Biology subjects

Levelt, C. N.

Publications and source records attributed to Levelt, C. N..

9 recordsLinked to original sources

bioRxiv2026

Memory-based and surround-based pattern completion show distinct laminar profiles in human V1

Visual input is often incomplete, requiring the brain to infer missing information from prior experience or contextual cues. Establishing whether memory-derived and context-derived information shape pattern completion through shared or distinct top-down pathways is central to understanding how perception emerges from the integration of sensory input and prior knowledge. Across two experiments, we used 7T layer fMRI to measure activity in an occluded region of human V1 while participants viewed natural scenes. Memory-based completion was enabled by varying the level of exposure to full scene images before scanning, while surround-based completion was implemented via two scenes that were repeatedly presented in partially occluded form but never seen intact. In both fMRI experiments, category decoding in the occluded V1 region only emerged after multiple prior exposures, whereas novel scenes did not show reliable decoding. Repeated partially occluded scenes also supported decoding, despite the hidden region never being shown, consistent with surround-based pattern completion. Critically, mnemonic and surround-based pattern completion showed opposite laminar decoding profiles across V1 depths, with mnemonic feedback dominating deep layers, and surround-based feedback dominating superficial layers. Together, these findings suggest that completion in the early visual cortex depends on the sources of inferred information, revealing dissociable feedback pathways for memory- and context-driven inference.

neuroscience↗

bioRxiv2025

A multiomic network approach uncovers disease modifying mechanisms of inborn errors of metabolism

For many inborn errors of metabolism (IEM) the understanding of disease mechanisms remains limited in part explaining their unmet medical needs. We hypothesize that the expressivity of IEM disease phenotypes is affected by the activity of specific modifier pathways, which is controlled by rare and common polygenic variation. To identify these modulating pathways, we used RNA sequencing to generate molecular signatures of IEM in disease relevant tissues. We then integrated these disease signatures with multiomic data and gene regulatory networks generated from animal and human populations without overt IEM. We identified and subsequently validated glucocorticoid signaling as a candidate modifier of mitochondrial fatty acid oxidation disorders, and we re-capitulated complement signaling as a modifier of inflammation in Gaucher disease. Our work describes a novel approach that can overcome the rare disease-rare data dilemma, and reveal new IEM pathophysiology and potential drug targets using multiomics data in seemingly healthy populations. Take-home message: Multiomic data and gene regulatory networks derived from animal and human populations without overt IEM can be used to study disease mechanisms in inborn errors of metabolism.

genetics↗

bioRxiv2024

Visual experience-dependent auditory and visual plasticity in the mouse visual cortex

A lack of early visual experience causes pronounced auditory and visual cross-modal changes. However, the visual cortical region-specific cross-modal organization down to the single neuron level remains unknown. Here we used two-photon calcium imaging in awake mice that were reared in darkness from birth to map auditory and visual responsiveness of single neurons. We targeted neurons in the primary visual cortex (V1) and higher visual cortical areas (HVAs) that resemble the ventral and dorsal stream regions. We found that lateral dorsal stream areas showed a pronounced increase in auditory response strength, even after accounting for tone-induced whisker movement. Strikingly, this was accompanied by a decreased visual drive, measured in number of recruited neurons and response strength, although these visual effects were more widespread across cortical regions. Together, these results provide a comprehensive functional map of auditory and visual cross-modal changes after a lack of early visual experience across the mouse visual cortex. Moreover, our results suggest that a lack of visual drive of dorsal stream regions might provide an opportunity for remaining senses to take over.

neuroscience↗

bioRxiv2024

Experience-dependent predictions of feedforward and contextual information in mouse visual cortex

To navigate complex environments, the visual system must prioritize unexpected inputs or omissions over predictable sensory backgrounds. This saliency assignment is a hallmark of visual processing and depends on comparing visual feedforward inputs with learned contextual surrounds, a process often conceptualized as a difference computation. However, cortical circuitry poses fundamental challenges: visual contextual feedback is predominantly amplifying, and feedback-driven inhibitory neurons necessary for subtractive computations are relatively sparse. How then can complex contextual feedback be selectively compared with feedforward input at the level of individual neurons? Here, we show that divergent plasticity rules within single pyramidal neurons provide a solution to this problem. Using two-photon calcium imaging, we recorded layer 2/3 pyramidal cell responses in mouse primary visual cortex before and after visual familiarization. We dissociated feedforward and contextual signals by comparing responses to stimuli with and without an occluded sector. Repeated feedforward responses selectively weakened through adaptation and surround suppression, whereas contextual responses strengthened and generalized across scenes. These strengthened contextual inputs amplified non-adapted responses to novel images and drove neuronal activity when occlusion of feedforward input prevented surround suppression. This produced a conserved structure of feedforward and contextual responses across mice, monkeys, and humans. Ultimately, these results reveal a cellular mechanism for saliency assignment that does not require feedback-driven inhibition. Pyramidal neurons autonomously learn the generalized statistical structure of familiar contexts, allowing them to selectively amplify improbable inputs or omissions.

neuroscience↗

bioRxiv2023

Astrocyte CB1 receptors are required for inhibitory maturation and ocular dominance plasticity in the mouse visual cortex

Summary and IntroductionNeuronal circuits are shaped by experience. This happens much more readily in the young compared to the adult brain. The unique learning capacity of the young brain is regulated through postnatal critical periods, during which the ability of neuronal networks to re-wire is greatly enhanced1. Endocannabinoids, which signal through the cannabinoid CB1 receptor (CB1R), regulate several forms of neuronal plasticity2. In the developing neocortex, CB1Rs play a key role in the maturation of inhibitory circuits. For example, interfering with CB1R signaling during development disrupts inhibitory maturation in the prefrontal cortex3. In developing primary visual cortex (V1), endocannabinoid-mediated plasticity at inhibitory synapses regulates the maturation of inhibitory synaptic transmission, shifting synapses from an immature state characterized by strong short-term depression to a mature state with reduced short-term depression4,5. This maturation step correlates with the timing of the critical period. While CB1Rs were originally thought to reside mainly on presynaptic axon terminals, recent studies have highlighted an unexpected role for astrocytic CB1Rs in endocannabinoid mediated plasticity6-8. Here, we investigate the impact of cell-type specific removal of CB1Rs from interneurons or astrocytes on development of inhibitory synapses and network plasticity of V1. We show that removing CB1Rs from astrocytes interferes with maturation of inhibitory synaptic transmission in V1. In addition, it strongly reduces ocular dominance (OD) plasticity during the critical period. In contrast, removing interneuron CB1Rs leaves these processes intact. Our results reveal an unexpected role of astrocytic CB1Rs in critical period plasticity in V1, and highlight the involvement of glial cells in the plasticity and synaptic maturation of sensory circuits.

neuroscience↗

bioRxiv2023

Visuomotor experience induces functional and structural plasticity of chandelier cells

Detailed characterization of interneuron types in primary visual cortex (V1) has greatly contributed to understanding visual perception, yet the role of chandelier cells (ChCs) in visual processing remains poorly characterized. Using viral tracing we found that V1 ChCs predominantly receive monosynaptic input from local layer 5 pyramidal cells and higher-order cortical regions. Two-photon calcium imaging and convolutional neural network modelling revealed that ChCs are visually responsive but weakly selective for stimulus content. In mice running in a virtual tunnel, ChCs respond strongly to events known to elicit arousal, including locomotion and visuomotor mismatch. Repeated exposure of the mice to the virtual tunnel was accompanied by reduced visual responses of ChCs and structural plasticity of ChC boutons and axon initial segment length. Finally, ChCs only weakly inhibited pyramidal cells. These findings suggest that ChCs provide an arousal-related signal to layer 2/3 pyramidal cells that may modulate their activity and/or gate plasticity of their axon initial segments during behaviorally relevant events.

neuroscience↗

bioRxiv2023

Thalamic regulation of ocular dominance plasticity in adult visual cortex

Experience-dependent plasticity in the adult visual system is generally thought of as a cortical process. However, several recent studies have shown that perceptual learning or monocular deprivation can also induce plasticity in the adult dorsolateral geniculate nucleus (dLGN) of the thalamus. How plasticity in the thalamus and cortex interact in the adult visual system is ill understood. To assess the influence of thalamic plasticity on plasticity in primary visual cortex (V1), we made use of our previous finding that during the critical period, ocular dominance (OD) plasticity occurs in dLGN and requires thalamic synaptic inhibition. Using multielectrode recordings we find that this is also true in adult mice, and that in the absence of thalamic inhibition and plasticity, OD plasticity in adult V1 is absent. To study the influence of V1 on thalamic plasticity we silenced V1 and show that during the critical period, but not in adulthood, the OD shift in dLGN is partially caused by feedback from V1. We conclude that during adulthood, the thalamus plays an unexpectedly dominant role in experience-dependent plasticity in V1. Our findings highlight the importance of considering the thalamus as a potential source of plasticity in learning events that are typically thought of as cortical processes.

neuroscience↗

bioRxiv2020

SpecSeg: cross spectral power-based segmentation of neurons and neurites in chronic calcium imaging datasets

Imaging calcium signals in neurons of awake, behaving animals using single- or multi-photon microscopy facilitates the study of coding in large neural populations. Such experiments produce massive datasets requiring powerful methods to extract responses from hundreds of neurons. We present SpecSeg, a new open-source toolbox for 1) segmentation of regions of interest (ROIs) representing neuronal structures, 2) inspection and manual editing of ROIs, 3) neuropil correction and signal extraction and 4) matching of ROIs in sequential recordings. SpecSeg uses a novel method for ROI registration, based on temporal cross-correlations of low-frequency components derived by Fourier analysis, of each pixel with its neighbors. The approach is insightful and enables ROI detection around neurons or neurites. It works for single- (miniscope) and multi-photon microscopy data, eliminating the need for separate toolboxes. SpecSeg thus provides an efficient and user-friendly approach for analyzing calcium responses in neuronal structures imaged over prolonged periods of time.

neuroscience↗

bioRxiv2020

A parameter-free statistical test that improves the detection of neuronal responsiveness

Neurophysiological studies depend on a reliable quantification of whether and when a neuron responds to stimulation. Simple methods to determine responsiveness require arbitrary parameter choices, such as binning size, while more advanced model-based methods require fitting and hyperparameter tuning. These parameter choices can change the results, which invites bad statistical practice and reduces the replicability. New recording techniques that yield increasingly large numbers of cells would benefit from a test for cell-inclusion that requires no manual curation. Here, we present the parameter-free ZETA-test, which outperforms t-tests, ANOVAs, and renewal-process-based methods by including more cells at a similar false-positive rate. We show that our procedure works across brain regions and recording techniques, including calcium imaging and Neuropixels data. Furthermore, in illustration of the method, we show in mouse visual cortex that 1) visuomotor-mismatch and spatial location are encoded by different neuronal subpopulations; and 2) optogenetic stimulation of VIP cells leads to early inhibition and subsequent disinhibition.

neuroscience↗