Brain areas involved in learning and memory must represent a large number of different sensory stimuli using distinct patterns of neural activity. One way to achieve this is through combinatorial sensory coding, where neurons at deeper layers of the brain integrate information that arises from different sensory inputs, selectively responding to specific combinations of inputs. In this proposal, we use the Drosophila olfactory system as a powerful model to study the role of combinatorial coding in sensory perception. Odor identity is thought to be represented by the activity pattern of combinations of multiple different Olfactory Receptor Neurons (ORNs). Anatomical evidence suggests neurons at the third layer of the olfactory system may receive input from multiple different ORN channels, and so are the putative integration site of the combinatorial ORN code. In Drosophila, this third layer is called the mushroom body (MB), an important brain area for associative olfactory learning. MB neurons exhibit highly stimulus-selective (sparse) responses, a general feature of brain areas involved in learning and memory. We will use electrophysiological and two-photon imaging techniques to examine how this high selectivity arises in MB neurons. Physiological recordings will be aided by genetic tools available in Drosophila to identify specific neurons and manipulate their activity. Using these approaches we will investigate the rules by which MB neurons integrate information from earlier layers. We hope this will explain how combinatorial integration creates high response specificity while minimizing the amount of information loss that can plague sparse neural codes. Combining physiology, functional imaging and genetics in this simple system provides an exceptional opportunity for understanding the neuronal mechanisms underlying sparse coding in a learning and memory center. The Drosophila MB shares many properties with mammalian brain areas such as the hippocampus and cerebellum, so a mechanistic understanding of the MB will shed light on the function of more sophisticated areas of the human brain and how those mechanisms could be perturbed in disease states.
The brain has a tremendous capacity to form many highly accurate memories;it is precisely this facility that is lost in diseases such as Alzheimer's and other dementias. The brain achieves this remarkable capacity by using its sensory inputs in a combinatorial manner. We will examine how combinatorial information is integrated by neurons in the learning and memory center of the brain of Drosophila melanogaster, a powerful system for combining genetic and electrophysiological studies of nervous system function.
|Vogt, Katrin; Aso, Yoshinori; Hige, Toshihide et al. (2016) Direct neural pathways convey distinct visual information to Drosophila mushroom bodies. Elife 5:|
|Hige, Toshihide; Aso, Yoshinori; Rubin, Gerald M et al. (2015) Plasticity-driven individualization of olfactory coding in mushroom body output neurons. Nature 526:258-62|
|Hige, Toshihide; Aso, Yoshinori; Modi, Mehrab N et al. (2015) Heterosynaptic Plasticity Underlies Aversive Olfactory Learning in Drosophila. Neuron 88:985-98|
|Campbell, Robert A A; Eifert, Robert W; Turner, Glenn C (2014) OpenStage: a low-cost motorized microscope stage with sub-micron positioning accuracy. PLoS One 9:e88977|
|Campbell, Robert A A; Honegger, Kyle S; Qin, Hongtao et al. (2013) Imaging a population code for odor identity in the Drosophila mushroom body. J Neurosci 33:10568-81|
|Gruntman, Eyal; Turner, Glenn C (2013) Integration of the olfactory code across dendritic claws of single mushroom body neurons. Nat Neurosci 16:1821-9|
|Wu, Chia-Lin; Shih, Meng-Fu Maxwell; Lai, Jason Sih-Yu et al. (2011) Heterotypic gap junctions between two neurons in the drosophila brain are critical for memory. Curr Biol 21:848-54|
|Honegger, Kyle S; Campbell, Robert A A; Turner, Glenn C (2011) Cellular-resolution population imaging reveals robust sparse coding in the Drosophila mushroom body. J Neurosci 31:11772-85|