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Zaccarella E, Papitto G, Friederici AD. Language and action in Broca's area: Computational differentiation and cortical segregation. Brain Cogn 2020; 147:105651. [PMID: 33254030 DOI: 10.1016/j.bandc.2020.105651] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Revised: 10/21/2020] [Accepted: 10/23/2020] [Indexed: 10/22/2022]
Abstract
Actions have been proposed to follow hierarchical principles similar to those hypothesized for language syntax. These structural similarities are claimed to be reflected in the common involvement of certain neural populations of Broca's area, in the Inferior Frontal Gyrus (IFG). In this position paper, we follow an influential hypothesis in linguistic theory to introduce the syntactic operation Merge and the corresponding motor/conceptual interfaces. We argue that actions hierarchies do not follow the same principles ruling language syntax. We propose that hierarchy in the action domain lies in predictive processing mechanisms mapping sensory inputs and statistical regularities of action-goal relationships. At the cortical level, distinct Broca's subregions appear to support different types of computations across the two domains. We argue that anterior BA44 is a major hub for the implementation of the syntactic operation Merge. On the other hand, posterior BA44 is recruited in selecting premotor mental representations based on the information provided by contextual signals. This functional distinction is corroborated by a recent meta-analysis (Papitto, Friederici, & Zaccarella, 2020). We conclude by suggesting that action and language can meet only where the interfaces transfer abstract computations either to the external world or to the internal mental world.
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Affiliation(s)
- Emiliano Zaccarella
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany.
| | - Giorgio Papitto
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany; International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Leipzig, Germany
| | - Angela D Friederici
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany
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Saeed U, Lang AE, Masellis M. Neuroimaging Advances in Parkinson's Disease and Atypical Parkinsonian Syndromes. Front Neurol 2020; 11:572976. [PMID: 33178113 PMCID: PMC7593544 DOI: 10.3389/fneur.2020.572976] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 09/02/2020] [Indexed: 12/11/2022] Open
Abstract
Parkinson's disease (PD) and atypical Parkinsonian syndromes are progressive heterogeneous neurodegenerative diseases that share clinical characteristic of parkinsonism as a common feature, but are considered distinct clinicopathological disorders. Based on the predominant protein aggregates observed within the brain, these disorders are categorized as, (1) α-synucleinopathies, which include PD and other Lewy body spectrum disorders as well as multiple system atrophy, and (2) tauopathies, which comprise progressive supranuclear palsy and corticobasal degeneration. Although, great strides have been made in neurodegenerative disease research since the first medical description of PD in 1817 by James Parkinson, these disorders remain a major diagnostic and treatment challenge. A valid diagnosis at early disease stages is of paramount importance, as it can help accommodate differential prognostic and disease management approaches, enable the elucidation of reliable clinicopathological relationships ideally at prodromal stages, as well as facilitate the evaluation of novel therapeutics in clinical trials. However, the pursuit for early diagnosis in PD and atypical Parkinsonian syndromes is hindered by substantial clinical and pathological heterogeneity, which can influence disease presentation and progression. Therefore, reliable neuroimaging biomarkers are required in order to enhance diagnostic certainty and ensure more informed diagnostic decisions. In this article, an updated presentation of well-established and emerging neuroimaging biomarkers are reviewed from the following modalities: (1) structural magnetic resonance imaging (MRI), (2) diffusion-weighted and diffusion tensor MRI, (3) resting-state and task-based functional MRI, (4) proton magnetic resonance spectroscopy, (5) transcranial B-mode sonography for measuring substantia nigra and lentiform nucleus echogenicity, (6) single photon emission computed tomography for assessing the dopaminergic system and cerebral perfusion, and (7) positron emission tomography for quantifying nigrostriatal functions, glucose metabolism, amyloid, tau and α-synuclein molecular imaging, as well as neuroinflammation. Multiple biomarkers obtained from different neuroimaging modalities can provide distinct yet corroborative information on the underlying neurodegenerative processes. This integrative "multimodal approach" may prove superior to single modality-based methods. Indeed, owing to the international, multi-centered, collaborative research initiatives as well as refinements in neuroimaging technology that are currently underway, the upcoming decades will mark a pivotal and exciting era of further advancements in this field of neuroscience.
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Affiliation(s)
- Usman Saeed
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Anthony E Lang
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Edmond J Safra Program in Parkinson's Disease and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Center, Toronto, ON, Canada.,Cognitive and Movement Disorders Clinic, Sunnybrook Health Sciences Center, Toronto, ON, Canada
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Papitto G, Friederici AD, Zaccarella E. The topographical organization of motor processing: An ALE meta-analysis on six action domains and the relevance of Broca's region. Neuroimage 2019; 206:116321. [PMID: 31678500 DOI: 10.1016/j.neuroimage.2019.116321] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 09/24/2019] [Accepted: 10/28/2019] [Indexed: 12/24/2022] Open
Abstract
Action is a cover term used to refer to a large set of motor processes differing in domain specificities (e.g. execution or observation). Here we review neuroimaging evidence on action processing (N = 416; Subjects = 5912) using quantitative Activation Likelihood Estimation (ALE) and Meta-Analytic Connectivity Modeling (MACM) approaches to delineate the functional specificities of six domains: (1) Action Execution, (2) Action Imitation, (3) Motor Imagery, (4) Action Observation, (5) Motor Learning, (6) Motor Preparation. Our results show distinct functional patterns for the different domains with convergence in posterior BA44 (pBA44) for execution, imitation and imagery processing. The functional connectivity network seeding in the motor-based localized cluster of pBA44 differs from the connectivity network seeding in the (language-related) anterior BA44. The two networks implement distinct cognitive functions. We propose that the motor-related network encompassing pBA44 is recruited when processing movements requiring a mental representation of the action itself.
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Affiliation(s)
- Giorgio Papitto
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Stephanstraße 1a, 04103, Leipzig, Germany; International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, Stephanstraße 1a, 04103, Leipzig, Germany.
| | - Angela D Friederici
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Stephanstraße 1a, 04103, Leipzig, Germany
| | - Emiliano Zaccarella
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Stephanstraße 1a, 04103, Leipzig, Germany
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Chiang FL, Wang Q, Yu FF, Romero RS, Huang SY, Fox PM, Tantiwongkosi B, Fox PT. Localised grey matter atrophy in multiple sclerosis is network-based: a coordinate-based meta-analysis. Clin Radiol 2019; 74:816.e19-816.e28. [PMID: 31421864 PMCID: PMC6757337 DOI: 10.1016/j.crad.2019.07.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 07/10/2019] [Indexed: 11/24/2022]
Abstract
AIM To test the network degeneration hypothesis in multiple sclerosis (MS) with a two-stage coordinate-based meta-analysis by: (1) characterising regional selectivity of grey matter (GM) atrophy and (2) testing for functional connectivity involving these regions. MATERIALS AND METHODS Meta-analytic sources included 33 journal articles (1,666 MS patients and 1,269 healthy controls) with coordinate-based results from voxel-based morphometry analysis demonstrating GM atrophy. Mass univariate and multivariate coordinate-based meta-analyses were performed to identify a convergent pattern of GM atrophy and determine inter-regional co-activation (as a surrogate of functional connectivity), with anatomical likelihood estimation and functional meta-analytic connectivity modelling, respectively. RESULTS Localised GM atrophy was demonstrated in the thalamus, putamen, caudate, sensorimotor cortex, insula, superior temporal gyrus, and cingulate gyrus. This convergent pattern of atrophy displayed significant inter-regional functional co-activations. CONCLUSION In MS, GM atrophy was regionally selective, and these regions were functionally connected. The meta-analytic model-based results of this study are intended to guide future development of quantitative neuroimaging markers for diagnosis, evaluating disease progression, and monitoring treatment response.
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Affiliation(s)
- F L Chiang
- Department of Radiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
| | - Q Wang
- Department of Neurology, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
| | - F F Yu
- Division of Neuroradiology, Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - R S Romero
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - S Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - P M Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - B Tantiwongkosi
- Department of Radiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - P T Fox
- Department of Radiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; South Texas Veterans Health Care System, San Antonio, TX, USA.
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