Randy L. Buckner

The brain’s default network: Anatomy, function, and relevance to disease

Thirty years of brain imaging research has converged to define the brains default network—a novel and only recently appreciated brain system that participates in internal modes of cognition. Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment. Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system. Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others. Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems. The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation. The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self‐relevant mental simulations. These two subsystems converge on important nodes of integration including the posterior cingulate cortex. The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world. We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimers disease.

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

The organization of the human cerebral cortex estimated by intrinsic functional connectivity

Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.

Self-Projection and the Brain

When thinking about the future or the upcoming actions of another person, we mentally project ourselves into that alternative situation. Accumulating data suggest that envisioning the future (prospection), remembering the past, conceiving the viewpoint of others (theory of mind) and possibly some forms of navigation reflect the workings of the same core brain network. These abilities emerge at a similar age and share a common functional anatomy that includes frontal and medial temporal systems that are traditionally associated with planning, episodic memory and default (passive) cognitive states. We speculate that these abilities, most often studied as distinct, rely on a common set of processes by which past experiences are used adaptively to imagine perspectives and events beyond those that emerge from the immediate environment.

Cortical Hubs Revealed by Intrinsic Functional Connectivity: Mapping, Assessment of Stability, and Relation to Alzheimer's Disease

Recent evidence suggests that some brain areas act as hubs interconnecting distinct, functionally specialized systems. These nexuses are intriguing because of their potential role in integration and also because they may augment metabolic cascades relevant to brain disease. To identify regions of high connectivity in the human cerebral cortex, we applied a computationally efficient approach to map the degree of intrinsic functional connectivity across the brain. Analysis of two separate functional magnetic resonance imaging datasets (each n = 24) demonstrated hubs throughout heteromodal areas of association cortex. Prominent hubs were located within posterior cingulate, lateral temporal, lateral parietal, and medial/lateral prefrontal cortices. Network analysis revealed that many, but not all, hubs were located within regions previously implicated as components of the default network. A third dataset (n = 12) demonstrated that the locations of hubs were present across passive and active task states, suggesting that they reflect a stable property of cortical network architecture. To obtain an accurate reference map, data were combined across 127 participants to yield a consensus estimate of cortical hubs. Using this consensus estimate, we explored whether the topography of hubs could explain the pattern of vulnerability in Alzheimers disease (AD) because some models suggest that regions of high activity and metabolism accelerate pathology. Positron emission tomography amyloid imaging in AD (n = 10) compared with older controls (n = 29) showed high amyloid-β deposition in the locations of cortical hubs consistent with the possibility that hubs, while acting as critical way stations for information processing, may also augment the underlying pathological cascade in AD.

Response and Habituation of the Human Amygdala during Visual Processing of Facial Expression

We measured amygdala activity in human volunteers during rapid visual presentations of fearful, happy, and neutral faces using functional magnetic resonance imaging (fMRI). The first experiment involved a fixed order of conditions both within and across runs, while the second one used a fully counterbalanced order in addition to a low level baseline of simple visual stimuli. In both experiments, the amygdala was preferentially activated in response to fearful versus neutral faces. In the counterbalanced experiment, the amygdala also responded preferentially to happy versus neutral faces, suggesting a possible generalized response to emotionally valenced stimuli. Rapid habituation effects were prominent in both experiments. Thus, the human amygdala responds preferentially to emotionally valenced faces and rapidly habituates to them.

Molecular, Structural, and Functional Characterization of Alzheimer's Disease: Evidence for a Relationship between Default Activity, Amyloid, and Memory

Alzheimers disease (AD) and antecedent factors associated with AD were explored using amyloid imaging and unbiased measures of longitudinal atrophy in combination with reanalysis of previous metabolic and functional studies. In total, data from 764 participants were compared across five in vivo imaging methods. Convergence of effects was seen in posterior cortical regions, including posterior cingulate, retrosplenial, and lateral parietal cortex. These regions were active in default states in young adults and also showed amyloid deposition in older adults with AD. At early stages of AD progression, prominent atrophy and metabolic abnormalities emerged in these posterior cortical regions; atrophy in medial temporal regions was also observed. Event-related functional magnetic resonance imaging studies further revealed that these cortical regions are active during successful memory retrieval in young adults. One possibility is that lifetime cerebral metabolism associated with regionally specific default activity predisposes cortical regions to AD-related changes, including amyloid deposition, metabolic disruption, and atrophy. These cortical regions may be part of a network with the medial temporal lobe whose disruption contributes to memory impairment.

Common blood flow changes across visual tasks: Ii. decreases in cerebral cortex

Nine previous positron emission tomography (PET) studies of human visual information processing were reanalyzed to determine the consistency across experiments of blood flow decreases during active tasks relative to passive viewing of the same stimulus array. Areas showing consistent decreases during active tasks included posterior cingulate/precuneous (Brodmann area, BA 31/7), left (BAS 40 and 39/19) and right (BA 40) inferior parietal cortex, left dorsolateral frontal cortex (BA S), left lateral inferior frontal cortex (BA 10/47), left inferior temporal gyrus @A 20), a strip of medial frontal regions running along a dorsal-ventral axis (BAs 8, 9, 10, and 32), and the right amygdala. Experiments involving language-related processes tended to show larger decreases than nonlanguage experiments. This trend mainly reflected blood flow increases at certain areas in the passive conditions of the language experiments (relative to a fixation control in which no task stimulus was present) and slight blood flow decreases in the passive conditions of the nonlanguage experiments. When the active tasks were referenced to the fixation condition, the overall size of blood flow decreases in language and nonlanguage tasks were the same, but differences were found across cortical areas. Decreases were more pronounced in the posterior cingulate/precuneous (BAS 31/7) and right inferior parietal cortex (BA 40) during language-related tasks and more pronounced in left inferior frontal cortex (BA 10/47) during nonlanguage tasks. Blood flow decreases did not generally show significant differences across the active task states within an experiment, but a verb-generation task produced larger decreases than a read task in right and left inferior parietal lobe (BA 40) and the posterior cingulate/precuneous (BA 31/7), while the read task produced larger decreases in left lateral inferior frontal cortex (BA 10/47). These effects mirrored those found between experiments in the language-nonlanguage comparison. Consistent active minus passive decreases may reflect decreased activity caused by active task processes that generalize over tasks or increased activity caused by passive task processes that are suspended during the active tasks. Increased activity during the passive condition might reflect ongoing processes, such as unconstrained verbally mediated thoughts and monitoring of the external environment, body, and emotional state.

The Influence of Head Motion on Intrinsic Functional Connectivity MRI

Functional connectivity MRI (fcMRI) has been widely applied to explore group and individual differences. A confounding factor is head motion. Children move more than adults, older adults more than younger adults, and patients more than controls. Head motion varies considerably among individuals within the same population. Here we explored the influence of head motion on fcMRI estimates. Mean head displacement, maximum head displacement, the number of micro movements (>0.1 mm), and head rotation were estimated in 1000 healthy, young adult subjects each scanned for two resting-state runs on matched 3T scanners. The majority of fcMRI variation across subjects was not linked to head motion. However, head motion had significant, systematic effects on fcMRI network measures. Head motion was associated with decreased functional coupling in the default and frontoparietal control networks--two networks characterized by coupling among distributed regions of association cortex. Other network measures increased with motion including estimates of local functional coupling and coupling between left and right motor regions--a region pair sometimes used as a control in studies to establish specificity. Comparisons between groups of individuals with subtly different levels of head motion yielded difference maps that could be mistaken for neuronal effects in other contexts. These effects are important to consider when interpreting variation between groups and across individuals.

Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization.

Resting state functional connectivity MRI (fcMRI) is widely used to investigate brain networks that exhibit correlated fluctuations. While fcMRI does not provide direct measurement of anatomic connectivity, accumulating evidence suggests it is sufficiently constrained by anatomy to allow the architecture of distinct brain systems to be characterized. fcMRI is particularly useful for characterizing large-scale systems that span distributed areas (e.g., polysynaptic cortical pathways, cerebro-cerebellar circuits, cortical-thalamic circuits) and has complementary strengths when contrasted with the other major tool available for human connectomics-high angular resolution diffusion imaging (HARDI). We review what is known about fcMRI and then explore fcMRI data reliability, effects of preprocessing, analysis procedures, and effects of different acquisition parameters across six studies (n = 98) to provide recommendations for optimization. Run length (2-12 min), run structure (1 12-min run or 2 6-min runs), temporal resolution (2.5 or 5.0 s), spatial resolution (2 or 3 mm), and the task (fixation, eyes closed rest, eyes open rest, continuous word-classification) were varied. Results revealed moderate to high test-retest reliability. Run structure, temporal resolution, and spatial resolution minimally influenced fcMRI results while fixation and eyes open rest yielded stronger correlations as contrasted to other task conditions. Commonly used preprocessing steps involving regression of nuisance signals minimized nonspecific (noise) correlations including those associated with respiration. The most surprising finding was that estimates of correlation strengths stabilized with acquisition times as brief as 5 min. The brevity and robustness of fcMRI positions it as a powerful tool for large-scale explorations of genetic influences on brain architecture. We conclude by discussing the strengths and limitations of fcMRI and how it can be combined with HARDI techniques to support the emerging field of human connectomics.