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Zhang T, Li T, Huang S, Zhang H, Xu X, Zheng H, Zhong Q, Gao Y, Wang T, Zhu Y, Liu H, Shen Y. Neural correlates of impaired learning and recognition of novel faces in mild cognitive impairment. Clin Neurophysiol 2024; 160:28-37. [PMID: 38368702 DOI: 10.1016/j.clinph.2024.02.005] [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: 09/04/2023] [Revised: 01/24/2024] [Accepted: 02/06/2024] [Indexed: 02/20/2024]
Abstract
OBJECTIVE Face memory impairment significantly affects social interactions and daily functioning in individuals with mild cognitive impairment (MCI). While deficits in recognizing familiar faces among individuals with MCI have been reported, their ability to learn and recognize unfamiliar faces remains unclear. This study examined the behavioral performance and event-related potentials (ERPs) of unfamiliar face memorization and recognition in MCI. METHODS Fifteen individuals with MCI and 15 healthy controls learned and recognized 90 unfamiliar neutral faces. Their performance accuracy and cortical ERPs were compared between the two groups across the learning and recognition phases. RESULTS Individuals with MCI had lower accuracy in identifying newly learned faces than healthy controls. Moreover, individuals with MCI had reduced occipitotemporal N170 and central vertex positive potential responses during both the learning and recognition phases, suggesting impaired initial face processing and attentional resources allocation. Also, individuals with MCI had reduced central N200 and frontal P300 responses during the recognition phase, suggesting impaired later-stage face recognition and attention engagement. CONCLUSION These findings provide neurobehavioral evidence for impaired learning and recognition of unfamiliar faces in individuals with MCI. SIGNIFICANCE Individuals with MCI may have face memory deficits in both early-stage face processing and later-stage recognition .
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Affiliation(s)
- Tianjiao Zhang
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Tingni Li
- Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Hong Kong SAR 999077, China
| | - Sisi Huang
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hangbin Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China; Department of Psychology, Brain Imaging and TMS Laboratory, University of Arizona, Tucson, AZ 85721, USA
| | - Xingjun Xu
- Department of Rehabilitation, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing 400038, China
| | - Hui Zheng
- Shanghai Key Laboratory of Psychotic Disorders, Brain Health Institute, National Center for Mental Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Qian Zhong
- Brain Imaging and TMS Laboratory, Department of Psychology, University of Arizona, Tucson, AZ, 85721, USA
| | - Yaxin Gao
- Rehabilitation Center, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou 215002, China
| | - Tong Wang
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Yi Zhu
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
| | - Hanjun Liu
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510080, China; Guangdong Provincial Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou 510080, China.
| | - Ying Shen
- Rehabilitation Medicine Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
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2
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Almeida VN. Somatostatin and the pathophysiology of Alzheimer's disease. Ageing Res Rev 2024; 96:102270. [PMID: 38484981 DOI: 10.1016/j.arr.2024.102270] [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: 07/18/2023] [Revised: 03/09/2024] [Accepted: 03/09/2024] [Indexed: 03/28/2024]
Abstract
Among the central features of Alzheimer's disease (AD) progression are altered levels of the neuropeptide somatostatin (SST), and the colocalisation of SST-positive interneurons (SST-INs) with amyloid-β plaques, leading to cell death. In this theoretical review, I propose a molecular model for the pathogenesis of AD based on SST-IN hypofunction and hyperactivity. Namely, hypofunctional and hyperactive SST-INs struggle to control hyperactivity in medial regions in early stages, leading to axonal Aβ production through excessive presynaptic GABAB inhibition, GABAB1a/APP complex downregulation and internalisation. Concomitantly, excessive SST-14 release accumulates near SST-INs in the form of amyloids, which bind to Aβ to form toxic mixed oligomers. This leads to differential SST-IN death through excitotoxicity, further disinhibition, SST deficits, and increased Aβ release, fibrillation and plaque formation. Aβ plaques, hyperactive networks and SST-IN distributions thereby tightly overlap in the brain. Conversely, chronic stimulation of postsynaptic SST2/4 on gulutamatergic neurons by hyperactive SST-INs promotes intense Mitogen-Activated Protein Kinase (MAPK) p38 activity, leading to somatodendritic p-tau staining and apoptosis/neurodegeneration - in agreement with a near complete overlap between p38 and neurofibrillary tangles. This model is suitable to explain some of the principal risk factors and markers of AD progression, including mitochondrial dysfunction, APOE4 genotype, sex-dependent vulnerability, overactive glial cells, dystrophic neurites, synaptic/spine losses, inter alia. Finally, the model can also shed light on qualitative aspects of AD neuropsychology, especially within the domains of spatial and declarative (episodic, semantic) memory, under an overlying pattern of contextual indiscrimination, ensemble instability, interference and generalisation.
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Affiliation(s)
- Victor N Almeida
- Institute of Psychiatry, Faculty of Medicine, University of São Paulo (USP), Brazil; Faculty of Languages, Federal University of Minas Gerais (UFMG), Brazil.
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3
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Laurence S, Baker KA, Proietti VM, Mondloch CJ. What happens to our representation of identity as familiar faces age? Evidence from priming and identity aftereffects. Br J Psychol 2022; 113:677-695. [PMID: 35277854 PMCID: PMC9544931 DOI: 10.1111/bjop.12560] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 02/07/2022] [Indexed: 11/28/2022]
Abstract
Matching identity in images of unfamiliar faces is error prone, but we can easily recognize highly variable images of familiar faces – even images taken decades apart. Recent theoretical development based on computational modelling can account for how we recognize extremely variable instances of the same identity. We provide complementary behavioural data by examining older adults’ representation of older celebrities who were also famous when young. In Experiment 1, participants completed a long‐lag repetition priming task in which primes and test stimuli were the same age or different ages. In Experiment 2, participants completed an identity after effects task in which the adapting stimulus was an older or young photograph of one celebrity and the test stimulus was a morph between the adapting identity and a different celebrity; the adapting stimulus was the same age as the test stimulus on some trials (e.g., both old) or a different age (e.g., adapter young, test stimulus old). The magnitude of priming and identity after effects were not influenced by whether the prime and adapting stimulus were the same age or different age as the test face. Collectively, our findings suggest that humans have one common mental representation for a familiar face (e.g., Paul McCartney) that incorporates visual changes across decades, rather than multiple age‐specific representations. These findings make novel predictions for state‐of‐the‐art algorithms (e.g., Deep Convolutional Neural Networks).
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Affiliation(s)
- Sarah Laurence
- School of Psychology & Counselling Open University Milton Keynes UK
| | - Kristen A. Baker
- Department of Psychology Brock University Canada University St. Catharines Ontario Canada
| | | | - Catherine J. Mondloch
- Department of Psychology Brock University Canada University St. Catharines Ontario Canada
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4
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Arzy S, Kaplan R. Transforming Social Perspectives with Cognitive Maps. Soc Cogn Affect Neurosci 2022; 17:939-955. [PMID: 35257155 PMCID: PMC9527473 DOI: 10.1093/scan/nsac017] [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: 08/30/2021] [Revised: 12/17/2021] [Accepted: 03/07/2022] [Indexed: 01/29/2023] Open
Abstract
Growing evidence suggests that cognitive maps represent relations between social knowledge similar to how spatial locations are represented in an environment. Notably, the extant human medial temporal lobe literature assumes associations between social stimuli follow a linear associative mapping from an egocentric viewpoint to a cognitive map. Yet, this form of associative social memory doesn't account for a core phenomenon of social interactions in which social knowledge learned via comparisons to the self, other individuals, or social networks are assimilated within a single frame of reference. We argue that hippocampal-entorhinal coordinate transformations, known to integrate egocentric and allocentric spatial cues, inform social perspective switching between the self and others. We present evidence that the hippocampal formation helps inform social interactions by relating self versus other social attribute comparisons to society in general, which can afford rapid and flexible assimilation of knowledge about the relationship between the self and social networks of varying proximities. We conclude by discussing the ramifications of cognitive maps in aiding this social perspective transformation process in states of health and disease.
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Affiliation(s)
- Shahar Arzy
- Faculty of Medicine and the Department of Cognitive Sciences, Hebrew University of Jerusalem, Jerusalem 91120, Israel
- Department of Neurology, Hadassah Hebrew University Medical School, Jerusalem 91120, Israel
| | - Raphael Kaplan
- Correspondence should be addressed to Raphael Kaplan, Department of Basic Psychology, Clinical Psychology, and Psychobiology, Universitat Jaume I, Avinguda de Vicent Sos Baynat, Castelló de la Plana, Spain. E-mail:
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5
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Hsu CH, Wu YN. Application of Empirical Mode Decomposition for Decoding Perception of Faces Using Magnetoencephalography. SENSORS 2021; 21:s21186235. [PMID: 34577441 PMCID: PMC8472346 DOI: 10.3390/s21186235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/14/2021] [Accepted: 09/14/2021] [Indexed: 11/16/2022]
Abstract
Neural decoding is useful to explore the timing and source location in which the brain encodes information. Higher classification accuracy means that an analysis is more likely to succeed in extracting useful information from noises. In this paper, we present the application of a nonlinear, nonstationary signal decomposition technique—the empirical mode decomposition (EMD), on MEG data. We discuss the fundamental concepts and importance of nonlinear methods when it comes to analyzing brainwave signals and demonstrate the procedure on a set of open-source MEG facial recognition task dataset. The improved clarity of data allowed further decoding analysis to capture distinguishing features between conditions that were formerly over-looked in the existing literature, while raising interesting questions concerning hemispheric dominance to the encoding process of facial and identity information.
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6
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Abstract
While the desire to uncover the neural correlates of consciousness has taken numerous directions, self-face recognition has been a constant in attempts to isolate aspects of self-awareness. The neuroimaging revolution of the 1990s brought about systematic attempts to isolate the underlying neural basis of self-face recognition. These studies, including some of the first fMRI (functional magnetic resonance imaging) examinations, revealed a right-hemisphere bias for self-face recognition in a diverse set of regions including the insula, the dorsal frontal lobe, the temporal parietal junction, and the medial temporal cortex. In this systematic review, we provide confirmation of these data (which are correlational) which were provided by TMS (transcranial magnetic stimulation) and patients in which direct inhibition or ablation of right-hemisphere regions leads to a disruption or absence of self-face recognition. These data are consistent with a number of theories including a right-hemisphere dominance for self-awareness and/or a right-hemisphere specialization for identifying significant social relationships, including to oneself.
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7
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Wei PH, Chen H, Ye Q, Zhao H, Xu Y, Bai F. Self-reference Network-Related Interactions During the Process of Cognitive Impairment in the Early Stages of Alzheimer's Disease. Front Aging Neurosci 2021; 13:666437. [PMID: 33841130 PMCID: PMC8024683 DOI: 10.3389/fnagi.2021.666437] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Accepted: 03/08/2021] [Indexed: 12/18/2022] Open
Abstract
Background: Normal establishment of cognition occurs after forming a sensation to stimuli from internal or external cues, in which self-reference processing may be partially involved. However, self-reference processing has been less studied in the Alzheimer’s disease (AD) field within the self-reference network (SRN) and has instead been investigated within the default-mode network (DMN). Differences between these networks have been proven in the last decade, while ultra-early diagnoses have increased. Therefore, investigation of the altered pattern of SRN is significantly important, especially in the early stages of AD. Methods: A total of 65 individuals, including 43 with mild cognitive impairment (MCI) and 22 cognitively normal individuals, participated in this study. The SRN, dorsal attention network (DAN), and salience network (SN) were constructed with resting-state functional magnetic resonance imaging (fMRI), and voxel-based analysis of variance (ANOVA) was used to explore significant regions of network interactions. Finally, the correlation between the network interactions and clinical characteristics was analyzed. Results: We discovered four interactions among the three networks, with the SRN showing different distributions in the left and right hemispheres from the DAN and SN and modulated interactions between them. Group differences in the interactions that were impaired in MCI patients indicated that the degree of damage was most severe in the SRN, least severe in the SN, and intermediate in the DAN. The two SRN-related interactions showed positive effects on the executive and memory performances of MCI patients with no overlap with the clinical assessments performed in this study. Conclusion: This study is the first and primary evidence of SRN interactions related to MCI patients’ functional performance. The influence of the SRN in the ultra-early stages of AD is nonnegligible. There are still many unknowns regarding the contribution of the SRN in AD progression, and we strongly recommend future research in this area.
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Affiliation(s)
- Ping-Hsuan Wei
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
| | - Haifeng Chen
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Qing Ye
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Hui Zhao
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Yun Xu
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- Department of Neurology, Affiliated Drum Tower Hospital of Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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8
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Gilson M, Zamora-López G, Pallarés V, Adhikari MH, Senden M, Campo AT, Mantini D, Corbetta M, Deco G, Insabato A. Model-based whole-brain effective connectivity to study distributed cognition in health and disease. Netw Neurosci 2020; 4:338-373. [PMID: 32537531 PMCID: PMC7286310 DOI: 10.1162/netn_a_00117] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Accepted: 12/02/2019] [Indexed: 12/12/2022] Open
Abstract
Neuroimaging techniques are now widely used to study human cognition. The functional associations between brain areas have become a standard proxy to describe how cognitive processes are distributed across the brain network. Among the many analysis tools available, dynamic models of brain activity have been developed to overcome the limitations of original connectivity measures such as functional connectivity. This goes in line with the many efforts devoted to the assessment of directional interactions between brain areas from the observed neuroimaging activity. This opinion article provides an overview of our model-based whole-brain effective connectivity to analyze fMRI data, while discussing the pros and cons of our approach with respect to other established approaches. Our framework relies on the multivariate Ornstein-Uhlenbeck (MOU) process and is thus referred to as MOU-EC. Once tuned, the model provides a directed connectivity estimate that reflects the dynamical state of BOLD activity, which can be used to explore cognition. We illustrate this approach using two applications on task-evoked fMRI data. First, as a connectivity measure, MOU-EC can be used to extract biomarkers for task-specific brain coordination, understood as the patterns of areas exchanging information. The multivariate nature of connectivity measures raises several challenges for whole-brain analysis, for which machine-learning tools present some advantages over statistical testing. Second, we show how to interpret changes in MOU-EC connections in a collective and model-based manner, bridging with network analysis. Our framework provides a comprehensive set of tools that open exciting perspectives to study distributed cognition, as well as neuropathologies.
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Affiliation(s)
- Matthieu Gilson
- Center for Brain and Cognition and Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Gorka Zamora-López
- Center for Brain and Cognition and Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Vicente Pallarés
- Center for Brain and Cognition and Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Mohit H. Adhikari
- Center for Brain and Cognition and Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Mario Senden
- Department of Cognitive Neuroscience, University of Maastricht, Maastricht, The Netherlands
| | | | - Dante Mantini
- Neuroplasticity and Motor Control Research Group, KU Leuven, Leuven, Belgium
- Brain Imaging and Neural Dynamics Research Group, IRCCS San Camillo Hospital, Venice, Italy
| | - Maurizio Corbetta
- Department of Neuroscience, Venetian Institute of Molecular Medicine (VIMM) and Padova Neuroscience Center (PNC), University of Padua, Italy
- Department of Neurology, Radiology, and Neuroscience, Washington University School of Medicine, St. Louis, MO, USA
| | - Gustavo Deco
- Center for Brain and Cognition and Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Andrea Insabato
- Institut de Neurosciences de la Timone, CNRS, Marseille, France
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9
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Antoine N, Bahri MA, Bastin C, Collette F, Phillips C, Balteau E, Genon S, Salmon E. Anosognosia and default mode subnetwork dysfunction in Alzheimer's disease. Hum Brain Mapp 2019; 40:5330-5340. [PMID: 31444942 PMCID: PMC6864891 DOI: 10.1002/hbm.24775] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2019] [Revised: 08/07/2019] [Accepted: 08/08/2019] [Indexed: 12/12/2022] Open
Abstract
Research on the neural correlates of anosognosia in Alzheimer's disease varied according to methods and objectives: they compared different measures, used diverse neuroimaging modalities, explored connectivity between brain networks, addressed the role of specific brain regions or tried to give support to theoretical models of unawareness. We used resting‐state fMRI connectivity with two different seed regions and two measures of anosognosia in different patient samples to investigate consistent modifications of default mode subnetworks and we aligned the results with the Cognitive Awareness Model. In a first study, patients and their relatives were presented with the Memory Awareness Rating Scale. Anosognosia was measured as a patient‐relative discrepancy score and connectivity was investigated with a parahippocampal seed. In a second study, anosognosia was measured in patients with brain amyloid (taken as a disease biomarker) by comparing self‐reported rating with memory performance, and connectivity was examined with a hippocampal seed. In both studies, anosognosia was consistently related to disconnection within the medial temporal subsystem of the default mode network, subserving episodic memory processes. Importantly, scores were also related to disconnection between the medial temporal and both the core subsystem (participating to self‐reflection) and the dorsomedial subsystem of the default mode network (the middle temporal gyrus that might subserve a personal database in the second study). We suggest that disparity in connectivity within and between subsystems of the default mode network may reflect impaired functioning of pathways in cognitive models of awareness.
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Affiliation(s)
- Nicolas Antoine
- Memory Clinic, Department of Neurology, CHU of Liège, Liège, Belgium.,GIGA-Cyclotron Research Centre-IVI, University of Liège, Liège, Belgium
| | - Mohamed A Bahri
- GIGA-Cyclotron Research Centre-IVI, University of Liège, Liège, Belgium
| | - Christine Bastin
- GIGA-Cyclotron Research Centre-IVI, University of Liège, Liège, Belgium.,Psychology and Neuroscience of Cognition, University of Liège, Liège, Belgium
| | - Fabienne Collette
- GIGA-Cyclotron Research Centre-IVI, University of Liège, Liège, Belgium.,Psychology and Neuroscience of Cognition, University of Liège, Liège, Belgium
| | | | - Evelyne Balteau
- GIGA-Cyclotron Research Centre-IVI, University of Liège, Liège, Belgium
| | - Sarah Genon
- GIGA-Cyclotron Research Centre-IVI, University of Liège, Liège, Belgium.,Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Eric Salmon
- Memory Clinic, Department of Neurology, CHU of Liège, Liège, Belgium.,GIGA-Cyclotron Research Centre-IVI, University of Liège, Liège, Belgium.,Psychology and Neuroscience of Cognition, University of Liège, Liège, Belgium
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10
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Funayama M, Nakagawa Y, Nakajima A, Takata T, Mimura Y, Mimura M. Dementia trajectory for patients with logopenic variant primary progressive aphasia. Neurol Sci 2019; 40:2573-2579. [DOI: 10.1007/s10072-019-04013-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 07/16/2019] [Indexed: 11/24/2022]
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11
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Extracting orthogonal subject- and condition-specific signatures from fMRI data using whole-brain effective connectivity. Neuroimage 2018; 178:238-254. [PMID: 29753842 PMCID: PMC6057306 DOI: 10.1016/j.neuroimage.2018.04.070] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2018] [Revised: 04/16/2018] [Accepted: 04/30/2018] [Indexed: 12/19/2022] Open
Abstract
The study of brain communication based on fMRI data is often limited because such measurements are a mixture of session-to-session variability with subject- and condition-related information. Disentangling these contributions is crucial for real-life applications, in particular when only a few recording sessions are available. The present study aims to define a reliable standard for the extraction of multiple signatures from fMRI data, while verifying that they do not mix information about the different modalities (e.g., subjects and conditions such as tasks performed by them). In particular, condition-specific signatures should not be contaminated by subject-related information, since they aim to generalize over subjects. Practically, signatures correspond to subnetworks of directed interactions between brain regions (typically 100 covering the whole brain) supporting the subject and condition identification for single fMRI sessions. The key for robust prediction is using effective connectivity instead of functional connectivity. Our method demonstrates excellent generalization capabilities for subject identification in two datasets, using only a few sessions per subject as reference. Using another dataset with resting state and movie viewing, we show that the two signatures related to subjects and tasks correspond to distinct subnetworks, which are thus topologically orthogonal. Our results set solid foundations for applications tailored to individual subjects, such as clinical diagnostic.
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12
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Doi H, Shinohara K. Attention allocation towards own face is pronounced during middle adolescence: an eye-tracking study. Dev Sci 2016; 21. [PMID: 27873384 DOI: 10.1111/desc.12490] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2015] [Accepted: 07/18/2016] [Indexed: 11/28/2022]
Abstract
Increased interest in the self has long been deemed to be one of the most peculiar characteristics of adolescence. On the basis of this, we conjectured that attentiveness towards self-relevant information, especially one's own face, becomes more pronounced during the middle adolescence. The present study tested this hypothesis by comparing the pattern of visuospatial attention allocation to their own face among early, middle and late adolescent males using an eye-tracking methodology. The results have shown a clear pattern of increased attention allocation towards their own face over a close friend's and a stranger's face in middle adolescents, but fixation durations on their own and a friend's face did not differ from each other in early and late adolescents. In addition, middle adolescents showed higher public self-consciousness and a lower level of self-esteem than early and late adolescents, respectively. These results indicate that attention allocation towards one's own face is more pronounced during middle adolescence, and is associated with increased interest in their own attributes.
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Affiliation(s)
- Hirokazu Doi
- Graduate School of Biomedical Sciences, Nagasaki University, Japan
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13
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Turner MP, Hubbard NA, Himes LM, Faghihahmadabadi S, Hutchison JL, Bennett IJ, Motes MA, Haley RW, Rypma B. Cognitive Slowing in Gulf War Illness Predicts Executive Network Hyperconnectivity: Study in a Population-Representative Sample. Neuroimage Clin 2016; 12:535-541. [PMID: 27672557 PMCID: PMC5030369 DOI: 10.1016/j.nicl.2016.08.022] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2015] [Revised: 06/06/2016] [Accepted: 08/24/2016] [Indexed: 12/30/2022]
Abstract
Cognitive slowing is a prevalent symptom observed in Gulf War Illness (GWI). The present study assessed the extent to which functional connectivity between dorsolateral prefrontal cortex (DLPFC) and other task-relevant brain regions was predictive of GWI-related cognitive slowing. GWI patients (n = 54) and healthy veteran controls (n = 29) were assessed on performance of a processing speed task (the Digit Symbol Substitution Task; DSST) while undergoing functional magnetic resonance imaging (fMRI). GWI patients were slower on the DSST relative to controls. Bilateral DLPFC connectivity with task-relevant nodes was altered in GWI patients compared to healthy controls during DSST performance. Moreover, hyperconnectivity in these networks predicted GWI-related increases in reaction time on the DSST, whereas hypoconnectivity did not. These results suggest that GWI-related cognitive slowing reflects reduced efficiency in cortical networks.
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Affiliation(s)
- Monroe P. Turner
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA
| | - Nicholas A. Hubbard
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA
| | - Lyndahl M. Himes
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA
| | | | - Joanna L. Hutchison
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ilana J. Bennett
- Center for the Neurobiology of Learning and Memory, University of California-Irvine, Irvine, CA, USA
| | - Michael A. Motes
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA
| | - Robert W. Haley
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Bart Rypma
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
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14
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Lavallée MM, Gandini D, Rouleau I, Vallet GT, Joannette M, Kergoat MJ, Busigny T, Rossion B, Joubert S. A Qualitative Impairment in Face Perception in Alzheimer’s Disease: Evidence from a Reduced Face Inversion Effect. J Alzheimers Dis 2016; 51:1225-36. [DOI: 10.3233/jad-151027] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Marie Maxime Lavallée
- Département de psychologie, Université de Montréal, Montréal, Canada
- Centre de recherche Institut universitaire de gériatrie de Montréal (CRIUGM), Montréal, Canada
| | - Delphine Gandini
- Département de psychologie, Université de Montréal, Montréal, Canada
- Centre de recherche Institut universitaire de gériatrie de Montréal (CRIUGM), Montréal, Canada
| | - Isabelle Rouleau
- Département de psychologie, Université du Québec à Montréal, Montréal, Canada
- Centre de recherche du Centre hospitalier universitaire de Montréal (CHUM), Montréal, Canada
| | - Guillaume T. Vallet
- Département de psychologie, Université de Montréal, Montréal, Canada
- Centre de recherche Institut universitaire de gériatrie de Montréal (CRIUGM), Montréal, Canada
| | - Maude Joannette
- Département de psychologie, Université de Montréal, Montréal, Canada
- Centre de recherche Institut universitaire de gériatrie de Montréal (CRIUGM), Montréal, Canada
| | - Marie-Jeanne Kergoat
- Département de médecine, Université de Montréal, Montréal, Canada
- Clinique de cognition, Institut universitaire de gériatrie de Montréal, Montréal, Canada
| | - Thomas Busigny
- CHU Purpan, Toulouse, France
- Institut de Recherche en Sciences Psychologique et institut de Neuroscience, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Bruno Rossion
- Institut de Recherche en Sciences Psychologique et institut de Neuroscience, Université Catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Sven Joubert
- Département de psychologie, Université de Montréal, Montréal, Canada
- Centre de recherche Institut universitaire de gériatrie de Montréal (CRIUGM), Montréal, Canada
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