14 papers · ranked by Valyu relevance
A. Sina Booeshaghi, Ingileif B. Hallgrímsdóttir, Ángel Gálvez-Merchán, Lior Pachter
Single-cell genomics analysis requires normalization of feature counts that stabilizes variance, accounts for variable cell sequencing depth, and preserves monotonicity of within-cell feature abundances. We show that normalization via an (additive in the raw counts) proportional fitting step followed by the logarithm…
Zaina A. Zayyad, John H. R. Maunsell, Jason N. MacLean
When multiple stimuli appear together in the receptive field of a visual cortical neuron, the response is typically close to the average of that neuron’s response to each individual stimulus. The departure from a linear sum of each individual response is referred to as normalization. In mammals, normalization has been…
Flaviano Morone, Shivang Rawat, David J. Heeger, Stefano Martiniani
Stability is a fundamental requirement for both biological and engineered neural circuits, yet it is surprisingly difficult to guarantee in the presence of recurrent interactions. Standard linear dynamical models of recurrent networks are sensitive to the precise values of the synaptic weights, since stability requires…
Flaviano Morone, Shivang Rawat, David J. Heeger, Stefano Martiniani
Stability is a fundamental requirement for both biological and engineered neural circuits, yet it is surprisingly difficult to guarantee in the presence of recurrent interactions. Standard linear dynamical models of recurrent networks are un-reasonably sensitive to the precise values of the synaptic weights, since…
Kunlun Wang, Kaoutar Ait-Ahmad, Sam Kupp, Zachary Sims + 7 more
Multiplexed tissue imaging (MTI) technologies enable high-dimensional spatial analysis of tumor microenvironments but face challenges with technical variability in staining intensities. Existing normalization methods, including Z-score, ComBat, and MxNorm, often fail to account for the heterogeneous, right-skewed…
Ziyue Wang, Dillon Lloyd, Shanshan Zhao, Alison Motsinger-Reif
In high-throughput sequencing studies, sequencing depth, which quantifies the total number of reads, varies across samples. Unequal sequencing depth can obscure true biological signals of interest and prevent direct comparisons between samples. To remove variability due to differential sequencing depth, taxa counts are…
Zeming Fang, Ilona Bloem, Catherine Olsson, Wei Ji Ma + 1 more
An influential account of neuronal responses in primary visual cortex is the normalized energy model. This model is often implemented as a two-stage computation. The first stage is the extraction of contrast energy, whereby a complex cell computes the squared and summed outputs of a pair of linear filters in quadrature…
Bo Yuan, Shulei Wang
Microbiome sequencing data normalization is crucial for eliminating technical bias and ensuring accurate downstream analysis. However, this process can be challenging due to the high frequency of zero counts in microbiome data. We propose a novel reference-based normalization method called normalization via rank…
H. Sebastian Seung
Normalization is a fundamental operation in image processing. Convolutional nets have evolved to include a large number of normalizations (29; 64; 65), and this architectural shift has proved essential for robust computer vision (27; 6; 48). Studies of biological vision, in contrast, have invoked just one or a few…
Deying Song, Douglas Ruff, Marlene Cohen, Chengcheng Huang
The size of a neuron’s receptive field increases along the visual hierarchy. Neurons in higher-order visual areas integrate information through a canonical computation called normalization, where neurons respond sublinearly to multiple stimuli in the receptive field. Neurons in the visual cortex exhibit highly…
Angus F. Chapman, Rachel N. Denison
Perception and neural activity are profoundly shaped by the spatial and temporal context of sensory input, which has been modeled by divisive normalization over space or time. However, theoretical work has largely treated normalization separately within these dimensions and has not explained how future stimuli can…
Gregory J. Hunt, Mark A. Dane, James E. Korkola, Laura M. Heiser + 1 more
High-throughput fluorescent microscopy is a popular class of techniques for studying tissues and cells through automated imaging and feature extraction of hundreds to thousands of samples. Like other high-throughput assays, these approaches can suffer from unwanted noise and technical artifacts that obscure the…
Hanneke Leegwater, Zhengzheng Zhang, Xiaobing Zhang, Thomas Hankemeier + 4 more
Sample collection can significantly affect measurements of relative lipid concentrations in cell line panels, hiding intrinsic biological properties of interest between cell lines. Most quality control steps in lipidomic data analysis focus on controlling technical variation. Correcting for the total amount of…
Saige Rutherford, Pieter Barkema, Ivy F. Tso, Chandra Sripada + 3 more
In this work, we expand the normative model repository introduced in Rutherford et al. (2022a) to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an updated online…