Neural Oscillations and the Decoding of Sensory Information

Citation

Perez-Orive, Javier (2004) Neural Oscillations and the Decoding of Sensory Information. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/8VSB-VD89. https://resolver.caltech.edu/CaltechETD:etd-05242004-174642

Abstract

An important problem in neuroscience is to understand how the brain encodes information. A hypothesis is that differences in the timing of action potentials, reflecting synchronization changes among neuronal ensembles --often occurring in the context of oscillations-- can be meaningful to downstream neurons detecting coincident input. Several properties, such as active conductances, feedforward inhibition and oscillatory input, could potentially influence whether a neuron acts as a coincidence detector. Although different neural circuits in various animal groups will use different strategies to solve somewhat varying problems, there will also be many powerful solutions to coding problems that will be used repeatedly across diverse processing stages and animal phyla. The insect olfactory system, sharing many design similarities with other systems while having a reduced complexity, provides an excellent model in which to study the functional interactions of all these coding features.

This dissertation focuses on the decoding of olfactory information by the mushroom body (MB), the second relay of the insect olfactory system, which receives oscillating input from the antennal lobe (the first relay, analogous to the vertebrate olfactory bulb). Kenyon cells (KCs), the intrinsic neurons of the MB, are found to respond very specifically to odors. These responses typically consist of one or two reliable action potentials, phase-locked to the global oscillations, over extremely low baseline firing rates. This leads to a dramatic sparsening of the olfactory representation in the MB. Several circuit and intrinsic properties are found to take part in this transformation. Feedforward inhibition contributes to odor specificity and sparseness: blocking inhibitory input to the KCs broadened their odor tuning and abolished their phase-locking, supporting the idea that feedforward inhibition limits the temporal window over which KCs integrate their inputs. Voltage-dependent conductances contribute to a supralinear summation of coincident postsynaptic potentials and a reduction of their half-widths, indicating that KC intrinsic properties further contribute to coincidence detection. Taken together, these results indicate that oscillations serve as a framework on which KCs act as coincidence detectors and sparsen the olfactory representation. Abolishing the input oscillations disrupts KC odor responses, decreasing their specificity and the sparseness in the MB.

The work in this dissertation describes a mechanism for decoding timing information and indicates that not all spikes are equally relevant to downstream neurons, their specific relevance depending on whether they are correlated, within a specific phase of an oscillation cycle, with other input spikes. These general features can also provide useful insights into neural coding in more complex neural systems, where all the mechanisms described here have been separately observed. This work illustrates how these mechanisms can interact to code sensory information and bring about drastic transformations of neural representations, increasing our understanding of how nervous systems can process information.

Thesis Files