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...     

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.     

Providing more or less detailed information in job advertisements—Does it matter?

Job advertising is a common and useful recruitment marketing method that is available to a wide range of candidates and offers a practical way to widen the applicant pool. Frequently, retail advertisements only briefly introduce job requirements, but others provide more detailed information. Existing message studies, however, are inconclusive about the effectiveness of message specificity. A scenario‐based experiment that included 164 participants revealed that the type of decision maker (maximizer or satisficer) moderates the specificity effects in recruitment messages. After receiving a detailed job message, more satisficers stop their search process, but only maximizers perceive the company as more attractive and increase intentions toward the advertised job. A follow‐up qualitative study involving 30 participants provided further insights.     

Correction to: Towards a Better Understanding of Cognitive Deficits in Absence Epilepsy: a Systematic Review and Meta-Analysis

Neuropsychology Review - Due to an error during the editorial phase, a correction regarding Fig. 2 is added to the original article: “Towards a Better Understanding of Cognitive...     

Building cardiovascular disease competence in an urban poor Ghanaian community: A social psychology of participation approach

This paper describes conceptual, methodological, and practical insights from a longitudinal social psychological project that aims to build cardiovascular disease (CVD) competence in a poor community in Accra, Ghana's capital. Informed by a social psychology of participation approach, mixed method data included qualitative interviews and household surveys from over 500 community members, including people living with diabetes, hypertension, and stroke, their caregivers, health care providers, and GIS mapping of pluralistic health systems, food vending sites, bars, and physical activity spaces. Data analysis was informed by the diagnosis‐psychosocial intervention‐reflexivity framework proposed by Guareschi and Jovchelovitch. The community had a high prevalence of CVD and risk factors, and CVD knowledge was cognitive polyphasic. The environment was obesogenic, alcohol promoting, and medically pluralistic. These factors shaped CVD experiences and eclectic treatment seeking behaviours. Psychosocial interventions included establishing a self‐help group and community screening and education. Applying the “AIDS‐competent communities” model proposed by Campbell and colleagues, we outline the psychosocial features of CVD competence that are relatively easy to implement, albeit with funds and labour, and those that are difficult. We offer a reflexive analysis of four challenges that future activities will address: social protection, increasing men's participation, connecting national health policy to community needs, and sustaining the project.     

Attachment and resource sharing

In three studies we examined the associations between resource sharing (RS) and attachment, and the enhancement of RS using attachment security primes. In Study 1, we showed that attachment avoidance was negatively associated with RS. We also identified differences and similarities between RS and pro‐sociality. In Studies 2 and 3, we showed that research participants were more likely to share their monetary resources after they were primed with attachment security. Study 3 further revealed that security priming affected mainly people low on state attachment anxiety. Our findings extend previous work on pro‐sociality into the specific realm of RS, provide behavioral evidence, and tie attachment and close relationships in with game theory and research on economic decision making.     

Women are not swayed by sugar‐coated acts of verbal sexual coercion

Sexual coercion is receiving much attention with the #MeToo movement. Not all of the tactics that perpetrators use to coerce sex are perceived to be equally unacceptable. This study examined factors that may mitigate negative perceptions, including features of the perpetrator's tactics (verbal vs. physical tactics, relationship‐focused vs. self‐focused reasons to coerce sex) and raters' own current relationship (commitment, dependence, sexually coercive experiences). College women (N = 498) rated whether the perpetrator's behavior was acceptable, was excusable, and would adversely affect a relationship. Verbal (vs. physical) coercion, dependence on a current partner, and sexually coercive experiences in a current relationship mitigated negative perceptions. However, participant ratings were not influenced by the perpetrator's use of relationship‐focused reasons for coercing sex (vs. self‐focused reasons), suggesting that women may resist male attempts to sugar‐coat sexual coercion.     

Statistical learning of multiple speech streams: A challenge for monolingual infants

Language acquisition depends on the ability to detect and track the distributional properties of speech. Successful acquisition also necessitates detecting changes in those properties, which can occur when the learner encounters different speakers, topics, dialects, or languages. When encountering multiple speech streams with different underlying statistics but overlapping features, how do infants keep track of the properties of each speech stream separately? In four experiments, we tested whether 8‐month‐old monolingual infants (N = 144) can track the underlying statistics of two artificial speech streams that share a portion of their syllables. We first presented each stream individually. We then presented the two speech streams in sequence, without contextual cues signaling the different speech streams, and subsequently added pitch and accent cues to help learners track each stream separately. The results reveal that monolingual infants experience difficulty tracking the statistical regularities in two speech streams presented sequentially, even when provided with contextual cues intended to facilitate separation of the speech streams. We discuss the implications of our findings for understanding how infants learn and separate the input when confronted with multiple statistical structures.