In-Vivo Connectivity in Monkeys

Major efforts are underway to provide highly detailed descriptions of static anatomical brain connectivity in rodents, even down to the level of individual synapses. To fully understand brain functioning and to bridge the gap between rodents and humans, however, I argue in this chapter that effective connectivity studies in nonhuman primates are equally critical. The primate community should embrace the novel, high-precision genetic-based toolkits developed in invertebrates and rodents to study how activity in one brain region influences that in connected brain regions. These methods will allow us to measure true functional weights of anatomical connections during highly varying cognitive and perceptual demands in primates. Why monkeys, and why effective connectivity in addition to anatomical connectivity? First, the nonhuman primate is critically important to understand the functioning of the human brain since important brain regions, such as the granular prefrontal cortex carrying higher cognitive functions, are lacking in rodents as opposed to primates. Second, a pure anatomical description of connections at different scales may be useful to constrain models of brain functioning, however, it has little value to explain perception and behavior emerging from dynamic neuronal activity in distributed brain networks. Hence, tools that allow us to measure these dynamics at large scale and to causally interfere with the system at high temporal and spatial resolution are required to increase our understanding of changes in information processing at different stages within a functional network. In this chapter I will review past and emerging methods to study effective connectivity (mainly) in nonhuman primates, in other words how activity within a given brain area influences processing in anatomically connected brain regions. I will also argue that high-resolution whole brain imaging in monkeys may be invaluable to guide reversible perturbations and massive neurophysiological recordings simultaneously within multiple nodes of functional networks.