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Bernáez Timón L, Ekelmans P, Kraynyukova N, Rose T, Busse L, Tchumatchenko T. How to incorporate biological insights into network models and why it matters. J Physiol 2023; 601:3037-3053. [PMID: 36069408 DOI: 10.1113/jp282755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/24/2022] [Indexed: 11/08/2022] Open
Abstract
Due to the staggering complexity of the brain and its neural circuitry, neuroscientists rely on the analysis of mathematical models to elucidate its function. From Hodgkin and Huxley's detailed description of the action potential in 1952 to today, new theories and increasing computational power have opened up novel avenues to study how neural circuits implement the computations that underlie behaviour. Computational neuroscientists have developed many models of neural circuits that differ in complexity, biological realism or emergent network properties. With recent advances in experimental techniques for detailed anatomical reconstructions or large-scale activity recordings, rich biological data have become more available. The challenge when building network models is to reflect experimental results, either through a high level of detail or by finding an appropriate level of abstraction. Meanwhile, machine learning has facilitated the development of artificial neural networks, which are trained to perform specific tasks. While they have proven successful at achieving task-oriented behaviour, they are often abstract constructs that differ in many features from the physiology of brain circuits. Thus, it is unclear whether the mechanisms underlying computation in biological circuits can be investigated by analysing artificial networks that accomplish the same function but differ in their mechanisms. Here, we argue that building biologically realistic network models is crucial to establishing causal relationships between neurons, synapses, circuits and behaviour. More specifically, we advocate for network models that consider the connectivity structure and the recorded activity dynamics while evaluating task performance.
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Affiliation(s)
- Laura Bernáez Timón
- Institute for Physiological Chemistry, University of Mainz Medical Center, Mainz, Germany
| | - Pierre Ekelmans
- Frankfurt Institute for Advanced Studies, Frankfurt, Germany
| | - Nataliya Kraynyukova
- Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, Bonn, Germany
| | - Tobias Rose
- Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, Bonn, Germany
| | - Laura Busse
- Division of Neurobiology, Faculty of Biology, LMU Munich, Munich, Germany
- Bernstein Center for Computational Neuroscience, Munich, Germany
| | - Tatjana Tchumatchenko
- Institute for Physiological Chemistry, University of Mainz Medical Center, Mainz, Germany
- Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, Bonn, Germany
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Jang H, Tong F. Improved modeling of human vision by incorporating robustness to blur in convolutional neural networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.29.551089. [PMID: 37577646 PMCID: PMC10418076 DOI: 10.1101/2023.07.29.551089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Whenever a visual scene is cast onto the retina, much of it will appear degraded due to poor resolution in the periphery; moreover, optical defocus can cause blur in central vision. However, the pervasiveness of blurry or degraded input is typically overlooked in the training of convolutional neural networks (CNNs). We hypothesized that the absence of blurry training inputs may cause CNNs to rely excessively on high spatial frequency information for object recognition, thereby causing systematic deviations from biological vision. We evaluated this hypothesis by comparing standard CNNs with CNNs trained on a combination of clear and blurry images. We show that blur-trained CNNs outperform standard CNNs at predicting neural responses to objects across a variety of viewing conditions. Moreover, blur-trained CNNs acquire increased sensitivity to shape information and greater robustness to multiple forms of visual noise, leading to improved correspondence with human perception. Our results provide novel neurocomputational evidence that blurry visual experiences are very important for conferring robustness to biological visual systems.
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Affiliation(s)
- Hojin Jang
- Department of Psychology and Vanderbilt Vision Research Center Vanderbilt University
| | - Frank Tong
- Department of Psychology and Vanderbilt Vision Research Center Vanderbilt University
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53
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Dȩbska A, Wójcik M, Chyl K, Dziȩgiel-Fivet G, Jednoróg K. Beyond the Visual Word Form Area - a cognitive characterization of the left ventral occipitotemporal cortex. Front Hum Neurosci 2023; 17:1199366. [PMID: 37576470 PMCID: PMC10416454 DOI: 10.3389/fnhum.2023.1199366] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 07/10/2023] [Indexed: 08/15/2023] Open
Abstract
The left ventral occipitotemporal cortex has been traditionally viewed as a pathway for visual object recognition including written letters and words. Its crucial role in reading was strengthened by the studies on the functionally localized "Visual Word Form Area" responsible for processing word-like information. However, in the past 20 years, empirical studies have challenged the assumptions of this brain region as processing exclusively visual or even orthographic stimuli. In this review, we aimed to present the development of understanding of the left ventral occipitotemporal cortex from the visually based letter area to the modality-independent symbolic language related region. We discuss theoretical and empirical research that includes orthographic, phonological, and semantic properties of language. Existing results showed that involvement of the left ventral occipitotemporal cortex is not limited to unimodal activity but also includes multimodal processes. The idea of the integrative nature of this region is supported by the broad functional and structural connectivity with language-related and attentional brain networks. We conclude that although the function of the area is not yet fully understood in human cognition, its role goes beyond visual word form processing. The left ventral occipitotemporal cortex seems to be crucial for combining higher-level language information with abstract forms that convey meaning independently of modality.
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Affiliation(s)
- Agnieszka Dȩbska
- Laboratory of Language Neurobiology, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Marta Wójcik
- Laboratory of Language Neurobiology, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Katarzyna Chyl
- Laboratory of Language Neurobiology, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
- The Educational Research Institute, Warsaw, Poland
| | - Gabriela Dziȩgiel-Fivet
- Laboratory of Language Neurobiology, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
| | - Katarzyna Jednoróg
- Laboratory of Language Neurobiology, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland
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54
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Lu X, Wang Q, Li X, Wang G, Chen Y, Li X, Li H. Connectivity reveals homology between the visual systems of the human and macaque brains. Front Neurosci 2023; 17:1207340. [PMID: 37476839 PMCID: PMC10354265 DOI: 10.3389/fnins.2023.1207340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 06/20/2023] [Indexed: 07/22/2023] Open
Abstract
The visual systems of humans and nonhuman primates share many similarities in both anatomical and functional organization. Understanding the homology and differences between the two systems can provide important insights into the neural basis of visual perception and cognition. This research aims to investigate the homology between human and macaque visual systems based on connectivity, using diffusion tensor imaging and resting-state functional magnetic resonance imaging to construct structural and functional connectivity fingerprints of the visual systems in humans and macaques, and quantitatively analyze the connectivity patterns. By integrating multimodal magnetic resonance imaging, this research explored the homology and differences between the two systems. The results showed that 9 brain regions in the macaque visual system formed highly homologous mapping relationships with 11 brain regions in the human visual system, and the related brain regions between the two species showed highly structure homologous, with their functional organization being essentially conserved across species. Finally, this research generated a homology information map of the visual system for humans and macaques, providing a new perspective for subsequent cross-species analysis.
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Affiliation(s)
- Xia Lu
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Qianshan Wang
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Xiaowen Li
- Shanxi Technology and Business College, Taiyuan, China
| | - Guolan Wang
- Shanxi Technology and Business College, Taiyuan, China
| | - Yifei Chen
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Xueqi Li
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
| | - Haifang Li
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China
- Shanxi Technology and Business College, Taiyuan, China
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55
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Xu Y, Vignali L, Sigismondi F, Crepaldi D, Bottini R, Collignon O. Similar object shape representation encoded in the inferolateral occipitotemporal cortex of sighted and early blind people. PLoS Biol 2023; 21:e3001930. [PMID: 37490508 PMCID: PMC10368275 DOI: 10.1371/journal.pbio.3001930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 06/23/2023] [Indexed: 07/27/2023] Open
Abstract
We can sense an object's shape by vision or touch. Previous studies suggested that the inferolateral occipitotemporal cortex (ILOTC) implements supramodal shape representations as it responds more to seeing or touching objects than shapeless textures. However, such activation in the anterior portion of the ventral visual pathway could be due to the conceptual representation of an object or visual imagery triggered by touching an object. We addressed these possibilities by directly comparing shape and conceptual representations of objects in early blind (who lack visual experience/imagery) and sighted participants. We found that bilateral ILOTC in both groups showed stronger activation during a shape verification task than during a conceptual verification task made on the names of the same manmade objects. Moreover, the distributed activity in the ILOTC encoded shape similarity but not conceptual association among objects. Besides the ILOTC, we also found shape representation in both groups' bilateral ventral premotor cortices and intraparietal sulcus (IPS), a frontoparietal circuit relating to object grasping and haptic processing. In contrast, the conceptual verification task activated both groups' left perisylvian brain network relating to language processing and, interestingly, the cuneus in early blind participants only. The ILOTC had stronger functional connectivity to the frontoparietal circuit than to the left perisylvian network, forming a modular structure specialized in shape representation. Our results conclusively support that the ILOTC selectively implements shape representation independently of visual experience, and this unique functionality likely comes from its privileged connection to the frontoparietal haptic circuit.
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Affiliation(s)
- Yangwen Xu
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
| | - Lorenzo Vignali
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
- International School for Advanced Studies (SISSA), Trieste, Italy
| | | | - Davide Crepaldi
- International School for Advanced Studies (SISSA), Trieste, Italy
| | - Roberto Bottini
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
| | - Olivier Collignon
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
- Psychological Sciences Research Institute (IPSY) and Institute of NeuroScience (IoNS), University of Louvain, Louvain-la-Neuve, Belgium
- School of Health Sciences, HES-SO Valais-Wallis, The Sense Innovation and Research Center, Lausanne and Sion, Switzerland
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56
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Wang H, Yao R, Zhang X, Chen C, Wu J, Dong M, Jin C. Visual expertise modulates resting-state brain network dynamics in radiologists: a degree centrality analysis. Front Neurosci 2023; 17:1152619. [PMID: 37266545 PMCID: PMC10229894 DOI: 10.3389/fnins.2023.1152619] [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: 01/28/2023] [Accepted: 04/26/2023] [Indexed: 06/03/2023] Open
Abstract
Visual expertise reflects accumulated experience in reviewing domain-specific images and has been shown to modulate brain function in task-specific functional magnetic resonance imaging studies. However, little is known about how visual experience modulates resting-state brain network dynamics. To explore this, we recruited 22 radiology interns and 22 matched healthy controls and used resting-state functional magnetic resonance imaging (rs-fMRI) and the degree centrality (DC) method to investigate changes in brain network dynamics. Our results revealed significant differences in DC between the RI and control group in brain regions associated with visual processing, decision making, memory, attention control, and working memory. Using a recursive feature elimination-support vector machine algorithm, we achieved a classification accuracy of 88.64%. Our findings suggest that visual experience modulates resting-state brain network dynamics in radiologists and provide new insights into the neural mechanisms of visual expertise.
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Affiliation(s)
- Hongmei Wang
- Department of Radiology, First Affiliated Hospital of Xi'an, Jiaotong University, Xi'an, China
- Department of Medical Imaging, Inner Mongolia People's Hospital, Hohhot, China
| | - Renhuan Yao
- Department of Nuclear Medicine, Inner Mongolia People's Hospital, Hohhot, China
| | - Xiaoyan Zhang
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Chao Chen
- PLA Funding Payment Center, Beijing, China
| | - Jia Wu
- School of Foreign Languages, Northwestern Polytechnical University, Xi'an, Shaanxi, China
| | - Minghao Dong
- Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education, School of Life Science and Technology, Xidian University, Xi'an, China
- Xi'an Key Laboratory of Intelligent Sensing and Regulation of Trans-Scale Life Information, School of Life Science and Technology, Xidian University, Xi'an, China
| | - Chenwang Jin
- Department of Radiology, First Affiliated Hospital of Xi'an, Jiaotong University, Xi'an, China
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57
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Taylor J, Xu Y. Comparing the Dominance of Color and Form Information across the Human Ventral Visual Pathway and Convolutional Neural Networks. J Cogn Neurosci 2023; 35:816-840. [PMID: 36877074 PMCID: PMC11283826 DOI: 10.1162/jocn_a_01979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2023]
Abstract
Color and form information can be decoded in every region of the human ventral visual hierarchy, and at every layer of many convolutional neural networks (CNNs) trained to recognize objects, but how does the coding strength of these features vary over processing? Here, we characterize for these features both their absolute coding strength-how strongly each feature is represented independent of the other feature-and their relative coding strength-how strongly each feature is encoded relative to the other, which could constrain how well a feature can be read out by downstream regions across variation in the other feature. To quantify relative coding strength, we define a measure called the form dominance index that compares the relative influence of color and form on the representational geometry at each processing stage. We analyze brain and CNN responses to stimuli varying based on color and either a simple form feature, orientation, or a more complex form feature, curvature. We find that while the brain and CNNs largely differ in how the absolute coding strength of color and form vary over processing, comparing them in terms of their relative emphasis of these features reveals a striking similarity: For both the brain and for CNNs trained for object recognition (but not for untrained CNNs), orientation information is increasingly de-emphasized, and curvature information is increasingly emphasized, relative to color information over processing, with corresponding processing stages showing largely similar values of the form dominance index.
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58
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Havlík M, Hlinka J, Klírová M, Adámek P, Horáček J. Towards causal mechanisms of consciousness through focused transcranial brain stimulation. Neurosci Conscious 2023; 2023:niad008. [PMID: 37089451 PMCID: PMC10120840 DOI: 10.1093/nc/niad008] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 01/10/2023] [Accepted: 03/30/2023] [Indexed: 04/25/2023] Open
Abstract
Conscious experience represents one of the most elusive problems of empirical science, namely neuroscience. The main objective of empirical studies of consciousness has been to describe the minimal sets of neural events necessary for a specific neuronal state to become consciously experienced. The current state of the art still does not meet this objective but rather consists of highly speculative theories based on correlates of consciousness and an ever-growing list of knowledge gaps. The current state of the art is defined by the limitations of past stimulation techniques and the emphasis on the observational approach. However, looking at the current stimulation technologies that are becoming more accurate, it is time to consider an alternative approach to studying consciousness, which builds on the methodology of causal explanations via causal alterations. The aim of this methodology is to move beyond the correlates of consciousness and focus directly on the mechanisms of consciousness with the help of the currently focused brain stimulation techniques, such as geodesic transcranial electric neuromodulation. This approach not only overcomes the limitations of the correlational methodology but will also become another firm step in the following science of consciousness.
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Affiliation(s)
- Marek Havlík
- Center for Advanced Studies of Brain and Consciousness, National Institute of Mental Health, Topolová 748, Klecany 250 67, Czech Republic
| | - Jaroslav Hlinka
- Center for Advanced Studies of Brain and Consciousness, National Institute of Mental Health, Topolová 748, Klecany 250 67, Czech Republic
- Department of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou věží 271/2, Prague 182 07, Czech Republic
| | - Monika Klírová
- Center for Advanced Studies of Brain and Consciousness, National Institute of Mental Health, Topolová 748, Klecany 250 67, Czech Republic
- Third Faculty of Medicine, Charles University, Ruská 87, Prague 10 100 00, Czech Republic
| | - Petr Adámek
- Center for Advanced Studies of Brain and Consciousness, National Institute of Mental Health, Topolová 748, Klecany 250 67, Czech Republic
- Third Faculty of Medicine, Charles University, Ruská 87, Prague 10 100 00, Czech Republic
| | - Jiří Horáček
- Center for Advanced Studies of Brain and Consciousness, National Institute of Mental Health, Topolová 748, Klecany 250 67, Czech Republic
- Third Faculty of Medicine, Charles University, Ruská 87, Prague 10 100 00, Czech Republic
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Kitazawa Y, Sonoda M, Sakakura K, Mitsuhashi T, Firestone E, Ueda R, Kambara T, Iwaki H, Luat AF, Marupudi NI, Sood S, Asano E. Intra- and inter-hemispheric network dynamics supporting object recognition and speech production. Neuroimage 2023; 270:119954. [PMID: 36828156 PMCID: PMC10112006 DOI: 10.1016/j.neuroimage.2023.119954] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 02/14/2023] [Accepted: 02/17/2023] [Indexed: 02/25/2023] Open
Abstract
We built normative brain atlases that animate millisecond-scale intra- and inter-hemispheric white matter-level connectivity dynamics supporting object recognition and speech production. We quantified electrocorticographic modulations during three naming tasks using event-related high-gamma activity from 1,114 nonepileptogenic intracranial electrodes (i.e., non-lesional areas unaffected by epileptiform discharges). Using this electrocorticography data, we visualized functional connectivity modulations defined as significant naming-related high-gamma modulations occurring simultaneously at two sites connected by direct white matter streamlines on diffusion-weighted imaging tractography. Immediately after stimulus onset, intra- and inter-hemispheric functional connectivity enhancements were confined mainly across modality-specific perceptual regions. During response preparation, left intra-hemispheric connectivity enhancements propagated in a posterior-to-anterior direction, involving the left precentral and prefrontal areas. After overt response onset, inter- and intra-hemispheric connectivity enhancements mainly encompassed precentral, postcentral, and superior-temporal (STG) gyri. We found task-specific connectivity enhancements during response preparation as follows. Picture naming enhanced activity along the left arcuate fasciculus between the inferior-temporal and precentral/posterior inferior-frontal (pIFG) gyri. Nonspeech environmental sound naming augmented functional connectivity via the left inferior longitudinal and fronto-occipital fasciculi between the medial-occipital and STG/pIFG. Auditory descriptive naming task enhanced usage of the left frontal U-fibers, involving the middle-frontal gyrus. Taken together, the commonly observed network enhancements include inter-hemispheric connectivity optimizing perceptual processing exerted in each hemisphere, left intra-hemispheric connectivity supporting semantic and lexical processing, and inter-hemispheric connectivity for symmetric oral movements during overt speech. Our atlases improve the currently available models of object recognition and speech production by adding neural dynamics via direct intra- and inter-hemispheric white matter tracts.
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Affiliation(s)
- Yu Kitazawa
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurology and Stroke Medicine, Yokohama City University, Yokohama, 2360004, Japan
| | - Masaki Sonoda
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurosurgery, Yokohama City University, Yokohama, 2360004, Japan
| | - Kazuki Sakakura
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurosurgery, University of Tsukuba, Tsukuba, 3058575, Japan
| | - Takumi Mitsuhashi
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurosurgery, Juntendo University, Tokyo, 1138421, Japan
| | - Ethan Firestone
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Physiology, Wayne State University, Detroit, 48201, USA
| | - Riyo Ueda
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA
| | - Toshimune Kambara
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Psychology, Hiroshima University, Hiroshima, 7398524, Japan
| | - Hirotaka Iwaki
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Psychiatry, Hachinohe City Hospital, Hachinohe, 0318555, Japan
| | - Aimee F Luat
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Pediatrics, Central Michigan University, Mount Pleasant, 48858, USA
| | - Neena I Marupudi
- Department of Neurosurgery, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA
| | - Sandeep Sood
- Department of Neurosurgery, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA
| | - Eishi Asano
- Department of Pediatrics, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA; Department of Neurology, Children's Hospital of Michigan, Wayne State University, Detroit, 48201, USA.
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MacLean MW, Hadid V, Spreng RN, Lepore F. Revealing robust neural correlates of conscious and unconscious visual processing: activation likelihood estimation meta-analyses. Neuroimage 2023; 273:120088. [PMID: 37030413 DOI: 10.1016/j.neuroimage.2023.120088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 03/30/2023] [Accepted: 04/03/2023] [Indexed: 04/09/2023] Open
Abstract
Our ability to consciously perceive information from the visual scene relies on a myriad of intrinsic neural mechanisms. Functional neuroimaging studies have sought to identify the neural correlates of conscious visual processing and to further dissociate from those pertaining to preconscious and unconscious visual processing. However, delineating what core brain regions are involved in eliciting a conscious percept remains a challenge, particularly regarding the role of prefrontal-parietal regions. We performed a systematic search of the literature that yielded a total of 54 functional neuroimaging studies. We conducted two quantitative meta-analyses using activation likelihood estimation to identify reliable patterns of activation engaged by i. conscious (n = 45 studies, comprising 704 participants) and ii. unconscious (n = 16 studies, comprising 262 participants) visual processing during various task performances. Results of the meta-analysis specific to conscious percepts quantitatively revealed reliable activations across a constellation of regions comprising the bilateral inferior frontal junction, intraparietal sulcus, dorsal anterior cingulate, angular gyrus, temporo-occipital cortex and anterior insula. Neurosynth reverse inference revealed conscious visual processing to be intertwined with cognitive terms related to attention, cognitive control and working memory. Results of the meta-analysis on unconscious percepts revealed consistent activations in the lateral occipital complex, intraparietal sulcus and precuneus. These findings highlight the notion that conscious visual processing readily engages higher-level regions including the inferior frontal junction and unconscious processing reliably recruits posterior regions, mainly the lateral occipital complex.
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Takeichi H, Taniguchi K, Shigemasu H. Visual and haptic cues in processing occlusion. Front Psychol 2023; 14:1082557. [PMID: 36968748 PMCID: PMC10036393 DOI: 10.3389/fpsyg.2023.1082557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 02/22/2023] [Indexed: 03/12/2023] Open
Abstract
IntroductionAlthough shape is effective in processing occlusion, ambiguities in segmentation can also be addressed using depth discontinuity given visually and haptically. This study elucidates the contribution of visual and haptic cues to depth discontinuity in processing occlusion.MethodsA virtual reality experiment was conducted with 15 students as participants. Word stimuli were presented on a head-mounted display for recognition. The central part of the words was masked with a virtual ribbon placed at different depths so that the ribbon appeared as an occlusion. The visual depth cue was either present with binocular stereopsis or absent with monocular presentation. The haptic cue was either missing, provided consecutively, or concurrently, by actively tracing a real off-screen bar edge that was positionally aligned with the ribbon in the virtual space. Recognition performance was compared between depth cue conditions.ResultsWe found that word recognition was better with the stereoscopic cue but not with the haptic cue, although both cues contributed to greater confidence in depth estimation. The performance was better when the ribbon was at the farther depth plane to appear as a hollow, rather than when it was at the nearer depth plane to cover the word.DiscussionThe results indicate that occlusion is processed in the human brain by visual input only despite the apparent effectiveness of haptic space perception, reflecting a complex set of natural constraints.
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Affiliation(s)
- Hiroshige Takeichi
- Computational Engineering Applications Unit, Head Office for Information Systems and Cybersecurity (ISC), RIKEN, Wako, Saitama, Japan
- Open Systems Information Science Team, Advanced Data Science Project (ADSP), RIKEN Information R&D and Strategy Headquarters (R-IH), RIKEN, Yokohama, Kanagawa, Japan
- *Correspondence: Hiroshige Takeichi,
| | - Keito Taniguchi
- School of Information, Kochi University of Technology, Kami, Kochi, Japan
| | - Hiroaki Shigemasu
- School of Information, Kochi University of Technology, Kami, Kochi, Japan
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Arrona-Cardoza P, Labonté K, Cisneros-Franco JM, Nielsen DE. The Effects of Food Advertisements on Food Intake and Neural Activity: A Systematic Review and Meta-Analysis of Recent Experimental Studies. Adv Nutr 2023; 14:339-351. [PMID: 36914293 DOI: 10.1016/j.advnut.2022.12.003] [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: 08/03/2022] [Revised: 12/01/2022] [Accepted: 12/22/2022] [Indexed: 01/01/2023] Open
Abstract
Food advertisements are ubiquitous in our daily environment. However, the relationships between exposure to food advertising and outcomes related to ingestive behavior require further investigation. The objective was to conduct a systematic review and meta-analysis of behavioral and neural responses to food advertising in experimental studies. PubMed, Web of Science, and Scopus were searched for articles published from January 2014 to November 2021 using a search strategy following PRISMA guidelines. Experimental studies conducted with human participants were included. A random-effects inverse-variance meta-analysis was performed on standardized mean differences (SMD) of food intake (behavioral outcome) between the food advertisement and nonfood advertisement conditions of each study. Subgroup analyses were performed by age, BMI group, study design, and advertising media type. A seed-based d mapping meta-analysis of neuroimaging studies was performed to evaluate neural activity between experimental conditions. Nineteen articles were eligible for inclusion, 13 for food intake (n = 1303) and 6 for neural activity (n = 303). The pooled analysis of food intake revealed small, but statistically significant, effects of increased intake after viewing food advertising compared with the control condition among adults and children (adult SMD: 0.16; 95% CI: 0.03, 0.28; P = 0.01; I2 = 0; 95% CI: 0, 95.0%; Children SMD: 0.25; 95% CI: 0.14, 0.37; P < 0.0001; I2 = 60.4%; 95% CI: 25.6%, 79.0%). The neuroimaging studies involved children only, and the pooled analysis corrected for multiple comparisons identified one significant cluster, the middle occipital gyrus, with increased activity after food advertising exposure compared with the control condition (peak coordinates: 30, -86, 12; z-value: 6.301, size: 226 voxels; P < 0.001). These findings suggest that acute exposure to food advertising increases food intake among children and adults and that the middle occipital gyrus is an implicated brain region among children. (PROSPERO registration: CRD42022311357).
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Affiliation(s)
| | - Katherine Labonté
- School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, Canada
| | - José Miguel Cisneros-Franco
- School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, Canada; Desautels Faculty of Management, McGill University, Montreal, Canada
| | - Daiva E Nielsen
- School of Human Nutrition, McGill University, Sainte-Anne-de-Bellevue, Canada.
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Taylor JJ, Lin C, Talmasov D, Ferguson MA, Schaper FLWVJ, Jiang J, Goodkind M, Grafman J, Etkin A, Siddiqi SH, Fox MD. A transdiagnostic network for psychiatric illness derived from atrophy and lesions. Nat Hum Behav 2023; 7:420-429. [PMID: 36635585 PMCID: PMC10236501 DOI: 10.1038/s41562-022-01501-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 11/23/2022] [Indexed: 01/13/2023]
Abstract
Psychiatric disorders share neurobiology and frequently co-occur. This neurobiological and clinical overlap highlights opportunities for transdiagnostic treatments. In this study, we used coordinate and lesion network mapping to test for a shared brain network across psychiatric disorders. In our meta-analysis of 193 studies, atrophy coordinates across six psychiatric disorders mapped to a common brain network defined by positive connectivity to anterior cingulate and insula, and by negative connectivity to posterior parietal and lateral occipital cortex. This network was robust to leave-one-diagnosis-out cross-validation and specific to atrophy coordinates from psychiatric versus neurodegenerative disorders (72 studies). In 194 patients with penetrating head trauma, lesion damage to this network correlated with the number of post-lesion psychiatric diagnoses. Neurosurgical ablation targets for psychiatric illness (four targets) also aligned with the network. This convergent brain network for psychiatric illness may partially explain high rates of psychiatric comorbidity and could highlight neuromodulation targets for patients with more than one psychiatric disorder.
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Affiliation(s)
- Joseph J Taylor
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
| | - Christopher Lin
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniel Talmasov
- Departments of Neurology and Psychiatry, Columbia University Medical Center, Columbia University College of Physicians and Surgeons, New York, NY, USA
| | - Michael A Ferguson
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Center for the Study of World Religions, Harvard Divinity School, Cambridge, MA, USA
| | - Frederic L W V J Schaper
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jing Jiang
- Stead Family Department of Pediatrics, University of Iowa Carver College of Medicine, Iowa City, IA, USA
- Iowa Neuroscience Institute, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - Madeleine Goodkind
- Departments of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
- New Mexico Veterans Affairs Healthcare System, Albuquerque, NM, USA
| | - Jordan Grafman
- Departments of Physical Medicine and Rehabilitation, Neurology, & Psychiatry, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- Shirley Ryan Ability Lab, Chicago, IL, USA
| | - Amit Etkin
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA
- Wu Tsai Neurosciences Institute at Stanford, Stanford University School of Medicine, Stanford, CA, USA
- Alto Neuroscience, Los Altos, CA, USA
| | - Shan H Siddiqi
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Michael D Fox
- Center for Brain Circuit Therapeutics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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64
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An expanded neural framework for shape perception. Trends Cogn Sci 2023; 27:212-213. [PMID: 36635181 DOI: 10.1016/j.tics.2022.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 12/02/2022] [Indexed: 01/12/2023]
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65
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Impact of glaucoma on the spatial frequency processing of scenes in central vision. Vis Neurosci 2023; 40:E001. [PMID: 36752177 PMCID: PMC9970733 DOI: 10.1017/s0952523822000086] [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] [Indexed: 02/09/2023]
Abstract
Glaucoma is an eye disease characterized by a progressive vision loss usually starting in peripheral vision. However, a deficit for scene categorization is observed even in the preserved central vision of patients with glaucoma. We assessed the processing and integration of spatial frequencies in the central vision of patients with glaucoma during scene categorization, considering the severity of the disease, in comparison to age-matched controls. In the first session, participants had to categorize scenes filtered in low-spatial frequencies (LSFs) and high-spatial frequencies (HSFs) as a natural or an artificial scene. Results showed that the processing of spatial frequencies was impaired only for patients with severe glaucoma, in particular for HFS scenes. In the light of proactive models of visual perception, we investigated how LSF could guide the processing of HSF in a second session. We presented hybrid scenes (combining LSF and HSF from two scenes belonging to the same or different semantic category). Participants had to categorize the scene filtered in HSF while ignoring the scene filtered in LSF. Surprisingly, results showed that the semantic influence of LSF on HSF was greater for patients with early glaucoma than controls, and then disappeared for the severe cases. This study shows that a progressive destruction of retinal ganglion cells affects the spatial frequency processing in central vision. This deficit may, however, be compensated by increased reliance on predictive mechanisms at early stages of the disease which would however decline in more severe cases.
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Palomar-García MÁ, Villar-Rodríguez E, Pérez-Lozano C, Sanjuán A, Bueichekú E, Miró-Padilla A, Costumero V, Adrián-Ventura J, Parcet MA, Ávila C. Two different brain networks underlying picture naming with familiar pre-existing native words and new vocabulary. BRAIN AND LANGUAGE 2023; 237:105231. [PMID: 36716643 DOI: 10.1016/j.bandl.2023.105231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 12/18/2022] [Accepted: 01/18/2023] [Indexed: 06/18/2023]
Abstract
The present research used fMRI to longitudinally investigate the impact of learning new vocabulary on the activation pattern of the language control network by measuring BOLD signal changes during picture naming tasks with familiar pre-existing native words (old words) and new vocabulary. Nineteen healthy participants successfully learned new synonyms for already known Spanish words, and they performed a picture naming task using the old words and the new words immediately after learning and two weeks after learning. The results showed that naming with old words, compared to naming with newly learned words, produced activations in a cortical network involving frontal and parietal regions, whereas the opposite contrast showed activation in a broader cortical/subcortical network, including the SMA/ACC, the hippocampus, and the midbrain. These two networks are maintained two weeks after learning. These results suggest that the language control network can be separated into two functional circuits for diverse cognitive purposes.
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Affiliation(s)
| | - Esteban Villar-Rodríguez
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology, Clinical Psychology and Psychobiology, University Jaume I, 12071 Castellón, Spain
| | - Cristina Pérez-Lozano
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology, Clinical Psychology and Psychobiology, University Jaume I, 12071 Castellón, Spain
| | - Ana Sanjuán
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology, Clinical Psychology and Psychobiology, University Jaume I, 12071 Castellón, Spain
| | - Elisenda Bueichekú
- Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Anna Miró-Padilla
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology, Clinical Psychology and Psychobiology, University Jaume I, 12071 Castellón, Spain
| | - Victor Costumero
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology, Clinical Psychology and Psychobiology, University Jaume I, 12071 Castellón, Spain
| | | | - María-Antonia Parcet
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology, Clinical Psychology and Psychobiology, University Jaume I, 12071 Castellón, Spain
| | - César Ávila
- Neuropsychology and Functional Neuroimaging Group, Department of Basic Psychology, Clinical Psychology and Psychobiology, University Jaume I, 12071 Castellón, Spain
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67
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Lee J, Jung M, Lustig N, Lee J. Neural representations of the perception of handwritten digits and visual objects from a convolutional neural network compared to humans. Hum Brain Mapp 2023; 44:2018-2038. [PMID: 36637109 PMCID: PMC9980894 DOI: 10.1002/hbm.26189] [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: 02/24/2022] [Revised: 12/04/2022] [Accepted: 12/12/2022] [Indexed: 01/14/2023] Open
Abstract
We investigated neural representations for visual perception of 10 handwritten digits and six visual objects from a convolutional neural network (CNN) and humans using functional magnetic resonance imaging (fMRI). Once our CNN model was fine-tuned using a pre-trained VGG16 model to recognize the visual stimuli from the digit and object categories, representational similarity analysis (RSA) was conducted using neural activations from fMRI and feature representations from the CNN model across all 16 classes. The encoded neural representation of the CNN model exhibited the hierarchical topography mapping of the human visual system. The feature representations in the lower convolutional (Conv) layers showed greater similarity with the neural representations in the early visual areas and parietal cortices, including the posterior cingulate cortex. The feature representations in the higher Conv layers were encoded in the higher-order visual areas, including the ventral/medial/dorsal stream and middle temporal complex. The neural representations in the classification layers were observed mainly in the ventral stream visual cortex (including the inferior temporal cortex), superior parietal cortex, and prefrontal cortex. There was a surprising similarity between the neural representations from the CNN model and the neural representations for human visual perception in the context of the perception of digits versus objects, particularly in the primary visual and associated areas. This study also illustrates the uniqueness of human visual perception. Unlike the CNN model, the neural representation of digits and objects for humans is more widely distributed across the whole brain, including the frontal and temporal areas.
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Affiliation(s)
- Juhyeon Lee
- Department of Brain and Cognitive EngineeringKorea UniversitySeoulRepublic of Korea
| | - Minyoung Jung
- Department of Brain and Cognitive EngineeringKorea UniversitySeoulRepublic of Korea
| | - Niv Lustig
- Department of Brain and Cognitive EngineeringKorea UniversitySeoulRepublic of Korea
| | - Jong‐Hwan Lee
- Department of Brain and Cognitive EngineeringKorea UniversitySeoulRepublic of Korea
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68
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Jiang X, Sultan AA, Dimick MK, Zai CC, Kennedy JL, MacIntosh BJ, Goldstein BI. The association of genetic variation in CACNA1C with resting-state functional connectivity in youth bipolar disorder. Int J Bipolar Disord 2023; 11:3. [PMID: 36637564 PMCID: PMC9839925 DOI: 10.1186/s40345-022-00281-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 12/13/2022] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND CACNA1C rs1006737 A allele, identified as a genetic risk variant for bipolar disorder (BD), is associated with anomalous functional connectivity in adults with and without BD. Studies have yet to investigate the association of CACNA1C rs1006737 with resting-state functional connectivity (rsFC) in youth BD. METHODS Participants included 139 youth with BD-I, -II, or -not otherwise specified, ages 13-20 years, including 27 BD A-carriers, 41 BD non-carriers, 32 healthy controls (HC) A-carriers, and 39 HC non-carriers. Anterior cingulate cortex (ACC), amygdala, and orbitofrontal cortex (OFC) were examined as regions-of-interest in seed-to-voxel analyses. General linear models included main effects of diagnosis and rs1006737, and an interaction term, controlling for age, sex, and race. RESULTS We observed a main effect of BD diagnosis on rsFC between the right amygdala and the right occipital pole (p = 0.02), and a main effect of rs1006737 genotypes on rsFC between the right OFC and bilateral occipital cortex (p < 0.001). Two significant BD diagnosis-by-CACNA1C rs1006737 interactions were also identified. The A allele was associated with positive rsFC between the right ACC and right amygdala in BD but negative rsFC in HC (p = 0.01), and negative rsFC between the left OFC and left putamen in BD but positive rsFC in HC (p = 0.01). CONCLUSION This study found that the rs1006737 A allele, identified as a genetic risk variant for BD in adults, was differentially associated with rsFC in youth with BD in regions relevant to emotion, executive function, and reward. Future task-based approaches are warranted to better understand brain connectivity in relation to CACNA1C in BD.
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Affiliation(s)
- Xinyue Jiang
- grid.155956.b0000 0000 8793 5925Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON Canada
| | - Alysha A. Sultan
- grid.155956.b0000 0000 8793 5925Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON Canada
| | - Mikaela K. Dimick
- grid.155956.b0000 0000 8793 5925Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON Canada
| | - Clement C. Zai
- grid.155956.b0000 0000 8793 5925Tanenbaum Centre for Pharmacogenetics, Psychiatric Neurogenetics Section, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, Canada
| | - James L. Kennedy
- grid.155956.b0000 0000 8793 5925Tanenbaum Centre for Pharmacogenetics, Psychiatric Neurogenetics Section, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Bradley J. MacIntosh
- grid.17063.330000 0001 2157 2938Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Medical Biophysics, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON Canada
| | - Benjamin I. Goldstein
- grid.155956.b0000 0000 8793 5925Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Pharmacology & Toxicology, University of Toronto, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, Canada
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Ayzenberg V, Simmons C, Behrmann M. Temporal asymmetries and interactions between dorsal and ventral visual pathways during object recognition. Cereb Cortex Commun 2023; 4:tgad003. [PMID: 36726794 PMCID: PMC9883614 DOI: 10.1093/texcom/tgad003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 12/30/2022] [Accepted: 01/02/2023] [Indexed: 01/15/2023] Open
Abstract
Despite their anatomical and functional distinctions, there is growing evidence that the dorsal and ventral visual pathways interact to support object recognition. However, the exact nature of these interactions remains poorly understood. Is the presence of identity-relevant object information in the dorsal pathway simply a byproduct of ventral input? Or, might the dorsal pathway be a source of input to the ventral pathway for object recognition? In the current study, we used high-density EEG-a technique with high temporal precision and spatial resolution sufficient to distinguish parietal and temporal lobes-to characterise the dynamics of dorsal and ventral pathways during object viewing. Using multivariate analyses, we found that category decoding in the dorsal pathway preceded that in the ventral pathway. Importantly, the dorsal pathway predicted the multivariate responses of the ventral pathway in a time-dependent manner, rather than the other way around. Together, these findings suggest that the dorsal pathway is a critical source of input to the ventral pathway for object recognition.
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Affiliation(s)
- Vladislav Ayzenberg
- Neuroscience Institute and Psychology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Claire Simmons
- School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Marlene Behrmann
- Neuroscience Institute and Psychology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, USA
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70
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Differential diagnosis of delusional symptoms in schizophrenia: Brain tractography data. COGN SYST RES 2023. [DOI: 10.1016/j.cogsys.2022.10.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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71
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Atilgan H, Koi JXJ, Wong E, Laakso I, Matilainen N, Pasqualotto A, Tanaka S, Chen SHA, Kitada R. Functional relevance of the extrastriate body area for visual and haptic object recognition: a preregistered fMRI-guided TMS study. Cereb Cortex Commun 2023; 4:tgad005. [PMID: 37188067 PMCID: PMC10176024 DOI: 10.1093/texcom/tgad005] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 03/22/2023] [Accepted: 03/27/2023] [Indexed: 05/17/2023] Open
Abstract
The extrastriate body area (EBA) is a region in the lateral occipito-temporal cortex (LOTC), which is sensitive to perceived body parts. Neuroimaging studies suggested that EBA is related to body and tool processing, regardless of the sensory modalities. However, how essential this region is for visual tool processing and nonvisual object processing remains a matter of controversy. In this preregistered fMRI-guided repetitive transcranial magnetic stimulation (rTMS) study, we examined the causal involvement of EBA in multisensory body and tool recognition. Participants used either vision or haptics to identify 3 object categories: hands, teapots (tools), and cars (control objects). Continuous theta-burst stimulation (cTBS) was applied over left EBA, right EBA, or vertex (control site). Performance for visually perceived hands and teapots (relative to cars) was more strongly disrupted by cTBS over left EBA than over the vertex, whereas no such object-specific effect was observed in haptics. The simulation of the induced electric fields confirmed that the cTBS affected regions including EBA. These results indicate that the LOTC is functionally relevant for visual hand and tool processing, whereas the rTMS over EBA may differently affect object recognition between the 2 sensory modalities.
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Affiliation(s)
- Hicret Atilgan
- Psychology, School of Social Sciences, Nanyang Technological University, 48 Nanyang Avenue, Singapore 639818, Singapore
| | - J X Janice Koi
- Psychology, School of Social Sciences, Nanyang Technological University, 48 Nanyang Avenue, Singapore 639818, Singapore
| | - Ern Wong
- IMT School for Advanced Studies Lucca, Piazza S. Francesco, 19, 55100 Lucca LU, Italy
| | - Ilkka Laakso
- Department of Electrical Engineering and Automation, Aalto University, Otakaari 3, 02150 Espoo, Finland
| | - Noora Matilainen
- Department of Electrical Engineering and Automation, Aalto University, Otakaari 3, 02150 Espoo, Finland
| | - Achille Pasqualotto
- Faculty of Human Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan
| | - Satoshi Tanaka
- Department of Psychology, Hamamatsu University School of Medicine, 1-20-1 Handayama, Higashi Ward, Hamamatsu, Shizuoka 431-3192, Japan
| | - S H Annabel Chen
- Psychology, School of Social Sciences, Nanyang Technological University, 48 Nanyang Avenue, Singapore 639818, Singapore
- Centre for Research and Development in Learning, Nanyang Technological University, 61 Nanyang Drive, Singapore 637335, Singapore
- Lee Kong Chian School of Medicine (LKCMedicine), Nanyang Technological University, 11 Mandalay Road, Singapore 308232, Singapore
| | - Ryo Kitada
- Corresponding author: Graduate School of Intercultural Studies, Kobe University, 12-1 Tsurukabuto, Nada Ward, Kobe, Hyogo 657-0013, Japan.
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Caravaglios G, Muscoso EG, Blandino V, Di Maria G, Gangitano M, Graziano F, Guajana F, Piccoli T. EEG Resting-State Functional Networks in Amnestic Mild Cognitive Impairment. Clin EEG Neurosci 2023; 54:36-50. [PMID: 35758261 DOI: 10.1177/15500594221110036] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background. Alzheimer's cognitive-behavioral syndrome is the result of impaired connectivity between nerve cells, due to misfolded proteins, which accumulate and disrupt specific brain networks. Electroencephalography, because of its excellent temporal resolution, is an optimal approach for assessing the communication between functionally related brain regions. Objective. To detect and compare EEG resting-state networks (RSNs) in patients with amnesic mild cognitive impairment (aMCI), and healthy elderly (HE). Methods. We recruited 125 aMCI patients and 70 healthy elderly subjects. One hundred and twenty seconds of artifact-free EEG data were selected and compared between patients with aMCI and HE. We applied standard low-resolution brain electromagnetic tomography (sLORETA)-independent component analysis (ICA) to assess resting-state networks. Each network consisted of a set of images, one for each frequency (delta, theta, alpha1/2, beta1/2). Results. The functional ICA analysis revealed 17 networks common to groups. The statistical procedure demonstrated that aMCI used some networks differently than HE. The most relevant findings were as follows. Amnesic-MCI had: i) increased delta/beta activity in the superior frontal gyrus and decreased alpha1 activity in the paracentral lobule (ie, default mode network); ii) greater delta/theta/alpha/beta in the superior frontal gyrus (i.e, attention network); iii) lower alpha in the left superior parietal lobe, as well as a lower delta/theta and beta, respectively in post-central, and in superior frontal gyrus(ie, attention network). Conclusions. Our study confirms sLORETA-ICA method is effective in detecting functional resting-state networks, as well as between-groups connectivity differences. The findings provide support to the Alzheimer's network disconnection hypothesis.
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Affiliation(s)
- G Caravaglios
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - E G Muscoso
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - V Blandino
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| | - G Di Maria
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - M Gangitano
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| | - F Graziano
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - F Guajana
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - T Piccoli
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
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Distinct multivariate structural brain profiles are related to variations in short- and long-delay memory consolidation across children and young adults. Dev Cogn Neurosci 2022; 59:101192. [PMID: 36566622 PMCID: PMC9803921 DOI: 10.1016/j.dcn.2022.101192] [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: 07/06/2022] [Revised: 12/12/2022] [Accepted: 12/21/2022] [Indexed: 12/24/2022] Open
Abstract
From early to middle childhood, brain regions that underlie memory consolidation undergo profound maturational changes. However, there is little empirical investigation that directly relates age-related differences in brain structural measures to memory consolidation processes. The present study examined memory consolidation of intentionally studied object-location associations after one night of sleep (short delay) and after two weeks (long delay) in normally developing 5-to-7-year-old children (n = 50) and young adults (n = 39). Behavioural differences in memory retention rate were related to structural brain measures. Our results showed that children, in comparison to young adults, retained correctly learnt object-location associations less robustly over short and long delay. Moreover, using partial least squares correlation method, a unique multivariate profile comprised of specific neocortical (prefrontal, parietal, and occipital), cerebellar, and hippocampal head and subfield structures in the body was found to be associated with variation in short-delay memory retention. A different multivariate profile comprised of a reduced set of brain structures, mainly consisting of neocortical (prefrontal, parietal, and occipital), hippocampal head, and selective hippocampal subfield structures (CA1-2 and subiculum) was associated with variation in long-delay memory retention. Taken together, the results suggest that multivariate structural pattern of unique sets of brain regions are related to variations in short- and long-delay memory consolidation across children and young adults.
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Labek K, Sittenberger E, Kienhöfer V, Rabl L, Messina I, Schurz M, Stingl JC, Viviani R. The gradient model of brain organization in decisions involving “empathy for pain”. Cereb Cortex 2022; 33:5839-5850. [PMID: 36537039 DOI: 10.1093/cercor/bhac464] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 09/20/2022] [Accepted: 09/26/2022] [Indexed: 12/24/2022] Open
Abstract
Abstract
Influential models of cortical organization propose a close relationship between heteromodal association areas and highly connected hubs in the default mode network. The “gradient model” of cortical organization proposes a close relationship between these areas and highly connected hubs in the default mode network, a set of cortical areas deactivated by demanding tasks. Here, we used a decision-making task and representational similarity analysis with classic “empathy for pain” stimuli to probe the relationship between high-level representations of imminent pain in others and these areas. High-level representations were colocalized with task deactivations or the transitions from activations to deactivations. These loci belonged to 2 groups: those that loaded on the high end of the principal cortical gradient and were associated by meta-analytic decoding with the default mode network, and those that appeared to accompany functional repurposing of somatosensory cortex in the presence of visual stimuli. These findings suggest that task deactivations may set out cortical areas that host high-level representations. We anticipate that an increased understanding of the cortical correlates of high-level representations may improve neurobiological models of social interactions and psychopathology.
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Affiliation(s)
- Karin Labek
- University of Innsbruck Institute of Psychology, , Universitätsstraße 5-7, 6020 Innsbruck , Austria
| | - Elisa Sittenberger
- University of Ulm Psychiatry and Psychotherapy Clinic III, , Leimgrubenweg 12, 89075 Ulm , Germany
| | - Valerie Kienhöfer
- University of Innsbruck Institute of Psychology, , Universitätsstraße 5-7, 6020 Innsbruck , Austria
- University of Ulm Psychiatry and Psychotherapy Clinic III, , Leimgrubenweg 12, 89075 Ulm , Germany
| | - Luna Rabl
- University of Innsbruck Institute of Psychology, , Universitätsstraße 5-7, 6020 Innsbruck , Austria
- University of Ulm Psychiatry and Psychotherapy Clinic III, , Leimgrubenweg 12, 89075 Ulm , Germany
| | - Irene Messina
- University of Ulm Psychiatry and Psychotherapy Clinic III, , Leimgrubenweg 12, 89075 Ulm , Germany
- Scienze e Tecniche Psicologiche,Universitas Mercatorum , Piazza Mattei 10, 00186 Rome , Italy
| | - Matthias Schurz
- University of Innsbruck Institute of Psychology, , Universitätsstraße 5-7, 6020 Innsbruck , Austria
- University of Innsbruck Digital Science Center (DiSC), , Innrain 15, 6020 Innsbruck , Austria
| | - Julia C Stingl
- University Clinic Aachen Clinical Pharmacology, , Wendlingweg 2, 52074 Aachen , Germany
| | - Roberto Viviani
- University of Innsbruck Institute of Psychology, , Universitätsstraße 5-7, 6020 Innsbruck , Austria
- University of Ulm Psychiatry and Psychotherapy Clinic III, , Leimgrubenweg 12, 89075 Ulm , Germany
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75
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Ulrich M, Harpaintner M, Trumpp NM, Berger A, Kiefer M. Academic training increases grounding of scientific concepts in experiential brain systems. Cereb Cortex 2022; 33:5646-5657. [PMID: 36514124 DOI: 10.1093/cercor/bhac449] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Revised: 10/18/2022] [Accepted: 10/19/2022] [Indexed: 12/15/2022] Open
Abstract
Scientific concepts typically transcendent our sensory experiences. Traditional approaches to science education therefore assume a shift towards amodal or verbal knowledge representations during academic training. Grounded cognition approaches, in contrast, predict a maintenance of grounding of the concepts in experiential brain networks or even an increase. To test these competing approaches, the present study investigated the semantic content of scientific psychological concepts and identified the corresponding neural circuits using functional magnetic resonance imaging (fMRI) in undergraduate psychology students (beginners) and in graduated psychologists (advanced learners). During fMRI scanning, participants were presented with words denoting scientific psychological concepts within a lexical decision task (e.g. "conditioning", "habituation"). The individual semantic property content of each concept was related to brain activity during abstract concept processing. In both beginners and advanced learners, visual and motor properties activated brain regions also involved in perception and action, while mental state properties increased activity in brain regions also recruited by emotional-social scene observation. Only in advanced learners, social constellation properties elicited brain activity overlapping with emotional-social scene observation. In line with grounded cognition approaches, the present results highlight the importance of experiential information for constituting the meaning of abstract scientific concepts during the course of academic training.
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Affiliation(s)
- Martin Ulrich
- Department of Psychiatry, Ulm University, Leimgrubenweg 12, Ulm 89075, Germany
| | - Marcel Harpaintner
- Department of Psychiatry, Ulm University, Leimgrubenweg 12, Ulm 89075, Germany
| | - Natalie M Trumpp
- Department of Psychiatry, Ulm University, Leimgrubenweg 12, Ulm 89075, Germany
| | - Alexander Berger
- Department of Psychiatry, Ulm University, Leimgrubenweg 12, Ulm 89075, Germany
| | - Markus Kiefer
- Department of Psychiatry, Ulm University, Leimgrubenweg 12, Ulm 89075, Germany
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76
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Zhu Y, Zeng Y, Ren J, Zhang L, Chen C, Fernandez G, Qin S. Emotional learning retroactively promotes memory integration through rapid neural reactivation and reorganization. eLife 2022; 11:e60190. [PMID: 36476501 PMCID: PMC9815824 DOI: 10.7554/elife.60190] [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: 06/18/2020] [Accepted: 12/06/2022] [Indexed: 12/13/2022] Open
Abstract
Neutral events preceding emotional experiences can be better remembered, likely by assigning them as significant to guide possible use in future. Yet, the neurobiological mechanisms of how emotional learning enhances memory for past mundane events remain unclear. By two behavioral studies and one functional magnetic resonance imaging study with an adapted sensory preconditioning paradigm, we show rapid neural reactivation and connectivity changes underlying emotion-charged retroactive memory enhancement. Behaviorally, emotional learning retroactively enhanced initial memory for neutral associations across the three studies. Neurally, emotional learning potentiated trial-specific reactivation of overlapping neural traces in the hippocampus and stimulus-relevant neocortex. It further induced rapid hippocampal-neocortical functional reorganization supporting such retroactive memory benefit, as characterized by enhanced hippocampal-neocortical coupling modulated by the amygdala during emotional learning, and a shift of hippocampal connectivity from stimulus-relevant neocortex to distributed transmodal prefrontal-parietal areas at post-learning rests. Together, emotional learning retroactively promotes memory integration for past neutral events through stimulating trial-specific reactivation of overlapping representations and reorganization of associated memories into an integrated network to foster its priority for future use.
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Affiliation(s)
- Yannan Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenNetherlands
| | - Yimeng Zeng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Jingyuan Ren
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenNetherlands
| | - Lingke Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
| | - Changming Chen
- School of Education, Chongqing Normal UniversityChongqingChina
| | - Guillen Fernandez
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterNijmegenNetherlands
| | - Shaozheng Qin
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijingChina
- Chinese Institute for Brain ResearchBeijingChina
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77
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Gifford AT, Dwivedi K, Roig G, Cichy RM. A large and rich EEG dataset for modeling human visual object recognition. Neuroimage 2022; 264:119754. [PMID: 36400378 PMCID: PMC9771828 DOI: 10.1016/j.neuroimage.2022.119754] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Revised: 09/14/2022] [Accepted: 11/14/2022] [Indexed: 11/16/2022] Open
Abstract
The human brain achieves visual object recognition through multiple stages of linear and nonlinear transformations operating at a millisecond scale. To predict and explain these rapid transformations, computational neuroscientists employ machine learning modeling techniques. However, state-of-the-art models require massive amounts of data to properly train, and to the present day there is a lack of vast brain datasets which extensively sample the temporal dynamics of visual object recognition. Here we collected a large and rich dataset of high temporal resolution EEG responses to images of objects on a natural background. This dataset includes 10 participants, each with 82,160 trials spanning 16,740 image conditions. Through computational modeling we established the quality of this dataset in five ways. First, we trained linearizing encoding models that successfully synthesized the EEG responses to arbitrary images. Second, we correctly identified the recorded EEG data image conditions in a zero-shot fashion, using EEG synthesized responses to hundreds of thousands of candidate image conditions. Third, we show that both the high number of conditions as well as the trial repetitions of the EEG dataset contribute to the trained models' prediction accuracy. Fourth, we built encoding models whose predictions well generalize to novel participants. Fifth, we demonstrate full end-to-end training of randomly initialized DNNs that output EEG responses for arbitrary input images. We release this dataset as a tool to foster research in visual neuroscience and computer vision.
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Affiliation(s)
- Alessandro T. Gifford
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany,Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany,Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany,Corresponding author.
| | - Kshitij Dwivedi
- Department of Computer Science, Goethe Universität, Frankfurt am Main, Germany
| | - Gemma Roig
- Department of Computer Science, Goethe Universität, Frankfurt am Main, Germany
| | - Radoslaw M. Cichy
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany,Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Berlin, Germany,Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany,Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
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78
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Zhang W, Andrews-Hanna JR, Mair RW, Goh JOS, Gutchess A. Functional connectivity with medial temporal regions differs across cultures during post-encoding rest. COGNITIVE, AFFECTIVE & BEHAVIORAL NEUROSCIENCE 2022; 22:1334-1348. [PMID: 35896854 PMCID: PMC9703377 DOI: 10.3758/s13415-022-01027-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 07/12/2022] [Indexed: 01/27/2023]
Abstract
Connectivity of the brain at rest can reflect individual differences and impact behavioral outcomes, including memory. The present study investigated how culture influences functional connectivity with regions of the medial temporal lobe. In this study, 46 Americans and 59 East Asians completed a resting state scan after encoding pictures of objects. To investigate cross-cultural differences in resting state functional connectivity, left parahippocampal gyrus (anterior and posterior regions) and left hippocampus were selected as seed regions. These regions were selected, because they were previously implicated in a study of cultural differences during the successful encoding of detailed memories. Results revealed that left posterior parahippocampal gyrus had stronger connectivity with temporo-occipital regions for East Asians compared with Americans and stronger connectivity with parieto-occipital regions for Americans compared with East Asians. Left anterior parahippocampal gyrus had stronger connectivity with temporal regions for East Asians than Americans and stronger connectivity with frontal regions for Americans than East Asians. Although connectivity did not relate to memory performance, patterns did relate to cultural values. The degree of independent self-construal and subjective value of tradition were associated with functional connectivity involving left anterior parahippocampal gyrus. Findings are discussed in terms of potential cultural differences in memory consolidation or more general trait or state-based processes, such as holistic versus analytic processing.
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Affiliation(s)
- Wanbing Zhang
- Department of Psychology, Brandeis University, 415 South Street, MS 062, Waltham, MA, 02453, USA
| | - Jessica R Andrews-Hanna
- Department of Psychology, University of Arizona, Tucson, AZ, USA
- Cognitive Science, University of Arizona, Tucson, AZ, USA
| | - Ross W Mair
- Center for Brain Science, Harvard University, Cambridge, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Joshua Oon Soo Goh
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei City, Taiwan
- Department of Psychology, National Taiwan University, Taipei City, Taiwan
- Neurobiology and Cognitive Science Center, National Taiwan University, Taipei City, Taiwan
- Center of Artificial Intelligence and Advanced Robotics, National Taiwan University, Taipei City, Taiwan
| | - Angela Gutchess
- Department of Psychology, Brandeis University, 415 South Street, MS 062, Waltham, MA, 02453, USA.
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79
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Scheliga S, Schwank R, Scholle R, Habel U, Kellermann T. A neural mechanism underlying predictive visual motion processing in patients with schizophrenia. Psychiatry Res 2022; 318:114934. [PMID: 36347125 DOI: 10.1016/j.psychres.2022.114934] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 10/22/2022] [Accepted: 10/27/2022] [Indexed: 11/06/2022]
Abstract
Psychotic symptoms may be traced back to sensory sensitivity. Thereby, visual motion (VM) processing particularly has been suggested to be impaired in schizophrenia (SCZ). In healthy brains, VM underlies predictive processing within hierarchically structured systems. However, less is known about predictive VM processing in SCZ. Therefore, we performed fMRI during a VM paradigm with three conditions of varying predictability, i.e., Predictable-, Random-, and Arbitrary motion. The study sample comprised 17 SCZ patients and 23 healthy controls. We calculated general linear model (GLM) analysis to assess group differences in VM processing across motion conditions. Here, we identified significantly lower activity in right temporoparietal junction (TPJ) for SCZ patients. Therefore, right TPJ was set as seed for connectivity analyses. For patients, across conditions we identified increased connections to higher regions, namely medial prefrontal cortex, or paracingulate gyrus. Healthy subjects activated sensory regions as area V5, or superior parietal lobule. Reduced TPJ activity may reflect both a failure in the bottom-up flow of visual information and a decrease of signal processing as consequence of increased top-down input from frontal areas. In sum, these altered neural patterns provide a framework for future studies focusing on predictive VM processing to identify potential biomarkers of psychosis.
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Affiliation(s)
- Sebastian Scheliga
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty RWTH, Aachen University, Pauwelsstraße 30, 52074 Aachen, Germany.
| | - Rosalie Schwank
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty RWTH, Aachen University, Pauwelsstraße 30, 52074 Aachen, Germany
| | - Ruben Scholle
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty RWTH, Aachen University, Pauwelsstraße 30, 52074 Aachen, Germany
| | - Ute Habel
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty RWTH, Aachen University, Pauwelsstraße 30, 52074 Aachen, Germany; JARA-Institute Brain Structure Function Relationship, Pauwelsstraße 30, 52074 Aachen, Germany
| | - Thilo Kellermann
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty RWTH, Aachen University, Pauwelsstraße 30, 52074 Aachen, Germany; JARA-Institute Brain Structure Function Relationship, Pauwelsstraße 30, 52074 Aachen, Germany
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80
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Ma S, Wang L, Chen P, Qin R, Hou L, Yan B. A Mixed Visual Encoding Model Based on the Larger-Scale Receptive Field for Human Brain Activity. Brain Sci 2022; 12:brainsci12121633. [PMID: 36552093 PMCID: PMC9775903 DOI: 10.3390/brainsci12121633] [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: 09/30/2022] [Revised: 11/18/2022] [Accepted: 11/28/2022] [Indexed: 11/30/2022] Open
Abstract
Research on visual encoding models for functional magnetic resonance imaging derived from deep neural networks, especially CNN (e.g., VGG16), has been developed. However, CNNs typically use smaller kernel sizes (e.g., 3 × 3) for feature extraction in visual encoding models. Although the receptive field size of CNN can be enlarged by increasing the network depth or subsampling, it is limited by the small size of the convolution kernel, leading to an insufficient receptive field size. In biological research, the size of the neuronal population receptive field of high-level visual encoding regions is usually three to four times that of low-level visual encoding regions. Thus, CNNs with a larger receptive field size align with the biological findings. The RepLKNet model directly expands the convolution kernel size to obtain a larger-scale receptive field. Therefore, this paper proposes a mixed model to replace CNN for feature extraction in visual encoding models. The proposed model mixes RepLKNet and VGG so that the mixed model has a receptive field of different sizes to extract more feature information from the image. The experimental results indicate that the mixed model achieves better encoding performance in multiple regions of the visual cortex than the traditional convolutional model. Also, a larger-scale receptive field should be considered in building visual encoding models so that the convolution network can play a more significant role in visual representations.
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81
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McGrath H, Zaveri HP, Collins E, Jafar T, Chishti O, Obaid S, Ksendzovsky A, Wu K, Papademetris X, Spencer DD. High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter. Sci Rep 2022; 12:18778. [PMID: 36335146 PMCID: PMC9637135 DOI: 10.1038/s41598-022-21543-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/28/2022] [Indexed: 11/06/2022] Open
Abstract
Precise cortical brain localization presents an important challenge in the literature. Brain atlases provide data-guided parcellation based on functional and structural brain metrics, and each atlas has its own unique benefits for localization. We offer a parcellation guided by intracranial electroencephalography, a technique which has historically provided pioneering advances in our understanding of brain structure-function relationships. We used a consensus boundary mapping approach combining anatomical designations in Duvernoy's Atlas of the Human Brain, a widely recognized textbook of human brain anatomy, with the anatomy of the MNI152 template and the magnetic resonance imaging scans of an epilepsy surgery cohort. The Yale Brain Atlas consists of 690 one-square centimeter parcels based around conserved anatomical features and each with a unique identifier to communicate anatomically unambiguous localization. We report on the methodology we used to create the Atlas along with the findings of a neuroimaging study assessing the accuracy and clinical usefulness of cortical localization using the Atlas. We also share our vision for the Atlas as a tool in the clinical and research neurosciences, where it may facilitate precise localization of data on the cortex, accurate description of anatomical locations, and modern data science approaches using standardized brain regions.
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Affiliation(s)
- Hari McGrath
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA.
- GKT School of Medical Education, King's College London, London, UK.
| | - Hitten P Zaveri
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Evan Collins
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
- Yale School of Engineering and Applied Science, New Haven, CT, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Tamara Jafar
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Omar Chishti
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
- Yale School of Engineering and Applied Science, New Haven, CT, USA
| | - Sami Obaid
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Alexander Ksendzovsky
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Kun Wu
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
| | - Xenophon Papademetris
- Department of Radiology and Biomedical Engineering, Yale School of Medicine, New Haven, CT, USA
- Department of Biomedical Engineering, Yale School of Medicine, New Haven, CT, USA
| | - Dennis D Spencer
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
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82
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Aminoff EM, Durham T. Scene-selective brain regions respond to embedded objects of a scene. Cereb Cortex 2022; 33:5066-5074. [PMID: 36305640 DOI: 10.1093/cercor/bhac399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 09/12/2022] [Accepted: 09/13/2022] [Indexed: 11/14/2022] Open
Abstract
Abstract
Objects are fundamental to scene understanding. Scenes are defined by embedded objects and how we interact with them. Paradoxically, scene processing in the brain is typically discussed in contrast to object processing. Using the BOLD5000 dataset (Chang et al., 2019), we examined whether objects within a scene predicted the neural representation of scenes, as measured by functional magnetic resonance imaging in humans. Stimuli included 1,179 unique scenes across 18 semantic categories. Object composition of scenes were compared across scene exemplars in different semantic scene categories, and separately, in exemplars of the same scene category. Neural representations in scene- and object-preferring brain regions were significantly related to which objects were in a scene, with the effect at times stronger in the scene-preferring regions. The object model accounted for more variance when comparing scenes within the same semantic category to scenes from different categories. Here, we demonstrate the function of scene-preferring regions includes the processing of objects. This suggests visual processing regions may be better characterized by the processes, which are engaged when interacting with the stimulus kind, such as processing groups of objects in scenes, or processing a single object in our foreground, rather than the stimulus kind itself.
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Affiliation(s)
- Elissa M Aminoff
- Fordham University Department of Psychology, , 226 Dealy Hall, 441 E. Fordham Rd, Bronx, NY 10458, United States
| | - Tess Durham
- Fordham University Department of Psychology, , 226 Dealy Hall, 441 E. Fordham Rd, Bronx, NY 10458, United States
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83
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Ramp-shaped neural tuning supports graded population-level representation of the object-to-scene continuum. Sci Rep 2022; 12:18081. [PMID: 36302932 PMCID: PMC9613906 DOI: 10.1038/s41598-022-21768-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 09/30/2022] [Indexed: 01/24/2023] Open
Abstract
We can easily perceive the spatial scale depicted in a picture, regardless of whether it is a small space (e.g., a close-up view of a chair) or a much larger space (e.g., an entire class room). How does the human visual system encode this continuous dimension? Here, we investigated the underlying neural coding of depicted spatial scale, by examining the voxel tuning and topographic organization of brain responses. We created naturalistic yet carefully-controlled stimuli by constructing virtual indoor environments, and rendered a series of snapshots to smoothly sample between a close-up view of the central object and far-scale view of the full environment (object-to-scene continuum). Human brain responses were measured to each position using functional magnetic resonance imaging. We did not find evidence for a smooth topographic mapping for the object-to-scene continuum on the cortex. Instead, we observed large swaths of cortex with opposing ramp-shaped profiles, with highest responses to one end of the object-to-scene continuum or the other, and a small region showing a weak tuning to intermediate scale views. However, when we considered the population code of the entire ventral occipito-temporal cortex, we found smooth and linear representation of the object-to-scene continuum. Our results together suggest that depicted spatial scale information is encoded parametrically in large-scale population codes across the entire ventral occipito-temporal cortex.
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84
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Working memory updating in individuals with bipolar and unipolar depression: fMRI study. Transl Psychiatry 2022; 12:441. [PMID: 36220840 PMCID: PMC9553934 DOI: 10.1038/s41398-022-02211-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 09/26/2022] [Accepted: 09/29/2022] [Indexed: 01/10/2023] Open
Abstract
Understanding neurobiological characteristics of cognitive dysfunction in distinct psychiatric disorders remains challenging. In this secondary data analysis, we examined neurobiological differences in brain response during working memory updating among individuals with bipolar disorder (BD), those with unipolar depression (UD), and healthy controls (HC). Individuals between 18-45 years of age with BD (n = 100), UD (n = 109), and HC (n = 172) were scanned using fMRI while performing 0-back (easy) and 2-back (difficult) tasks with letters as the stimuli and happy, fearful, or neutral faces as distractors. The 2(n-back) × 3(groups) × 3(distractors) ANCOVA examined reaction time (RT), accuracy, and brain activation during the task. HC showed more accurate and faster responses than individuals with BD and UD. Difficulty-related activation in the prefrontal, posterior parietal, paracingulate cortices, striatal, lateral occipital, precuneus, and thalamic regions differed among groups. Individuals with BD showed significantly lower difficulty-related activation differences in the left lateral occipital and the right paracingulate cortices than those with UD. In individuals with BD, greater difficulty-related worsening in accuracy was associated with smaller activity changes in the right precuneus, while greater difficulty-related slowing in RT was associated with smaller activity changes in the prefrontal, frontal opercular, paracingulate, posterior parietal, and lateral occipital cortices. Measures of current depression and mania did not correlate with the difficulty-related brain activation differences in either group. Our findings suggest that the alterations in the working memory circuitry may be a trait characteristic of reduced working memory capacity in mood disorders. Aberrant patterns of activation in the left lateral occipital and paracingulate cortices may be specific to BD.
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85
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Folvik L, Sneve MH, Ness HT, Vidal-Piñeiro D, Raud L, Geier OM, Walhovd KB, Fjell AM. Sustained upregulation of widespread hippocampal-neocortical coupling following memory encoding. Cereb Cortex 2022; 33:4844-4858. [PMID: 36190442 PMCID: PMC10110434 DOI: 10.1093/cercor/bhac384] [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: 02/11/2022] [Revised: 08/29/2022] [Accepted: 08/30/2022] [Indexed: 11/14/2022] Open
Abstract
Systems consolidation of new experiences into lasting episodic memories involves hippocampal-neocortical interactions. Evidence of this process is already observed during early post-encoding rest periods, both as increased hippocampal coupling with task-relevant perceptual regions and reactivation of stimulus-specific patterns following intensive encoding tasks. We investigate the spatial and temporal characteristics of these hippocampally anchored post-encoding neocortical modulations. Eighty-nine adults participated in an experiment consisting of interleaved memory task- and resting-state periods. We observed increased post-encoding functional connectivity between hippocampus and individually localized neocortical regions responsive to stimuli encountered during memory encoding. Post-encoding modulations were manifested as a nearly system-wide upregulation in hippocampal coupling with all major functional networks. The configuration of these extensive modulations resembled hippocampal-neocortical interaction patterns estimated from active encoding operations, suggesting hippocampal post-encoding involvement exceeds perceptual aspects. Reinstatement of encoding patterns was not observed in resting-state scans collected 12 h later, nor when using other candidate seed regions. The similarity in hippocampal functional coupling between online memory encoding and offline post-encoding rest suggests reactivation in humans involves a spectrum of cognitive processes engaged during the experience of an event. There were no age effects, suggesting that upregulation of hippocampal-neocortical connectivity represents a general phenomenon seen across the adult lifespan.
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Affiliation(s)
- Line Folvik
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Forskningsveien 3A, 0373 Oslo, Norway
| | - Markus H Sneve
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Forskningsveien 3A, 0373 Oslo, Norway
| | - Hedda T Ness
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Forskningsveien 3A, 0373 Oslo, Norway
| | - Didac Vidal-Piñeiro
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Forskningsveien 3A, 0373 Oslo, Norway
| | - Liisa Raud
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Forskningsveien 3A, 0373 Oslo, Norway
| | - Oliver M Geier
- Department of Diagnostic Physics, Oslo University Hospital, Postbox 4950 Nydalen, OUS, Rikshospitalet, 0424 Oslo, Norway
| | - Kristine B Walhovd
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Forskningsveien 3A, 0373 Oslo, Norway.,Division of Radiology and Nuclear Medicine, Oslo University Hospital, Postbox 4950 Nydalen, OUS, Rikshospitalet, 0424 Oslo, Norway
| | - Anders M Fjell
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition, University of Oslo, Forskningsveien 3A, 0373 Oslo, Norway.,Division of Radiology and Nuclear Medicine, Oslo University Hospital, Postbox 4950 Nydalen, OUS, Rikshospitalet, 0424 Oslo, Norway
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86
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The medial temporal lobe structure and function support positive affect. Neuropsychologia 2022; 176:108373. [PMID: 36167193 DOI: 10.1016/j.neuropsychologia.2022.108373] [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: 05/24/2022] [Revised: 09/20/2022] [Accepted: 09/21/2022] [Indexed: 11/24/2022]
Abstract
Positive affect (PA) is not only associated with individuals' psychological and physical health, but also their cognitive processes. However, whether medial temporal lobe (MTL) and its subfields' volume/functional connectivity can explain individual variability in PA remains understudied. We investigated the morphological (i.e., grey matter volume; GMV) and functional characteristics (i.e., resting-state functional connectivity; rsFC) of PA with a combination of univariate and multivariate pattern analyses (MVPA) using a large sample of participants (n = 321). We simultaneously collected the T1-weighted (n = 321), high-resolution MTL T2-weighted, and resting-state functional imaging data (n = 209). The MTL and its subfields' volumes, including the CA1, CA2+3, DG, and subiculum (SUB), perirhinal cortex (PRC), and parahippocampus (PHC), were extracted using an automatic segmentation of hippocampal subfields (ASHS) software. The morphological results revealed that GMVs in the prefrontal-occipital and limbic (i.e., hippocampus, amygdala, and PHC) systems were associated with variability in PA at the whole-brain level using MVPA but not univariate analysis. Linear regression results further revealed a positive association between the MTL subfields' GMV, especially for the right PRC, and PA after controlling for several covariates. PRC-seed-based rsFC analyses further revealed that its couplings with the fronto-parietal-occipital system predicted PA in both univariate and MVPA. These findings provide novel insights into the neuroanatomical and functional substrates underlying human PA trait. Findings also suggest critical contributions of the MTL and its subfield of the perirhinal cortex, but not hippocampal subfields, as well as its functional coupling with the fronto-parietal control-system on the formation of PA.
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87
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Fox FAU, Diers K, Lee H, Mayr A, Reuter M, Breteler MMB, Aziz NA. Association Between Accelerometer-Derived Physical Activity Measurements and Brain Structure: A Population-Based Cohort Study. Neurology 2022; 99:e1202-e1215. [PMID: 35918154 PMCID: PMC9536740 DOI: 10.1212/wnl.0000000000200884] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 05/11/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES While there is growing evidence that physical activity promotes neuronal health, studies examining the relation between physical activity and brain morphology remain inconclusive. We therefore examined whether objectively quantified physical activity is related to brain volume, cortical thickness, and gray matter density in a large cohort study. In addition, we assessed molecular pathways that may underlie the effects of physical activity on brain morphology. METHODS We used cross-sectional baseline data from 2,550 eligible participants (57.6% women; mean age: 54.7 years, range: 30-94 years) of a prospective cohort study. Physical activity dose (metabolic equivalent hours and step counts) and intensity (sedentary and light-intensity and moderate-to-vigorous intensity activities) were recorded with accelerometers. Brain volumetric, gray matter density, and cortical thickness measures were obtained from 3T MRI scans using FreeSurfer and Statistical Parametric Mapping. The relation of physical activity (independent variable) and brain structure (outcome) was examined with polynomial multivariable regression, while adjusting for age, sex, intracranial volume, education, and smoking. Using gene expression profiles from the Allen Brain Atlas, we extracted molecular signatures associated with the effects of physical activity on brain morphology. RESULTS Physical activity dose and intensity were independently associated with larger brain volumes, gray matter density, and cortical thickness of several brain regions. The effects of physical activity on brain volume were most pronounced at low physical activity quantities and differed between men and women and across age. For example, more time spent in moderate-to-vigorous intensity activities was associated with greater total gray matter volume, but the relation leveled off with more activity (standardized β [95% CIs]: 1.37 [0.35-2.39] and -0.70 [-1.25 to -0.15] for the linear and quadratic terms, respectively). The strongest effects of physical activity were observed in motor regions and cortical regions enriched for genes involved in mitochondrial respiration. DISCUSSION Our findings suggest that physical activity benefits brain health, with the strongest effects in motor regions and regions with a high oxidative demand. While young adults may particularly profit from additional high-intensity activities, older adults may already benefit from light-intensity activities. Physical activity and reduced sedentary time may be critical in the prevention of age-associated brain atrophy and neurodegenerative diseases.
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Affiliation(s)
- Fabienne A U Fox
- From the Population Health Sciences (F.A.U.F., H.L., M.M.B.B., N.A.A.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Image Analysis (K.D., M.R.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Institute for Medical Biometry (A.M., M.M.B.B.), Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Germany; A.A. Martinos Center for Biomedical Imaging (M.R.), Massachusetts General Hospital, Boston; Department of Radiology (M.R.), Harvard Medical School, Boston, MA; and Department of Neurology (N.A.A.), Faculty of Medicine, University of Bonn, Germany
| | - Kersten Diers
- From the Population Health Sciences (F.A.U.F., H.L., M.M.B.B., N.A.A.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Image Analysis (K.D., M.R.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Institute for Medical Biometry (A.M., M.M.B.B.), Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Germany; A.A. Martinos Center for Biomedical Imaging (M.R.), Massachusetts General Hospital, Boston; Department of Radiology (M.R.), Harvard Medical School, Boston, MA; and Department of Neurology (N.A.A.), Faculty of Medicine, University of Bonn, Germany
| | - Hweeling Lee
- From the Population Health Sciences (F.A.U.F., H.L., M.M.B.B., N.A.A.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Image Analysis (K.D., M.R.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Institute for Medical Biometry (A.M., M.M.B.B.), Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Germany; A.A. Martinos Center for Biomedical Imaging (M.R.), Massachusetts General Hospital, Boston; Department of Radiology (M.R.), Harvard Medical School, Boston, MA; and Department of Neurology (N.A.A.), Faculty of Medicine, University of Bonn, Germany
| | - Andreas Mayr
- From the Population Health Sciences (F.A.U.F., H.L., M.M.B.B., N.A.A.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Image Analysis (K.D., M.R.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Institute for Medical Biometry (A.M., M.M.B.B.), Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Germany; A.A. Martinos Center for Biomedical Imaging (M.R.), Massachusetts General Hospital, Boston; Department of Radiology (M.R.), Harvard Medical School, Boston, MA; and Department of Neurology (N.A.A.), Faculty of Medicine, University of Bonn, Germany
| | - Martin Reuter
- From the Population Health Sciences (F.A.U.F., H.L., M.M.B.B., N.A.A.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Image Analysis (K.D., M.R.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Institute for Medical Biometry (A.M., M.M.B.B.), Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Germany; A.A. Martinos Center for Biomedical Imaging (M.R.), Massachusetts General Hospital, Boston; Department of Radiology (M.R.), Harvard Medical School, Boston, MA; and Department of Neurology (N.A.A.), Faculty of Medicine, University of Bonn, Germany
| | - Monique M B Breteler
- From the Population Health Sciences (F.A.U.F., H.L., M.M.B.B., N.A.A.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Image Analysis (K.D., M.R.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Institute for Medical Biometry (A.M., M.M.B.B.), Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Germany; A.A. Martinos Center for Biomedical Imaging (M.R.), Massachusetts General Hospital, Boston; Department of Radiology (M.R.), Harvard Medical School, Boston, MA; and Department of Neurology (N.A.A.), Faculty of Medicine, University of Bonn, Germany
| | - N Ahmad Aziz
- From the Population Health Sciences (F.A.U.F., H.L., M.M.B.B., N.A.A.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Image Analysis (K.D., M.R.), German Center for Neurodegenerative Diseases (DZNE), Bonn; Institute for Medical Biometry (A.M., M.M.B.B.), Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Germany; A.A. Martinos Center for Biomedical Imaging (M.R.), Massachusetts General Hospital, Boston; Department of Radiology (M.R.), Harvard Medical School, Boston, MA; and Department of Neurology (N.A.A.), Faculty of Medicine, University of Bonn, Germany.
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88
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Evidence of genetic overlap and causal relationships between blood-based biochemical traits and human cortical anatomy. Transl Psychiatry 2022; 12:373. [PMID: 36075890 PMCID: PMC9458732 DOI: 10.1038/s41398-022-02141-3] [Citation(s) in RCA: 5] [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] [Received: 03/13/2022] [Revised: 08/18/2022] [Accepted: 08/25/2022] [Indexed: 01/08/2023] Open
Abstract
Psychiatric disorders such as schizophrenia are commonly associated with structural brain alterations affecting the cortex. Recent genetic evidence suggests circulating metabolites and other biochemical traits play a causal role in many psychiatric disorders which could be mediated by changes in the cerebral cortex. Here, we leveraged publicly available genome-wide association study data to explore shared genetic architecture and evidence for causal relationships between a panel of 50 biochemical traits and measures of cortical thickness and surface area. Linkage disequilibrium score regression identified 191 genetically correlated biochemical-cortical trait pairings, with consistent representation of blood cell counts and other biomarkers such as C-reactive protein (CRP), haemoglobin and calcium. Spatially organised patterns of genetic correlation were additionally uncovered upon clustering of region-specific correlation profiles. Interestingly, by employing latent causal variable models, we found strong evidence suggesting CRP and vitamin D exert causal effects on region-specific cortical thickness, with univariable and multivariable Mendelian randomization further supporting a negative causal relationship between serum CRP levels and thickness of the lingual region. Our findings suggest a subset of biochemical traits exhibit shared genetic architecture and potentially causal relationships with cortical structure in functionally distinct regions, which may contribute to alteration of cortical structure in psychiatric disorders.
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89
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Macoveanu J, Stougaard ME, Kjærstad HL, Knudsen GM, Vinberg M, Kessing LV, Miskowiak KW. Trajectory of aberrant reward processing in patients with bipolar disorder - A longitudinal fMRI study. J Affect Disord 2022; 312:235-244. [PMID: 35760195 DOI: 10.1016/j.jad.2022.06.053] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 05/31/2022] [Accepted: 06/20/2022] [Indexed: 11/29/2022]
Abstract
BACKGROUND Bipolar disorder (BD), and especially the mania phenotype, is characterized by heightened reward responsivity and aberrant reward processing. In this longitudinal fMRI study, we investigated neuronal response during reward anticipation as the computed expected value (EV) and outcome evaluation as reward prediction error (RPE) in recently diagnosed patients with BD. METHODS Eighty remitted patients with BD and 60 healthy controls (HC) underwent fMRI during which they performed a card guessing task. Of these, 41 patients and 36 HC were re-scanned after 16 months. We compared reward-related neural activity between groups at baseline and longitudinally and assessed the impact of mood relapse. RESULTS Patients showed lower RPE signal in areas of the ventrolateral prefrontal cortex (vlPFC) than HC. In these regions, the HC showed decrease in RPE signal over time, which was absent in patients. Patients further exhibited decreased EV signal in the occipital cortex across baseline and follow-up. Patients who remained in remission showed normalization of the EV signal at follow-up. Baseline activity in the identified regions was not associated with subsequent relapse. LIMITATIONS Follow-up scans were only available in a relatively small sample. Medication status, follow-up time and BD illness duration prior to diagnosis varied. CONCLUSIONS Lower RPE signal in the vlPFC in patients with BD at baseline and its lack of normative reduction over time may represent a trait marker of dysfunctional reward-based learning or habituation. The increase in EV signal in the occipital cortex over time in patients who remained in remission may indicate normalization of reward anticipation activity.
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Affiliation(s)
- J Macoveanu
- Copenhagen Affective Disorder research Centre (CADIC), Psychiatric Centre Copenhagen, Copenhagen University Hospital, Rigshospitalet, Denmark
| | - M E Stougaard
- Copenhagen Affective Disorder research Centre (CADIC), Psychiatric Centre Copenhagen, Copenhagen University Hospital, Rigshospitalet, Denmark
| | - H L Kjærstad
- Copenhagen Affective Disorder research Centre (CADIC), Psychiatric Centre Copenhagen, Copenhagen University Hospital, Rigshospitalet, Denmark
| | - G M Knudsen
- Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet, Denmark; Department of Clinical Medicine, University of Copenhagen, Denmark
| | - M Vinberg
- Copenhagen Affective Disorder research Centre (CADIC), Psychiatric Centre Copenhagen, Copenhagen University Hospital, Rigshospitalet, Denmark; Mental Health Centre, Northern Zealand, Copenhagen University Hospital-Mental Health Services CPH, Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Denmark
| | - L V Kessing
- Copenhagen Affective Disorder research Centre (CADIC), Psychiatric Centre Copenhagen, Copenhagen University Hospital, Rigshospitalet, Denmark; Department of Clinical Medicine, University of Copenhagen, Denmark
| | - K W Miskowiak
- Copenhagen Affective Disorder research Centre (CADIC), Psychiatric Centre Copenhagen, Copenhagen University Hospital, Rigshospitalet, Denmark; Department of Psychology, University of Copenhagen, Denmark.
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90
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High-Level Visual Encoding Model Framework with Hierarchical Ventral Stream-Optimized Neural Networks. Brain Sci 2022; 12:brainsci12081101. [PMID: 36009164 PMCID: PMC9406060 DOI: 10.3390/brainsci12081101] [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: 06/28/2022] [Revised: 07/26/2022] [Accepted: 08/18/2022] [Indexed: 11/20/2022] Open
Abstract
Visual encoding models based on deep neural networks (DNN) show good performance in predicting brain activity in low-level visual areas. However, due to the amount of neural data limitation, DNN-based visual encoding models are difficult to fit for high-level visual areas, resulting in insufficient encoding performance. The ventral stream suggests that higher visual areas receive information from lower visual areas, which is not fully reflected in the current encoding models. In the present study, we propose a novel visual encoding model framework which uses the hierarchy of representations in the ventral stream to improve the model’s performance in high-level visual areas. Under the framework, we propose two categories of hierarchical encoding models from the voxel and the feature perspectives to realize the hierarchical representations. From the voxel perspective, we first constructed an encoding model for the low-level visual area (V1 or V2) and extracted the voxel space predicted by the model. Then we use the extracted voxel space of the low-level visual area to predict the voxel space of the high-level visual area (V4 or LO) via constructing a voxel-to-voxel model. From the feature perspective, the feature space of the first model is extracted to predict the voxel space of the high-level visual area. The experimental results show that two categories of hierarchical encoding models effectively improve the encoding performance in V4 and LO. In addition, the proportion of the best-encoded voxels for different models in V4 and LO show that our proposed models have obvious advantages in prediction accuracy. We find that the hierarchy of representations in the ventral stream has a positive effect on improving the performance of the existing model in high-level visual areas.
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91
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McIntyre-Wood C, Madan C, Owens M, Amlung M, Sweet LH, MacKillop J. Neuroanatomical foundations of delayed reward discounting decision making II: Evaluation of sulcal morphology and fractal dimensionality. Neuroimage 2022; 257:119309. [PMID: 35598732 DOI: 10.1016/j.neuroimage.2022.119309] [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: 11/22/2021] [Revised: 04/01/2022] [Accepted: 05/10/2022] [Indexed: 11/25/2022] Open
Abstract
Delayed reward discounting (DRD) is a form of decision-making reflecting valuation of smaller immediate rewards versus larger delayed rewards, and high DRD has been linked to several health behaviors, including substance use disorders, attention-deficit/hyperactivity disorder, and obesity. Elucidating the underlying neuroanatomical factors may offer important insights into the etiology of these conditions. We used structural MRI scans of 1038 Human Connectome Project participants (Mage = 28.86, 54.7% female) to explore two novel measures of neuroanatomy related to DRD: 1) sulcal morphology (SM; depth and width) and 2) fractal dimensionality (FD), or cortical morphometric complexity, of parcellated cortical and subcortical regions. To ascertain unique contributions to DRD preferences, indicators that displayed significant partial correlations with DRD after family-wise error correction were entered into iterative mixed-effect models guided by the association magnitude. When considering only SM indicators, the depth of the right inferior and width of the left central sulci were uniquely associated with DRD preferences. When considering only FD indicators, the FD of the left middle temporal gyrus, right lateral orbitofrontal cortex, and left lateral occipital and entorhinal cortices uniquely contributed DRD. When considering SM and FD indicators simultaneously, the right inferior frontal sulcus depth and left central sulcus width; and the FD of the left middle temporal gyrus, lateral occipital cortex and entorhinal cortex were uniquely associated with DRD. These results implicate SM and FD as features of the brain that underlie variation in the DRD decision-making phenotype and as promising candidates for understanding DRD as a biobehavioral disease process.
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Affiliation(s)
- Carly McIntyre-Wood
- Peter Boris Centre for Addictions Research, McMaster University & St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - Christopher Madan
- School of Psychology, University of Nottingham, Nottingham, United Kingdom
| | - Max Owens
- Peter Boris Centre for Addictions Research, McMaster University & St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
| | - Michael Amlung
- Cofrin Logan Center for Addiction Research and Treatment, Lawrence, KS, United States of America; Department of Applied Behavioural Sciences, University of Kansas, Lawrence, KS, United States of America
| | - Lawrence H Sweet
- Department of Psychology, University of Georgia, Athens, GA, United States of America
| | - James MacKillop
- Peter Boris Centre for Addictions Research, McMaster University & St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
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92
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Campane LZ, Nucci MP, Nishiyama M, Von Zuben M, Amaro E, da Luz PL. Long term effects of red wine consumption in brain: an MRI, fMRI and neuropsychological evaluation study. Nutr Neurosci 2022:1-12. [PMID: 35943074 DOI: 10.1080/1028415x.2022.2108258] [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: 10/15/2022]
Abstract
Red wine (RW) consumption has been proposed to have a potential health benefit. However, the effect of RW consumption on the brain is not entirely known, mainly when associated with aging. Regular red wine consumers (n = 30) and abstainers (ABST; n = 27) without cognitive impairment were evaluated for brain structural characteristics (Fazekas score and voxel-based morphometry) and for functional adaptations assessed by fMRI (using the Word Tasks Color Stroop (WCST) and Two-Back (TBT)), as well as by neuropsychological tests in different domains. There were no significant differences regarding brain morphological features. RW consumers showed greater activation in the thalamus during WCST and in paracingulate/anterior cingulate cortices, left superior frontal gyrus and frontal pole during TBT. ABST required higher activation of different cortical areas in the left parietal lobe during WCST. Age and intelligence quotient influenced those activations. In Stroop and trail-making neuropsychological tests, RW consumers performed slightly better than ABST. This study should be viewed as hypothesis-generating rather than conclusive.
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Affiliation(s)
- Lucas Zoppi Campane
- LIM-44 (NIF - Neuroimagem Funcional), Departamento de Radiologia, Faculdade de Medicina da Universidade de São Paulo (USP), São Paulo, Brazil
| | - Mariana Penteado Nucci
- LIM-44 (NIF - Neuroimagem Funcional), Departamento de Radiologia, Faculdade de Medicina da Universidade de São Paulo (USP), São Paulo, Brazil
| | - Marcelo Nishiyama
- Instituto de Cardiologia (InCor), Faculdade de Medicina da Universidade de São Paulo (USP), São Paulo, Brazil
| | - Marina Von Zuben
- Instituto de Psiquiatria, Faculdade de Medicina da Universidade de São Paulo (USP), São Paulo, Brazil
| | - Edson Amaro
- LIM-44 (NIF - Neuroimagem Funcional), Departamento de Radiologia, Faculdade de Medicina da Universidade de São Paulo (USP), São Paulo, Brazil
| | - Protasio Lemos da Luz
- Instituto de Cardiologia (InCor), Faculdade de Medicina da Universidade de São Paulo (USP), São Paulo, Brazil
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Jarret J, Ferré P, Chedid G, Bedetti C, Bore A, Joanette Y, Rouleau I, Maria Brambati S. Functional network and structural connections involved in picture naming. BRAIN AND LANGUAGE 2022; 231:105146. [PMID: 35709592 DOI: 10.1016/j.bandl.2022.105146] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Revised: 04/14/2022] [Accepted: 06/03/2022] [Indexed: 06/15/2023]
Abstract
We mapped the left hemisphere cortical regions and fiber bundles involved in picture naming in adults by integrating task-based fMRI with dMRI tractography. We showed that a ventral pathway that "maps image and sound to meaning" involves the middle occipital, inferior temporal, superior temporal, inferior frontal gyri, and the temporal pole where a signal exchange is made possible by the inferior fronto-occipital, inferior longitudinal, middle longitudinal, uncinate fasciculi, and the extreme capsule. A dorsal pathway that "maps sound to speech" implicates the inferior temporal, superior temporal, inferior frontal, precentral gyri, and the supplementary motor area where the arcuate fasciculus and the frontal aslant ensure intercommunication. This study provides a neurocognitive model of picture naming and supports the hypothesis that the ventral indirect route passes through the temporal pole. This further supports the idea that the inferior and superior temporal gyri may play pivotal roles within the dual-stream framework of language.
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Affiliation(s)
- Julien Jarret
- Département de psychologie, Université de Montréal, Montréal, QC, Canada; Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
| | - Perrine Ferré
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
| | - Georges Chedid
- Département de psychologie, Université de Montréal, Montréal, QC, Canada; Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
| | - Christophe Bedetti
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
| | - Arnaud Bore
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
| | - Yves Joanette
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada
| | - Isabelle Rouleau
- Département de psychologie, Université du Québec à Montréal (UQÀM), QC, Canada
| | - Simona Maria Brambati
- Département de psychologie, Université de Montréal, Montréal, QC, Canada; Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Montréal, QC, Canada.
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Girault JB, Donovan K, Hawks Z, Talovic M, Forsen E, Elison JT, Shen MD, Swanson MR, Wolff JJ, Kim SH, Nishino T, Davis S, Snyder AZ, Botteron KN, Estes AM, Dager SR, Hazlett HC, Gerig G, McKinstry R, Pandey J, Schultz RT, St John T, Zwaigenbaum L, Todorov A, Truong Y, Styner M, Pruett JR, Constantino JN, Piven J. Infant Visual Brain Development and Inherited Genetic Liability in Autism. Am J Psychiatry 2022; 179:573-585. [PMID: 35615814 PMCID: PMC9356977 DOI: 10.1176/appi.ajp.21101002] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE Autism spectrum disorder (ASD) is heritable, and younger siblings of ASD probands are at higher likelihood of developing ASD themselves. Prospective MRI studies of siblings report that atypical brain development precedes ASD diagnosis, although the link between brain maturation and genetic factors is unclear. Given that familial recurrence of ASD is predicted by higher levels of ASD traits in the proband, the authors investigated associations between proband ASD traits and brain development among younger siblings. METHODS In a sample of 384 proband-sibling pairs (89 pairs concordant for ASD), the authors examined associations between proband ASD traits and sibling brain development at 6, 12, and 24 months in key MRI phenotypes: total cerebral volume, cortical surface area, extra-axial cerebrospinal fluid, occipital cortical surface area, and splenium white matter microstructure. Results from primary analyses led the authors to implement a data-driven approach using functional connectivity MRI at 6 months. RESULTS Greater levels of proband ASD traits were associated with larger total cerebral volume and surface area and larger surface area and reduced white matter integrity in components of the visual system in siblings who developed ASD. This aligned with weaker functional connectivity between several networks and the visual system among all siblings during infancy. CONCLUSIONS The findings provide evidence that specific early brain MRI phenotypes of ASD reflect quantitative variation in familial ASD traits. Multimodal anatomical and functional convergence on cortical regions, fiber pathways, and functional networks involved in visual processing suggest that inherited liability has a role in shaping the prodromal development of visual circuitry in ASD.
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Affiliation(s)
- Jessica B Girault
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Educational Psychology (Wolff), University of Minnesota, Minneapolis;Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Kevin Donovan
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Zoë Hawks
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Muhamed Talovic
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Elizabeth Forsen
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Jed T Elison
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Mark D Shen
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Meghan R Swanson
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Jason J Wolff
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Sun Hyung Kim
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Tomoyuki Nishino
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Savannah Davis
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Abraham Z Snyder
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Kelly N Botteron
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Annette M Estes
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Stephen R Dager
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Heather C Hazlett
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Guido Gerig
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Robert McKinstry
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Juhi Pandey
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Robert T Schultz
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Tanya St John
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Lonnie Zwaigenbaum
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Alexandre Todorov
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Young Truong
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Martin Styner
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - John R Pruett
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - John N Constantino
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
| | -
- Carolina Institute for Developmental Disabilities (Girault, Forsen, Shen, Hazlett, Piven), Department of Psychiatry (Girault, Shen, Kim, Hazlett, Styner, Piven), Department of Biostatistics (Donovan, Truong), and ; Department of Psychological and Brain Sciences (Hawks) and Department of Psychiatry (Talovic, Nishino, Davis, Botteron, Todorov, Pruett, Constantino), Washington University School of Medicine in St. Louis; Institute of Child Development (Elison) and Department of Psychology, School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, Tex. (Swanson); Department of Radiology, Washington University in St. Louis (Snyder, McKinstry); Department of Speech and Hearing Science, University of Washington, Seattle (Estes, St. John); Department of Radiology, University of Washington Medical Center, Seattle (Dager); Tandon School of Engineering, New York University, New York (Gerig); Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia (Pandey, Schultz); Department of Pediatrics, University of Alberta, Edmonton, Canada (Zwaigenbaum)
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Thams F, Külzow N, Flöel A, Antonenko D. Modulation of network centrality and gray matter microstructure using multi-session brain stimulation and memory training. Hum Brain Mapp 2022; 43:3416-3426. [PMID: 35373873 PMCID: PMC9248322 DOI: 10.1002/hbm.25857] [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: 11/08/2021] [Revised: 02/15/2022] [Accepted: 03/24/2022] [Indexed: 11/07/2022] Open
Abstract
Neural mechanisms of behavioral improvement induced by repeated transcranial direct current stimulation (tDCS) combined with cognitive training are yet unclear. Previously, we reported behavioral effects of a 3-day visuospatial memory training with concurrent anodal tDCS over the right temporoparietal cortex in older adults. To investigate intervention-induced neural alterations we here used functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) datasets available from 35 participants of this previous study, acquired before and after the intervention. To delineate changes in whole-brain functional network architecture, we employed eigenvector centrality mapping. Gray matter alterations were analyzed using DTI-derived mean diffusivity (MD). Network centrality in the bilateral posterior temporooccipital cortex was reduced after anodal compared to sham stimulation. This focal effect is indicative of decreased functional connectivity of the brain region underneath the anodal electrode and its left-hemispheric homolog with other "relevant" (i.e., highly connected) brain regions, thereby providing evidence for reorganizational processes within the brain's network architecture. Examining local MD changes in these clusters, an interaction between stimulation condition and training success indicated a decrease of MD in the right (stimulated) temporooccipital cluster in individuals who showed superior behavioral training benefits. Using a data-driven whole-brain network approach, we provide evidence for targeted neuromodulatory effects of a combined tDCS-and-training intervention. We show for the first time that gray matter alterations of microstructure (assessed by DTI-derived MD) may be involved in tDCS-enhanced cognitive training. Increased knowledge on how combined interventions modulate neural networks in older adults, will help the development of specific therapeutic interventions against age-associated cognitive decline.
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Affiliation(s)
- Friederike Thams
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany
| | - Nadine Külzow
- Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Neurocure Cluster of Excellence, Berlin, Germany.,Neurological Rehabilitation Clinic, Kliniken Beelitz GmbH, Beelitz, Germany
| | - Agnes Flöel
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany.,German Centre for Neurodegenerative Diseases (DZNE) Standort Greifswald, Greifswald, Germany
| | - Daria Antonenko
- Department of Neurology, Universitätsmedizin Greifswald, Greifswald, Germany
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96
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Masuda T, Shi S, Varma P, Fisher D, Shirazi S. Do Surrounding People's Emotions Affect Judgment of the Central Person's Emotion? Comparing Within Cultural Variation in Holistic Patterns of Emotion Perception in the Multicultural Canadian Society. Front Hum Neurosci 2022; 16:886971. [PMID: 35874162 PMCID: PMC9300416 DOI: 10.3389/fnhum.2022.886971] [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: 03/01/2022] [Accepted: 06/06/2022] [Indexed: 11/13/2022] Open
Abstract
Previous studies in cultural psychology have suggested that when assessing a target person's emotion, East Asians are more likely to incorporate the background figure's emotion into the judgment of the target's emotion compared to North Americans. The objective of this study was to further examine cultural variation in emotion perception within a culturally diverse population that is representative of Canada's multicultural society. We aimed to see whether East-Asian Canadians tended to keep holistic tendencies of their heritage culture regarding emotion perception. Participants were presented with 60 cartoon images consisting of a central figure and four surrounding figures and were then asked to rate the central figure's emotion; out of the four cartoon figures, two were female and two were male. Each character was prepared with 5 different emotional settings with corresponding facial expressions including: extremely sad, moderately sad, neutral, moderately happy, and extremely happy. Each central figure was surrounded by a group of 4 background figures. As a group, the background figures either displayed a sad, happy, or neutral expression. The participant's task was to judge the intensity of the central figures' happiness or sadness on a 10-point Likert scale ranging from 0 (not at all) to 9 (extremely). For analysis, we divided the participants into three groups: European Canadians (N = 105), East Asian Canadians' (N = 104) and Non-East Asian/Non-European Canadians (N = 161). The breakdown for the Non-East Asian/Non-European Canadian group is as follows: 94 South Asian Canadians, 25 Middle Eastern Canadians, 23 African Canadians, 9 Indigenous Canadians, and 10 Latin/Central/South American Canadians. Results comparing European Canadians and East Asian Canadians demonstrated cultural variation in emotion judgment, indicating that East Asian Canadians were in general more likely than their European Canadian counterparts to be affected by the background figures' emotion. The study highlights important cultural variations in holistic and analytic patterns of emotional attention in the ethnically diverse Canadian society. We discussed future studies which broaden the scope of research to incorporate a variety of diverse cultural backgrounds outside of the Western educational context to fully comprehend cultural variations in context related attentional patterns.
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Affiliation(s)
- Takahiko Masuda
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
| | - Shuwei Shi
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
| | - Pragya Varma
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
| | - Delaney Fisher
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
| | - Safi Shirazi
- Department of Psychology, University of Alberta, Edmonton, AB, Canada
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97
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Rapid Automatized Picture Naming in an Outpatient Concussion Center: Quantitative Eye Movements during the Mobile Universal Lexicon Evaluation System (MULES) Test. CLINICAL AND TRANSLATIONAL NEUROSCIENCE 2022. [DOI: 10.3390/ctn6030018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Number and picture rapid automatized naming (RAN) tests are useful sideline diagnostic tools. The main outcome measure of these RAN tests is the completion time, which is prolonged with a concussion, yet yields no information about eye movement behavior. We investigated eye movements during a digitized Mobile Universal Lexicon Evaluation System (MULES) test of rapid picture naming. A total of 23 participants with a history of concussion and 50 control participants performed MULES testing with simultaneous eye tracking. The test times were longer in participants with a concussion (32.4 s [95% CI 30.4, 35.8] vs. 26.9 s [95% CI 25.9, 28.0], t=6.1). The participants with a concussion made more saccades per picture than the controls (3.6 [95% CI 3.3, 4.1] vs. 2.7 [95% CI 2.5, 3.0]), and this increase was correlated with longer MULES times (r = 0.46, p = 0.026). The inter-saccadic intervals (ISI) did not differ between the groups, nor did they correlate with the test times. Following a concussion, eye movement behavior differs during number versus picture RAN performance. Prior studies have shown that ISI prolongation is the key finding for a number-based RAN test, whereas this study shows a primary finding of an increased saccade number per picture with a picture-based RAN test. Number-based and picture-based RAN tests may be complimentary in concussion detection, as they may detect different injury effects or compensatory strategies.
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98
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Functional alterations in large-scale resting-state networks of amyotrophic lateral sclerosis: A multi-site study across Canada and the United States. PLoS One 2022; 17:e0269154. [PMID: 35709100 PMCID: PMC9202847 DOI: 10.1371/journal.pone.0269154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Accepted: 05/16/2022] [Indexed: 11/19/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a multisystem neurodegenerative disorder characterized by progressive degeneration of upper motor neurons and lower motor neurons, and frontotemporal regions resulting in impaired bulbar, limb, and cognitive function. Magnetic resonance imaging studies have reported cortical and subcortical brain involvement in the pathophysiology of ALS. The present study investigates the functional integrity of resting-state networks (RSNs) and their importance in ALS. Intra- and inter-network resting-state functional connectivity (Rs-FC) was examined using an independent component analysis approach in a large multi-center cohort. A total of 235 subjects (120 ALS patients; 115 healthy controls (HC) were recruited across North America through the Canadian ALS Neuroimaging Consortium (CALSNIC). Intra-network and inter-network Rs-FC was evaluated by the FSL-MELODIC and FSLNets software packages. As compared to HC, ALS patients displayed higher intra-network Rs-FC in the sensorimotor, default mode, right and left fronto-parietal, and orbitofrontal RSNs, and in previously undescribed networks including auditory, dorsal attention, basal ganglia, medial temporal, ventral streams, and cerebellum which negatively correlated with disease severity. Furthermore, ALS patients displayed higher inter-network Rs-FC between the orbitofrontal and basal ganglia RSNs which negatively correlated with cognitive impairment. In summary, in ALS there is an increase in intra- and inter-network functional connectivity of RSNs underpinning both motor and cognitive impairment. Moreover, the large multi-center CALSNIC dataset permitted the exploration of RSNs in unprecedented detail, revealing previously undescribed network involvement in ALS.
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99
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Testing the distributed representation hypothesis in object recognition in two open datasets. Neurosci Lett 2022; 783:136709. [PMID: 35667579 DOI: 10.1016/j.neulet.2022.136709] [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: 11/04/2021] [Revised: 05/30/2022] [Accepted: 05/31/2022] [Indexed: 11/23/2022]
Abstract
Neural representation has long been thought to follow the modularity hypothesis, which states that each type of information corresponds to a specific brain area. Though supported by many studies, this hypothesis surfers the pitfall of inefficiency for information encoding. To overcome difficulties the modularity representation hypothesis faced, researchers have proposed that information may be distributed represented in a specific brain area. The distributed representation hypothesis along with the multi-variate pattern approaches have made great success in detecting representation patterns in the previous decade. However, this hypothesis implicitly requires that the pattern should be transformed in a consistent way with respect to all of the represented information in the specific brain area. And the accuracy and validity of the prediction have never been thoroughly tested. Here in the present study, we tested this prediction in two open datasets compiling the object recognition. We validated the distributed representation patterns in the lateral occipital complex/ventral temporal gyrus where all six classifiers were capable of predicting the correct category represented. Furthermore, we correlated the classifiers' decision function values to the bold signals and found that the decision function value of the logistic regression classifier was exclusively correlated with activities of the same brain area in both datasets. These results support the distributed representation hypothesis and suggest that our neural system may be embedded within the algorithm of a specific classifier.
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100
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Peel HJ, Chouinard PA. fMRI form adaptation and size repetition enhancement in different subdivisions of the lateral occipital complex. Cortex 2022; 154:135-148. [DOI: 10.1016/j.cortex.2022.04.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 04/20/2022] [Accepted: 04/29/2022] [Indexed: 11/25/2022]
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