Determinants of multiple semantic priming: a meta-analysis and spike frequency adaptive model of a cortical network.
Recall and language comprehension while processing sequences of words involves multiple semantic priming between several related and/or unrelated words. Accounting for multiple and interacting priming effects in terms of underlying neuronal structure and dynamics is a challenge for current models of semantic priming. Further elaboration of current models requires a quantifiable and reliable account of the simplest case of multiple priming resulting from two primes on a target. The meta-analytic approach offers a better understanding of the experimental data from studies on multiple priming regarding the additivity pattern of priming. The meta-analysis points to the effects of prime-target stimuli onset asynchronies on the pattern of underadditivity, overadditivity, or strict additivity of converging activation from multiple primes. The modeling approach is then constrained by results of the meta-analysis. We propose a model of a cortical network embedding spike frequency adaptation, which allows frequency and time-dependent modulation of neural activity. Model results give a comprehensive understanding of the meta-analysis results in terms of dynamics of neuron populations. They also give predictions regarding how stimuli intensities, association strength, and spike frequency adaptation influence multiple priming effects.
Lavigne
Frédéric
F
Laboratoire de Psychologie Cognitive et Sociale, Université de Nice-Sophia Antipolis, Nice, France. lavigne@unice.fr
Dumercy
Laurent
L
Darmon
Nelly
N
D000200:Action Potentials / Q000502:physiology*; D000222:Adaptation, Physiological / Q000502:physiology*; D002540:Cerebral Cortex / Q000502:physiology*; D006801:Humans; D016571:Neural Networks, Computer; D012660:Semantics