The local field potential (LFP) is the low-pass filtered extracellular potential recorded inside brain tissue. Unlike spikes, which reflect neuronal action potentials and thus the output of neurons, the LFP is believed to predominantly reflect the synaptic inputs to neurons. Here, we use computer simulations and approximate analytical formulas of LFPs from single neurons and populations of neurons to give a comprehensive overview of the various factors that can contribute to shaping the LFP and its frequency content. We consider the effects of neural morphology, intrinsic dendritic filtering, synaptic distributions, synchrony in synaptic inputs, the position of the recording electrode, and possible contributions from action potentials, calcium spikes, NMDA spikes, and active subthreshold dendritic ion channels.

This chapter explores the recent shift in cognitive science toward the brain. The first two sections introduce the rudiments of brain anatomy and then explore Ungerleider and Mishkin's two visual systems hypothesis. Their work provides neural evidence of the two visual pathways (ventral and dorsal routes) in the brain from animal studies. The third section introduces the parallel distributed processing model of cognition introduced by Rumelhart, McClelland, and the PDP group. This model, and what came to be known as artificial neural networks, provide a powerful theoretical explanation of how the brain might process information. The last three sections are focused on early brain imaging studies on cognitive functions. First, Petersen and his colleagues used PET to detect how different brain regions respond to different stages of lexical processing. Next, Brewer and his colleagues localized the brain regions in memory tasks using event-related fMRI. Finally, Logothetis and his colleagues' exploration of the neural correlates of the BOLD signal suggests that fMRI signals could be a function of the input to neural regions rather than of neural firing.