Brian J. Fischer

Distinct sensory representations of wind and near-field sound in the Drosophila brain

Behavioural responses to wind are thought to have a critical role in controlling the dispersal and population genetics of wild Drosophila species, as well as their navigation in flight, but their underlying neurobiological basis is unknown. We show that Drosophila melanogaster, like wild-caught Drosophila strains, exhibits robust wind-induced suppression of locomotion in response to air currents delivered at speeds normally encountered in nature. Here we identify wind-sensitive neurons in Johnston’s organ, an antennal mechanosensory structure previously implicated in near-field sound detection (reviewed in refs 5 and 6). Using enhancer trap lines targeted to different subsets of Johnston’s organ neurons, and a genetically encoded calcium indicator, we show that wind and near-field sound (courtship song) activate distinct populations of Johnston’s organ neurons, which project to different regions of the antennal and mechanosensory motor centre in the central brain. Selective genetic ablation of wind-sensitive Johnston’s organ neurons in the antenna abolishes wind-induced suppression of locomotion behaviour, without impairing hearing. Moreover, different neuronal subsets within the wind-sensitive population respond to different directions of arista deflection caused by air flow and project to different regions of the antennal and mechanosensory motor centre, providing a rudimentary map of wind direction in the brain. Importantly, sound- and wind-sensitive Johnston’s organ neurons exhibit different intrinsic response properties: the former are phasically activated by small, bi-directional, displacements of the aristae, whereas the latter are tonically activated by unidirectional, static deflections of larger magnitude. These different intrinsic properties are well suited to the detection of oscillatory pulses of near-field sound and laminar air flow, respectively. These data identify wind-sensitive neurons in Johnston’s organ, a structure that has been primarily associated with hearing, and reveal how the brain can distinguish different types of air particle movements using a common sensory organ.

Owl's behavior and neural representation predicted by Bayesian inference

The owl captures prey using sound localization. In the classical model, the owl infers sound direction from the position of greatest activity in a brain map of auditory space. However, this model fails to describe the actual behavior. Although owls accurately localize sources near the center of gaze, they systematically underestimate peripheral source directions. We found that this behavior is predicted by statistical inference, formulated as a Bayesian model that emphasizes central directions. We propose that there is a bias in the neural coding of auditory space, which, at the expense of inducing errors in the periphery, achieves high behavioral accuracy at the ethologically relevant range. We found that the owls map of auditory space decoded by a population vector is consistent with the behavioral model. Thus, a probabilistic model describes both how the map of auditory space supports behavior and why this representation is optimal.

Cross-Correlation in the Auditory Coincidence Detectors of Owls

Interaural time difference (ITD) plays a central role in many auditory functions, most importantly in sound localization. The classic model for how ITD is computed was put forth by Jeffress (1948). One of the predictions of the Jeffress model is that the neurons that compute ITD should behave as cross-correlators. Whereas cross-correlation-like properties of the ITD-computing neurons have been reported, attempts to show that the shape of the ITD response function is determined by the spectral tuning of the neuron, a core prediction of cross-correlation, have been unsuccessful. Using reverse correlation analysis, we demonstrate in the barn owl that the relationship between the spectral tuning and the ITD response of the ITD-computing neurons is that predicted by cross-correlation. Moreover, we show that a model of coincidence detector responses derived from responses to binaurally uncorrelated noise is consistent with binaural interaction based on cross-correlation. These results are thus consistent with one of the key tenets of the Jeffress model. Our work sets forth both the methodology to answer whether cross-correlation describes coincidence detector responses and a demonstration that in the barn owl, the result is that expected by theory.

Forced Desynchrony Reveals Independent Contributions of Suprachiasmatic Oscillators to the Daily Plasma Corticosterone Rhythm in Male Rats

The suprachiasmatic nucleus (SCN) is required for the daily rhythm of plasma glucocorticoids; however, the independent contributions from oscillators within the different subregions of the SCN to the glucocorticoid rhythm remain unclear. Here, we use genetically and neurologically intact, forced desynchronized rats to test the hypothesis that the daily rhythm of the glucocorticoid, corticosterone, is regulated by both light responsive and light-dissociated circadian oscillators in the ventrolateral (vl-) and dorsomedial (dm-) SCN, respectively. We show that when the vlSCN and dmSCN are in maximum phase misalignment, the peak of the plasma corticosterone rhythm is shifted and the amplitude reduced; whereas, the peak of the plasma adrenocorticotropic hormone (ACTH) rhythm is also reduced, the phase is dissociated from that of the corticosterone rhythm. These data support previous studies suggesting an ACTH-independent pathway contributes to the corticosterone rhythm. To determine if either SCN subregion independently regulates corticosterone through the sympathetic nervous system, we compared unilateral adrenalectomized, desynchronized rats that had undergone either transection of the thoracic splanchnic nerve or sham transection to the remaining adrenal. Splanchnicectomy reduced and phase advanced the peak of both the corticosterone and ACTH rhythms. These data suggest that both the vlSCN and dmSCN contribute to the corticosterone rhythm by both reducing plasma ACTH and differentially regulating plasma corticosterone through an ACTH- and sympathetic nervous system-independent pathway.

Bilateral matching of frequency tuning in neural cross-correlators of the owl

Sound localization requires comparison between the inputs to the left and right ears. One important aspect of this comparison is the differences in arrival time to each side, also called interaural time difference (ITD). A prevalent model of ITD detection, consisting of delay lines and coincidence-detector neurons, was proposed by Jeffress (J Comp Physiol Psychol 41:35–39, 1948). As an extension of the Jeffress model, the process of detecting and encoding ITD has been compared to an effective cross-correlation between the input signals to the two ears. Because the cochlea performs a spectrotemporal decomposition of the input signal, this cross-correlation takes place over narrow frequency bands. Since the cochlear tonotopy is arranged in series, sounds of different frequencies will trigger neural activity with different temporal delays. Thus, the matching of the frequency tuning of the left and right inputs to the cross-correlator units becomes a ‘timing’ issue. These properties of auditory transduction gave theoretical support to an alternative model of ITD-detection based on a bilateral mismatch in frequency tuning, called the ‘stereausis’ model. Here we first review the current literature on the owl’s nucleus laminaris, the equivalent to the medial superior olive of mammals, which is the site where ITD is detected. Subsequently, we use reverse correlation analysis and stimulation with uncorrelated sounds to extract the effective monaural inputs to the cross-correlator neurons. We show that when the left and right inputs to the cross-correlators are defined in this manner, the computation performed by coincidence-detector neurons satisfies conditions of cross-correlation theory. We also show that the spectra of left and right inputs are matched, which is consistent with predictions made by the classic model put forth by Jeffress.

Effect of instantaneous frequency glides on interaural time difference processing by auditory coincidence detectors

Detecting interaural time difference (ITD) is crucial for sound localization. The temporal accuracy required to detect ITD, and how ITD is initially encoded, continue to puzzle scientists. A fundamental question is whether the monaural inputs to the binaural ITD detectors differ only in their timing, when temporal and spectral tunings are largely inseparable in the auditory pathway. Here, we investigate the spectrotemporal selectivity of the monaural inputs to ITD detector neurons of the owl. We found that these inputs are selective for instantaneous frequency glides. Modeling shows that ITD tuning depends strongly on whether the monaural inputs are spectrotemporally matched, an effect that may generalize to mammals. We compare the spectrotemporal selectivity of monaural inputs of ITD detector neurons in vivo, demonstrating that their selectivity matches. Finally, we show that this refinement can develop through spike timing-dependent plasticity. Our findings raise the unexplored issue of time-dependent frequency tuning in auditory coincidence detectors and offer a unifying perspective.

Variability Reduction in Interaural Time Difference Tuning in the Barn Owl

The interaural time difference (ITD) is the primary auditory cue used by the barn owl for localization in the horizontal direction. ITD is initially computed by circuits consisting of axonal delay lines from one of the cochlear nuclei and coincidence detector neurons in the nucleus laminaris (NL). NL projects directly to the anterior part of the dorsal lateral lemniscal nucleus (LLDa), and this area projects to the core of the central nucleus of the inferior colliculus (ICcc) in the midbrain. To show the selectivity of an NL neuron for ITD requires averaging of responses over several stimulus presentations for each ITD. In contrast, ICcc neurons detect their preferred ITD in a single burst of stimulus. We recorded extracellularly the responses of LLDa neurons to ITD in anesthetized barn owls and show that this ability is already present in LLDa, raising the possibility that ICcc inherits its noise reduction property from LLDa.

Estimated Cochlear Delays in Low Best-Frequency Neurons in the Barn Owl Cannot Explain Coding of Interaural Time Difference

The functional role of the low-frequency range (<3 kHz) in barn owl hearing is not well understood. Here, it was tested whether cochlear delays could explain the representation of interaural time difference (ITD) in this frequency range. Recordings were obtained from neurons in the core of the central nucleus of the inferior colliculus. The response of these neurons varied with the ITD of the stimulus. The response peak shared by all neurons in a dorsoventral penetration was called the array-specific ITD and served as criterion for the representation of a given ITD in a neuron. Array-specific ITDs were widely distributed. Isolevel frequency response functions obtained with binaural, contralateral, and ispilateral stimulation exhibited a clear response peak and the accompanying frequency was called the best frequency. The data were tested with respect to predictions of a model, the stereausis model, assuming cochlear delays as source for the best ITD of a neuron. According to this model, different cochlear delays determined by mismatches between the ipsilateral and contralateral best frequencies are the source for the ITD in a binaural neuron. The mismatch should depend on the best frequency and the best ITD. The predictions of the stereausis model were not fulfilled in the low best-frequency neurons analyzed here. It is concluded that cochlear delays are not responsible for the representation of best ITD in the barn owl.

Spatial cue reliability drives frequency tuning in the barn Owl's midbrain

The robust representation of the environment from unreliable sensory cues is vital for the efficient function of the brain. However, how the neural processing captures the most reliable cues is unknown. The interaural time difference (ITD) is the primary cue to localize sound in horizontal space. ITD is encoded in the firing rate of neurons that detect interaural phase difference (IPD). Due to the filtering effect of the head, IPD for a given location varies depending on the environmental context. We found that, in barn owls, at each location there is a frequency range where the head filtering yields the most reliable IPDs across contexts. Remarkably, the frequency tuning of space-specific neurons in the owls midbrain varies with their preferred sound location, matching the range that carries the most reliable IPD. Thus, frequency tuning in the owls space-specific neurons reflects a higher-order feature of the code that captures cue reliability. DOI: http://dx.doi.org/10.7554/eLife.04854.001

Population-wide bias of surround suppression in auditory spatial receptive fields of the owl’s midbrain

The physical arrangement of receptive fields (RFs) within neural structures is important for local computations. Nonuniform distribution of tuning within populations of neurons can influence emergent tuning properties, causing bias in local processing. This issue was studied in the auditory system of barn owls. The owls external nucleus of the inferior colliculus (ICx) contains a map of auditory space in which the frontal region is overrepresented. We measured spatiotemporal RFs of ICx neurons using spatial white noise. We found a population-wide bias in surround suppression such that suppression from frontal space was stronger. This asymmetry increased with laterality in spatial tuning. The bias could be explained by a model of lateral inhibition based on the overrepresentation of frontal space observed in ICx. The model predicted trends in surround suppression across ICx that matched the data. Thus, the uneven distribution of spatial tuning within the map could explain the topography of time-dependent tuning properties. This mechanism may have significant implications for the analysis of natural scenes by sensory systems.