Graded Encoding of Food Odor Value in the Drosophila Brain

Odors are highly evocative, yet how and where in the brain odors derive meaning remains unknown. Our analysis of the Drosophila brain extends the role of a small number of hunger-sensing neurons to include food-odor value representation. In vivo two-photon calcium imaging shows the amplitude of food odor-evoked activity in neurons expressing Drosophila neuropeptide F (dNPF), the neuropeptide Y homolog, strongly correlates with food-odor attractiveness. Hunger elevates neural and behavioral responses to food odors only, although food odors that elicit attraction in the fed state also evoke heightened dNPF activity in fed flies. Inactivation of a subset of dNPF-expressing neurons or silencing dNPF receptors abolishes food-odor attractiveness, whereas genetically enhanced dNPF activity not only increases food-odor attractiveness but promotes attraction to aversive odors. Varying the amount of presented odor produces matching graded neural and behavioral curves, which can function to predict preference between odors. We thus demonstrate a possible motivationally scaled neural "value signal" accessible from uniquely identifiable cells

Representation of Time-Varying Stimuli by a Network Exhibiting Oscillations on a Faster Time Scale

Sensory processing is associated with gamma frequency oscillations (30–80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input; the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp. Author Summary Sensory processing of time-varying stimuli, such as speech, is associated with high-frequency oscillatory cortical activity, the functional significance of which is still unknown. One possibility is that the oscillations are part of a stimulus-encoding mechanism. Here, we investigate a computational model of such a mechanism, a spiking neuronal network whose intrinsic oscillations interact with external input (waveforms simulating short speech segments in a single acoustic frequency band) to encode stimuli that extend over a time interval longer than the oscillation's period. The network implements a temporally sparse encoding, whose robustness to time warping and neuronal noise we quantify. To our knowledge, this study is the first to demonstrate that a biophysically plausible model of oscillations occurring in the processing of auditory input may generate a representation of signals that span multiple oscillation cycles.National Science Foundation (DMS-0211505); Burroughs Wellcome Fund; U.S. Air Force Office of Scientific Researc

Encoding Odorant Identity by Spiking Packets of Rate-Invariant Neurons in Awake Mice

Background: How do neural networks encode sensory information? Following sensory stimulation, neural coding is commonly assumed to be based on neurons changing their firing rate. In contrast, both theoretical works and experiments in several sensory systems showed that neurons could encode information as coordinated cell assemblies by adjusting their spike timing and without changing their firing rate. Nevertheless, in the olfactory system, there is little experimental evidence supporting such model. Methodology/Principal Findings: To study these issues, we implanted tetrodes in the olfactory bulb of awake mice to record the odorant-evoked activity of mitral/tufted (M/T) cells. We showed that following odorant presentation, most M/T neurons do not significantly change their firing rate over a breathing cycle but rather respond to odorant stimulation by redistributing their firing activity within respiratory cycles. In addition, we showed that sensory information can be encoded by cell assemblies composed of such neurons, thus supporting the idea that coordinated populations of globally rateinvariant neurons could be efficiently used to convey information about the odorant identity. We showed that different coding schemes can convey high amount of odorant information for specific read-out time window. Finally we showed that the optimal readout time window corresponds to the duration of gamma oscillations cycles. Conclusion: We propose that odorant can be encoded by population of cells that exhibit fine temporal tuning of spiking activity while displaying weak or no firing rate change. These cell assemblies may transfer sensory information in spikin

Neural Representations of Airflow in Drosophila Mushroom Body

The Drosophila mushroom body (MB) is a higher olfactory center where olfactory and other sensory information are thought to be associated. However, how MB neurons of Drosophila respond to sensory stimuli other than odor is not known. Here, we characterized the responses of MB neurons to a change in airflow, a stimulus associated with odor perception. In vivo calcium imaging from MB neurons revealed surprisingly strong and dynamic responses to an airflow stimulus. This response was dependent on the movement of the 3rd antennal segment, suggesting that Johnston's organ may be detecting the airflow. The calyx, the input region of the MB, responded homogeneously to airflow on. However, in the output lobes of the MB, different types of MB neurons responded with different patterns of activity to airflow on and off. Furthermore, detailed spatial analysis of the responses revealed that even within a lobe that is composed of a single type of MB neuron, there are subdivisions that respond differently to airflow on and off. These subdivisions within a single lobe were organized in a stereotypic manner across flies. For the first time, we show that changes in airflow affect MB neurons significantly and these effects are spatially organized into divisions smaller than previously defined MB neuron types

Is there a space–time continuum in olfaction?

The coding of olfactory stimuli across a wide range of organisms may rely on fundamentally similar mechanisms in which a complement of specific odorant receptors on olfactory sensory neurons respond differentially to airborne chemicals to initiate the process by which specific odors are perceived. The question that we address in this review is the role of specific neurons in mediating this sensory system—an identity code—relative to the role that temporally specific responses across many neurons play in producing an olfactory perception—a temporal code. While information coded in specific neurons may be converted into a temporal code, it is also possible that temporal codes exist in the absence of response specificity for any particular neuron or subset of neurons. We review the data supporting these ideas, and we discuss the research perspectives that could help to reveal the mechanisms by which odorants become perceptions

Defensive marketing strategy in the prescription analgesic market

Thesis (M.S.)--Massachusetts Institute of Technology, Alfred P. Sloan School of Management, 1982.MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY.Bibliography: leaves 155-156.by Joseph J. Beshel.M.S

A Leptin Analog Locally Produced in the Brain Acts via a Conserved Neural Circuit to Modulate Obesity-Linked Behaviors in Drosophila

Leptin, a typically adipose-derived "satiety hormone," has a well-established role in weight regulation. Here we describe a functionally conserved model of genetically induced obesity in Drosophila by manipulating the fly leptin analog unpaired 1 (upd1). Unexpectedly, cell-type-specific knockdown reveals upd1 in the brain, not the adipose tissue, mediates obesity-related traits. Disrupting brain-derived upd1 in flies leads to all the hallmarks of mammalian obesity: increased attraction to food cues, increased food intake, and increased weight. These effects are mediated by domeless receptors on neurons expressing Drosophila neuropeptide F, the orexigenic mammalian neuropeptide Y homolog. In vivo two-photon imaging reveals upd1 and domeless inhibit this hedonic signal in fed animals. Manipulations along this central circuit also create hypersensitivity to obesogenic conditions, emphasizing the critical interplay between biological predisposition and environment in overweight and obesity prevalence. We propose adipose- and brain-derived upd/leptin may control differing features of weight regulation through distinct neural circuits

Olfactory oscillations: the what, how and what for

Olfactory system oscillations play out with beautiful temporal and behavioral regularity on the oscilloscope and seem to scream ‘meaning’. Always there is the fear that, although attractive, these symbols of dynamic regularity might be just seductive epiphenomena. There are now many studies that have isolated some of the neural mechanisms involved in these oscillations, and recent work argues that they are functional and even necessary at the physiological and cognitive levels. However, much remains to be done for a full understanding of their functions

A circadian output center controlling feeding:fasting rhythms in Drosophila.

Circadian rhythms allow animals to coordinate behavioral and physiological processes with respect to one another and to synchronize these processes to external environmental cycles. In most animals, circadian rhythms are produced by core clock neurons in the brain that generate and transmit time-of-day signals to downstream tissues, driving overt rhythms. The neuronal pathways controlling clock outputs, however, are not well understood. Furthermore, it is unclear how the central clock modulates multiple distinct circadian outputs. Identifying the cellular components and neuronal circuitry underlying circadian regulation is increasingly recognized as a critical step in the effort to address health pathologies linked to circadian disruption, including heart disease and metabolic disorders. Here, building on the conserved components of circadian and metabolic systems in mammals and Drosophila melanogaster, we used a recently developed feeding monitor to characterize the contribution to circadian feeding rhythms of two key neuronal populations in the Drosophila pars intercerebralis (PI), which is functionally homologous to the mammalian hypothalamus. We demonstrate that thermogenetic manipulations of PI neurons expressing the neuropeptide SIFamide (SIFa) as well as mutations of the SIFa gene degrade feeding:fasting rhythms. In contrast, manipulations of a nearby population of PI neurons that express the Drosophila insulin-like peptides (DILPs) affect total food consumption but leave feeding rhythms intact. The distinct contribution of these two PI cell populations to feeding is accompanied by vastly different neuronal connectivity as determined by trans-Tango synaptic mapping. These results for the first time identify a non-clock cell neuronal population in Drosophila that regulates feeding rhythms and furthermore demonstrate dissociable control of circadian and homeostatic aspects of feeding regulation by molecularly-defined neurons in a putative circadian output hub