Examining the effects of thought records and behavioral experiments in instigating belief change

The modalities of communication are the sum of the expression dimension (linguistics) and the expressivity dimension (prosody), both being equally important in language communication. The expressivity dimension which comes first in the act of speech, is the basis on which phonemes, syllables, words, grammar and morphosyntax, i.e., the expression dimension of speech is superimposed. We will review evidence (1) revealing the importance of prosody in language acquisition and (2) showing that prosody triggers the involvement of specific brain areas dedicated to sentences and word-list processing. To support the first point, we will not only rely on experimental psychology studies conducted in newborns and young children but also on neuroimaging studies that have helped to validate these behavioral experiments. Then, neuroimaging data on adults will allow for concluding that the expressivity dimension of speech modulates both the right hemisphere prosodic areas and the left hemisphere network in charge of the expression dimension

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The Upworthy Research Archive, a time series of 32,487 experiments in U.S. media

Scientific Data ◽

10.1038/s41597-021-00934-7 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

J. Nathan Matias ◽

Kevin Munger ◽

Marianne Aubin Le Quere ◽

Charles Ebersole

Keyword(s):

Data Mining ◽

Time Series ◽

Open Access ◽

Randomized Trial ◽

Digital Technology ◽

Behavioral Experiments ◽

Media Politics ◽

B Test ◽

Scientific Questions ◽

Advance Knowledge

AbstractThe pursuit of audience attention online has led organizations to conduct thousands of behavioral experiments each year in media, politics, activism, and digital technology. One pioneer of A/B tests was Upworthy.com, a U.S. media publisher that conducted a randomized trial for every article they published. Each experiment tested variations in a headline and image “package,” recording how many randomly-assigned viewers selected each variation. While none of these tests were designed to answer scientific questions, scientists can advance knowledge by meta-analyzing and data-mining the tens of thousands of experiments Upworthy conducted. This archive records the stimuli and outcome for every A/B test fielded by Upworthy between January 24, 2013 and April 30, 2015. In total, the archive includes 32,487 experiments, 150,817 experiment arms, and 538,272,878 participant assignments. The open access dataset is organized to support exploratory and confirmatory research, as well as meta-scientific research on ways that scientists make use of the archive.

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Policy learning as complex contagion: how social networks shape organizational beliefs in forest-based climate change mitigation

Policy Sciences ◽

10.1007/s11077-021-09418-2 ◽

2021 ◽

Author(s):

Antti Gronow ◽

Maria Brockhaus ◽

Monica Di Gregorio ◽

Aasa Karimo ◽

Tuomas Ylä-Anttila

Keyword(s):

Social Network ◽

Social Influence ◽

Belief Change ◽

Forest Degradation ◽

Policy Learning ◽

Policy Network ◽

Policy Problem ◽

Perceived Need ◽

Organizational Beliefs ◽

Policy Subsystems

AbstractPolicy learning can alter the perceptions of both the seriousness and the causes of a policy problem, thus also altering the perceived need to do something about the problem. This then allows for the informed weighing of different policy options. Taking a social network perspective, we argue that the role of social influence as a driver of policy learning has been overlooked in the literature. Network research has shown that normatively laden belief change is likely to occur through complex contagion—a process in which an actor receives social reinforcement from more than one contact in its social network. We test the applicability of this idea to policy learning using node-level network regression models on a unique longitudinal policy network survey dataset concerning the Reducing Deforestation and Forest Degradation (REDD+) initiative in Brazil, Indonesia, and Vietnam. We find that network connections explain policy learning in Indonesia and Vietnam, where the policy subsystems are collaborative, but not in Brazil, where the level of conflict is higher and the subsystem is more established. The results suggest that policy learning is more likely to result from social influence and complex contagion in collaborative than in conflictual settings.

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Quantifying the Predictability of Visual Scanpaths Using Active Information Storage

Entropy ◽

10.3390/e23020167 ◽

2021 ◽

Vol 23 (2) ◽

pp. 167

Author(s):

Patricia Wollstadt ◽

Martina Hasenjäger ◽

Christiane B. Wiebel-Herboth

Keyword(s):

Information Storage ◽

Gaze Behavior ◽

Behavioral Experiments ◽

Human Machine Interaction ◽

Cognitive States ◽

Visual Scanpath ◽

Active Information Storage ◽

Temporal Horizon ◽

Machine Interaction ◽

Transition Entropy

Entropy-based measures are an important tool for studying human gaze behavior under various conditions. In particular, gaze transition entropy (GTE) is a popular method to quantify the predictability of a visual scanpath as the entropy of transitions between fixations and has been shown to correlate with changes in task demand or changes in observer state. Measuring scanpath predictability is thus a promising approach to identifying viewers’ cognitive states in behavioral experiments or gaze-based applications. However, GTE does not account for temporal dependencies beyond two consecutive fixations and may thus underestimate the actual predictability of the current fixation given past gaze behavior. Instead, we propose to quantify scanpath predictability by estimating the active information storage (AIS), which can account for dependencies spanning multiple fixations. AIS is calculated as the mutual information between a processes’ multivariate past state and its next value. It is thus able to measure how much information a sequence of past fixations provides about the next fixation, hence covering a longer temporal horizon. Applying the proposed approach, we were able to distinguish between induced observer states based on estimated AIS, providing first evidence that AIS may be used in the inference of user states to improve human–machine interaction.

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Zhuyu Annao decoction promotes angiogenesis in mice with cerebral hemorrhage by inhibiting the activity of PHD3

Human & Experimental Toxicology ◽

10.1177/09603271211008523 ◽

2021 ◽

pp. 096032712110085

Author(s):

L Wu ◽

Y Hu ◽

L Jiang ◽

N Liang ◽

P Liu ◽

...

Keyword(s):

Oxidative Stress ◽

Signaling Pathway ◽

Morris Water Maze ◽

Cerebral Hemorrhage ◽

Water Maze ◽

Luciferase Reporter ◽

Morris Water Maze Test ◽

Therapeutic Effects ◽

Vascular Endothelial ◽

Behavioral Experiments

Some traditional Chinese decoctions, such as Zhuyu Annao, exert favorable therapeutic effects on acute cerebral hemorrhage, hemorrhagic stroke, and other neurological diseases, but the underlying mechanism remains unclear. This study aimed to determine whether Zhuyu Annao decoction (ZYAND) protects the injured brain by promoting angiogenesis following intracerebral hemorrhage (ICH) and elucidate its specific mechanism. The effect of ZYAND on the nervous system of mice after ICH was explored through behavioral experiments, such as the Morris water maze and Rotarod tests, and its effects on oxidative stress were explored by detecting several oxidative stress markers, including malondialdehyde, nitric oxide, glutathione peroxidase, and superoxide dismutase. Real-time quantitative RT-PCR and WB were used to detect the effects of ZYAND on the levels of prolyl hydroxylase domain 3 (PHD3), hypoxia-inducible factor-1α (HIF-1α), and vascular endothelial growth factor (VEGF) in the brain tissues of mice. The effect of ZYAND on the NF-κB signaling pathway was detected using a luciferase reporter gene. A human umbilical cord vascular endothelial cell angiogenesis experiment was performed to determine whether ZYAND promotes angiogenesis. The Morris water maze test and other behavioral experiments verified that ZYAND improved the neurobehavior of mice after ICH. ZYAND activated the PHD3/HIF-1α signaling pathway, inhibiting the oxidative damage caused by ICH. In angiogenesis experiments, it was found that ZYAND promoted VEGF-induced angiogenesis by upregulating the expression of HIF-1α, and NF-κB signaling regulated the expression of HIF-1α by inhibiting PHD3. ZYAND exerts a reparative effect on brain tissue damaged after ICH through the NF-κB/ PHD3/HIF-1α/VEGF signaling axis.

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Predictive olfactory learning in Drosophila

Scientific Reports ◽

10.1038/s41598-021-85841-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Chang Zhao ◽

Yves F. Widmer ◽

Sören Diegelmann ◽

Mihai A. Petrovici ◽

Simon G. Sprecher ◽

...

Keyword(s):

Synaptic Plasticity ◽

Dopaminergic Neurons ◽

Mushroom Body ◽

Trace Conditioning ◽

Fruit Fly ◽

Olfactory Learning ◽

Shock Strength ◽

Behavioral Experiments ◽

Kenyon Cells ◽

Output Neurons

AbstractOlfactory learning and conditioning in the fruit fly is typically modelled by correlation-based associative synaptic plasticity. It was shown that the conditioning of an odor-evoked response by a shock depends on the connections from Kenyon cells (KC) to mushroom body output neurons (MBONs). Although on the behavioral level conditioning is recognized to be predictive, it remains unclear how MBONs form predictions of aversive or appetitive values (valences) of odors on the circuit level. We present behavioral experiments that are not well explained by associative plasticity between conditioned and unconditioned stimuli, and we suggest two alternative models for how predictions can be formed. In error-driven predictive plasticity, dopaminergic neurons (DANs) represent the error between the predictive odor value and the shock strength. In target-driven predictive plasticity, the DANs represent the target for the predictive MBON activity. Predictive plasticity in KC-to-MBON synapses can also explain trace-conditioning, the valence-dependent sign switch in plasticity, and the observed novelty-familiarity representation. The model offers a framework to dissect MBON circuits and interpret DAN activity during olfactory learning.

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