scholarly journals Overlapping connectivity gradients in the anterior temporal lobe underlie semantic cognition

2020 ◽  
Author(s):  
Myrthe Faber ◽  
Izabela Przeździk ◽  
Guillén Fernández ◽  
Koen V. Haak ◽  
Christian F. Beckmann
Keyword(s):  
Individual Differences ◽  
Functional Connectivity ◽  
Temporal Lobe ◽  
Functional Organization ◽  
The Other ◽  
Story Comprehension ◽  
Anterior Temporal Lobe ◽  
Semantic Cognition ◽  
Human Connectome Project ◽  
Spatially Varying

AbstractConvergent evidence from neuroimaging, computational, and clinical research has shown that the anterior temporal lobe (ATL) is critically involved in two key aspects of semantic cognition: the representation of semantic knowledge, and the executive regulation of this knowledge. Both are necessary for integrating features to understand concepts, and to integrate concepts to understand discourse. Here, we tested the hypothesis that these differential aspects of integration map onto different patterns of ATL connectivity. Specifically, we hypothesized that there are two overlapping modes of functional connectivity of the ATL that each predict distinct aspects of semantic cognition on an individual level. We used a novel analytical approach (connectopic mapping) to identify the first two dominant modes connection topographies (i.e. maps of spatially varying connectivity) in the ATL in 766 participants (Human Connectome Project), and summarized these into 16 parameters that reflect inter-individual differences in their functional organization. If these connection topographies reflect the ATL’s functional multiplicity, then we would expect to find a dissociation where one mode (but not the other) correlates with cross-modal matching of verbal and visual information (picture vocabulary naming), and the other (but not the former) correlates with how quickly and accurately relevant semantic information is retrieved (story comprehension). Our analysis revealed a gradient of spatially varying connectivity along the inferior-superior axis, and secondly, an anterior to posterior gradient. Multiple regression analyses revealed a double dissociation such that individual differences in the inferior-superior gradient are predictive of differences in story comprehension, whereas the anterior-posterior gradient maps onto differences in picture vocabulary naming, but not vice versa. These findings indicate that overlapping gradients of functional connectivity in the ATL are related to differential behaviors, which is important for understanding how its functional organization underlies its multiple functions.

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

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.

scholarly journals Heritability of hippocampal functional and microstructural organisation

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.

scholarly journals Familiarity impairments after anterior temporal-lobe resection with hippocampal sparing: Lessons learned from case NB

2019 ◽  
Author(s):  
Stefan Köhler ◽  
Chris B. Martin
Keyword(s):  
Temporal Lobe ◽  
Functional Organization ◽  
Single Case ◽  
Perirhinal Cortex ◽  
Lessons Learned ◽  
Dual Process ◽  
Medial Temporal Lobes ◽  
Anterior Temporal Lobe ◽  
Temporal Lobe Resection ◽  
Feature Overlap

We review evidence from an extensive single case study in an individual (NB) who underwent a rare left-sided anterior temporal-lobe resection with sparing of the hippocampus. Our study aimed to determine whether memory functions of perirhinal cortex, which was largely removed in the resection, can be impaired against a background of preserved hippocampus-dependent memory processing. This research was guided by the proposal that item-based familiarity assessment relies on contributions of perirhinal cortex, and that the hippocampus plays a unique role in the relational binding of items to episodic contexts, which is critical for recollection. Seven sets of findings have emerged from this research in NB and from follow-up work in other patients: (i) Familiarity impairments can be selective and be revealed with multiple methods; (ii) selective familiarity and selective recollection impairments can be double dissociated; (iii) selective familiarity impairments show material specificity; (iv) selective familiarity impairments extend to assessment of cumulative lifetime experience; (v) selective familiarity impairments are sensitive to degree of feature overlap between object concepts; (vi) selective familiarity impairments are associated with preserved task-related fMRI signals in the hippocampus; (vii) selective familiarity impairments can be observed in other lesion cases. Despite our main focus on the dual-process framework, we also discuss implications for the functional organization of the medial temporal lobes in broader terms. We argue that our findings shed light on this organization even if the functional specialization of different medial temporal structures is ultimately not fully captured with reference to the cognitive distinction between familiarity and recollection.

scholarly journals General Functional Connectivity: shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks

2018 ◽  
Author(s):  
Maxwell L. Elliott ◽  
Annchen R. Knodt ◽  
Megan Cooke ◽  
M. Justin Kim ◽  
Tracy R. Melzer ◽  
...  
Keyword(s):  
Individual Differences ◽  
Functional Connectivity ◽  
Resting State ◽  
Biomarker Discovery ◽  
Resting State Functional Connectivity ◽  
Heritable Variation ◽  
State Data ◽  
Human Connectome Project ◽  
Intrinsic Connectivity ◽  
And Task

AbstractIntrinsic connectivity, measured using resting-state fMRI, has emerged as a fundamental tool in the study of the human brain. However, due to practical limitations, many studies do not collect enough resting-state data to generate reliable measures of intrinsic connectivity necessary for studying individual differences. Here we present general functional connectivity (GFC) as a method for leveraging shared features across resting-state and task fMRI and demonstrate in the Human Connectome Project and the Dunedin Study that GFC offers better test-retest reliability than intrinsic connectivity estimated from the same amount of resting-state data alone. Furthermore, at equivalent scan lengths, GFC displays higher heritability on average than resting-state functional connectivity. We also show that predictions of cognitive ability from GFC generalize across datasets, performing as well or better than resting-state or task data alone. Collectively, our work suggests that GFC can improve the reliability of intrinsic connectivity estimates in existing datasets and, subsequently, the opportunity to identify meaningful correlates of individual differences in behavior. Given that task and resting-state data are often collected together, many researchers can immediately derive more reliable measures of intrinsic connectivity through the adoption of GFC rather than solely using resting-state data. Moreover, by better capturing heritable variation in intrinsic connectivity, GFC represents a novel endophenotype with broad applications in clinical neuroscience and biomarker discovery.

scholarly journals Innate connectivity patterns drive the development of the visual word form area

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Jin Li ◽  
David E. Osher ◽  
Heather A. Hansen ◽  
Zeynep M. Saygin
Keyword(s):  
Functional Connectivity ◽  
Functional Organization ◽  
Visual Word ◽  
Word Form ◽  
Functional Magnetic Resonance ◽  
Visual Word Form Area ◽  
Human Connectome Project ◽  
Connectivity Patterns ◽  
Set Up ◽  
Language Network

Abstract What determines the functional organization of cortex? One hypothesis is that innate connectivity patterns, either structural or functional connectivity, set up a scaffold upon which functional specialization can later take place. We tested this hypothesis by asking whether the visual word form area (VWFA), an experience-driven region, was already functionally connected to proto language networks in neonates scanned within one week of birth. Using the data from the Human Connectone Project (HCP) and the Developing Human Connectome Project (dHCP), we calculated intrinsic functional connectivity during resting-state functional magnetic resonance imaging (fMRI), and found that neonates showed similar functional connectivity patterns to adults. We observed that (1) language regions connected more strongly with the putative VWFA than other adjacent ventral visual regions that also show foveal bias, and (2) the VWFA connected more strongly with frontotemporal language regions than with regions adjacent to these language regions. These data suggest that the location of the VWFA is earmarked at birth due to its connectivity with the language network, providing evidence that innate connectivity instructs the later refinement of cortex.

scholarly journals Transdiagnostic, Connectome-Based Prediction of Memory Constructs Across Psychiatric Disorders

2020 ◽  
Author(s):  
Daniel S Barron ◽  
Siyuan Gao ◽  
Javid Dadashkarimi ◽  
Abigail S Greene ◽  
Marisa N Spann ◽  
...  
Keyword(s):  
Individual Differences ◽  
Functional Connectivity ◽  
Psychiatric Disorders ◽  
Memory Performance ◽  
Brain Networks ◽  
Memory Deficits ◽  
Computational Method ◽  
Long Term Memory ◽  
Whole Brain ◽  
Human Connectome Project

Abstract Memory deficits are observed in a range of psychiatric disorders, but it is unclear whether memory deficits arise from a shared brain correlate across disorders or from various dysfunctions unique to each disorder. Connectome-based predictive modeling is a computational method that captures individual differences in functional connectomes associated with behavioral phenotypes such as memory. We used publicly available task-based functional MRI data from patients with schizophrenia (n = 33), bipolar disorder (n = 34), attention deficit hyper-activity disorder (n = 32), and healthy controls (n = 73) to model the macroscale brain networks associated with working, short- and long-term memory. First, we use 10-fold and leave-group-out analyses to demonstrate that the same macroscale brain networks subserve memory across diagnostic groups and that individual differences in memory performance are related to individual differences within networks distributed throughout the brain, including the subcortex, default mode network, limbic network, and cerebellum. Next, we show that diagnostic groups are associated with significant differences in whole-brain functional connectivity that are distinct from the predictive models of memory. Finally, we show that models trained on the transdiagnostic sample generalize to novel, healthy participants (n = 515) from the Human Connectome Project. These results suggest that despite significant differences in whole-brain patterns of functional connectivity between diagnostic groups, the core macroscale brain networks that subserve memory are shared.

scholarly journals Distributed Patterns of Functional Connectivity Predict Working Memory Performance in Novel Healthy and Memory-impaired Individuals

2020 ◽  
Vol 32 (2) ◽  
pp. 241-255 ◽  
Author(s):  
Emily W. Avery ◽  
Kwangsun Yoo ◽  
Monica D. Rosenberg ◽  
Abigail S. Greene ◽  
Siyuan Gao ◽  
...  
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Functional Connectivity ◽  
Sustained Attention ◽  
Fluid Intelligence ◽  
Memory Performance ◽  
Data Set ◽  
Human Connectome Project ◽  
Connectivity Patterns ◽  
Intelligence Models

Individual differences in working memory relate to performance differences in general cognitive ability. The neural bases of such individual differences, however, remain poorly understood. Here, using a data-driven technique known as connectome-based predictive modeling, we built models to predict individual working memory performance from whole-brain functional connectivity patterns. Using n-back or rest data from the Human Connectome Project, connectome-based predictive models significantly predicted novel individuals' 2-back accuracy. Model predictions also correlated with measures of fluid intelligence and, with less strength, sustained attention. Separate fluid intelligence models predicted working memory score, as did sustained attention models, again with less strength. Anatomical feature analysis revealed significant overlap between working memory and fluid intelligence models, particularly in utilization of prefrontal and parietal regions, and less overlap in predictive features between working memory and sustained attention models. Furthermore, showing the generality of these models, the working memory model developed from Human Connectome Project data generalized to predict memory in an independent data set of 157 older adults (mean age = 69 years; 48 healthy, 54 amnestic mild cognitive impairment, 55 Alzheimer disease). The present results demonstrate that distributed functional connectivity patterns predict individual variation in working memory capability across the adult life span, correlating with constructs including fluid intelligence and sustained attention.

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