Biology subjects

Nejatbakhsh, A.

Publications and source records attributed to Nejatbakhsh, A..

6 recordsLinked to original sources

bioRxiv2025

Quantifying Differences in Neural Population Activity With Shape Metrics

Quantifying differences across species and individuals is fundamental to many fields of biology. However, it remains challenging to draw detailed functional comparisons between large populations of interacting neurons. Here, we introduce a general framework for comparing neural population activity in terms of shape distances. This approach defines similarity in terms of explicit geometric transformations, which can be flexibly specified to obtain different measures of population-level neural similarity. Moreover, differences between systems are defined by a distance that is symmetric and satisfies the triangle inequality, enabling downstream analyses such as clustering and nearest-neighbor regression. We demonstrate this approach on datasets spanning multiple behavioral tasks (navigation, passive viewing of images, and decision making) and species (mice and non-human primates), highlighting its potential to measure functional variability across subjects and brain regions, as well as its ability to relate neural geometry to animal behavior.

neuroscience↗

bioRxiv2022

Versatile Multiple Object Tracking in Sparse 2D/3D Videos Via Diffeomorphic Image Registration

Tracking body parts in behaving animals, extracting fluorescence signals from cells embedded in deforming tissue, and analyzing cell migration patterns during development all require tracking objects with partially correlated motion. As dataset sizes increase, manual tracking of objects becomes prohibitively inefficient and slow, necessitating automated and semi-automated computational tools. Unfortunately, existing methods for multiple object tracking (MOT) are either developed for specific datasets and hence do not generalize well to other datasets, or require large amounts of training data that are not readily available. This is further exacerbated when tracking fluorescent sources in moving and deforming tissues, where the lack of unique features and sparsely populated images create a challenging environment, especially for modern deep learning techniques. By leveraging technology recently developed for spatial transformer networks, we propose ZephIR, an image registration framework for semi-supervised MOT in 2D and 3D videos. ZephIR can generalize to a wide range of biological systems by incorporating adjustable parameters that encode spatial (sparsity, texture, rigidity) and temporal priors of a given data class. We demonstrate the accuracy and versatility of our approach in a variety of applications, including tracking the body parts of a behaving mouse and neurons in the brain of a freely moving C. elegans. We provide an open-source package along with a web-based graphical user interface that allows users to provide small numbers of annotations to interactively improve tracking results.

neuroscience↗

bioRxiv2021

Visualizing the organization and differentiation of the male-specific nervous system of C. elegans

Sex differences in the brain are prevalent throughout the animal kingdom and particularly well appreciated in the nematode C. elegans. While 294 neurons are shared between the two sexes, the nervous system of the male contains an additional 93 malespecific neurons, most of which have received very little attention so far. To make these neurons amenable for future study, we describe here how a multicolor, multipromoter reporter transgene, NeuroPAL, is capable of visualizing the distinct identities of all male specific neurons. We used this tool to visualize and characterize a number of features of the male-specific nervous system. We provide several proofs of concept for using NeuroPAL to identify the sites of expression of gfp-tagged reporter genes. We demonstrate the usage of NeuroPAL for cellular fate analysis by analyzing the effect of removal of developmental patterning genes, including a HOX cluster gene (egl-5), a miRNA (lin-4) and a proneural gene (lin-32/Ato), on neuronal identity acquisition within the male-specific nervous system. We use NeuroPAL and its intrinsic cohort of more than 40 distinct differentiation markers to show that, even though male-specific neurons are generated throughout all four larval stages, they execute their terminal differentiation program in a coordinated manner in the fourth larval stage that is concomitant with male tale retraction. This wave of differentiation couples neuronal maturation programs with the appearance of sexual organs. We call this wave "just-in-time" differentiation by its analogy to the mechanism of "just-in-time" transcription of metabolic pathway genes.

neuroscience↗

bioRxiv2020

Predicting perturbation effects from resting state activity using functional causal flow

A crucial challenge in targeted manipulation of neural activity is to identify perturbation sites whose stimulation exerts significant effects downstream (high efficacy), a procedure currently achieved by labor-intensive trial-and-error. Targeted perturbations will be greatly facilitated by understanding causal interactions within neural ensembles and predicting the efficacy of perturbation sites before intervention. Here, we address this issue by developing a computational framework to predict how single-site micorstimulation alters the ensemble spiking activity in an alert monkeys prefrontal cortex. Our framework uses delay embedding techniques to infer the ensembles functional causal flow (FCF) based on the functional interactions inferred at rest. We validate FCF using ground truth data from models of cortical circuits, showing that FCF is robust to noise and can be inferred from brief recordings of even a small fraction of neurons in the circuit. A detailed comparison of FCF with several alternative methods, including Granger causality and transfer entropy, highlighted the advantages of FCF in predicting perturbation effects on empirical data. Our results provide the foundation for using targeted circuit manipulations to develop targeted interventions suitable for brain-machine interfaces and ameliorating cognitive dysfunctions in the human brain.

neuroscience↗

bioRxiv2020

Extracting neural signals from semi-immobilized animals with deformable non-negative matrix factorization

Extracting calcium traces from populations of neurons is a critical step in the study of the large-scale neural dynamics that govern behavior. Accurate activity extraction requires the correction of motion and movement-induced deformations as well as demixing of signals that may overlap spatially due to limitations in optical resolution. Traditionally, non-negative matrix factorization (NMF) methods have been successful in demixing and denoising cellular calcium activity in relatively motionless or pre-registered videos. However, standard NMF methods fail in animals undergoing significant non-rigid motion; similarly, standard image registration methods based on template matching can fail when large changes in activity lead to mismatches with the image template. To address these issues simultaneously, we introduce a deformable non-negative matrix factorization (dNMF) framework that jointly optimizes registration with signal demixing. On simulated data and real semi-immobilized C. elegans microscopy videos, dNMF outperforms traditional demixing methods that account for motion and demixing separately. Finally, following the extraction of neural traces from multiple imaging experiments, we develop a quantile regression time-series normalization technique to account for varying neural signal intensity baselines across different animals or different imaging setups. Open source code implementing this pipeline is available at https://github.com/amin-nejat/dNMF.

neuroscience↗

bioRxiv2019

NeuroPAL: A Neuronal Polychromatic Atlas of Landmarks for Whole-Brain Imaging in C. elegans

Comprehensively resolving single neurons and their cellular identities from whole-brain fluorescent images is a major challenge. We achieve this in C. elegans through the engineering and use of a multicolor transgene called NeuroPAL (a Neuronal Polychromatic Atlas of Landmarks). NeuroPAL worms share a stereotypical multicolor fluorescence map for the entire hermaphrodite nervous system that allows comprehensive determination of neuronal identities. Neurons labeled with NeuroPAL do not exhibit fluorescence in the green, cyan, or yellow emission channels, allowing the transgene to be used with numerous reporters of gene expression or neuronal dynamics. Here we showcase three studies that leverage NeuroPAL for nervous-system-wide neuronal identification. First, we determine the brainwide expression patterns of all metabotropic receptors for acetylcholine, GABA, and glutamate, completing a map of this communication network. Second, we uncover novel changes in cell fate caused by transcription factor mutations. Third, we record brainwide activity in response to attractive and repulsive chemosensory cues, characterizing multimodal coding and novel neuronal asymmetries for these stimuli. We present a software package that enables semi-automated determination of all neuronal identities based on color and positional information. The NeuroPAL framework and software provide a means to design landmark atlases for other tissues and organisms. In conclusion, we expect NeuroPAL to serve as an invaluable tool for gene expression analysis, neuronal fate studies, and for mapping whole-brain activity patterns.

neuroscience↗