Search

Psychological theory is advanced through empirical tests of predictions derived from quantitative cognitive models. As cognitive models are developed and extended, they tend to increase in complexity–leading to more precise predictions–which places concomitant demands on the behavioral data used to discriminate between candidate theories. To aid discrimination between cognitive models and, more recently, to constrain parameter estimation, neural data have been used as an adjunct to behavioral data, or as a central stream of information, in the evaluation of cognitive models. Such a model-based neuroscience approach entails many advantages, including precise tests of hypotheses about brain–behavior relationships. There have, however, been few systematic investigations of the capacity for neural data to constrain the recovery of cognitive models. Through the lens of cognitive models of speeded decision-making, we investigated the efficiency of neural data to aid identification of latent cognitive states in models fit to behavioral data. We studied two theoretical frameworks that differed in their assumptions about the composition of the latent generating state. The first assumed that observed performance was generated from a mixture of discrete latent states. The second conceived of the latent state as dynamically varying along a continuous dimension. We used a simulation-based approach to compare recovery of latent data-generating states in neurally-informed versus neurally-uninformed cognitive models. We found that neurally-informed cognitive models were more reliably recovered under a discrete state representation than a continuous dimension representation for medium effect sizes, although recovery was difficult for small sample sizes and moderate noise in neural data. Recovery improved for both representations when a larger effect size differentiated the latent states. We conclude that neural data aids the identification of latent states in cognitive models, but different frameworks for quantitatively informing cognitive models with neural information have different model recovery efficiencies. We provide full worked examples and freely-available code to implement the two theoretical frameworks. [ABSTRACT FROM AUTHOR]

Several studies on patients with Alzheimer's disease (AD) have used transcranial direct current stimulation (tDCS) to enhance neural excitability in the left dorsolateral prefrontal cortex (lDLPFC). Interindividual differences in brain anatomy in AD patients pose a challenge to efficiently target the lDLPFC using scalp-based coordinates, calling for new and more precise tDCS protocols.

Aging is accompanied by declines in cognitive and sensorimotor functions. However, at present, the interrelation between attentional processes and dexterity in aging has not been thoroughly addressed. This study explored the relationship between executive function, working memory, and dexterity performance in 15 young and 15 healthy elderly, right-handed participants. A modified version of the Purdue Pegboard Test was used for dexterity assessment. Two subtasks were selected to calculate temporal and kinematic parameters of reaching, grasping, transport, and insertion of pegs. Evaluation of executive function and working memory was performed using neuropsychological tests. The relationship between dexterity and cognitive outcomes were also examined. Results showed that the prehensile movements involved in grasping and their speed significantly differed between groups and correlated with executive function in the young group. For elderly adults, variability of hand movements turned out to be associated with executive abilities.

There is growing evidence from neuro-computational studies that instrumental learning involves the dynamic interaction of a computationally rigid, low-level striatal and a more flexible, high-level prefrontal component.

Mind wandering (MW) is a mental phenomenon humans experience daily. Yet, we lack a complete understanding of the neural basis of this pervasive mental state. Over the past decade there has been an increase in publications using transcranial direct current stimulation (tDCS) to modulate the propensity to mind wander, but findings are diverse, and a satisfactory conclusion is missing. Recently, Boayue et al. (2020) reported successful reduction of mind wandering using high-definition tDCS (HD-tDCS) over the dorsolateral prefrontal cortex, providing preliminary evidence for the efficacy of HD-tDCS in interfering with mind wandering. The current study is a high-powered, pre-registered direct replication attempt of the effect found by Boayue et al. (2020). In addition, we investigated whether the effects of HD-tDCS on mind wandering would be prolonged and assessed the underlying processes of mind wandering using electroencephalography (EEG) and pupillometry during a finger-tapping random sequence generation task that requires the use of executive resources. We failed to find any evidence of the original effect of reduced MW during and after stimulation. When combining our data with the data from Boayue et al. (2020), the original effect of reduced MW caused by HD-tDCS disappeared. In addition, we observed increased occipital alpha power as task duration increased and increased midfrontal theta power preceding response patterns signaling high executive function use. Finally, tonic and phasic pupil size decreased as task duration increased yet, phasic responses were increased, while tonic responses were reduced preceding reports of MW. Additionally phasic pupil size also showed a tendency to be increased during periods of high executive function use. Importantly, none of the EEG or pupil measures were modulated by HD-tDCS. We conclude that HD-tDCS over the dorsolateral prefrontal cortex does not affect MW propensity and its neural signatures. Furthermore, we recommend that previously reported effects of tDCS on mind wandering and other cognitive functions should only be accepted after a successful pre-registered replication.

Objectives/AimsLearning from experience and making decisions based on integrated environmental feedback is crucial for human functioning and wellbeing. Difficulties in learning and decision-making have been found in several psychiatric conditions. Pavlovian bias, a tendency to approach reward and remain passive in the face of punishment, can be advantageous in some situations, while in others, it can lead to maladaptive decisions and needs to be overcome by cognitive control. It has been suggested that healthy humans rely more heavily on Pavlovian bias when instrumental control over environmental reinforcers is compromised. In our study, we were focusing on the influence of transcranial direct current stimulation (tDCS) on Pavlovian bias during and after an intermittent loss of control over rewards and losses.MethodsIn our pilot study, 19 adults underwent three blocks of an orthogonalized go-nogo reinforcement learning task. Blocks 1 and 3 had a response-feedback contingency of 70–30%, enabling learning via trial-and-error. In the second block, the outcome was independent of the participants’ responses (50%-50% contingency level). Cortical responses of all participants were recorded via EEG. Multi-electrode tDCS targeting the medial prefrontal cortex was administered in a randomised, double-blind placebo-controlled manner.ResultsWe conducted a repeated-measures ANOVA with ‘session’ (PRE x tDCS x POST), ‘valence’ (Win x Avoid) and ‘PB-congruency’ (Pavlovian bias congruent x incongruent) as within-factors, ‘group’ (Active stimulation x Sham) as the between- factor and ‘accuracy’ as the dependent variable. The interaction of ‘session’ and ‘PB- congruency’ with F(2,16)=2.62, p=0.09 were marginally significant, pointing towards slightly enhanced Pavlovian bias in the second block. However, the interaction of ‘session’, ‘PB-congruency’ and ‘group’ was not significant (F(2,16)=0.46, p=0.63). The evaluation of the feedback-related negativity (FRN) in the EEG revealed gradually increasing amplitudes in reward trials in the sham group, whereas we found a trend towards reduced FRN amplitude in the active group with F(2,13)=2.83, p=0.08.ConclusionsOur preliminary data show that a loss of control over feedbacks might increase the effect of Pavlovian bias on the choices of all participants. Although active tDCS seems to attenuate cortical responses during feedback evaluation, this effect is not accompanied by alterations in choice behaviour. Our data collection is still ongoing. The results from the full sample of 50 participants will be analysed by February 2020.