Pioneering Neuroscience Journal
Contact Person: Clark Lindgren
The Grinnell Journal of Neurophysiology
The articles collected in these volumes represent original contributions to the field of neuroscience by students in Biology 150: Introduction to Biological Inquiry "The Language of Neurons", and Biology 363: Neurobiology.
Faculty Research Interests
My research interests are in the philosophy of language, and concern in particular the problem of normativity and the critical assessment of naturalistic approaches to meaning and mind.
I use biochemical and electrophysiological techniques to understand the molecular properties of neurotransmitter receptors, focusing on the nicotinic acetylcholine receptors. I am planning also to investigate the role of these receptors in the developing nervous system of a model vertebrate zebrafish, using both biochemical and molecular biological approaches.
I use electrophysiological (and optical) techniques to study synaptic transmission. In particular, I am interested in presynaptic events involved in the control and modulation of neurotransmitter release. Most of my work has been performed on neuromuscular junctions isolated from frog, crayfish, and lizard.
Philosophy of Mind with an emphasis on Consciousness and Cognitive Neuroscience.
Early Modern Philosophy (Particularly Spinoza, Cartesianism and the Dutch Enlightenment), Philosophy and History of Science, Asian Philosophy, Nietzsche.
I use behavioral and neuroanatomical techniques to study the role of prefrontal cortex in emotion and memory. My current work focuses on understanding the contributions of distinct regions of the rat prefrontal cortex to emotional memory.
My primary research interest is ingestive behavior - specifically, the role of learning in food choice and food motivation, with a particular focus on how these influence, and are influenced by, obesity. My lab uses a rat model to study the behavioral and neural mechanisms underlying these processes using a variety of biological and behavioral techniques.
I am interested in visual learning, especially inducing properties of the environment, i.e. what are relevant features? what is an appropriate model of reasoning for a visual task? Typically this involves bringing many sources of information to bear on a problem and using them in a unified fashion.