Task-related functional connectivity (fc-MRI) indexes the interaction of brain regions during cognitive tasks. Two general classes of methods exist to investigate fc-MRI: the most widely used method calculates temporal correlations between voxels/regions within subjects, and then determines if within-subject correlations are reliable across subjects (ws-fcMRI); the other calculates the average BOLD signal within voxels/regions and then performs correlations across subjects (as-fcMRI). That is, while both methods rely on correlational techniques, the level at which correlations are calculated are fundamentally different. While conceptually distinct, it is not known how well these two methods of fc-MRI analyses converge on the same findings. The current study addresses this question across a number of analyses. First, using default-mode network regions as seeds, we show that as-fcMRI does not strongly predict ws-fcMRI during episodic simulation tasks. Next, we show that the relationship between as-fcMRI and ws-fcMRI is contingent on whether correlations are calculated between regions from the same functional network (default-mode or dorsal-attention networks) or between regions from different functional networks. Lastly, we compare seed partial least squares (PLS) – a well-established as-fcMRI method – with a novel version of seed PLS that combines the multivariate approach of PLS analyses with within-subject correlations. The results showed that while many regions showed congruent as-fcMRI and ws-fcMRI effects, the two analyses produced effects in opposite directions for some regions. Results are discussed in relation to the Simpson’s Paradox, a phenomenon in which across-subject correlations are reversed within individuals present in a sample.

Theta (4 – 7 Hz) oscillations are increasingly recognised as a key neural signature of cognitive control. These theta oscillations are thought to permit information to be propagated expediently through the canonical frontoparietal control network. However, to date, most studies exploring the role of theta during control rely on paradigms that use transient, moment-to-moment adjustments of the cognitive control system (i.e., reactive control). It is unclear whether theta oscillations are also involved in anticipatory, proactive control processes. Here, we present novel evidence to show that theta oscillations are indeed involved in proactive control processes and that theta oscillations are temporally sensitive. Results from three studies will be presented. Firstly, during cued-trials task switching, preparatory and target-driven interference processes were both associated with broad frontoparietal connectivity. Such theta oscillations were seen to be behaviourally relevant with variability in phase locking across trials predictive of variability in behavioural performance. Finally, we show that temporally contextual information, as quantified using information theory, was linked to a frontal gradient of theta power, with higher levels of information resulting in stronger and broader frontal theta. Together, these studies support the role of theta in cognitive control and suggest theta is a distinct neural signature of temporally sensitive processing in frontoparietal control networks.

Theories of human brain development in childhood postulate an increasing ‘top down’ influence of frontal cortex on activity in posterior brain regions (Stevens, Brain Cognition, 2009). We tested this prediction using a child-customized magnetoencephalography (MEG) system to record brain responses of 25 young children (51.83 ± 7.77 months) during an auditory oddball task. Participants listened to sequences of tones containing occasional deviant tones that differed in pitch. As expected, these deviants elicited a classic mismatch response followed by a P3 component.
We then subjected the MEG data to dynamic causal modelling, comparing four families of models. All models had nodes in bilateral primary auditory cortex and superior temporal gyrus (STG) but differed in the presence or absence of additional nodes in left and right inferior frontal gyrus (IFG). We also varied whether forward, backward, or both types of connections were dynamic (i.e., whether they depended on the type of tone being presented).
Using Bayesian model selection, we determined that, from 228 ms after tone onset, the MEG data were best accounted for by a model with bilateral frontal sources and dynamic forward (but not backward) connections ( > 0.9 family exceedance probability).
Our findings differ from those of previous studies modelling data from adults using the same oddball paradigm, which assumed a right-lateralised frontal component and favoured dynamic backward as well as forward connections (Garrido et al., PNAS, 2007). Together, these findings provide direct evidence for a developmental shift in fronto-temporal effective brain connectivity between early childhood and adulthood.

Our capacity for higher cognitive reasoning – often known as fluid intelligence – allows us to understand complex and abstract ideas. Classical neuropsychological studies have identified the frontal lobes as being critical for reasoning abilities, but more recent network-based analyses of functional brain imaging data have revealed the importance of functional interactions across a wide range of cortical and subcortical areas in the service of fluid intelligence. To better understand the nature of these interactions, we collected fMRI data at 7T to maximize both temporal and spatial resolution, in a cohort of 60 healthy adult participants who also underwent standard intelligence testing. Neural activity was measured during the performance of a non-verbal reasoning task akin to Sudoku, known as the Latin Square Task, as well as at rest before and after the task. Participant accuracy scaled with reasoning complexity, such that performance declined with increments in the number of elements to be related within a trial. Brain activity within canonical ‘task-positive’ brain regions increased parametrically with task complexity, whereas ‘task-negative’ regions showed a stepwise decrease in activity as task complexity increased. Network analyses of task-related changes in connectivity revealed significant interactions between regions comprising the fronto-parietal, cingulo-opercular, and default-mode networks in association with increased task demands. Interestingly, resting-state connectivity within and between these networks decreased from pre- to post-task sessions. Our results suggest that overlapping changes in large-scale connectivity patterns across task and resting-state contexts are key predictors of reasoning performance, as well as more global intelligence measures.