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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., Competing Interests: Declaration of Competing Interest The authors declare no issues of competing interests., (Copyright © 2022. Published by Elsevier Inc.)

The cognitive effects of pharmacologically enhancing cortical dopamine (DA) tone are variable across healthy human adults. It has been postulated that individual differences in drug responses are linked to baseline cortical DA activity according to an inverted-U-shaped function. To better understand the effect of divergent starting points along this curve on DA drug responses, researchers have leveraged a common polymorphism (rs4680) in the gene encoding the enzyme catechol-O-methyltransferase (COMT) that gives rise to greater (Met allele) or lesser (Val allele) extracellular levels of cortical DA. Here we examined the extent to which changes in resting cortical perfusion following the administration of two mechanistically-distinct dopaminergic drugs vary by COMT genotype, and thereby track predictions of the inverted-U model. Using arterial spin labeling (ASL) and a double-blind, within-subject design, perfusion was measured in 75 healthy, genotyped participants once each after administration of tolcapone (a COMT inhibitor), bromocriptine (a DA D2/3 agonist), and placebo. COMT genotype and drug interacted such that COMT Val homozygotes exhibited increased prefusion in response to both drugs, whereas Met homozygotes did not. Additionally, tolcapone-related perfusion changes in the right inferior frontal gyrus correlated with altered performance on a task of executive function. No comparable effects were found for a genetic polymorphism (rs1800497) affecting striatal DA system function. Together, these results indicate that both the directionality and magnitude of drug-induced perfusion change provide meaningful information about individual differences in response to enhanced cortical DA tone., Competing Interests: Declaration of Competing Interest The authors declare no competing financial interests., (Copyright © 2021. Published by Elsevier Inc.)

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., (Copyright © 2015 Elsevier Inc. All rights reserved.)

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., (Copyright © 2014 Elsevier Inc. All rights reserved.)

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., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Interpretation of fMRI data depends on our ability to understand or model the shape of the hemodynamic response (HR) to a neural event. Although the HR has been studied almost since the beginning of fMRI, we are still far from having robust methods to account for the full range of known HR variation in typical fMRI analyses. This paper reviews how the authors and others contributed to our understanding of HR variation. We present an overview of studies that describe HR variation across voxels, healthy volunteers, populations, and dietary or pharmaceutical modulations. We also describe efforts to minimize the effects of HR variation in intrasubject, group, population, and connectivity analyses and the limits of these methods., (Published by Elsevier Inc.)

Background: Medial temporal lobe (MTL) atrophy is one of the key biomarkers to detect early neurodegenerative changes in the course of Alzheimer's disease (AD). There is active research aimed at identifying automated methodologies able to extract accurate classification indexes from T1-weighted magnetic resonance images (MRI). Such indexes should be fit for identifying AD patients as early as possible., Subjects: A reference group composed of 144AD patients and 189 age-matched controls was used to train and test the procedure. It was then applied on a study group composed of 302 MCI subjects, 136 having progressed to clinically probable AD (MCI-converters) and 166 having remained stable or recovered to normal condition after a 24month follow-up (MCI-non converters). All subjects came from the ADNI database., Methods: We sampled the brain with 7 relatively small volumes, mainly centered on the MTL, and 2 control regions. These volumes were filtered to give intensity and textural MRI-based features. Each filtered region was analyzed with a Random Forest (RF) classifier to extract relevant features, which were subsequently processed with a Support Vector Machine (SVM) classifier. Once a prediction model was trained and tested on the reference group, it was used to compute a classification index (CI) on the MCI cohort and to assess its accuracy in predicting AD conversion in MCI patients. The performance of the classification based on the features extracted by the whole 9 volumes is compared with that derived from each single volume. All experiments were performed using a bootstrap sampling estimation, and classifier performance was cross-validated with a 20-fold paradigm., Results: We identified a restricted set of image features correlated with the conversion to AD. It is shown that most information originate from a small subset of the total available features, and that it is enough to give a reliable assessment. We found multiple, highly localized image-based features which alone are responsible for the overall clinical diagnosis and prognosis. The classification index is able to discriminate Controls from AD with an Area Under Curve (AUC)=0.97 (sensitivity ≃89% at specificity ≃94%) and Controls from MCI-converters with an AUC=0.92 (sensitivity ≃89% at specificity ≃80%). MCI-converters are separated from MCI-non converters with AUC=0.74(sensitivity ≃72% at specificity ≃65%)., Findings: The present automated MRI-based technique revealed a strong relationship between highly localized baseline-MRI features and the baseline clinical assessment. In addition, the classification index was also used to predict the probability of AD conversion within a time frame of two years. The definition of a single index combining local analysis of several regions can be useful to detect AD neurodegeneration in a typical MCI population., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Response selection activates appropriate response representations to task-relevant environmental stimuli. Research implicates dorsolateral prefrontal cortex (dlPFC) for this process. On the other hand, studies of semantic selection, which activates verbal responses based on the semantic requirements of a task, implicate ventrolateral PFC (vlPFC). Despite this apparent dissociation, the neurocognitive distinction between response and semantic selection is controversial. The current functional MRI study attempts to resolve this controversy by investigating verbal response and semantic selection in the same participants. Participants responded vocally with a word to a visually presented noun, either from a memorized list of paired associates (response selection task), or by generating a semantically related verb (semantic selection task). We found a dissociation in left lateral PFC. Activation increased significantly in dlPFC with response selection difficulty, but not semantic selection difficulty. Conversely, semantic, but not response, selection difficulty increased activity significantly in vlPFC. Activity in left parietal cortex, on the other hand, was affected by difficulty increases in both selection tasks. These results suggest that response and semantic selection may be distinct cognitive processes mediated by different regions of lateral PFC; but both of these selection processes rely on cognitive mechanisms mediated by parietal cortex.

Refreshing is a basic reflective component process that can serve to prolong activation of task-relevant information. Neuroimaging work has shown that left middle frontal gyrus (MFG) and supramarginal gyrus (SMG) are selectively engaged during refreshing. Functional MRI (fMRI), however, is not able to determine if these regions are necessary for refreshing. In this experiment, we utilize repetitive transcranial magnetic stimulation (rTMS) to assess the behavioral effect of functionally deactivating these regions. We report a selective slowing of response times (RTs) to refresh words following MFG stimulation, consistent with a role of lateral prefrontal cortex (PFC) in top-down control mechanisms necessary for refreshing. In contrast, SMG stimulation slowed participants in both refreshing and repeating words, indicating a more general role of SMG in verbal processing.

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.

A new approach for analysis of event-related fMRI (BOLD) signals is proposed. The technique is based on measures from information theory and is used both for spatial localization of task-related activity, as well as for extracting temporal information regarding the task-dependent propagation of activation across different brain regions. This approach enables whole brain visualization of voxels (areas) most involved in coding of a specific task condition, the time at which they are most informative about the condition, as well as their average amplitude at that preferred time. The approach does not require prior assumptions about the shape of the hemodynamic response function (HRF) nor about linear relations between BOLD response and presented stimuli (or task conditions). We show that relative delays between different brain regions can also be computed without prior knowledge of the experimental design, suggesting a general method that could be applied for analysis of differential time delays that occur during natural, uncontrolled conditions. Here we analyze BOLD signals recorded during performance of a motor learning task. We show that, during motor learning, the BOLD response of unimodal motor cortical areas precedes the response in higher-order multimodal association areas, including posterior parietal cortex. Brain areas found to be associated with reduced activity during motor learning, predominantly in prefrontal brain regions, are informative about the task typically at significantly later times.

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.

Since its inception, experimental psychology has sought to account for individual differences in human performance. Some neuroimaging research, involving complex behavioral paradigms, has suggested that faster-performing individuals show greater neural activity than slower performers. Other research has suggested that faster-performing individuals show less neural activity than slower performers. To examine the neural basis of individual performance differences, we had participants perform a simple speeded-processing task during fMRI scanning. In some prefrontal cortical (PFC) brain regions, faster performers showed less cortical activity than slower performers while in other PFC and parietal regions they showed greater activity. Regional-causality analysis indicated that PFC exerted more influence over other brain regions for slower than for faster individuals. These results suggest that a critical determinant of individual performance differences is the efficiency of interactions between brain regions and that slower individuals may require more prefrontal executive control than faster individuals to perform successfully.

Maintaining relevant information for later use is a critical aspect of working memory (WM). The lateral prefrontal cortex (PFC) and posterior sensory cortical areas appear to be important in supporting maintenance. However, the relative and unique contributions of these areas remain unclear. We have designed a WM paradigm with distraction to probe the contents of maintenance representations in these regions. During delayed recognition trials of faces, selective interference was evident behaviorally with face distraction leading to significantly worse performance than with scene distraction. Event-related fMRI of the human brain showed that maintenance activity in the lateral PFC, but not in visual association cortex (VAC), was selectively disrupted by face distraction. Additionally, the functional connectivity between the lateral PFC and the VAC was perturbed during these trials. We propose a hierarchical and distributed model of active maintenance in which the lateral PFC codes for abstracted mnemonic information, while sensory areas represent specific features of the memoranda. Furthermore, persistent coactivation between the PFC and sensory areas may be a mechanism by which information is actively maintained.

Socrates said that in order to lead a balanced life one must, "know thyself." In two fMRI experiments, the present study examined the mechanisms mediating two ways in which the self can be known: through direct appraisals (i.e., an individual's own self-beliefs) and reflected appraisals (i.e., an individual's perception of how others view him or her). Experiment 1 examined the common and distinct neural bases of direct appraisals of the self, close others, and normative judgments of trait desirability. All three judgment types activated medial prefrontal cortex (MPFC) to a similar degree. Experiment 2 examined the common and distinct neural bases of (1) direct appraisals of self, a close other or a non-close other, and (2) reflected appraisals made from the perspective of a close or a non-close other. Consistent with Experiment 1, all judgment types activated MPFC. Direct appraisals of the self as compared to others more strongly recruited MPFC and right rostrolateral PFC. Direct appraisals as compared to reflected appraisals recruited regions associated with a first-person perspective (posterior cingulate), whereas reflected as compared to direct appraisals recruited regions associated with emotion and memory (insula, orbitofrontal, and temporal cortex). These results support models suggesting that MPFC mediates meta-cognitive processes that may be recruited for direct and reflected self appraisals depending upon the demands of a specific task.

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.

Widespread and distributed brain regions are thought to form networks that together support working memory. We recently demonstrated that different cortical areas maintain relatively different codes across a memory delay (Curtis et. al., J Neurosci, 2004; 24:3944-3952). The frontal eye fields (FEF), for example, were more active during the delay when the direction of the memory-guided saccade was known compared to when it was not known throughout the delay. Other areas showed the opposite pattern. Despite these task-dependent differences in regional activity, we could only assume but not address the functional interactions between the identified nodes of the putative network. Here, we use a bivariate technique, coherence, to formally characterize functional interactions between a seed region and other brain areas. We find that the type of representational codes that are being maintained in working memory biases frontal-parietal interactions. For example, coherence between FEF and other oculomotor areas was greater when a motor representation was an efficient strategy to bridge the delay period. However, coherence between the FEF and higher-order heteromodal areas, e.g., dorsolateral prefrontal cortex, was greater when a sensory representation must be maintained in working memory.

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.

Previous neuroimaging studies have shown that neural activity changes with task practice. The types of changes reported have been inconsistent, however, and the neural mechanisms involved remain unclear. In this study, we investigated the influence of practice on different component processes of working memory (WM) using a face WM task. Event-related functional magnetic resonance imaging (fMRI) methodology allowed us to examine signal changes from early to late in the scanning session within different task stages (i.e., encoding, delay, retrieval), as well as to determine the influence of different levels of WM load on neural activity. We found practice-related decreases in fMRI signal and effects of memory load occurring primarily during encoding. This suggests that practice improves encoding efficiency, especially at higher memory loads. The decreases in fMRI signal we observed were not accompanied by improved behavioral performance; in fact, error rate increased for high WM load trials, indicating that practice-related changes in activation may occur during a scanning session without behavioral evidence of learning. Our results suggest that practice influences particular component processes of WM differently, and that the efficiency of these processes may not be captured by performance measures alone.

Estimates of hemodynamic response functions (HRF) are often integral parts of event-related fMRI analyses. Although HRFs vary across individuals and brain regions, few studies have investigated how variations affect the results of statistical analyses using the general linear model (GLM). In this study, we empirically estimated HRFs from primary motor and visual cortices and frontal and supplementary eye fields (SEF) in 20 subjects. We observed more variability across subjects than regions and correlated variation of time-to-peak values across several pairs of regions. Simulations examined the effects of observed variability on statistical results and ways different experimental designs and statistical models can limit these effects. Widely spaced and rapid event-related experimental designs with two sampling rates were tested. Statistical models compared an empirically derived HRF to a canonical HRF and included the first derivative of the HRF in the GLM. Small differences between the estimated and true HRFs did not cause false negatives, but larger differences within an observed range of variation, such as a 2.5-s time-to-onset misestimate, led to false negatives. Although small errors minimally affected detection of activity, time-to-onset misestimates as small as 1 s influenced model parameter estimation and therefore random effects analyses across subjects. Experiment and analysis design methods such as decreasing the sampling rate or including the HRF's temporal derivative in the GLM improved results, but did not eliminate errors caused by HRF misestimates. These results highlight the benefits of determining the best possible HRF estimate and potential negative consequences of assuming HRF consistency across subjects or brain regions.

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.

The use of functional neuroimaging to test hypotheses regarding age-related changes in the neural substrates of cognitive processes relies on assumptions regarding the coupling of neural activity to neuroimaging signal. Differences in neuroimaging signal response between young and elderly subjects can be mapped directly to differences in neural response only if such coupling does not change with age. Here we examined spatial and temporal characteristics of the BOLD fMRI hemodynamic response in primary sensorimotor cortex in young and elderly subjects during the performance of a simple reaction time task. We found that 75% of elderly subjects (n = 20) exhibited a detectable voxel-wise relationship with the behavioral paradigm in this region as compared to 100% young subjects (n = 32). The median number of suprathreshold voxels in the young subjects was greater than four times that of the elderly subjects. Young subjects had a slightly greater signal:noise per voxel than the elderly subjects that was attributed to a greater level of noise per voxel in the elderly subjects. The evidence did not support the idea that the greater head motion observed in the elderly was the cause of this greater voxel-wise noise. There were no significant differences between groups in either the shape of the hemodynamic response or in its the within-group variability, although the former evidenced a near significant trend. The overall finding that some aspects of the hemodynamic coupling between neural activity and BOLD fMRI signal change with age cautions against simple interpretations of the results of imaging studies that compare young and elderly subjects., (Copyright 1999 Academic Press.)

An experimental design for functional MRI (fMRI) is presented whose conceptual units of analysis are behavioral trials, in contrast to blocks of trials. This type of design is referred to as a trial-based (TB) fMRI design. It is explained how TB designs can afford the ability to: (1) randomize the presentation of behavioral trials and (2) utilize intertrial variance in uncontrolled behavioral measures to examine their functional correlates. A particular type of TB design that involves modeling trial-evoked fMRI responses with one or more shifted impulse response functions is described. This design is capable of discriminating functional changes occurring during temporally separated behavioral subcomponents within trials. An example of such a design is implemented and its statistical specificity, functional sensitivity, and functional specificity are tested., (Copyright 1997 Academic Press.)