Learning Spike-Based Population Codes by Reward and Population Feedback

We investigate a recently proposed model for decision learning in a population of spiking neurons where synaptic plasticity is modulated by a population signal in addition to reward feedback. For the basic model, binary population decision making based on spike/no-spike coding, a detailed computational analysis is given about how learning performance depends on population size and task complexity. Next, we extend the basic model to n-ary decision making and show that it can also be used in conjunction with other population codes such as rate or even latency coding.

Effects of anxiety on decision making and visual search behaviour in complex sport situations

Introduction Current empirical findings indicate that the efficiency of decision making (both for experts and near-experts) in simple situations is reduced under increased stress (Wilson, 2008). Explaining the phenomenon, the Attentional Control Theory (ACT, Eysenck et al., 2007) postulates an impairment of attentional processes resulting in a less efficient processing of visual information. From a practitioner’s perspective, it would be highly relevant to know whether this phenomenon can also be found in complex sport situations like in the game of football. Consequently, in the present study, decision making of football players was examined under regular vs. increased anxiety conditions. Methods 22 participants (11 experts and 11 near-experts) viewed 24 complex football situations (counterbalanced) in two anxiety conditions from the perspective of the last defender. They had to decide as fast and accurate as possible on the next action of the player in possession (options: shot on goal, dribble or pass to a designated team member) for equal numbers of trials in a near and far distance condition (based on the position of the player in possession). Anxiety was manipulated via a competitive environment, false feedback as well as ego threats. Decision time and accuracy, gaze behaviour (e.g., fixation duration on different locations) as well as state anxiety and mental effort were used as dependent variables and analysed with 2 (expertise) x 2 (distance) x 2 (anxiety) ANOVAs with repeated measures on the last two factors. Besides expertise differences, it was hypothesised that, based on ACT, increased anxiety reduces performance efficiency and impairs gaze behaviour. Results and Discussion Anxiety was manipulated successfully, indicated by higher ratings of state anxiety, F(1, 20) = 13.13, p < .01, ηp2 = .40. Besides expertise differences in decision making – experts responded faster, F(1, 20) = 11.32, p < .01, ηp2 = .36, and more accurate, F(1,20) = 23.93, p < .01, ηp2 = .55, than near-experts – decision time, F(1, 20) = 9.29, p < .01, ηp2 = .32, and mental effort, F(1, 20) = 7.33, p = .01, ηp2 = .27, increased for both groups in the high anxiety condition. This result confirms the ACT assumption that processing efficiency is reduced when being anxious. Replicating earlier findings, a significant expertise by distance interaction could be observed, F(1, 18) = 18.53, p < .01, ηp2 = .51), with experts fixating longer on the player in possession or the ball in the near distance and longer on other opponents, teammates and free space in the far distance condition. This shows that experts are able to adjust their gaze behaviour to affordances of displayed playing patterns. Additionally, a three way interaction was found, F(1, 18) = 7.37 p = .01, ηp2 = .29, revealing that experts utilised a reduced number of fixations in the far distance condition when being anxious indicating a reduced ability to pick up visual information. Since especially the visual search behaviour of experts was impaired, the ACT prediction that particularly top-down processes are affected by anxiety could be confirmed. Taken together, the results show that sports performance is negatively influenced by anxiety since longer response times, higher mental effort and inefficient visual search behaviour were observed. From a practitioner’s perspective, this finding might suggest preferring (implicit) perceptual cognitive training; however, this recommendation needs to be empirically supported in intervention studies. References: Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7, 336-353. Wilson, M. (2008). From processing efficiency to attentional control: A mechanistic account of the anxiety-performance relationship. Int. Review of Sport and Exercise Psychology, 1, 184-201.

Perceptual Training in Beach Volleyball Defence: Different Effects of Gaze-Path Cueing on Gaze and Decision-Making

For perceptual-cognitive skill training, a variety of intervention methods has been proposed, including the so-called “color-cueing method” which aims on superior gaze-path learning by applying visual markers. However, recent findings challenge this method, especially, with regards to its actual effects on gaze behavior. Consequently, after a preparatory study on the identification of appropriate visual cues for life-size displays, a perceptual-training experiment on decision-making in beach volleyball was conducted, contrasting two cueing interventions (functional vs. dysfunctional gaze path) with a conservative control condition (anticipation-related instructions). Gaze analyses revealed learning effects for the dysfunctional group only. Regarding decision-making, all groups showed enhanced performance with largest improvements for the control group followed by the functional and the dysfunctional group. Hence, the results confirm cueing effects on gaze behavior, but they also question its benefit for enhancing decision-making. However, before completely denying the method’s value, optimisations should be checked regarding, for instance, cueing-pattern characteristics and gaze-related feedback.