Self-organizing individual differences in brain development

Brain development is self-organizing in that the unique structure of each brain evolves in unpredictable ways through recursive modifications of synaptic networks. In this article, I review mechanisms of neural change in real time and over development, and I argue that change at each of these time scales embodies principles of self-organizing systems. I demonstrate how corticolimbic configurations that emerge within occasions lay down synaptic structure across occasions, giving rise to individual trajectories that become entrenched with age. Emotions have a powerful influence on this process.This is because the neural processes mediating emotion consolidate patterns of activation across the brain, through their enhancement of inter-regional coordination in real time and their contribution to synaptic shaping over development. The loss of corticolimbic plasticity with age is an unfortunate fact of development, but it is compensated in part by transitional phases and individual learning experiences through which habits are modified or replaced. I emphasize variations in inter-systemic coupling as a key mediator of developing individual differences, and I discuss the acquisition of anxious/depressive appraisals as an example.     

Cognition as a dynamic system: Principles from embodiment

Traditional approaches to cognitive development concentrate on the stability of cognition and explain that stability via concepts segregated from perceiving acting. A dynamic systems approach in contrast focuses on the self-organization of behavior in tasks. This article uses recent results concerning the embodiment of cognition to argue for a dynamic systems approach. The embodiment hypothesis is the idea that intelligence emerges in the interaction of an organism with an environment and as a result of sensory-motor activity. The continual coupling of cognition to the world through the body both adapts cognition to the idiosyncrasies of the here and now, makes it relevant, and provides the mechanism for developmental change.     

Dynamic valuation: Preference changes in the context of face-to-face negotiation

This experiment examines the dynamics of preference change in the context of face-to-face negotiation. Participants playing the role of “student” or “financial aid officer” exchanged proposals regarding the terms of a student loan. Consistent with dissonance theory, participants increased their liking for proposals they offered and/or ultimately accepted. The reactance theory prediction that participants would devalue proposals received from their opponents was confirmed for loan officers, but not for students. A pair of experimental manipulations involving the pre-rating of proposals and/or the opportunity for participants to engage in a brief discussion period prior to the initial exchange of offers mediated these effects, and influenced subsequent rates of agreement. Underlying attributional mechanisms and the implications of these findings for facilitating agreements are discussed.     

The cost of facing fear: Visual working memory is impaired for faces expressing fear

Previous research has identified numerous factors affecting the capacity and accuracy of visual working memory (VWM). One potentially important factor is the emotionality of the stimuli to be encoded and held in VWM. We often must hold in VWM information that is emotionally charged, but much is still unknown about how the emotionality of stimuli impacts VWM performance. In the current research, we performed four studies examining the impact of fearful facial expressions on VWM for faces. Fearful expressions were found to produce a consistent cost to VWM performance. This cost was modulated by encoding time, but not set size. This cost was only present for faces in an upright orientation consistent with this cost being a product of the emotionality of the faces rather than lower‐level perceptual differences between neutral and fearful faces. These findings are discussed in the context of existing theoretical accounts of the impact of emotion on information processing. We suggest that a number of competing effects drive both costs and benefits and are at play when emotional information must be stored in VWM, with the task context determining the balance between them.     

Motion planning strategies in human control of non-rigid objects with internal degrees of freedom

The paper deals with modeling of human-like reaching movements in dynamic environments. A simple but not trivial example of reaching in a dynamic environment is the rest-to-rest manipulation of a multi-mass flexible object with the elimination of residual vibrations. Two approaches to the prediction of reaching movements are formulated in position and force actuation settings. In the first approach, either the position of the hand or the hand force is specified by the lowest order polynomial satisfying the boundary conditions of the reaching task. The second approach is based on the minimization of either the hand jerk or the hand force-change, with taking into account the dynamics of the flexible object. To verify the resulting four mathematical models, an experiment on the manipulation of a ten-masses flexible object of low stiffness is conducted. The experimental results show that the second approach gives a significantly better prediction of human movements, with the minimum hand force-change model having a slight but consistent edge over the minimum hand jerk one.     

The effects of social anxiety on emotional face discrimination and its modulation by mouth salience

People high in social anxiety experience fear of social situations due to the likelihood of social evaluation. Whereas happy faces are generally processed very quickly, this effect is impaired by high social anxiety. Mouth regions are implicated during emotional face processing, therefore differences in mouth salience might affect how social anxiety relates to emotional face discrimination. We designed an emotional facial expression recognition task to reveal how varying levels of sub-clinical social anxiety (measured by questionnaire) related to the discrimination of happy and fearful faces, and of happy and angry faces. We also categorised the facial expressions by the salience of the mouth region (i.e. high [open mouth] vs. low [closed mouth]). In a sample of 90 participants higher social anxiety (relative to lower social anxiety) was associated with a reduced happy face reaction time advantage. However, this effect was mainly driven by the faces with less salient closed mouths. Our results are consistent with theories of anxiety that incorporate an oversensitive valence evaluation system.     

Is it in your face?: Exploring the effects of sexual dimorphism on perception of leadership potential

Perceptions of a leader in a work environment is important from 2 perspectives: the leader themselves and more importantly the external observer. But what information does the observer use when making these judgments of leadership potential? Many studies on role congruity have demonstrated that gender stereotyping and perceived leadership ability is strongly tied to gender role incongruity. The role of facial appearance has been associated with leadership status and potential and becomes essentially relevant in military settings. Thus, the manner in which an individual’s face is perceived and evaluated may impact perceptions of his or her leadership ability and subsequent success. The present study seeks to extend research on how sex and gender characteristics of an individual’s face may possibly influence the perception of leadership abilities in a military service academy. Findings indicated that participants preferred individuals with gender congruent faces, which may reflect a preference for physical prowess and abilities.     

高社交焦虑个体对正性面孔的解释偏差

本研究采用情绪启动范式考察社交焦虑个体对正性刺激解释偏差。研究以正性和打碎的面孔为启动项,正性或负性非社交词为目标项,要求高社交焦虑组被试和控制组被试判断目标项的情感色彩,并记录其反应时与准确率。结果发现,两组被试具有不同的情绪启动模式：高焦虑组被试未表现出显著地相容性效应;他们在正性-正性条件下的反应时显著慢于控制组被试。研究结果提示高社交焦虑个体具有对正性社交刺激的解释偏差,他们不能充分理解正性社交刺激的积极含义。     

Equivalent Dynamic Models

Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.     

Planning Beyond the Next Trial in Adaptive Experiments: A Dynamic Programming Approach

Experimentation is at the heart of scientific inquiry. In the behavioral and neural sciences, where only a limited number of observations can often be made, it is ideal to design an experiment that leads to the rapid accumulation of information about the phenomenon under study. Adaptive experimentation has the potential to accelerate scientific progress by maximizing inferential gain in such research settings. To date, most adaptive experiments have relied on myopic, one‐step‐ahead strategies in which the stimulus on each trial is selected to maximize inference on the next trial only. A lingering question in the field has been how much additional benefit would be gained by optimizing beyond the next trial. A range of technical challenges has prevented this important question from being addressed adequately. This study applies dynamic programming (DP), a technique applicable for such full‐horizon, “global” optimization, to model‐based perceptual threshold estimation, a domain that has been a major beneficiary of adaptive methods. The results provide insight into conditions that will benefit from optimizing beyond the next trial. Implications for the use of adaptive methods in cognitive science are discussed.