In this study the authors investigated molecular pathways associated with memory formation. They used the behavioral genetics approach to identify genetic variations related to memory performance. An additional fMRI-study was conducted to validate their genetic findings as well as to capture brain activity related to the genotype. Out of 336 healthy subjects that underwent an episodic memory task, 32 were selected for the fMRI-Study due to their comparable memory performance. By choosing subjects of equal memory performance the authors sought to exclude performance dependent brain activation and to capture memory-related genotype effects. The remaining sample of 304 subjects was in a first step genotyped to search for sets of marker loci associated with memory. In a second step using the set association method the previously identified 16 genetic variations were narrowed down to a cluster of seven genetic variations significantly related to memory performance. This cluster was then used to calculate an individual memory-associated genetic score (IMAGS) reflecting the individual memory-related genetic variability. To link the IMAGS to memory associated brain activity activations of the previously selected 32 subjects performing an episodic memory task was measured by fMRI. Results showed that the IMAGS correlated significantly with memory-related brain regions, underlining that the IMAGS captures indeed genetic variations associated with memory. Moreover the authors were able to demonstrate that individual memory performance and memory-related brain activation can directly be associated with a person’s individual genetic variability.
de Quervain, D., & Papassotiropoulos, A. (2006). Identification of a genetic cluster influencing memory performance and hippocampal activity in humans Proceedings of the National Academy of Sciences, 103 (11), 4270-4274 DOI: 10.1073/pnas.0510212103
Tags: fMRI, genes, learning, Memory, molecular cascade
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Am 17. January 2012 um 12:05 Uhr
In the discussion, we were a bit skeptical about the interpretation of the data. If we believe the data, individuals who have the best gene combination (calculated with 7 SNPs) also have an higher activity in the MLT during training (a brain region whose activity is correlated with better performance in other subjects), they nevertheless show similar behavior as the control group (a priori setting). If I would naively conclude that this highest activity can explain the relatively low score of the individuals with good gene combination, the author conclude that:
best genes -> higher activity in MLT -> highest learning.
the idea is that they nevertheless perform at the same level as the control for different reasons for each individual (therefore, it cannot be cached by the imaging), like attention or motivation, but that they learning capacity was higher.