Cosyne 2009 Workshops
March 2-3, 2009
Snow Bird, Utah
Workshop Title
Olfactory coding: Many roles of neural plasticity in shaping odor codes
Organizer(s)
Maxim Bazhenov, University of California, Riverside (primary contact)
Mark Stopfer, NIH-NICHD
Abstract
The olfactory system maps complex and high-dimensional olfactory stimuli into unique and reproducible ensembles of neuronal activity. This mapping includes multilevel processing and involves complex strategies for information encoding. Recent work shows that several forms of neural plasticity, from the continued regeneration and integration of neurons (both primary and central), to spike-timing dependent plasticity, contribute to the establishment, maintenance, and transmission of odor codes. In this workshop we will discuss how olfactory stimuli are represented in the olfactory system, and how different forms of neural plasticity may improve and optimize odor encoding and decoding in the brain. The goal of this workshop is to bring together experimental and computational neuroscientists to discuss how neural plasticity contributes fundamentally to a well-characterized form of sensory processing.
Schedule
Morning session (8:10 – 11:00AM)
8:10 – 8:45 Nathalie Mandairon and Christiane Linster (Cornell University), Odor perception and olfactory bulb plasticity
8:45 – 9:20 Leslie Kay (The University of Chicago), Dynamic reconfiguration of olfactory processing networks
9:20 – 9:50 Break for coffee and discussion
9:50 - 10:25 Stuart Firestein (Columbia University), What happens to odors in the brain?
10:25 – 11:00 Michele Pignatelli (Brain Mind Institute, EPFL, Lausanne), Synaptic modulation of the Olfactory Bulb microcircuit output
Afternoon session (4:30 – 7:30PM)
4:30 – 5:05 Mark Stopfer (NIH-NICHD), Adaptive dynamics on multiple time scales for detecting salient features of natural odor stimuli
5:05 – 5:40 Maxim Bazhenov (University of California, Riverside), Plasticity mechanisms underlying frequency shifts in odor-evoked neural oscillations
5:40 - 6:10 Break for coffee & discussion
6:10 – 6:45 Stijn Cassenaer (Caltech), The consequences of STDP in the locust mushroom body
6:45 – 7:20 Brian Smith (Arizona State University), Plasticity in early olfactory processing ‘tunes’ neural networks to specific odor stimuli
Speakers
Nathalie Mandairon and Christiane Linster (Cornell University), Odor perception and olfactory bulb plasticity
Sensory processing involves a hierarchy of interconnected sensory, cortical and sub-cortical areas. When discussing these hierarchies and interactions, olfactory processing is often set apart due to their lack of direct thalamic pathways between sensory and cortical processing areas. Indeed, olfactory signals, after being received and transformed by sensory neurons, are projected directly to an anatomically well studied cortical structure, the olfactory bulb, with projections to the thalamus established further downstream of the pathway. A recent review has compared the olfactory bulb to the thalamus in its functional signal processing properties (Kay and Sherman, 2007). Here we review evidence showing that the olfactory bulb is more than a relay station or a feedforward filter but rather actively shapes, and is actively shaped by, olfactory perception. We discuss data showing how olfactory experience changes the olfactory bulb network and that manipulations of the olfactory bulb network change odor perception on a long timescale. We finally review in more detail a few experiments showing a tight correlation between the modulation olfactory bulb neural activity and odor processing. We argue that the olfactory bulb has evolved to be an adapting network, allowing animals to adjust olfactory computations to changing environments.
Leslie Kay (The University of Chicago), Dynamic reconfiguration of olfactory processing networks
Early stages of processing in the olfactory system are considered to consist of relatively static mechanisms, dictated by glomerular input patterns and local modulation. My lab and others have shown that changes in the temporal precision of principal excitatory neurons, is related to processing highly overlapping odorant input patterns. This precision is represented by gamma oscillations in the mammalian olfactory bulb. However, we have also shown that the structure of the task used to perform odor identification can influence the type of oscillatory mode, the involvement of central brain areas in primary odor processing, and the difficulty of the discrimination itself. In some tasks the processing mode switches to the lower frequency beta oscillation (~20 Hz). This oscillation mode is thus not just a different frequency but a different network, involving the entire limbic system. This larger and more distributed network is associated with more flexibility in learning odor associations.
Funding: NIDCD R01 DC007995 (CRCNS grant)
Stuart Firestein (Columbia University), What happens to odors in the brain?
Of all the senses, the olfactory system of mammals has the shortest pathway through the brain. From the peripheral olfactory epithelium, where odorants are first bound to receptors, to the piriform cortex where olfactory perceptions are presumably formed, there are only two projection synapses. The first of these occurs between the axons of incoming sensory fibers and the apical dendrites of mitral cells in the glomeruli of the olfactory bulb; the second is the between the mitral cell axons and pyramidal cells of the three layered olfactory cortex. Even in the taste system two synapses would take us no further than a mid brain nucleus, and in vision we would still be in the outer retina. How can so complex a stimulus as is presented by the chemical environment be processed with so little neural machinery?
Within these two synapses the system seems to take two opposed strategies. In the olfactory bulb information from receptors is strictly sorted with like axons converging into highly restricted glomeruli and maintained in an almost labeled line sort of organization. However mitral cell axons carrying information from these glomeruli are arranged in a highly distributed rather than modular organization in the piriform cortex. Thus piriform cortex contrasts with other sensory cortices in being a three layered, distributed tissue.
In order to understand how the olfactory system manages this processing feat we have taken the strategy of approaching function through development. IN this we follow the lead of Ramon y Cajal who so perceptively noted that, “Since the full grown forest turns out to be impenetrable and indefinable. why not revert to the study of the young wood, in the nursery stage, as we might say.” We will present developmental data that suggests possible models for understanding the emergence of perception from stimulus in such a short synaptic pathway.
Michele Pignatelli (Brain Mind Institute, EPFL, Lausanne), Synaptic modulation of the Olfactory Bulb microcircuit output
The surface of the mouse Olfactory Bulb (OB) is arranged in 1800 spherical structures known as glomeruli. Each glomerulus receives converging axons from olfactory receptor neurons (ORN) expressing the same olfactory receptor (OR) and mediates the interaction between ORN axons and Mitral and Tufted cells (M/T cells) apical dendrites. Action potentials generated in the soma of a M/T cell can backpropagate to the tuft of the apical dendrite triggering glutamate release and allowing M/T cells to interact synaptically. Multiple patch clamp electrophysiological recording coupled with anatomical staining allowed us to dissect the microcircuit connectivity characterizing synaptic properties such as kinetic and short-term plasticity. Microcircuit simulation suggests that synaptic connections are responsible for the synergistic expression of simple network operations like signal detection and amplification, short-term memory and network homeostasis. Synaptic interaction between M/T cells in the glomerular site tune and control the microcircuit output.
Mark Stopfer (NIH-NICHD), Adaptive dynamics on multiple time scales for detecting salient features of natural odor stimuli
As information moves through the brain, it is dramatically transformed in multiple steps in myriad ways. This restructuring process can be stimulus and history dependent, revealing the work of several forms of neural plasticity. Using natural types of odor presentations, we found evidence for both excitatory and inhibitory non-associative plasticity (changes induced simply by repeating stimuli) shaping the neural response to the odor at several time scales. By tracing the effects of plasticity as they cascade and compound through multiple layers of neurons, we found that they serve, at least in part, to extract salient features of natural stimuli.
In the locust, we found interneuronal responses to natural forms of odor stimuli are shaped by rapid adaptation in the receptors, and relatively enduring facilitation of inhibition within their downstream targets. Peripheral adaptation renders the olfactory system relatively insensitive to stimuli that repeat very rapidly; central facilitation of inhibition increases the reliability and sparseness of stimuli that are encountered repeatedly but relatively slowly. Together, these mechanisms appear to highlight the onset and offset and other prominent features of odor plumes. Further, these mechanisms constrain the principal neuron ensemble to provide relatively stable output to its downstream followers, thereby allowing the encoding of information about odor identity and concentration with firing patterns that are not confounded by the timing patterns of the stimulus. We support these observations with a computational model.
Maxim Bazhenov (University of California, Riverside), Plasticity mechanisms underlying frequency shifts in odor-evoked neural oscillations
In the insect olfactory system olfactory receptor neurons (ORNs) synapse onto a smaller group of excitatory projection neurons (PNs) and local inhibitory interneurons (LNs) in the antennal lobe (AL). The interaction between AL neurons produces spatiotemporal activity patterns that evolve over multiple time scales. In locusts, odor-evoked oscillation frequency varies only slightly over the course of an odor stimulus and over a wide range of concentrations. However, in the moth Manduca sexta oscillations induced by lengthy odor presentations (like those encountered during feeding) are initially fast (40 Hz for about 1 s) and then rapidly shift to a much slower rate (10-20 Hz for the remainder of the odor pulse); the oscillation frequency roughly tracks electroantennogram (EAG) amplitude. Interestingly, LFP recordings showed that the initial oscillation frequency was invariant over a wide range of odor concentrations whereas EAG amplitudes varied greatly with concentration. To explore this apparent contradiction, we developed a computer model of the moth AL including populations of synaptically coupled PNs and LNs. The model mimicked the sharp transition between discrete fast and slow oscillatory states when input intensity (ORN firing rates) gradually decreased. In contrast, recruiting additional, but less well-tuned, ORNs to simulate responses to higher concentrations did not affect oscillation frequency. Our results suggest that oscillation frequency shifts between two stable states, dependent upon the varying output intensity of adapting receptors, rather than upon the concentration of the odorant. Our model indicates this is possible if ORNs that are highly tuned for a given odor fire at near saturating rates even when presented with low odor concentrations, with higher concentrations recruiting additional ORNs.
Stijn Cassenaer (Caltech), The consequences of STDP in the locust mushroom body
Odor representations in insects undergo progressive transformations from the receptor array in the antenna, via the antennal lobe (AL), to the presumed site of odor learning, the mushroom body (MB). Broad activation of the AL by an olfactory stimulus gives rise to oscillatory population activity and diverging trajectories of projection neuron (PN) activation [1-7]. Different points along these trajectories can be thought of as representing different aspects of the odor stimulus, and cells that decode PN activity in the MB, Kenyon cells (KCs), respond sparsely at specific time-points along the PN trajectories [8]. Previous work suggests that individual oscillation cycles are meaningful units for the encoding and decoding of olfactory information by PNs and KCs, and this appears to be the case also for extrinsic neurons in the mushroom body beta-lobe (bLNs), which decode the KCs' sparse responses. I will describe the results of intracellular recordings made from KCs and bLNs to examine synaptic transmission, plasticity and odor representation in this circuit. We have found that KC-bLN synapses undergo Hebbian spike-timing dependent plasticity (STDP) on a timescale similar to the oscillatory population discharge, which is generated by the AL and propagated throughout the circuit [9]. This plasticity has a homeostatic effect on the phase of bLN firing, facilitates the synchronous flow of olfactory information, and maintains the segregation between oscillation cycles. We have found an additional component that contributes to this segregation, namely lateral inhibition among bLNs. We construct a simple network model to evaluate the consequences of the interaction between STDP and the competition among bLNs due to this phase-locked inhibition. Considered within the context of the circuit in which the KC-bLN network is embedded, these results suggest a mechanism for learning different aspects of an odor stimulus, after formatting as a function of oscillation cycle in the AL.
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Brian Smith (Arizona State University), Plasticity in early olfactory processing ‘tunes’ neural networks to specific odor stimuli
Both the mammalian Olfactory Bulb and its analog the insect Antennal Lobe are the first stations in the brain for synaptic processing of afferent sensory information about odors. Several lines of analysis have shown that plasticity for odor memories in part encoded in the neural networks of these two structures. Both structures are extensively innervated by neural processes that release monoamines (epinephrine in the OB and octopamine in the AL) in response to reinforcement. It is likely that these monoamines modify the neural networks of the OB and AL when an odor is associated with reinforcement. Accordingly, electrophysiological and imaging studies have revealed changes in the activity patterns induced by an odor after its association with reinforcement. However, it is unclear what these changes mean in regard to detection or discrimination of odors. To investigate this problem we associatively conditioned honey bees to discriminate odor mixtures that differ in the ratios of two components (9:1 vs 1:9, for example). The spatiotemporal activity patterns induced by these odors in the AL are distinct, and smooth transitions of the ratio produce smooth transitions in the AL activity pattern. When we condition honey bees to discriminate one odor mixture from the other the activity patterns become more distinct, which correlates to behavioral measures of discriminability. These data suggest that the AL is becoming tuned by reinforcement to separate odors that are relevant to solving a particular task at a given point in time, Because the OB and AL are very similar in regard to how odor sensory information is processed, including plasticity, it is likely that this plasticity is essential for effective detection and discrimination to occur.
