Patterns of cortical interactivity supporting speech production and lexical retrieval: A graph signal processing approach at the individual level

2020 ◽  
Vol 56 ◽  
pp. 100936 ◽  
Author(s):  
S. Ries ◽  
S. Tavildar ◽  
R. Rohilla ◽  
C. Sperling ◽  
A. Ashrafi
Author(s):  
Leandro A. S. Moreira ◽  
Antonio L. L. Ramos ◽  
Marcello L. R. de Campos ◽  
Jose A. Apolinario ◽  
Felipe G. Serrenho

2020 ◽  
Author(s):  
Corrado Sandini ◽  
Daniela Zöller ◽  
Maude Schneider ◽  
Anjali Tarun ◽  
Marco Armando ◽  
...  

AbstractThere is a growing recognition that psychiatric symptoms have the potential to causally interact with one another. Particularly in the earliest stages of psychopathology dynamic interactions between symptoms could contribute heterogeneous and cross-diagnostic clinical evolutions. Current clinical approaches attempt to merge clinical manifestations that co-occur across subjects and could therefore significantly hinder our understanding of clinical pathways connecting individual symptoms. Network approaches have the potential to shed light on the complex dynamics of early psychopathology. In the present manuscript we attempt to address 2 main limitations that have in our opinion hindered the application of network approaches in the clinical setting. The first limitation is that network analyses have mostly been applied to cross-sectional data, yielding results that often lack the intuitive interpretability of simpler categorical or dimensional approaches. Here we propose an approach based on multi-layer network analysis that offers an intuitive low-dimensional characterization of longitudinal pathways involved in the evolution of psychopathology, while conserving high-dimensional information on the role of specific symptoms. The second limitation is that network analyses typically characterize symptom connectivity at the level of a population, whereas clinical practice deals with symptom severity at the level of the individual. Here we propose an approach based on graph signal processing that exploits knowledge of network interactions between symptoms to predict longitudinal clinical evolution at the level of the individual. We test our approaches in two independent samples of individuals with genetic and clinical vulnerability for developing psychosis.


2020 ◽  
Vol 169 ◽  
pp. 107404
Author(s):  
Fernando Gama ◽  
Antonio G. Marques ◽  
Gonzalo Mateos ◽  
Alejandro Ribeiro

2019 ◽  
Author(s):  
Ladislas Nalborczyk ◽  
Romain Grandchamp ◽  
Ernst H. W. Koster ◽  
Marcela Perrone-Bertolotti ◽  
Hélène Loevenbruck

Although having a long history of scrutiny in experimental psychology, it is still controversial whether inner speech (covert speech) production is accompanied by specific activity in speech muscles. We address this question by briefly reviewing previous findings related to inner speech and to the broader phenomenon of motor imagery. We then present the results of a preregistered experiment looking at the electromyographic correlates of both overt speech and inner speech production of two phonetic classes of nonwords. An automatic classification approach was undertaken to discriminate between two articulatory features contained in nonwords uttered in both overt and covert speech. Although this approach led to reasonable accuracy rates during overt speech production, it failed to discriminate inner speech phonetic content based on surface electromyography signals alone. However, exploratory analyses conducted at the individual level revealed that it seemed possible to distinguish between rounded and spread nonwords covertly produced, in two participants. We discuss these results in relation to the existing literature and suggest alternative ways to test the engagement of the speech motor system during inner speech production. Pre-registered protocol, preprint, data, as well as reproducible code and figures are available at: https://osf.io/czer4/.


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