PubMed Health⌕ Search

PubMed · 16248747

Unconscious primes activate motor codes through semantics.

Abstract

Today, it is generally accepted that unconscious stimuli can activate a response code, which leads to a response congruency effect (RCE) on a subsequent target. However, it is not yet clear whether this is due to the semantic processing of the primes or to the formation of direct stimulus-response (S-R) associations bypassing the semantic system. Recently, it was shown that even novel primes, for which no direct S-R links exist, can also evoke an RCE that is in line with the activation of response codes through semantics. In these experiments, the authors examined 3 alternatives for this RCE from novel primes and report a novel effect in unconscious priming. First, the authors show that this effect is not limited to a small set of numerical stimuli but also extends to letter stimuli (Experiments 1-3). Second, the authors show that the RCE is not a side effect of the prime-target distance effect, as has been reported before (Experiments 1-2). Third, the authors found that, for RCE to occur, overlap at the motor level but not at the semantic level was crucial (Experiments 2-3). Finally, in addition, the results showed a category match priming effect independent of RCE. This last result is evidence that novel unconscious primes activate their semantic category prior to the target and might be considered a good marker for semantic processing.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Bert Reynvoet, Wim Gevers, Bernie Caessens. 2005. Unconscious primes activate motor codes through semantics.. https://doi.org/10.1037/0278-7393.31.5.991

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗