A neuropsycholinguistic chronometric embodied cognition investigation of the vertical representation of affect in visuo-spatial target detection

Published: 4 Dec 2019 | Version 1 | DOI: 10.17632/5jdxx67dhj.1

Description of this data

In two psychophysical experiments we investigated if experimentally induced affective states (positive vs. negative mood induced by film-clips) bias subsequent performance in a computerised visual singleton target detection task. Neuropsycholinguistic research indicates that affective conceptual metaphors consistently associate positive affect with elevated vertical spatial positions and negative affect with depressed spatial positions. According to the generic neuronal theory of thought and language, these semantic percept-concept association are neurocomputationally encoded in Gestalt circuits according to Hebbian principles of long-term potentiation/depression (LTP/LTD) and spike-timing depended plasticity (STDP), inter alia. Based on this theoretical background we predicted a priori that positive experimental mood induction facilitates reaction times (RTs) for target detection in the superior visual field (VFS) relative to the orthogonal inferior visual field (VFI). Vice versa, we expected that negative mood induction facilitates target detection RTs in VFI relative to VFS (Experiment 1 and 2). In addition, Experiment 1 explicitly tested the prediction that affective states bias perceptual judgments on the horizontal axis. Ex hypothesi, we predicted that positive mood induction facilitates target detection RTs in the right temporal visual field (VFR) compared to the contralateral left field (VFL). Per contrast, we predicted the inverse effect for target detection RTs in VFL versus VFR. Impetus for the last hypothesis was derived from the neuropsychological valence model of hemispheric processing of emotion perception which postulates asymmetric neuronal lateralisation for specific classes of emotions. The data did not corroborate our directional predictions. All a priori formulated hypotheses were falsified in a quasi-Popperian sense (in support of the urgently needed open-science revolution we provide a URL to the raw data for the purpose of statistical cross-validation and/or analytical reviews). Implications of the findings are discussed in the generic theoretical framework of embodied cognition and we will expound the crucial importance of negative results in a meta-analytic context (e.g., big-data AI machine learning / publication & confirmation bias). Furthermore, the de facto irrational epistemological basis of current publishing praxis is criticised from a universal philosophy of science vantage point. We will close with a critical embodied cognition discussion of the detrimental effects of constant screen exposure (e.g., ocular fixation on *smart*phones) on the development of the neuroplastic sensorimotor architecture of children.

Experiment data files

Steps to reproduce

E-Mail: mail@cognovo.christopher-germann.eu
Personal URL: http://cognovo.christopher-germann.eu
Raw data + analysis syntax: http://cognovo.data-sup2.christopher-germann.eu/index.zip
This work was supported by the European Union Marie Curie Initial Training Network
Marie Curie Actions: FP7-PEOPLE-2013-ITN-604764
Associated URL: http://cognovo.eu

Latest version

  • Version 1


    Published: 2019-12-04

    DOI: 10.17632/5jdxx67dhj.1

    Cite this dataset

    Germann, Christopher (2019), “A neuropsycholinguistic chronometric embodied cognition investigation of the vertical representation of affect in visuo-spatial target detection”, Mendeley Data, v1 http://dx.doi.org/10.17632/5jdxx67dhj.1


Views: 12
Downloads: 3


University of Plymouth


Psychology, Behavioral Neuroscience, Perception, Cognitive Neuroscience, Cognitive Linguistics, Cognitive Bias


CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

What does this mean?
You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.