Functional modular architecture underlying attentional control in aging

The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis

The large number of different analytical choices used by researchers is partly responsible for the challenge of replication in neuroimaging studies. For an exhaustive robustness analysis, knowledge of the full space of analytical options is essential. We conducted a systematic literature review to identify the analytical decisions in functional neuroimaging data preprocessing and analysis in the emerging field of cognitive network neuroscience. We found 61 different steps, with 17 of them having debatable parameter choices. Scrubbing, global signal regression, and spatial smoothing are among the controversial steps. There is no standardized order in which different steps are applied, and the parameter settings within several steps vary widely across studies. By aggregating the pipelines across studies, we propose three taxonomic levels to categorize analytical choices: 1) inclusion or exclusion of specific steps, 2) parameter tuning within steps, and 3) distinct sequencing of steps. We have developed a decision support application with high educational value called METEOR to facilitate access to the data in order to design well-informed robustness (multiverse) analysis.

Age-related differences in resting-state, task-related, and structural brain connectivity: graph theoretical analyses and visual search performance

Previous magnetic resonance imaging (MRI) research suggests that aging is associated with a decrease in the functional interconnections within and between groups of locally organized brain regions (modules). Further, this age-related decrease in the segregation of modules appears to be more pronounced for a task, relative to a resting state, reflecting the integration of functional modules and attentional allocation necessary to support task performance. Here, using graph-theoretical analyses, we investigated age-related differences in a whole-brain measure of module connectivity, system segregation, for 68 healthy, community-dwelling individuals 18-78 years of age. We obtained resting-state, task-related (visual search), and structural (diffusion-weighted) MRI data. Using a parcellation of modules derived from the participants' resting-state functional MRI data, we demonstrated that the decrease in system segregation from rest to task (i.e., reconfiguration) increased with age, suggesting an age-related increase in the integration of modules required by the attentional demands of visual search. Structural system segregation increased with age, reflecting weaker connectivity both within and between modules. Functional and structural system segregation had qualitatively different influences on age-related decline in visual search performance. Functional system segregation (and reconfiguration) influenced age-related decline in the rate of visual evidence accumulation (drift rate), whereas structural system segregation contributed to age-related slowing of encoding and response processes (nondecision time). The age-related differences in the functional system segregation measures, however, were relatively independent of those associated with structural connectivity.

Age-related fornix decline predicts conservative response strategy-based slowing in perceptual decision-making

Aging leads to response slowing but the underpinning cognitive and neural mechanisms remain elusive. We modelled older and younger adults' response times (RT) from a flanker task with a diffusion drift model (DDM) and employed diffusion-weighted magnetic resonance imaging and spectroscopy to study neurobiological predictors of DDM components (drift-rate, boundary separation, non-decision time). Microstructural indices were derived from white matter pathways involved in visuo-perceptual and attention processing [optic radiation, inferior and superior longitudinal fasciculi (ILF, SLF), fornix]. Estimates of metabolite concentrations [N-acetyl aspartate (NAA), glutamate (Glx), and γ-aminobutyric acid (GABA), creatine (Cr), choline (Cho), myoinositol (mI)] were measured from occipital (OCC), anterior cingulate (ACC) and posterior parietal cortices (PPC). Age-related increases in RT, boundary separation, and non-decision time were observed with response conservatism acounting for RT slowing. Aging was associated with reductions in white matter microstructure (lower fractional anisotropy and restricted signal fraction, larger diffusivities) and in metabolites (NAA in ACC and PPC, Glx in ACC). Regression analyses identified brain regions involved in top-down (fornix, SLF, ACC, PPC) and bottom-up (ILF, optic radiation OCC) processing as predictors for DDM parameters and RT. Fornix FA was the strongest predictor for increases in boundary separation (beta = -0.8) and mediated the effects of age on RT. These findings demonstrate that response slowing in visual discrimination is driven by the adoption of a more conservative response strategy. Age-related fornix decline may result in noisier communication of contextual information from the hippocampus to anterior decision-making regions and thus contribute to the conservative response strategy shift.

Quantitative susceptibility mapping of brain iron in healthy aging and cognition

Quantitative susceptibility mapping (QSM) is a magnetic resonance imaging (MRI) technique that can assess the magnetic properties of cerebral iron in vivo. Although brain iron is necessary for basic neurobiological functions, excess iron content disrupts homeostasis, leads to oxidative stress, and ultimately contributes to neurodegenerative disease. However, some degree of elevated brain iron is present even among healthy older adults. To better understand the topographical pattern of iron accumulation and its relation to cognitive aging, we conducted an integrative review of 47 QSM studies of healthy aging, with a focus on five distinct themes. The first two themes focused on age-related increases in iron accumulation in deep gray matter nuclei versus the cortex. The overall level of iron is higher in deep gray matter nuclei than in cortical regions. Deep gray matter nuclei vary with regard to age-related effects, which are most prominent in the putamen, and age-related deposition of iron is also observed in frontal, temporal, and parietal cortical regions during healthy aging. The third theme focused on the behavioral relevance of iron content and indicated that higher iron in both deep gray matter and cortical regions was related to decline in fluid (speed-dependent) cognition. A handful of multimodal studies, reviewed in the fourth theme, suggest that iron interacts with imaging measures of brain function, white matter degradation, and the accumulation of neuropathologies. The final theme concerning modifiers of brain iron pointed to potential roles of cardiovascular, dietary, and genetic factors. Although QSM is a relatively recent tool for assessing cerebral iron accumulation, it has significant promise for contributing new insights into healthy neurocognitive aging.

Age-related differences in frontoparietal activation for target and distractor singletons during visual search

Age-related decline in visual search performance has been associated with different patterns of activation in frontoparietal regions using functional magnetic resonance imaging (fMRI), but whether these age-related effects represent specific influences of target and distractor processing is unclear. Therefore, we acquired event-related fMRI data from 68 healthy, community-dwelling adults ages 18-78 years, during both conjunction (T/F target among rotated Ts and Fs) and feature (T/F target among Os) search. Some displays contained a color singleton that could correspond to either the target or a distractor. A diffusion decision analysis indicated age-related increases in sensorimotor response time across all task conditions, but an age-related decrease in the rate of evidence accumulation (drift rate) was specific to conjunction search. Moreover, the color singleton facilitated search performance when occurring as a target and disrupted performance when occurring as a distractor, but only during conjunction search, and these effects were independent of age. The fMRI data indicated that decreased search efficiency for conjunction relative to feature search was evident as widespread frontoparietal activation. Activation within the left insula mediated the age-related decrease in drift rate for conjunction search, whereas this relation in the FEF and parietal cortex was significant only for individuals younger than 30 or 44 years, respectively. Finally, distractor singletons were associated with significant parietal activation, whereas target singletons were associated with significant frontoparietal deactivation, and this latter effect increased with adult age. Age-related differences in frontoparietal activation therefore reflect both the overall efficiency of search and the enhancement from salient targets.

Cortical iron mediates age-related decline in fluid cognition

Brain iron dyshomeostasis disrupts various critical cellular functions, and age-related iron accumulation may contribute to deficient neurotransmission and cell death. While recent studies have linked excessive brain iron to cognitive function in the context of neurodegenerative disease, little is known regarding the role of brain iron accumulation in cognitive aging in healthy adults. Further, previous studies have focused primarily on deep gray matter regions, where the level of iron deposition is highest. However, recent evidence suggests that cortical iron may also contribute to cognitive deficit and neurodegenerative disease. Here, we used quantitative susceptibility mapping (QSM) to measure brain iron in 67 healthy participants 18-78 years of age. Speed-dependent (fluid) cognition was assessed from a battery of 12 psychometric and computer-based tests. From voxelwise QSM analyses, we found that QSM susceptibility values were negatively associated with fluid cognition in the right inferior temporal gyrus, bilateral putamen, posterior cingulate gyrus, motor, and premotor cortices. Mediation analysis indicated that susceptibility in the right inferior temporal gyrus was a significant mediator of the relation between age and fluid cognition, and similar effects were evident for the left inferior temporal gyrus at a lower statistical threshold. Additionally, age and right inferior temporal gyrus susceptibility interacted to predict fluid cognition, such that brain iron was negatively associated with a cognitive decline for adults over 45 years of age. These findings suggest that iron may have a mediating role in cognitive decline and may be an early biomarker of neurodegenerative disease.

Alzheimer's Pathology Is Associated with Dedifferentiation of Intrinsic Functional Memory Networks in Aging

In presymptomatic Alzheimer's disease (AD), beta-amyloid plaques (Aβ) and tau tangles accumulate in distinct spatiotemporal patterns within the brain, tracking closely with episodic memory decline. Here, we tested whether age-related changes in the segregation of the brain's intrinsic functional episodic memory networks-anterior-temporal (AT) and posterior-medial (PM) networks-are associated with the accumulation of Aβ, tau, and memory decline using fMRI and PET. We found that AT and PM networks were less segregated in older than that in younger adults and this reduced specialization was associated with more tau and Aβ in the same regions. The effect of network dedifferentiation on memory depended on the amount of Aβ and tau, with low segregation and pathology associated with better performance at baseline and low segregation and high pathology related to worse performance over time. This pattern suggests a compensation phase followed by a degenerative phase in the early, preclinical phase of AD.

Predicting Age From Behavioral Test Performance for Screening Early Onset of Cognitive Decline

Background: Neuronal reactions and cognitive processes slow down during aging. The onset, rate, and extent of changes vary considerably from individual to individual. Assessing the changes throughout the lifespan is a challenging task. No existing test covers all domains, and batteries of tests are administered. The best strategy is to study each functional domain separately by applying different behavioral tasks whereby the tests reflect the conceptual structure of cognition. Such an approach has limitations that are described in the article. Objective: Our aim was to improve the diagnosis of early cognitive decline. We estimated the onset of cognitive decline in a healthy population, using behavioral tests, and predicted the age group of an individual. The comparison between the predicted ("cognitive") and chronological age will contribute to the early diagnosis of accelerated aging. Materials and Methods: We used publicly available datasets (POBA, SSCT) and Pearson correlation coefficients to assess the relationship between age and tests results, Kruskal-Wallis test to compare distribution, clustering methods to find an onset of cognitive decline, feature selection to enhance performance of the clustering algorithms, and classification methods to predict an age group from cognitive tests results. Results: The major results of the psychophysiological tests followed a U-shape function across the lifespan, which reflected the known inverted function of white matter volume changes. Optimal values were observed in those aged over 35 years, with a period of stability and accelerated decline after 55-60 years of age. The shape of the age-related variance of the performance of major cognitive tests was linear, which followed the trend of lifespan gray matter volume changes starting from adolescence. There was no significant sex difference in lifelong dynamics of major tests estimates. The performance of the classification model for identifying subject age groups was high. Conclusions: ML models can be designed and utilized as computer-aided detectors of neurocognitive decline. Our study demonstrated great promise for the utility of classification models to predict age-related changes. These findings encourage further explorations combining several tests from the cognitive and psychophysiological test battery to derive the most reliable set of tests toward the development of a highly-accurate ML model.

Age-Related Compensatory Reconfiguration of PFC Connections during Episodic Memory Retrieval

During demanding cognitive tasks, older adults (OAs) frequently show greater prefrontal cortex (PFC) activity than younger adults (YAs). This age-related increase in PFC activity is often associated with enhanced cognitive performance, suggesting functional compensation. However, the brain is a complex network of interconnected regions, and it is unclear how network connectivity of PFC regions differs for OAs versus YAs. To investigate this, we examined the age-related difference on the functional brain networks mediating episodic memory retrieval. YAs and OAs participants encoded and recalled visual scenes, and age-related differences in network topology during memory retrieval were investigated as a function of memory performance. We measured both changes in functional integration and reconfiguration in connectivity patterns. The study yielded three main findings. First, PFC regions were more functionally integrated with the rest of the brain network in OAs. Critically, this age-related increase in PFC integration was associated with better retrieval performance. Second, PFC regions showed stronger performance-related reconfiguration of connectivity patterns in OAs. Finally, the PFC reconfiguration increases in OAs tracked reconfiguration reductions in the medial temporal lobe (MTL)-a core episodic memory region, suggesting that PFC connectivity in OAs may be compensating for MTL deficits.

Resting-State Functional Magnetic Resonance Imaging Reveals Overactivation of the Habitual Control Brain System in Tobacco Dependence

INTRODUCTION

We studied the regulatory mechanism of the habitual brain network in tobacco dependence to provide a theoretical basis for the regulation and cessation of tobacco dependence.

METHODS

We used resting-state functional magnetic resonance imaging (rs-fMRI) to explore the Fractional amplitude of low-frequency fluctuations (fALFF) and functional connectivity (FC) of the habitual brain network in tobacco-dependent subjects and to evaluate the relationship between the FC level and tobacco selection preference behavior. In total, 29 male tobacco-dependent participants and 28 male nonsmoking participants were recruited. rs-fMRI was used to collect blood oxygen level-dependent signals of the participants in the resting and awake states. After rs-fMRI, all subjects completed cigarette/coin selection tasks (task 1 and task 2).

RESULTS

Compared with the control group, the tobacco dependence group showed increased fractional amplitude values of fALFF in the left posterior cingulate cortex and right parahippocampus. FC in the tobacco-dependent group was increased in the right inferior temporal gyrus, left middle frontal gyrus, left cingulated gyrus, and bilateral superior frontal gyrus, compared with that in the control group. Moreover, the preference selection behavior was associated with the enhancement of FC about parts of the brain regions in the habitual brain network of the tobacco-dependent participants. Thus, habitual network activity was significantly enhanced in tobacco-dependent participants in the resting state. Moreover, a positive correlation was found between the cigarette selection preference of the smokers and certain brain regions related to the habitual network.

DISCUSSION

This suggests that increased activity of the habitual brain network may be essential in the development of tobacco-dependent behavior.

Influence of structural and functional brain connectivity on age-related differences in fluid cognition

We used graph theoretical measures to investigate the hypothesis that structural brain connectivity constrains the influence of functional connectivity on the relation between age and fluid cognition. Across 143 healthy, community-dwelling adults 19-79 years of age, we estimated structural network properties from diffusion-weighted imaging and functional network properties from resting-state functional magnetic resonance imaging. We confirmed previous reports of age-related decline in the strength and efficiency of structural networks, as well as in the connectivity strength within and between structural network modules. Functional networks, in contrast, exhibited age-related decline only in system segregation, a measure of the distinctiveness among network modules. Aging was associated with decline in a composite measure of fluid cognition, particularly tests of executive function. Functional system segregation was a significant mediator of age-related decline in executive function. Structural network properties did not directly influence the age-related decline in functional system segregation. The raw correlational data underlying the graph theoretical measures indicated that structural connectivity exerts a limited constraint on age-related decline in functional connectivity.

Differences in network centrality between high and low myopia: a voxel-level degree centrality study

BACKGROUND

Previous studies have linked high myopia (HM) to brain activity, and the difference between HM and low myopia (LM) can be assessed.

PURPOSE

To study the differences in functional networks of brain activity between HM and LM by the voxel-level degree centrality (DC) method.

MATERIAL AND METHODS

Twenty-eight patients with HM (10 men, 18 women), 18 patients with LM (4 men, 14 women), and 59 healthy controls (27 men, 32 women) were enrolled in this study. The voxel-level DC method was used to assess spontaneous brain activity. Correlation analysis was used to explore the change of average DC value in different brain regions, in order to analyze differences in brain activity between HM and LM.

RESULTS

DC values of the right cerebellum anterior lobe/brainstem, right parahippocampal gyrus, and left caudate in HM patients were significantly higher than those in LM patients (P < 0.05). In contrast, DC values of the left medial frontal gyrus, right inferior frontal gyrus, left middle frontal gyrus, and left inferior parietal lobule were significantly lower in patients with HM (P < 0.05). However, there was no correlation between behavior and average DC values in different brain regions (P < 0.05).

CONCLUSION

Different changes in brain regions between HM and LM may indicate differences in neural mechanisms between HM and LM. DC values could be useful as biomarkers for differences in brain activity between patients with HM and LM. This study provides a new method to assess differences in functional networks of brain activity between patients with HM and LM.

Response-level processing during visual feature search: Effects of frontoparietal activation and adult age

Previous research suggests that feature search performance is relatively resistant to age-related decline. However, little is known regarding the neural mechanisms underlying the age-related constancy of feature search. In this experiment, we used a diffusion decision model of reaction time (RT), and event-related functional magnetic resonance imaging (fMRI) to investigate age-related differences in response-level processing during visual feature search. Participants were 80 healthy, right-handed, community-dwelling individuals, 19–79 years of age. Analyses of search performance indicated that targets accompanied by response-incompatible distractors were associated with a significant increase in the nondecision-time (t0) model parameter, possibly reflecting the additional time required for response execution. Nondecision time increased significantly with increasing age, but no age-related effects were evident in drift rate, cautiousness (boundary separation, a), or in the specific effects of response compatibility. Nondecision time was also associated with a pattern of activation and deactivation in frontoparietal regions. The relation of age to nondecision time was indirect, mediated by this pattern of frontoparietal activation and deactivation. Response-compatible and -incompatible trials were associated with specific patterns of activation in the medial and superior parietal cortex, and frontal eye field, but these activation effects did not mediate the relation between age and search performance. These findings suggest that, in the context of a highly efficient feature search task, the age-related influence of frontoparietal activation is operative at a relatively general level, which is common to the task conditions, rather than at the response level specifically.

Reduced Capacity of Cognitive Control in Older Adults with Mild Cognitive Impairment

Cognitive control for the coordination of mental operations is essential in normal cognitive functioning of daily life. Although the decline of cognitive control in older adults with mild cognitive impairment (MCI) has been demonstrated, whether this decline is a core deficit in MCI remains unclear. In this study, we employed a perceptual decision-making task to estimate the capacity of cognitive control (CCC) in older adults with MCI (n = 55) and the age-, sex-, and education-matched healthy controls (HC, n = 55) selected based on a commonly used battery of ten neuropsychological tests in five cognitive domains. We found that the CCC was significantly correlated to the neuropsychological measures of the battery. The mean CCC was significantly lower in the MCI group (3.06 bps) than in the HC group (3.59 bps) and significantly lower in the amnestic MCI subgroup (2.90 bps) than in the nonamnestic MCI subgroup (3.22 bps). In detecting and classifying MCI using machine learning, the classifier with the CCC as the input feature outperformed the overall classification with neuropsychological measures in a single cognitive domain. The classification performance was significantly increased when the CCC was included as a feature in addition to measures in a single domain, and the CCC served as a key feature in optimal classifiers with inputs from multiple domains. These results support the hypothesis that the decline in cognitive control is a core deficit in MCI and suggest that the CCC may serve as a key index in the diagnosis of MCI.

Markers of cognitive function in individuals with metabolic disease: Morquio syndrome and tyrosinemia type III

We characterized cognitive function in two metabolic diseases. MPS-IVa (mucopolysaccharidosis IVa, Morquio) and tyrosinemia type III individuals were assessed using tasks of attention, language and oculomotor function. MPS-IVa individuals were slower in visual search, but the display size effects were normal, and slowing was not due to long reaction times (ruling out slow item processing or distraction). Maintaining gaze in an oculomotor task was difficult. Results implicated sustained attention and task initiation or response processing. Shifting attention, accumulating evidence and selecting targets were unaffected. Visual search was also slowed in tyrosinemia type III, and patterns in visual search and fixation tasks pointed to sustained attention impairments, although there were differences from MPS-IVa. Language was impaired in tyrosinemia type III but not MPS-IVa. Metabolic diseases produced selective cognitive effects. Our results, incorporating new methods for developmental data and model selection, illustrate how cognitive data can contribute to understanding function in biochemical brain systems.

Connectome-based models predict attentional control in aging adults

There are well-characterized age-related differences in behavioral and neural responses to tasks of attentional control. However, there is also increasing recognition of individual variability in the process of neurocognitive aging. Using connectome-based predictive modeling, a method for predicting individual-level behaviors from whole-brain functional connectivity, a sustained attention connectome-based prediction model (saCPM) has been derived in young adults. The saCPM consists of two large-scale functional networks: a high-attention network whose strength predicts better attention and a low-attention network whose strength predicts worse attention. Here we examined the generalizability of the saCPM for predicting inhibitory control in an aging sample. Forty-two healthy young adults (n = 21, ages 18-30) and older adults (n = 21, ages 60-80) performed a modified Stroop task, on which older adults exhibited poorer performance, indexed by higher reaction time cost between incongruent and congruent trials. The saCPM generalized to predict reaction time cost across age groups, but did not account for age-related differences in performance. Exploratory analyses were conducted to characterize the effects of age on functional connectivity and behavior. We identified subnetworks of the saCPM that exhibited age-related differences in strength. The strength of two low-attention subnetworks, consisting of frontoparietal, medial frontal, default mode, and motor nodes that were more strongly connected in older adults, mediated the effect of age group on performance. These results support the saCPM's ability to capture attention-related patterns reflected in each individual's functional connectivity signature across both task context and age. However, older and younger adults exhibit functional connectivity differences within components of the saCPM networks, and it is these connections that better account for age-related deficits in attentional control.

Abnormal degree centrality in chronic users of codeine-containing cough syrups: A resting-state functional magnetic resonance imaging study

Codeine-containing cough syrups (CCS) have become one of the most popular drugs of abuse in young population worldwide. However, the neurobiological mechanisms underlying CCS-dependence are yet ill-defined. Therefore, understanding the brain abnormalities in chronic users of CCS is crucial for developing effective interventions. The present study depicted the intrinsic dysconnectivity pattern of whole-brain functional networks at the voxel level in chronic users of CCS. In addition, the degree centrality (DC) changes were correlated to the Barratt Impulsiveness Scale (BIS-11) total score, dose, duration of CCS use, and the age at first use of cough syrups. The current study included 38 chronic CCS users and 34 matched control subjects. All patients were evaluated using the BIS-11. Next, resting-state functional magnetic resonance imaging (rs-fMRI) datasets were acquired from these CCS users and controls. Whole-brain connectivity was analyzed using a graph theory approach: degree centrality (DC). CCS-dependent individuals exhibited low DC values in the left inferior parietal lobule and the left middle temporal gyrus, while high DC values were noted in the right pallidum and the right hippocampus (P < 0.01, AlphaSim corrected). Also, significant correlations were established between average DC value in the left inferior parietal lobule and attentional impulsivity scores and the age at first CCS use. The rs-fMRI study suggested that the abnormal intrinsic dysconnectivity pattern of whole-brain functional networks may provide an insight into the neural substrates of abnormalities in the cognitive control circuit, the reward circuit, and the learning and memory circuit in CCS-dependent individuals.

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The abuse of CCS has gained a severe foothold among young individuals worldwide.

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DC is one of the more reliable and compelling measures among several nodal network metrics.

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The present study depicted intrinsic dysconnectivity pattern of whole-brain functional networks in CCS-dependent individuals.

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CCS-dependent individuals showed altered DC in the right pallidum, right hippocampus, left IPL and left middle temporal gyrus.

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Significant correlations were established between average DC value in the left IPL and attentional impulsivity scores and the age at first CCS use.

Functional networks underlying item and source memory: shared and distinct network components and age-related differences

Although the medial temporal lobes (MTLs) are critical for both item memory (IM) and source memory (SM), the lateral prefrontal cortex and posterior parietal cortex play a greater role during SM than IM. It is unclear, however, how these differences translate into shared and distinct IM versus SM network components and how these network components vary with age. Within a sample of younger adults (YAs; n = 15, M_age = 19.5 years) and older adults (OAs; n = 40, M_age = 68.6 years), we investigated the functional networks underlying IM and SM. Before functional MRI scanning, participants encoded nouns while making either pleasantness or size judgments. During functional MRI scanning, participants completed IM and SM retrieval tasks. We found that MTL nodes were similarly interconnected among each other during both IM and SM (shared network components) but maintained more intermodule connections during SM (distinct network components). Also, during SM, OAs (compared to YAs) had MTL nodes with more widespread connections. These findings provide a novel viewpoint on neural mechanism differences underlying IM versus SM in YAs and OAs.

Search and recovery of autobiographical and laboratory memories: Shared and distinct neural components

Functional neuroimaging evidence suggests that there are differences in the neural correlates of episodic memory for laboratory stimuli (laboratory memory) and for events from one's own life (autobiographical memory). However, this evidence is scarce and often confounded with differences in memory testing procedures. Here, we directly compared the neural mechanisms underlying the search and recovery of autobiographical and laboratory memories while minimizing testing differences. Before scanning, participants completed a laboratory memory encoding task in which they studied four-word "chains" spread across three word pairs. During scanning, participants completed a laboratory memory retrieval task, in which they recalled the word chains, and an autobiographical memory retrieval task, in which they recalled specific personal events associated with word cues. Importantly, response times were similar in the two tasks, allowing for a direct comparison of the activation time courses. We found that during memory search (searching for the memory target), similar brain regions were activated during both the autobiographical and laboratory tasks, whereas during memory recovery (accessing the memory traces; i.e., ecphory), clear differences emerged: regions of the default mode network (DMN) were activated greater during autobiographical than laboratory memory, whereas the bilateral superior parietal lobules were activated greater during laboratory than autobiographical memory. Also, multivariate functional connectivity analyses revealed that regardless of memory stage, the DMN and ventral attention network exhibited a more integrated topology in the functional network underlying autobiographical (vs. laboratory) memory retrieval, whereas the fronto-parietal task control network exhibited a more integrated topology in the functional network underlying laboratory (vs. autobiographical) memory retrieval. These findings further characterize the shared and distinct neural components underlying autobiographical and laboratory memories, and suggest that differences in autobiographical vs. laboratory memory brain activation previously reported in the literature reflect memory recovery rather than search differences.