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Litwińczuk MC, Muhlert N, Trujillo‐Barreto N, Woollams A. Impact of brain parcellation on prediction performance in models of cognition and demographics. Hum Brain Mapp 2024; 45:e26592. [PMID: 38339892 PMCID: PMC10831203 DOI: 10.1002/hbm.26592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 12/18/2023] [Accepted: 12/31/2023] [Indexed: 02/12/2024] Open
Abstract
Brain connectivity analysis begins with the selection of a parcellation scheme that will define brain regions as nodes of a network whose connections will be studied. Brain connectivity has already been used in predictive modelling of cognition, but it remains unclear if the resolution of the parcellation used can systematically impact the predictive model performance. In this work, structural, functional and combined connectivity were each defined with five different parcellation schemes. The resolution and modality of the parcellation schemes were varied. Each connectivity defined with each parcellation was used to predict individual differences in age, education, sex, executive function, self-regulation, language, encoding and sequence processing. It was found that low-resolution functional parcellation consistently performed above chance at producing generalisable models of both demographics and cognition. However, no single parcellation scheme showed a superior predictive performance across all cognitive domains and demographics. In addition, although parcellation schemes impacted the graph theory measures of each connectivity type (structural, functional and combined), these differences did not account for the out-of-sample predictive performance of the models. Taken together, these findings demonstrate that while high-resolution parcellations may be beneficial for modelling specific individual differences, partial voluming of signals produced by the higher resolution of the parcellation likely disrupts model generalisability.
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Affiliation(s)
| | - Nils Muhlert
- School of Health SciencesUniversity of ManchesterManchesterUK
| | | | - Anna Woollams
- School of Health SciencesUniversity of ManchesterManchesterUK
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2
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Diveica V, Riedel MC, Salo T, Laird AR, Jackson RL, Binney RJ. Graded functional organization in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity. Cereb Cortex 2023; 33:11384-11399. [PMID: 37833772 PMCID: PMC10690868 DOI: 10.1093/cercor/bhad373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 08/17/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023] Open
Abstract
The left inferior frontal gyrus has been ascribed key roles in numerous cognitive domains, such as language and executive function. However, its functional organization is unclear. Possibilities include a singular domain-general function, or multiple functions that can be mapped onto distinct subregions. Furthermore, spatial transition in function may be either abrupt or graded. The present study explored the topographical organization of the left inferior frontal gyrus using a bimodal data-driven approach. We extracted functional connectivity gradients from (i) resting-state fMRI time-series and (ii) coactivation patterns derived meta-analytically from heterogenous sets of task data. We then sought to characterize the functional connectivity differences underpinning these gradients with seed-based resting-state functional connectivity, meta-analytic coactivation modeling and functional decoding analyses. Both analytic approaches converged on graded functional connectivity changes along 2 main organizational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior functional connectivity) to being more tightly coupled with perceptually driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal functional connectivity), and with the semantic network, on the other (ventral). These results provide novel insights into an overarching graded functional organization of the functional connectivity that explains its role in multiple cognitive domains.
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Affiliation(s)
- Veronica Diveica
- Department of Psychology & Cognitive Neuroscience Institute, Bangor University, Bangor, Wales LL57 2AS, United Kingdom
- Department of Neurology and Neurosurgery & Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Michael C Riedel
- Department of Physics, Florida International University, Miami, FL 33199, United States
| | - Taylor Salo
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, 19104, United States
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL 33199, United States
| | - Rebecca L Jackson
- Department of Psychology & York Biomedical Research Institute, University of York, York, YO10 5DD, United Kingdom
| | - Richard J Binney
- Department of Psychology & Cognitive Neuroscience Institute, Bangor University, Bangor, Wales LL57 2AS, United Kingdom
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Rajesh A, Seider NA, Newbold DJ, Adeyemo B, Marek S, Greene DJ, Snyder AZ, Shimony JS, Laumann TO, Dosenbach NUF, Gordon EM. Structure-Function Coupling in Highly Sampled Individual Brains. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.04.560909. [PMID: 37873167 PMCID: PMC10592963 DOI: 10.1101/2023.10.04.560909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Structural connections (SC) between distant regions of the brain support synchronized function known as functional connectivity (FC) and give rise to the large-scale brain networks that enable cognition and behavior. Understanding how SC enables FC is important to understand how injuries to structural connections may alter brain function and cognition. Previous work evaluating whole-brain SC-FC relationships showed that SC explained FC well in unimodal visual and motor areas, but only weakly in association areas, suggesting a unimodal-heteromodal gradient organization of SC-FC coupling. However, this work was conducted in group-averaged SC/FC data. Thus, it could not account for inter-individual variability in the locations of cortical areas and white matter tracts. We evaluated the correspondence of SC and FC within three highly sampled healthy participants. For each participant, we collected 78 minutes of diffusion-weighted MRI for SC and 360 minutes of resting state fMRI for FC. We found that FC was best explained by SC in visual and motor systems, as well as in anterior and posterior cingulate regions. A unimodal-to-heteromodal gradient could not fully explain SC-FC coupling. We conclude that the SC-FC coupling of the anterior-posterior cingulate circuit is more similar to unimodal areas than to heteromodal areas. SIGNIFICANCE STATEMENT Structural connections between distant regions of the human brain support networked function that enables cognition and behavior. Improving our understanding of how structure enables function could allow better insight into how brain disconnection injuries impair brain function.Previous work using neuroimaging suggested that structure-function relationships vary systematically across the brain, with structure better explaining function in basic visual/motor areas than in higher-order areas. However, this work was conducted in group-averaged data, which may obscure details of individual-specific structure-function relationships.Using individual-specific densely sampled neuroimaging data, we found that in addition to visual/motor regions, structure strongly predicts function in specific circuits of the higher-order cingulate gyrus. The cingulate's structure-function relationship suggests that its organization may be unique among higher-order cortical regions.
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Zhang R, Wang J, Lin H, Turk-Browne NB, Cai Q. Neural signatures of second language proficiency in narrative processing. Cereb Cortex 2023:7143624. [PMID: 37100085 DOI: 10.1093/cercor/bhad133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 03/22/2023] [Accepted: 03/23/2023] [Indexed: 04/28/2023] Open
Abstract
Making sense of speech in a second language relies on multiple abilities. Differences in brain activity related to proficiency in language tasks have often been attributed to processing demands. However, during naturalistic narrative comprehension, listeners at different proficiency levels may form different representations of the same speech. We hypothesized that the intersubject synchronization of these representations could be used to measure second-language proficiency. Using a searchlight-shared response model, we found highly proficient participants showed synchronization in regions similar to those of native speakers, including in the default mode network and the lateral prefrontal cortex. In contrast, participants with low proficiency showed more synchronization in auditory cortex and word-level semantic processing areas in the temporal lobe. Moderate proficiency showed the greatest neural diversity, suggesting lower consistency in the source of this partial proficiency. Based on these synchronization differences, we were able to classify the proficiency level or predict behavioral performance on an independent English test in held-out participants, suggesting the identified neural systems represented proficiency-sensitive information that was generalizable to other individuals. These findings suggest higher second-language proficiency leads to more native-like neural processing of naturalistic language, including in systems beyond the cognitive control network or the core language network.
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Affiliation(s)
- Ruiqing Zhang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
- Shanghai Key Laboratory of Artificial Intelligence in Learning and Cognitive Science, LAIX Inc, Shanghai 200090, China
| | - Jing Wang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201210, China
| | - Hui Lin
- Shanghai Key Laboratory of Artificial Intelligence in Learning and Cognitive Science, LAIX Inc, Shanghai 200090, China
| | - Nicholas B Turk-Browne
- Department of Psychology, Yale University, 2 Hillhouse Avenue, New Haven, CT 06520, United States
| | - Qing Cai
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education), Affiliated Mental Health Center (ECNU), Institute of Brain and Education Innovation, School of Psychology and Cognitive Science, East China Normal University, Shanghai 200062, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201210, China
- NYU-ECNU Institute of Brain and Cognitive Science, New York University Shanghai, Shanghai 200126, China
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Jung J, Lambon Ralph MA. Distinct but cooperating brain networks supporting semantic cognition. Cereb Cortex 2023; 33:2021-2036. [PMID: 35595542 PMCID: PMC9977382 DOI: 10.1093/cercor/bhac190] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 04/25/2022] [Accepted: 04/07/2022] [Indexed: 02/02/2023] Open
Abstract
Semantic cognition is a complex multifaceted brain function involving multiple processes including sensory, semantic, and domain-general cognitive systems. However, it remains unclear how these systems cooperate with each other to achieve effective semantic cognition. Here, we used independent component analysis (ICA) to investigate the functional brain networks that support semantic cognition. We used a semantic judgment task and a pattern-matching control task, each with 2 levels of difficulty, to disentangle task-specific networks from domain-general networks. ICA revealed 2 task-specific networks (the left-lateralized semantic network [SN] and a bilateral, extended semantic network [ESN]) and domain-general networks including the frontoparietal network (FPN) and default mode network (DMN). SN was coupled with the ESN and FPN but decoupled from the DMN, whereas the ESN was synchronized with the FPN alone and did not show a decoupling with the DMN. The degree of decoupling between the SN and DMN was associated with semantic task performance, with the strongest decoupling for the poorest performing participants. Our findings suggest that human higher cognition is achieved by the multiple brain networks, serving distinct and shared cognitive functions depending on task demands, and that the neural dynamics between these networks may be crucial for efficient semantic cognition.
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Affiliation(s)
- JeYoung Jung
- School of Psychology, University of Nottingham, Nottingham NG7 2RD, United Kingdom
| | - Matthew A Lambon Ralph
- MRC Cognition and Brain Science Unit (CBU), University of Cambridge, Cambridge, CB2 7EF United Kingdom
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Chiou R, Cox CR, Lambon Ralph MA. Bipartite functional fractionation within the neural system for social cognition supports the psychological continuity of self versus other. Cereb Cortex 2023; 33:1277-1299. [PMID: 35394005 PMCID: PMC9930627 DOI: 10.1093/cercor/bhac135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 02/10/2022] [Accepted: 03/14/2022] [Indexed: 11/12/2022] Open
Abstract
Research of social neuroscience establishes that regions in the brain's default-mode network (DN) and semantic network (SN) are engaged by socio-cognitive tasks. Research of the human connectome shows that DN and SN regions are both situated at the transmodal end of a cortical gradient but differ in their loci along this gradient. Here we integrated these 2 bodies of research, used the psychological continuity of self versus other as a "test-case," and used functional magnetic resonance imaging to investigate whether these 2 networks would encode social concepts differently. We found a robust dissociation between the DN and SN-while both networks contained sufficient information for decoding broad-stroke distinction of social categories, the DN carried more generalizable information for cross-classifying across social distance and emotive valence than did the SN. We also found that the overarching distinction of self versus other was a principal divider of the representational space while social distance was an auxiliary factor (subdivision, nested within the principal dimension), and this representational landscape was more manifested in the DN than in the SN. Taken together, our findings demonstrate how insights from connectome research can benefit social neuroscience and have implications for clarifying the 2 networks' differential contributions to social cognition.
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Affiliation(s)
| | - Christopher R Cox
- Department of Psychology, Louisiana State University, LA 70803, Baton Rouge, United States
| | - Matthew A Lambon Ralph
- MRC Cognition & Brain Science Unit, University of Cambridge, Cambridge, CB2 7EF, United Kingdom
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Diveica V, Riedel MC, Salo T, Laird AR, Jackson RL, Binney RJ. Graded functional organisation in the left inferior frontal gyrus: evidence from task-free and task-based functional connectivity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.02.526818. [PMID: 36778322 PMCID: PMC9915604 DOI: 10.1101/2023.02.02.526818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The left inferior frontal gyrus (LIFG) has been ascribed key roles in numerous cognitive domains, including language, executive function and social cognition. However, its functional organisation, and how the specific areas implicated in these cognitive domains relate to each other, is unclear. Possibilities include that the LIFG underpins a domain-general function or, alternatively, that it is characterized by functional differentiation, which might occur in either a discrete or a graded pattern. The aim of the present study was to explore the topographical organisation of the LIFG using a bimodal data-driven approach. To this end, we extracted functional connectivity (FC) gradients from 1) the resting-state fMRI time-series of 150 participants (77 female), and 2) patterns of co-activation derived meta-analytically from task data across a diverse set of cognitive domains. We then sought to characterize the FC differences driving these gradients with seed-based resting-state FC and meta-analytic co-activation modelling analyses. Both analytic approaches converged on an FC profile that shifted in a graded fashion along two main organisational axes. An anterior-posterior gradient shifted from being preferentially associated with high-level control networks (anterior LIFG) to being more tightly coupled with perceptually-driven networks (posterior). A second dorsal-ventral axis was characterized by higher connectivity with domain-general control networks on one hand (dorsal LIFG), and with the semantic network, on the other (ventral). These results provide novel insights into a graded functional organisation of the LIFG underpinning both task-free and task-constrained mental states, and suggest that the LIFG is an interface between distinct large-scale functional networks.
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Affiliation(s)
- Veronica Diveica
- Cognitive Neuroscience Institute, Department of Psychology, School of Human and Behavioural Sciences, Bangor University, Wales, UK
| | - Michael C. Riedel
- Department of Physics, Florida International University, Miami, FL, USA
| | - Taylor Salo
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Angela R. Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Rebecca L. Jackson
- Department of Psychology & York Biomedical Research Institute, University of York, UK
| | - Richard J. Binney
- Cognitive Neuroscience Institute, Department of Psychology, School of Human and Behavioural Sciences, Bangor University, Wales, UK
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Posterior-prefrontal and medial orbitofrontal regions play crucial roles in happiness and sadness recognition. Neuroimage Clin 2022; 35:103072. [PMID: 35689975 PMCID: PMC9192961 DOI: 10.1016/j.nicl.2022.103072] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 05/31/2022] [Accepted: 05/31/2022] [Indexed: 11/23/2022]
Abstract
Brain areas underlying trade-off relations between emotions were identified. Damage to the PPF area reduces accuracy of happiness recognition. Damage to the PPF increases accuracy of sadness recognition. A similar tendency was observed in orbitofrontal regions for sadness recognition. Only a deficit in sadness, but not happiness, persisted in the chronic phase.
The core brain regions responsible for basic human emotions are not yet fully understood. We investigated the key areas responsible for emotion recognition of facial expressions of happiness and sadness using data obtained from patients who underwent local brain resection. A total of 44 patients with right cerebral hemispheric brain tumors and 33 healthy volunteers were enrolled and subjected to a facial expression recognition test. Voxel-based lesion-symptom mapping was performed to investigate the relationship between the accuracy of emotion recognition and the resected regions. Consequently, trade-off relationships were discovered: the posterior-prefrontal region was related to a low score of happiness recognition and a high score of sadness recognition (disorder-of-happiness group), whereas the medial orbitofrontal region was related to a low score of sadness recognition and a high score of happiness recognition (disorder-of-sadness group). The emotion recognition score in both the happiness and sadness disorder groups was significantly lower than that in the control group (p = 0.0009 and p = 0.021, respectively). Interestingly, the deficit in happiness recognition was temporary, whereas the deficit in sadness recognition persisted during the chronic phase. Using graph theoretical analysis, we identified structural connectivity between the posterior-prefrontal and medial orbitofrontal regions. When either of these regions was damaged, the tract volume connecting them was significantly reduced (p = 0.013). These results indicate that the posterior-prefrontal and medial orbitofrontal regions may be crucial for maintaining a balance between happiness and sadness recognition in humans. Investigating the clinical impact of certain area resections using lesion studies combined with connectivity analysis is a useful neuroimaging method for understanding neural networks.
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Subregions of DLPFC Display Graded yet Distinct Structural and Functional Connectivity. J Neurosci 2022; 42:3241-3252. [PMID: 35232759 PMCID: PMC8994544 DOI: 10.1523/jneurosci.1216-21.2022] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 11/10/2021] [Accepted: 01/02/2022] [Indexed: 02/02/2023] Open
Abstract
The human dorsolateral prefrontal cortex (DLPFC; approximately corresponding to Brodmann areas 9 and 46) has demonstrable roles in diverse executive functions such as working memory, cognitive flexibility, planning, inhibition, and abstract reasoning. However, it remains unclear whether this is the result of one functionally homogeneous region or whether there are functional subdivisions within the DLPFC. Here, we divided the DLPFC into seven areas along rostral-caudal and dorsal-ventral axes anatomically and explored their respective patterns of structural and functional connectivity. In vivo probabilistic tractography (11 females and 13 males) and resting-state functional magnetic resonance imaging (fMRI; 57 females and 21 males) were employed to map out the patterns of connectivity from each DLPFC subregion. Structural connectivity demonstrated graded intraregional connectivity within the DLPFC. The patterns of structural connectivity between the DLPFC subregions and other cortical areas revealed that the dorsal-rostral subregions connections were restricted to other frontal and limbic areas, whereas the ventral-caudal region was widely connected to frontal, parietal, and limbic cortex. Functional connectivity analyses demonstrated that subregions of DLPFC were strongly interconnected to each other. The dorsal subregions were associated with the default mode network (DMN), while middle dorsal-rostral subregions were linked with the multiple demand network (MDN). The ventral-caudal subregion showed increased functional coupling with both DMN and MDN. Our results suggest that the connectivity of the DLPFC may be subdivided along a dorsorostral-ventrocaudal axis with differing (albeit graded) patterns of connectivity reflecting the integrative executive function of the DLPFC.SIGNIFICANCE STATEMENT Research has shown that the dorsolateral prefrontal cortex (DLPFC) plays a role in various executive functions. By dividing the DLPFC into seven areas along rostral-caudal and dorsal-ventral axes anatomically, we explored their patterns of structural and functional connectivity. The patterns of connectivity within DLPFC subregions demonstrated graded intraregional connectivity. There were distinctive patterns of connectivity with other cortical areas in dorsal-rostral and ventral-caudal DLPFC subregions. Divisions across DLPFC subregions seem to align with their structural and functional connectivity. Our results suggest that DLPFC may be subdivided by the diagonal axis of the dorsal-ventral axis and rostral-caudal axis, supporting the framework of a functional organization along the anterior-posterior axis in the lateral PFC.
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Possible limitations of perceptual studies for informing production networks - the case of laughter. Cortex 2022; 148:218-221. [DOI: 10.1016/j.cortex.2022.01.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Revised: 01/18/2022] [Accepted: 01/18/2022] [Indexed: 11/20/2022]
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Gonzalez Alam TRDJ, Mckeown BLA, Gao Z, Bernhardt B, Vos de Wael R, Margulies DS, Smallwood J, Jefferies E. A tale of two gradients: differences between the left and right hemispheres predict semantic cognition. Brain Struct Funct 2021; 227:631-654. [PMID: 34510282 PMCID: PMC8844158 DOI: 10.1007/s00429-021-02374-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Accepted: 08/27/2021] [Indexed: 01/21/2023]
Abstract
Decomposition of whole-brain functional connectivity patterns reveals a principal gradient that captures the separation of sensorimotor cortex from heteromodal regions in the default mode network (DMN). Functional homotopy is strongest in sensorimotor areas, and weakest in heteromodal cortices, suggesting there may be differences between the left and right hemispheres (LH/RH) in the principal gradient, especially towards its apex. This study characterised hemispheric differences in the position of large-scale cortical networks along the principal gradient, and their functional significance. We collected resting-state fMRI and semantic, working memory and non-verbal reasoning performance in 175 + healthy volunteers. We then extracted the principal gradient of connectivity for each participant, tested which networks showed significant hemispheric differences on the gradient, and regressed participants’ behavioural efficiency in tasks outside the scanner against interhemispheric gradient differences for each network. LH showed a higher overall principal gradient value, consistent with its role in heteromodal semantic cognition. One frontotemporal control subnetwork was linked to individual differences in semantic cognition: when it was nearer heteromodal DMN on the principal gradient in LH, participants showed more efficient semantic retrieval—and this network also showed a strong hemispheric difference in response to semantic demands but not working memory load in a separate study. In contrast, when a dorsal attention subnetwork was closer to the heteromodal end of the principal gradient in RH, participants showed better visual reasoning. Lateralization of function may reflect differences in connectivity between control and heteromodal regions in LH, and attention and visual regions in RH.
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Affiliation(s)
| | | | - Zhiyao Gao
- Department of Psychology, University of York, York, UK
| | - Boris Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Reinder Vos de Wael
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Daniel S Margulies
- Centre National de la Recherche Scientifique (CNRS) and Université de Paris, INCC UMR 8002, Paris, France
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Jiang N, Xu J, Li X, Wang Y, Zhuang L, Qin S. Negative Parenting Affects Adolescent Internalizing Symptoms Through Alterations in Amygdala-Prefrontal Circuitry: A Longitudinal Twin Study. Biol Psychiatry 2021; 89:560-569. [PMID: 33097228 DOI: 10.1016/j.biopsych.2020.08.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 08/03/2020] [Accepted: 08/03/2020] [Indexed: 12/29/2022]
Abstract
BACKGROUND The synergic interaction of risk genes and environmental factors has been thought to play a critical role in mediating emotion-related brain circuitry function and dysfunction in depression and anxiety disorders. Little, however, is known regarding neurodevelopmental bases underlying how maternal negative parenting affects emotion-related brain circuitry linking to adolescent internalizing symptoms and whether this neurobehavioral association is heritable during adolescence. METHODS The effects of maternal parenting on amygdala-based emotional circuitry and internalizing symptoms were examined by using longitudinal functional magnetic resonance imaging among 100 monozygotic twins and 78 dizygotic twins from early adolescence (age 13 years) to mid-adolescence (age 16 years). The mediation effects among variables of interest and their heritability were assessed by structural equation modeling and quantitative genetic analysis, respectively. RESULTS Exposure to maternal negative parenting was positively predictive of stronger functional connectivity of the amygdala with the ventrolateral prefrontal cortex. This neural pathway mediated the association between negative parenting and adolescent depressive symptoms and exhibited moderate heritability (21%). CONCLUSIONS These findings highlight that maternal negative parenting in early adolescence is associated with the development of atypical amygdala-prefrontal connectivity in relation to internalizing depressive symptoms in mid-adolescence. Such abnormality of emotion-related brain circuitry is heritable to a moderate degree.
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Affiliation(s)
- Nengzhi Jiang
- Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; School of Psychology, Weifang Medical University, Weifang, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Jiahua Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Xinying Li
- Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing, China; Department of Psychology, University of Chinese Academy of Sciences, Beijing, China.
| | - Yanyu Wang
- School of Psychology, Weifang Medical University, Weifang, China
| | - Liping Zhuang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; Chinese Institute for Brain Research, Beijing, China.
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Wang X, Margulies DS, Smallwood J, Jefferies E. A gradient from long-term memory to novel cognition: Transitions through default mode and executive cortex. Neuroimage 2020; 220:117074. [PMID: 32574804 PMCID: PMC7573535 DOI: 10.1016/j.neuroimage.2020.117074] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 05/21/2020] [Accepted: 06/17/2020] [Indexed: 12/15/2022] Open
Abstract
Human cognition flexibly guides decision-making in familiar and novel situations. Although these decisions are often treated as dichotomous, in reality, situations are neither completely familiar, nor entirely new. Contemporary accounts of brain organization suggest that neural function is organized along a connectivity gradient from unimodal regions of sensorimotor cortex, through executive regions to transmodal default mode network. We examined whether this graded view of neural organization helps to explain how decision-making changes across situations that vary in their alignment with long-term knowledge. We used a semantic judgment task, which parametrically varied the global semantic similarity of items within a feature matching task to create a 'task gradient', from conceptual combinations that were highly overlapping in long-term memory to trials that only shared the goal-relevant feature. We found the brain's response to the task gradient varied systematically along the connectivity gradient, with the strongest response in default mode network when the probe and target items were highly overlapping conceptually. This graded functional change was seen in multiple brain regions and within individual brains, and was not readily explained by task difficulty. Moreover, the gradient captured the spatial layout of networks involved in semantic processing, providing an organizational principle for controlled semantic cognition across the cortex. In this way, the cortex is organized to support semantic decision-making in both highly familiar and less familiar situations.
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Affiliation(s)
- Xiuyi Wang
- Department of Psychology, University of York, Heslington, York, YO10 5DD, United Kingdom.
| | - Daniel S Margulies
- Centre National de la Recherche Scientifique (CNRS) UMR 7225, Frontlab, Institut du Cerveau et de la Moelle Épinière, Paris, France
| | - Jonathan Smallwood
- Department of Psychology, University of York, Heslington, York, YO10 5DD, United Kingdom
| | - Elizabeth Jefferies
- Department of Psychology, University of York, Heslington, York, YO10 5DD, United Kingdom.
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Moss RA. Psychotherapy in pain management: New viewpoints and treatment targets based on a brain theory. AIMS Neurosci 2020; 7:194-207. [PMID: 32995484 PMCID: PMC7519970 DOI: 10.3934/neuroscience.2020013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 06/30/2020] [Indexed: 11/24/2022] Open
Abstract
The current paper provides an explanation of neurophysiological pain processing based the Dimensional Systems Model (DSM), a theory of higher cortical functions in which the cortical column is considered the binary digit for all cortical functions. Within the discussion, novel views on the roles of the basal ganglia, cerebellum, and cingulate cortex are presented. Additionally, an applied Clinical Biopsychological Model (CBM) based on the DSM will be discussed as related to psychological treatment with chronic pain patients. Three specific areas that have not been adequately addressed in the psychological treatment of chronic pain patients will be discussed based on the CBM. The treatment approaches have been effectively used in a clinical setting. Conclusions focus on a call for researchers and clinicians to fully evaluate the value of both the DSM and CBM.
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Affiliation(s)
- Robert A. Moss
- North Mississippi Regional Pain Consultants, 4381 Eason Blvd., Tupelo, MS 38801 USA
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Bajada CJ, Costa Campos LQ, Caspers S, Muscat R, Parker GJM, Lambon Ralph MA, Cloutman LL, Trujillo-Barreto NJ. A tutorial and tool for exploring feature similarity gradients with MRI data. Neuroimage 2020; 221:117140. [PMID: 32650053 PMCID: PMC7116330 DOI: 10.1016/j.neuroimage.2020.117140] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 06/09/2020] [Accepted: 07/02/2020] [Indexed: 11/15/2022] Open
Abstract
There has been an increasing interest in examining organisational principles of the cerebral cortex (and subcortical regions) using different MRI features such as structural or functional connectivity. Despite the widespread interest, introductory tutorials on the underlying technique targeted for the novice neuroimager are sparse in the literature. Articles that investigate various "neural gradients" (for example based on region studied "cortical gradients," "cerebellar gradients," "hippocampal gradients" etc … or feature of interest "functional gradients," "cytoarchitectural gradients," "myeloarchitectural gradients" etc …) have increased in popularity. Thus, we believe that it is opportune to discuss what is generally meant by "gradient analysis". We introduce basics concepts in graph theory, such as graphs themselves, the degree matrix, and the adjacency matrix. We discuss how one can think about gradients of feature similarity (the similarity between timeseries in fMRI, or streamline in tractography) using graph theory and we extend this to explore such gradients across the whole MRI scale; from the voxel level to the whole brain level. We proceed to introduce a measure for quantifying the level of similarity in regions of interest. We propose the term "the Vogt-Bailey index" for such quantification to pay homage to our history as a brain mapping community. We run through the techniques on sample datasets including a brain MRI as an example of the application of the techniques on real data and we provide several appendices that expand upon details. To maximise intuition, the appendices contain a didactic example describing how one could use these techniques to solve a particularly pernicious problem that one may encounter at a wedding. Accompanying the article is a tool, available in both MATLAB and Python, that enables readers to perform the analysis described in this article on their own data. We refer readers to the graphical abstract as an overview of the analysis pipeline presented in this work.
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Affiliation(s)
- Claude J Bajada
- Department of Physiology and Biochemistry, Faculty of Medicine and Surgery, The University of Malta, Malta; Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK; Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany.
| | - Lucas Q Costa Campos
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany; Institute of Complex Systems and Institute for Advanced Simulation (ICS-2/IAS-2), Research Centre Jülich, 52425, Jülich, Germany
| | - Svenja Caspers
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany; Institute for Anatomy I, Medical Faculty, Heinrich-Heine-University Duesseldorf, 40221, Duesseldorf, Germany; JARA-BRAIN, Jülich-Aachen Research Alliance, 52425, Jülich, Germany
| | - Richard Muscat
- Department of Physiology and Biochemistry, Faculty of Medicine and Surgery, The University of Malta, Malta
| | - Geoff J M Parker
- Centre for Medical Image Computing, Department of Computer Science, and Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, UK; Bioxydyn Limited, Manchester, UK
| | | | - Lauren L Cloutman
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK
| | - Nelson J Trujillo-Barreto
- Division of Neuroscience & Experimental Psychology, School of Biological Sciences, The University of Manchester, UK
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16
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Chase HW, Grace AA, Fox PT, Phillips ML, Eickhoff SB. Functional differentiation in the human ventromedial frontal lobe: A data-driven parcellation. Hum Brain Mapp 2020; 41:3266-3283. [PMID: 32314470 PMCID: PMC7375078 DOI: 10.1002/hbm.25014] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 03/06/2020] [Accepted: 04/07/2020] [Indexed: 12/18/2022] Open
Abstract
Ventromedial regions of the frontal lobe (vmFL) are thought to play a key role in decision-making and emotional regulation. However, aspects of this area's functional organization, including the presence of a multiple subregions, their functional and anatomical connectivity, and the cross-species homologies of these subregions with those of other species, remain poorly understood. To address this uncertainty, we employed a two-stage parcellation of the region to identify six distinct structures within the region on the basis of data-driven classification of functional connectivity patterns obtained using the meta-analytic connectivity modeling (MACM) approach. From anterior to posterior, the derived subregions included two lateralized posterior regions, an intermediate posterior region, a dorsal and ventral central region, and a single anterior region. The regions were characterized further by functional connectivity derived using resting-state fMRI and functional decoding using the Brain Map database. In general, the regions could be differentiated on the basis of different patterns of functional connectivity with canonical "default mode network" regions and/or subcortical regions such as the striatum. Together, the findings suggest the presence of functionally distinct neural structures within vmFL, consistent with data from experimental animals as well prior demonstrations of anatomical differences within the region. Detailed correspondence with the anterior cingulate, medial orbitofrontal cortex, and rostroventral prefrontal cortex, as well as specific animal homologs are discussed. The findings may suggest future directions for resolving potential functional and structural correspondence of subregions within the frontal lobe across behavioral contexts, and across mammalian species.
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Affiliation(s)
- Henry W Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Anthony A Grace
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.,Department of Neuroscience and Psychology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center, San Antonio, Texas, USA.,Department of Radiology, University of Texas Health Science Center, San Antonio, Texas, USA.,Department of Psychiatry, University of Texas Health Science Center, San Antonio, Texas, USA.,Research and Development Service, South Texas Veterans Health Care System, San Antonio, Texas, USA
| | - Mary L Phillips
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
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17
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Irish M, Vatansever D. Rethinking the episodic-semantic distinction from a gradient perspective. Curr Opin Behav Sci 2020. [DOI: 10.1016/j.cobeha.2020.01.016] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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18
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Lissek S, Klass A, Tegenthoff M. Left Inferior Frontal Gyrus Participates in Mediating the Renewal Effect Irrespective of Context Salience. Front Behav Neurosci 2020; 14:43. [PMID: 32292332 PMCID: PMC7118360 DOI: 10.3389/fnbeh.2020.00043] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 03/13/2020] [Indexed: 11/13/2022] Open
Abstract
The renewal effect of extinction demonstrates the context-dependency of extinction learning. It is defined as the recovery of an extinguished response occurring when the contexts of extinction and recall differ. Behavioral studies showed that modulating context relevance can strengthen context-specific responses. In our fMRI study, we investigated to what extent a modulation of context salience can alter renewal levels and provide additional information about the neural basis for renewal. In a within-subjects design, participants completed two sessions of an associative learning task in randomized order. In the salient condition (SAL), a context was presented alone at the start of each trial, before being presented together with the stimulus. The regular condition (REG) contained no context-alone phase. In about one-third of participants (SWITCH), the context salience modulation significantly increased renewal rates in the SAL compared to the REG condition. The other participants showed either renewal (REN) or no renewal (NoREN) in both conditions. The modulation did not significantly affect learning performance during the initial forming of associations or extinction learning. In the SWITCH group, activation in left opercular inferior frontal gyrus (iFG) during the recall phase was associated with a renewal effect, together with activity in the bilateral posterior hippocampus and ventromedial prefrontal cortex (vmPFC). Also during the extinction phase, left opercular iFG activation was higher in groups exhibiting renewal in recall, irrespective of the context salience modulation. Besides confirming the participation of vmPFC in extinction recall, our findings provide novel insights regarding an as yet undetected, potentially important role for renewal-supporting processes in left iFG during extinction learning and recall, which are presumably based on the region's proposed function of evaluating competing response options under conditions of ambiguity.
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Affiliation(s)
- Silke Lissek
- Department of Neurology, BG University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
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