Spriggs, M. J. | bioRxiv Science

bioRxiv2018

Human sensory Long-Term Potentiation (LTP) predicts visual memory performance and is modulated by the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism

BackgroundLong-Term Potentiation (LTP) is recognised as a core neuronal process underlying long-term memory. However, a direct relationship between LTP and human memory performance is yet to be demonstrated. The first aim of the current study was thus to assess the relationship between LTP and human long-term memory performance. With this also comes an opportunity to explore factors thought to mediate the relationship between LTP and long-term memory, and to gain additional insight into variations in memory function and memory decline. The second aim of the current study was to explore the relationship between LTP and memory in groups differing with respect to BDNF Val66Met; a single nucleotide polymorphism implicated in memory function.\n\nMethods28 participants (15 female) were split into three genotype groups (Val/Val, Val/Met, Met/Met) and were presented with both an EEG paradigm for inducing LTP-like enhancements of the visually-evoked response, and a test of visual memory.\n\nResultsThe magnitude of LTP 40 minutes after induction was predictive of long-term memory performance. Additionally, the BDNF Met allele was associated with both reduced LTP and reduced memory performance.\n\nConclusionsThe current study not only presents the first evidence for a relationship between sensory LTP and human memory performance, but also demonstrates how targeting this relationship can provide insight into factors implicated in variation in human memory performance. It is anticipated that this will be of utility to future clinical studies of disrupted memory function.

neuroscience↗

bioRxiv2017

Indexing sensory plasticity: Evidence for distinct Predictive Coding and Hebbian Learning mechanisms in the cerebral cortex

HighlightsO_LIERP and DCM study of two sensory plasticity paradigms: roving MMN and visual LTP\nC_LIO_LIFirst demonstration of multiple learning mechanisms under different task demands\nC_LIO_LIEvidence for both Predictive Coding and Hebbian learning mechanisms\nC_LIO_LIThe BDNF Val66Met polymorphism modulates ERPs for both paradigms\nC_LIO_LIHowever, the polymorphism only modulates MMN network connectivity\nC_LI\n\nThe Roving Mismatch Negativity (MMN), and Visual LTP paradigms are widely used as independent measures of sensory plasticity. However, the paradigms are built upon fundamentally different (and seemingly opposing) models of perceptual learning; namely, Predictive Coding (MMN) and Hebbian plasticity (LTP). The aims of the current study were to 1) compare the generative mechanisms of the MMN and visual LTP, therefore assessing whether Predictive Coding and Hebbian mechanisms co-occur in the brain, and 2) assess whether the paradigms identify similar group differences in plasticity. Forty participants were split into two groups based on the BDNF Val66Met polymorphism and were presented with both paradigms. Consistent with Predictive Coding and Hebbian predictions, Dynamic Causal Modelling revealed that the generation of the MMN modulates forward and backward connections in the underlying network, while visual LTP only modulates forward connections. Genetic differences were identified in the ERPs for both paradigms, but were only apparent in backward connections of the MMN network. These results suggest that both Predictive Coding and Hebbian mechanisms are utilized by the brain under different task demands. Additionally, both tasks provide unique insight into plasticity mechanisms, which has important implications for future studies of aberrant plasticity in clinical populations.

neuroscience↗