Modulation of neural activity in frontopolar cortex drives reward-based motor learning

The frontopolar cortex (FPC) contributes to tracking the reward of alternative choices during decision making, as well as their reliability. Whether this FPC function extends to reward gradients associated with continuous movements during motor learning remains unknown. We used anodal transcranial direct current stimulation (tDCS) over the right FPC to investigate its role in reward-based motor learning. Nineteen healthy human participants practiced novel sequences of finger movements on a digital piano with corresponding auditory feedback. Their aim was to use trialwise reward feedback to discover a hidden performance goal along a continuous dimension: timing. We additionally modulated the contralateral motor cortex (left M1) activity, and included a control sham stimulation. Right FPC-tDCS led to faster learning compared to lM1-tDCS and sham through regulation of motor variability. Bayesian computational modelling revealed that in all stimulation protocols, an increase in the trialwise expectation of reward was followed by greater exploitation, as shown previously. Yet, this association was weaker in lM1-tDCS suggesting a less efficient learning strategy. The effects of frontopolar stimulation were dissociated from those induced by lM1-tDCS and sham, as motor exploration was more sensitive to inferred changes in the reward tendency (volatility). The findings suggest that rFPC-tDCS increases the sensitivity of motor exploration to updates in reward volatility, accelerating reward-based motor learning

Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems

Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future

Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)

Banishing the control homunculi in studies of action control and behaviour change

types: ReviewDOI and citation will be added to the record once they are known.© 2014 Association for Psychological ScienceFor centuries, human self-control has fascinated scientists and nonscientists alike. Current theories often attribute it to an executive control system. But even though executive control receives a great deal of attention across disciplines, most aspects of it are still poorly understood. Many theories rely on an ill-defined set of ‘homunculi’ doing jobs like 'response inhibition' or ‘updating’ without explaining how they do so. Furthermore, it is not always appreciated that control takes place across different time-scales. These two issues hamper major advances. Here we focus on the mechanistic basis for the executive control of actions. We propose that at the most basic level, action control depends on three cognitive processes: signal detection, action selection, and action execution. These processes are modulated via error-correction or outcome-evaluation mechanisms, preparation, and task rules maintained in working- and long-term memory. We also consider how executive control of actions becomes automatised with practice, and how people develop a control network. Finally, we discuss how the application of this unified framework in clinical domains can increase our understanding of control deficits and provide a theoretical basis for the development of novel ‘behavioural change’ interventions