Jessica R. Andrews-Hanna

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.

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.

Disruption of Large-Scale Brain Systems in Advanced Aging

Cognitive decline is commonly observed in advanced aging even in the absence of disease. Here we explore the possibility that normal aging is accompanied by disruptive alterations in the coordination of large-scale brain systems that support high-level cognition. In 93 adults aged 18 to 93, we demonstrate that aging is characterized by marked reductions in normally present functional correlations within two higher-order brain systems. Anterior to posterior components within the default network were most severely disrupted with age. Furthermore, correlation reductions were severe in older adults free from Alzheimers disease (AD) pathology as determined by amyloid imaging, suggesting that functional disruptions were not the result of AD. Instead, reduced correlations were associated with disruptions in white matter integrity and poor cognitive performance across a range of domains. These results suggest that cognitive decline in normal aging arises from functional disruption in the coordination of large-scale brain systems that support cognition.

The default network and self-generated thought: component processes, dynamic control, and clinical relevance.

Though only a decade has elapsed since the default network (DN) was first defined as a large‐scale brain system, recent years have brought great insight into the networks adaptive functions. A growing theme highlights the DN as playing a key role in internally directed or self‐generated thought. Here, we synthesize recent findings from cognitive science, neuroscience, and clinical psychology to focus attention on two emerging topics as current and future directions surrounding the DN. First, we present evidence that self‐generated thought is a multifaceted construct whose component processes are supported by different subsystems within the network. Second, we highlight the dynamic nature of the DN, emphasizing its interaction with executive control systems when regulating aspects of internal thought. We conclude by discussing clinical implications of disruptions to the integrity of the network, and consider disorders when thought content becomes polarized or network interactions become disrupted or imbalanced.

The Brain’s Default Network and Its Adaptive Role in Internal Mentation

During the many idle moments that comprise daily life, the human brain increases its activity across a set of midline and lateral cortical brain regions known as the “default network.” Despite the robustness with which the brain defaults to this pattern of activity, surprisingly little is known about the network’s precise anatomical organization and adaptive functions. To provide insight into these questions, this article synthesizes recent literature from structural and functional imaging with a growing behavioral literature on mind wandering. Results characterize the default network as a set of interacting hubs and subsystems that play an important role in “internal mentation”—the introspective and adaptive mental activities in which humans spontaneously and deliberately engage in every day.

Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity

IMPORTANCE Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive. OBJECTIVE To investigate network dysfunction in MDD through a meta-analysis of rsFC studies. DATA SOURCES Seed-based voxelwise rsFC studies comparing individuals with MDD with healthy controls (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web of Science, and EMBASE) and authors contacted for additional data. STUDY SELECTION Twenty-seven seed-based voxel-wise rsFC data sets from 25 publications (556 individuals with MDD and 518 healthy controls) were included in the meta-analysis. DATA EXTRACTION AND SYNTHESIS Coordinates of seed regions of interest and between-group effects were extracted. Seeds were categorized into seed-networks by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive or reduced negative connectivity) or hypoconnectivity (increased negative or reduced positive connectivity) with each seed-network. RESULTS Major depressive disorder was characterized by hypoconnectivity within the frontoparietal network, a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network involved in attending to the external environment. Major depressive disorder was also associated with hyperconnectivity within the default network, a network believed to support internally oriented and self-referential thought, and hyperconnectivity between frontoparietal control systems and regions of the default network. Finally, the MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline cortical regions that may mediate top-down regulation of such functions. CONCLUSIONS AND RELEVANCE Reduced connectivity within frontoparietal control systems and imbalanced connectivity between control systems and networks involved in internal or external attention may reflect depressive biases toward internal thoughts at the cost of engaging with the external world. Meanwhile, altered connectivity between neural systems involved in cognitive control and those that support salience or emotion processing may relate to deficits regulating mood. These findings provide an empirical foundation for a neurocognitive model in which network dysfunction underlies core cognitive and affective abnormalities in depression.

Distinct Cortical Anatomy Linked to Subregions of the Medial Temporal Lobe Revealed by Intrinsic Functional Connectivity

The hippocampus and adjacent cortical structures in the medial temporal lobe (MTL) contribute to memory through interactions with distributed brain areas. Studies of monkey and rodent anatomy suggest that parallel pathways converge on distinct subregions of the MTL. To explore the cortical areas linked to subregions of the MTL in humans, we examined cortico-cortical and hippocampal-cortical correlations using high-resolution, functional connectivity analysis in 100 individuals. MTL seed regions extended along the anterior to posterior axis and included hippocampus and adjacent structures. Results revealed two separate brain pathways that correlated with distinct subregions within the MTL. The body of the hippocampus and posterior parahippocampal cortex correlated with lateral parietal cortex, regions along the posterior midline including posterior cingulate and retrosplenial cortex, and ventral medial prefrontal cortex. By contrast, anterior hippocampus and the perirhinal/entorhinal cortices correlated with distinct regions in the lateral temporal cortex extending into the temporal pole. The present results are largely consistent with known connectivity in the monkey and provide a novel task-independent dissociation of the parallel pathways supporting the MTL memory system in humans. The cortical pathways include regions that have undergone considerable areal expansion in humans, providing insight into how the MTL memory system has evolved to support a diverse array of cognitive domains.

The wandering brain: meta-analysis of functional neuroimaging studies of mind-wandering and related spontaneous thought processes.

The neural basis and cognitive functions of various spontaneous thought processes, particularly mind-wandering, are increasingly being investigated. Although strong links have been drawn between the occurrence of spontaneous thought processes and activation in brain regions comprising the default mode network (DMN), spontaneous thought also appears to recruit other, non-DMN regions just as consistently. Here we present the first quantitative meta-analysis of neuroimaging studies of spontaneous thought and mind-wandering in order to address the question of their neural correlates. Examining 24 functional neuroimaging studies of spontaneous thought processes, we conducted a meta-analysis using activation likelihood estimation (ALE). A number of key DMN areas showed consistent recruitment across studies, including medial prefrontal cortex, posterior cingulate cortex, medial temporal lobe, and bilateral inferior parietal lobule. Numerous non-DMN regions, however, were also consistently recruited, including rostrolateral prefrontal cortex, dorsal anterior cingulate cortex, insula, temporopolar cortex, secondary somatosensory cortex, and lingual gyrus. These meta-analytic results indicate that DMN activation alone is insufficient to adequately capture the neural basis of spontaneous thought; frontoparietal control network areas, and other non-DMN regions, appear to be equally central. We conclude that further progress in the cognitive and clinical neuroscience of spontaneous thought will therefore require a re-balancing of our view of the contributions of various regions and networks throughout the brain, and beyond the DMN.

Mind-wandering as spontaneous thought: a dynamic framework.

Most research on mind-wandering has characterized it as a mental state with contents that are task unrelated or stimulus independent. However, the dynamics of mind-wandering — how mental states change over time — have remained largely neglected. Here, we introduce a dynamic framework for understanding mind-wandering and its relationship to the recruitment of large-scale brain networks. We propose that mind-wandering is best understood as a member of a family of spontaneous-thought phenomena that also includes creative thought and dreaming. This dynamic framework can shed new light on mental disorders that are marked by alterations in spontaneous thought, including depression, anxiety and attention deficit hyperactivity disorder.

Separate neural representations for physical pain and social rejection

Current theories suggest that physical pain and social rejection share common neural mechanisms, largely by virtue of overlapping functional magnetic resonance imaging (fMRI) activity. Here we challenge this notion by identifying distinct multivariate fMRI patterns unique to pain and rejection. Sixty participants experience painful heat and warmth and view photos of ex-partners and friends on separate trials. FMRI pattern classifiers discriminate pain and rejection from their respective control conditions in out-of-sample individuals with 92% and 80% accuracy. The rejection classifier performs at chance on pain, and vice versa. Pain- and rejection-related representations are uncorrelated within regions thought to encode pain affect (for example, dorsal anterior cingulate) and show distinct functional connectivity with other regions in a separate resting-state data set (N = 91). These findings demonstrate that separate representations underlie pain and rejection despite common fMRI activity at the gross anatomical level. Rather than co-opting pain circuitry, rejection involves distinct affective representations in humans.