Prefrontal cortical plasticity during learning of cognitive tasks

Training in working memory tasks is associated with lasting changes in prefrontal cortical activity. To assess the neural activity changes induced by training, we recorded single units, multi-unit activity (MUA) and local field potentials (LFP) with chronic electrode arrays implanted in the prefrontal cortex of two monkeys, throughout the period they were trained to perform cognitive tasks. Mastering different task phases was associated with distinct changes in neural activity, which included recruitment of larger numbers of neurons, increases or decreases of their firing rate, changes in the correlation structure between neurons, and redistribution of power across LFP frequency bands. In every training phase, changes induced by the actively learned task were also observed in a control task, which remained the same across the training period. Our results reveal how learning to perform cognitive tasks induces plasticity of prefrontal cortical activity, and how activity changes may generalize between tasks.

Functional cortical localization of tongue movements using corticokinematic coherence with a deep learning-assisted motion capture system

Corticokinematic coherence (CKC) between magnetoencephalographic and movement signals using an accelerometer is useful for the functional localization of the primary sensorimotor cortex (SM1). However, it is difficult to determine the tongue CKC because an accelerometer yields excessive magnetic artifacts. Here, we introduce a novel approach for measuring the tongue CKC using a deep learning-assisted motion capture system with videography, and compare it with an accelerometer in a control task measuring finger movement. Twelve healthy volunteers performed rhythmical side-to-side tongue movements in the whole-head magnetoencephalographic system, which were simultaneously recorded using a video camera and examined using a deep learning-assisted motion capture system. In the control task, right finger CKC measurements were simultaneously evaluated via motion capture and an accelerometer. The right finger CKC with motion capture was significant at the movement frequency peaks or its harmonics over the contralateral hemisphere; the motion-captured CKC was 84.9% similar to that with the accelerometer. The tongue CKC was significant at the movement frequency peaks or its harmonics over both hemispheres. The CKC sources of the tongue were considerably lateral and inferior to those of the finger. Thus, the CKC with deep learning-assisted motion capture can evaluate the functional localization of the tongue SM1.

EXPRESS: Task demands moderate the effect of emotion on attentional capture

The current experiment examined the effect of task demands on attention to emotional images. Eighty participants viewed pairs of images, with each pair consisting of an emotional (negative or positive) and a neutral image, or two neutral images. Participants’ eye movements were recorded during picture viewing, and participants were either asked 1) which picture contains more colour? (colour task), 2) are the images equally pleasant? (pleasantness task), 3) which picture do you prefer? (preference task), or 4) were given no task instructions (control task). Although the results did not suggest that emotional images strongly captured attention, emotional images were looked at earlier than neutral images. Importantly, the pattern of results were dependent upon the task instructions; whilst the preference and colour task conditions showed early attentional biases to emotional images, only positive images were looked at earlier in the pleasantness task condition, and no early attentional biases were observed in the control task. Moreover, total fixation duration was increased for positive images in the preference task condition, but not in the other task conditions. It was concluded that attention to emotional stimuli can be modified by the demands of the task during viewing. However, further research should consider additional factors, such as the cognitive load of the viewing tasks, and the content of the images used.

Authoring esteem: Writing about vicarious and personal life story chapters boosts state self-esteem

Constructing personal life stories carries benefits for psychological adjustment. We examined whether writing about the life stories of parents (i.e., vicarious life stories) hold similar advantages. In Study 1, we adapted an established experimental paradigm to an online format. Participants wrote either about personal life story chapters or about famous persons (control condition) and completed pre- and post-measures of state self-esteem. We found the predicted interaction as self-esteem increased in the chapter but not in the control condition. In Studies 2 and 3, we added the critical condition of writing about vicarious chapters. Study 2 did not find the predicted interaction. Instead, all three conditions increased in self-esteem. Study 3, which used a new neutral control task (writing about historical events), showed that the two chapter conditions, but not the control condition, increased in self-esteem. This suggests that authoring life stories for both oneself and close others momentarily boosts self-esteem.

Evolutionary vs. imitation learning for neuromorphic control at the edge

Neuromorphic computing offers the opportunity to implement extremely low power artificial intelligence at the edge. Control applications, such as autonomous vehicles and robotics, are also of great interest for neuromorphic systems at the edge. It is not clear, however, what the best neuromorphic training approaches are for control applications at the edge. In this work, we implement and compare the performance of evolutionary optimization and imitation learning approaches on an autonomous race car control task using an edge neuromorphic implementation. We show that the evolutionary approaches tend to achieve better performing smaller network sizes that are well-suited to edge deployment, but they also take significantly longer to train. We also describe a workflow to allow for future algorithmic comparisons for neuromorphic hardware on control applications at the edge.

Enhancement of loudness discrimination acuity for self-generated sound is independent of musical experience

Musicians tend to have better auditory and motor performance than non-musicians because of their extensive musical experience. In a previous study, we established that loudness discrimination acuity is enhanced when sound is produced by a precise force generation task. In this study, we compared the enhancement effect between experienced pianists and non-musicians. Without the force generation task, loudness discrimination acuity was better in pianists than non-musicians in the condition. However, the force generation task enhanced loudness discrimination acuity similarly in both pianists and non-musicians. The reaction time was also reduced with the force control task, but only in the non-musician group. The results suggest that the enhancement of loudness discrimination acuity with the precise force generation task is independent of musical experience and is, therefore, a fundamental function in auditory-motor interaction.

EXPRESS: A meta-analysis of the effects of episodic future thinking on delay discounting

Delay discounting (DD) refers to the phenomenon in which the subjective value of future rewards is reduced over time. There are individual differences in the DD rate, and increased discounting has been observed in those with various psychiatric disorders. Episodic future thinking (EFT) is the act of vividly imagining events that may happen in the future. Studies have shown that EFT could reduce DD, although inconsistent results have been reported. The aim of this meta-analysis was to clarify the efficacy with which EFT reduces DD and to identify potential moderators. Forty-seven studies (including 63 contrasts) were included in the final analysis. EFT was found to significantly reduce DD (Hedges’ g =0.52). Moderator analysis showed that positive EFT (g=0.64) was more effective in reducing DD than EFT with the valence not specifically mentioned (g=0.28), and EFT with neutral or negative valence (g=-0.03). In addition, several factors related to the control task and DD task were related to the efficacy of EFT to reduce DD. These findings have implications for using EFT to reduce DD in the future.

Learning Neuroplastic Matching of Robot Dynamics in Closed-loop CPGs

Legged robots have the potential to show locomotion performance with reduced control effort and energy efficiency by leveraging elastic structures inspired by animals' elastic tendons and muscles. However, it remains a challenge to match the natural dynamics of complex legged robots and their control task dynamics. Here we present a framework to match control task dynamics and natural dynamics based on the neuroelasticity and neuroplasticity concept. Inspired by animals we design quadruped robot Morti with strong natural dynamics as a testing platform. It is controlled through a bioinspired closed-loop central pattern generator (CPG) that is designed to neuroelastically mitigate short term perturbations using sparse contact feedback. We use the amount of neuroelastic activity as a proxy to quantify the dynamics' mismatching. By minimizing neuroelastic activity, we neuroplastically match the control task dynamics to the robot's natural dynamics. Through matching the robot learns to walk within one hour with only sparse feedback and improves its energy efficiency without explicitly minimizing it in the cost function.