Biology subjects

Antolik, J.

Publications and source records attributed to Antolik, J..

8 recordsLinked to original sources

bioRxiv2025

Beyond retinotopy: exploiting native visual representations in cortical neuroprostheses for vision loss remediation

Cortical prosthetic systems offer a promising path to restoring vision in blindness by stimulating neurons in the visual cortex to evoke visual percepts. To effectively encode visual information, however, it is essential to target neurons based on their functional encoding properties. Current stimulation protocols focus on retinotopic information, ignoring other key encoding properties, and therefore fail to reproduce complex visual percepts. We demonstrate that incorporating orientation selectivity alongside retinotopy to guide stimulation dramatically improves fidelity of the evoked activity to the underlying neural code. We propose a Bottlenecked Rotation-Equivariant CNN (BRCNN) and demonstrate that neural responses can be predicted to a large degree using only retinotopy and orientation preference. Using this model, we design a retinotopy-and-orientation aware stimulation protocol and validate it in a state-of-the-art large-scale optogenetic stimulation simulation framework of primary visual cortex. Our protocol elicits neural activity patterns exhibiting substantially higher correlation with natural vision responses compared to retinotopic-only approaches.

neuroscience↗

bioRxiv2025

Efficient incorporation of dendrites into a large-scale cortical model reveals their surprising role in sharpening optogenetic responses

Single-photon optogenetics enables chronic wide-field stimulation of cortex, facilitating large-scale manipulation of neural code to study cortical processing and advance neuroprosthetics. However, access to neural codes organized at fine spatial scales is compromised by the horizontal spread of stimulation-evoked cortical activity. Overcoming this limitation requires a quantitative understanding of the mechanisms contributing to spread, which include light scattering, dendritic activation, and synaptic transmission. We addressed this with morphology-aware simulations of optogenetic stimulation in a functionally-detailed network model of primary visual cortex. We find that synaptic transmission extends activation by 37-50% beyond the illuminated area, while, paradoxically, neuronal morphology sharpens activation, as apical dendrites sample from the superficial cortex, which is less affected by light dispersion. This unexpected sharpening enhances the fidelity of stimulation with spatially distributed patterns. Our study offers guidance for optogenetic interventions targeting topographically organized neural codes and provides a computational testbed to interpret such experiments.

neuroscience↗

bioRxiv2025

Non-linearity of spatial integration varies across layers of primary visual cortex

The receptive field (RF) of visual cortical neurons is highly dynamic and context-dependent, shaped by both the spatial and temporal properties of stimuli and the complex architecture of cortical circuits. While classical RF mapping through extracellular recordings reveals only the area triggering spiking responses, intracellular recordings reveal a much broader region of subthreshold synaptic input. We investigated how neurons in different cortical layers integrate visual input across space, with a focus on the linearity of spatial summation. Using intracellular recordings, we found that supragranular complex cells integrate input in a highly sublinear manner, in contrast to infragranular complex cells and simple cells, which exhibited near-linear summation. To understand the underlying mechanisms, we employed a large-scale recurrent spiking model of cat primary visual cortex (V1). Modeling results point to the differential patterning of long-range horizontal connections--particularly their targeting of excitatory versus inhibitory neurons--as a potential source of the observed layer-specific integration properties. These findings suggest that RFs emerge from interaction of feedforward, horizontal, and possibly feedback inputs, that are continuous in space, challenging the conventional notions of fixed spatial RF boundaries in early visual processing. O_LIThe properties of receptive fields (RF) of neurons in the primary visual cortex (V1) are not static but change depending on spatiotemporal properties of visual stimulus. C_LIO_LITo study spatial integration of visual information by V1 neurons in a RF independent way, we made intracellular recordings across the cat V1 in response to drifting gratings confined to either circular apertures of variable diameters (disks), or in annuli with fixed outer diameters and variable inner diameters (rings). C_LIO_LIWe find that supragranular complex cells integrate input in a sublinear manner, whereas infragranular complex cells and simple cells exhibit near-linear summation. C_LIO_LIOur large-scale recurrent spiking model shows that these differences between supragranular and infragranular complex cells can be explained by laminar differences in horizontal connectivity properties. C_LIO_LIThese results highlight the substantial differences in spatial integration of visual information at different stages of visual processing C_LI

neuroscience↗

bioRxiv2024

Iso-orientation bias of layer 2/3 connections: the unifying mechanism of spontaneous, visually and optogenetically driven V1 dynamics

Functionally specific long-range lateral connectivity in layer 2/3 of the adult primary visual cortex (V1) supports the integration of visual information across visual space and shapes spontaneous, visual and optogenetically driven V1 activity. However, a comprehensive understanding of how these diverse cortical regimes emerge from this underlying cortical circuitry remains elusive. Here we address this gap by showing how the same model assuming moderately iso-orientation biassed long-range cortical connectivity architecture explains diverse phenomena, including (i) range of visually driven phenomena, (ii) modular spontaneous activity, (iii) the propagation of spontaneous cortical waves, and (iv) neural responses to patterned optogenetic stimulation. The model offers testable predictions, including presence of slower and iso-tropic spontaneous wave propagation in layer 4 and non-monotonicity of optogenetically driven cortical response to increasingly larger disk of illumination. We thus offer a holistic framework for studying how cortical circuitry governs information integration across multiple operating regimes.

neuroscience↗

bioRxiv2024

Consequences of neuronal morphology for spatially precise optogenetic stimulation

Single-photon optogenetic stimulation is a crucial tool in neuroscience, enabling precise, cell-type-specific modulation of neuronal circuits. Miniaturization of this technique in the form of fully implantable wide-field stimulator arrays enables interrogation of cortical circuits in long-term experiments and promises to enhance Brain-Machine Interfaces for restoring sensory and motor functions. However, for both basic science and clinical applications, it is essential that this technique achieves the precision needed for selective activation of sensory and motor representations at the single-column level. Yet studies report differing and sometimes conflicting neuronal responses within the stimulated cortical areas. While recurrent network mechanisms contribute to complex responses, here we demonstrate that complexity starts already at the level of neuronal morphology. Simulating optogenetic responses in detailed models of layer-2/3 and layer-5 pyramidal neurons, we accounted for realistic physiological dynamics across different stimulation intensities, including threshold, sustained, and depolarization-block responses. Our findings suggest that the spatial distribution of activated neurons from a single stimulator location at the cortical surface can be inhomogeneous and varies with stimulation intensity and neuronal morphology across layers, potentially explaining the observed response heterogeneity in earlier experiments. We found that activation spreads laterally up to several hundred micrometers from the light source due to neuronal morphology. To enhance precision, we explored two strategies: preferentially somatic expression of channelrhodopsin, which was effective only in layer-5 neurons, and narrowing the stimulating light beam, which improved precision in both layers. Our results indicate that, under the right optical setup, single-column precision of stimulation is achievable, and that optical enhancements to the stimulator may offer more significant precision improvements than genetic modifications targeting the soma.

neuroscience↗

bioRxiv2022

The cortico-thalamic loop attunes competitive lateral interactions across retinotopic and orientation preference maps

In the early visual system, corticothalamic feedback projections greatly outnumber thalamocortical feedforward projections. Extensive experimental and modeling work has been devoted to the functional impact of the feedforward pathway, but the role of its denser feedback counterpart remains elusive. Here, we propose a novel unifying framework where thalamic recurrent interactions and corticothalamic feedback act in a closed-loop fashion to attune multiple stimulus representations. At each position of the visual field, the loop puts into competition local representations of the stimulus in thalamus and cortex through direct excitation of narrow topologically-aligned portions of the thalamus, accompanied with peri-geniculate nucleus mediated broad inhibition suppressing the topological surround. We built a detailed conductance-based spiking model incorporating retinal input, lateral geniculate nucleus, peri-geniculate nucleus, primary visual cortex, and all the relevant intra-areal and feedback pathways. For the first time we perform comparative analyses between model configurations with completely or locally inactivated cortico-thalamic feedback, as in the experimental preparations. The model mechanistically explains (i) the existence of intra-thalamic surround suppression, (ii) the sensitivity of thalamic neurons to orientation tuning, (iii) the cortex-dependent center-surround opponency in thalamic cells, (iv) the cortical increase of size and orientation selectivity, (v) the cortically enhanced competition between cross-oriented domains within the hypercolumn, and (vi) the selective suppression of cortical functional connectivity. Our results integrate decades of experimental and theoretical research, supporting the hypothesis that cortico-thalamic loop exerts competitive influence between neighboring regions in the thalamus and cortex, complementing the lateral intra-V1 interactions in center-surround contextual modulation.

neuroscience↗

bioRxiv2019

Cortical visual prosthesis: a detailed large-scale simulation study

Recent advances in applying optogenetics in primates initiated the development of light based prosthetic implants for sensory restoration. Thanks to being the most well explored cortical area that is readily accessible at the surface of the brain, vision restoration via direct optogenetic activation of primary visual cortex is one of the most promising early targets for a optogenetics based prosthetic program. However, two fundamental elements of the cortical optogenetic prosthesis remain unclear. First, the exact mechanisms of neural dynamics under direct cortical stimulation, especially in the context of living, active and functionally specific intra-cortical neural circuitry, is poorly understood. Second, we lack protocols for transformation of arbitrary visual stimuli into light activation patterns that would induce perception of the said stimulus by the subject. In this study we address these issues using a large-scale spiking neural network modeling strategy of high biological fidelity. We examine the relationship between specific spatial configuration of light delivered to cortex and the resulting spatio-temporal pattern of activity evoked in the simulated cortical circuitry. Using such virtual experiments, we design a protocol for translation of a specific set of stimuli to activation pattern of a matrix of light emitting elements and provide a detailed assessment of the resulting cortical activations with respect to the natural vision control condition. In this study we restrict our focus to the grating stimulus class, which are an ideal starting point for exploration due to their thoroughly characterized representation in V1 and well-defined information content. However, we also provide an outline of a straight-forward road-map for transforming this grating centric stimulation protocol towards general strategy capable of transforming arbitrary spatio-temporal visual stimulus to a spatio-temporal pattern of light, thus enabling vision restoration via optogenetic V1 activation.

neuroscience↗

bioRxiv2018

A comprehensive data-driven model of cat primary visual cortex

1Knowledge integration based on the relationship between structure and function of the neural substrate is one of the main targets of neuroinformatics and data-driven computational modeling. However, the multiplicity of data sources, the diversity of benchmarks, the mixing of observables of different natures, and the necessity of a long-term, systematic approach make such a task challenging. Here we present a first snapshot of a long-term integrative modeling program designed to address this issue in the domain of the visual system: a comprehensive spiking model of cat primary visual cortex. The presented model satisfies an extensive range of anatomical, statistical and functional constraints under a wide range of visual input statistics. In the presence of physiological levels of tonic stochastic bombardment by spontaneous thalamic activity, the modelled cortical reverberations self-generate a sparse asynchronous ongoing activity that quantitatively matches a range of experimentally measured statistics. When integrating feed-forward drive elicited by a high diversity of visual contexts, the simulated network produces a realistic, quantitatively accurate interplay between visually evoked excitatory and inhibitory conductances; contrast-invariant orientation-tuning width; center surround interactions; and stimulus-dependent changes in the precision of the neural code. This integrative model offers insights into how the studied properties interact, contributing to a better understanding of visual cortical dynamics. It provides a basis for future development towards a comprehensive model of low-level perception. 2 Author summaryComputational modeling can integrate fragments of understanding generated by experimental neuroscience. However, most models considered only a few features of neural computation at a time, leading to either poorly constrained models with many parameters, or lack of expressiveness in over-simplified models. A solution is to develop detailed models, but constrain them with a broad range of anatomical and functional data to prevent overfitting. This requires a long-term systematic approach. Here we present a first snapshot of such an integrative program: a large-scale spiking model of cat primary visual cortex, that is constrained by an extensive range of anatomical and functional features. Together with the associated modeling infrastructure, this study lays the groundwork for a broad integrative modeling program seeking an in-depth understanding of vision.

neuroscience↗