Lessons from COVID-19 in Clinical Neurology

Jin-Woo Park; Byung-Jo Kim

doi:10.3988/jcn.2022.18.1.1

Newton's Madness: Further Tales of Clinical Neurology

Contemporary Psychology ◽

10.1037/032361 ◽

1992 ◽

Vol 37 (7) ◽

pp. 689-690

Author(s):

Thomas E. Beniak

Keyword(s):

Clinical Neurology

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Review of A textbook of clinical neurology.

American Journal of Orthopsychiatry ◽

10.1037/h0099125 ◽

1940 ◽

Vol 10 (4) ◽

pp. 889-889

Author(s):

Lawson G. Lowrey

Keyword(s):

Clinical Neurology

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Theme Issue on Genetics and Genomics of Neuroscience and Clinical Neurology

Archives of Neurology ◽

10.1001/archneur.64.9.1235 ◽

2007 ◽

Vol 64 (9) ◽

pp. 1235

Keyword(s):

Clinical Neurology ◽

Theme Issue ◽

Genetics And Genomics

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The use of computerised tomography in mental handicap patients

Psychiatric Bulletin ◽

10.1192/pb.16.10.616 ◽

1992 ◽

Vol 16 (10) ◽

pp. 616-618

Author(s):

S. K. Lekh ◽

B. K. Puri ◽

I. Singh

Keyword(s):

Psychiatric Disorders ◽

Research Tool ◽

Clinical Neurology ◽

Computerised Tomography ◽

Chronic Schizophrenic ◽

Mental Handicap ◽

Schizophrenic Patients

Since its inception (Hounsfield, 1973), computerised tomography (CT) has become an invaluable diagnostic and research tool, particularly in clinical neurology and neurosurgery. Clinically, CT has proved useful in differentiating between ‘functional’ and ‘organic’ psychiatric disorders where it is particularly helpful in the diagnosis of potentially treatable organic disorders. For example, Owens et al (1980) found clinically unsuspected intracranial pathology in 12 of 136 chronic schizophrenic patients examined by CT and Roberts & Lishman (1984) found diagnosis, management, and/or prognosis were influenced in approximately 12% of cases referred by psychiatrists for CT imagining.

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Research on Emotion Recognition and Dementias: Foundations and Prospects

Journal of Alzheimer s Disease ◽

10.3233/jad-210096 ◽

2021 ◽

pp. 1-12

Author(s):

Gregorio González-Alcaide ◽

Mercedes Fernández-Ríos ◽

Rosa Redolat ◽

Emilia Serra

Keyword(s):

Emotion Recognition ◽

Neurological Disorders ◽

Web Of Science ◽

Research Area ◽

Scientific Output ◽

Autism Spectrum ◽

Intellectual Structure ◽

Clinical Neurology ◽

Spectrum Disorders ◽

Cognitive Areas

Background: The study of emotion recognition could be crucial for detecting alterations in certain cognitive areas or as an early sign of neurological disorders. Objective: The main objective of the study is to characterize research development on emotion recognition, identifying the intellectual structure that supports this area of knowledge, and the main lines of research attracting investigators’ interest. Methods: We identified publications on emotion recognition and dementia included in the Web of Science Core Collection, analyzing the scientific output and main disciplines involved in generating knowledge in the area. A co-citation analysis and an analysis of the bibliographic coupling between the retrieved documents elucidated the thematic orientations of the research and the reference works that constitute the foundation for development in the field. Results: A total of 345 documents, with 24,282 bibliographic references between them, were included. This is an emerging research area, attracting the interest of investigators in Neurosciences, Psychology, Clinical Neurology, and Psychiatry, among other disciplines. Four prominent topic areas were identified, linked to frontotemporal dementia, autism spectrum disorders, Alzheimer’s disease, and Parkinson’s and Huntington disease. Many recent papers focus on the detection of mild cognitive impairment. Conclusion: Impaired emotion recognition may be a key sign facilitating the diagnosis and early treatment of different neurodegenerative diseases as well as for triggering the necessary provision of social and family support, explaining the growing research interest in this area.

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