Using relatively simple animals, and focusing primarily on olfaction, our unit combines electrophysiological, anatomical, behavioral, and genetic techniques to examine the ways intact neural circuits, driven by sensory stimuli, process information. In the past year, our research program has addressed several questions, among them: What mechanisms underlie information coding and decoding? How are multi-modal stimuli integrated into unified perceptions? And how are innate sensory preferences determined? Our work reveals basic mechanisms by which sensory information is transformed, stabilized, and compared as it makes its way through the nervous system.? ? In the last year our unit focused on the mechanisms used by sensory systems to create neural codes that represent information within the brain. Stimulus-elicited oscillatory synchronization of neurons has been observed in many species and sensory systems. Using three simple organisms, each with unique but interlocking experimental advantages, we examined the generation and functions of odor-elicited oscillatory synchronization of populations of neurons in the olfactory pathway. ? ? To study neural mechanisms underlying synchronization, we took advantage of the genetic manipulations possible in Drosophila. Using techniques developed in our lab, we discovered that odors evoke neural oscillations in Drosophilas olfactory system. We established, with paired extracellular field potential and intracellular recordings from genetically-labeled neurons, that the oscillations originate within antennal lobe circuitry. The oscillations could be eliminated by application of picrotoxin, establishing that inhibitory neurons play a critical role in generating the oscillations. We found that there are actually two morphologically distinct classes of inhibitory neuron in the antennal lobe. Using the shibere genetic mutant, we could target, and under temperature control, reversibly remove either class of local neuron from the circuit. We found that one particular class of local neuron is responsible for the oscillations. Thus, we are dissecting the neural circuitry responsible for this ubiquitous aspect of sensory processing.? ? In several brain systems, neural oscillations can undergo shifts in frequency. Such shifts in oscillation frequency in neural circuits are widely observed but have not been carefully explored. To study this phenomenon, we used a larger organism, more suitable for intracellular recording, the moth Manduca. We found that odors elicit oscillations in the olfactory system of this animal, that the oscillations originate in the antennal lobe circuitry, and that the oscillations strongly influence the timing of spiking responses of downstream neurons. When moths encounter odors while feeding, the odor exposure typically endures for several seconds. We found that, over the course of a several-second odor pulse, odor-evoked oscillations slow from about 40Hz to about 20Hz, a particularly dramatic shift. Combining our physiological data with a dynamical systems computational model, we determined that the frequency change arises from adaptation-induced decrements in input intensity, which in turn shifts the neural circuit into a different stable state. We are using our model to investigate the functions of frequency shifts in processing of information by neural oscillatory synchronization.? ? Finally, we investigated how neural oscillations contribute to sparse coding, a widely observed feature of sensory systems. Sparse coding, a neural information processing strategy featuring minimal, broadly distributed spiking activity, is very common across brain areas and species. We examined how sparse codes can be maintained across a broad range of stimulus intensities. In the mushroom body of locusts, odors are represented by sparse codes consisting of very few spikes in a small number of neurons, a highly efficient strategy. Physiological studies of these neurons show that sparseness is maintained across thousand-fold changes in odor concentration. Using a realistic computational model tightly constrained by results of electrophysiological recordings, we found that sparseness in the olfactory system can be regulated by adaptive feedforward inhibition. When odor concentration changes, feedforward inhibition modulates the duration of the temporal window over which the mushroom body neurons may integrate excitatory presynaptic input. In general, this simple adaptive mechanism could maintain the sparseness of sensory representations across wide ranges of stimulus conditions.? ? Together, our work is advancing fundamental knowledge of neural mechanisms for representing environmental stimuli.
| Assisi, Collins; Stopfer, Mark; Laurent, Gilles et al. (2007) Adaptive regulation of sparseness by feedforward inhibition. Nat Neurosci 10:1176-84 |
| Vislay-Meltzer, Rebecca L; Stopfer, Mark (2007) Olfactory coding: a plastic approach to timing precision. Curr Biol 17:R797-9 |
| Stopfer, Mark (2007) Olfactory processing: massive convergence onto sparse codes. Curr Biol 17:R363-4 |
| Kay, Leslie M; Stopfer, Mark (2006) Information processing in the olfactory systems of insects and vertebrates. Semin Cell Dev Biol 17:433-42 |
| Bazhenov, Maxim; Stopfer, Mark; Sejnowski, Terrence J et al. (2005) Fast odor learning improves reliability of odor responses in the locust antennal lobe. Neuron 46:483-92 |
| Brown, Stacey L; Joseph, Joby; Stopfer, Mark (2005) Encoding a temporally structured stimulus with a temporally structured neural representation. Nat Neurosci 8:1568-76 |
| Stopfer, Mark; Jayaraman, Vivek; Laurent, Gilles (2003) Intensity versus identity coding in an olfactory system. Neuron 39:991-1004 |
