fMRI BOLD and MEG theta power reflect complementary aspects of activity during lexicosemantic decision in adolescents with ASD.

Neuroimaging studies of autism spectrum disorder (ASD) have been predominantly unimodal. While many fMRI studies have reported atypical activity patterns for diverse tasks, the MEG literature in ASD remains comparatively small. Our group recently reported atypically increased event-related theta power in individuals with ASD during lexicosemantic processing. The current multimodal study examined the relationship between fMRI BOLD signal and anatomically-constrained MEG (aMEG) theta power. Thirty-three adolescents with ASD and 23 typically developing (TD) peers took part in both fMRI and MEG scans, during which they distinguished between standard words (SW), animal words (AW), and pseudowords (PW). Regions-of-interest (ROIs) were derived based on task effects detected in BOLD signal and aMEG theta power. BOLD signal and theta power were extracted for each ROI and word condition. Compared to TD participants, increased theta power in the ASD group was found across several time windows and regions including left fusiform and inferior frontal, as well as right angular and anterior cingulate gyri, whereas BOLD signal was significantly increased in the ASD group only in right anterior cingulate gyrus. No significant correlations were observed between BOLD signal and theta power. Findings suggest that the common interpretation of increases in BOLD signal and theta power as 'activation' require careful differentiation, as these reflect largely distinct aspects of regional brain activity. Some group differences in dynamic neural processing detected with aMEG that are likely relevant for lexical processing may be obscured by the hemodynamic signal source and low temporal resolution of fMRI.

Dynamic time warping outperforms Pearson correlation in detecting atypical functional connectivity in autism spectrum disorders.

Resting state fMRI (rsfMRI) is frequently used to study brain function, including in clinical populations. Similarity of blood-oxygen-level-dependent (BOLD) fluctuations during rsfMRI between brain regions is thought to reflect intrinsic functional connectivity (FC), potentially due to history of coactivation. To quantify similarity, studies have almost exclusively relied on Pearson correlation, which assumes linearity and can therefore underestimate FC if the hemodynamic response function differs regionally or there is BOLD signal lag between timeseries. Here we show in three cohorts of children, adolescents and adults, with and without autism spectrum disorders (ASDs), that measuring the similarity of BOLD signal fluctuations using non-linear dynamic time warping (DTW) is more robust to global signal regression (GSR), has higher test-retest reliability and is more sensitive to task-related changes in FC. Additionally, when comparing FC between individuals with ASDs and typical controls, more group differences are detected using DTW. DTW estimates are also more related to ASD symptom severity and executive function, while Pearson correlation estimates of FC are more strongly associated with respiration during rsfMRI. Together these findings suggest that non-linear methods such as DTW improve estimation of resting state FC, particularly when studying clinical populations whose hemodynamics or neurovascular coupling may be altered compared to typical controls.

Encoding strategy accounts for individual differences in change detection measures of VSTM.

Visual short-term memory (VSTM) capacity is often assessed using change detection tasks, and individual differences in performance have been shown to predict cognitive aptitudes across a range of domains in children and adults. We recently showed that intelligence correlates with an attentional component necessary for change detection rather than with memory capacity per se (Cusack, Lehmann, Veldsman, & Mitchell, 2009). It remained unclear, however, whether different attentional strategies during change detection have most impact during the encoding or maintenance of information. Here we present recent findings from our laboratory supporting the hypothesis that attentional selection during encoding dominates individual differences in change detection measures of visual short-term memory. In a first study, we unpredictably varied whether short-term memory was probed using change detection or whole report, encouraging participants to adopt the same encoding strategy throughout the tasks. Change detection performance of lower-IQ individuals improved. In a second study, we found that deficits in top-down attentional selectivity can be alleviated in participants with low change detection performance by providing helpful grouping information during encoding. Finally, a meta-analysis of neuroimaging data from 112 participants performing a variety of VSTM tasks showed that performance correlates with activity in several parietal and frontal regions during the encoding but not the maintenance phase. Taken together, these results support the notion that encoding strategy and not short-term memory capacity itself largely determines individual differences in visual change detection performance.