Ulisse Ferrari

Biologically grounded locality priors close the data gap for vision transformers in neural prediction

Matteo Farina, pietro zamberlan, Arno Onken, Ulisse Ferrari

Abstract For datasets with thousands of neurons and images, vision transformers have proven successful at predicting neural responses to stimuli. However, they are expected to underperform in low-data regimes, where CNNs and Gaussian processes are considered more effective. We ask whether transformers …

fr, gb (code pays fourni par la source)

Viability of engineered AAVs via protein language models

Mélissa Desrosiers, Tommaso Ocari, Jeanne Trinquier, Emilia A. Zin et autres

Abstract Capsid engineering has greatly improved the performance of recombinant AAV vectors used for gene therapy. One commonly used strategy is the insertion of a short, 7-mer, peptide into surface-exposed loops to modify receptor interactions and enhance cell entry. While effective in …

fr, jp (code pays fourni par la source)

Promfusion : a synthetic fusion promoter enabling enhanced and balanced photoreceptor transgene expression

Sophie Tran, Jeanne Trinquier, Timothé Van Meter, Emilia A. Zin et autres

Abstract Achieving efficient and balanced transgene expression in both rods and cones remains a major challenge in retinal gene therapy. Current promoters either lack specificity or fail to provide sufficient cellular coverage and expression level. To address this limitation, we developed and …

fr (code pays fourni par la source)

A multi-scale information geometry reveals the structure of mutual information in neural populations

Simone Azeglio, Steeve Laquitaine, Ulisse Ferrari, Matthew Chalk

Understanding how neural population responses represent sensory information is a central problem in systems neuroscience. One approach is to define a representational geometry on stimulus space in which distances reflect how reliably stimuli can be distinguished from neural activity. However, different constructions …

A multi-scale information geometry reveals the structure of mutual information in neural populations

Simone Azeglio, Steeve Laquitaine, Ulisse Ferrari, Matthew Chalk

Understanding how neural population responses represent sensory information is a central problem in systems neuroscience. One approach is to define a representational geometry on stimulus space in which distances reflect how reliably stimuli can be distinguished from neural activity. However, different constructions …

fr (code pays fourni par la source)

VIP+ amacrine cells synchronize neural activity in the retina

Déborah Varró, Samuele Virgili, Simone Ebert, Gabriel Mahuas et autres

In early sensory circuits, inhibitory interneurons are best known for mediating lateral inhibition, gain control, and feature selectivity, but their roles at the population level are less understood. Using two photon digital holography, we found that in the retina, vasoactive intestinal peptide …

fr (code pays fourni par la source)

Stimulus sensitivity in noisy neural systems

Carlo Paris, Steeve Laquitaine, Matthew Chalk, Ulisse Ferrari

Abstract Understanding how neural populations encode sensory information requires a precise definition of neuronal sensitivity to stimuli. While tuning curves and firing rates offer intuitive insights, theoretical frameworks based on signal-to-noise ratio and decoding efficiency identify Fisher information as the canonical measure …

fr (code pays fourni par la source)

Balanced spatiotemporal color responses are fine-tuned to natural light spectrum in mice ventral retina

Tom Quétu, Awen Louboutin, Filippo Castellani, Remi Baroux et autres

Color vision is vital for animal survival, essential for foraging and predator detection. In mice, as in other mammals, color vision originates in the retina, where photoreceptor signals are processed by neural circuits. However, retinal responses to stimuli involving multiple colors are …

fr, it (code pays fourni par la source)

Optimal sequencing depth for measuring the concentrations of molecular barcodes

Tommaso Ocari, Emilia A. Zin, Muge Tekinsoy, Timothé Van Meter et autres

In combinatorial genetic engineering experiments, next-generation sequencing (NGS) allows for measuring the concentrations of barcoded or mutated genes within highly diverse libraries. When designing and interpreting these experiments, sequencing depths are thus important parameters to take into account. Service providers follow established …

fr, it, jp (code pays fourni par la source)

Direction-selective retinal ganglion cells encode motion direction uniformly, despite having discretely distributed cardinal preferences

Félix Hubert, Felix Franke, Olivier Marre, Matthew Chalk et autres

On-Off direction-selective retinal ganglion cells (DS RGCs) exhibit broad tuning curves, responding robustly to motion aligned with or near their preferred direction. These cells comprise four major subtypes, each tuned to motion along one of the four cardinal axes: nasal, superior, temporal, …

fr, ch, ae (code pays fourni par la source)

Higher-Order Convolution Improves Neural Predictivity in the Retina

Simone Azeglio, Victor Calbiague Garcia, Guilhem Glaziou, Peter Neri et autres

We present a novel approach to neural response prediction that incorporates higher-order operations directly within convolutional neural networks (CNNs). Our model extends traditional 3D CNNs by embedding higher-order operations within the convolutional operator itself, enabling direct modeling of multiplicative interactions between neighboring …

fr (code pays fourni par la source)

Diagrammatic expansion for the mutual-information rate in the realm of limited statistics

Tobias Kühn, Gabriel Mahuas, Ulisse Ferrari

Neurons in sensory systems encode stimulus information into their stochastic spiking response. The mutual information has been extensively applied to these systems to quantify the neurons' capacity of transmitting such information. Yet, while for discrete stimuli, like flashed images or single tones, …

fr (code pays fourni par la source)