Univariate - Multivariate Approaches: Joint Modeling of Imaging & Genetic Data

<div>Talk given during the "Introduction to Imaging Genetics" workshop at the 2014 Organization for Human Brain Mapping (OHBM) conference in Hamburg, 8-12 June.</div><div><br></div

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 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

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

Opposite Modulation of Brain Functional Networks Implicated at Low vs. High Demand of Attention and Working Memory

<div><p>Background</p><p>Functional magnetic resonance imaging (fMRI) studies indicate that the brain organizes its activity into multiple functional networks (FNs) during either resting condition or task-performance. However, the functions of these FNs are not fully understood yet.</p><p>Methodology/Principal Findings</p><p>To investigate the operation of these FNs, spatial independent component analysis (sICA) was used to extract FNs from fMRI data acquired from healthy participants performing a visual task with two levels of attention and working memory load. The task-related modulations of extracted FNs were assessed. A group of FNs showed increased activity at low-load conditions and reduced activity at high-load conditions. These FNs together involve the left lateral frontoparietal cortex, insula, and ventromedial prefrontal cortex. A second group of FNs showed increased activity at high-load conditions and reduced activity at low-load conditions. These FNs together involve the intraparietal sulcus, frontal eye field, lateral frontoparietal cortex, insula, and dorsal anterior cingulate, bilaterally. Though the two groups of FNs showed opposite task-related modulations, they overlapped extensively at both the lateral and medial frontoparietal cortex and insula. Such an overlap of FNs would not likely be revealed using standard general-linear-model-based analyses.</p><p>Conclusions</p><p>By assessing task-related modulations, this study differentiated the functional roles of overlapping FNs. Several FNs including the left frontoparietal network are implicated in task conditions of low attentional load, while another set of FNs including the dorsal attentional network is implicated in task conditions involving high attentional demands.</p></div

The average ISC for each video clip.

<p>ISC’s were calculated across all unique subject pairs and electrodes. The ISC's were averaged across all electrodes and subject pairs for each individual. The distribution of individual average ISC’s are indicated in each boxplot, separately for each clip. The boxplots are organized with the highest average ISC’s on top and the lowest ISC’s on bottom. ISC’s were greater than zero (permutation test: p < 0.0028) for 15 out of 16 clips. Within each boxplot, the upper and lower bars indicate the maximum and minimum data points, respectively. The red bar spans the first (lower) and third (upper) quartiles. The solid line indicates the median and the circle indicates the mean.</p

ICs activated at low-load conditions.

<p>A. Colors on the Montreal Neurological Institute (MNI) T1 templates show the spatial distributions of positive sub-networks from ICs exhibiting increased activity at low- relative to high-load conditions. Only clusters surviving corrections for voxel-wise whole-brain analyses are shown. The numbers at the bottom right of each brain image indicate Z coordinates in MNI space. The color bar indicates t values. The “Beta-weight” column shows values of beta-weights at low- and high-load conditions. Error bars indicate standard errors (SEs) of the mean. The p value on each panel indicates the statistical significance of the main effect of task load on beta-weight. The “Timecourse” column shows task-load-related modulations in the timecourses of related ICs within 30 s after the onset of task blocks in the four task conditions. For x-axis, 0 represents the onset of task blocks and the block duration is 19.2 s. B. Yellow-red colors on T1 templates indicate brain regions covered by one or more ICs. The color bar indicates the number of overlapping ICs. The number below each brain image indicates the Z coordinates in MNI space. Abbreviations: L: low load without distractors; LD: low load with distractors; H: high load without distractors; HD: high load with distractors; R: right.</p

ICs activated at high-load conditions.

<p>A. Colors on the Montreal Neurological Institute (MNI) T1 templates show the spatial distribution of positive sub-networks from ICs exhibiting increased activity at high- relative to low-load conditions. B. Yellow-red colors on T1 templates indicate brain regions covered by one or more ICs. Please see fig. 1 legend for additional details.</p