Bridging the Gap between Basic and Clinical Neuroscience: How Behavioral, Molecular and Computational Research Can Promote Care of Mental and Neurological Disorders

A special issue of Psychiatry International (ISSN 2673-5318).

Deadline for manuscript submissions: closed (31 August 2023) | Viewed by 4000

Special Issue Editors


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Guest Editor
Department of Neurology, Universitätsmedizin Greifswald, 17475 Greifswald, Germany
Interests: EEG; neuroimmunology and immunological psychiatry; neuroscience of language and cognition

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Guest Editor
1. Department of Computing, Goldsmiths, University of London, London SE14 6NW, UK
2. Brain Language Laboratory, Department of Philosophy and Humanities, Freie Universität Berlin, 14195 Berlin, Germany
Interests: intersection of computational and cognitive neuroscience; implementation of biologically realistic neural-network models closely mimicking structure; connectivity; physiology of the human cortex

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Guest Editor
Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
Interests: clinical psychology and psychotherapy; speech-language therapy; music in psychotherapy and speech-language therapy; treatment of post-stroke depression in individuals with aphasia; neuroscience of verbal communication

Special Issue Information

Dear Colleagues,

The etiology of mental and neurological disorders including, for instance, syndromes from the affective or schizophrenic spectra, dementias, movement disturbances, and inflammatory diseases of the CNS remains largely unknown in spite of decades of progress in behavioral, genetic, biochemical, immunological, and computational research. Ultra-specialization within these various subfields of neuroscience has created remarkable knowledge and skills but also increasingly challenged multidisciplinary integration. Even when causality seems to be evident, such as in post-stroke aphasia, the neurocognitive mechanisms of recovery and rehabilitation strategies often remain controversial among experts. At the same time, pioneering technologies such as computational modeling have found widespread use in the treatment of mental and neurological disorders. The present Special Issue seeks to channel innovative advances at the intersection between established fields of neuroscience into actual or potential applications that attempt to improve patient care in clinical practice.

 

Topics for such a multidisciplinary forum include, but are not limited to:

  • Clinical applications of neuroimaging techniques, including EEG, ECoG, fMRI, NIRS, and non-invasive brain stimulation.
  • The role of infections and immunity in psychiatric and neurological disorders; immunity–cognition interactions.
  • Brain-constrained computational models of cognitive and behavioral dysfunction, including language disorders, neurodegenerative diseases, and dementias.
  • The role of neurocomputational methods for the diagnosis and treatment of cognitive and behavioral syndromes.
  • The combination of psychotherapy and neurobiological or neurocomputational approaches.
  • Critical discussion of neuroscientific evidence in terms of its conclusiveness as proof of clinical efficacy.

Dr. Guglielmo Lucchese
Dr. Max Garagnani
Dr. Benjamin Stahl
Guest Editors

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Keywords

  • neuroimmunology and immunological psychiatry
  • neuroimaging
  • computational modeling
  • psychiatry

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Published Papers (1 paper)

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Research

25 pages, 415 KiB  
Article
Cautionary Observations Concerning the Introduction of Psychophysiological Biomarkers into Neuropsychiatric Practice
by Paul E. Rapp, Christopher Cellucci, David Darmon and David Keyser
Psychiatry Int. 2022, 3(2), 181-205; https://doi.org/10.3390/psychiatryint3020015 - 25 May 2022
Viewed by 2380
Abstract
The combination of statistical learning technologies with large databases of psychophysiological data has appropriately generated enthusiastic interest in future clinical applicability. It is argued here that this enthusiasm should be tempered with the understanding that significant obstacles must be overcome before the systematic [...] Read more.
The combination of statistical learning technologies with large databases of psychophysiological data has appropriately generated enthusiastic interest in future clinical applicability. It is argued here that this enthusiasm should be tempered with the understanding that significant obstacles must be overcome before the systematic introduction of psychophysiological measures into neuropsychiatric practice becomes possible. The objective of this study is to identify challenges to this effort. The nonspecificity of psychophysiological measures complicates their use in diagnosis. Low test-retest reliability complicates use in longitudinal assessment, and quantitative psychophysiological measures can normalize in response to placebo intervention. Ten cautionary observations are introduced and, in some instances, possible directions for remediation are suggested. Full article
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