Biology subjects

Okun, M.

Publications and source records attributed to Okun, M..

9 recordsLinked to original sources

bioRxiv2026

Heteroskedasticity of neuronal population responses

Typical changes in a neuronal circuit's operating regime - such as shifts in sensorimotor conditions or in brain state - reshuffle firing rates across its neurons. One well-established key organising principle is rate preservation: firing rates correlate strongly across conditions. Here, we demonstrate that the joint distribution of firing log-rates across pairs of conditions exhibits an additional pervasive and previously unrecognised property: strong heteroskedasticity around the rate-preservation axis, whereby slow-firing neurons (< 1 spike/s) display substantially more variable relative responses across conditions than fast-firing neurons (>10 spikes/s). Using large-scale recordings across multiple brain regions (visual cortex, hippocampus, thalamus, and motor cortex) in mice and primates, we demonstrate that this structure is a generic feature of neuronal population responses. A spike subsampling procedure and explainable variance analysis confirm that this heteroskedasticity reflects true biophysical variance rather than statistical estimation bias resulting from low spike counts. Rate and spiking network models reproduce this phenomenon, revealing its key mechanism: while the standard neuronal transfer function (the F-I curve) is convex, its log-rate counterpart (the logF-I curve) is concave. Consequently, for equivalent input current shifts slow-firing neurons exhibit greater relative sensitivity whereas fast-firing neurons exhibit greater absolute sensitivity. Finally, we show that heteroskedasticity strongly influences downstream readout. Under wiring constraints, neurons with intermediate firing rates provide optimal discrimination performance, whereas under metabolic constraints, large assemblies of slow-firing neurons are most advantageous. These findings identify heteroskedasticity as a fundamental organising principle of neuronal population responses, establishing a mechanistic link between non-linear cellular transfer functions, population-level responses and energy-efficient representations.

neuroscience↗

bioRxiv2026

Body Mass Index-Specific Nanoparticle Protein Corona Signatures in Late Pregnancy

The protein corona (PC) formed on the surface of nanoparticles (NPs) upon exposure to human biofluids is a dynamic interface that reflects the physiological and pathological status of the host. In this study, we investigated how maternal body mass index (BMI) influences the composition of the NPs PC during late pregnancy. Polystyrene NPs were incubated with plasma samples collected from third-trimester pregnant individuals across normal weight, overweight, and obese BMI categories. Comprehensive characterization using dynamic light scattering (DLS), zeta potential measurements, and transmission electron microscopy (TEM) confirmed BMI-dependent differences in PC thickness and colloidal stability. SDS-PAGE and label-free quantitative proteomics revealed distinct molecular compositions: PCs from obese individuals were enriched in inflammatory and lipid metabolism-associated proteins (e.g., APOE, CRP), while normal weight-derived PCs showed higher levels of complement regulators and extracellular matrix proteins. Principal component analysis (PCA) demonstrated clear clustering of proteomic profiles by BMI group, suggesting BMI-specific PC fingerprints. These findings indicate that maternal metabolic phenotype shapes nano-bio interactions at the proteomic level and highlight the potential of PC profiling as a non-invasive approach for assessing maternal health and metabolic status. This work lays the foundation for integrating NP-based proteomics into precision nanomedicine for maternal-fetal health monitoring.

biophysics↗

bioRxiv2025

Disassociating cerebral vasomotion from low frequency spontaneous neurovascular coupling

Vasomotion, vascular oscillations at [~]0.1 Hz, may serve as a biomarker and therapeutic target for neurodegenerative diseases, but its origins, structure across brain vasculature, and correlation with neural activity remain unclear. This study examined the spatiotemporal characteristics of cerebral vasomotion and its relationship to neural activity in anaesthetised Hooded Lister rats using simultaneous recordings of neuronal activity and haemodynamics in motor and whisker barrel cortices. In a subset of rats, tissue oxygen was also measured. Blood pressure was pharmacologically modulated to alter vascular oscillations. We found that vasomotion was driven by the arterial tree. Two prominent activity patterns emerged: global vasomotion across the entire hemisphere and phasic vasomotion seen as a travelling wave running through the surface arteries. Moreover, vasomotion was associated with low tissue oxygen and was largely independent of spontaneous neural activity and therefore not a product of neurovascular coupling.

neuroscience↗

bioRxiv2021

Stretching and squeezing of neuronal log firing rate distribution by psychedelic and intrinsic brain state transitions

How psychedelic drugs change the activity of cortical neuronal populations and whether such changes are specific to transition into the psychedelic brain state or shared with other brain state transitions is not well understood. Here, we used Neuropixels probes to record from large populations of neurons in prefrontal cortex of mice given the psychedelic drug TCB-2. Drug ingestion significantly stretched the distribution of log firing rates of the population of recorded neurons. This phenomenon was previously observed across transitions between sleep and wakefulness, which suggested that stretching of the log-rate distribution can be triggered by different kinds of brain state transitions and prompted us to examine it in more detail. We found that modulation of the width of the log-rate distribution of a neuronal population occurred in multiple areas of the cortex and in the hippocampus even in awake drug-free mice, driven by intrinsic fluctuations in their arousal level. Arousal, however, did not explain the stretching of the log-rate distribution by TCB-2. In both psychedelic and naturally occurring brain state transitions, the stretching or squeezing of the log-rate distribution of an entire neuronal population reflected concomitant changes in two subpopulations, with one subpopulation undergoing a downregulation and often also stretching of its neurons log-rate distribution, while the other subpopulation undergoes upregulation and often also a squeeze of its log-rate distribution. In both subpopulations, the stretching and squeezing were a signature of a greater relative impact of the brain state transition on the rates of the slow-firing neurons. These findings reveal a generic pattern of reorganisation of neuronal firing rates by different kinds of brain state transitions.

neuroscience↗

bioRxiv2021

TNF increases Tyrosine Hydroxylase expression in human monocytes

Most, if not all, peripheral immune cells in humans and animals express tyrosine hydroxylase (TH), the rate limiting enzyme in catecholamine synthesis. Since TH is typically studied in the context of brain catecholamine signaling, little is known about changes in TH production and function in peripheral immune cells. This knowledge gap is due, in part, to the lack of an adequately sensitive assay to measure TH in immune cells expressing lower TH levels compared to other TH expressing cells. Here, we report the development of a highly sensitive and reproducible Bio-ELISA to quantify picogram levels of TH in multiple model systems. We have applied this assay to monocytes isolated from blood of persons with Parkinsons disease (PD) and to age-matched, healthy controls. Our study unexpectedly revealed that PD patients monocytes express significantly higher levels of TH protein in peripheral monocytes relative to healthy controls. Tumor necrosis factor (TNF{delta}), a pro-inflammatory cytokine, has also been shown to be increased in the brains and peripheral circulation in human PD, as well as in animal models of PD. Therefore, we investigated a possible connection between higher levels of TH protein and the known increase in circulating TNF{delta} in PD. Monocytes isolated from healthy donors were treated with TNF{delta} or with TNF{delta} in the presence of an inhibitor. Tissue plasminogen activator (TPA) was used as a positive control. We observed that TNF{delta} stimulation increased both the number of TH+ monocytes and the quantity of TH per monocyte, without increasing the total numbers of monocytes. These results revealed that TNF{delta} could potentially modify monocytic TH production and serve a regulatory role in peripheral immune function. The development and application of a highly sensitive assay to quantify TH in both human and animal cells will provide a novel tool for further investigating possible PD immune regulatory pathways between brain and periphery.

neuroscience↗

bioRxiv2020

Neuropixels 2.0: A miniaturized high-density probe for stable, long-term brain recordings

To study the dynamics of neural processing across timescales, we require the ability to follow the spiking of thousands of individually separable neurons over weeks and months, during unrestrained behavior. To address this need, we introduce the Neuropixels 2.0 probe together with novel analysis algorithms. The new probe has over 5,000 sites and is miniaturized such that two probes plus a headstage, recording 768 sites at once, weigh just over 1 g, suitable for implanting chronically in small mammals. Recordings with high quality signals persisting for at least two months were reliably obtained in two species and six different labs. Improved site density and arrangement combined with new data processing methods enable automatic post-hoc stabilization of data despite brain movements during behavior and across days, allowing recording from the same neurons in the mouse visual cortex for over 2 months. Additionally, an optional configuration allows for recording from multiple sites per available channel, with a penalty to signal-to-noise ratio. These probes and algorithms enable stable recordings from >10,000 sites during free behavior in small animals such as mice.

neuroscience↗

bioRxiv2020

Equations governing dynamics of excitation and inhibition in the mouse corticothalamic network

Although cortical circuits are complex and interconnected with the rest of the brain, their macroscopic dynamics are often approximated by modeling the averaged activities of excitatory and inhibitory cortical neurons, without interactions with other brain circuits. To verify the validity of such mean-field models, we optogenetically stimulated populations of excitatory and parvalbumin-expressing inhibitory neurons in awake mouse visual cortex, while recording population activity in cortex and in its thalamic correspondent, the lateral geniculate nucleus. The cortical responses to brief test pulses could not be explained by a mean-field model including only cortical excitatory and inhibitory populations. However, these responses could be predicted by extending the model to include thalamic interactions that cause net cortical suppression following activation of cortical excitatory neurons. We conclude that mean-field models can accurately summarize cortical dynamics, but only when the cortex is considered as part of a dynamic corticothalamic network.

neuroscience↗

bioRxiv2018

Dopaminergic and frontal signals for decisions guided by sensory evidence and reward value

Making efficient decisions requires combining present sensory evidence with previous reward values, and learning from the resulting outcome. To establish the underlying neural processes, we trained mice in a task that probed such decisions. Mouse choices conformed to a reinforcement learning model that estimates predicted value (reward value times sensory confidence) and prediction error (outcome minus predicted value). Predicted value was encoded in the pre-outcome activity of prelimbic frontal neurons and midbrain dopamine neurons. Prediction error was encoded in the post-outcome activity of dopamine neurons, which reflected not only reward value but also sensory confidence. Manipulations of these signals spared ongoing choices but profoundly affected subsequent learning. Learning depended on the pre-outcome activity of prelimbic neurons, but not dopamine neurons. Learning also depended on the post-outcome activity of dopamine neurons, but not prelimbic neurons. These results reveal the distinct roles of frontal and dopamine neurons in learning under uncertainty.

neuroscience↗

bioRxiv2018

Distinct structure of cortical population activity on fast and infraslow timescales

Cortical activity is organised across multiple spatial and temporal scales. Most research on the dynamics of neuronal spiking is concerned with timescales of 1 ms - 1 s, and little is known about spiking dynamics on timescales of tens of seconds and minutes. Here, we used frequency domain analyses to study the structure of individual neurons spiking activity and its coupling to local population rate and to arousal level across frequencies ranging from 0.01 to 100 Hz. In mouse medial prefrontal cortex (mPFC), the spiking dynamics of individual neurons could be quantitatively captured by a combination of interspike interval and firing rate power spectrum distributions. The relative strength of coherence with local population often differed across timescales: a neuron strongly coupled to population rate on fast timescales could be weakly coupled on slow timescales, and vice versa. On slow but not fast timescales, a substantial proportion of neurons showed firing anti-correlated with the population. Infraslow firing rate changes were largely determined by arousal rather than by local factors, which could explain the timescale dependence of population coupling strength of individual neurons. These observations demonstrate how individual neurons simultaneously partake in fast local dynamics, and slow brain-wide dynamics, extending our understanding of infraslow cortical activity beyond the mesoscale resolution of fMRI studies.

neuroscience↗