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Chakrabarty M, Klooster N, Biswas A, Chatterjee A. The scope of using pragmatic language tests for early detection of dementia: A systematic review of investigations using figurative language. Alzheimers Dement 2023; 19:4705-4728. [PMID: 37534671 DOI: 10.1002/alz.13369] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 06/02/2023] [Accepted: 06/02/2023] [Indexed: 08/04/2023]
Abstract
INTRODUCTION Dementia cases are expected to rise to 81.1 million in 2040. Efforts are underway to develop diagnostic methods to facilitate early detection of the disease. Herein we review research findings focusing on pragmatic dysfunction in patients with dementia and evaluate the usefulness of assessing dementia and its progress with a battery of tests assessing figurative language skills. METHODS A total of 74,778 article titles were identified from EMBASE, PubMed, and Google Scholar databases. After systematic screening, 51 journal articles were selected for the final review. RESULT The review suggests that impaired figurative language might be a marker for early cognitive decline. Different forms of figurative language may be impaired at different stages of the disease and in different types of dementia involving different neuropathologies. CONCLUSION The use of pragmatic tests in combination with the existing diagnostic protocols might increase the probability of early diagnosis. HIGHLIGHTS Pragmatic impairment could be a marker of early cognitive impairment. Figurative language-an important pragmatic aspect-is disrupted in mild cognitive impairment (MCI) and early Alzheimer's disease (AD). Figurative language impairment might precede literal language impairment. Pragmatic tests could be more sensitive than standard neuropsychological tests. Inclusion of pragmatic tests in diagnostic guidelines might bolster early detection.
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Affiliation(s)
- Madhushree Chakrabarty
- Department of Neurology, Institute of Post Graduate Medical Education & Research and Bangur Institute of Neurosciences, Kolkata, West Bengal, India
| | - Nathaniel Klooster
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Moss Rehabilitation Research Institute, Elkins Park, Pennsylvania, USA
- Hope College, Holland, Michigan, USA
| | - Atanu Biswas
- Department of Neurology, Institute of Post Graduate Medical Education & Research and Bangur Institute of Neurosciences, Kolkata, West Bengal, India
| | - Anjan Chatterjee
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Moss Rehabilitation Research Institute, Elkins Park, Pennsylvania, USA
- Penn Center for Neuroaesthetics, University of Pennsylvania, Goddard Laboratories, Philadelphia, Pennsylvania, USA
- Penn Memory Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Hauptman M, Blank I, Fedorenko E. Non-literal language processing is jointly supported by the language and theory of mind networks: Evidence from a novel meta-analytic fMRI approach. Cortex 2023; 162:96-114. [PMID: 37023480 PMCID: PMC10210011 DOI: 10.1016/j.cortex.2023.01.013] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 11/08/2022] [Accepted: 01/11/2023] [Indexed: 03/12/2023]
Abstract
Going beyond the literal meaning of language is key to communicative success. However, the mechanisms that support non-literal inferences remain debated. Using a novel meta-analytic approach, we evaluate the contribution of linguistic, social-cognitive, and executive mechanisms to non-literal interpretation. We identified 74 fMRI experiments (n = 1,430 participants) from 2001 to 2021 that contrasted non-literal language comprehension with a literal control condition, spanning ten phenomena (e.g., metaphor, irony, indirect speech). Applying the activation likelihood estimation approach to the 825 activation peaks yielded six left-lateralized clusters. We then evaluated the locations of both the individual-study peaks and the clusters against probabilistic functional atlases (cf. anatomical locations, as is typically done) for three candidate brain networks-the language-selective network (Fedorenko, Behr, & Kanwisher, 2011), which supports language processing, the Theory of Mind (ToM) network (Saxe & Kanwisher, 2003), which supports social inferences, and the domain-general Multiple-Demand (MD) network (Duncan, 2010), which supports executive control. These atlases were created by overlaying individual activation maps of participants who performed robust and extensively validated 'localizer' tasks that selectively target each network in question (n = 806 for language; n = 198 for ToM; n = 691 for MD). We found that both the individual-study peaks and the ALE clusters fell primarily within the language network and the ToM network. These results suggest that non-literal processing is supported by both i) mechanisms that process literal linguistic meaning, and ii) mechanisms that support general social inference. They thus undermine a strong divide between literal and non-literal aspects of language and challenge the claim that non-literal processing requires additional executive resources.
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Affiliation(s)
- Miriam Hauptman
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA; Department of Psychological & Brain Sciences, Johns Hopkins University, Baltimore, MD 21218, USA.
| | - Idan Blank
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA; Department of Psychology, UCLA, Los Angeles, CA 90095, USA; Department of Linguistics, UCLA, Los Angeles, CA 90095, USA
| | - Evelina Fedorenko
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA; Program in Speech and Hearing in Bioscience and Technology, Harvard University, Boston, MA 02114, USA.
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Pisano F, Manfredini A, Brachi D, Landi L, Sorrentino L, Bottone M, Incoccia C, Marangolo P. How Has COVID-19 Impacted Our Language Use? INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:13836. [PMID: 36360715 PMCID: PMC9656816 DOI: 10.3390/ijerph192113836] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/02/2022] [Revised: 10/19/2022] [Accepted: 10/21/2022] [Indexed: 06/16/2023]
Abstract
The COVID-19 pandemic has led to severe consequences for people's mental health. The pandemic has also influenced our language use, shaping our word formation habits. The overuse of new metaphorical meanings has received particular attention from the media. Here, we wanted to investigate whether these metaphors have led to the formation of new semantic associations in memory. A sample of 120 university students was asked to decide whether a target word was or was not related to a prime stimulus. Responses for pandemic pairs in which the target referred to the newly acquired metaphorical meaning of the prime (i.e., "trench"-"hospital") were compared to pre-existing semantically related pairs (i.e., "trench"-"soldier") and neutral pairs (i.e., "trench"-"response"). Results revealed greater accuracy and faster response times for pandemic pairs than for semantic pairs and for semantic pairs compared to neutral ones. These findings suggest that the newly learned pandemic associations have created stronger semantic links in our memory compared to the pre-existing ones. Thus, this work confirms the adaptive nature of human language, and it underlines how the overuse of metaphors evoking dramatic images has been, in part, responsible for many psychological disorders still reported among people nowadays.
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Affiliation(s)
- Francesca Pisano
- Department of Humanities Studies, University Federico II, 80133 Naples, Italy
| | - Alessio Manfredini
- Department of Humanities Studies, University Federico II, 80133 Naples, Italy
| | - Daniela Brachi
- Department of Humanities Studies, University Federico II, 80133 Naples, Italy
| | - Luana Landi
- Department of Humanities Studies, University Federico II, 80133 Naples, Italy
| | - Lucia Sorrentino
- Department of Humanities Studies, University Federico II, 80133 Naples, Italy
| | - Marianna Bottone
- Department of Humanities Studies, University Federico II, 80133 Naples, Italy
| | | | - Paola Marangolo
- Department of Humanities Studies, University Federico II, 80133 Naples, Italy
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Klooster N, Humphries S, Cardillo E, Hartung F, Xie L, Das S, Yushkevich P, Pilania A, Wang J, Wolk DA, Chatterjee A. Sensitive Measures of Cognition in Mild Cognitive Impairment. J Alzheimers Dis 2021; 82:1123-1136. [PMID: 34151789 PMCID: PMC8822438 DOI: 10.3233/jad-201280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Sensitive measures of cognition are needed in preclinical and prodromal Alzheimer's disease (AD) to track cognitive change and evaluate potential interventions. Neurofibrillary tangle pathology in AD is first observed in Brodmann Area 35 (BA35), the medial portion of the perirhinal cortex. The importance of the perirhinal cortex for semantic memory may explain early impairments of semantics in preclinical AD. Additionally, our research has tied figurative language impairment to neurodegenerative disease. OBJECTIVE We aim to identify tasks that are sensitive to cognitive impairment in individuals with mild cognitive impairment (MCI), and that are sensitive to atrophy in BA35. METHODS Individuals with MCI and cognitively normal participants (CN) were tested on productive and receptive experimental measures of semantic memory and experimental tests of figurative language comprehension (including metaphor and verbal analogy). Performance was related to structural imaging and standard neuropsychological assessment. RESULTS On the experimental tests of semantics and figurative language, people with MCI performed worse than CN participants. The experimental semantic memory tasks are sensitive and specific; performance on the experimental semantic memory tasks related to medial temporal lobe structural integrity, including BA35, while standard neuropsychological assessments of semantic memory did not, demonstrating the sensitivity of these experimental measures. A visuo-spatial analogy task did not differentiate groups, confirming the specificity of semantic and figurative language tasks. CONCLUSION These experimental measures appear sensitive to cognitive change and neurodegeneration early in the AD trajectory and may prove useful in tracking cognitive change in clinical trials aimed at early intervention.
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Affiliation(s)
- Nathaniel Klooster
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
- Moss Rehabilitation Research Institute, Elkins Park, PA, USA
| | - Stacey Humphries
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Neuroaesthetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Eileen Cardillo
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Neuroaesthetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Franziska Hartung
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Neuroaesthetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Long Xie
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Sandhitsu Das
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA
| | - Paul Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA
| | - Arun Pilania
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Jieqiong Wang
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Anjan Chatterjee
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
- Moss Rehabilitation Research Institute, Elkins Park, PA, USA
- Penn Center for Neuroaesthetics, University of Pennsylvania, Philadelphia, PA, USA
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
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