Biology subjects

Busse, L.

Publications and source records attributed to Busse, L..

13 recordsLinked to original sources

bioRxiv2026

Ethological variability shapes the structure and content of sensory population codes

Established theories of sensory coding posit that sensory systems are adapted to the statistics of natural stimuli that originate in the external environment. In natural, ethological conditions, however, sensory populations are simultaneously influenced by multiple modulatory processes. During behavior, the statistics of population responses already at the sensory periphery reflect not only external signals, but also internal and behavioral states such as locomotion, attention, and arousal. Theories of sensory coding in real-world conditions must therefore explain adaptation not only to natural scenes, but also to the structured variability induced by these internal processes and behavior. Here, we investigated population activity in the dorsal lateral geniculate nucleus (dLGN), a critical early stage of the visual pathway. Using a simple probabilistic model and information-theoretic approaches, we characterized this variability through the statistics of the population messages conveyed downstream. Our results show that population variability is multidimensional: even when one behavioral factor is constant, responses can vary substantially as other modulatory factors fluctuate. Under natural conditions, sensory population codes can therefore change their statistical structure and content, i.e., the stimulus features they encode along multiple dimensions simultaneously. These findings highlight the need for sensory coding theories that account not only for adaptation to natural stimuli, but also to the statistics of internal and behavioral states.

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bioRxiv2026

Learning stabilizes temporal activity but not neuronal selectivity in prefrontal cortex

Intelligent behavior requires neural representations to change with new demands while preserving learned structure. The prefrontal cortex is central to this ability, but the mechanisms are unclear. Here, we tracked medial prefrontal neurons for months as mice learned an association task with successive rule switches. Learning progressively stabilized when individual neurons were active during a trial, but not what task variables they responded to. Neurons repeatedly gained, lost, or changed selectivity even after their activity profile had stabilized. We developed Sparse Tensor Component Analysis to show that, rather than reflecting random drift, dynamic single-neuron selectivity arose through rule-dependent recombination of a fixed set of task representations. Thus, learning established a stable temporal scaffold in the prefrontal cortex within which neurons participated flexibly in different representations.

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bioRxiv2024

Anatomically resolved oscillatory bursts orchestrate visual thalamocortical activity during naturalistic stimulus viewing

Natural vision involves encoding of complex visual input, which engages a plethora of interacting circuit mechanisms. In the mammalian forebrain, one signature of such interacting circuit mechanisms is fast oscillatory dynamics, which can be reflected in the local field potential (LFP). We here used data from the Allen Neuropixels Visual Coding project to show that local visual features in naturalistic stimuli induce retinotopically specific V1 oscillations in various frequency bands. These LFP oscillations occurred in bursts, were localized to specific V1 layers, and were associated with phase coupling of V1 translaminar spiking, pointing to feature-specific circuit motifs. Finally, we discovered that these visually-induced circuit motifs occurred across a range of stimuli, suggesting that they might constitute general routes for feature-specific information flow. Together, our analyses demonstrate visually-induced, fast oscillations, which likely reflect the operation of distinct mesoscale circuits for the differential and multiplexed coding of complex visual input and feature-specific thalamo-cortical information propagation.

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bioRxiv2024

A hemispheric dome setup for naturalistic visual stimulation in head-fixed mice

The visual system of any animal species is adapted to its ecological niche. Thus, investigating visual function and behavior using naturalistic stimuli holds significant potential. In mice, these adaptations include a field of view of [~]280{degrees} and cone opsins sensitive to UV and green wavelengths. Such adaptations, however, cannot be probed with standard consumer displays. To present naturalistic visual stimuli to mice, we built a hemispheric dome setup, enabling the controlled projection of wide-field movies with UV-green spectral content. For our UV-green projection, we used a customized light engine with external high-power LEDs. We mitigated spatial distortions introduced by the projection through a geometry-independent calibration procedure. Additionally, we adapted a head-mounted eye tracking system to capture behavioral responses of head-fixed mice viewing these stimuli. We validated our setup by quantifying the pupillary light reflex to uniform stimuli and the optokinetic reflex to drifting gratings. Finally, in experiments with naturalistic movies, we investigated whether mice showed differential saccades and eye positions based on visual input. Comparing naturalistic movies to a uniform screen control condition, we observed that although head-fixed mice did not make targeted saccades during movies, their overall eye position consistently shifted towards more frontal regions of visual space. This indicates that mice adjust their eye position in a stimulus-dependent way, potentially to optimize visual processing of information ahead in the visual field. Together, our results highlight the utility of our setup for in vivo studies of the mouse visual system with more naturalistic visual stimulation. Significance StatementOver the past decades, mice have emerged as a prominent model for vision. Nonetheless, compared to primates, mice inhabit a different visual niche, featuring several species-specific adaptations, including a wide field of view and sensitivity to UV light. Both adaptations cannot be adequately studied using consumer displays commonly employed in vision research. We therefore built a hemispheric dome setup allowing the presentation of wide field movies with appropriate spectral content and tracking eye movements and pupil dynamics in head-fixed mice with minimal shadows. We provide a baseline assessment of the setup leveraging two well-established eye reflexes. We also showcase the setups utility by reporting adjustments in eye movements when mice viewed the naturalistic movies.

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bioRxiv2023

Effects of non-retinal inputs in visual thalamus depend on visual responsiveness and stimulus context

In the dorsolateral geniculate nucleus (dLGN) of the thalamus, stimulus-driven signals are combined with modulatory inputs such as corticothalamic (CT) feedback and behavioural state. How these shape dLGN activity remains an open question. We recorded extracellular responses in dLGN of awake mice to a movie stimulus, while photosuppressing CT feedback, and tracking locomotion and pupil size. To assess the relative impact of stimulus and modulatory inputs, we fit single neuron responses with generalized linear models. While including CT feedback and behavioural state as predictors significantly improved the models overall performance, the improvement was especially pronounced for a subpopulation of neurons poorly responsive to the movie stimulus. In addition, the observed impact of CT feedback was faster and more prevalent in the absence of a patterned visual stimulus. Finally, for neurons that were sensitive to CT feedback, visual stimuli could be more easily discriminated based on spiking activity when CT feedback was suppressed. Together, these results show that effects of modulatory inputs in dLGN depend on visual responsiveness and stimulus type.

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bioRxiv2022

Efficient coding of natural scenes improves neural system identification

Neural system identification aims at learning the response function of neurons to arbitrary stimuli using experimentally recorded data, but typically does not leverage normative principles such as efficient coding of natural environments. Visual systems, however, have evolved to efficiently process input from the natural environment. Here, we present a normative network regularization for system identification models by incorporating, as a regularizer, the efficient coding hypothesis, which states that neural response properties of sensory representations are strongly shaped by the need to preserve most of the stimulus information with limited resources. Using this approach, we explored if a system identification model can be improved by sharing its convolutional filters with those of an autoencoder which aims to efficiently encode natural stimuli. To this end, we built a hybrid model to predict the responses of retinal neurons to noise stimuli. This approach did not only yield a higher performance than the "stand-alone" system identification model, it also produced more biologically-plausible filters. We found these results to be consistent for retinal responses to different stimuli and across model architectures. Moreover, our normatively regularized model performed particularly well in predicting responses of direction-of-motion sensitive retinal neurons. In summary, our results support the hypothesis that efficiently encoding environmental inputs can improve system identification models of early visual processing.

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bioRxiv2021

Pupil size dynamics predict dLGN firing mode over a wide range of timescales

The processing of sensory information, even at early processing stages, is influenced by the internal state of the animal. Internal states, such as arousal, are often characterized by relating neural activity to a single "level" of arousal, defined by a behavioral indicator such as pupil size. In this study, we expand the understanding of arousal-related modulations in sensory systems by uncovering multiple timescales of pupil dynamics and their relationship to neural activity. Specifically, we observed coupling between spiking activity in the mouse dorsal lateral geniculate nucleus (dLGN) of the thalamus and pupil dynamics across timescales spanning three orders of magnitude, from seconds to minutes. Throughout all of these timescales, two distinct spiking patterns - tonic spikes and bursts - preferred opposing phases of pupil dynamics. This multi-scale coupling captures modulations distinct from those captured by pupil size per se, transitions between locomotion and quiescence, or saccadic eye movements. Furthermore, coupling persisted even during viewing of a naturalistic movie, where it contributed to differences in how visual information was encoded. We conclude that dLGN spiking activity is influenced by arousal processes associated with pupil dynamics occurring simultaneously across a broad range of timescales, with implications for the transfer of sensory information to the cortex.

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bioRxiv2020

Mouse retinal specializations reflect knowledge of natural environment statistics

Pressures for survival drive sensory circuit adaption to a species habitat, making it essential to statistically characterise natural scenes. Mice, a prominent visual system model, are dichromatic with enhanced sensitivity to green and UV. Their visual environment, however, is rarely considered. Here, we built a UV-green camera to record footage from mouse habitats. We found chromatic contrast to greatly diverge in the upper but not the lower visual field, an environmental difference that may underlie the species superior colour discrimination in the upper visual field. Moreover, training an autoencoder on upper but not lower visual field scenes was sufficient for the emergence of colour-opponent filters. Furthermore, the upper visual field was biased towards dark UV contrasts, paralleled by more light-offset-sensitive cells in the ventral retina. Finally, footage recorded at twilight suggests that UV promotes aerial predator detection. Our findings support that natural scene statistics shaped early visual processing in evolution. Lead contactFurther information and requests for resources and reagents should be directed to and will be fulfilled by the Lead Contact, Thomas Euler (thomas.euler@cin.uni-tuebingen.de)

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bioRxiv2020

Corticothalamic feedback sculpts visual spatial integration in mouse thalamus

En route from retina to cortex, visual information passes through the dorsolateral geniculate nucleus of the thalamus (dLGN), where extensive corticothalamic (CT) feedback has been suggested to modulate spatial processing. How this modulation arises from direct excitatory and indirect inhibitory CT feedback pathways remains enigmatic. Here we show that in awake mice, retinotopically organized cortical feedback sharpens receptive fields (RFs) and increases surround suppression in the dLGN. Guided by a network model indicating that widespread inhibitory CT feedback is necessary to reproduce these effects, we targeted the visual sector of the thalamic reticular nucleus (visTRN) for recordings. We found that visTRN neurons have large receptive fields, show little surround suppression, and exhibit strong feedback-dependent responses to large stimuli. These features make them an ideal candidate for mediating feedback-enhanced surround suppression in the dLGN. We conclude that cortical feedback sculpts spatial integration in dLGN, likely via recruitment of neurons in visTRN.

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bioRxiv2019

Robust effects of cortical feedback on thalamic firing mode during naturalistic stimulation

Neurons in the dorsolateral geniculate nucleus (dLGN) of the thalamus receive a substantial proportion of modulatory inputs from corticothalamic (CT) feedback and brain stem nuclei. Hypothesizing that these modulatory influences might be differentially engaged depending on the visual stimulus and behavioral state, we performed in vivo extracellular recordings from mouse dLGN while optogenetically suppressing CT feedback and monitoring behavioral state by locomotion and pupil dilation. For naturalistic movie clips, we found CT feedback to consistently increase dLGN response gain and promote tonic firing. In contrast, for gratings, CT feedback effects on firing rates were mixed. For both stimulus types, the neural signatures of CT feedback closely resembled those of behavioral state, yet effects of behavioral state on responses to movies persisted even when CT feedback was suppressed. We conclude that CT feedback modulates visual information on its way to cortex in a stimulus-dependent manner, but largely independently of behavioral state.

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bioRxiv2018

Mouse dLGN receives input from a diverse population of retinal ganglion cells with limited convergence

In the mouse, the parallel output of more than 30 functional types of retinal ganglion cells (RGCs) serves as the basis for all further visual processing. Little is known about how the representation of visual information changes between the retina and the dorsolateral geniculate nucleus (dLGN) of the thalamus, the main relay station between the retina and cortex. Here, we functionally characterized responses of retrogradely labeled dLGN-projecting RGCs and dLGN neurons to the same set of visual stimuli. We found that many of the previously identified functional RGC types innervate the dLGN, which maintained a high degree of functional diversity. Using a linear model to assess functional connectivity between RGC types and dLGN neurons, we found that the responses of dLGN neurons could be predicted as a linear combination of inputs from on average five RGC types, but only two of those had the strongest functional impact. Thus, mouse dLGN receives input from a diverse population of RGCs with limited functional convergence.

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bioRxiv2018

Layer 3 dynamically coordinates columnar activity during spatial integration in mouse V1

Spatial integration is a fundamental, context-dependent neural operation that involves extensive neural circuits across cortical layers of V1. To better understand how spatial integration is dynamically coordinated across layers we recorded single- and multi-unit activity and local field potentials across V1 layers of awake mice, and used dynamic Bayesian model comparisons to identify when laminar activity and inter-laminar functional interactions showed surround suppression, the hallmark of spatial integration. We found that surround suppression is strongest in layer 3 (L3) and L4 activity, showing rapidly sharpening receptive fields and increasing suppression strength. Importantly, we also found that specific directed functional connections were strongest for intermediate stimulus sizes and suppressed for larger ones, particularly for the L3->L5 and L3->L1 connections. Taken together, the results shed light on the different functional roles of cortical layers in spatial integration and show how L3 dynamically coordinates activity across a cortical column depending on spatial context.

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bioRxiv2016

Learning enhances sensory processing in mouse V1 before improving behavior

A fundamental property of visual cortex is to enhance the representation of those stimuli that are relevant for behavior, but it remains poorly understood how such enhanced representations arise during learning. Using classical conditioning in mice, we show that orientation discrimination is learned in a sequence of distinct behavioral stages, in which animals first rely on stimulus appearance before exploiting its orientation to guide behavior. After confirming that orientation discrimination under classical conditioning requires primary visual cortex (V1), we measured, during learning, response properties of V1 neurons. Learning improved neural discriminability, sharpened orientation tuning and led to higher contrast sensitivity. Remarkably, these learning-related improvements in the V1 representation were fully expressed before successful orientation discrimination was evident in the animals behavior. We propose that V1 plays a key role early in discrimination learning to enhance behaviorally relevant sensory information.

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