Biology subjects

Unal, G.

Publications and source records attributed to Unal, G..

6 recordsLinked to original sources

bioRxiv2026

Biophysical modeling reveals how recording geometry shapes representations of cortical activity

Extracellular electrophysiological recordings reflect both the organization of neural activity and the geometry through which that activity is sampled. Here, we used biophysical modeling and experimental recordings from the macaque auditory cortex to determine how cortical activity is transformed across neural sources, extracellular signals, and recording geometries. In a biophysically detailed thalamocortical model, four separately instantiated cortical-column conditions spanning graded thalamic recruitment exhibited a graded response hierarchy across local field potential, current-source density, and multiunit activity, despite signal-dependent differences in the contributions of cortical neuronal populations. We then arranged independently simulated cortical columns into controlled spatial configurations and sampled the same underlying sources using virtual linear laminar and Directional and Scalable (DiSc) electrode arrays. The linear geometry primarily represented variation along cortical depth, whereas DiSc additionally represented circumferential variation associated with lateral source organization, demonstrating that recording geometry determines which spatial dimensions of common underlying activity are represented in extracellular measurements. Experimental recordings obtained with the corresponding geometries were consistent with these model-derived predictions: broadband-noise responses exhibited spatial organization shared across tone-evoked responses in both multidimensional DiSc maps and laminar profiles, despite substantial variation in frequency-dependent response magnitude across penetrations. Together, these results show that extracellular measurements represent an interaction between biological source organization and recording geometry. Biophysical forward modeling therefore provides a framework for determining which features of underlying circuit organization remain identifiable after extracellular sampling and for relating neural-interface design to the dimensions of cortical activity accessible experimentally.

neuroscience↗

bioRxiv2026

Context-Aware Evidence-Gated Plasticity for Multi-Goal Learning in Spiking Neural Networks

Background / IntroductionBiologically inspired spiking neural networks can model adaptive behavior, but learning multiple goals is difficult because synaptic updates for different targets can interfere. We tested whether multi-timescale plasticity and context-specific credit assignment could improve continual multi-goal learning in a spiking navigation system inspired by entorhinal-hippocampal circuitry. MethodsWe developed a closed-loop spiking model containing grid-like, place-like, target-related, association, and motor-output populations. An agent navigated in a two-dimensional environment with randomized starting locations and learned through reward-modulated spike-timing dependent plasticity (STDP/RL) and a novel evidence-gated plasticity (EGP) framework. EGP accumulates candidate synaptic modifications, evaluates them using reward evidence, and consolidates only changes that improve performance. A target-context variant maintained separate proposal stores and reward evaluation for each target. ResultsSTDP/RL learned and retained a single-target navigation policy, but multi-target training produced substantial interference, including attraction to incorrect targets after learning. Across 10 connectivity seeds, target-context EGP achieved higher late-stage reward than global EGP, improved weakest-target performance, and increased the fraction of targets achieving positive reward. In a longer continual-learning simulation, reward increased for all targets, TEST-phase performance increasingly exceeded TRAIN-phase performance, and proposal magnitudes grew over learning. Dwell-time confusion analyses showed that target-context EGP reduced wrong-target attraction and improved target selectivity relative to multi-target STDP/RL. ConclusionsThese results demonstrate that spiking navigation circuits can learn goal-directed behavior using local plasticity, but robust multi-goal learning benefits from context-specific evidence-based consolidation. Target-context EGP provides a biologically motivated mechanism for reducing interference during continual reinforcement learning in spiking neural networks.

neuroscience↗

bioRxiv2026

DeltaQ: Value-Guided Hebbian Learning in Spiking Neuronal Networks for Multi-Goal Navigation

Animals must often navigate environments where feedback about progress toward a goal is sparse or delayed, requiring internal representations of space and memory of prior experience. The hippocampal-entorhinal system is believed to support this capability through distributed spatial representations that guide goal-directed behavior. However, many computational models of these circuits focus primarily on reproducing neural dynamics rather than demonstrating how such representations support learning on navigation tasks. We present a biologically inspired spiking neuronal network (SNN) model that combines grid-cell-derived spatial representations, {Delta}Q-modulated Hebbian plasticity, and context-dependent modulation to support navigation under sparse reward conditions. Grid Cell populations generate distributed spatial codes that are transformed by an Association Cell population into more spatially selective internal representations. Learning is driven by changes in Q-values ({Delta}Q) computed from a goal-conditioned Q-table, allowing local synaptic plasticity to incorporate information about long-term navigation outcomes. For environments containing multiple navigation objectives, a Context Cell population provides task-dependent modulation that enables a shared network architecture to support distinct navigation policies. Across two complementary maze environments, the model demonstrates three core capabilities: generation of distinct spatial representations, learning of efficient navigation policies under sparse and delayed reward, and support for multiple navigation objectives within a shared environment. The results further show that contextual modulation introduces subtle task-dependent variations into a largely shared population representation, allowing identical spatial locations to support different navigation behaviors. These findings demonstrate that biologically inspired spatial representations, value-guided plasticity, and contextual modulation can jointly support flexible navigation in spiking neuronal networks, providing a bridge between mechanistic neural circuit models and functional reinforcement learning.

neuroscience↗

bioRxiv2025

Advancing RNAi-Based Strategies Against Downy Mildews: Insights Into dsRNA Uptake and Gene Silencing

Downy mildew (DMs) dieases are caused by destructive obligate pathogens with limited control options, posing a significant threat to global agriculture. RNA interference (RNAi) has emerged as a promising, environmentally sustainable strategy for disease management. In this study, we evaluated the efficacy of dsRNA-mediated RNAi in suppressing key biological functions in DM pathogens of Arabidopsis thaliana, pea and lettuce DM pathogens, Hyaloperonospora arabidopsidis (Hpa), Peronospora viciae f. sp. pisi (Pvp) and Bremia lactucae (Bl), respectively. We specifically targeted the cellulose synthase 3 (CesA3) and the beta tubulin (BTUB) genes. Silencing CesA3 impaired spore germination and infection across multiple species, while BTUB silencing reinforced the potential of dsRNA-mediated inhibition. Reduction in gene expression levels correlated well with the sporulation assays confirming the effectiveness of dsRNA-mediated gene silencing. We used dsRNAs that were chemically synthesized, in vitro transcribed (IVT) or produced in E. coli. We found that the length and concentration of these dsRNAs significantly affected uptake efficiency, spore germination, and sporulation, with higher concentrations enhancing inhibitory effects. Confocal microscopy using Cy-5-labelled short-synthesized dsRNA (SS-dsRNA) provided direct evidence of spore uptake, confirming the potential of SS-dsRNA for pathogen control. However, species-specific sequence variations influenced dsRNA efficacy, underscoring the importance of target sequence design. Multiplexed RNAi impacted silencing synergisticly, further reducing germination and sporulation in Hpa. Additionally, we demonstrated that SS-dsRNA-mediated gene silencing is sustained over time, with a significant reduction in gene expression level at 4, 7, 10 and 11dpi. This indicates the durability and efficacy of this approach. Taken together, these findings demonstrate the potential of dsRNA-mediated gene silencing as a precision tool for managing DM pathogens.

plant biology↗

bioRxiv2022

Differential Role of GABAergic and Cholinergic Ventral Pallidal Neurons in Behavioral Despair, Conditioned Fear Memory and Active Coping

The ventral pallidum (VP), a core structure of the reward circuit, is well-associated with appetitive behaviors. Recent evidence suggests that this basal forebrain nucleus may have an overarching role in affective processing, including behavioral responses to aversive stimuli. We investigated this possibility by utilizing selective immunotoxin lesions and a series of behavioral tests in adult male Wistar rats. We made bilateral GAT1-Saporin, 192-IgG-Saporin or PBS (vehicle) injections into the VP to respectively eliminate GABAergic and cholinergic neurons, and tested the animals in the forced swim test (FST), open field test (OFT), elevated plus maze (EPM), Morris water maze (MWM) and cued fear conditioning. Both GAT1-Saporin and 192-IgG-Saporin injections reduced behavioral despair without altering general locomotor activity. This antidepressant-like effect was accompanied by reduced freezing and increased darting in the acquisition phase of cued fear conditioning. In the test phase, cholinergic, but not GABAergic lesions, impaired context-dependent fear memory, while both groups showed diminished conditioned freezing in a novel context. In line with this, selective cholinergic lesions impaired spatial memory in the MWM as compared to GAT1-Saporin or vehicle-injected animals. No differential effect was observed in anxiety-like behavior assessed in the OFT or EPM. These findings show that both the GABAergic and cholinergic cell groups of the VP contribute to behavioral despair and acquired fear responses by suppressing active coping. In conditioned learning, cholinergic ventral pallidal neurons contribute to the fear response in a context-independent manner, while the GABAergic population is required when the context information is missing. Significance StatementThe ventral pallidum (VP), associated with motivation and appetitive behaviors, is tested for its role in behavioral responses to aversive stimuli. Findings show that both the GABAergic and cholinergic neuronal groups of the VP contribute to behavioral despair and acquired fear response by suppressing active coping. In conditioned learning, the cholinergic neurons are required for the acquired fear response, while the VP GABAergic population becomes necessary only when the context information is missing. These results suggest that ventral pallidal GABAergic and cholinergic projections to the amygdaloid complex may constitute therapeutic targets for affective disorders.

neuroscience↗

bioRxiv2020

Adaptive current-flow models of ECT: Explaining individual static impedance, dynamic impedance, and brain current delivery

BackgroundImprovements in electroconvulsive therapy (ECT) outcomes have followed refinement in device electrical output and electrode montage. The physical properties of the ECT stimulus, together with those of the patients head, determine the impedances measured by the device and govern current delivery to the brain and ECT outcomes. ObjectiveHowever, the precise relations among physical properties of the stimulus, patient head anatomy, and patient-specific impedance to the passage of current are long-standing questions in ECT research and practice. MethodsWe developed anatomical MRI-derived models of transcranial electrical stimulation (tES) that included changes in tissue conductivity due to local electrical current flow. These "adaptive" models simulate ECT both during therapeutic stimulation using high (~1 A) current and when dynamic impedance is measured, as well as prior to stimulation when low (~1 mA) current is used to measure static impedance. We modeled two scalp layers: a superficial scalp layer with adaptive conductivity that increases with electric field up to a subject specific maximum [Formula], and a deep scalp layer with a subject-specific fixed conductivity ({sigma}DS). ResultsWe demonstrate that variation in these scalp parameters explain clinical data on subject-specific static impedance and dynamic impedance, their imperfect correlation across subjects, their relationships to seizure threshold, and the role of head anatomy. Adaptive tES models demonstrate that current flow changes local tissue conductivity which in turn shapes current delivery to the brain in a manner not accounted for in fixed tissue conductivity models. ConclusionsOur predictions that variation in individual skin properties, rather than other aspects of anatomy, largely govern the relationship between static impedance, dynamic impedance, and current delivery to the brain, are themselves subject to assumptions about tissue properties. Broadly, our novel pipeline for tES models is important in ongoing efforts to optimize devices, personalize interventions, and explain clinical findings.

bioengineering↗