Repetition priming effects for famous faces through dynamic causal modelling of latency‐corrected event‐related brain potentials

Abstract

Repetition priming, that is, the repeated processing of a stimulus, facilitates performance. However, the neural underpinnings of repetition priming for famous faces in terms of effective connectivity are not known. Here we investigated this problem using dynamic causal modelling of latency‐corrected event‐related brain potentials (RERPs). Source waveforms of RERP‐derived sources in the Occipital Lobe, Fusiform Gyrus, Mediotemporal Lobe, Prefrontal Cortex and Anterotemporal Lobe of each hemisphere entered into models with only forward (F) or also with backward (FB) connections. Based on the framework of predictive coding formulated for repetition suppression, modulations of F and FB connections were expected for sources that displayed priming effects in their source waveforms. Hence, neural sources in each hemisphere were fitted with either F or FB connections. Inter‐hemispheric connections were considered between homologous areas and were allowed to be modulated in an incremental manner resulting in a model space that comprised of 24 models. Bayesian model averaging across models revealed effective bidirectional connectivity between the Fusiform Gyrus (face perception) and Prefrontal Cortex (decision‐making) in both hemispheres to be modulated by priming. In the left hemisphere, there is also a substantial involvement from the Mediotemporal Lobe, indicating the facilitation of automatic retrieval of the famous person's name. Furthermore, there is evidence that the priming is supported by connections from the right to the left Fusiform Gyri possibly in the service of inter‐hemispheric cooperation. Altogether, the study indicates that along with top–down modulations, efficient processing within and across the two hemispheres is crucial for famous face priming.

Dynamic Causal Modeling on the Identification of Interacting Networks in the Brain: A Systematic Review

“…3) FC-OC: We found 27 papers [17], [24], [36], [48], [58][59][60], [66], [70], [78], [87], [95], [97][98], [100][101], [119][120][121][122][123][124][125][126][127][128][129] involved in this connectivity category, spanning eight different task types, of which disease diagnosis had the highest prevalence.…”

“…4) FC-TC: We found 30 publications [17], [30], [34], [37], [45], [52], [57][58], [64], [68], [112], [116], [121][122], [125], [130][131][132][133][134][135][136][137][138] on this connectivity category. Eight task types were proposed for its analysis, the most frequent being sensory tasks, speech tasks, and disease diagnosis.…”

Sex difference in tDCS current mediated by changes in cortical anatomy: A study across young, middle and older adults

“…Overall, modelling studies are helpful and can serve as a starting point to identify induced electrical current behaviour in recent years. However, future studies with neuroimaging methods like PET, cerebral blood flow and electrophysiological techniques could complement the tDCS modelling studies to clarify the associated physiological changes (for details, [98,99]).…”

Focality-Oriented Selection of Current Dose for Transcranial Direct Current Stimulation

“…We have shown how DTDI can be used for a target ROI. However, a user may be interested in stimulating multiple target ROIs, or a network of ROIs specific to a particular functionality [82][83][84][85][86][87][88]. This may be because studies have shown that more than one brain area can be involved in neuropsychiatric disorders like depression [89,90].…”