Dr. Nixon M. Abraham
Postdoctoral fellow
Laboratory of Sensory Perception and Plasticity
Department of Fundamental Neuroscience
University Medical Centre, University of Geneva
Title: Temporal aspects of information processing in the olfactory system
A cardinal question in neuroscience is how the brain perceives the ever-changing external world
and subsequently makes the appropriate decisions to adapt the behavior. Of critical importance is how fast the brain can extract information, and what factors control the speed of information processing and decision-making? Olfaction, the sense of smell, was generally thought as a ‘slow’ sense compared to ‘fast’ senses such as vision or hearing. To investigate the speed of olfactory information processing using mouse as the model system, I quantified the temporal course of olfactory decision-making by using simple and complex stimuli. Mice discriminated simple odors in <200 ms with high accuracy. Binary mixtures evoking highly overlapping spatiotemporal activity patterns in the olfactory bulb (OB) were discriminated equally well but required longer (~300 ms) discrimination times (DTs). These findings show on the contrary to prior assumptions that olfaction is a “fast” sense and its temporal course depends on the complexity of odors (Abraham et al, Neuron 2004).
These findings argue that neural mechanisms contributing to odor discrimination must act
on a fast time scale, requiring only a brief moment of odor-specific spatiotemporal
representations to achieve rapid odor discrimination. Such olfactory representation can be
maintained in the OB plausibly by the inhibitory network, orchestrated by granule cells (GCs). I
tested this hypothesis by altering the excitability of GCs, through targeted deletion of AMPA and
NMDA receptors in GCs. GC specific GluA2 deletion resulted in reduced DTs for complex odors
and enhanced synaptic inhibition, whereas GluN1 deletion caused increased DTs for complex odors and reduced synaptic inhibition. In summary, these results show that DT differences for olfactory stimuli are initially generated in the OB by a dynamic balance between local excitation and inhibition (Abraham et al, Neuron 2010).
In the next step I investigated how the GC inhibition controls firing properties of output
neurons by directly correlating the behavior outputs with physiological changes. I established a head-restrained behavior paradigm and proved that behavior readouts using this strategy are similar to what we obtained by the freely moving strategy (Abraham et al., PLOS ONE 2012). By specific stimulation of GCs using Channelrhodopsin (ChR2), we could show enhancement of pattern separation by the output neurons (mitral/tufted cells), which helped the animals to learn complex odorant discrimination tasks faster than control subjects (Gschwend & Abraham et al., In preparation).
After studying the inhibitory networks in OB, I have focused on the sensory periphery to
investigate the factors controlling odor discrimination efficiency at the sensory input level.
Studying the glomerular activity patterns of different chemical classes at different concentrations
in trained and naïve mice showed that similarity and strength of glomerular activation define the
extent of neuronal processing as reflected in the DT measurements. Therefore the similarity of glomerular representations can be used as a neural metric to predict olfactory discrimination time (Abraham et al, in communication). Olfactory associative learning, but not passive odor exposure caused a potentiation at the sensory input level, which lasted several weeks after the end of discrimination training. This long-lasting plasticity we observed at the periphery should improve odor detection and contribute towards accurate and fast odor discriminations (Abraham et al, Revised, eLIFE).
The future goal is to focus on synaptic and molecular mechanisms of sensory perception
and decision-making by giving special attention to different inhibitory circuits of mouse olfactory
bulb. Initially my focus would be on basic mechanisms of synaptic inhibition, followed by
understanding behavioral neural networks in model organism.
| Joby Joseph Reader Center for Neural and Cognitive Sciences University of Hyderabad, India Ph: +918008531777 Fax: +914023134493 Web:Neuronal Systems Lab Alt email: jjcncs@uohyd.ernet.in |  |
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