Biology subjects

Buckner, R. L.

Publications and source records attributed to Buckner, R. L..

At least 19 recordsLinked to original sources

bioRxiv2026

Large-Scale Network Embedding Predicts Opposing Functions of Adjacent Regions Within Human Prefrontal Cortex

Prefrontal regions are hypothesized to be organized hierarchically in support of cognitive control. Using precision functional MRI in three independent cohorts of intensively scanned participants (N=37), we consistently identified a lateral prefrontal cortex (LPFC) region linked to a canonical control network separate from a nearby rostral LPFC region linked to the action-mode network. Despite their spatial juxtaposition, the two regions were differentially coupled to the caudate and ventral putamen, suggesting they are components of segregated networks. Working memory demands activated the canonical LPFC control region but not the adjacent region. Contrasting go and no-go trials during target detection revealed a robust functional double dissociation during goal-directed behavior. The canonical LPFC control region activated when responses were withheld, while the putamen-coupled LPFC region increased activity during executed responses. These findings demonstrate that adjacent LPFC regions participate in opposing functions predicted by their embedding within distinct parallel large-scale networks.

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bioRxiv2026

Multiple Nested Distributed Language Networks in the Human Brain

Brain regions specialized for language have been extensively described, yet their arrangement into one or multiple networks remains debated. Using precision functional mapping across three independent cohorts of intensively scanned individuals (22 individuals scanned over 216 separate MRI sessions), we dissociated two nested left-lateralized perisylvian networks: an intermediate language network (intLANG) and an anatomically distinct association language network (aLANG). intLANG is anchored to precentral speech areas and the Sylvian parietal-temporal area (Spt), whereas aLANG surrounds intLANG and extends into higher-order prefrontal and temporal association cortices. The two networks can be fully recapitulated by functional connectivity from adjacent cerebellar regions, indicating that they are segregated, brain-wide networks. Task-based analyses further reveal that intLANG and aLANG are functionally distinct: intLANG responds robustly during rhyme judgments and nonword reading that emphasize phonology, whereas aLANG is preferentially recruited during meaning-based sentence processing. These findings indicate that human language engages nested distributed networks each specialized for distinct components of language processing: a lower-order network biased toward phonology, and a surrounding association network that subserves higher-order syntax and semantics. This nested organization is similar to other brain systems suggesting a shared hierarchical motif that may give rise to specialized cognitive functions across the human brain.

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bioRxiv2026

Structural Brain Indicators of Cognitive Performance in Middle and Late Adulthood: The Human Connectome Project in Aging/Aging Adult Brain Connectome Cohort

IntroductionSignificant effort has been put towards mapping patterns of atrophy in the cerebral cortex that are related to pathological aging, including the characteristic patterns of neurodegeneration in Alzheimers disease (AD). In contrast, brain structural patterns that support preserved or even exceptional cognition throughout the adult age-span and especially in later life are much less known. It is possible that superior cognitive performance in late life is supported by a preservation of brain structures vulnerable to typical aging. Alternatively, elevated performance could be related to preservation of brain regions vulnerable to age-associated pathology. Examination of individuals that exhibit superior cognition throughout the adult lifespan may provide unique insights into neural mechanisms that support cognitive resilience in late life. MethodsWe examined cross-sectional associations between cortical brain structure and cognitive performance across three stages of adulthood: midlife (36-59), young-old (60-79), and older adults (80+) in typically aging individuals enrolled as part of the Human Connectome Project Lifespan-Aging (HCP-A)/Aging Adult Brain Connectome (AABC) studies. Participants were considered generally healthy and excluded for significant and/or atypical health conditions for their demographic category, including a clinical diagnosis of cognitive impairment or dementia. Domain-specific cognitive factor scores representing memory, fluid intelligence, and crystalized intelligence were sex-stratified and residualized relative to age, and participants were classified as high, middle, or low performers based on their unique performance relative to the study sample. ResultsIn the full sample, high performers demonstrated greater cortical thickness in regions of somatomotor, visual, and auditory cortices, as well as cortical areas in the frontal, parietal, and insular cortices (e.g., 5m, LIPv, MBelt). We also found associations between medial temporal and cingulate cortical thickness and cognitive performance, but only for select analyses. Group differences in cortical thickness were greatest when contrasting high and low performers for fluid intelligence compared to the other cognitive factors and were most prominent in the midlife participants compared to the other age strata. These group differences were primarily driven by reduced cortical thickness in the low performing individuals in the younger age bins relative to the typically performing sample. Effects were rather limited when contrasting high and low performers in the 80+ age group. The cortical areas of high statistical significance appeared to show a cross-sectional convergence effect, such that the differences in cortical thickness between high vs. low cognitive performance groups diminished with increasing age. Despite lower statistical power, effect sizes were greatest when contrasting individuals at the extremes of performance (e.g., top 10% vs. bottom 10% performers). These effects were robust to subsample replications using longitudinally defined cognitive classifications. DiscussionElevated cognitive performance was cross-sectionally associated with increased regional cortical thickness and effects were most prominent in mid-life compared to later ages. Notably, contrary to brain regions that may be expected to support such high-order cognitive performance, a significant portion of primary sensory, motor, and insular cortical areas exhibited group differences between the high- and low-performing groups in this relatively younger age group. Group differences were due to lower thickness in these regions in the low performing group relative to the typical performers. In contrast to the younger portion of the sample, regions typically considered vulnerable to Alzheimers disease (i.e., regions in the medial temporal lobe) were only infrequently implicated. These results suggest that specific patterns of cortical brain structural integrity including preserved thickness of primary motor and sensory cortical regions may be a necessary but not sufficient mechanism supporting superior cognitive abilities in earlier adulthood, while alternate neural mechanisms may support cognitive resilience later in life. These results must be interpreted with caution given the cross-sectional nature of this study. Cognitive capacity can only be estimated from a single timepoint, and several factors contribute to inter-individual variation that will not be accounted for in the models applied here. Longitudinal assessment of cognitive resilience in the HCP-A/AABC cohort will be performed in future work.

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bioRxiv2025

Adjacent Dorsolateral Prefrontal Cortex (DLPFC) Regions Participate in Distinct Large-Scale Networks Differentially Recruited for Social and Cognitive Control Functions

Human prefrontal cortex (PFC) is heterogenous. In monkeys, side-by-side PFC regions, including within dorsolateral PFC (DLPFC), show distinct long-range anatomical projection profiles, raising the possibility that adjacent regions might specialize as a consequence of the distributed networks in which they are embedded. Consistent with this possibility, recent findings in humans provide evidence for PFC regions domain-specialized for scene (spatial) processing and language processing that are adjacent to distinct domain-flexible regions responding to traditional cognitive control demands. Here we tested functional specialization of PFC regions linked to another domain-specialized network recruited by certain forms of social processing (theory-of-mind, ToM, tasks). Using within-individual precision neuroimaging approaches, side-by-side DLPFC regions embedded within parallel distributed networks were identified within the idiosyncratic anatomy of each individual (N=13). Functional responses between these distinct regions revealed a robust functional double dissociation: one DLPFC region was preferentially recruited by ToM tasks and an adjacent DLPFC region by working memory task demands. The region responding to social processing demands was small and its position varied slightly from one person to the next suggesting why it may have been underappreciated in past group-based analyses. These findings add to evidence that PFC features more functional specialization than commonly appreciated and further that the specialization of juxtaposed regions within PFC can be understood by examining the distributed networks within which the regions are embedded.

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bioRxiv2025

Increased Aperiodic Exponents Track Depression Symptom Severity

Roughly one-third of patients with major depressive disorder (MDD) fail to respond to standard treatments and develop treatment-resistant MDD. For these patients, alternative therapies ofer additional options but yield inconsistent outcomes. Progress has been limited by the absence of objective, brain-based biomarkers to guide target selection or track therapeutic response in real time. Instead, clinicians rely on behavioral assessments that evolve slowly over weeks to months, obscuring the underlying neural dynamics of symptom changes. Here, we test whether the aperiodic exponent of intracranial EEG (iEEG) local field potentials can serve as a neurophysiological marker of depression symptom severity. We leveraged a large iEEG cohort (N = 20) undergoing invasive monitoring for refractory epilepsy, yielding over 1,800 contacts spanning cortical and subcortical zones. For each contact, we estimated the aperiodic exponent (thought to reflect aspects of cortical excitability) of the power spectrum across 10-100 Hz within local brain regions and across distributed cortical association networks. Depressive symptoms were assessed with the Beck Depression Inventory-II (BDI-II) immediately before intracranial resting state recordings. With respect to the BDI-II scale, participants were identified as experiencing minimal (BDI-II [≤] 13) or elevated depression symptoms (BDI-II [≥] 14). Associations between symptom severity (BDI-II total score and Somatic-Afective, Cognitive, and Anhedonia subscales) and region- or network-level exponents were modeled with ordinary least squares (OLS) regression. The whole-brain, mean aperiodic exponent for each participant discriminated symptom status (AUC = 0.82). At the regional level, the orbitofrontal cortex, anterior cingulate cortex, insula, and amygdala showed higher exponents in the elevated depression symptom group (d = 1.18-1.71; p = 0.032-0.004). A post-hoc classification analysis across these four regions misclassified one participant per group (AUC = 0.86; 95% CI 0.64-1.00). In continuous analyses, BDI-II scores correlated positively with exponents in these same four regions (pFDR = 0.019-0.027; partial r=0.61-0.70) and at the network level in the Salience network (pFDR = 0.024; partial r = 0.63) and Default (pFDR = 0.046; partial r = 0.55) network. The Salience network significantly tracked Anhedonia symptoms (p = 0.004; partial r = 0.62). Here we report that intracranial aperiodic exponents within fronto-limbic and insular circuits, overlapping with networks implicated in contemporary accounts of depression pathophysiology, diferentiate depressive symptom status and scale with severity. These findings support the aperiodic exponent as a candidate neurophysiological marker of current depression symptom burden, with potential relevance for individualized neuromodulation in MDD.

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bioRxiv2025

Verbal versus Nonverbal Processing Leads to Generalized Hemispheric Laterality Effects that Span Multiple Networks

Precision neuroimaging was used to explore specialization for verbal versus nonverbal processing. Consistent with prior findings, individuals exhibited a spatially left-lateralized association language network, with regions in both hemispheres robustly responding to processing of meaning-based sentences. We next examined differential responses to verbal (words) versus nonverbal (faces) materials within the same working memory task. The right hemisphere components of the language network responded more strongly to nonverbal than to verbal materials, splitting the networks functional profile between the hemispheres. Similar patterns were observed across multiple association networks including putative cognitive-control, action-mode, and attention networks. The hemispheric laterality effect was prospectively replicated in a second independent study. These findings highlight a generalized laterality phenomenon that transcends the specialization of individual networks that has been the recent focus of the human systems neuroscience field, and aligns with a broad mechanism that modulates processing between the hemispheres.

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bioRxiv2025

Old-New Recognition Memory Revisited

Identifying old items during recognition memory tasks elicits widespread cortical responses. Recent results suggest that a distributed network, labeled the Parietal Memory Network (PMN), responds to old items potentially reflecting mnemonic familiarity. An independent, parallel line of evidence suggests that the same network responds to salient stimuli in non-mnemonic contexts, referring to the network as the Salience Network (SAL). Here we examined responses during old-new recognition and non-mnemonic detection tasks in intensively scanned individuals to directly contrast component processes related to mnemonic familiarity with more general processes associated with target detection. In an oddball detection paradigm devoid of traditional memory demands, SAL/PMN was robustly activated. SAL/PMN was also activated by old words in a standard old-new recognition task, thus reproducing both previously reported effects. In a critical oppositional contrast, recognition was examined when the task was to detect uncommon old words versus when the task was to detect uncommon new words. SAL/PMN was activated during the detection of targets even when those targets were new items, consistent with a response to the task relevance of the targets not mnemonic familiarity. Exploratory analyses further suggested that a right-lateralized network, referred to as Frontoparietal Network B (FPN-B), responds to mnemonic familiarity. These results revise our understanding of brain networks contributing to old-new recognition separating component processes common to many forms of target detection task from processes preferentially associated with mnemonic history.

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bioRxiv2025

Age- and Sex-Related Differences in Sleep Patterns and Their Relations to Self-Reported Sleep and Mood

Robust age- and sex-related differences in sleep were identified (n=38,546) and replicated (n=38,547) from week-long passive actigraphy data in UK Biobank participants ages 44-82. Sleep patterns reflected reliable non-linear interactions between age and sex. Younger women slept about 17 min more than their male counterparts, though this difference diminished with age, with both sexes reducing total sleep duration in later life. Middle-aged individuals exhibited shorter sleep durations during the week, with weekend sleep increasing by as much as 50 min. Participants in their seventh and eighth decades showed more consistent sleep patterns throughout the week. Sleep patterns also suggest maintenance of total sleep duration: individuals reporting waking too early maintain sleep duration by going to sleep earlier, while individuals reporting sleeping too much fall asleep later but also wake later, again maintaining sleep duration. Self-reported depression and anhedonia were associated with reduced total sleep duration across multiple age groups and both sexes. These collective results indicate that the timing, consistency, and overall amount of sleep differs by age and is affected by individual factors.

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bioRxiv2025

Within-Individual Precision Mapping of Brain Networks Exclusively Using Task Data

Precision mapping of brain networks within individuals has become a widely used tool that prevailingly relies on functional connectivity analysis of resting-state data. Here we explored whether networks could be precisely estimated solely using data acquired during active task paradigms. The straightforward strategy involved extracting residualized data after application of a task-based general linear model (GLM) and then applying standard functional connectivity analysis. Functional correlation matrices estimated from task data were highly similar to those derived from traditional resting-state fixation data. The largest factor affecting similarity between correlation matrices was the amount of data. Networks estimated within-individual from task data displayed strong spatial overlap with those estimated from resting-state fixation data and predicted the same triple functional dissociation in independent data. The implications of these findings are that (1) existing task data can be reanalyzed to estimate within-individual network organization, (2) restingstate fixation and task data can be pooled to increase statistical power, and (3) future studies can exclusively acquire task data to both estimate networks and extract task responses. Most broadly, the present results suggest that there is an underlying, stable network architecture that is idiosyncratic to the individual and persists across task states.

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bioRxiv2024

Ventral Striatum is Preferentially Correlated with the Salience Network Including Regions in Dorsolateral Prefrontal Cortex

The ventral striatum (VS) receives input from the cerebral cortex and is modulated by midbrain dopaminergic projections in support of processing reward and motivation. Here we explored the organization of cortical regions linked to the human VS using within-individual functional connectivity MRI in intensively scanned participants. In two initial participants (scanned 31 sessions each), seed regions in the VS were preferentially correlated with distributed cortical regions that are part of the Salience (SAL) network. The VS seed region recapitulated SAL network topography in each individual including anterior and posterior midline regions, anterior insula, and dorsolateral prefrontal cortex (DLPFC) - a topography that was distinct from a nearby striatal seed region. The region of DLPFC linked to the VS is positioned adjacent to regions associated with domain-flexible cognitive control. The full pattern was replicated in independent data from the same two individuals and generalized to 15 novel participants (scanned 8 or more sessions each). These results suggest that the VS forms a cortico-basal ganglia loop as part of the SAL network. The DLPFC is a neuromodulatory target to treat major depressive disorder. The present results raise the possibility that the DLPFC may be an effective neuromodulatory target because of its preferential coupling to the VS and suggests a path toward further personalization.

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bioRxiv2023

Specialization of the Human Hippocampal Long Axis Revisited

The hippocampus possesses anatomical differences along its long axis. Here the functional specialization of the human hippocampal long axis was explored using network-anchored precision functional MRI (N = 11) paired with behavioral analyses (N=266). Functional connectivity analyses demonstrated that the anterior hippocampus was preferentially correlated with a cerebral network associated with remembering, while the posterior hippocampus was correlated with a distinct network associated with behavioral salience. Seed regions placed within the hippocampus recapitulated the distinct cerebral networks. Functional characterization using task data within the same intensively sampled individuals discovered a functional double dissociation between the anterior and posterior hippocampal regions. The anterior hippocampal region was sensitive to remembering and imagining the future, specifically tracking the process of scene construction, while the posterior hippocampal region displayed transient responses to targets in an oddball detection task and to transitions between task blocks. These findings suggest specialization along the long axis of the hippocampus with differential responses reflecting the functional properties of the partner cerebral networks.

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bioRxiv2023

Within-Individual Organization of the Human Cognitive Cerebellum: Evidence for Closely Juxtaposed, Functionally Specialized Regions

The human cerebellum possesses multiple regions linked to cerebral association cortex. Here we mapped the cerebellum using precision functional MRI within individual participants (N=15), first estimating regions using connectivity and then prospectively testing functional properties using independent task data. Network estimates in all participants revealed a Crus I / II cerebellar megacluster of five higher-order association networks often with multiple, discontinuous regions for the same network. Seed regions placed within the megaclusters, including the disjointed regions, yielded spatially selective networks in the cerebral cortex. Compelling evidence for functional specialization within the cerebellar megaclusters emerged from the task responses. Reflecting functional distinctions found in the cerebrum, domain-flexible cerebellar regions involved in cognitive control dissociated from distinct domain-specialized regions with differential responses to language, social, and spatial / episodic task demands. These findings provide a clear demonstration that the cerebellum encompasses multiple zones dedicated to cognition, featuring juxtaposed regions specialized for distinct processing domains.

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bioRxiv2023

Human Striatal Association Megaclusters

The striatum receives projections from multiple regions of the cerebral cortex consistent with its role in diverse motor, affective, and cognitive functions. Supporting cognitive functions, the caudate receives projections from cortical association regions. Building on recent insights about the details of how multiple cortical networks are specialized for distinct aspects of higher-order cognition, we revisited caudate organization using within-individual precision neuroimaging (n=2, each participant scanned 31 times). Detailed analysis revealed that the caudate has side-by-side zones that are coupled to at least Give distinct distributed association networks, paralleling the specialization observed in the cerebral cortex. Examining correlation maps from closely juxtaposed seed regions in the caudate recapitulated the Give distinct cerebral networks including their multiple spatially distributed regions. These results extend the general notion of parallel specialized basal ganglia circuits, with the additional discovery that even within the caudate, there is Gine-grained separation of multiple distinct higher-order networks.

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bioRxiv2023

Within-Individual Organization of the Human Cerebral Cortex: Networks, Global Topography, and Function

The human cerebral cortex is populated by specialized regions that are organized into networks. Here we estimated networks using a Multi-Session Hierarchical Bayesian sModel (MS-HBM) applied to intensively sampled within-individual functional MRI (fMRI) data. The network estimation procedure was initially developed and tested in two participants (each scanned 31 times) and then prospectively applied to 15 new participants (each scanned 8 to 11 times). Detailed analysis of the networks revealed a global organization. Locally organized first-order sensory and motor networks were surrounded by spatially adjacent second-order networks that also linked to distant regions. Third-order networks each possessed regions distributed widely throughout association cortex. Moreover, regions of distinct third-order networks displayed side-by-side juxtapositions with a pattern that repeated similarly across multiple cortical zones. We refer to these as Supra-Areal Association Megaclusters (SAAMs). Within each SAAM, two candidate control regions were typically adjacent to three separate domain-specialized regions. Independent task data were analyzed to explore functional response properties. The somatomotor and visual first-order networks responded to body movements and visual stimulation, respectively. A subset of the second-order networks responded to transients in an oddball detection task, consistent with a role in orienting to salient or novel events. The third-order networks, including distinct regions within each SAAM, showed two levels of functional specialization. Regions linked to candidate control networks responded to working memory load across multiple stimulus domains. The remaining regions within each SAAM did not track working memory load but rather dissociated across language, social, and spatial / episodic processing domains. These results support a model of the cerebral cortex in which progressively higher-order networks nest outwards from primary sensory and motor cortices. Within the apex zones of association cortex there is specialization of large-scale networks that divides domain-flexible from domain-specialized regions repeatedly across parietal, temporal, and prefrontal cortices. We discuss implications of these findings including how repeating organizational motifs may emerge during development.

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bioRxiv2022

Functional Specialization of Parallel Distributed Networks Revealed by Analysis of Trial-to-Trial Variation in Processing Demands

Multiple large-scale networks populate human association cortex. Here we explored the functional properties of these networks by exploiting trial-to-trial variation in component processing demands. In two behavioral studies (N=136 and N=238), participants quantified strategies used to solve individual task trials that spanned remembering, imagining future scenarios, and various control trials. These trials were also all scanned in an independent sample of functional MRI participants (N=10), each with sufficient data to precisely define within-individual networks. Stable latent factors varied across trials and correlated with trial-level functional responses selectively across networks. One network linked to parahippocampal cortex, labeled Default Network A (DN-A), tracked scene construction, including for control trials that possessed minimal episodic memory demands. To the degree a trial encouraged participants to construct a mental scene with vivid imagery and awareness about spatial locations of objects or places, the response in DN-A increased. The juxtaposed Default Network B (DN-B) showed no such response but varied in relation to social processing demands. Another adjacent network, labeled Frontoparietal Network B (FPN-B), robustly correlated with trial difficulty. These results support that DN-A and DN-B are specialized networks differentially supporting information processing within spatial and social domains. Both networks are dissociable from a closely juxtaposed domain-general control network that tracks cognitive effort.

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bioRxiv2022

A Third Somatomotor Representation in the Human Cerebellum

Seminal neurophysiological studies in the 1940s discovered two somatomotor maps in the cerebellum - an inverted anterior lobe map and an upright posterior lobe map. Both maps have been confirmed in the human using non-invasive neuroimaging with additional hints of a third map near to the cerebellar vermis. Here we sought direct evidence for the third somatomotor map by using intensive, repeated functional MRI (fMRI) scanning of individuals performing movements across multiple body parts (tongue, hands, glutes and feet). An initial discovery sample (N=4, 4 sessions per individual including 576 separate blocks of body movements) yielded evidence for the two established cerebellar somatomotor maps, as well as evidence for a third discontinuous foot representation near to the vermis. When the left versus right foot movements were directly contrasted, the third representation could be clearly distinguished from the second representation in multiple individuals. Functional connectivity from seed regions in the third somatomotor representation confirmed anatomically-specific connectivity with the cortex, paralleling the patterns observed for the two well-established maps. All results were prospectively replicated in an independent dataset with new individuals (N=4). These collective findings provide direct support for a third somatomotor map in the vermis of the cerebellum. We discuss the relations of this candidate third map to the broader topography of the cerebellum as well as its implications for understanding the specific organization of the human cerebellar vermis where distinct zones appear functionally specialized for somatomotor and visual domains.

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bioRxiv2021

Graded variation in cortical T1w/T2w myelination during adolescence

Myelination influences brain connectivity during sensitive periods of development by enhancing neural signaling speed and regulating synapse formation to reduce plasticity. However, in vivo studies characterizing the maturational timing of cortical myelination during human development remain scant. Here, we take advantage of recent advances in high-resolution cortical T1w/T2w myelin mapping methods, including principled correction of B1+ transmit field effects, using data from the Human Connectome Project in Development (N=628, ages 8-21) to characterize the maturational timing of myelination from childhood through early adulthood throughout the cerebral neocortex. We apply Bayesian spline models and functional latent clustering analysis to demonstrate graded variation in the rate of cortical T1w/T2w myelin growth in neocortical areas that is strongly correlated with the sensorimotor-association (S-A) axis of cortical organization reported by others. In sensorimotor areas T1w/T2w myelin starts at high levels at early ages, increases at a fast pace, and decelerates at later ages (18-21). In intermediate multimodal areas along the S-A axis, T1w/T2w myelin tends to start at intermediate levels and increase linearly at an intermediate pace. In transmodal/paralimbic association areas high along the S-A axis, T1w/T2w myelin tends to start at low levels and increase linearly at the slowest pace. These data provide evidence for graded variation along the S-A axis in the rate of cortical myelination during adolescence, which could reflect ongoing plasticity underlying the development of complex information processing and psychological functioning. Significance StatementMyelin is a lipid membrane that is essential to healthy brain function. Myelin wraps axons to increase neural signaling speed, enabling complex neuronal functioning underlying learning and cognition. Here we characterize the developmental timing of myelination across the cerebral cortex during adolescence using recent advances in non-invasive myelin mapping. Our results provide new evidence demonstrating graded variation across the cortex in the timing of myelination during adolescence, with rapid myelination in lower-order sensory areas and gradual myelination in higher-order association areas. This spatial pattern of microstructural brain development closely parallels the sensorimotor-to-association axis of cortical organization and plasticity during ontogeny.

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bioRxiv2021

DPSleep: Open-Source Longitudinal Sleep Analysis From Accelerometer Data

Wearable devices are now widely available to collect continuous objective behavioral data from individuals and to measure sleep. Here we introduce a pipeline to infer sleep onset, duration, and quality from raw accelerometer data and then quantify relationships between derived sleep metrics and other variables of interest. The pipeline released here for the deep phenotyping of sleep, as the "DPSleep" software package, uses (a) a stepwise algorithm to detect missing data; (b) within-individual, minute-based, spectral power percentiles of activity; and (c) iterative, forward- and backward-sliding windows to estimate the major Sleep Episode onset and offset. Software modules allow for manual quality control adjustment of derived sleep features and correction for time zone changes. In this report, we illustrate the pipeline with data from participants studied for more than 200 days each. Actigraphy-based measures of sleep duration are associated with self-report rating of sleep quality. Simultaneous measures of smartphone use and GPS location data support the validity of the sleep timing inferences and reveal how phone measures of sleep timing can differ from actigraphy data. We discuss the uses of DPSleep in relation to other available sleep estimation approaches and provide example use cases that include multi-dimensional, deep longitudinal phenotyping, extended measurement of dynamics associated with mental illness, and the possibility of combining wearable actigraphy and personal electronic device data (e.g., smartphone, tablet) to measure individual differences across a wide range of behavioral variation in health and disease.

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