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

Abstract

Highlights:• ERP and DCM study of two sensory plasticity paradigms: roving MMN and visual LTP• First demonstration of multiple learning mechanisms under different task demands• Evidence for both Predictive Coding and Hebbian learning mechanisms• The BDNF Val66Met polymorphism modulates ERPs for both paradigms• However, the polymorphism only modulates MMN network connectivity not peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/189944 doi: bioRxiv preprint first posted online Sep. 17, 2017; The 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.

Human Sensory LTP Predicts Memory Performance and Is Modulated by the BDNF Val66Met Polymorphism

“…This effect was seen in the comparisons between all three groups in the late post-tetanus block, and between Val homozygotes and Met carriers in the early post-tetanus block. Spriggs et al (2017b) 1 also found that the Val 66 Met polymorphism impacted the magnitude of visual LTP, with genotype differences in the P2 component of the VEP (greater shift in Met carriers) 2 . It will therefore be important for further studies to characterise the complex relationship between the BDNF Val 66 Met polymorphism and visual LTP.…”

“… 2 While the results of these two studies may seem contradictory, there are significant differences in the approaches taken between them. First, Spriggs et al (2017b) grouped Met homozygotes and heterozygotes together into a “Met Carrier” group, thus overshadowing the dosage effect seen in the late post-tetanus block of the current study. Additionally, the current study employed previously established analysis methods and specifically focused on the N1b.…”

“…With the ability to study LTP and memory performance comes an unique opportunity to also study the role that LTP alterations play in variations in human memory performance. Previous studies using the human sensory LTP paradigm have demonstrated modulated LTP in healthy populations differing in physical fitness (Smallwood et al, 2015), age (de Gobbi Porto et al, 2015; Spriggs et al, 2017a), and genetics (Spriggs et al, 2017b), as well as in clinical conditions such as depression (Normann et al, 2007) and schizophrenia (Çavuş et al, 2012). However, how these differences in LTP magnitude impact upon memory performance is yet to be assessed.…”

GABA-ergic Dynamics in Human Frontotemporal Networks Confirmed by Pharmaco-Magnetoencephalography

“…The intrinsic connectivities are shown in Figure 1a; note the excitatory conductances based on AMPA and NMDA and inhibitory GABA-A and GABA-B conductances. The model is an extension of the SPM conductancebased CMM model (SPM12, 2013): inclusion of separate supragranular and infragranular interneuron populations creates a more biophysically realistic model that allows a greater flexibility of independence of deep and superficial activity than in previous work (Bhatt et al, 2016;Shaw et al, 2019;Spriggs et al, 2018). Additionally, the new 'tp' population expressed a hyperpolarization-activated cation current (H-current) and a non-inactivating potassium current (M-current) to provide surrogate intrinsic dynamics involved in the characteristic intrinsic bursting behavior of these cells.…”

“…Using parametric empirical Bayes to optimize the model across participants and drug conditions we examined how modeled GABAergic dynamics are altered by tiagabine. Based on the hypothesis that prediction and prediction error depend onshort-termGABAergicplasticity (Castro-Alamancos and Connors, 1996;Garrido et al, 2009a;Mongillo et al, 2018;Spriggs et al, 2018), we predicted that upper and lower hierarchical frontotemporal processing would be differentially affected by tiagabine during standard and deviant tones.…”