Biology subjects

Poleg-Polsky, A.

Publications and source records attributed to Poleg-Polsky, A..

8 recordsLinked to original sources

bioRxiv2025

Machine Learning Discovers Numerous New Computational Principles Supporting Elementary Motion Detection

Motion direction detection is a fundamental visual computation that transforms spatial luminance patterns into directionally tuned outputs. Classical models of direction selectivity rely on temporal asymmetry, where motion detection arises through either delayed excitation or inhibition. Here, I used biologically inspired machine learning applied to retinal and cortical circuits to uncover multiple novel feedforward architectures capable of direction selectivity. These include mechanisms based on asymmetric synaptic properties, spatial receptive field variations, new roles for pre- and postsynaptic inhibition, and previously unrecognized kinetic implementations. Conceptually, these circuit architectures cluster into eight computational primitives underlying motion detection, four of which are newly discovered. Many of the solutions rival or outperform classical models in both robustness and precision, and several exhibit enhanced noise tolerance. All mechanisms are biologically plausible and correspond to known physiological and anatomical motifs, offering fresh insights into motion processing and illustrating how machine learning can uncover general principles of neural computation.

neuroscience↗

bioRxiv2024

Neural substrates for saccadic modulation of visual representations in mouse superior colliculus

How do sensory systems account for stimuli generated by natural behavior? We addressed this question by examining how an ethologically relevant class of saccades modulates visual representations in the mouse superior colliculus (SC), a key region for sensorimotor integration. We quantified saccadic modulation by recording SC responses to visual probes presented at stochastic saccade-probe latencies. Saccades significantly impacted population representations of the probes, with early enhancement that began prior to saccades and pronounced suppression for several hundred milliseconds following saccades, independent of units visual response properties or directional tuning. To determine the cause of saccadic modulation, we presented fictive saccades that simulated the visual experience during saccades without motor output. Some units exhibited similar modulation by fictive and real saccades, suggesting a sensory-driven origin of saccadic modulation, while others had dissimilar modulation, indicating a motor contribution. These findings advance our understanding of the neural basis of natural visual coding.

neuroscience↗

bioRxiv2024

Neural Net Derived Gene Targets For The Nervous System, & Nervous System Derived Hierarchies For The Neural Net

This paper introduces a machine learning approach, GraSP, for retinal cell classification that addresses key challenges in spatial biology, alongside a novel neural network architecture, CuttleNet, tailored for class and subclass inference with incomplete datasets. We propose an innovative, unbiased gene selection method that utilizes simple neural networks for each target cell subclass, such that Gradient Selected Predictors (GraSP) corresponding to gene importance are found for each. This approach significantly outperforms traditional machine learning techniques and expert-selected gene targets, reducing the necessary genes for classification from over 18k to 300 within the murine retina. Such reduction is crucial for advancing spatial biology, particularly in mapping retinal cell subclasses. Furthermore, our hierarchical architecture inspired by the organization of the cephalopod nervous system, CuttleNet, adeptly handles the pervasive issue of missing data in disjointed single-cell RNA sequencing datasets. CuttleNet operates by first classifying cell classes using consistently measured genes, then dynamically routing to subclass-specific subnetworks that leverage all available data for subclass classification. CuttleNet establishes a new standard in handling systematically missing data, offering substantial improvements over existing models in our targeted application.

bioinformatics↗

bioRxiv2023

Long-term in vivo three-photon imaging reveals region-specific differences in healthy and regenerative oligodendrogenesis

The generation of new myelin-forming oligodendrocytes in the adult CNS is critical for cognitive function and regeneration following injury. Oligodendrogenesis varies between gray and white matter regions suggesting that local cues drive regional differences in myelination and the capacity for regeneration. Yet, the determination of regional variability in oligodendrocyte cell behavior is limited by the inability to monitor the dynamics of oligodendrocytes and their transcriptional subpopulations in white matter of the living brain. Here, we harnessed the superior imaging depth of three-photon microscopy to permit long-term, longitudinal in vivo three-photon imaging of an entire cortical column and underlying subcortical white matter without cellular damage or reactivity. Using this approach, we found that the white matter generated substantially more new oligodendrocytes per volume compared to the gray matter, yet the rate of population growth was proportionally higher in the gray matter. Following demyelination, the white matter had an enhanced population growth that resulted in higher oligodendrocyte replacement compared to the gray matter. Finally, deep cortical layers had pronounced deficits in regenerative oligodendrogenesis and restoration of the MOL5/6-positive oligodendrocyte subpopulation following demyelinating injury. Together, our findings demonstrate that regional microenvironments regulate oligodendrocyte population dynamics and heterogeneity in the healthy and diseased brain.

neuroscience↗

bioRxiv2023

Heterogeneous presynaptic receptive fields contribute to directional tuning in starburst amacrine cells.

The processing of visual information by retinal starburst amacrine cells (SACs) involves transforming excitatory input from bipolar cells (BCs) into directional calcium output. While previous studies have suggested that an asymmetry in the kinetic properties of bipolar cells along the soma-dendritic axes of the postsynaptic cell could enhance directional tuning at the level of individual branches, it remains unclear whether biologically relevant presynaptic kinetics contribute to direction selectivity when visual stimulation engages the entire dendritic tree. To address this question, we built multicompartmental models of the bipolar-SAC circuit and trained them to boost directional tuning. We report that despite significant dendritic crosstalk and dissimilar directional preferences along the dendrites that occur during whole-cell stimulation, the rules that guide BC kinetics leading to optimal directional selectivity are similar to the single-dendrite condition. To correlate model predictions to empirical findings, we utilized two-photon glutamate imaging to study the dynamics of bipolar release onto ON- and OFF- starburst dendrites in the murine retina. We reveal diverse presynaptic dynamics in response to motion in both BC populations; algorithms trained on the experimental data suggested that the differences in the temporal release kinetics are likely to correspond to heterogeneous receptive field (RF) properties among the different BC types, including the spatial extent of the center and surround components. In addition, we demonstrate that circuit architecture composed of presynaptic units with experimentally recorded dynamics could enhance directional drive but not to levels that replicate empirical findings, suggesting other DS mechanisms are required to explain SAC function. Our study provides new insights into the complex mechanisms underlying direction selectivity in retinal processing and highlights the potential contribution of presynaptic kinetics to the computation of visual information by starburst amacrine cells.

neuroscience↗

bioRxiv2021

Novel Object Detection and Multiplexed Motion Representation in Retinal Bipolar Cells

Antagonistic interactions between the center and surround receptive field (RF) components lie at the heart of the computations performed in the visual system. Center-surround RFs are thought to enhance responses to spatial contrasts (i.e., edges), but how they contribute to motion processing is unknown. Here, we addressed this question in retinal bipolar cells, the first visual neuron with classic center-surround interactions. We found that bipolar glutamate release emphasizes objects that emerge in the RF; their responses to continuous motion are smaller, slower, and cannot be predicted by signals elicited by stationary stimuli. The alteration in signal dynamics induced by novel objects dwarfs the enhancement of spatial edges and can be explained by priming of RF surround during continuous motion. These findings echo the salience of human visual perception and demonstrate an unappreciated capacity of the center-surround architecture to facilitate novel object detection and multiplexed encoding of distinct sensory modalities.

neuroscience↗

bioRxiv2018

Dendritic spikes expand the range of well-tolerated population noise structures

The brain operates surprisingly well despite the noisy nature of individual neurons. The central mechanism for noise mitigation in the nervous system is thought to involve averaging over multiple noise-corrupted inputs. Subsequently, there has been considerable interest recently to identify noise structures that can be averaged out to preserve reliable signal encoding. By analyzing realistic synaptic integration in biophysically accurate neuronal models, I report a role for a complementary de-noising approach mediated by focal dendritic spikes. Dendritic spikes might seem unlikely candidates for noise reduction due to their miniscule integration compartments and poor averaging abilities. Nonetheless, the extra thresholding step introduced by dendritic spike generation could increase neuronal tolerance for a broad category of noise structures, some of which cannot be resolved well with averaging. Computations with multiple dendritic spikes compensate for compartment size constraints and expand the repertoire of conditions that can be reliably processed by neuronal populations.

neuroscience↗

bioRxiv2018

NMDA spikes mediate amplification of odor pathway information in the piriform cortex

The piriform cortex (PCx) receives direct input from the olfactory bulb (OB) and is the brains main station for odor recognition and memory. The transformation of the odor code from OB to PCx is profound: mitral and tufted cells in olfactory glomeruli respond to individual odorant molecules, whereas pyramidal neurons (PNs) in the PCx responds to multiple, apparently random combinations of activated glomeruli. How these \"discontinuous\" receptive fields are formed from OB inputs remains unknown. Counter to the prevailing view that olfactory PNs sum their inputs passively, we show for the first time that NMDA spikes within individual dendrites can both amplify OB inputs and impose combination selectivity upon them, while their ability to compartmentalize voltage signals allows different dendrites to represent different odorant combinations. Thus, the 2-layer integrative behavior of olfactory PN dendrites provides a parsimonious account for the nonlinear remapping of the odor code from bulb to cortex.

neuroscience↗