Cumulating evidence from epidemiologic studies implicates cardiovascular health and cerebrovascular function in several brain diseases in late life. We examined vascular risk factors with respect to a cerebrovascular measure of brain functioning in subjects in mid-life, which could represent a marker of brain changes in later life. Breath-hold functional MRI (fMRI) was performed in 541 women and men (mean age 50.4 years) from the Coronary Artery Risk Development in Young Adults (CARDIA) Brain MRI sub-study. Cerebrovascular reactivity (CVR) was quantified as percentage change in blood-oxygen level dependent (BOLD) signal in activated voxels, which was mapped to a common brain template and log-transformed. Mean CVR was calculated for anatomic regions underlying the default-mode network (DMN) - a network implicated in AD and other brain disorders - in addition to areas considered to be relatively spared in the disease (e.g. occipital lobe), which were utilized as reference regions. Mean CVR was significantly reduced in the posterior cingulate/precuneus (β=-0.063, 95% CI: -0.106, -0.020), anterior cingulate (β=-0.055, 95% CI: -0.101, -0.010), and medial frontal lobe (β=-0.050, 95% CI: -0.092, -0.008) relative to mean CVR in the occipital lobe, after adjustment for age, sex, race, education, and smoking status, in subjects with pre-hypertension/hypertension compared to normotensive subjects. By contrast, mean CVR was lower, but not significantly, in the inferior parietal lobe (β=-0.024, 95% CI: -0.062, 0.014) and the hippocampus (β=-0.006, 95% CI: -0.062, 0.050) relative to mean CVR in the occipital lobe. Similar results were observed in subjects with diabetes and dyslipidemia compared to those without these conditions, though the differences were non-significant. Reduced CVR may represent diminished vascular functionality for the DMN for individuals with prehypertension/hypertension in mid-life, and may serve as a preclinical marker for brain dysfunction in later life.

The inherently multivariate nature of functional brain imaging data affords the unique opportunity to explore how anatomically disparate brain areas interact during cognitive tasks. We introduce a new method for characterizing inter-regional interactions using event-related functional magnetic resonance imaging (fMRI) data. This method's principle advantage over existing analytical techniques is its ability to model the functional connectivity between brain regions during distinct stages of a cognitive task. The method is implemented by using separate covariates to model the activity evoked during each stage of each individual trial in the context of the general linear model (GLM). The resulting parameter estimates (beta values) are sorted according to the stage from which they were derived to form a set of stage-specific beta series. Regions whose beta series are correlated during a given stage are inferred to be functionally interacting during that stage. To validate the assumption that correlated fluctuations in trial-to-trial beta values imply functional connectivity, we applied the method to an event-related fMRI data set in which subjects performed two sequence-tapping tasks. In concordance with previous electrophysiological and fMRI coherence studies, we found that the task requiring greater bimanual coordination induced stronger correlations between motor regions of the two hemispheres. The method was then applied to an event-related fMRI data set in which subjects performed a delayed recognition task. Distinct functional connectivity maps were generated during the component stages of this task, illustrating how important and novel observations of neural networks within the isolated stages of a cognitive task can be obtained.

Understanding functional connectivity within the brain is crucial to understanding neural function; even the simplest cognitive operations are supported by highly distributed neural circuits. We developed a novel method to measure task-related functional interactions between neural regions by applying coherence and partial coherence analyses to functional magnetic resonance imaging (fMRI) data. Coherence and partial coherence are spectral measures that estimate the linear time-invariant (LTI) relationship between time series. They can be used to generate maps of task-specific connectivity associated with seed regions of interest (ROIs). These maps may then be compared across tasks, revealing nodes with task-related changes of connectivity to the seed ROI. To validate the method, we applied it to an event-related fMRI data set acquired while subjects performed two sequence tapping tasks, one of which required more bimanual coordination. Areas showing increased functional connectivity with both tasks were the same as those showing increased activity. Furthermore, though there were no significant differences in mean activity between the two tasks, significant increases in interhemispheric coherence were found between the primary motor (M1) and premotor (PM) regions for the task requiring more bimanual coordination. This increase in interhemispheric connectivity is supported by other brain imaging techniques as well as patient studies.

Circadian rhythms (lasting approximately 24 h) control and entrain various physiological processes, ranging from neural activity and hormone secretion to sleep cycles and eating habits. Several studies have shown that time of day (TOD) is associated with human cognition and brain functions. In this study, utilizing a chronotype-based paradigm, we applied a graph theory approach on resting-state functional MRI (rs-fMRI) data to compare whole-brain functional network topology between morning and evening sessions and between morning-type (MT) and evening-type (ET) participants. Sixty-two individuals (31 MT and 31 ET) underwent two fMRI sessions, approximately 1 hour (morning) and 10 h (evening) after their wake-up time, according to their declared habitual sleep-wake pattern on a regular working day. In the global analysis, the findings revealed the effect of TOD on functional connectivity (FC) patterns, including increased small-worldness, assortativity, and synchronization across the day. However, we identified no significant differences based on chronotype categories. The study of the modular structure of the brain at mesoscale showed that functional networks tended to be more integrated with one another in the evening session than in the morning session. Local/regional changes were affected by both factors (i.e., TOD and chronotype), mostly in areas associated with somatomotor, attention, frontoparietal, and default networks. Furthermore, connectivity and hub analyses revealed that the somatomotor, ventral attention, and visual networks covered the most highly connected areas in the morning and evening sessions: the latter two were more active in the morning sessions, and the first was identified as being more active in the evening. Finally, we performed a correlation analysis to determine whether global and nodal measures were associated with subjective assessments across participants. Collectively, these findings contribute to an increased understanding of diurnal fluctuations in resting brain activity and highlight the role of TOD in future studies on brain function and the design of fMRI experiments.

We present a novel method to measure relative latencies between functionally connected regions using phase-delay of functional magnetic resonance imaging data. Derived from the phase component of coherency, this quantity estimates the linear delay between two time-series. In conjunction with coherence, derived from the magnitude component of coherency, phase-delay can be used to examine the temporal properties of functional networks. In this paper, we apply coherence and phase-delay methods to fMRI data in order to investigate dynamics of the motor network during task and rest periods. Using the supplementary motor area (SMA) as a reference region, we calculated relative latencies between the SMA and other regions within the motor network including the dorsal premotor cortex (PMd), primary motor cortex (M1), and posterior parietal cortex (PPC). During both the task and rest periods, we measured significant delays that were consistent across subjects. Specifically, we found significant delays between the SMA and the bilateral PMd, bilateral M1, and bilateral PPC during the task condition. During the rest condition, we found that the temporal dynamics of the network changed relative to the task period. No significant delays were measured between the SMA and the left PM and left M1; however, the right PM, right M1, and bilateral PPC were significantly delayed with respect to the SMA. Additionally, we observed significant map-wise differences in the dynamics of the network at task compared to the network at rest. These differences were observed in the interaction between the SMA and the left M1, left superior frontal gyrus, and left middle frontal gyrus. These temporal measurements are important in determining how regions within a network interact and provide valuable information about the sequence of cognitive processes within a network.

Recent functional imaging studies of working memory (WM) have suggested a relationship between the requirement for response selection and activity in dorsolateral prefrontal (DLPFC) and parietal regions. Although a number of WM operations are likely to occur during response selection, the current study was particularly interested in the contribution of this neural network to WM-based response selection when compared to the selection of an item from a list being maintained in memory, during a verbal learning task. The design manipulated stimulus-response mappings so that selecting an item from memory was not always accompanied with selecting a motor response. Functional activation during selection supported previous findings of fronto-parietal involvement, although in contrast to previous findings left, rather than right, DLPFC activity was significantly more active for selecting a memory-guided motor response, when compared to selecting an item currently maintained in memory or executing a memory-guided response. Our results contribute to the debate over the role of fronto-parietal activity during WM tasks, suggesting that this activity appears particularly related to response selection, potentially supporting the hypothesized role of prefrontal activity in biasing attention toward task-relevant material in more posterior regions.

Current models of executive function hold that the internal representations of stimuli used during reflective thought are maintained in the same posterior cortical regions initially activated during perception, and that activity in such regions is modulated by top-down signals originating in prefrontal cortex. In an event-related functional magnetic resonance imaging study, we presented participants with two pictures simultaneously, a face and a scene, immediately followed either by a repetition of one of the pictures (perception) or by a cue to think briefly of one of the just-seen, but no longer present, pictures (refreshing, a reflective act). Refreshing faces and scenes modulated activity in the fusiform face area (FFA) and parahippocampal place area (PPA), respectively, as well as other regions exhibiting relative perceptual selectivity for either faces or scenes. Four scene-selective regions (lateral precuneus, retrosplenial cortex, PPA, and middle occipital gyrus) showed an anatomical gradient of responsiveness to top-down reflective influences versus bottom-up perceptual influences. These results demonstrate that a brief reflective act can modulate posterior cortical activity in a stimulus-specific manner, suggesting that such modulatory mechanisms are engaged even during transient ongoing thought. Our findings are consistent with the hypothesis that refreshing is a component of more complex modulatory operations such as working memory and mental imagery, and that refresh-related activity may thus contribute to the common activation patterns seen across different cognitive tasks.

Phase/amplitude coupling (PAC) is emerging as an important electrophysiological measure of local and long-distance neuronal communication. Current techniques for calculating PAC provide a numerical index that represents an average value across an arbitrarily long time period. This requires researchers to rely on block design experiments and temporal concatenation at the cost of the sub-second temporal resolution afforded by electrophysiological recordings. Here we present a method for calculating event-related phase/amplitude coupling (ERPAC) designed to capture the temporal evolution of task-related changes in PAC across events or between distant brain regions that is applicable to human or animal electromagnetic recording.

While many neuroimaging studies have investigated verbal working memory (WM) by manipulating memory load, the subvocal rehearsal rate at these various memory loads has generally been left uncontrolled. Therefore, the goal of this study was to investigate how mnemonic load and the rate of subvocal rehearsal modulate patterns of activity in the core neural circuits underlying verbal working memory. Using fMRI in healthy subjects, we orthogonally manipulated subvocal rehearsal rate and memory load in a verbal WM task with long 45-s delay periods. We found that middle frontal gyrus (MFG) and superior parietal lobule (SPL) exhibited memory load effects primarily early in the delay period and did not exhibit rehearsal rate effects. In contrast, we found that inferior frontal gyrus (IFG), premotor cortex (PM) and Sylvian-parietal-temporal region (area Spt) exhibited approximately linear memory load and rehearsal rate effects, with rehearsal rate effects lasting through the entire delay period. These results indicate that IFG, PM and area Spt comprise the core articulatory rehearsal areas involved in verbal WM, while MFG and SPL are recruited in a general supervisory role once a memory load threshold in the core rehearsal network has been exceeded.