Spike timing-dependent plasticity (STDP) has been suggested as one of the key mechanism underlying learning and memory. Due to its importance, timing-dependent plasticity studies have been approached in the living human brain by means of non-invasive brain stimulation (NIBS) protocols such as paired associative stimulation (PAS). However, contrary to STDP studies at a cellular level, functional plasticity induction in the human brain implies the interaction among target cortical networks and investigates plasticity mechanisms at a systems level. This thesis comprises of two independent studies that aim at understanding the importance of considering broad cortical networks when predicting the outcome of timing-dependent associative plasticity induction in the human brain. In the first study we developed a new protocol (ipsilateral PAS (ipsiPAS)) that required timing- and regional-specific information transfer across hemispheres for the induction of timing-dependent plasticity within M1 (see chapter 3). In the second study, we tested the influence of individual brain structure, as measured with voxel-based cortical thickness, on a standard PAS protocol (see chapter 4). In summary, we observed that the near-synchronous associativity taking place within M1 is not the only determinant influencing the outcome of PAS protocols. Rather, the online interaction of the cortical networks integrating information during a PAS intervention determines the outcome of the pairing of inputs in M1.

This thesis is divided into three main parts. In the first, we discuss that, although permutation tests can provide exact control of false positives under the reasonable assumption of exchangeability, there are common examples in which global exchangeability does not hold, such as in experiments with repeated measurements or tests in which subjects are related to each other. To allow permutation inference in such cases, we propose an extension of the well known concept of exchangeability blocks, allowing these to be nested in a hierarchical, multi-level definition. This definition allows permutations that retain the original joint distribution unaltered, thus preserving exchangeability. The null hypothesis is tested using only a subset of all otherwise possible permutations. We do not need to explicitly model the degree of dependence between observations; rather the use of such permutation scheme leaves any dependence intact. The strategy is compatible with heteroscedasticity and can be used with permutations, sign flippings, or both combined. In the second part, we exploit properties of test statistics to obtain accelerations irrespective of generic software or hardware improvements. We compare six different approaches using synthetic and real data, assessing the methods in terms of their error rates, power, agreement with a reference result, and the risk of taking a different decision regarding the rejection of the null hypotheses (known as the resampling risk). In the third part, we investigate and compare the different methods for assessment of cortical volume and area from magnetic resonance images using surface-based methods. Using data from young adults born with very low birth weight and coetaneous controls, we show that instead of volume, the permutation-based non-parametric combination (NPC) of thickness and area is a more sensitive option for studying joint effects on these two quantities, giving equal weight to variation in both, and allowing a better characterisation of biological processes that can affect brain morphology.

Spike timing-dependent plasticity (STDP) has been suggested as one of the key mechanism underlying learning and memory. Due to its importance, timing-dependent plasticity studies have been approached in the living human brain by means of non-invasive brain stimulation (NIBS) protocols such as paired associative stimulation (PAS). However, contrary to STDP studies at a cellular level, functional plasticity induction in the human brain implies the interaction among target cortical networks and investigates plasticity mechanisms at a systems level. This thesis comprises of two independent studies that aim at understanding the importance of considering broad cortical networks when predicting the outcome of timing-dependent associative plasticity induction in the human brain. In the first study we developed a new protocol (ipsilateral PAS (ipsiPAS)) that required timing- and regional-specific information transfer across hemispheres for the induction of timing-dependent plasticity within M1 (see chapter 3). In the second study, we tested the influence of individual brain structure, as measured with voxel-based cortical thickness, on a standard PAS protocol (see chapter 4). In summary, we observed that the near-synchronous associativity taking place within M1 is not the only determinant influencing the outcome of PAS protocols. Rather, the online interaction of the cortical networks integrating information during a PAS intervention determines the outcome of the pairing of inputs in M1.