series is pre-processed and feed into the ICA to be decomposed into 50 ICA networks and the associated time-courses (detail of these ICA networks is provided in supplementary material of (Allen, 2014 #510)). Complex morlet wavelet is used to map the time-courses to the time-frequency domain. Finally, canonical patterns of power spectra are estimated by k-means clustering which we refer to as “frequency modes”. (B) "Frequency modes" as the representatives of the variation in spectral powers of networks time-courses, Each mode is formed by similar instantaneous frequency content of time-courses which have been clustered together.</p

Analysis of age and gender effect on.

<p>(A) occurrence rate of individual frequency modes and (B) cco-occurrence rate of pair of modes. In (A) specific networks and in (B) pairs of networks are highlighted [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0171647#pone.0171647.ref013" target="_blank">13</a>] in which occurrence rate of given mode and cco-occurrence of pair of modes are significantly effected by age or gender</p

Time-varying spectral power of resting-state fMRI networks reveal cross-frequency dependence in dynamic connectivity

<div><p>Brain oscillations and synchronicity among brain regions (brain connectivity) have been studied in resting-state (RS) and task-induced settings. RS-connectivity which captures brain functional integration during an unconstrained state is shown to vary with the frequency of oscillations. Indeed, high temporal resolution modalities have demonstrated both between and cross-frequency connectivity spanning across frequency bands such as theta and gamma. Despite high spatial resolution, functional magnetic resonance imaging (fMRI) suffers from low temporal resolution due to modulation with slow-varying hemodynamic response function (HRF) and also relatively low sampling rate. This limits the range of detectable frequency bands in fMRI and consequently there has been no evidence of cross-frequency dependence in fMRI data. In the present work we uncover recurring patterns of spectral power in network timecourses which provides new insight on the actual nature of frequency variation in fMRI network activations. Moreover, we introduce a new measure of dependence between pairs of rs-fMRI networks which reveals significant cross-frequency dependence between functional brain networks specifically default-mode, cerebellar and visual networks. This is the first strong evidence of cross-frequency dependence between functional networks in fMRI and our subject group analysis based on age and gender supports usefulness of this observation for future clinical applications.</p></div

Analysis of occurrence the modes.

<p>Boxplots of occurrence rates of each individual frequency mode in ICA networks. Networks with significantly higher (filled boxplots) or lower (dashed boxplots) occurrence of the given mode than majority (85%) of all networks are identified.</p

Expected number of vaccines used per year (over a 30-year simulation period) for scenarios with and without strain replacement.

<p>Error bars represents 95% projection intervals (error bars that are shorter than the width of symbols are not shown). PMC, polyvalent meningococcal conjugate; PMP, polyvalent meningococcal polysaccharide.</p

(A) Weekly clinical meningitis cases in Burkina Faso reported between 2002 and 2015 (data were made available from the Ministry of Health, Burkina Faso). (B) Percentage of confirmed meningitis cases that are associated to <i>Neisseria meningitis</i> serogroup A, <i>N</i>. <i>meningitidis</i> non-A serogroups (including C, W, and X), and other pathogens (including <i>Streptococcus pneumoniae</i> and <i>Haemophilus influenzae</i> type b) from 2002–2015.

<p>These estimates are obtained from WHO [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002495#pmed.1002495.ref031" target="_blank">31</a>] (for 2002), WHO Enhanced Meningitis Bulletin (for 2003–2005), Burkina Faso <i>Maladies Potentiel Épidémie</i> (MPE) surveillance data (for 2006 and 2012–2015), and Novak et al. [<a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002495#pmed.1002495.ref011" target="_blank">11</a>] (for 2007–2011) (see <a href="http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1002495#pmed.1002495.s002" target="_blank">S1 Data</a>). Men-A, meningitis serogroup A; Non Men-A, meningitis serogroups other than A.</p

Alternative vaccine strategies for employing polyvalent meningococcal vaccines (post 2020).

<p>Alternative vaccine strategies for employing polyvalent meningococcal vaccines (post 2020).</p

The expected percentage reduction in annual meningococcal cases over a 30-year simulation period for the vaccination strategies described in Table 1, compared to the Base strategy.

<p>Bars represent the 95% prediction intervals.</p

Annual number of meningococcal cases for scenarios with and without strain replacement projected by the model under the vaccination strategies described in Table 1.

<p>The long bars represent the average annual number of meningococcal cases expected under each strategy option.</p