Abstract
Frontostriatal disorders, such as Parkinson’s disease (PD), are characterized by progressive disruption of cortico-subcortical dopaminergic loops involved in diverse higher-order domains, including language. Indeed, syntactic and emotional language tasks have emerged as potential biomarkers of frontostriatal disturbances. However, relevant studies and models have typically considered these linguistic dimensions in isolation, overlooking the potential advantages of targeting multidimensional markers. Here, we examined whether patient classification can be improved through the joint assessment of both dimensions using sentential stimuli. We evaluated 31 early PD patients and 24 healthy controls via two syntactic measures (functional-role assignment, parsing of long-distance dependencies) and a verbal task tapping social emotions (envy, Schadenfreude) and compared their classification accuracy when analyzed in isolation and in combination. Complementarily, we replicated our approach to discriminate between patients on and off medication. Results showed that specific measures of each dimension were selectively impaired in PD. In particular, joint analysis of outcomes in functional-role assignment and Schadenfreude improved the classification accuracy of patients and controls, irrespective of their overall cognitive and affective state. These results suggest that multidimensional linguistic assessments may better capture the complexity and multi-functional impact of frontostriatal disruptions, highlighting their potential contributions in the ongoing quest for sensitive markers of PD.
Highlights
Given the high prevalence of frontostriatal motor disorders in general, and Parkinson’s disease (PD) in particular (Rossi et al, 2018), increasing efforts are being made to identify condition-sensitive markers (Delenclos et al, 2016)
Group differences in Touching A with B remained significant after co-varying for Montreal Cognitive Assessment (MoCA), INECO Frontal Screening (IFS), and Hamilton Depression Rating Scale (HDRS)
The marginal differences between subgroups in Touching A with B remained similar after adjusting for MoCA, IFS, and HDRS
Summary
Given the high prevalence of frontostriatal motor disorders in general, and Parkinson’s disease (PD) in particular (Rossi et al, 2018), increasing efforts are being made to identify condition-sensitive markers (Delenclos et al, 2016). Notwithstanding, most studies on PD have ignored the anatomical complexity and multifunctionality of frontostriatal circuits, considering language dimensions as compartmentalized (if not altogether modular) functions. This isolationist approach to cognitive processes precludes the identification of multidimensional markers, which are potentially more sensitive for the characterization and identification of PD patients. Despite recent calls for more integrative multidimensional frameworks to characterize cognitive processes (Ibáñez and García, 2018; Ibáñez, 2019) and their dysfunctions in neurological conditions (Caselli et al, 2014; Canevelli et al, 2015; Delenclos et al, 2016), no study in PD has yet explored whether patient classification can be improved through a joint assessment of syntactic and emotional language processing.
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