Off Pathway
OFF pathway
How fly neurons compute the direction of visual motion
Detecting the direction of image motion is important for visual navigation, predator avoidance and prey capture, and thus essential for the survival of all animals that have eyes. However, the direction of motion is not explicitly represented at the level of the photoreceptors: it rather needs to be computed by subsequent neural circuits, involving a comparison of the signals from neighboring photoreceptors over time. The exact nature of this process represents a classic example of neural computation and has been a longstanding question in the field. Much progress has been made in recent years in the fruit fly Drosophila melanogaster by genetically targeting individual neuron types to block, activate or record from them. Our results obtained this way demonstrate that the local direction of motion is computed in two parallel ON and OFF pathways. Within each pathway, a retinotopic array of four direction-selective T4 (ON) and T5 (OFF) cells represents the four Cartesian components of local motion vectors (leftward, rightward, upward, downward). Since none of the presynaptic neurons is directionally selective, direction selectivity first emerges within T4 and T5 cells. Our present research focuses on the cellular and biophysical mechanisms by which the direction of image motion is computed in these neurons.
How fly neurons compute the direction of visual motion
Detecting the direction of image motion is important for visual navigation, predator avoidance and prey capture, and thus essential for the survival of all animals that have eyes. However, the direction of motion is not explicitly represented at the level of the photoreceptors: it rather needs to be computed by subsequent neural circuits. The exact nature of this process represents a classic example of neural computation and has been a longstanding question in the field. Our results obtained in the fruit fly Drosophila demonstrate that the local direction of motion is computed in two parallel ON and OFF pathways. Within each pathway, a retinotopic array of four direction-selective T4 (ON) and T5 (OFF) cells represents the four Cartesian components of local motion vectors (leftward, rightward, upward, downward). Since none of the presynaptic neurons is directionally selective, direction selectivity first emerges within T4 and T5 cells. Our present research focuses on the cellular and biophysical mechanisms by which the direction of image motion is computed in these neurons.
A Flash of Darkness within Dusk: Crossover inhibition in the mouse retina
To survive in the wild small rodents evolved specialized retinas. To escape predators, looming shadows need to be detected with speed and precision. To evade starvation, small seeds, grass, nuts and insects need to also be detected quickly. Some of these succulent seeds and insects may be camouflaged offering only low contrast targets.Moreover, these challenging tasks need to be accomplished continuously at dusk, night, dawn and daytime. Crossover inhibition is thought to be involved in enhancing contrast detectionin the microcircuits of the inner plexiform layer of the mammalian retina. The AII amacrine cells are narrow field cells that play a key role in crossover inhibition. Our lab studies the synaptic physiology that regulates glycine release from AII amacrine cellsin mouse retina. These interneurons receive excitation from rod and conebipolar cells and transmit excitation to ON-type bipolar cell terminals via gap junctions. They also transmit inhibition via multiple glycinergic synapses onto OFF bipolar cell terminals.AII amacrine cells are thus a central hub of synaptic information processing that cross links the ON and the OFF pathways. What are the functions of crossover inhibition? How does it enhance contrast detection at different ambient light levels? How is the dynamicrange, frequency response and synaptic gain of glycine release modulated by luminance levels and circadian rhythms? How is synaptic gain changed by different extracellular neuromodulators, like dopamine, and by intracellular messengers like cAMP, phosphateand Ca2+ ions from Ca2+ channels and Ca2+ stores? My talk will try to answer some of these questions and will pose additional ones. It will end with further hypothesis and speculations on the multiple roles of crossover inhibition.
The Dark Side of Vision: Resolving the Neural Code
All sensory information – like what we see, hear and smell – gets encoded in spike trains by sensory neurons and gets sent to the brain. Due to the complexity of neural circuits and the difficulty of quantifying complex animal behavior, it has been exceedingly hard to resolve how the brain decodes these spike trains to drive behavior. We now measure quantal signals originating from sparse photons through the most sensitive neural circuits of the mammalian retina and correlate the retinal output spike trains with precisely quantified behavioral decisions. We utilize a combination of electrophysiological measurements on the most sensitive ON and OFF retinal ganglion cell types and a novel deep-learning based tracking technology of the head and body positions of freely-moving mice. We show that visually-guided behavior relies on information from the retinal ON pathway for the dimmest light increments and on information from the retinal OFF pathway for the dimmest light decrements (“quantal shadows”). Our results show that the distribution of labor between ON and OFF pathways starts already at starlight supporting distinct pathway-specific visual computations to drive visually-guided behavior. These results have several fundamental consequences for understanding how the brain integrates information across parallel information streams as well as for understanding the limits of sensory signal processing. In my talk, I will discuss some of the most eminent consequences including the extension of this “Quantum Behavior” paradigm from mouse vision to monkey and human visual systems.