| To understand the mechanisms underlying many cognitive processes and brain disorders, we need to record from a large number of neurons in multiple areas simultaneously with high spatial and temporal resolution. Current experimental techniques, however, typically have either coarse spatiotemporal resolution or are only able to record from one to several neurons, resulting in large gap in our understanding between local, cellular-level changes and changes in cognition and behavior. Our knowledge of neurmodulatory systems, including the dopaminergic, cholinergic, noradrenergic, and serotonergic systems clearly demonstrates the shortcomings of these techniques. Specifically, we understand a great deal about where these neuromodulatory neurons project, how they affect their neuronal targets, and how they influence cognition and behavior, however, it is unclear mechanistically how the changes they produce at the cellular level lead to changes in behavior and cognition and, potentially, brain disorders.;This thesis utilizes large-scale neural network models in order to better understand how neuromodulation-mediated changes at the molecular and cellular level can lead to changes at the circuit level and, ultimately, behavior. Neuromodulatory effects on neurons and synapses, such as altering cell excitability and synaptic transmission, were incorporated into mean firing rate and spiking neural network models. In general, these models investigate how neuromodulatory systems influence both bottom-up (sensory) and top-down (goal-directed) attention by projecting to the thalamus, visual cortex, and prefrontal cortex. We were able to make predictions and match experimental data showing that neurmodulatory systems respond to uncertainty in the environment and, in turn, gate the influence of bottom-up and top-down information on behavior; influence correlations in visual cortex and thalamus and facilitate/regulate both bottom-up and top-down attention; and affect the amount of noise in working memory. These findings deepen our understanding of neuromodulatory effects from the molecular to the systems level. Furthermore, this thesis helps to solidify the fact that many neural processes are highly distributed and large-scale and, to understand brain disorders and complex neural functions, large-scale neural models are necessary. |
