A minimal synaptic model for direction selective neurons in Drosophila

Visual motion estimation is a canonical neural computation. In Drosophila, recent advances have identified anatomical and functional circuitry underlying direction-selective computations. Models with varying levels of abstraction have been proposed to explain specific experimental results, but have rarely been compared across experiments. Here we construct a minimal, biophysically inspired synaptic model for Drosophila’s first-order direction-selective T4 cells using the wealth of available anatomical and physiological data. We show how this model relates mathematically to classical models of motion detection, including the Hassenstein-Reichardt correlator model. We used numerical simulation to test how well this synaptic model could reproduce measurements of T4 cells across many datasets and stimulus modalities. These comparisons include responses to sinusoid gratings, to apparent motion stimuli, to stochastic stimuli, and to natural scenes. Without fine-tuning this model, it sufficed to reproduce many, but not all, response properties of T4 cells. Since this model is flexible and based on straightforward biophysical properties, it provides an extensible framework for developing a mechanistic understanding of T4 neural response properties. Moreover, it can be used to assess the sufficiency of simple biophysical mechanisms to describe features of the direction-selective computation and identify where our understanding must be improved.

Neural Correlates and Mechanisms of Spatial Release From Masking: Single-Unit and Population Responses in the Inferior Colliculus

Spatial release from masking (SRM), a factor in listening in noisy environments, is the improvement in auditory signal detection obtained when a signal is separated in space from a masker. To study the neural mechanisms of SRM, we recorded from single units in the inferior colliculus (IC) of barbiturate-anesthetized cats, focusing on low-frequency neurons sensitive to interaural time differences. The stimulus was a broadband chirp train with a 40-Hz repetition rate in continuous broadband noise, and the unit responses were measured for several signal and masker (virtual) locations. Masked thresholds (the lowest signal-to-noise ratio, SNR, for which the signal could be detected for 75% of the stimulus presentations) changed systematically with signal and masker location. Single-unit thresholds did not necessarily improve with signal and masker separation; instead, they tended to reflect the units' azimuth preference. Both how the signal was detected (through a rate increase or decrease) and how the noise masked the signal response (suppressive or excitatory masking) changed with signal and masker azimuth, consistent with a cross-correlator model of binaural processing. However, additional processing, perhaps related to the signal's amplitude modulation rate, appeared to influence the units' responses. The population masked thresholds (the most sensitive unit's threshold at each signal and masker location) did improve with signal and masker separation as a result of the variety of azimuth preferences in our unit sample. The population thresholds were similar to human behavioral thresholds in both SNR value and shape, indicating that these units may provide a neural substrate for low-frequency SRM.

Improving Mark III Correlator Models After Correlation

Weak objects such as stars can only be mapped with VLBI using phase-referencing techniques. Phase-reference mapping is highly sensitive to imperfect interferometer delay models, and therefore cannot generally be performed on data from MKIII correlators for source separations of more than a few minutes of arc. An AIPS task has been developed to replace the correlator model in a UV data set with the VLBA correlator model (CALC 8.0). It is mainly intended for MKIII data which was read into AIPS via the task MK3IN, but can also be used to improve the precision of phase-reference mapping of VLBA data by correcting wrong apriori geometric information. A second task can replace the atmospheric model used in the correlator with measured values and an improved mapping function.