The (Dis)Pleasures of Creativity: Spontaneous Eye Blink Rate during Divergent and Convergent Thinking Depends on Individual Differences in Positive and Negative Affect

Previous research has demonstrated that individual differences in affect and motivation predict divergent and convergent thinking performance, two thinking processes involved in creative idea generation. Individual differences in affect and motivation also predict spontaneous eye blink rate (sEBR) during divergent and convergent thinking; and sEBR predicts divergent and convergent thinking performance. This study investigates experimentally whether the relationship between sEBR and divergent and convergent thinking depends on individual differences in affect and motivation. Eighty-two participants completed the Emotion/motivation-related Divergent and Convergent thinking styles Scale (EDICOS; G. Soroa et al., 2015), performed the alternative uses task (AUT; divergent thinking) or the remote associates task (RAT; convergent thinking), while their sEBR was captured with an eye-tracker. The results showed that individual differences in positive affect positively correlated with sEBR for the AUT, whereas individual differences in negative affect positively correlated with sEBR for the RAT. Furthermore, the interaction between individual differences in positive and negative affect and sEBR predicted divergent and convergent thinking performance. The contribution of our study is therefore that individual differences in positive and negative affect can both positively correlate with sEBR during divergent and convergent thinking; and that this predicts divergent and convergent thinking performance.     

Murray Sidman: A life of giving

Murray Sidman's contributions to the science of behavior span many areas including avoidance behavior, coercion and its effects, stimulus control, errorless learning, programmed learning, stimulus equivalence, and single-subject methodology. He was also a great mentor to many and helped shape the discipline we now call behavior analysis. In this memoriam, we briefly highlight his scholarly legacy and share some personal anecdotes.     

Intercessory Prayer on Spiritual Distress,Spiritual Coping,Anxiety, Depression and Salivary Amylase in Breast Cancer Patients During Radiotherapy: Randomized Clinical Trial

The goal of this study was to assess the effect of intercessory prayer in the psychological, spiritual and biological scores of breast cancer patients who are undergoing radiotherapy. Double-blind RCT comprising a sample of 31 participants (15 in the Control Group and 16 in the Intervention Group). Data collection was performed in three time points (T₀, T₁ and T₂). Significant changes have been identified in the intra-group analysis, concerning the decrease in spiritual distress score; negative religious/spiritual coping prevailed, while the total religious/spiritual coping increased between the posttest T₂ to T₀. Intercessory prayer was effective in religious and spiritual scores.

     

Extending the Basic Local Independence Model to Polytomous Data

Psychometrika - A probabilistic framework for the polytomous extension of knowledge space theory (KST) is proposed. It consists in a probabilistic model, called polytomous local independence model,...     

Does Partisan Bias Modulate Neural Processing of Political Information? An Analysis of the Neural Correlates of Corruption and Positive Messages

Daily worldwide newspapers print articles exposing government corruption. Yet these messages do not lead to a loss of votes for the corrupt parties. Sympathizers’ partisan bias, which respectively minimizes and maximizes corruption and positive messages of their own parties respectively, is widely considered the main cause of the loss of effectiveness of political communications. Despite the well-established existence of such bias when processing political information, little is known as to its psychological origin. Through the use of neuroscience (fMRI), this study explores the underlying brain mechanisms of negative (corruption) and positive political messages related to a conservative and a socialist Spanish political party, as well as the differences between their sympathizers. The findings reveal that negative (vs. positive) political messages exert the greatest neuroimaging impact on the electorate, as shown in aversive, risk, and disappointment-related brain regions. Interestingly, we show that there exists a main partisan bias against opposite parties (and not a positive bias toward one’s own party) that stems from a higher risk, ambiguity, and disbelief provoked by both positive and negative information about rival parties. Furthermore, this bias was more pronounced among conservative supporters. The current findings provide valuable insights for political parties to improve their communication campaigns.     

Truth Without Reference: The Use of Fictional Names

Topoi - Singular terms without referents are called empty or vacuous terms. But not all of them are equally empty. In particular, not all proper names that fail to name an existing object fail in...     

Precise Worlds for Certain Minds: An Ecological Perspective on the Relational Self in Autism

Topoi - Autism Spectrum Condition (ASC) presents a challenge to social and relational accounts of the self, precisely because it is broadly seen as a disorder impacting social relationships. Many...     

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.     

Assessment of Executive Functions after Treatment of Childhood Acute Lymphoid Leukemia: a Systematic Review

Neuropsychology Review - Individuals treated for childhood acute lymphoblastic leukemia (ALL) have a high survival rate. This fact, however, may lead to neurocognitive impairments in survivors, as...