Contributions of episodic retrieval and mentalizing to autobiographical thought: evidence from functional neuroimaging, resting-state connectivity, and fMRI meta-analyses

Self and other body perception in anorexia nervosa: The role of posterior DMN nodes

OBJECTIVES

Body image distortion is a core symptom of anorexia nervosa (AN), which involves alterations in self- (and other's) evaluative processes arising during body perception. At a neural level, self-related information is thought to rely on areas of the so-called default mode network (DMN), which, additionally, shows prominent synchronised activity at rest.

METHODS

Twenty female patients with AN and 20 matched healthy controls were scanned using magnetic resonance imaging when: (a) viewing video clips of their own body and another's body; (b) at rest. Between-group differences within the DMN during task performance were evaluated and further explored for task-related and resting-state-related functional connectivity alterations.

RESULTS

AN patients showed a hyperactivation of the dorsal posterior cingulate cortex during their own-body processing but a response failure to another's body processing at the precuneus and ventral PCC. Increased task-related connectivity was found between dPCC-dorsal anterior cingulate cortex and precuneus-mid-temporal cortex. Further, AN patients showed decreased resting-state connectivity between the dPCC and the angular gyrus.

CONCLUSIONS

The PCC and the precuneus are suggested as key components of a network supporting self-other-evaluative processes implicated in body distortion, while the existence of DMN alterations at rest might reflect a sustained, task-independent breakdown within this network in AN.

The Neural Basis of Successful Word Reading in Aphasia

Understanding the neural basis of recovery from stroke is a major research goal. Many functional neuroimaging studies have identified changes in brain activity in people with aphasia, but it is unclear whether these changes truly support successful performance or merely reflect increased task difficulty. We addressed this problem by examining differences in brain activity associated with correct and incorrect responses on an overt reading task. On the basis of previous proposals that semantic retrieval can assist pronunciation of written words, we hypothesized that recruitment of semantic areas would be greater on successful trials. Participants were 21 patients with left-hemisphere stroke with phonologic retrieval deficits. They read words aloud during an event-related fMRI paradigm. BOLD signals obtained during correct and incorrect trials were contrasted to highlight brain activity specific to successful trials. Successful word reading was associated with higher BOLD signal in the left angular gyrus. In contrast, BOLD signal in bilateral posterior inferior frontal cortex, SMA, and anterior cingulate cortex was greater on incorrect trials. These data show for the first time the brain regions where neural activity is correlated specifically with successful performance in people with aphasia. The angular gyrus is a key node in the semantic network, consistent with the hypothesis that additional recruitment of the semantic system contributes to successful word production when phonologic retrieval is impaired. Higher activity in other brain regions during incorrect trials likely reflects secondary engagement of attention, working memory, and error monitoring processes when phonologic retrieval is unsuccessful.

Mind-Wandering in People with Hippocampal Damage

Subjective inner experiences, such as mind-wandering, represent the fundaments of human cognition. Although the precise function of mind-wandering is still debated, it is increasingly acknowledged to have influence across cognition on processes such as future planning, creative thinking, and problem-solving and even on depressive rumination and other mental health disorders. Recently, there has been important progress in characterizing mind-wandering and identifying the associated neural networks. Two prominent features of mind-wandering are mental time travel and visuospatial imagery, which are often linked with the hippocampus. People with selective bilateral hippocampal damage cannot vividly recall events from their past, envision their future, or imagine fictitious scenes. This raises the question of whether the hippocampus plays a causal role in mind-wandering and, if so, in what way. Leveraging a unique opportunity to shadow people (all males) with bilateral hippocampal damage for several days, we examined, for the first time, what they thought about spontaneously, without direct task demands. We found that they engaged in as much mind-wandering as control participants. However, whereas controls thought about the past, present, and future, imagining vivid visual scenes, hippocampal damage resulted in thoughts primarily about the present comprising verbally mediated semantic knowledge. These findings expose the hippocampus as a key pillar in the neural architecture of mind-wandering and also reveal its impact beyond episodic memory, placing it at the heart of our mental life.SIGNIFICANCE STATEMENT Humans tend to mind-wander ∼30-50% of their waking time. Two prominent features of this pervasive form of thought are mental time travel and visuospatial imagery, which are often associated with the hippocampus. To examine whether the hippocampus plays a causal role in mind-wandering, we examined the frequency and phenomenology of mind-wandering in patients with selective bilateral hippocampal damage. We found that they engaged in as much mind-wandering as controls. However, hippocampal damage changed the form and content of mind-wandering from flexible, episodic, and scene based to abstract, semanticized, and verbal. These findings expose the hippocampus as a key pillar in the neural architecture of mind-wandering and reveal its impact beyond episodic memory, placing it at the heart of our mental life.

Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks

The frontoparietal control network (FPCN) plays a central role in executive control. It has been predominantly viewed as a unitary domain general system. Here, we examined patterns of FPCN functional connectivity (FC) across multiple conditions of varying cognitive demands, to test for FPCN heterogeneity. We identified two distinct subsystems within the FPCN based on hierarchical clustering and machine learning classification analyses of within-FPCN FC patterns. These two FPCN subsystems exhibited distinct patterns of FC with the default network (DN) and the dorsal attention network (DAN). FPCN_A exhibited stronger connectivity with the DN than the DAN, whereas FPCN_B exhibited the opposite pattern. This twofold FPCN differentiation was observed across four independent datasets, across nine different conditions (rest and eight tasks), at the level of individual-participant data, as well as in meta-analytic coactivation patterns. Notably, the extent of FPCN differentiation varied across conditions, suggesting flexible adaptation to task demands. Finally, we used meta-analytic tools to identify several functional domains associated with the DN and DAN that differentially predict activation in the FPCN subsystems. These findings reveal a flexible and heterogeneous FPCN organization that may in part emerge from separable DN and DAN processing streams. We propose that FPCN_A may be preferentially involved in the regulation of introspective processes, whereas FPCN_B may be preferentially involved in the regulation of visuospatial perceptual attention.

Heterogeneity within the frontoparietal control network and its relationship to the default and dorsal attention networks

The frontoparietal control network (FPCN) plays a central role in executive control. It has been predominantly viewed as a unitary domain general system. Here, we examined patterns of FPCN functional connectivity (FC) across multiple conditions of varying cognitive demands, to test for FPCN heterogeneity. We identified two distinct subsystems within the FPCN based on hierarchical clustering and machine learning classification analyses of within-FPCN FC patterns. These two FPCN subsystems exhibited distinct patterns of FC with the default network (DN) and the dorsal attention network (DAN). FPCN_A exhibited stronger connectivity with the DN than the DAN, whereas FPCN_B exhibited the opposite pattern. This twofold FPCN differentiation was observed across four independent datasets, across nine different conditions (rest and eight tasks), at the level of individual-participant data, as well as in meta-analytic coactivation patterns. Notably, the extent of FPCN differentiation varied across conditions, suggesting flexible adaptation to task demands. Finally, we used meta-analytic tools to identify several functional domains associated with the DN and DAN that differentially predict activation in the FPCN subsystems. These findings reveal a flexible and heterogeneous FPCN organization that may in part emerge from separable DN and DAN processing streams. We propose that FPCN_A may be preferentially involved in the regulation of introspective processes, whereas FPCN_B may be preferentially involved in the regulation of visuospatial perceptual attention.

The medial temporal lobe functional connectivity patterns associated with forming different mental representations

The medial temporal lobes (MTL), and more specifically the hippocampus, are critical for forming mental representations of past experiences-autobiographical memories-and for forming other "nonexperienced" types of mental representations, such as imagined scenarios. How the MTL coordinate with other brain areas to create these different types of representations is not well understood. To address this issue, we performed a task-based functional connectivity analysis on a previously published dataset in which fMRI data were collected as participants created different types of mental representations under three conditions. One condition required forming and relating together details from a past event (autobiographical task), another required forming and relating together details of a spatial context (spatial task) and another condition required relating together conceptual/perceptual features of an object (conceptual task). We contrasted the connectivity patterns associated with a functionally defined region in the parahippocampal cortex (PHC) and anatomically defined anterior and posterior hippocampal segments across these tasks. Examining PHC connectivity patterns revealed that the PHC seed was distinctly connected to other MTL structures during the autobiographical task, to posterior parietal regions during the spatial task and to a distributed network of regions for the conceptual task. Examining hippocampal connectivity patterns revealed that the anterior hippocampus was preferentially connected to regions of default mode network during the autobiographical task and to areas implicated in semantic processing for the conceptual task whereas the posterior hippocampus was preferentially connected to medial-posterior regions of the brain during the spatial task. We interpret our findings as evidence that there are MTL-guided networks for forming distinct types of mental representations that align with functional distinctions within the hippocampus.

Resting state brain networks in the prairie vole

Resting state functional magnetic resonance imaging (rsfMRI) has shown the hierarchical organization of the human brain into large-scale complex networks, referred as resting state networks. This technique has turned into a promising translational research tool after the finding of similar resting state networks in non-human primates, rodents and other animal models of great value for neuroscience. Here, we demonstrate and characterize the presence of resting states networks in Microtus ochrogaster, the prairie vole, an extraordinary animal model to study complex human-like social behavior, with potential implications for the research of normal social development, addiction and neuropsychiatric disorders. Independent component analysis of rsfMRI data from isoflurane-anestethized prairie voles resulted in cortical and subcortical networks, including primary motor and sensory networks, but also included putative salience and default mode networks. We further discuss how future research could help to close the gap between the properties of the large scale functional organization and the underlying neurobiology of several aspects of social cognition. These results contribute to the evidence of preserved resting state brain networks across species and provide the foundations to explore the use of rsfMRI in the prairie vole for basic and translational research.

The default network and the combination of cognitive processes that mediate self-generated thought

Self-generated cognitions, such as recalling personal memories or empathizing with others, are ubiquitous and essential for our lives. Such internal mental processing is ascribed to the Default Mode Network, a large network of the human brain, though the underlying neural and cognitive mechanisms remain poorly understood. Here, we tested the hypothesis that our mental experience is mediated by a combination of activities of multiple cognitive processes. Our study included four functional MRI experiments with the same participants and a wide range of cognitive tasks, as well as an analytical approach that afforded the identification of cognitive processes during self-generated cognition. We showed that several cognitive processes functioned simultaneously during self-generated mental activity. The processes had specific and localized neural representations, suggesting that they support different aspects of internal processing. Overall, we demonstrate that internally directed experience may be achieved by pooling over multiple cognitive processes.

Neural congruence between intertemporal and interpersonal self-control: Evidence from delay and social discounting

Behavioral studies using delay and social discounting as indices of self-control and altruism, respectively, have revealed functional similarities between farsighted and social decisions. However, neural evidence for this functional link is lacking. Twenty-five young adults completed a delay and social discounting task during fMRI scanning. A spatiotemporal partial least squares analysis revealed that both forms of discounting were well characterized by a pattern of brain activity in areas comprising frontoparietal control, default, and mesolimbic reward networks. Both forms of discounting appear to draw on common neurocognitive mechanisms, regardless of whether choices involve intertemporal or interpersonal outcomes. We also observed neural profiles differentiating between high and low discounters. High discounters were well characterized by increased medial temporal lobe and limbic activity. In contrast, low discount rates were associated with activity in the medial prefrontal cortex and right temporoparietal junction. This pattern may reflect biological mechanisms underlying behavioral heterogeneity in discount rates.

Taking tests in the magnet: Brain mapping standardized tests

Standardized psychometric tests are sophisticated, well-developed, and consequential instruments; test outcomes are taken as facts about people that impact their lives in important ways. As part of an initial demonstration that human brain mapping techniques can add converging neural-level evidence to understanding standardized tests, our participants completed items from standardized tests during an fMRI scan. We compared tests for diagnosing posttraumatic stress disorder (PTSD) and the correlated measures of Neuroticism, Attachment, and Centrality of Event to a general-knowledge baseline test. Twenty-three trauma-exposed participants answered 20 items for each of our five tests in each of the three runs for a total of 60 items per test. The tests engaged different neural processes; which test a participant was taking was accurately predicted from other participants' brain activity. The novelty of the application precluded specific anatomical predictions; however, the interpretation of activated regions using meta-analyses produced encouraging results. For instance, items on the Attachment test engaged regions shown to be more active for tasks involving judgments of others than judgments of the self. The results are an initial demonstration of a theoretically and practically important test-taking neuroimaging paradigm and suggest specific neural processes in answering PTSD-related tests. Hum Brain Mapp 38:5706-5725, 2017. © 2017 Wiley Periodicals, Inc.

Decoding brain activity using a large-scale probabilistic functional-anatomical atlas of human cognition

A central goal of cognitive neuroscience is to decode human brain activity—that is, to infer mental processes from observed patterns of whole-brain activation. Previous decoding efforts have focused on classifying brain activity into a small set of discrete cognitive states. To attain maximal utility, a decoding framework must be open-ended, systematic, and context-sensitive—that is, capable of interpreting numerous brain states, presented in arbitrary combinations, in light of prior information. Here we take steps towards this objective by introducing a probabilistic decoding framework based on a novel topic model—Generalized Correspondence Latent Dirichlet Allocation—that learns latent topics from a database of over 11,000 published fMRI studies. The model produces highly interpretable, spatially-circumscribed topics that enable flexible decoding of whole-brain images. Importantly, the Bayesian nature of the model allows one to “seed” decoder priors with arbitrary images and text—enabling researchers, for the first time, to generate quantitative, context-sensitive interpretations of whole-brain patterns of brain activity.

A central goal of cognitive neuroscience is to decode human brain activity—i.e., to be able to infer mental processes from observed patterns of whole-brain activity. However, existing approaches to brain decoding suffer from a number of important limitations—for example, they often work only in one narrow domain of cognition, and cannot be easily generalized to novel contexts. Here we address such limitations by introducing a simple probabilistic framework based on a novel topic modeling approach. We use our approach to extract a set of highly interpretable latent “topics” from a large meta-analytic database of over 11,000 published fMRI studies. Each topic is associated with a single brain region and a set of semantically coherent cognitive functions. We demonstrate how these topics can be used to automatically “decode” brain activity in an open-ended way, enabling researchers to draw tentative conclusions about mental function on the basis of virtually any pattern of whole-brain activity. We highlight several important features of our framework, notably including the ability to take into account knowledge of the experimental context and/or prior experimenter belief.

Parallel Interdigitated Distributed Networks within the Individual Estimated by Intrinsic Functional Connectivity

Certain organizational features of brain networks present in the individual are lost when central tendencies are examined in the group. Here we investigated the detailed network organization of four individuals each scanned 24 times using MRI. We discovered that the distributed network known as the default network is comprised of two separate networks possessing adjacent regions in eight or more cortical zones. A distinction between the networks is that one is coupled to the hippocampal formation while the other is not. Further exploration revealed that these two networks were juxtaposed with additional networks that themselves fractionate group-defined networks. The collective networks display a repeating spatial progression in multiple cortical zones, suggesting that they are embedded within a broad macroscale gradient. Regions contributing to the newly defined networks are spatially variable across individuals and adjacent to distinct networks, raising issues for network estimation in group-averaged data and applied endeavors, including targeted neuromodulation.

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Within-individual characterization of brain networks reveals new spatial details

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Group-defined networks fractionate into distinct parallel networks in individuals

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Parallel networks possess closely juxtaposed regions in numerous cortical zones

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Networks share a conserved motif that may be organized along a macroscale gradient

Intrinsic neural network dysfunction in quiescent Crohn's Disease

Psychological factors and comorbidities play an important role in inflammatory bowel diseases. Such comorbidity could be associated with a specific neural phenotype. Brain regions associated with emotion regulation and self-referential processing, including areas assigned to the “default mode network” (DMN), could be promising candidates in this regard. We investigated the functional integrity of multiple intrinsic neural networks in remitted patients with Crohn’s disease (CD) and sought to establish relationships between neural network connectivity and psychiatric symptoms. Fifteen CD patients in remission and 14 controls were investigated. We employed resting-state functional magnetic resonance imaging (fMRI) at 3 Tesla followed by a spatial Independent Component Analysis for fMRI data. Abnormal connectivity in CD patients was observed in DMN subsystems only (p < 0.05, cluster-corrected). Increased connectivity was found in the anterior cingulate and left superior medial frontal gyrus (aDMN) and the middle cingulate cortex (pDMN). Middle cingulate activity showed a significant association with anxiety scores in patients (p = 0.029). This study provides first evidence of selectively disrupted intrinsic neural network connectivity in CD and suggests abnormalities of self-referential neural networks. An increased sensitivity to self-related affective and somatic states in CD patients could account for these findings and explain a higher risk for anxiety symptoms.

Distinct contributions of the fornix and inferior longitudinal fasciculus to episodic and semantic autobiographical memory

Autobiographical memory (AM) is multifaceted, incorporating the vivid retrieval of contextual detail (episodic AM), together with semantic knowledge that infuses meaning and coherence into past events (semantic AM). While neuropsychological evidence highlights a role for the hippocampus and anterior temporal lobe (ATL) in episodic and semantic AM, respectively, it is unclear whether these constitute dissociable large-scale AM networks. We used high angular resolution diffusion-weighted imaging and constrained spherical deconvolution-based tractography to assess white matter microstructure in 27 healthy young adult participants who were asked to recall past experiences using word cues. Inter-individual variation in the microstructure of the fornix (the main hippocampal input/output pathway) related to the amount of episodic, but not semantic, detail in AMs - independent of memory age. Conversely, microstructure of the inferior longitudinal fasciculus, linking occipitotemporal regions with ATL, correlated with semantic, but not episodic, AMs. Further, these significant correlations remained when controlling for hippocampal and ATL grey matter volume, respectively. This striking correlational double dissociation supports the view that distinct, large-scale distributed brain circuits underpin context and concepts in AM.

Contextual and Developmental Differences in the Neural Architecture of Cognitive Control

Because both development and context impact functional brain architecture, the neural connectivity signature of a cognitive or affective predisposition may similarly vary across different ages and circumstances. To test this hypothesis, we investigated the effects of age and cognitive versus social-affective context on the stable and time-varying neural architecture of inhibition, the putative core cognitive control component, in a subsample (N = 359, 22-36 years, 174 men) of the Human Connectome Project. Among younger individuals, a neural signature of superior inhibition emerged in both stable and dynamic connectivity analyses. Dynamically, a context-free signature emerged as stronger segregation of internal cognition (default mode) and environmentally driven control (salience, cingulo-opercular) systems. A dynamic social-affective context-specific signature was observed most clearly in the visual system. Stable connectivity analyses revealed both context-free (greater default mode segregation) and context-specific (greater frontoparietal segregation for higher cognitive load; greater attentional and environmentally driven control system segregation for greater reward value) signatures of inhibition. Superior inhibition in more mature adulthood was typified by reduced segregation in the default network with increasing reward value and increased ventral attention but reduced cingulo-opercular and subcortical system segregation with increasing cognitive load. Failure to evidence this neural profile after the age of 30 predicted poorer life functioning. Our results suggest that distinguishable neural mechanisms underlie individual differences in cognitive control during different young adult stages and across tasks, thereby underscoring the importance of better understanding the interplay among dispositional, developmental, and contextual factors in shaping adaptive versus maladaptive patterns of thought and behavior.SIGNIFICANCE STATEMENT The brain's functional architecture changes across different contexts and life stages. To test whether the neural signature of a trait similarly varies, we investigated cognitive versus social-affective context effects on the stable and time-varying neural architecture of inhibition during a period of neurobehavioral fine-tuning (age 22-36 years). Younger individuals with superior inhibition showed distinguishable context-free and context-specific neural profiles, evidenced in both static and dynamic connectivity analyses. More mature individuals with superior inhibition evidenced only context-specific profiles, revealed in the static connectivity patterns linked to increased reward or cognitive load. Delayed expression of this profile predicted poorer life functioning. Our results underscore the importance of understanding the interplay among dispositional, developmental, and contextual factors in shaping behavior.

Remembering and imagining alternative versions of the personal past

Although autobiographical memory and episodic simulations recruit similar core brain regions, episodic simulations engage additional neural recruitment in the frontoparietal control network due to greater demands on constructive processes. However, previous functional neuroimaging studies showing differences in remembering and episodic simulation have focused on veridical retrieval of past experiences, and thus have not fully considered how retrieving the past in different ways from how it was originally experienced may also place similar demands on constructive processes. Here we examined how alternative versions of the past are constructed when adopting different egocentric perspectives during autobiographical memory retrieval compared to simulating hypothetical events from the personal past that could have occurred, or episodic counterfactual thinking. Participants were asked to generate titles for specific autobiographical memories from the last five years, and then, during functional magnetic resonance (fMRI) scanning, were asked to repeatedly retrieve autobiographical memories or imagine counterfactual events cued by the titles. We used an fMRI adaptation paradigm in order to isolate neural regions that were sensitive to adopting alternative egocentric perspectives and counterfactual simulations of the personal past. The fMRI results revealed that voxels within left posterior inferior parietal and ventrolateral frontal cortices were sensitive to novel visual perspectives and counterfactual simulations. Our findings suggest that the neural regions supporting remembering become more similar to those underlying episodic simulation when we adopt alternative egocentric perspectives of the veridical past.

Multi-echo EPI of human fear conditioning reveals improved BOLD detection in ventromedial prefrontal cortex

Standard T₂^* weighted functional magnetic resonance imaging (fMRI) performed with echo-planar imaging (EPI) suffers from signal loss in the ventromedial prefrontal cortex (vmPFC) due to macroscopic field inhomogeneity. However, this region is of special interest to affective neuroscience and psychiatry. The Multi-echo EPI (MEPI) approach has several advantages over EPI but its performance against EPI in the vmPFC has not yet been examined in a study with sufficient statistical power using a task specifically eliciting activity in this region. We used a fear conditioning task with MEPI to compare the performance of MEPI and EPI in vmPFC and control regions in 32 healthy young subjects. We analyzed activity associated with short (12ms), standard (29ms) and long (46ms) echo times, and a voxel-wise combination of these three echo times. Behavioral data revealed successful differentiation of the conditioned versus safety stimulus; activity in the vmPFC was shown by the contrast "safety stimulus > conditioned stimulus" as in previous research and proved significantly stronger with the combined MEPI than standard single-echo EPI. Then, we aimed to demonstrate that the additional cluster extent (ventral extension) detected in the vmPFC with MEPI reflects activation in a relevant cluster (i.e., not just non-neuronal noise). To do this, we used resting state data from the same subjects to show that the time-course of this region was both connected to bilateral amygdala and the default mode network. Overall, we demonstrate that MEPI (by means of the weighted sum combination approach) outperforms standard EPI in vmPFC; MEPI performs always at least as good as the best echo time for a given brain region but provides all necessary echo times for an optimal BOLD sensitivity for the whole brain. This is relevant for affective neuroscience and psychiatry given the critical role of the vmPFC in emotion regulation.

Heterogeneous fractionation profiles of meta-analytic coactivation networks

Computational cognitive neuroimaging approaches can be leveraged to characterize the hierarchical organization of distributed, functionally specialized networks in the human brain. To this end, we performed large-scale mining across the BrainMap database of coordinate-based activation locations from over 10,000 task-based experiments. Meta-analytic coactivation networks were identified by jointly applying independent component analysis (ICA) and meta-analytic connectivity modeling (MACM) across a wide range of model orders (i.e., d=20-300). We then iteratively computed pairwise correlation coefficients for consecutive model orders to compare spatial network topologies, ultimately yielding fractionation profiles delineating how "parent" functional brain systems decompose into constituent "child" sub-networks. Fractionation profiles differed dramatically across canonical networks: some exhibited complex and extensive fractionation into a large number of sub-networks across the full range of model orders, whereas others exhibited little to no decomposition as model order increased. Hierarchical clustering was applied to evaluate this heterogeneity, yielding three distinct groups of network fractionation profiles: high, moderate, and low fractionation. BrainMap-based functional decoding of resultant coactivation networks revealed a multi-domain association regardless of fractionation complexity. Rather than emphasize a cognitive-motor-perceptual gradient, these outcomes suggest the importance of inter-lobar connectivity in functional brain organization. We conclude that high fractionation networks are complex and comprised of many constituent sub-networks reflecting long-range, inter-lobar connectivity, particularly in fronto-parietal regions. In contrast, low fractionation networks may reflect persistent and stable networks that are more internally coherent and exhibit reduced inter-lobar communication.

The spatiotemporal substrates of autobiographical recollection: Using event-related ICA to study cognitive networks in action

Higher cognitive functions depend upon dynamically unfolding brain network interactions. Autobiographical recollection - the autonoetic re-experiencing of context rich, emotionally laden, personally experienced episodes - is an excellent example of such a process. Autobiographical recollection unfolds over time, with different cognitive processes engaged at different times throughout. In this paper we apply a recently developed analysis technique - event related independent components analysis (eICA) - to study the spatiotemporal dynamics of neural activity supporting autobiographical recollection. Participants completed an in-scanner autobiographical recollection paradigm in which the recalled episodes varied in chronological age and emotional content. By combining eICA with these cognitive manipulations we show that the brain-wide response to autobiographical recollection comprises brain networks with (i) different sensitivities to psychological aspects of the to-be-recollected material and (ii) distinct temporal profiles of activity during recollection. We identified networks with transient activations (in language and cognitive control related regions) and deactivations (in auditory and sensorimotor regions) to each autobiographical probe question, as well as networks with responses that are sustained over the course of the recollection period. These latter networks together overlapped spatially with the broader default mode network (DMN), indicating subspecialisation within the DMN. The vividness of participants' recollection was associated with the magnitude of activation in left dorsolateral prefrontal cortex and deactivation in visual association cortices. We interpret our results in the context of current theories of the spatial and temporal organisation of the human autobiographical memory system. Our findings demonstrate the utility of eICA as a tool for studying higher cognitive functions. The application of eICA to high spatial and temporal resolution datasets identifies in a single experimental protocol spatially specific networks that are recruited during cognitive activity, as well as the temporal order of activation of these networks.

Rumination and Default Mode Network Subsystems Connectivity in First-episode, Drug-Naive Young Patients with Major Depressive Disorder

Neuroimaging evidence implicates the association between rumination and default mode network (DMN) in major depressive disorder (MDD). However, the relationship between rumination and DMN subsystems remains incompletely understood, especially in patients with MDD. Thirty-three first-episode drug-naive patients with MDD and thirty-three healthy controls (HCs) were enrolled and underwent resting-sate fMRI scanning. Functional connectivity analysis was performed based on 11 pre-defined regions of interest (ROIs) for three DMN subsystems: the midline core, dorsal medial prefrontal cortex (dMPFC) and medial temporal lobe (MTL). Compared with HCs group, patients with MDD exhibited increased within-system connectivity in the dMPFC subsystem and inter-system connectivity between the dMPFC and MTL subsystems. Decreased inter-system connectivity was identified between the midline core and dMPFC subsystem in MDD patients. Depressive rumination was positively correlated with within-system connectivity in the dMPFC subsystem (dMPFC-TempP) and with inter-system connectivity between the dMPFC and MTL subsystems (LTC-PHC). Our results suggest MDD may be characterized by abnormal DMN subsystems connectivity, which may contribute to the pathophysiology of the maladaptive self-focus in MDD patients.

Regional homogeneity associated with overgeneral autobiographical memory of first-episode treatment-naive patients with major depressive disorder in the orbitofrontal cortex: A resting-state fMRI study

BACKGROUND

Overgeneral autobiographical memory (OGM) is involved in the onset and maintenance of depression. Recent studies have shown correlations between OGM and alterations of some brain regions by using task-state functional magnetic resonance imaging (fMRI). However, the correlation between OGM and spontaneous brain activity in depression remains unclear. The purpose of this study was to determine whether patients with major depressive disorder (MDD) show abnormal regional homogeneity (ReHo) and, if so, whether the brain areas with abnormal ReHo are associated with OGM.

METHODS

Twenty five patients with MDD and 25 age-matched, sex-matched, and education-matched healthy controls underwent resting-state fMRI. All participants were also assessed by 17-item Hamilton Depression Rating Scale and autobiographical memory test. The ReHo method was used to analyze regional synchronization of spontaneous neuronal activity.

RESULTS

Patients with MDD, compared to healthy controls, exhibited extensive ReHo abnormalities in some brain regions, including the frontal, temporal, and occipital cortex. Moreover, ReHo value of the orbitofrontal cortex was negatively correlated with OGM scores in patients with MDD.

LIMITATIONS

The sample size of this study was relatively small, and the influence of physiological noise was not completely excluded.

CONCLUSIONS

These results suggest that abnormal ReHo of spontaneous brain activity in the orbitofrontal cortex may be involved in the pathophysiology of OGM in patients with MDD.

Interactions between the default network and dorsal attention network vary across default subsystems, time, and cognitive states

Anticorrelation between the default network (DN) and dorsal attention network (DAN) is thought to be an intrinsic aspect of functional brain organization reflecting competing functions. However, the effect size of functional connectivity (FC) between the DN and DAN has yet to be established. Furthermore, the stability of anticorrelations across distinct DN subsystems, different contexts, and time, remains unexplored. In study 1 we summarize effect sizes of DN-DAN FC from 20 studies, and in study 2 we probe the variability of DN-DAN interactions across six different cognitive states in a new data set. We show that: (i) the DN and DAN have an independent rather than anticorrelated relationship when global signal regression is not used (median effect size across studies: r=-.06; 95% CI: -.15 to .08); (ii) the DAN exhibits weak negative FC with the DN Core subsystem but is uncorrelated with the dorsomedial prefrontal and medial temporal lobe subsystems; (iii) DN-DAN interactions vary significantly across different cognitive states; (iv) DN-DAN FC fluctuates across time between periods of anticorrelation and periods of positive correlation; and (v) changes across time in the strength of DN-DAN coupling are coordinated with interactions involving the frontoparietal control network (FPCN). Overall, the observed weak effect sizes related to DN-DAN anticorrelation suggest the need to re-conceptualize the nature of interactions between these networks. Furthermore, our findings demonstrate that DN-DAN interactions are not stable, but rather, exhibit substantial variability across time and context, and are coordinated with broader network dynamics involving the FPCN.

Connectivity Disruption, Atrophy, and Hypometabolism within Posterior Cingulate Networks in Alzheimer's Disease

The posterior cingulate cortex (PCC) is a critical brain network hub particularly sensitive to Alzheimer's disease (AD) and can be subdivided into ventral (vPCC) and dorsal (dPCC) regions. The aim of the present study was to highlight functional connectivity (FC) disruption, atrophy, and hypometabolism within the ventral and dorsal PCC networks in patients with amnestic mild cognitive impairment (aMCI) or AD. Forty-three healthy elders (HE) (68.7 ± 6 years), 34 aMCI (73.4 ± 6.8 years) and 24 AD (70.9 ± 9.1 years) patients underwent resting-state functional MRI, anatomical T1-weighted MRI and FDG-PET scans. We compared FC maps obtained from the vPCC and dPCC seeds in HE to identify the ventral and dorsal PCC networks. We then compared patients and HE on FC, gray matter volume and metabolism within each network. In HE, the ventral PCC network involved the hippocampus and posterior occipitotemporal and temporoparietal regions, whereas the dorsal PCC network included mainly frontal, middle temporal and temporoparietal areas. aMCI patients had impaired ventral network FC in the bilateral hippocampus, but dorsal network FC was preserved. In AD, the ventral network FC disruption had spread to the left parahippocampal and angular regions, while the dorsal network FC was also affected in the right middle temporal cortex. The ventral network was atrophied in the bilateral hippocampus in aMCI patients, and in the vPCC and angular regions as well in AD patients. The dorsal network was only atrophied in AD patients, in the dPCC, bilateral supramarginal and temporal regions. By contrast, hypometabolism was already present in both the vPCC and dPCC networks in aMCI patients, and further extended to include the whole networks in AD patients. The vPCC and dPCC connectivity networks were differentially sensitive to AD. Atrophy and FC disruption were only present in the vPCC network in aMCI patients, and extended to the dPCC network in AD patients, suggesting that the pathology spreads from the vPCC to the dPCC networks. By contrast, hypometabolism seemed to follow a different route, as it was present in both networks since the aMCI stage, possibly reflecting not only local disruption but also distant synaptic dysfunction.

Tracking thoughts: Exploring the neural architecture of mental time travel during mind-wandering

The capacity to imagine situations that have already happened or fictitious events that may take place in the future is known as mental time travel (MTT). Studies have shown that MTT is an important aspect of spontaneous thought, yet we lack a clear understanding of how the neurocognitive architecture of the brain constrains this element of human cognition. Previous functional magnetic resonance imaging (MRI) studies have shown that MTT involves the coordination between multiple regions that include mesiotemporal structures such as the hippocampus, as well as prefrontal and parietal regions commonly associated with the default mode network (DMN). The current study used a multimodal neuroimaging approach to identify the structural and functional brain organisation that underlies individual differences in the capacity to spontaneously engage in MTT. Using regionally unconstrained diffusion tractography analysis, we found increased diffusion anisotropy in right lateralised temporo-limbic, corticospinal, inferior fronto-occipital tracts in participants who reported greater MTT. Probabilistic connectivity mapping revealed a significantly higher connection probability of the right hippocampus with these tracts. Resting-state functional MRI connectivity analysis using the right hippocampus as a seed region revealed greater functional coupling to the anterior regions of the DMN with increasing levels of MTT. These findings demonstrate that the interactions between the hippocampus and regions of the cortex underlie the capacity to engage in MTT, and support contemporary theoretical accounts that suggest that the integration of the hippocampus with the DMN provides the neurocognitive landscape that allows us to imagine distant times and places.

Shifting visual perspective during retrieval shapes autobiographical memories

The dynamic and flexible nature of memories is evident in our ability to adopt multiple visual perspectives. Although autobiographical memories are typically encoded from the visual perspective of our own eyes they can be retrieved from the perspective of an observer looking at our self. Here, we examined the neural mechanisms of shifting visual perspective during long-term memory retrieval and its influence on online and subsequent memories using functional magnetic resonance imaging (fMRI). Participants generated specific autobiographical memories from the last five years and rated their visual perspective. In a separate fMRI session, they were asked to retrieve the memories across three repetitions while maintaining the same visual perspective as their initial rating or by shifting to an alternative perspective. Visual perspective shifting during autobiographical memory retrieval was supported by a linear decrease in neural recruitment across repetitions in the posterior parietal cortices. Additional analyses revealed that the precuneus, in particular, contributed to both online and subsequent changes in the phenomenology of memories. Our findings show that flexibly shifting egocentric perspective during autobiographical memory retrieval is supported by the precuneus, and suggest that this manipulation of mental imagery during retrieval has consequences for how memories are retrieved and later remembered.

The development of the intrinsic functional connectivity of default network subsystems from age 3 to 5

In recent years, research on human functional brain imaging using resting-state fMRI techniques has been increasingly prevalent. The term "default mode" was proposed to describe a baseline or default state of the brain during rest. Recent studies suggested that the default mode network (DMN) is comprised of two functionally distinct subsystems: a dorsal-medial prefrontal cortex (DMPFC) subsystem involved in self-oriented cognition (i.e., theory of mind) and a medial temporal lobe (MTL) subsystem engaged in memory and scene construction; both subsystems interact with the anterior medial prefrontal cortex (aMPFC) and posterior cingulate (PCC) as the core regions of DMN. The present study explored the development of DMN core regions and these two subsystems in both hemispheres from 3- to 5-year-old children. The analysis of the intrinsic activity showed strong developmental changes in both subsystems, and significant changes were specifically found in MTL subsystem, but not in DMPFC subsystem, implying distinct developmental trajectories for DMN subsystems. We found stronger interactions between the DMPFC and MTL subsystems in 5-year-olds, particularly in the left subsystems that support the development of environmental adaptation and relatively complex mental activities. These results also indicate that there is stronger right hemispheric lateralization at age 3, which then changes as bilateral development gradually increases through to age 5, suggesting in turn the hemispheric dominance in DMN subsystems changing with age. The present results provide primary evidence for the development of DMN subsystems in early life, which might be closely related to the development of social cognition in childhood.

Similarities and differences in the default mode network across rest, retrieval, and future imagining

The default mode network (DMN) has been identified reliably during rest, as well as during the performance of tasks such as episodic retrieval and future imagining. It remains unclear why this network is engaged across these seemingly distinct conditions, though many hypotheses have been proposed to account for these effects. Prior to generating hypotheses explaining common DMN involvement, the degree of commonality in the DMN across these conditions, within individuals, must be statistically determined to test whether or not the DMN is truly a unitary network, equally engaged across rest, retrieval and future imagining. To provide such a test, we used comparable paradigms (self-directed, uninterrupted thought of equal duration) across the three conditions (rest, retrieval, and future imagining) in a within-participant design. We found lower than expected pattern similarity in DMN functional connectivity across the three conditions. Similarity in connectivity accounted for only 40-50% of the total variance. Partial Least Squares (PLS) analyses revealed the medial temporal regions of the DMN were preferentially coupled with one another during episodic retrieval and future imagining, whereas the non-medial temporal regions of the DMN (e.g., medial prefrontal cortex, lateral temporal cortex, and temporal pole) were preferentially coupled during rest. These results suggest that DMN connectivity may be more flexible than previously considered. Our findings are in line with emerging evidence that the DMN is not a static network engaged commonly across distinct cognitive processes, but is instead a dynamic system, topographically changing in relation to ongoing cognitive demands. Hum Brain Mapp 38:1155-1171, 2017. © 2016 Wiley Periodicals, Inc.

Sleep-Wake Differences in Relative Regional Cerebral Metabolic Rate for Glucose among Patients with Insomnia Compared with Good Sleepers

STUDY OBJECTIVES

The neurobiological mechanisms of insomnia may involve altered patterns of activation across sleep-wake states in brain regions associated with cognition, self-referential processes, affect, and sleep-wake promotion. The objective of this study was to compare relative regional cerebral metabolic rate for glucose (rCMRglc) in these brain regions across wake and nonrapid eye movement (NREM) sleep states in patients with primary insomnia (PI) and good sleeper controls (GS).

METHODS

Participants included 44 PI and 40 GS matched for age (mean = 37 y old, range 21-60), sex, and race. We conducted [18F]fluoro-2-deoxy-D-glucose positron emission tomography scans in PI and GS during both morning wakefulness and NREM sleep at night. Repeated measures analysis of variance was used to test for group (PI vs. GS) by state (wake vs. NREM sleep) interactions in relative rCMRglc.

RESULTS

Significant group-by-state interactions in relative rCMRglc were found in the precuneus/posterior cingulate cortex, left middle frontal gyrus, left inferior/superior parietal lobules, left lingual/fusiform/occipital gyri, and right lingual gyrus. All clusters were significant at Pcorrected < 0.05.

CONCLUSIONS

Insomnia was characterized by regional alterations in relative glucose metabolism across NREM sleep and wakefulness. Significant group-by-state interactions in relative rCMRglc suggest that insomnia is associated with impaired disengagement of brain regions involved in cognition (left frontoparietal), self-referential processes (precuneus/posterior cingulate), and affect (left middle frontal, fusiform/lingual gyri) during NREM sleep, or alternatively, to impaired engagement of these regions during wakefulness.

Episodic specificity induction impacts activity in a core brain network during construction of imagined future experiences

Recent behavioral work suggests that an episodic specificity induction-brief training in recollecting the details of a past experience-enhances performance on subsequent tasks that rely on episodic retrieval, including imagining future experiences, solving open-ended problems, and thinking creatively. Despite these far-reaching behavioral effects, nothing is known about the neural processes impacted by an episodic specificity induction. Related neuroimaging work has linked episodic retrieval with a core network of brain regions that supports imagining future experiences. We tested the hypothesis that key structures in this network are influenced by the specificity induction. Participants received the specificity induction or one of two control inductions and then generated future events and semantic object comparisons during fMRI scanning. After receiving the specificity induction compared with the control, participants exhibited significantly more activity in several core network regions during the construction of imagined events over object comparisons, including the left anterior hippocampus, right inferior parietal lobule, right posterior cingulate cortex, and right ventral precuneus. Induction-related differences in the episodic detail of imagined events significantly modulated induction-related differences in the construction of imagined events in the left anterior hippocampus and right inferior parietal lobule. Resting-state functional connectivity analyses with hippocampal and inferior parietal lobule seed regions and the rest of the brain also revealed significantly stronger core network coupling following the specificity induction compared with the control. These findings provide evidence that an episodic specificity induction selectively targets episodic processes that are commonly linked to key core network regions, including the hippocampus.

The effect of age on relational encoding as revealed by hippocampal functional connectivity

The neural processes mediating cognition occur in networks distributed throughout the brain. The encoding and retrieval of relational memories, memories for multiple items or multifeatural events, is supported by a network of brain regions, particularly the hippocampus. The hippocampal coupling hypothesis suggests that the hippocampus is functionally connected with the default mode network (DMN) during retrieval, but during encoding, decouples from the DMN. Based on prior research suggesting that older adults are less able to modulate between brain network states, we tested the hypothesis that older adults' hippocampus would show functional connectivity with the DMN during relational encoding. The results suggest that, while the hippocampus is functionally connected to some regions of the DMN during relational encoding in both younger and older adults, older adults show additional DMN connectivity. Such age-related changes in network modulation appear not to be mediated by compensatory processes, but rather to reflect a form of neural inefficiency, most likely due to reduced inhibition.

Using fMRI to understand event construction in developmental amnesia

Recently, neuroimaging and patient-lesion methods have been combined to explain anomalies such as patients' intact performance on tasks on which they would be predicted to perform poorly. In some cases, preserved performance has been attributed to activation of residual tissue within the damaged region. However, activation of remnant tissue can also occur in relation to impaired performance and, thus, may not necessarily correspond to successful recruitment. To constrain these neuroimaging interpretations, what is needed is a paradigm with closely matched conditions that yields intact and impaired performance in the same patient. We investigated this in H.C., an amnesic person with congenital abnormalities of the hippocampus and its connections, who was scanned during remembering and imagining, abilities known to depend on the hippocampus. Specifically, we examined whether differences in activation and/or functional connectivity would explain H.C.'s compromised ability to construct events relating to herself in autobiographical memory (SELF condition) and events relating to personally familiar others (FAMILIAR condition) versus her intact ability to construct events relating to unknown others (UNFAMILIAR condition). Despite behavioral dissociations in H.C., the pattern of activation and functional connectivity supporting her performance was strikingly similar to that of controls across conditions. Most notably, like controls, H.C. showed robust hippocampal activation and functional connectivity to the hippocampus, both when her performance was intact and impaired. Across all conditions, H.C. activated several extra-hippocampal regions to a greater extent than did controls, and modest differences were observed in functional connectivity between extra-hippocampal regions. Taken together, these findings urge caution when drawing conclusions about the functional integrity of a structurally compromised brain region even when it is activated and/or co-activated with other regions.

Improving effect size estimation and statistical power with multi-echo fMRI and its impact on understanding the neural systems supporting mentalizing

Functional magnetic resonance imaging (fMRI) research is routinely criticized for being statistically underpowered due to characteristically small sample sizes and much larger sample sizes are being increasingly recommended. Additionally, various sources of artifact inherent in fMRI data can have detrimental impact on effect size estimates and statistical power. Here we show how specific removal of non-BOLD artifacts can improve effect size estimation and statistical power in task-fMRI contexts, with particular application to the social-cognitive domain of mentalizing/theory of mind. Non-BOLD variability identification and removal is achieved in a biophysical and statistically principled manner by combining multi-echo fMRI acquisition and independent components analysis (ME-ICA). Without smoothing, group-level effect size estimates on two different mentalizing tasks were enhanced by ME-ICA at a median rate of 24% in regions canonically associated with mentalizing, while much more substantial boosts (40-149%) were observed in non-canonical cerebellar areas. Effect size boosting occurs via reduction of non-BOLD noise at the subject-level and consequent reductions in between-subject variance at the group-level. Smoothing can attenuate ME-ICA-related effect size improvements in certain circumstances. Power simulations demonstrate that ME-ICA-related effect size enhancements enable much higher-powered studies at traditional sample sizes. Cerebellar effects observed after applying ME-ICA may be unobservable with conventional imaging at traditional sample sizes. Thus, ME-ICA allows for principled design-agnostic non-BOLD artifact removal that can substantially improve effect size estimates and statistical power in task-fMRI contexts. ME-ICA could mitigate some issues regarding statistical power in fMRI studies and enable novel discovery of aspects of brain organization that are currently under-appreciated and not well understood.

Decoding fMRI Signatures of Real-world Autobiographical Memory Retrieval

Extant neuroimaging data implicate frontoparietal and medial-temporal lobe regions in episodic retrieval, and the specific pattern of activity within and across these regions is diagnostic of an individual's subjective mnemonic experience. For example, in laboratory-based paradigms, memories for recently encoded faces can be accurately decoded from single-trial fMRI patterns [Uncapher, M. R., Boyd-Meredith, J. T., Chow, T. E., Rissman, J., & Wagner, A. D. Goal-directed modulation of neural memory patterns: Implications for fMRI-based memory detection. Journal of Neuroscience, 35, 8531–8545, 2015; Rissman, J., Greely, H. T., & Wagner, A. D. Detecting individual memories through the neural decoding of memory states and past experience. Proceedings of the National Academy of Sciences, U.S.A., 107, 9849–9854, 2010]. Here, we investigated the neural patterns underlying memory for real-world autobiographical events, probed at 1- to 3-week retention intervals as well as whether distinct patterns are associated with different subjective memory states. For 3 weeks, participants (n = 16) wore digital cameras that captured photographs of their daily activities. One week later, they were scanned while making memory judgments about sequences of photos depicting events from their own lives or events captured by the cameras of others. Whole-brain multivoxel pattern analysis achieved near-perfect accuracy at distinguishing correctly recognized events from correctly rejected novel events, and decoding performance did not significantly vary with retention interval. Multivoxel pattern classifiers also differentiated recollection from familiarity and reliably decoded the subjective strength of recollection, of familiarity, or of novelty. Classification-based brain maps revealed dissociable neural signatures of these mnemonic states, with activity patterns in hippocampus, medial PFC, and ventral parietal cortex being particularly diagnostic of recollection. Finally, a classifier trained on previously acquired laboratory-based memory data achieved reliable decoding of autobiographical memory states. We discuss the implications for neuroscientific accounts of episodic retrieval and comment on the potential forensic use of fMRI for probing experiential knowledge.

The Self-Pleasantness Judgment Modulates the Encoding Performance and the Default Mode Network Activity

In this functional magnetic resonance imaging (fMRI) study, we evaluated the effect of self-relevance on cerebral activity and behavioral performance during an incidental encoding task. Recent findings suggest that pleasantness judgments reliably induce self-oriented (internal) thoughts and increase default mode network (DMN) activity. We hypothesized that this increase in DMN activity would relate to increased memory recognition for pleasantly-judged stimuli (which depend on internally-oriented attention) but decreased recognition for unpleasantly-judged items (which depend on externally-oriented attention). To test this hypothesis, brain activity was recorded from 21 healthy participants while they performed a pleasantness judgment requiring them to rate visual stimuli as pleasant or unpleasant. One hour later, participants performed a surprise memory recognition test outside of the scanner. Thus, we were able to evaluate the effects of pleasant and unpleasant judgments on cerebral activity and incidental encoding. The behavioral results showed that memory recognition was better for items rated as pleasant than items rated as unpleasant. The whole brain analysis indicated that successful encoding (SE) activates the inferior frontal and lateral temporal cortices, whereas unsuccessful encoding (UE) recruits two key medial posterior DMN regions, the posterior cingulate cortex (PCC) and precuneus (PCU). A region of interest (ROI) analysis including classic DMN areas, revealed significantly greater involvement of the medial prefrontal cortex (mPFC) in pleasant compared to unpleasant judgments, suggesting this region’s involvement in self-referential (i.e., internal) processing. This area may be responsible for the greater recognition performance seen for pleasant stimuli. Furthermore, a significant interaction between the encoding performance (successful vs. unsuccessful) and pleasantness was observed for the PCC, PCU and inferior frontal gyrus (IFG). Overall, our results suggest the involvement of medial frontal and parietal DMN regions during the evaluation of self-referential pleasantness. We discuss these results in terms of the introspective referential of pleasantness judgments and the differential brain modulation based on internally- vs. externally-oriented attention during encoding.

The Functional and Structural Neuroanatomy of Systems Consolidation for Autobiographical and Semantic Memory

It is well established that patients with memory impairment have more difficulty retrieving memories from the recent past relative to the remote past and that damage to the medial temporal lobe (MTL) plays a key role in this pattern of impairment. The precise role of the MTL and how it may interact with other brain regions remains an area of active research. We investigated the role of structures in a memory network that supports remembering. Our chapter focuses on two types of memory: episodic memory and semantic memory. Findings from studies of patients with brain damage and neuroimaging studies in patients and healthy individuals were considered together to identify the functional and structural neuroanatomy of past remembrance.

Longitudinal changes in resting-state fMRI from age 5 to age 6years covary with language development

Resting-state functional magnetic resonance imaging is a powerful technique to study the whole-brain neural connectivity that underlies cognitive systems. The present study aimed to define the changes in neural connectivity in their relation to language development. Longitudinal resting-state functional data were acquired from a cohort of preschool children at age 5 and one year later, and changes in functional connectivity were correlated with language performance in sentence comprehension. For this, degree centrality, a voxel-based network measure, was used to assess age-related differences in connectivity at the whole-brain level. Increases in connectivity with age were found selectively in a cluster within the left posterior superior temporal gyrus and sulcus (STG/STS). In order to further specify the connection changes, a secondary seed-based functional connectivity analysis on this very cluster was performed. The correlations between resting-state functional connectivity (RSFC) and language performance revealed developmental effects with age and, importantly, also dependent on the advancement in sentence comprehension ability over time. In children with greater advancement in language abilities, the behavioral improvement was positively correlated with RSFC increase between left posterior STG/STS and other regions of the language network, i.e., left and right inferior frontal cortex. The age-related changes observed in this study provide evidence for alterations in the language network as language develops and demonstrates the viability of this approach for the investigation of normal and aberrant language development.

Theory of Mind and the Whole Brain Functional Connectivity: Behavioral and Neural Evidences with the Amsterdam Resting State Questionnaire

A topic of common interest to psychologists and philosophers is the spontaneous flow of thoughts when the individual is awake but not involved in cognitive demands. This argument, classically referred to as the "stream of consciousness" of James, is now known in the psychological literature as "Mind-Wandering." Although of great interest, this construct has been scarcely investigated so far. Diaz et al. (2013) created the Amsterdam Resting State Questionnaire (ARSQ), composed of 27 items, distributed in seven factors: discontinuity of mind, theory of mind (ToM), self, planning, sleepiness, comfort, and somatic awareness. The present study aims at: testing psychometric properties of the ARSQ in a sample of 670 Italian subjects; exploring the neural correlates of a subsample of participants (N = 28) divided into two groups on the basis of the scores obtained in the ToM factor. Results show a satisfactory reliability of the original factional structure in the Italian sample. In the subjects with a high mean in the ToM factor compared to low mean subjects, functional MRI revealed: a network (48 nodes) with higher functional connectivity (FC) with a dominance of the left hemisphere; an increased within-lobe FC in frontal and insular lobes. In both neural and behavioral terms, our results support the idea that the mind, which does not rest even when explicitly asked to do so, has various and interesting mentalistic-like contents.

The dorsal anterior cingulate cortex is selective for pain: Results from large-scale reverse inference

Dorsal anterior cingulate cortex (dACC) activation is commonly observed in studies of pain, executive control, conflict monitoring, and salience processing, making it difficult to interpret the dACC's specific psychological function. Using Neurosynth, an automated brainmapping database [of over 10,000 functional MRI (fMRI) studies], we performed quantitative reverse inference analyses to explore the best general psychological account of the dACC function P(Ψ process|dACC activity). Results clearly indicated that the best psychological description of dACC function was related to pain processing--not executive, conflict, or salience processing. We conclude by considering that physical pain may be an instance of a broader class of survival-relevant goals monitored by the dACC, in contrast to more arbitrary temporary goals, which may be monitored by the supplementary motor area.

Localizing Pain Matrix and Theory of Mind networks with both verbal and non-verbal stimuli

Functional localizer tasks allow researchers to identify brain regions in each individual's brain, using a combination of anatomical and functional constraints. In this study, we compare three social cognitive localizer tasks, designed to efficiently identify regions in the "Pain Matrix," recruited in response to a person's physical pain, and the "Theory of Mind network," recruited in response to a person's mental states (i.e. beliefs and emotions). Participants performed three tasks: first, the verbal false-belief stories task; second, a verbal task including stories describing physical pain versus emotional suffering; and third, passively viewing a non-verbal animated movie, which included segments depicting physical pain and beliefs and emotions. All three localizers were efficient in identifying replicable, stable networks in individual subjects. The consistency across tasks makes all three tasks viable localizers. Nevertheless, there were small reliable differences in the location of the regions and the pattern of activity within regions, hinting at more specific representations. The new localizers go beyond those currently available: first, they simultaneously identify two functional networks with no additional scan time, and second, the non-verbal task extends the populations in whom functional localizers can be applied. These localizers will be made publicly available.

Laterality effects in functional connectivity of the angular gyrus during rest and episodic retrieval

INTRODUCTION

The angular gyrus (AG) is consistently reported in neuroimaging studies of episodic memory retrieval and is a fundamental node within the default mode network (DMN). Its specific contribution to episodic memory is debated, with some suggesting it is important for the subjective experience of episodic recollection, rather than retrieval of objective episodic details. Across studies of episodic retrieval, the left AG is recruited more reliably than the right. We explored functional connectivity of the right and left AG with the DMN during rest and retrieval to assess whether connectivity could provide insight into the nature of this laterality effect.

METHODS

Using data from the publically available 1000 Functional Connectome Project, 8min of resting fMRI data from 180 healthy young adults were analysed. Whole-brain functional connectivity at rest was measured using a seed-based Partial Least Squares (seed-PLS) approach (McIntosh and Lobaugh, 2004) with bilateral AG seeds. A subsequent analysis used 6-min of rest and 6-min of unconstrained, silent retrieval of autobiographical events from a new sample of 20 younger adults. Analysis of this dataset took a more targeted approach to functional connectivity analysis, consisting of univariate pairwise correlations restricted to nodes of the DMN.

RESULTS

The seed-PLS analysis resulted in two Latent Variables that together explained ~86% of the shared cross-block covariance. The first LV revealed a common network consistent with the DMN and engaging the AG bilaterally, whereas the second LV revealed a less robust, yet significant, laterality effect in connectivity - the left AG was more strongly connected to the DMN. Univariate analyses of the second sample again revealed better connectivity between the left AG and the DMN at rest. However, during retrieval the left AG was more strongly connected than the right to non-medial temporal (MTL) nodes of the DMN, and MTL nodes were more strongly connected to the right AG.

DISCUSSION

The multivariate analysis of resting connectivity revealed that the left and right AG show similar connectivity with the DMN. Only after accounting for this commonality were we able to detect a left laterality effect in DMN connectivity. Further probing with univariate connectivity analyses during retrieval demonstrates that the left preference we observe is restricted to the non-MTL regions of the DMN, whereas the right AG shows significantly better connectivity with the MTL. These data suggest bilateral involvement of the AG during retrieval, despite the focus on the left AG in the literature. Furthermore, the results suggest that the contribution of the left AG to retrieval may be separable from that of the MTL, consistent with a role for the left AG in the subjective aspects of recollection in memory, whereas the MTL and the right AG may contribute to objective recollection of specific memory details.

A human brain atlas derived via n-cut parcellation of resting-state and task-based fMRI data

The growth of functional MRI has led to development of human brain atlases derived by parcellating resting-state connectivity patterns into functionally independent regions of interest (ROIs). All functional atlases to date have been derived from resting-state fMRI data. But given that functional connectivity between regions varies with task, we hypothesized that an atlas incorporating both resting-state and task-based fMRI data would produce an atlas with finer characterization of task-relevant regions than an atlas derived from resting-state alone. To test this hypothesis, we derived parcellation atlases from twenty-nine healthy adult participants enrolled in the Cognitive Connectome project, an initiative to improve functional MRI's translation into clinical decision-making by mapping normative variance in brain-behavior relationships. Participants underwent resting-state and task-based fMRI spanning nine cognitive domains: motor, visuospatial, attention, language, memory, affective processing, decision-making, working memory, and executive function. Spatially constrained n-cut parcellation derived brain atlases using (1) all participants' functional data (Task) or (2) a single resting-state scan (Rest). An atlas was also derived from random parcellation for comparison purposes (Random). Two methods were compared: (1) a parcellation applied to the group's mean edge weights (mean), and (2) a two-stage approach with parcellation of individual edge weights followed by parcellation of mean binarized edges (two-stage). The resulting Task and Rest atlases had significantly greater similarity with each other (mean Jaccard indices JI=0.72-0.85) than with the Random atlases (JI=0.59-0.63; all p<0.001 after Bonferroni correction). Task and Rest atlas similarity was greatest for the two-stage method (JI=0.85), which has been shown as more robust than the mean method; these atlases also better reproduced voxelwise seed maps of the left dorsolateral prefrontal cortex during rest and performing the n-back working memory task (r=0.75-0.80) than the Random atlases (r=0.64-0.72), further validating their utility. We expected regions governing higher-order cognition (such as frontal and anterior temporal lobes) to show greatest difference between Task and Rest atlases; contrary to expectations, these areas had greatest similarity between atlases. Our findings indicate that atlases derived from parcellation of task-based and resting-state fMRI data are highly comparable, and existing resting-state atlases are suitable for task-based analyses. We introduce an anatomically labeled fMRI-derived whole-brain human atlas for future Cognitive Connectome analyses.

Distinct neural correlates for attention lapses in patients with schizophrenia and healthy participants

Momentary lapses in attention are common in healthy populations. This phenomenon has recently received increased investigation, particularly in relationship to the default mode network (DMN). Previous research has suggested that these lapses may be due to intrusive task-irrelevant thoughts. The study of this phenomenon in schizophrenia, which is characterized by a wide variety of cognitive deficits including deficits in attention, has not previously been explored. We used the AX Continuous Performance Task to investigate attention lapses in healthy participants as well as patients with schizophrenia. We found distinct patterns of network activation between these two groups. Lapses in healthy participants were associated with DMN activation, while in patients, the same behavioral phenomenon was associated with deactivations in frontal-parietal control network (FPCN) regions. When considered in contrast to the results observed in healthy participants, these results suggest an additional origin of attention lapses in patients derived from a loss of task-related context, rather than intrusive task-irrelevant thoughts.