Biology subjects

Lloyd, B.

Publications and source records attributed to Lloyd, B..

9 recordsLinked to original sources

bioRxiv2026

Reprogramming CAR-T cell function through synthetic cytokine receptors suppresses metastatic progression of TNBC

Patient T cells modified with chimeric antigen receptors (CARs) have shown remarkable therapeutic success in previously incurable cancers. However, despite its success in hematological malignancies, CAR-T therapy has shown only modest efficacy in solid tumors. The medical field has focused on developing new molecular designs that enhance CAR-T persistence, prevent exhaustion in the tumor microenvironment (TME), and increase the specificity of the CAR-T cell to various tumor antigens. However, much less effort has been placed on enhancing CAR-T cells' invasion into and migration through the stromal matrix of the TME, where they can elicit tumor-directed cytotoxicity. Here, we engineered CAR-T cells with synthetic cytokine receptors targeting inflammatory cytokines produced by the cells themselves, which increase their speed through collagen I matrices. We show that this enhanced motility is driven by increased CAR-T cell translocation through confined microchannels via cellular deformation, together with elevated migratory speeds in proximity to neighboring cells, suggesting improved responsiveness to local cues. These migration-enhanced CAR-T cells significantly reduce both primary tumor size and distant organ metastasis in triple-negative breast cancer (TNBC) mouse models compared to standard CAR-T cells. These results support molecular design strategies that exploit mechanisms to improve cellular therapies for metastatic solid tumors.

bioengineering↗

bioRxiv2026

Accurate Hippocampal Electric Field Modeling for Electroconvulsive Therapy: Numerical Accuracy and Convergence

Accurate hippocampal electric field (E-field) prediction is important for individualized electroconvulsive therapy (ECT) dosing and emerging deep-brain stimulation approaches such as temporal interference. Because hippocampal fields are far weaker than those beneath the stimulation electrodes, they are highly sensitive to tissue interfaces, conductivity contrasts, and numerical discretization, so numerical error can rival the physical uncertainties of anatomy and conductivity. We investigate this numerical component of hippocampal dosimetry using individualized head models from eleven ECT patients. Identical head40 segmentations, comprising 40 tissue compartments including the bilateral hippocampi, were simulated with three independent numerical methods: a charge-based boundary-element fast multipole method (BEM-FMM), a voxel-based hexahedral finite-element solver, and a conformal tetrahedral finite-element solver. For each, resolution was increased systematically and convergence assessed from the average hippocampal E-field magnitude. At the highest attainable resolutions, the three methods agreed closely, differing by 6%-7% in the left hippocampus and 9%-12% in the right. At default or coarse resolutions, however, they disagreed by 28.8% on average and up to 50.3% in the right hippocampus. Numerical convergence should therefore be established before differences are attributed to anatomical or conductivity uncertainty, and independent-solver agreement provides a practical basis for reliable hippocampal dosimetry.

neuroscience↗

bioRxiv2026

The unique value of zero prediction errors in reinforcement learning

Updating beliefs when necessary is at the cornerstone of learning. A fundamental problem is to describe under which conditions humans update their internal models of the world. The general assumption across animal, human, and artificial learning models1-3 has been that updates occur when outcomes deviate from expectations. Perfectly predicted outcomes cause no learning. As a result, no research has examined cases in which predictions are surprisingly perfect. Here, we empirically test this assumption and find that zero prediction errors are psychologically unique. We show that after zero prediction errors, momentary happiness is the highest, and belief updates do indeed occur in a pattern that cannot be reproduced by a benchmark model. We present a new model that captures this non-linear pattern in belief updating by postulating that zero prediction errors elicit a distinct latent belief state, guiding subsequent updating. This latent state then tracks neural activity patterns measured with EEG precisely when zero prediction errors occur, exactly as the model would predict. Crucially, the strength of the neural activity during this time window exhibits a dissociation in predicting the next belief update depending on whether feedback was a zero prediction error or a regular prediction error. Overall, we provide strong evidence that surprisingly perfect predictions are treated in a unique, non-linear fashion at affective, behavioral and neural levels. Being surprisingly accurate can function as a distinct belief updating signal, conforming trial-and-hit learning.

neuroscience↗

bioRxiv2024

Subcortical nuclei of the human ascending arousal system encode anticipated reward but do not predict subsequent memory

Subcortical nuclei of the ascending arousal system play an important role in regulating brain and cognition. However, functional MRI of these nuclei in humans involves unique challenges due to their size and location deep within the brain. Here, we used ultra-high-field MRI and other methodological advances to investigate the activity of six subcortical nuclei during reward anticipation and memory encoding: the locus coeruleus, basal forebrain, median and dorsal raphe nuclei, substantia nigra and ventral tegmental area. Participants performed a monetary incentive delay task, which successfully induced a state of reward anticipation, and a 24-hour delayed surprise memory test. Region-of-interest analyses revealed that activity in all subcortical nuclei increased in anticipation of potential rewards as opposed to neutral outcomes. In contrast, activity in none of the nuclei predicted memory performance 24 hours later. These findings provide new insights into the cognitive functions that are supported by the human ascending arousal system.

neuroscience↗

bioRxiv2024

Simulation Insights on the Compound Action Potential in Multifascicular Nerves

ObjectiveDevelop an efficient method for simulating evoked compound action potential (eCAP) signals from complex nerves to help optimize and interpret eCAP recordings; validate it through comparison with measured vagus nerve eCAP recordings; elucidate the subtle interplay giving rise to specific eCAP signal shapes and magnitudes. ApproachWe developed an extended reciprocity theorem approach to model neuron signals in heterogeneous environments, and use it to study analytically the single fibre action potential. We then established a semi-analytic model that also uses hybrid electromagnetic-electrophysiological simulations to model eCAP signals from complex nerves populated with heterogeneous fiber populations of fibers. A cuff electrode was used to measure activity induced by vagus nerve stimulation in in vivo porcine experiments; these measurements were compared with signals produced by the model. Main ResultsThe semi-analytic model produces signals that approximate the shape and amplitude of in vivo measurements. Partially activated fascicles contribute substantially to the signal, as eCAP contributions from smoothly varying fiber calibers in fully activated ones partially cancel. As a result, eCAP magnitude does not depend monotonically on the stimulation current and recruitment level. Because the eCAP is sensitive to the degree of activation in individual fascicles, and to the location of the recording electrodes with respect to individual fascicles, the contributions of different fascicles to the recorded eCAP signals vary significantly with changes in the shape and placement of the stimulus and the recording electrodes. SignificanceOur method can be used to rapidly assess new stimulation and recording setups involving complex nerves and neurovascular bundles, e.g., to maximize signal information content, for closed-loop control in bioelectronic medicine applications, and potentially to non-destructively reconstruct structural and functional nerve topologies through inverse problem solving.

neuroscience↗

bioRxiv2024

BlueRecording: A Pipeline for the efficient calculation of extracellular recordings in large-scale neural circuit models

As the size and complexity of network simulations accessible to computational neuroscience grows, new avenues open for research into extracellularly recorded electric signals. Biophysically detailed simulations permit the identification of the biological origins of the different components of recorded signals, the evaluation of signal sensitivity to different anatomical, physiological, and geometric factors, and selection of recording parameters to maximize the signal information content. Simultaneously, virtual extracellular signals produced by these networks may become important metrics for neuro-simulation validation. To enable efficient calculation of extracellular signals from large neural network simulations, we have developed BlueRecording, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. In particular, we implement a general form of the reciprocity theorem, which is capable of handling non-dipolar current sources, such as may be found in long axons and recordings close to the current source, as well as complex tissue anatomy, dielectric heterogeneity, and electrode geometries. To our knowledge, this is the first application of this generalized (i.e., non-dipolar) reciprocity-based approach to simulate EEG recordings. We use these tools to calculate extracellular signals from an in silico model of the rat somatosensory cortex and hippocampus and to study signal contribution differences between regions and cell types.

neuroscience↗

bioRxiv2023

Non-invasive vagus nerve stimulation and the motivation to work for rewards: a replication

BackgroundThe vagus nerve is thought to be involved in the allostatic regulation of motivation and energy metabolism via gut-brain interactions. A recent study by Neuser and colleagues [1] provided novel evidence for this process in humans, by reporting a positive effect of transcutaneous auricular vagus nerve stimulation (taVNS) on the invigoration of reward-seeking behaviors, especially for food rewards. ObjectiveWe conducted an independent direct replication of Neuser et al. [1], to assess the robustness of their findings. MethodsFollowing the original study, we used a single-blind, sham-controlled, randomized cross-over design. We applied left-sided taVNS in healthy human volunteers (n=40), while they performed an effort allocation task in which they had to work for monetary and food rewards. The replication study was purely confirmatory in that it strictly followed the analysis plans and scripts used by Neuser et al. [1]. ResultsAlthough, in line with Neuser et al. [1], we found strong effects of task variables on effort invigoration and effort maintenance, we failed to replicate their key finding: taVNS did not increase the strength of invigoration (p = .62); the data were five times more likely (BF10 = 0.19) under the null hypothesis. We also found substantial evidence against an effect of taVNS on effort maintenance (p = 0.50; BF10 = 0.20). ConclusionsOur results provide evidence against the idea that taVNS boosts the motivational drive to work for rewards. Our study also highlights the need for direct replications of influential taVNS studies.

neuroscience↗

bioRxiv2023

Short-term transcutaneous vagus nerve stimulation increases pupil size but does not affect EEG alpha power: a replication

BackgroundTranscutaneous auricular vagus nerve stimulation (taVNS) is a promising brain stimulation method for the treatment of pharmaco-resistant epilepsy and depression. Its clinical efficacy is thought to depend on taVNS-induced activation of the locus coeruleus. However, unlike for invasive VNS, there is little evidence for an effect of taVNS on noradrenergic activity. ObjectiveWe attempted to replicate recently published findings by Sharon et al. (2021), showing that short bursts of taVNS transiently increased pupil size and decreased EEG alpha power, two correlates of central noradrenergic activity. MethodsFollowing the original study, we used a single-blind, sham-controlled, randomized cross-over design. We applied short-term (3.4 s) taVNS in healthy human volunteers (n=29), while collecting resting-state pupil-size and EEG data. To analyze the data, we used scripts provided by Sharon and colleagues. ResultsConsistent with Sharon et al. (2021), pupil dilation was significantly larger during taVNS than during sham stimulation (p = .009; Bayes factor supporting the difference = 7.45). However, we failed to replicate the effect of taVNS on EEG alpha power (p = .37); the data were four times more likely under the null hypothesis (BF10 = 0.28). ConclusionOur findings support the effectiveness of short-term taVNS in inducing transient pupil dilation, a correlate of phasic noradrenergic activity. However, we failed to replicate the recent finding by Sharon et al. (2021) that taVNS attenuates EEG alpha activity. Overall, this study highlights the need for continued research on the neural mechanisms underlying taVNS efficacy and its potential as a treatment option for pharmaco-resistant conditions. It also highlights the need for direct replications of influential taVNS studies.

neuroscience↗

bioRxiv2022

Assessing pupil size as an index of activation of subcortical ascending arousal system nuclei during rest

Neuromodulatory nuclei that are part of the ascending arousal system (AAS) play a crucial role in regulating cortical state and optimizing task performance. Pupil diameter, under constant luminance conditions, is increasingly used as an index of activity of these AAS nuclei. Indeed, task-based functional imaging studies in humans have begun to provide evidence of stimulus-driven pupil-AAS coupling. However, whether there is such a tight pupil-AAS coupling during rest is not clear. To address this question, we examined simultaneously acquired resting-state fMRI and pupil-size data from 74 participants, focusing on six AAS nuclei: the locus coeruleus, ventral tegmental area, substantia nigra, dorsal and median raphe nuclei, and cholinergic basal forebrain. Activation in all six AAS nuclei was optimally correlated with pupil size at 0-to 2-second lags, suggesting that spontaneous pupil changes were almost immediately followed by corresponding BOLD-signal changes in the AAS. These results suggest that spontaneous changes in pupil size that occur during states of rest can be used as a noninvasive general index of activity in AAS nuclei. Importantly, the nature of pupil-AAS coupling during rest appears to be vastly different from the relatively slow canonical hemodynamic response function that has been used to characterize task-related pupil-AAS coupling.

neuroscience↗