Brainwide functional networks associated with anatomically- and functionally-defined hippocampal subfields using ultrahigh-resolution fMRI

AbstractThe hippocampus is critical for learning and memory and may be separated into anatomically-defined hippocampal subfields (aHPSFs). Hippocampal functional networks, particularly during resting state, are generally analyzed using aHPSFs as seed regions, with the underlying assumption that the function within a subfield is homogeneous, yet heterogeneous between subfields. However, several prior studies have observed similar resting-state functional connectivity (FC) profiles between aHPSFs. Alternatively, data-driven approaches investigate hippocampal functional organization without a priori assumptions. However, insufficient spatial resolution may result in a number of caveats concerning the reliability of the results. Hence, we developed a functional Magnetic Resonance Imaging (fMRI) sequence on a 7 T MR scanner achieving 0.94 mm isotropic resolution with a TR of 2 s and brain-wide coverage to (1) investigate the functional organization within hippocampus at rest, and (2) compare the brain-wide FC associated with fine-grained aHPSFs and functionally-defined hippocampal subfields (fHPSFs). This study showed that fHPSFs were arranged along the longitudinal axis that were not comparable to the lamellar structures of aHPSFs. For brain-wide FC, the fHPSFs rather than aHPSFs revealed that a number of fHPSFs connected specifically with some of the functional networks. Different functional networks also showed preferential connections with different portions of hippocampal subfields.

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Brain-Wide Functional Networks Associated With Anatomically- and Functionally-Defined Hippocampal Subfields Using Ultrahigh-Resolution fMRI

10.21203/rs.3.rs-129412/v1 ◽

2020 ◽

Author(s):

Wei-Tang Chang ◽

Stephanie Langella ◽

Yichuan Tang ◽

Sahar Ahmad ◽

Han Zhang ◽

...

Keyword(s):

Resting State ◽

Functional Organization ◽

A Priori ◽

Longitudinal Axis ◽

Functional Networks ◽

Resting State Functional Connectivity ◽

Underlying Assumption ◽

Isotropic Resolution ◽

Hippocampal Subfields ◽

Fine Grained

Abstract The hippocampus is critical for learning and memory and may be separated into anatomically-defined hippocampal subfields (aHPSFs). Hippocampal functional networks, particularly during resting state, are generally analyzed using aHPSFs as seed regions, with the underlying assumption that the function within a subfield is homogeneous, yet heterogeneous between subfields. However, several prior studies have observed similar resting-state functional connectivity (FC) profiles between aHPSFs. Alternatively, data-driven approaches investigate hippocampal functional organization without a priori assumptions. However, insufficient spatial resolution may result in a number of caveats concerning the reliability of the results. Hence, we developed a functional Magnetic Resonance Imaging (fMRI) sequence on a 7T MR scanner achieving 0.94 mm isotropic resolution with a TR of 2s and brain-wide coverage to 1) investigate the functional organization within hippocampus at rest, and 2) compare the brain-wide FC associated with fine-grained aHPSFs and functionally-defined hippocampal subfields (fHPSFs). This study showed that fHPSFs were arranged along the longitudinal axis that were not comparable to the lamellar structures of aHPSFs. For brain-wide FC, the fHPSFs rather than aHPSFs revealed that a number of fHPSFs connected specifically with some of the functional networks. Different functional networks also showed preferential connections with different portions of hippocampal subfields.

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Brain-wide functional networks associated with anatomically- and functionally-defined hippocampal subfields using ultrahigh-resolution fMRI

10.1101/2020.12.01.407049 ◽

2020 ◽

Author(s):

Wei-Tang Chang ◽

Stephanie K. Langella ◽

Yichuan Tang ◽

Han Zhang ◽

Pew-Thian Yap ◽

...

Keyword(s):

Resting State ◽

Functional Organization ◽

Longitudinal Axis ◽

Functional Networks ◽

Resting State Functional Connectivity ◽

Ultrahigh Resolution ◽

Underlying Assumption ◽

Isotropic Resolution ◽

Hippocampal Subfields ◽

Lamellar Structures

ABSTRACTThe hippocampus is critical for learning and memory and may be separated into anatomically-defined hippocampal subfields (aHPSFs). Many studies have shown that aHPSFs, and their respective functional networks, are differentially vulnerable to a variety of disorders. Hippocampal functional networks, particularly during resting state, are generally analyzed using aHPSFs as seed regions, with the underlying assumption that the function within a subfield is homogeneous, yet heterogeneous between subfields. However, several prior studies that have utilized aHPSFs and assessed brain-wide cortical connectivity have observed similar resting-state functional connectivity profiles between aHPSFs. Alternatively, data-driven approaches offer a means to investigate hippocampal functional organization without a priori assumptions. However, insufficient spatial resolution may lead to partial volume effects at the boundaries of hippocampal subfields, resulting in a number of caveats concerning the reliability of the results. Hence, we developed a functional Magnetic Resonance Imaging (fMRI) sequence on a 7T MR scanner achieving 0.94 mm isotropic resolution with a TR of 2s and brain-wide coverage to 1) investigate whether hippocampal functional segmentation with ultrahigh-resolution data demonstrate similar anatomical, lamellar structures in the hippocampus, and 2) define and compare the brain-wide FC associated with fine-grained aHPSFs and functionally-defined hippocampal subfields (fHPSFs). Using a spatially restricted hippocampal Independent Component Analysis (ICA) approach, this study showed that fHPSFs were arranged along the longitudinal axis of the hippocampus that were not comparable to the lamellar structures of aHPSFs. Contrary to the anatomically defined hippocampal subfields which are bilaterally symmetrical, 13 out of 20 fHPSFs were unilateral. For brain-wide FC, the fHPSFs rather than aHPSFs revealed that a number of fHPSFs connected specifically with some of the functional networks. The visual and sensorimotor networks preferentially connected with different portions of CA1, CA3 and CA4/DG. The DMN was also found to connect more extensively with posterior subfields rather than anterior subfields. Finally, the frontoparietal network (FPN) was anticorrelated with the head portion of CA1. The investigation of functional networks associated with the fHPSFs may enhance the sensitivity of biomarkers for a range of neurological disorders, as network-based approaches take into account disease-related alterations in brain-wide interconnections rather than measuring the regional changes of hippocampus.

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Resting-state functional connectivity of emotion regulation networks in euthymic and non-euthymic bipolar disorder patients

European Psychiatry ◽

10.1016/j.eurpsy.2015.12.005 ◽

2016 ◽

Vol 34 ◽

pp. 56-63 ◽

Cited By ~ 28

Author(s):

G. Rey ◽

C Piguet ◽

A Benders ◽

S Favre ◽

SB Eickhoff ◽

...

Keyword(s):

Bipolar Disorder ◽

Functional Connectivity ◽

Resting State ◽

Clinical Symptoms ◽

Mood State ◽

A Priori ◽

Emotion Processing ◽

Population Sample ◽

Small Population ◽

Resting State Functional Connectivity

AbstractBackgroundPrevious functional magnetic resonance imaging studies in bipolar disorder (BD) have evidenced changes in functional connectivity (FC) in brain areas associated with emotion processing, but how these changes vary with mood state and specific clinical symptoms is not fully understood.MethodsWe investigated resting-state FC between a priori regions of interest (ROIs) from the default-mode network and key structures for emotion processing and regulation in 27 BD patients and 27 matched healthy controls. We further compared connectivity patterns in subgroups of 15 euthymic and 12 non-euthymic patients and tested for correlations of the connectivity strength with measures of mood, anxiety, and rumination tendency. No correction for multiple comparisons was applied given the small population sample and pre-defined target ROIs.ResultsOverall, regardless of mood state, BD patients exhibited increased FC of the left amygdala with left sgACC and PCC, relative to controls. In addition, non-euthymic BD patients showed distinctive decrease in FC between right amygdala and sgACC, whereas euthymic patients showed lower FC between PCC and sgACC. Euthymic patients also displayed increased FC between sgACC and right VLPFC. The sgACC–PCC and sgACC–left amygdala connections were modulated by rumination tendency in non-euthymic patients, whereas the sgACC-VLPFC connection was modulated by both the current mood and tendency to ruminate.ConclusionsOur results suggest that sgACC-amygdala coupling is critically affected during mood episodes, and that FC of sgACC play a pivotal role in mood normalization through its interactions with the VLPFC and PCC. However, these preliminary findings require replication with larger samples of patients.

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Functional Segregation of Human Brain Networks Across the Lifespan: An Exploratory Analysis of Static and Dynamic Resting-State Functional Connectivity

Frontiers in Neuroscience ◽

10.3389/fnins.2020.561594 ◽

2020 ◽

Vol 14 ◽

Author(s):

Benjamin M. Rosenberg ◽

Eva Mennigen ◽

Martin M. Monti ◽

Roselinde H. Kaiser

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Dwell Time ◽

Brain Networks ◽

Older Age ◽

Functional Network ◽

Functional Networks ◽

Resting State Functional Connectivity ◽

Network State ◽

High Connectivity

Prior research has shown that during development, there is increased segregation between, and increased integration within, prototypical resting-state functional brain networks. Functional networks are typically defined by static functional connectivity over extended periods of rest. However, little is known about how time-varying properties of functional networks change with age. Likewise, a comparison of standard approaches to functional connectivity may provide a nuanced view of how network integration and segregation are reflected across the lifespan. Therefore, this exploratory study evaluated common approaches to static and dynamic functional network connectivity in a publicly available dataset of subjects ranging from 8 to 75 years of age. Analyses evaluated relationships between age and static resting-state functional connectivity, variability (standard deviation) of connectivity, and mean dwell time of functional network states defined by recurring patterns of whole-brain connectivity. Results showed that older age was associated with decreased static connectivity between nodes of different canonical networks, particularly between the visual system and nodes in other networks. Age was not significantly related to variability of connectivity. Mean dwell time of a network state reflecting high connectivity between visual regions decreased with age, but older age was also associated with increased mean dwell time of a network state reflecting high connectivity within and between canonical sensorimotor and visual networks. Results support a model of increased network segregation over the lifespan and also highlight potential pathways of top-down regulation among networks.

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Brain connectivity at rest predicts individual differences in normative activity during movie watching

10.1101/2021.01.06.425410 ◽

2021 ◽

Author(s):

David C Gruskin ◽

Gaurav H Patel

Keyword(s):

Spatial Distribution ◽

Individual Differences ◽

Resting State ◽

Functional Organization ◽

Brain Connectivity ◽

Brain Activity ◽

Sensory Information ◽

Resting State Functional Connectivity ◽

Similar Region ◽

Human Connectome Project

When multiple individuals are exposed to the same sensory event, some are bound to have less typical experiences than others. These atypical experiences are underpinned by atypical stimulus-evoked brain activity, the extent of which is often indexed by intersubject correlation (ISC). Previous research has attributed individual differences in ISC to variation in trait-like behavioral phenotypes. Here, we extend this line of work by showing that an individual's degree and spatial distribution of ISC are closely related to their brain's intrinsic functional architecture. Using resting state and movie watching fMRI data from 176 Human Connectome Project participants, we reveal that resting state functional connectivity (RSFC) profiles can be used to predict cortex-wide ISC with considerable accuracy. Similar region-level analyses demonstrate that the amount of ISC a brain region exhibits during movie watching is associated with its connectivity to others at rest, and that the nature of these connectivity-activity relationships varies as a function of the region's role in sensory information processing. Finally, we show that an individual's unique spatial distribution of ISC, independent of its magnitude, is also related to their RSFC profile. These findings suggest that the brain's ability to process complex sensory information is tightly linked to its baseline functional organization and motivate a more comprehensive understanding of individual responses to naturalistic stimuli.

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The Role of the Human Brain Neuron–Glia–Synapse Composition in Forming Resting-State Functional Connectivity Networks

Brain Sciences ◽

10.3390/brainsci11121565 ◽

2021 ◽

Vol 11 (12) ◽

pp. 1565

Author(s):

Sayan Kahali ◽

Marcus E Raichle ◽

Dmitriy A Yablonskiy

Keyword(s):

Human Brain ◽

Resting State ◽

Functional Networks ◽

Bold Signal ◽

Resting State Functional Connectivity ◽

Healthy Human ◽

Neuronal Density ◽

Wide Range ◽

Functional Units ◽

The Brain

While significant progress has been achieved in studying resting-state functional networks in a healthy human brain and in a wide range of clinical conditions, many questions related to their relationship to the brain’s cellular constituents remain. Here, we use quantitative Gradient-Recalled Echo (qGRE) MRI for mapping the human brain cellular composition and BOLD (blood–oxygen level-dependent) MRI to explore how the brain cellular constituents relate to resting-state functional networks. Results show that the BOLD signal-defined synchrony of connections between cellular circuits in network-defined individual functional units is mainly associated with the regional neuronal density, while the between-functional units’ connectivity strength is also influenced by the glia and synaptic components of brain tissue cellular constituents. These mechanisms lead to a rather broad distribution of resting-state functional network properties. Visual networks with the highest neuronal density (but lowest density of glial cells and synapses) exhibit the strongest coherence of the BOLD signal as well as the strongest intra-network connectivity. The Default Mode Network (DMN) is positioned near the opposite part of the spectrum with relatively low coherence of the BOLD signal but with a remarkably balanced cellular contents, enabling DMN to have a prominent role in the overall organization of the brain and hierarchy of functional networks.

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Heritability of hippocampal functional and microstructural organisation

10.1101/2021.11.10.468049 ◽

2021 ◽

Author(s):

Seyma Bayrak ◽

Reinder Vos de Wael ◽

H. Lina Schaare ◽

Benoit Caldairou ◽

Andrea Bernasconi ◽

...

Keyword(s):

Functional Connectivity ◽

Medial Temporal Lobe ◽

Functional Organization ◽

Hippocampal Formation ◽

Resting State Functional Connectivity ◽

Hippocampal Subfields ◽

Emotional Processes ◽

Human Connectome Project ◽

Cornu Ammonis ◽

Learning And Plasticity

The hippocampal formation is an uniquely infolded anatomical structure in the medial temporal lobe and it is involved in a broad range of cognitive and emotional processes. It consists of anatomically and functionally different subfields, including the subiculum (SUB), cornu ammonis areas (CA), and the dentate gyrus (DG). However, despite ample research on learning and plasticity of the hippocampal formation, heritability of its structural and functional organization is not fully known. To answer this question, we extracted microstructurally sensitive neuroimaging (i.e., T1w/T2w ratios) and resting-state functional connectivity information along hippocampal subfield surfaces from a sample of healthy twins and unrelated individuals of the Human Connectome Project Dataset. Our findings robustly demonstrate that functional connectivity and local microstructure of hippocampal subfields are highly heritable. Second, we found marked covariation and genetic correlation between the microstructure of the hippocampal subfields and the isocortex, indicating shared genetic factors influencing the microstructure of the hippocampus and isocortex. In both structural and functional measures, we observed a dissociation of cortical projections across subfields. In sum, our study shows that the functional and structural organization of the hippocampal formation is heritable and has a genetic relation to divergent macroscale functional networks within the isocortex.

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Connectome-based Models Predict Separable Components of Attention in Novel Individuals

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_01197 ◽

2018 ◽

Vol 30 (2) ◽

pp. 160-173 ◽

Cited By ~ 38

Author(s):

Monica D. Rosenberg ◽

Wei-Ting Hsu ◽

Dustin Scheinost ◽

R. Todd Constable ◽

Marvin M. Chun

Keyword(s):

Functional Connectivity ◽

Sustained Attention ◽

Executive Control ◽

Resting State ◽

Functional Organization ◽

Cognitive Conflict ◽

Annual Review ◽

Resting State Functional Connectivity ◽

Independent Components ◽

Functional Brain Networks

Although we typically talk about attention as a single process, it comprises multiple independent components. But what are these components, and how are they represented in the functional organization of the brain? To investigate whether long-studied components of attention are reflected in the brain's intrinsic functional organization, here we apply connectome-based predictive modeling (CPM) to predict the components of Posner and Petersen's influential model of attention: alerting (preparing and maintaining alertness and vigilance), orienting (directing attention to a stimulus), and executive control (detecting and resolving cognitive conflict) [Posner, M. I., & Petersen, S. E. The attention system of the human brain. Annual Review of Neuroscience, 13, 25–42, 1990]. Participants performed the Attention Network Task (ANT), which measures these three factors, and rested during fMRI scanning. CPMs tested with leave-one-subject-out cross-validation successfully predicted novel individual's overall ANT accuracy, RT variability, and executive control scores from functional connectivity observed during ANT performance. CPMs also generalized to predict participants' alerting scores from their resting-state functional connectivity alone, demonstrating that connectivity patterns observed in the absence of an explicit task contain a signature of the ability to prepare for an upcoming stimulus. Suggesting that significant variance in ANT performance is also explained by an overall sustained attention factor, the sustained attention CPM, a model defined in prior work to predict sustained attentional abilities, predicted accuracy, RT variability, and executive control from task-based data and predicted RT variability from resting-state data. Our results suggest that, whereas executive control may be closely related to sustained attention, the infrastructure that supports alerting is distinct and can be measured at rest. In the future, CPM may be applied to elucidate additional independent components of attention and relationships between the functional brain networks that predict them.

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In silico exploration of mouse brain dynamics by focal stimulation reflects the organization of functional networks and sensory processing

Network Neuroscience ◽

10.1162/netn_a_00152 ◽

2020 ◽

Vol 4 (3) ◽

pp. 807-851

Author(s):

Andreas Spiegler ◽

Javad Karimi Abadchi ◽

Majid Mohajerani ◽

Viktor K. Jirsa

Keyword(s):

Information Processing ◽

Sensory Processing ◽

Resting State ◽

Functional Organization ◽

Brain Dynamics ◽

Functional Networks ◽

Brain Responses ◽

Sensory Cortices ◽

Stimulation Paradigm

Resting-state functional networks such as the default mode network (DMN) dominate spontaneous brain dynamics. To date, the mechanisms linking brain structure and brain dynamics and functions in cognition, perception, and action remain unknown, mainly due to the uncontrolled and erratic nature of the resting state. Here we used a stimulation paradigm to probe the brain’s resting behavior, providing insights on state-space stability and multiplicity of network trajectories after stimulation. We performed explorations on a mouse model to map spatiotemporal brain dynamics as a function of the stimulation site. We demonstrated the emergence of known functional networks in brain responses. Several responses heavily relied on the DMN and were suggestive of the DMN playing a mechanistic role between functional networks. We probed the simulated brain responses to the stimulation of regions along the information processing chains of sensory systems from periphery up to primary sensory cortices. Moreover, we compared simulated dynamics against in vivo brain responses to optogenetic stimulation. Our results underwrite the importance of anatomical connectivity in the functional organization of brain networks and demonstrate how functionally differentiated information processing chains arise from the same system.

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