Understanding the human functional connectome in a causal way and designing specific neuroengineering applications in diseases where error monitoring is faulty, such as in autism spectrum disorder (ASD), are relevant quests. We seek to link the neural basis of conflict-based impulsive vs. controlled decision-making by causally understanding of the neural connectivity of error monitoring underlying correct or erroneous decisions driving action. We focus on error monitoring in decisions where the speed vs. accuracy tradeoff is important for adaptive behavior. This process is based on putative prediction-error based interactions between low-level bottom-up and top down mechanisms. Following-up our previous simultaneous EEG-fMRI studies, we address, using EEG and real time fMRI (including a neurofeeback approach addressing causality in a novel way), the functional dichotomy between impulsive behaviour and cognitive control during simple decisions. Further, we will investigate the effective connectivity of error monitoring during such decisions, and the relation with parameters of diffusion/drift decision or prediction error models. We will apply this knowledge to understand the imbalance between impulsivity and cognitive control in 2 neurodevelopmental disorders: autism and ADHD. Finally we will implement a test/training brain computer interface to improve error monitoring in these disorders, where impulsivity is a major trait.
Cognitive control refers to the deliberate countermand of prepotent responses that should be inhibited, which fails during impulsive or distracted behavior, leading to errors. It is usually investigated during action withdrawal or cancellations, such as in go/no-go tasks. Cognitive control impairments may be found in ASD and ADHD. Underactivation in right Inferior Frontal Gyrus (IFG) is found in the latter. Impaired activation of dACC/dmPFC in autism possibly reflects reduced performance monitoring and top-down cognitive control. Since the right IFG is a critical region involved in cognitive inhibition and is part of the bottom-up stimulus-driven ventral attention network, it is important to unravel the underlying effective connectivity in disorders with similar attentional/impulsivity co-morbidities (ASD and ADHD).
Outcome monitoring is crucial for behavioral adjustment, and decision outcomes and respective response times depend on the quality of available evidence from low-level perceptual and contextual conditions, which determine the rate at which evidence accumulates. We will use diffusion drift and prediction error accounts to characterize how subjects accumulate evidence and perform in decision paradigms where the quality of error monitoring is critical, such as in go/no-go tasks and other impulsivity designs. Finally, we will develop a Neurofeedback/BCI approach to train error monitoring and communication abilities, which are both relevant in conditions such as autism.