Jayaraman Lab
Our lab is interested in establishing causal links between the dynamics of neural circuits and the behavioral decisions that an animal continuously makes as it navigates a multi-sensory world. We aim to uncover general principles about the neural representation of sensorimotor states and the functional organization and operation of small neural circuits. We use the powerful genetic model organism, Drosophila melanogaster, for our experiments, and work in close collaboration with several others at Janelia Farm. We have developed experimental tools to record neural activity in tethered walking and flying flies during behavior. We recently used these tools to find that neurons in an early visual area of the fly (the optic lobe) change their gain and even their tuning depending on the fly's behavioral state. We are now using a combination of two-photon imaging, electrophysiology, quantitative behavior, optogenetics and various computational techniques in our attempt to mechanistically link computation in sensorimotor circuits to the fly's adaptive behavioral decisions.
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Vivek Jayaraman Lab Head
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Johannes Seelig Research Staff
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Romain Franconville Postdoctoral Associate
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Chuntao Dan Research Staff
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Sung Soo Kim Postdoctoral Associate
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Sharon Kearney
Janelia Publications
Sensorimotor integration is a field rich in theory backed by a large body of psychophysical evidence. Relating the underlying neural circuitry to these theories has, however, been more challenging. With a wide array of complex behaviors coordinated by their small brains, insects provide powerful model systems to study key features of sensorimotor integration at a mechanistic level. Insect neural circuits perform both hard-wired and learned sensorimotor transformations. They modulate their neural processing based on both internal variables, such as the animal's behavioral state, and external ones, such as the time of day. Here we present some studies using insect model systems that have produced insights, at the level of individual neurons, about sensorimotor integration and the various ways in which it can be modified by context.
Changes in behavioral state modify neural activity in many systems. In some vertebrates such modulation has been observed and interpreted in the context of attention and sensorimotor coordinate transformations. Here we report state-dependent activity modulations during walking in a visual-motor pathway of Drosophila. We used two-photon imaging to monitor intracellular calcium activity in motion-sensitive lobula plate tangential cells (LPTCs) in head-fixed Drosophila walking on an air-supported ball. Cells of the horizontal system (HS)--a subgroup of LPTCs--showed stronger calcium transients in response to visual motion when flies were walking rather than resting. The amplified responses were also correlated with walking speed. Moreover, HS neurons showed a relatively higher gain in response strength at higher temporal frequencies, and their optimum temporal frequency was shifted toward higher motion speeds. Walking-dependent modulation of HS neurons in the Drosophila visual system may constitute a mechanism to facilitate processing of higher image speeds in behavioral contexts where these speeds of visual motion are relevant for course stabilization.
Drosophila melanogaster is a model organism rich in genetic tools to manipulate and identify neural circuits involved in specific behaviors. Here we present a technique for two-photon calcium imaging in the central brain of head-fixed Drosophila walking on an air-supported ball. The ball's motion is tracked at high resolution and can be treated as a proxy for the fly's own movements. We used the genetically encoded calcium sensor, GCaMP3.0, to record from important elements of the motion-processing pathway, the horizontal-system lobula plate tangential cells (LPTCs) in the fly optic lobe. We presented motion stimuli to the tethered fly and found that calcium transients in horizontal-system neurons correlated with robust optomotor behavior during walking. Our technique allows both behavior and physiology in identified neurons to be monitored in a genetic model organism with an extensive repertoire of walking behaviors.
Genetically encoded calcium indicators (GECIs) can be used to image activity in defined neuronal populations. However, current GECIs produce inferior signals compared to synthetic indicators and recording electrodes, precluding detection of low firing rates. We developed a single-wavelength GCaMP2-based GECI (GCaMP3), with increased baseline fluorescence (3-fold), increased dynamic range (3-fold) and higher affinity for calcium (1.3-fold). We detected GCaMP3 fluorescence changes triggered by single action potentials in pyramidal cell dendrites, with signal-to-noise ratio and photostability substantially better than those of GCaMP2, D3cpVenus and TN-XXL. In Caenorhabditis elegans chemosensory neurons and the Drosophila melanogaster antennal lobe, sensory stimulation-evoked fluorescence responses were significantly enhanced with GCaMP3 (4-6-fold). In somatosensory and motor cortical neurons in the intact mouse, GCaMP3 detected calcium transients with amplitudes linearly dependent on action potential number. Long-term imaging in the motor cortex of behaving mice revealed large fluorescence changes in imaged neurons over months.
Prior Publications (4)
Genetically encoded optical indicators hold the promise of enabling non-invasive monitoring of activity in identified neurons in behaving organisms. However, the interpretation of images of brain activity produced using such sensors is not straightforward. Several recent studies of sensory coding used G-CaMP 1.3-a calcium sensor-as an indicator of neural activity; some of these studies characterized the imaged neurons as having narrow tuning curves, a conclusion not always supported by parallel electrophysiological studies. To better understand the possible cause of these conflicting results, we performed simultaneous in vivo 2-photon imaging and electrophysiological recording of G-CaMP 1.3 expressing neurons in the antennal lobe (AL) of intact fruitflies. We find that G-CaMP has a relatively high threshold, that its signal often fails to capture spiking response kinetics, and that it can miss even high instantaneous rates of activity if those are not sustained. While G-CaMP can be misleading, it is clearly useful for the identification of promising neural targets: when electrical activity is well above the sensor's detection threshold, its signal is fairly well correlated with mean firing rate and G-CaMP does not appear to alter significantly the responses of neurons that express it. The methods we present should enable any genetically encoded sensor, activator, or silencer to be evaluated in an intact neural circuit in vivo in Drosophila.
Odors evoke complex responses in locust antennal lobe projection neurons (PNs)-the mitral cell analogs. These patterns evolve over hundreds of milliseconds and contain information about odor identity and concentration. In nature, animals often encounter many odorants in short temporal succession. We explored the effects of such conditions by presenting two different odors with variable intervening delays. PN ensemble representations tracked stimulus changes and, in some delay conditions, reached states that corresponded neither to the representation of either odor alone nor to the static mixture of the two. We then recorded from Kenyon cells (KCs), the PNs' targets. Their responses were consistent with the PN population's behavior: in some conditions, KCs were recruited that did not fire during single-odor or mixture stimuli. Thus, PN population dynamics are history dependent, and responses of individual KCs are consistent with piecewise temporal decoding of PN output over large sections of the PN population.
We examined the encoding and decoding of odor identity and intensity by neurons in the antennal lobe and the mushroom body, first and second relays, respectively, of the locust olfactory system. Increased odor concentration led to changes in the firing patterns of individual antennal lobe projection neurons (PNs), similar to those caused by changes in odor identity, thus potentially confounding representations for identity and concentration. However, when these time-varying responses were examined across many PNs, concentration-specific patterns clustered by identity, resolving the apparent confound. This is because PN ensemble representations changed relatively continuously over a range of concentrations of each odorant. The PNs' targets in the mushroom body-Kenyon cells (KCs)-had sparse identity-specific responses with diverse degrees of concentration invariance. The tuning of KCs to identity and concentration and the patterning of their responses are consistent with piecewise decoding of their PN inputs over oscillation-cycle length epochs.
