Human brain is a complex dynamical system, whose complexity could be highly functional and characterize cognitive abilities or mental disorders. The APOE ɛ4 allele is a well-known genetic risk factor for the development of Alzheimer's Disease and cognitive decline in later human life. However, there are no robust conclusions about the APOE genotype-phenotype association among young healthy adults. The main goal of this study is to investigate the bridges between brain signal complexity, APOE genotype and cognitive performance among young adults under the framework of individual difference. Before going deeper to the main topic, the first study assessed the reliability of Residue Iteration decomposition (RIDE), a method for analysis brain signals that was applied in the main parts of my thesis. Using a dataset independent from the main topic, I demonstrated that as compared with conventional analysis method, the RIDE-reconstructed event-related-potentials (ERPs), including the N400 component reflecting the evaluation of semantic incongruities during social communication, could more sensitively characterize people across a spectrum of autistic level. The second study investigated how individual differences in APOE genotypes are associated with 1) brain signal complexity measured with Multiscale Entropy (MSE) and 2) cognitive ability in specific domain, especially, working memory capacity. Using Structural Equation Modelling (SEM) we showed that APOE ε4 is associated with higher entropy at scale 1-4 and lower entropy at scale 5 and above, especially at frontal scalp regions and in an eyes open condition; in addition, we showed a stronger drop in MSE from closed to open eyes condition among ε4 carriers than non-carriers. The ε4 association with cognitive performance was complex, but basically ε4 seems to be associated with worse cognitive performance among lower educated people, whereas no such association appeared among the higher educated. The third study connected MSE with a different cognitive domain - face and object cognition abilities We showed that 1) increased MSE at all scales is associated with better cognitive performance from the view of both diffusion process during perceptual decision making and task performance accuracy. However, the association was only consistent for a closed eyes condition. 2) Increased MSE at higher scales (7 or 8) was associated with tighter coupling between RIDE-extracted single trial stimulus evaluation speed at the neural level and reaction time at the behavior level. To summarize, the results of my doctoral study connected brain signal complexity, APOE genotype and cognitive behavior among young healthy adults, providing a deeper understanding of brain-behavior relationships and - potentially - for early AD diagnosis when cognitive decline is not yet evident.

This doctoral thesis details a series of projects at the border of chemistry and neuroscience leading to the development of a novel family of probes which chemically target specific cells and molecules in the brain. Chapter 1 concisely introduces the history, development and applications of probes for monitoring brain activity and highlights synthetic voltage sensitive dyes as probes which have not yet reached their full potential, partly due to the lack of targeting strategies in brain tissue. Chapter 2 details the development of a new class of polymer-supported probes for ligand-directed delivery of fluorescent voltage sensitive dyes to monoaminergic neurons in live brain tissue. The polysaccharide dextran equipped with dichloropane as a ligand and either an electrochromic or PeT-based voltage sensor selectively targets dopaminergic and noradrenergic axons in mouse brain slice preparations. The new probes enabled voltage imaging in a defined neuronal population without the use of genetic manipulation. All following chapters describe modification of one of the components of the targeting platform developed in Chapter 2 aiming to optimize its performance or broaden its application potential. Chapter 3 extends the developed polymer platform to the targeting of a different molecular target – the AMPA-type glutamate receptor – via a ligand-directed covalent labeling strategy. Chapter 4 examines PEG as an alternative polymer carrier and shows that while dextran is more universal as a carrier, PEG provides superior targeting selectivity with negatively charged PeT-based voltage sensors. A series of targetable probes with improved voltage sensitivity based on the PEG platform is introduced here as well. Chapter 5 describes the synthesis of targetable probes carrying voltage sensors for imaging modalities other than visible light fluorescence, specifically for short wave infrared (SWIR) fluorescence and photoacoustic (PA) imaging. Chapter 6 shows the first steps towards adapting the delivery platform to the development of dual-ligand drugs for cell-selective pharmacology in the brain.

Synaptic plasticity is thought to be integral to learning and memory. The two most common forms of plasticity are long-term potentiation (LTP) and long-term depression (LTD), both of which can be supported either by presynaptic changes in transmitter release probability (Pr), or by postsynaptic changes in AMPA receptor number. It is generally thought that the induction of LTP and LTD at Schaffer-collateral synapses in the hippocampus depends on the activation of NMDA receptors (GluN). Recent studies, however, have demonstrated that both increases and decreases in Pr can be induced under blockade of postsynaptic GluN receptors, suggesting that the activation of postsynaptic GluN receptors by glutamate is only a strict requirement for postsynaptic plasticity. In this thesis, I therefore re-examined the role of glutamate in presynaptic plasticity. I used single synapse imaging along with electrophysiological and pharmacological techniques to independently manipulate and monitor the levels of glutamatergic signalling during synaptic activity. I discovered that glutamate is inhibitory and unnecessary for the induction of LTP at the presynaptic locus. My findings support a novel model of presynaptic plasticity in which the net activity-dependent changes in Pr at an active presynaptic terminal is jointly determined by two opposing processes that can be simultaneously active: 1) postsynaptic depolarization, which, via the activation of L-type voltage-gated Ca²⁺ channels, increases Pr by driving the synthesis and release of nitric oxide from neuronal dendrites and 2) glutamate release, which through the activation of presynaptic GluN receptors, decreases Pr. Computationally, this model suggests that plasticity functions to reduce prediction-errors that arise during synaptic activity, and, thereby offers a biologically plausible mechanism by which neuronal networks may optimize learning at the level of single synapses.