National Institutes of Health

Eunice Kennedy Shriver National Institute of Child Health and Human Development

2017 Annual Report of the Division of Intramural Research

Olfactory Coding and Decoding by Neuron Ensembles

Mark Stopfer
  • Mark Stopfer, PhD, Head, Section on Sensory Coding and Neural Ensembles
  • Zane Aldworth, PhD, Staff Scientist
  • Alejandra Boronat Garcia, PhD, Postdoctoral Fellow
  • Yu-Shan Hung, PhD, Postdoctoral Fellow
  • Subhasis Ray, PhD, Postdoctoral Fellow
  • Kui Sun, MD, Technician
  • Brian Kim, BS, Postbaccalaureate Fellow

All animals need to know what is going on in the world around them. Brain mechanisms have thus evolved to gather and organize sensory information in order to build transient and sometimes enduring internal representations of the environment. Using relatively simple animals and focusing primarily on olfaction and gustation, we combine electrophysiological, anatomical, behavioral, computational, genetic, and other techniques to examine the ways in which intact neural circuits, driven by sensory stimuli, process information. Our work reveals basic mechanisms by which sensory information is transformed, stabilized, and compared, as it makes its way through the nervous system.

Oscillatory integration windows in neurons

Oscillatory synchronization of neurons occurs in many brain regions, including the olfactory systems of vertebrates and invertebrates, and is indispensable for precise olfactory coding. One mechanism by which oscillations have been proposed to influence coding is through the creation of cyclic integration windows—specific times within the oscillation cycle when synaptic input is most efficiently integrated by a post-synaptic neuron. Cyclic integration windows could allow a neuron to respond preferentially to spikes arriving from multiple presynaptic neurons coincidentally in a specific part of the cycle. Thus, coincidence detection mediated by integration windows could help read precise temporal codes for odors. Phase-specific effects of synaptic inputs have been described both in brain slices and in simulations. However, the existence of cyclic integration windows has not been demonstrated, and their functional requirements are unknown.

With paired local field potential (LFP) and intracellular recordings and controlled stimulus manipulations we directly test this idea in the locust olfactory system. We focused on the responses of Kenyon cells, which are high-order neurons in a brain area analogous to the vertebrate piriform cortex and which fire spikes when the animal is presented with an odor pulse. We found that inputs arriving in Kenyon cells sum most effectively in a preferred window of the oscillation cycle. With a computational model, we established that the non-uniform structure of noisy activity in the membrane potential helps mediate this process. Further experiments performed in vivo demonstrated that integration windows can form in the absence of inhibition and at a broad range of oscillation frequencies.

Our results establish that cyclic integration windows can be formed from very few ingredients: oscillatory input and noise in the membrane potential. Given the ubiquity of membrane noise, the mechanisms we describe likely apply to a wide variety of neurons that receive oscillatory inputs, with or without inhibition and across a range of frequencies. Our results reveal how a fundamental coincidence-detection mechanism in a neural circuit functions to decode temporally organized spiking.

Gustatory second-order neuron in the Drosophila brain

Little is known, in any species, about neural circuitry immediately following gustatory sensory neurons, which makes it difficult to know how gustatory information is processed by the brain. By genetically labeling and manipulating specific parts of the nervous system, we identified and characterized a bilateral pair of gustatory second-order neurons in Drosophila. Previous studies had already identified gustatory sensory neurons that relay information to distinct parts of the gnathal (sub-esophageal) ganglia. To identify candidate gustatory second-order neurons, we took an anatomical approach. We screened about 5,000 GAL4 driver strains for lines that label neural fibers innervating the gnathal ganglia. We then combined GRASP (GFP reconstitution across synaptic partners) with presynaptic labeling to visualize potential synaptic contacts between the dendrites of the candidate gustatory second-order neurons and the axonal terminals of Gr5a–expressing sensory neurons, which have been shown to respond to sucrose. Results of the GRASP analysis, followed by a single-cell analysis by FLP-out recombination, identified a specific pair of neurons that contact Gr5a axon terminals in both brain hemispheres and send axonal arborizations to a distinct region within the gnathal ganglia. To characterize the input and output branches, we expressed the fluorescence-tagged acetylcholine receptor subunit (Da7) and active-zone marker (Brp) in the gustatory second-order neurons, respectively.

We found that input sites of the gustatory second-order neurons overlaid GRASP–labeled synaptic contacts to Gr5a neurons, while presynaptic sites were broadly distributed throughout the neurons’ arborizations. GRASP analysis and further tests with a new version of GRASP that labels active synapses suggested that the identified second-order neurons receive synaptic inputs from Gr5a–expressing sensory neurons, but not from Gr66a–expressing sensory neurons, which respond to caffeine. The identified second-order neurons relay information from Gr5a–expressing sensory neurons to stereotypical regions in the gnathal ganglia. Our findings suggest an unexpected complexity for taste-information processing in the first relay of the gustatory system. We are presently following up on this work to identify additional second-order neurons and, with optical imaging and intracellular electrophysiology experiments, to characterize their functions and information-coding strategies.

Spatio-temporal coding of individual chemicals by the gustatory system

Four of the five major sensory systems (vision, olfaction, somatosensation, and audition) are thought to be encoded by spatio-temporal patterns of neural activity. The only exception is gustation. Gustatory coding by the nervous system is thought to be relatively simple: every chemical (‘tastant’) is associated with one of a small number of basic tastes, and the presence of a basic taste, rather than the specific tastant, is represented by the brain. In mammals as well as insects, five basic tastes are usually recognized: sweet, salty, sour, bitter, and umami. The neural mechanism for representing basic tastes is unclear. The most widely accepted postulate is that, in both mammals and insects, gustatory information is carried through labelled lines, that is, in separate channels, from the periphery to sites deep in the brain, of cells sensitive to a single basic taste. An alternate proposal is that the basic tastes are represented by populations of cells, with each cell sensitive to multiple basic tastes.

Testing these ideas requires determining, point-to-point, how tastes are initially represented within the population of receptor cells and how this representation is transformed as it moves to higher-order neurons. However, it has been highly challenging to deliver precisely timed tastants while recording cellular activity from directly connected cells at successive layers of the gustatory system. Using a new moth preparation, we designed a stimulus and recording system that allowed us to fully characterize the timing of tastant delivery and the dynamics of the tastant-elicited responses of gustatory receptor neurons and their mono-synaptically connected second-order gustatory neurons, before, during, and after tastant delivery.

Surprisingly, we found no evidence consistent with a basic taste model of gustation. Instead, we found that the moth’s gustatory system represents individual tastant chemicals as spatio-temporal patterns of activity distributed across the population of gustatory receptor neurons. Further, we found that the representations are transformed substantially, given that many types of gustatory receptor neurons converge broadly upon follower neurons. The results of our physiological and behavioral experiments suggest that the gustatory system encodes information not about basic taste categories but rather about the identities of individual tastants. Further, the information is carried not by labelled lines but rather by distributed, spatio-temporal activity, which is a fast and accurate code. The results provide a dramatically new view of taste processing.

A population of projection neurons that inhibits the lateral horn but excites the antennal lobe through chemical synapses in Drosophila

The insect antennal lobe is a useful model system in which to study neural computations. Drosophila has been a particularly beneficial model system because it offers numerous genetic tools for labeling and manipulating the activity of neurons. In the insect olfactory system, odor information is transferred from the antennal lobe to higher brain areas by projection neurons running through multiple antennal lobe tracts. In several species, one of these tracts, the mediolateral antennal lobe tract (mlALT), contains projection neurons expressing GABA, a neurotransmitter that usually elicits inhibition; in the Drosophila brain, the great majority of ventral projection neurons (vPNs) are GABAergic and project through this tract to a brain area called the lateral horn. Most projection neurons, which are excitatory (ePNs), project through the mALT to the lateral horn and another brain area, the mushroom body. Recent studies have shown that GABAergic vPNs play inhibitory roles at their axon terminals in the lateral horn. However, little is known about the properties and functions of vPNs at their dendritic branches in the antennal lobe.

We used genetic manipulations and optogenetic and patch clamp techniques to investigate the functional roles of vPNs in the antennal lobe. Surprisingly, our results show that specific activation of vPNs always elicits strong excitatory post-synaptic potentials in ePNs, even though most vPNs are GABAergic. Moreover, we found that the connections between vPNs and ePNs are mediated by direct chemical synapses rather than, as has been previously reported, by gap junctions. Neither pulses of GABA nor pharmacological or genetic blockade of GABAergic transmission gave results consistent with the involvement of GABA in vPN–ePN excitatory transmission. A possibility we cannot rule out is that GABAergic vPNs co-express an excitatory neurotransmitter and release it at specific compartments within cells; for example, GABA could be released at the axonal terminals in the lateral horn and an excitatory neurotransmitter released at the dendritic presynaptic terminals in the antennal lobe. Indeed, several examples of mammalian neurons that can release multiple fast excitatory or inhibitory neurotransmitters have been reported, such as spatially segregated release of GABA and ACh in the retina. These unexpected results suggest new roles for the vPN population in olfactory information processing.

Classification of odorants across layers in locust olfactory pathway

Olfactory processing takes place across multiple layers of neurons from the transduction of odorants in the periphery, to odor quality processing, learning, and decision making in higher olfactory structures. In insects, projection neurons in the antennal lobe send odor information to the Kenyon cells of the mushroom bodies and lateral horn neurons. To examine the odor information content in different structures of the insect brain (antennal lobe, mushroom bodies, and lateral horn), we designed a model of the olfactory network based on electrophysiological recordings made in vivo in the locust. We found that classification performance was better for all types of cells (projection neurons, lateral horn neurons, and Kenyon cells) when populations of cells were considered rather than individual cells. Classification success was even greater when the neurons constituting these populations were each tuned to different odor features. This finding therefore reflects an emergent network property. Odor classification improved with increasing stimulus duration: for similar odorants, Kenyon cells and lateral horn neuron ensembles reached optimal discrimination within the first 300–500 ms of the odor response. Performance improvement with time was much greater for a population of cells than for individual neurons. We conclude that, for projection neurons, lateral horn neurons, and Kenyon cells, ensemble responses are always much more informative than single-cell responses, despite the accumulation of noise along with odor information.

Additional Funding

  • NICHD Director’s Award for a collaborative grant written by Mark Stopfer and Chi-Hon Lee.

Publications

  1. Gupta N, Singh SS, Stopfer M. Oscillatory integration windows in neurons. Nat Commun 2016 7:13808.
  2. Shimizu K, Stopfer M. A population of projection neurons that inhibits the lateral horn but excites the antennal lobe through chemical synapses in Drosophila. Front Neural Circuits 2017 11:30.
  3. Reiter S, Campillo Rodriguez C, Sun K, Stopfer M. Spatiotemporal coding of individual chemicals by the gustatory system. J Neurosci 2015 35:12309-12321.
  4. Miyazaki T, Lin TY, Ito K, Lee CH, Stopfer M. A gustatory second-order neuron that connects sucrose-sensitive primary neurons and a distinct region of the gnathal ganglion in the Drosophila brain. J Neurogenet 2015 29(2-3):144-155.
  5. Sanda P, Kee T, Gupta N, Stopfer M, Bazhenov M. Classification of odorants across layers in locust olfactory pathway. J Neurophysiol 2016 115:2303-2316.

Collaborators

  • Maxim Bazhenov, PhD, Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA
  • Chi-Hon Lee, MD, PhD, Section on Neuronal Connectivity, NICHD, Bethesda, MD

Contact

For more information, email stopferm@mail.nih.gov or visit https://neuroscience.nih.gov/Faculty/Profile/mark-stopfer.aspx or https://irp.nih.gov/pi/mark-stopfer.

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