Fast-scale adaptive changes of directional tuning in fly tangential cells are explained by a static nonlinearity

Adaptation-induced modification of motion selectivity tuning in visual tectal neurons of adult zebrafish

In the developing brain, training-induced emergence of direction selectivity and plasticity of orientation tuning appear to be widespread phenomena. These are found in the visual pathway across different classes of vertebrates. Moreover, short-term plasticity of orientation tuning in the adult brain has been demonstrated in several species of mammals. However, it is unclear whether neuronal orientation and direction selectivity in nonmammalian species remains modifiable through short-term plasticity in the fully developed brain. To address this question, we analyzed motion tuning of neurons in the optic tectum of adult zebrafish by calcium imaging. In total, orientation and direction selectivity was enhanced by adaptation, responses of previously orientation-selective neurons were sharpened, and even adaptation-induced emergence of selectivity in previously nonselective neurons was observed in some cases. The different observed effects are mainly based on the relative distance between the previously preferred and the adaptation direction. In those neurons in which a shift of the preferred orientation or direction was induced by adaptation, repulsive shifts (i.e., away from the adapter) were more prevalent than attractive shifts. A further novel finding for visually induced adaptation that emerged from our study was that repulsive and attractive shifts can occur within one brain area, even with uniform stimuli. The type of shift being induced also depends on the difference between the adapting and the initially preferred stimulus direction. Our data indicate that, even within the fully developed optic tectum, short-term plasticity might have an important role in adjusting neuronal tuning functions to current stimulus conditions.

A neuronally based model of contrast gain adaptation in fly motion vision

Motion-sensitive neurons in the visual systems of many species, including humans, exhibit a depression of motion responses immediately after being exposed to rapidly moving images. This motion adaptation has been extensively studied in flies, but a neuronal mechanism that explains the most prominent component of adaptation, which occurs regardless of the direction of motion of the visual stimulus, has yet to be proposed. We identify a neuronal mechanism, namely frequency-dependent synaptic depression, which explains a number of the features of adaptation in mammalian motion-sensitive neurons and use it to model fly motion adaptation. While synaptic depression has been studied mainly in spiking cells, we use the same principles to develop a simple model for depression in a graded synapse. By incorporating this synaptic model into a neuronally based model for elementary motion detection, along with the implementation of a center-surround spatial band-pass filtering stage that mimics the interactions among a subset of visual neurons, we show that we can predict with remarkable success most of the qualitative features of adaptation observed in electrophysiological experiments. Our results support the idea that diverse species share common computational principles for processing visual motion and suggest that such principles could be neuronally implemented in very similar ways.

Stochastic characterization of small-scale algorithms for human sensory processing

Human sensory processing can be viewed as a functional H mapping a stimulus vector s into a decisional variable r. We currently have no direct access to r; rather, the human makes a decision based on r in order to drive subsequent behavior. It is this (typically binary) decision that we can measure. For example, there may be two external stimuli s([0]) and s([1]), mapped onto r([0]) and r([1]) by the sensory apparatus H; the human chooses the stimulus associated with largest r. This kind of decisional transduction poses a major challenge for an accurate characterization of H. In this article, we explore a specific approach based on a behavioral variant of reverse correlation techniques, where the input s contains a target signal corrupted by a controlled noisy perturbation. The presence of the target signal poses an additional challenge because it distorts the otherwise unbiased nature of the noise source. We consider issues arising from both the decisional transducer and the target signal, their impact on system identification, and ways to handle them effectively for system characterizations that extend to second-order functional approximations with associated small-scale cascade models.

Adaptation accentuates responses of fly motion-sensitive visual neurons to sudden stimulus changes

Adaptation in sensory and neuronal systems usually leads to reduced responses to persistent or frequently presented stimuli. In contrast to simple fatigue, adapted neurons often retain their ability to encode changes in stimulus intensity and to respond when novel stimuli appear. We investigated how the level of adaptation of a fly visual motion-sensitive neuron affects its responses to discontinuities in the stimulus, i.e. sudden brief changes in one of the stimulus parameters (velocity, contrast, grating orientation and spatial frequency). Although the neuron's overall response decreased gradually during ongoing motion stimulation, the response transients elicited by stimulus discontinuities were preserved or even enhanced with adaptation. Moreover, the enhanced sensitivity to velocity changes by adaptation was not restricted to a certain velocity range, but was present regardless of whether the neuron was adapted to a baseline velocity below or above its steady-state velocity optimum. Our results suggest that motion adaptation helps motion-sensitive neurons to preserve their sensitivity to novel stimuli even in the presence of strong tonic stimulation, for example during self-motion.

Adaptation changes directional sensitivity in a visual motion-sensitive neuron of the fly

The blowfly visual system is a well-suited model to investigate the functional consequences of adaptation. Similar to cortical motion-sensitive neurons, fly tangential cells are directional selective and adapt during prolonged stimulation. Here we demonstrate in a tangential cell large changes in directionality after adaptation with motion in one direction. Surprisingly, depending on stimulation parameters, sensitivity for motion in the adapted direction relative to the unadapted direction can be either enhanced or attenuated. A simple model reproduces our results. It only incorporates previously identified changes in contrast sensitivity with motion adaptation. Thus, novel forms of motion adaptation seem unnecessary.