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von Seth J, Nicholls VI, Tyler LK, Clarke A. Recurrent connectivity supports higher-level visual and semantic object representations in the brain. Commun Biol 2023; 6:1207. [PMID: 38012301 PMCID: PMC10682037 DOI: 10.1038/s42003-023-05565-9] [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: 03/21/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023] Open
Abstract
Visual object recognition has been traditionally conceptualised as a predominantly feedforward process through the ventral visual pathway. While feedforward artificial neural networks (ANNs) can achieve human-level classification on some image-labelling tasks, it's unclear whether computational models of vision alone can accurately capture the evolving spatiotemporal neural dynamics. Here, we probe these dynamics using a combination of representational similarity and connectivity analyses of fMRI and MEG data recorded during the recognition of familiar, unambiguous objects. Modelling the visual and semantic properties of our stimuli using an artificial neural network as well as a semantic feature model, we find that unique aspects of the neural architecture and connectivity dynamics relate to visual and semantic object properties. Critically, we show that recurrent processing between the anterior and posterior ventral temporal cortex relates to higher-level visual properties prior to semantic object properties, in addition to semantic-related feedback from the frontal lobe to the ventral temporal lobe between 250 and 500 ms after stimulus onset. These results demonstrate the distinct contributions made by semantic object properties in explaining neural activity and connectivity, highlighting it as a core part of object recognition not fully accounted for by current biologically inspired neural networks.
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Affiliation(s)
- Jacqueline von Seth
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | | | - Lorraine K Tyler
- Department of Psychology, University of Cambridge, Cambridge, UK
- Cambridge Centre for Ageing and Neuroscience (Cam-CAN), University of Cambridge and MRC Cognition and Brain Sciences Unit, Cambridge, UK
| | - Alex Clarke
- Department of Psychology, University of Cambridge, Cambridge, UK.
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2
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Fargier R, Laganaro M. Referential and inferential production across the lifespan: different patterns and different predictive cognitive factors. Front Psychol 2023; 14:1237523. [PMID: 38022984 PMCID: PMC10643179 DOI: 10.3389/fpsyg.2023.1237523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 09/18/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction The ability to speak is grounded in general memory and control processes and likely changes across the lifespan. However, our knowledge on how word production abilities naturally evolve from childhood to old age remains marginally investigated. Our aim was to shed further light on this issue by exploiting the contrast between two ways to elicit word production: referential picture naming and inferential naming from definition. Methods We collected accuracy and production latencies in a picture naming task and in a naming from definition task from 130 participants ranging from 10 to 80 years old. Measures of vocabulary size, digit span memory, semantic and phonemic fluencies and processing speed were also collected. We used multivariate adaptative regression splines and regression models to characterize lifespan patterns of the two tasks. Results Patterns of increase in performance were similar for picture naming and naming from definition only from childhood to young adulthood. In the second half of the lifespan, significant decrease of performance was found in older adults for picture naming (from around 60 years-old) but not for naming from definition. Clearly, word production elicited with an inferential task (naming from definition) yields different age-related patterns than usually described in the literature with a referential task (picture naming). Discussion We discuss how cognitive processes such as visual-conceptual processes and lexical prediction may explain the differential pattern of results in aging in referential and inferential production tasks. We argue for more lifespan studies and the need to investigate language production beyond picture naming, in particular with respect to aging.
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Affiliation(s)
| | - Marina Laganaro
- Neuropsycholinguistics Laboratory, Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
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3
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Liu X, Tyler LK, Cam-Can, Davis SW, Rowe JB, Tsvetanov KA. Cognition's dependence on functional network integrity with age is conditional on structural network integrity. Neurobiol Aging 2023; 129:195-208. [PMID: 37392579 DOI: 10.1016/j.neurobiolaging.2023.06.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 05/29/2023] [Accepted: 06/02/2023] [Indexed: 07/03/2023]
Abstract
Maintaining good cognitive function is crucial for well-being across the lifespan. We proposed that the degree of cognitive maintenance is determined by the functional interactions within and between large-scale brain networks. Such connectivity can be represented by the white matter architecture of structural brain networks that shape intrinsic neuronal activity into integrated and distributed functional networks. We explored how the function-structure connectivity convergence, and the divergence of functional connectivity from structural connectivity, contribute to the maintenance of cognitive function across the adult lifespan. Multivariate analyses were used to investigate the relationship between function-structure connectivity convergence and divergence with multivariate cognitive profiles, respectively. Cognitive function was increasingly dependent on function-structure connectivity convergence as age increased. The dependency of cognitive function on connectivity was particularly strong for high-order cortical networks and subcortical networks. The results suggest that brain functional network integrity sustains cognitive functions in old age, as a function of the integrity of the brain's structural connectivity.
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Affiliation(s)
- Xulin Liu
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
| | - Lorraine K Tyler
- The Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK
| | - Cam-Can
- Cambridge Centre for Ageing and Neuroscience (Cam-CAN), MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Simon W Davis
- Department of Neurology, Duke University, School of Medicine, Durham, NC, USA
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Kamen A Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; The Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK
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4
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Ventalon G, Erjavec G, Tijus C. A review of processing and analysing visual metaphors in psychology. EUROPEAN REVIEW OF APPLIED PSYCHOLOGY 2023. [DOI: 10.1016/j.erap.2022.100836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/12/2023]
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5
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Bruffaerts R, Pongos A, Shain C, Lipkin B, Siegelman M, Wens V, Sjøgård M, Pantazis D, Blank I, Goldman S, De Tiège X, Fedorenko E. Functional identification of language-responsive channels in individual participants in MEG investigations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.23.533424. [PMID: 36993378 PMCID: PMC10055362 DOI: 10.1101/2023.03.23.533424] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Making meaningful inferences about the functional architecture of the language system requires the ability to refer to the same neural units across individuals and studies. Traditional brain imaging approaches align and average brains together in a common space. However, lateral frontal and temporal cortex, where the language system resides, is characterized by high structural and functional inter-individual variability. This variability reduces the sensitivity and functional resolution of group-averaging analyses. This problem is compounded by the fact that language areas often lay in close proximity to regions of other large-scale networks with different functional profiles. A solution inspired by other fields of cognitive neuroscience (e.g., vision) is to identify language areas functionally in each individual brain using a 'localizer' task (e.g., a language comprehension task). This approach has proven productive in fMRI, yielding a number of discoveries about the language system, and has been successfully extended to intracranial recording investigations. Here, we apply this approach to MEG. Across two experiments (one in Dutch speakers, n=19; one in English speakers, n=23), we examined neural responses to the processing of sentences and a control condition (nonword sequences). We demonstrated that the neural response to language is spatially consistent at the individual level. The language-responsive sensors of interest were, as expected, less responsive to the nonwords condition. Clear inter-individual differences were present in the topography of the neural response to language, leading to greater sensitivity when the data were analyzed at the individual level compared to the group level. Thus, as in fMRI, functional localization yields benefits in MEG and thus opens the door to probing fine-grained distinctions in space and time in future MEG investigations of language processing.
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Affiliation(s)
- Rose Bruffaerts
- Computational Neurology, Experimental Neurobiology Unit (ENU), Department of Biomedical Sciences, University of Antwerp, Belgium; Department of Neurosciences, KU Leuven, Belgium
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Alvince Pongos
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Bioengineering, UC Berkeley-UCSF, San Francisco, CA, USA
| | - Cory Shain
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Benjamin Lipkin
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Matthew Siegelman
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Psychology, Columbia University, New York, NY, USA
| | - Vincent Wens
- Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles, Brussels, Belgium
| | - Martin Sjøgård
- Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles, Brussels, Belgium
| | - Dimitrios Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Idan Blank
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Psychology, University of California Los Angeles, CA, USA
| | - Serge Goldman
- Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles, Brussels, Belgium
| | - Xavier De Tiège
- Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles, Brussels, Belgium
| | - Evelina Fedorenko
- Brain and Cognitive Sciences Department, Massachusetts Institute of Technology, Cambridge, MA, USA
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
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6
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Semantic cognition in healthy ageing: Neural signatures of representation and control mechanisms in naming typical and atypical objects. Neuropsychologia 2023; 184:108545. [PMID: 36934809 DOI: 10.1016/j.neuropsychologia.2023.108545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 11/19/2022] [Accepted: 03/16/2023] [Indexed: 03/19/2023]
Abstract
Effective use of conceptual knowledge engages semantic representation and control processes to access information in a goal-driven manner. Neuropsychological findings of patients presenting either degraded knowledge (e.g., semantic dementia) or disrupted control (e.g., semantic aphasia) converge with neuroimaging evidence from young adults, and delineate the neural segregation of representation and control mechanisms. However, there is still scarce research on the neurofunctional underpinnings of such mechanisms in healthy ageing. To address this, we conducted an fMRI study, wherein young and older adults performed a covert naming task of typical and atypical objects. Three main age-related differences were found. As shown by age group and typicality interactions, older adults exhibited overactivation during naming of atypical (e.g., avocado) relative to typical concepts in brain regions associated to semantic representation, including anterior and medial portions of left temporal lobe (respectively, ATL and MTG). This provides evidence for the reorganization of neural activity in these brain regions contingent to the enrichment of semantic repositories in older ages. The medial orbitofrontal gyrus was also overactivated, indicating that the processing of atypical concepts (relative to typical items) taxes additional control resources in the elderly. Increased activation in the inferior frontal gyrus (IFG) was observed in naming typical items (relative to atypical ones), but only for young adults. This suggests that naming typical items (e.g., strawberry) taxes more on control processes in younger ages, presumably due to the semantic competition set by other items that share multiple features with the target (e.g., raspberry, blackberry, cherry). Together, these results reveal the dynamic nature of semantic control interplaying with conceptual representations as people grow older, by indicating that distinct neural bases uphold semantic performance from young to older ages. These findings may be explained by neural compensation mechanisms coming into play to support neurocognitive changes in healthy ageing.
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7
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Abstract
Explicit (declarative) memory declines with age, but age effects on implicit (nondeclarative) memory are debated. Some studies have reported null changes in implicit memory (e.g., priming in word-fragment completion, perceptual identification, category exemplar generation) with age, while others have uncovered declines. One factor that may account for these discrepancies is processing. Evidence suggests that conceptual and perceptual processes are not equally affected by ageing, yet processing requirements have varied greatly between studies. Processing may moderate age effects on priming, but no study has systematically examined this issue. This registered report presents an experiment to manipulate processing (conceptual / perceptual) during incidental encoding of words, prior to measures of perceptual (perceptual identification) and conceptual (category verification) priming. The perceptual and conceptual priming tasks were matched on all characteristics except processing, making them highly comparable. The four orthogonal conditions (perceptual encoding, perceptual test [PP]; conceptual encoding, perceptual test [CP]; perceptual encoding, conceptual test [PC]; conceptual encoding, conceptual test [CC]) were designed to clarify situations in which age effects on implicit memory emerge, which holds important practical and theoretical implications. Significant effects of Age, Test, and an Age × Processing interaction emerged. Priming was greater in young than older adults and on the perceptual than the conceptual test, but in contrast to the predictions, the age difference was only significant when prior encoding was perceptual (i.e., in the PP and CP conditions).
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Affiliation(s)
- Emma V Ward
- Emma V Ward, Faculty of Science and Technology, Psychology Department, Middlesex University, The Burroughs, London NW4 4BT, UK.
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8
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Guardia T, Geerligs L, Tsvetanov KA, Ye R, Campbell KL. The role of the arousal system in age-related differences in cortical functional network architecture. Hum Brain Mapp 2022; 43:985-997. [PMID: 34713955 PMCID: PMC8764482 DOI: 10.1002/hbm.25701] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Revised: 10/04/2021] [Accepted: 10/17/2021] [Indexed: 01/10/2023] Open
Abstract
A common finding in the aging literature is that of the brain's decreased within- and increased between-network functional connectivity. However, it remains unclear what is causing this shift in network organization with age. Given the essential role of the ascending arousal system (ARAS) in cortical activation and previous findings of disrupted ARAS functioning with age, it is possible that age differences in ARAS functioning contribute to disrupted cortical connectivity. We test this possibility here using resting state fMRI data from over 500 individuals across the lifespan from the Cambridge Center for Aging and Neuroscience (Cam-CAN) population-based cohort. Our results show that ARAS-cortical connectivity declines with age and, consistent with our expectations, significantly mediates some age-related differences in connectivity within and between association networks (specifically, within the default mode and between the default mode and salience networks). Additionally, connectivity between the ARAS and association networks predicted cognitive performance across several tasks over and above the effects of age and connectivity within the cortical networks themselves. These findings suggest that age differences in cortical connectivity may be driven, at least in part, by altered arousal signals from the brainstem and that ARAS-cortical connectivity relates to cognitive performance with age.
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Affiliation(s)
- Tiago Guardia
- Department of PsychologyBrock UniversitySt. CatharinesOntarioCanada
| | - Linda Geerligs
- Donders Institute for Brain, Cognition, and BehaviourRadboud UniversityNijmegenThe Netherlands
| | | | - Rong Ye
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
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9
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Domain-General Cognitive Skills in Children with Mathematical Difficulties and Dyscalculia: A Systematic Review of the Literature. Brain Sci 2022; 12:brainsci12020239. [PMID: 35204002 PMCID: PMC8870543 DOI: 10.3390/brainsci12020239] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 01/29/2022] [Accepted: 02/03/2022] [Indexed: 12/10/2022] Open
Abstract
Mathematical performance implies a series of numerical and mathematical skills (both innate and derived from formal training) as well as certain general cognitive abilities that, if inadequate, can have a cascading effect on mathematics learning. These latter skills were the focus of the present systematic review. Method: The reviewing process was conducted according to the PRISMA statement. We included 46 studies comparing school-aged children’s performance with and without math difficulties in the following cognitive domains: processing speed, phonological awareness, short- and long-term memory, executive functions, and attention. Results: The results showed that some general cognitive domains were compromised in children with mathematical difficulties (i.e., executive functions, attention, and processing speed). Conclusions: These cognitive functions should be evaluated during the diagnostic process in order to better understand the child’s profile and propose individually tailored interventions. However, further studies should investigate the role of skills that have been poorly investigated to date (e.g., long-term memory and phonological awareness).
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10
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Borghesani V, Dale CL, Lukic S, Hinkley LBN, Lauricella M, Shwe W, Mizuiri D, Honma S, Miller Z, Miller B, Houde JF, Gorno-Tempini ML, Nagarajan SS. Neural dynamics of semantic categorization in semantic variant of primary progressive aphasia. eLife 2021; 10:e63905. [PMID: 34155973 PMCID: PMC8241439 DOI: 10.7554/elife.63905] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 06/21/2021] [Indexed: 12/28/2022] Open
Abstract
Semantic representations are processed along a posterior-to-anterior gradient reflecting a shift from perceptual (e.g., it has eight legs) to conceptual (e.g., venomous spiders are rare) information. One critical region is the anterior temporal lobe (ATL): patients with semantic variant primary progressive aphasia (svPPA), a clinical syndrome associated with ATL neurodegeneration, manifest a deep loss of semantic knowledge. We test the hypothesis that svPPA patients perform semantic tasks by over-recruiting areas implicated in perceptual processing. We compared MEG recordings of svPPA patients and healthy controls during a categorization task. While behavioral performance did not differ, svPPA patients showed indications of greater activation over bilateral occipital cortices and superior temporal gyrus, and inconsistent engagement of frontal regions. These findings suggest a pervasive reorganization of brain networks in response to ATL neurodegeneration: the loss of this critical hub leads to a dysregulated (semantic) control system, and defective semantic representations are seemingly compensated via enhanced perceptual processing.
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Affiliation(s)
- V Borghesani
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - CL Dale
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - S Lukic
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - LBN Hinkley
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - M Lauricella
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - W Shwe
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - D Mizuiri
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - S Honma
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - Z Miller
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - B Miller
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
| | - JF Houde
- Department of Otolaryngology, University of California, San FranciscoSan FranciscoUnited States
| | - ML Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California, San FranciscoSan FranciscoUnited States
- Department of Neurology, Dyslexia Center University of California, San FranciscoSan FranciscoUnited States
| | - SS Nagarajan
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
- Department of Otolaryngology, University of California, San FranciscoSan FranciscoUnited States
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11
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Tsvetanov KA, Henson RNA, Rowe JB. Separating vascular and neuronal effects of age on fMRI BOLD signals. Philos Trans R Soc Lond B Biol Sci 2021; 376:20190631. [PMID: 33190597 PMCID: PMC7741031 DOI: 10.1098/rstb.2019.0631] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/19/2020] [Indexed: 12/14/2022] Open
Abstract
Accurate identification of brain function is necessary to understand the neurobiology of cognitive ageing, and thereby promote well-being across the lifespan. A common tool used to investigate neurocognitive ageing is functional magnetic resonance imaging (fMRI). However, although fMRI data are often interpreted in terms of neuronal activity, the blood oxygenation level-dependent (BOLD) signal measured by fMRI includes contributions of both vascular and neuronal factors, which change differentially with age. While some studies investigate vascular ageing factors, the results of these studies are not well known within the field of neurocognitive ageing and therefore vascular confounds in neurocognitive fMRI studies are common. Despite over 10 000 BOLD-fMRI papers on ageing, fewer than 20 have applied techniques to correct for vascular effects. However, neurovascular ageing is not only a confound in fMRI, but an important feature in its own right, to be assessed alongside measures of neuronal ageing. We review current approaches to dissociate neuronal and vascular components of BOLD-fMRI of regional activity and functional connectivity. We highlight emerging evidence that vascular mechanisms in the brain do not simply control blood flow to support the metabolic needs of neurons, but form complex neurovascular interactions that influence neuronal function in health and disease. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.
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Affiliation(s)
- Kamen A. Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
- Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK
| | - Richard N. A. Henson
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SP, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - James B. Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
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12
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Bethlehem RAI, Paquola C, Seidlitz J, Ronan L, Bernhardt B, Consortium CC, Tsvetanov KA. Dispersion of functional gradients across the adult lifespan. Neuroimage 2020; 222:117299. [PMID: 32828920 PMCID: PMC7779368 DOI: 10.1016/j.neuroimage.2020.117299] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Revised: 07/25/2020] [Accepted: 08/17/2020] [Indexed: 12/28/2022] Open
Abstract
Ageing is commonly associated with changes to segregation and integration of functional brain networks, but, in isolation, current network-based approaches struggle to elucidate changes across the many axes of functional organisation. However, the advent of gradient mapping techniques in neuroimaging provides a new means of studying functional organisation in a multi-dimensional connectivity space. Here, we studied ageing and behaviourally-relevant differences in a three-dimensional connectivity space using the Cambridge Centre for Ageing Neuroscience cohort (n = 643). Building on gradient mapping techniques, we developed a set of measures to quantify the dispersion within and between functional communities. We detected a strong shift of the visual network across the adult lifespan from an extreme to a more central position in the 3D gradient space. In contrast, the dispersion distance between transmodal communities (dorsal attention, ventral attention, frontoparietal and default mode) did not change. However, these communities themselves were increasingly dispersed with increasing age, reflecting more dissimilar functional connectivity profiles within each community. Increasing dispersion of frontoparietal, attention and default mode networks, in particular, were associated negatively with cognition, measured by fluid intelligence. By using a technique that explicitly captures the ordering of functional systems in a multi-dimensional hierarchical framework, we identified behaviorally-relevant age-related differences of within and between network organisation. We propose that the study of functional gradients across the adult lifespan could provide insights that may facilitate the development of new strategies to maintain cognitive ability across the lifespan in health and disease.
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Affiliation(s)
- Richard A I Bethlehem
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK; Autism Research Centre, Department of Psychiatry, University of Cambridge, England, United Kingdom.
| | - Casey Paquola
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia PA, USA; Department of Psychiatry, University of Pennsylvania, Philadelphia PA, USA
| | - Lisa Ronan
- Department of Psychiatry, University of Cambridge, United Kingdom
| | - Boris Bernhardt
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Cam-Can Consortium
- Medical Research Council Cognition and Brain Sciences Unit, Cambridge CB2 7EF, UK
| | - Kamen A Tsvetanov
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge CB2 3EB, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0QQ, UK
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13
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Zheng S, Meng Y, Lin G. The attentional boost effect with semantic information detection tasks. Q J Exp Psychol (Hove) 2020; 74:510-522. [PMID: 33063602 DOI: 10.1177/1747021820969037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The attentional boost effect (ABE) is a phenomenon in which in some dual tasks, increased attention to target detection causes an increase in memory performance related to items paired with the target. However, in previous studies concerning the ABE, the detection task objects usually reflected perceptual information. Whether the ABE could be observed if the task involves detecting semantic information is unclear. To answer this question, the present study adopted the classic dual-task paradigm of the ABE. Arabic numerals were used as semantic information stimuli in the detection tasks, and the degree of semantic processing in the detection task gradually increased over three experiments. The results showed that target detection with semantic information (i.e., digits) triggered the ABE (Experiment 1) and that the ABE was also generated under the semantic judgement-based detection task (i.e., odd-even detection task) regardless of whether the detection task used a single-target stimulus (Experiment 2) or a multi-target stimulus (Experiment 3). These findings indicate that an increased semantic load before the target decision in the detection task does not affect the ABE, and both perceptual detection and semantic detection can trigger the ABE.
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Affiliation(s)
- Siqi Zheng
- School of Psychology, Fujian Normal University, Fuzhou, P.R. China
| | - Yingfang Meng
- School of Psychology, Fujian Normal University, Fuzhou, P.R. China
| | - Guyang Lin
- School of Psychology, Fujian Normal University, Fuzhou, P.R. China
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14
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Ventalon G, Erjavec G, Tijus C. Processing visual metaphors in advertising: an exploratory study of cognitive abilities. JOURNAL OF COGNITIVE PSYCHOLOGY 2020. [DOI: 10.1080/20445911.2020.1817038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Affiliation(s)
- Geoffrey Ventalon
- Laboratoire “Cognition Humaine et Artificielle” CHArt, Université Paris 8, Saint-Denis, France
| | - Grozdana Erjavec
- Laboratoire “Cognition Humaine et Artificielle” CHArt, Université Paris 8, Saint-Denis, France
| | - Charles Tijus
- Laboratoire “Cognition Humaine et Artificielle” CHArt, Université Paris 8, Saint-Denis, France
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15
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Wardle SG, Baker C. Recent advances in understanding object recognition in the human brain: deep neural networks, temporal dynamics, and context. F1000Res 2020; 9. [PMID: 32566136 PMCID: PMC7291077 DOI: 10.12688/f1000research.22296.1] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/08/2020] [Indexed: 12/17/2022] Open
Abstract
Object recognition is the ability to identify an object or category based on the combination of visual features observed. It is a remarkable feat of the human brain, given that the patterns of light received by the eye associated with the properties of a given object vary widely with simple changes in viewing angle, ambient lighting, and distance. Furthermore, different exemplars of a specific object category can vary widely in visual appearance, such that successful categorization requires generalization across disparate visual features. In this review, we discuss recent advances in understanding the neural representations underlying object recognition in the human brain. We highlight three current trends in the approach towards this goal within the field of cognitive neuroscience. Firstly, we consider the influence of deep neural networks both as potential models of object vision and in how their representations relate to those in the human brain. Secondly, we review the contribution that time-series neuroimaging methods have made towards understanding the temporal dynamics of object representations beyond their spatial organization within different brain regions. Finally, we argue that an increasing emphasis on the context (both visual and task) within which object recognition occurs has led to a broader conceptualization of what constitutes an object representation for the brain. We conclude by identifying some current challenges facing the experimental pursuit of understanding object recognition and outline some emerging directions that are likely to yield new insight into this complex cognitive process.
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Affiliation(s)
- Susan G Wardle
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Chris Baker
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, 20892, USA
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Bruffaerts R, Schaeverbeke J, De Weer AS, Nelissen N, Dries E, Van Bouwel K, Sieben A, Bergmans B, Swinnen C, Pijnenburg Y, Sunaert S, Vandenbulcke M, Vandenberghe R. Multivariate analysis reveals anatomical correlates of naming errors in primary progressive aphasia. Neurobiol Aging 2019; 88:71-82. [PMID: 31955981 DOI: 10.1016/j.neurobiolaging.2019.12.016] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 12/10/2019] [Accepted: 12/15/2019] [Indexed: 12/30/2022]
Abstract
Primary progressive aphasia (PPA) is an overarching term for a heterogeneous group of neurodegenerative diseases which affect language processing. Impaired picture naming has been linked to atrophy of the anterior temporal lobe in the semantic variant of PPA. Although atrophy of the anterior temporal lobe proposedly impairs picture naming by undermining access to semantic knowledge, picture naming also entails object recognition and lexical retrieval. Using multivariate analysis, we investigated whether cortical atrophy relates to different types of naming errors generated during picture naming in 43 PPA patients (13 semantic, 9 logopenic, 11 nonfluent, and 10 mixed variant). Omissions were associated with atrophy of the anterior temporal lobes. Semantic errors, for example, mistaking a rhinoceros for a hippopotamus, were associated with atrophy of the left mid and posterior fusiform cortex and the posterior middle and inferior temporal gyrus. Semantic errors and atrophy in these regions occurred in each PPA subtype, without major between-subtype differences. We propose that pathological changes to neural mechanisms associated with semantic errors occur across the PPA spectrum.
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Affiliation(s)
- Rose Bruffaerts
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium; Neurology Department, University Hospitals Leuven, Leuven, Belgium.
| | - Jolien Schaeverbeke
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - An-Sofie De Weer
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Natalie Nelissen
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Eva Dries
- Neurology Department, University Hospitals Leuven, Leuven, Belgium
| | - Karen Van Bouwel
- Neurology Department, University Hospitals Leuven, Leuven, Belgium
| | - Anne Sieben
- Neurology Department, University Hospital Ghent, Ghent, Belgium
| | - Bruno Bergmans
- Neurology Department, University Hospital Ghent, Ghent, Belgium; Neurology Department, AZ Sint-Jan Brugge-Oostende AV, Bruges, Belgium
| | | | - Yolande Pijnenburg
- Neurology Department, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Stefan Sunaert
- Radiology Department, University Hospitals Leuven, Leuven, Belgium
| | | | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium; Neurology Department, University Hospitals Leuven, Leuven, Belgium
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