Errors indicate the need to adjust attention for improved future performance. Detecting errors is thus a fundamental step to adjust and control attention. These functions have been associated with the dorsal anterior cingulate cortex (dACC), predicting that dACC cells should track the specific processing states giving rise to errors in order to identify which processing aspects need readjustment. Here, we tested this prediction by recording cells in the dACC and lateral prefrontal cortex (latPFC) of macaques performing an attention task that dissociated 3 processing stages. We found that, across prefrontal subareas, the dACC contained the largest cell populations encoding errors indicating (1) failures of inhibitory control of the attentional focus, (2) failures to prevent bottom-up distraction, and (3) lapses when implementing a choice. Error-locked firing in the dACC showed the earliest latencies across the PFC, emerged earlier than reward omission signals, and involved a significant proportion of putative inhibitory interneurons. Moreover, early onset error-locked response enhancement in the dACC was followed by transient prefrontal-cingulate inhibition, possibly reflecting active disengagement from task processing. These results suggest a functional specialization of the dACC to track and identify the actual processes that give rise to erroneous task outcomes, emphasizing its role to control attentional performance.
Parkinson disease (PD) probably represents a syndrome of different disorders and origins converging into a relatively uniform neurodegenerative process. Although clinical-pathological studies have suggested that the presymptomatic phase of PD may be relatively short, perhaps less than a decade, the authors postulate that the pathogenic mechanisms may begin much earlier, possibly even in the prenatal period. Thus, some patients with PD may be born with a fewer than normal number of dopaminergic (and nondopaminergic) neurons as a result of genetic or other abnormalities sustained during the prenatal or perinatal period; as a result of normal age-related neuronal attrition, they eventually reach the critical threshold (60% or more) of neuronal loss needed for onset of PD to become clinically manifest. The authors review the emerging evidence that genetic disruption of normal development, coupled with subsequent environmental factors (the so called multiple-hit hypothesis), plays an important role in the etiopathogenesis of PD.
Purpose This study investigated whether maximum speech performance, more specifically, the ability to rapidly alternate between similar syllables during speech production, is associated with executive control abilities in a nonclinical young adult population. Method Seventy-eight young adult participants completed two speech tasks, both operationalized as maximum performance tasks, to index their articulatory control: a diadochokinetic (DDK) task with nonword and real-word syllable sequences and a tongue-twister task. Additionally, participants completed three cognitive tasks, each covering one element of executive control (a Flanker interference task to index inhibitory control, a letter–number switching task to index cognitive switching, and an operation span task to index updating of working memory). Linear mixed-effects models were fitted to investigate how well maximum speech performance measures can be predicted by elements of executive control. Results Participants' cognitive switching ability was associated with their accuracy in both the DDK and tongue-twister speech tasks. Additionally, nonword DDK accuracy was more strongly associated with executive control than real-word DDK accuracy (which has to be interpreted with caution). None of the executive control abilities related to the maximum rates at which participants performed the two speech tasks. Conclusion These results underscore the association between maximum speech performance and executive control (cognitive switching in particular).
Schizophrenia is characterized by abnormal brain structure such as global reductions in gray matter volume. Machine learning models trained to estimate the age of brains from structural neuroimaging data consistently show advanced brain-age to be associated with schizophrenia. Yet, it is unclear whether advanced brain-age is specific to schizophrenia compared to other psychotic disorders, and whether evidence that brain structure is “older” than chronological age actually reflects neurodevelopmental rather than atrophic processes. It is also unknown whether advanced brain-age is associated with genetic liability for psychosis carried by biological relatives of people with schizophrenia. We used the Brain-Age Regression Analysis and Computation Utility Software (BARACUS) prediction model and calculated the residualized brain-age gap of 332 adults (163 individuals with psychotic disorders: 105 schizophrenia, 17 schizoaffective disorder, 41 bipolar I disorder with psychotic features; 103 first-degree biological relatives; 66 controls). The model estimated advanced brain-ages for people with psychosis in comparison to controls and relatives, with no differences among psychotic disorders or between relatives and controls. Specifically, the model revealed an enlarged brain-age gap for schizophrenia and bipolar disorder with psychotic features. Advanced brain-age was associated with lower cognitive and general functioning in the full sample. Among relatives, cognitive performance and schizotypal symptoms were related to brain-age gap, suggesting that advanced brain-age is associated with the subtle expressions associated with psychosis. Exploratory longitudinal analyses suggested that brain aging was not accelerated in individuals with a psychotic disorder. In sum, we found that people with psychotic disorders, irrespective of specific diagnosis or illness severity, show indications of non-progressive, advanced brain-age. These findings support a transdiagnostic, neurodevelopmental formulation of structural brain abnormalities in psychotic psychopathology.
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