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Kemppainen, J.

Publications and source records attributed to Kemppainen, J..

4 recordsLinked to original sources

Associative learning reconfigures colour-guided behaviour in Drosophila larvae

Colour-guided behaviour can be innate or learned, yet how a numerically simple nervous system assigns value to spectral cues remains unresolved. We developed an automated differential-conditioning assay in which third-instar Drosophila larvae were trained with blue and green light, one of which was paired with electric shock. Wild-type larvae subsequently avoided the shock-paired colour, whereas naive controls showed no strong blue-green preference. This learned avoidance persisted when the relative intensity cue was transferred to the alternative colour, indicating that behavioural choice followed spectral identity rather than simply tracking the dimmer stimulus. Disruption of either the blue-sensitive Rh5 or green-sensitive Rh6 photoreceptor pathway significantly weakened the training-induced behavioural shift relative to wild type, with Rh5 mutants showing only a small residual shift. Complementary extracellular recordings confirmed light-evoked activity in the larval visual system, with robust responses to ultraviolet and broadband white illumination but smaller and more variable responses to blue and green light. Together, these results show that larvae can discriminate blue from green, demonstrating elementary colour vision; that associative experience reconfigures their colour-guided behaviour; and that both photoreceptor pathways contribute to this learned response. This paradigm separates learned spectral preference from baseline light preference and provides a tractable framework for linking defined sensory inputs to the circuit mechanisms of visual memory.

neuroscience↗

Synaptic high-frequency jumping synchronises vision to high-speed behaviour

During high-speed behaviour, animals must synchronise perception and action despite rapid environmental and self-generated motion. How neural systems achieve such precision remains unclear. Here we show how the housefly (Musca domestica) maintains visual accuracy during fast motion. Using intracellular and photomechanical recordings during saccade-like stimulation, we traced information flow from photoreceptors to large monopolar cells (LMCs). Visual neurons achieved record-high information sampling ([~]2,500 bits{middle dot}s-1) and synaptic transmission ([~]4,100 bits{middle dot}s-1), far exceeding previous estimates. We identify a previously unknown mechanism - synaptic high-frequency jumping - in which photoreceptor-LMC synapses dynamically shift transmission toward higher frequencies during saccades, extending visual bandwidth to [~]1,000 Hz, effectively eliminating synaptic delays, and quadrupling classical flicker-fusion limits ([~]230 Hz). Behavioural experiments show flies respond synchronously within [~]13-20 ms, even before photoreceptor responses peak. A biophysically realistic model reveals how photomechanical-stochastic-refractory quantal sampling co-adapts with saccadic behaviour: through self-motion, flies efficiently translate image motion into temporally-precise, predictive high-speed vision.

neuroscience↗

High-speed imaging of light-induced photoreceptor microsaccades in compound eyes

Inside compound eyes, photoreceptors contract to light changes, sharpening retinal images of the moving world in time. Current methods to measure these so-called photoreceptor microsaccades in living insects are spatially limited and technically challenging. Here, we present goniometric high-speed deep pseudopupil (GHS-DPP) microscopy to assess how the rhabdomeric insect photoreceptors and their microsaccades are organised across the compound eyes. This method enables non-invasive rhabdomere orientation mapping, whilst their microsaccades can be locally light-activated, revealing the eyes underlying active sampling motifs. By comparing the microsaccades in wild-type Drosophilas open rhabdom eyes to spam-mutant eyes, reverted to an ancestral fused rhabdom state, and honeybees fused rhabdom eyes, we show how different eye types sample light information. These results show different ways compound eyes initiate the conversion of spatial light patterns in the environment into temporal neural signals and highlight how this active sampling can evolve with insects visual needs.

neuroscience↗

Binocular Mirror-Symmetric Microsaccadic Sampling of Hyperacute 3D-Vision

Neural mechanisms behind stereopsis, which requires simultaneous disparity inputs from two eyes, have remained mysterious. Here we show how ultrafast mirror-symmetric photomechanical contractions in the frontal forward-facing left and right eye photoreceptors give Drosophila super-resolution 3D-vision. By interlinking multiscale in vivo assays with multiscale simulations, we reveal how these photoreceptor microsaccades - by verging, diverging and narrowing the eyes overlapping receptive fields - channel depth information, as phasic binocular image motion disparity signals in time. We further show how peripherally, outside stereopsis, microsaccadic sampling tracks a flying flys optic flow field to better resolve the world in motion. These results change our understanding of how insect compound eyes work and suggest a general dynamic stereo-information sampling strategy for animals, robots and sensors. Significance statementTo move efficiently, animals must continuously work out their x,y,z-positions in respect to real-world objects, and many animals have a pair of eyes to achieve this. How photoreceptors actively sample the eyes optical image disparity is not understood because this fundamental information-limiting step has not been investigated in vivo over the eyes whole sampling matrix. This integrative multiscale study will advance our current understanding of stereopsis from static image disparity comparison to a new morphodynamic active sampling theory. It shows how photomechanical photoreceptor microsaccades enable Drosophila super-resolution 3D-vision and proposes neural computations for accurately predicting these flies depth-perception dynamics, limits, and visual behaviors.

neuroscience↗