Neurophotonics

Wide-field imaging (WFI) is a mesoscopic approach for monitoring cortex-wide activity with high temporal resolution and a broad field of view. Owing to its simple optical configuration and compatibility with chronic preparations, WFI has become an important tool in systems neuroscience and disease-model research. In this chapter, we describe practical protocols for chronic transcranial WFI in mice using two complementary optical signals: genetically encoded calcium indicators (GCaMP) and endogenous flavoprotein autofluorescence. Calcium imaging provides a robust readout of neuronal population activity, whereas flavoprotein imaging reflects mitochondrial redox dynamics and cellular metabolic demand. We detail procedures for animal preparation, skull clearing, headplate implantation, macroscope assembly, synchronized sensory stimulation, triggered image acquisition, and MATLAB-based data analysis. The analysis workflow includes {Delta}F/F normalization, reference-based signal correction, and artifact reduction, followed by trial averaging, atlas registration, and region-of-interest analysis. Because imaging is performed through the intact skull, the protocol enables repeated longitudinal measurements in the same animal over extended periods. This approach is reproducible, cost-effective, and adaptable to studies of cortical physiology and neurological disorders.

When hearing fails, cochlear implants (CIs) partially restore auditory perception. Yet, poor coding of spectral information remains a bottleneck as each electrode broadly activates the auditory nerve. As light can be more conveniently confined, optical (o)CIs present a promising alternative. Here, we combined expression of the potent channelrhodopsin ChReef in spiral ganglion neurons (SGNs) and oCIs based on 5-10 green LED in gerbils. We characterized the oCI encoding of intensity and spectral information by ChReef-SGNs using recordings from the central nucleus of the inferior colliculus (ICC). ChReef aligned light sensitivity of SGNs well with the radiant fluxes provided by individual LEDs: ICC-activity had thresholds <200 nJ and reached a maximum close to that achieved with 46 dB tones. Multichannel oCIs enabled tonotopically ordered and spectrally distinct stimulation indistinguishable from acoustic stimulation for up to moderate activity levels. Some LEDs elicited >1 spectral peaks for stronger intensities. Representational Similarity Analysis and Linear Discriminant Analysis of ICC activity indicated improved channel discriminability of optical over electrical stimulation. In summary, {micro}J oCI stimulation achieves near-physiological spectral resolution. The Paper ExplainedO_ST_ABSProblemC_ST_ABSElectrical cochlear implants (eCIs) partially restore speech comprehension in most of >1 million otherwise deaf users, who still face challenges hearing in daily situations. This is primarily due to poor spectral selectivity of electrical sound encoding. Spatially more confined optogenetic activation of the auditory nerve by optical cochlear implants (oCI) promises to overcome this limitation. However, a thorough characterization of bionic coding of sound information by multichannel oCI is needed to evaluate the potential for improved hearing restoration. ResultsHere, we combine the potent channelrhodopsin ChReef and 10-channel oCI based on green LEDs in gerbils and characterize their utility for encoding of spectral and intensity information by multielectrode array recordings from the midbrain. ChReef enabled activation of the auditory pathway with nano-joule thresholds and up to high levels of midbrain activity with low {micro}J radiant energy. The cochlear spread of excitation and channel discriminability for low to medium activity levels were close to what we observed with acoustic stimulation. ImpactOur work demonstrates great potential of multichannel optogenetic stimulation for encoding sound frequency information.

A central challenge in opsin engineering is identifying mutations that reliably improve desired functional properties, a task made difficult by the enormous mutation space and limited throughput of electrophysiological screening. Improving opsin properties such as photocurrent amplitude and light sensitivity have the potential to broaden the use of opsins to low-light and deep-tissue applications. With this goal, we applied zero-shot protein language models (ESM-1b/1v) to recommend ChrimsonR mutations and experimentally validated all 17 of these variants using whole-cell patch clamp electrophysiology (n=6 cells per mutation). Despite many mutations reducing function, protein language models identified both known functional residues and unconventional substitutions that produced large functional gains and synergized with K176R to improve kinetics. Two mutations, E300G and E300P, increased sustained photocurrents from 66 pA (control) to 305 pA and 255 pA at 635 nm, reduced EC50 at 575 nm from 0.19 mW to 0.07 mW, and altered kinetics ({tau}off increased from 0.06 s up to 0.40 s). Our results suggest that protein language models, even without task-specific training, can be used alongside electrophysiological measurements as a strategy for screening opsins for enhanced photocurrent.

Microglia represent the immune component of the central nervous system (CNS) that displays dynamic responses to injury and disease. Across the developing and mature CNS, microglia emerge as immunocompetent cells that continuously survey their surroundings to maintain tissue homeostasis and respond to threats. There remains a gap in 3D in vitro models that contain microglia and can provide both developmental and mature functional hallmarks. Using a 3D neural multicellular model, cortical microtissues, derived from primary rat cortical cells, we conducted live imaging to monitor microglia dynamics from early, middle, and late stage microtissue maturation. We optimized a within-micromold imaging approach that allows for live microglia imaging without removing microtissues from their culturing environment. We confirm that microglia exhibit baseline surveillance characterized by relatively stationary somas and highly dynamic cell processes that continuously extend and retract. Following proinflammatory challenges, microglia engulf lipopolysaccharide particles, accompanied by dynamic shifts in motility patterns; and rapidly respond to laser-induced tissue damage through process extension, whole-cell displacement, and local recruitment. Lastly, we show that microtissue age in culture strongly influences both baseline and directed motility profiles. Collectively, these studies demonstrate that within a 3D microenvironment, microglia exhibit pronounced changes in morphology, surveillance area, motility, and injury response across microtissue maturation. Microtissues can serve as a valuable in vitro platform for both microglia developmental studies and investigations of brain inflammation related to CNS injuries, infections, and diseases.

When hearing fails, stimulation of the auditory nerve by electrical cochlear implants (eCIs) partially restores hearing, with most eCI users achieving open speech understanding. However, the broad current spread from each electrode limits frequency coding and speech understanding in daily situations with background noise. Spatially confined optogenetic stimulation by future optical cochlear implants (oCIs) improves frequency coding but millisecond closing kinetics of channelrhodopsins (ChRs) might limit temporal coding. Here, we evaluated the utility of fast-closing ChR f-Chrimson for processing temporal information in the auditory system of Mongolian gerbils. We recorded neural activity in the inferior colliculus evoked by f-Chrimson-mediated optogenetic stimulation of the cochlea. F-Chrimson enabled energy-efficient stimulation of the auditory pathway at rates [&ge;]150 Hz, outperforming the slower ChR variants CatCh (blue) and ChReef (green). Energy thresholds for activation of the auditory pathway were in the low {micro}J range, between ChReef (sub-{micro}J) and CatCh. Dynamic range and frequency selectivity were comparable to previous observations with CatCh and outperformed electrical stimulation. In conclusion, employing fast-gating ChRs harnesses improved spectral coding without degrading temporal coding. The Paper ExplainedO_ST_ABSProblemC_ST_ABSElectrical cochlear implants (eCIs) partially restore speech comprehension in most of 1 million otherwise severely deaf people. However, most CI-users face challenges hearing in daily situations. Spectrally more selective stimulation of the auditory nerve by optical cochlear implants (oCIs) promises to overcome this limitation. However, the closing kinetics of channelrhodopsins (ChR) limit the temporal bandwidth of bionic sound coding. Improving the ChR properties and evaluating temporal coding remain major objectives for developing hearing restoration by oCI. ResultsHere, we evaluate the utility of waveguide-based oCI using the fast-closing ChR Chrimson (f-Chrimson) for encoding of temporal, spectral and intensity information by multi-electrode-array (MEA) recordings from the midbrain. We compare f-Chrimson-mediated bionic coding to acoustic coding as well as to previous data acquired with optogenetic stimulation using other ChRs and with electrical stimulation. F-Chrimson enabled energy-efficient stimulation of the auditory pathway at rates [&ge;]150 Hz, outperforming the slower ChR variants CatCh (blue) and ChReef (green). Intensity and frequency coding were comparable to previous observations with CatCh and outperformed electrical stimulation. ImpactThis study demonstrates near physiological temporal coding with the fast-closing ChR f-Chrimson, indicating that improved spectral coding by oCI is not traded off by poor temporal fidelity.

Zebrafish (Danio rerio) are an important vertebrate model for vision and neuroscience research. In the larval stages, the aquatic species begins to elicit the optomotor response (OMR) to stabilize themselves in water -- a behaviour that may be exploited in the laboratory to measure visual acuity. However, up to now, the measurement of the OMR in juvenile and adult zebrafish has been limited due to their behavioural complexity. Here, we optimize a protocol to assay zebrafish aged between 4 and 9 weeks-post-fertilization, by displaying sinusoidal gratings parallel to the zebrafish eye to elicit a robust OMR. We assessed the visual spatial-frequency tuning function of an environmentally induced myopia model to confirm the sensitivity and robustness of the protocol. Additionally, we show the OMR is sensitive to the contrast and temporal resolution of the sinusoidal gratings. Furthermore, we found that the time between stimulus presentations impact the spatial-frequency tuning function likely as time is required for zebrafish to return to baseline swimming after eliciting the OMR. Finally, we found that the OMR after ten versus twenty seconds of stimulus onset appears comparable; indicating that robust OMR responses in zebrafish can be elicited through relatively short stimulus presentations. Through the experiments conducted, we present an optimized protocol specific to zebrafish. The protocol may be used to follow the progression or treatment efficacy of progressive neurological disorders including specific visual disorders and higher brain functions with visual endophenotypes. Ultimately, this protocol allows for high-throughput robust measures of visual and neural function in zebrafish.

We find that multi-site temporal control of optogenetic photostimulation in peripheral nerves can enhance firing rates by overcoming the intrinsic limitation of opsin photophysics. The benefits of multi-site optogenetic stimulation were demonstrated with three approaches: (1) in silico modeling, (2) ex vivo in the sciatic nerve, and (3) in vivo in the vagus nerve. An in silico model of multi-site optogenetic stimulation was developed in two Hodgkin and Huxley type neuron models, that supported our hypothesis. The ex vivo sciatic nerve showed an increase in firing frequency that is physiologically relevant for functional control. The technique was then applied in vivo for optogenetic vagus nerve stimulation resulting in significant changes in heart rate compared with standard methods of single-site stimulation. Improving the control of optogenetically induced neural firing will have broad impacts for future developments in optical nerve interfaces and brain-machine interfaces.

Quantitative eye movement analysis is important for neuro- logical diagnostics, yet existing video-oculography (VOG) systems typ- ically require calibration, device-specific settings, or accurate gaze la- bels. We present VOGeo-Gaze, a real-time, calibration-free, geometry- aware neural network that estimates gaze by reconstructing anatomi- cally meaningful eyeball parameters from image features. The method combines segmentation-driven projection geometry, a refraction-aware pupil correction module, and temporal anatomical stabilization, so gaze is derived from interpretable eye geometry rather than direct angular regression. Trained only on the public TEyeD dataset with weak gaze supervision, VOGeo-Gaze was evaluated on 116 clinical recordings from 17 patients and 19 healthy subjects using EyeSeeCam, a clinical gold- standard VOG system. It achieved median absolute angular errors of 0.33{whitebullet} horizontally and 0.35{whitebullet} vertically, with nearly 92% of recordings below 1{whitebullet} error while operating at >300 FPS. These results demonstrate sub-degree clinical gaze estimation without subject-specific calibration, camera intrinsics, or accurate gaze labels, providing a scalable and inter- pretable alternative to conventional VOG pipelines. Code is available at https://github.com/DSGZ-MotionLab/VOGeo-Gaze.

Honey bees (Apis mellifera) offer an alternative model for investigating magnetoreception, exhibiting reliable navigation and behavioral responses to magnetic fields. Thanks to their compact brains, well-matched to the penetration depth of modern optical imaging techniques, they may offer insights into the neural and biochemical mechanisms underlying this sense, something that standard models, like migrating birds, have not so far provided. But also in honeybees, this progress requires tools capable of resolving weak, magnetically induced neural activity with high spatio-temporal precision. The approach, presented here, bridges quantum biology and neuroscience, allowing for testing the radical pair mechanism (RPM) as a potential basis for magnetic sensing. As the RPM predicts that magnetoreception is coupled to the visual system, we developed an in vivo two-photon calcium imaging approach to measure neural activity in the anterior optic tubercle, a higher-order visual center involved in chromatic processing and potentially navigation. Bees were prepared using a minimally invasive technique, in which this neuropil was retrogradely labelled with a fluorescent calcium indicator, enabling stable recording conditions over several hours. Controlled blue-light stimuli were provided by the scattered output of a fiber laser, and weak magnetic-field stimuli were applied by a shielded, three-axis Helmholtz coil system that allowed precise modulation of field strength and polarity while minimizing electromagnetic interference. Visual stimulation evoked consistent and reproducible calcium responses, validating the preparation and imaging stability. Magnetic stimulation produced small fluorescence decreases, suggesting field-dependent modulation of neural activity. The developed imaging framework shows the feasibility of detecting magnetic modulation in vision- and navigation-related brain regions, suggesting neural amplification of weak magnetic cues and providing a platform for controlled tests of RPM-specific predictions, including light dependence, polarity independence, and radiofrequency perturbation.

PurposeTo evaluate the retinal safety of repeated low-level red-light (RLRL) therapy using the Eyerising Myopia Management Device (EMMD) by analysing exposure parameters relative to established thermal and photochemical retinal injury thresholds and empirical human exposure data. MethodsEmission characteristics of the EMMD were measured in an accredited laboratory under worst-case conditions. Parameters assessed included wavelength, intraocular power, corneal irradiance, and retinal image characteristics across accommodative states. These measurements were compared with international safety standards, maximum permissible exposure limits, and experimentally derived retinal injury thresholds from animal studies and validated computational models. The effects of repeated exposures from RLRL therapy using the EMMD were evaluated using photochemical additivity principles and repair kinetics, and further contextualised using human volunteer exposure data. ResultsThe EMMD emitted red laser radiation at 654-655 nm with a maximum intraocular power of approximately 1 mW through a 7 mm pupil, placing it within Class 3R and marginally above the Class 2 limit. Corneal irradiance was approximately 26 W m- 2, well below conservative photochemical exposure limits. Thermal injury modelling indicated retinal damage thresholds above device exposure, including under worst-case assumptions of minimal retinal image size and absence of eye movements. Accounting for repeated daily exposures and photochemical additivity, safety margins remained approximately 3-fold for a 7 mm pupil and approximately 8-fold for a more realistic 4 mm pupil. Human volunteer studies demonstrated no detectable structural or functional retinal injury at exposure levels approximately five times higher than those produced by the EMMD. ConclusionExposure parameters of RLRL therapy using the EMMD remain well below conservative retinal injury thresholds under prescribed use conditions. Integration of experimental, modelling, and human data indicates substantial safety margins, supporting its safe clinical use.

Objective. Continuous, unsupervised monitoring of cognitive brain responses has long been constrained by the demands of laboratory EEG. Whether the P300 event-related potential, an established marker of attention and cognitive processing, can be elicited as an incidental byproduct of genuine gameplay, recorded with a minimal wearable EEG system under unsupervised home conditions, has not been established. Approach. Ten healthy adults played a gamified visual oddball task in which infrequent target stimuli (green gates) were embedded among frequent non-targets (red gates) within a continuous third-person running game. EEG was recorded with a four-channel dry-electrode headband (EEG channels: O1, O2, T3, T4; forehead reference; 250Hz) with self-mounted electrodes in a home setting, without experimenter supervision. Group-level effects were assessed with cluster-based permutation tests and peak-amplitude tests. Single-trial classification used linear discriminant analysis (LDA) with four features per channel (16 total). Additional analyses included a within-subject comparison with a classical visual oddball paradigm using identical hardware, pilot data from a patient with relapsing-remitting multiple sclerosis, within-subject stability across 48 sessions, and pilot recordings with a headphone form factor. Main results. A robust P300-like difference wave emerged on all four channels at the group level (cluster-based permutation tests, p < 0.05), with individual-level detection in 8 of 10 participants (exact binomial p < 0.001). Single-trial LDA yielded a median cross-validated AUC of 0.730 (95% CI 0.672-0.820), with 9 of 10 participants exceeding chance. In a within-subject comparison, waveform morphology was closely preserved relative to a classical laboratory oddball, and classification performance was markedly higher in the game condition (AUC 0.820 versus 0.555). A patient with relapsing-remitting multiple sclerosis produced a clear P300 (AUC 0.853) with latencies within the healthy range. Within-session split-half reliability was high (r > 0.70 on three of four channels), though between-session reliability was near zero across 48 sessions in one participant, with a declining classification trend over time. Pilot recordings with a headphone form factor also yielded a P300-like deflection. Significance. These results demonstrate that the P300 can be elicited as a gameplay-integrated neural readout during genuine gameplay with a wearable, dry-electrode EEG system under unsupervised conditions. Gamification does not compromise P300 elicitation; in the within-subject comparison, it enhanced single-trial discriminability. The findings indicate that gamified, home-based P300 monitoring is achievable with minimal hardware and provide preliminary evidence for applicability in clinical populations, most notably multiple sclerosis, where P300 has established biomarker value but where the logistical burden of laboratory assessment currently precludes longitudinal use.

ObjectiveSimultaneous recording of brain activity, behaviour, and virtual environments is essential for understanding large-scale neural dynamics during behaviour. However, existing systems often rely on software-based synchronization or post hoc alignment, introducing latency, jitter, and drift that obscure fast brain-behavior interactions. ApproachHere, we present a deterministically synchronized widefield calcium imaging platform that unifies neural imaging, high-speed behavioural monitoring, and closed-loop virtual reality (VR) under a shared hardware-defined clock. This system enables millisecond-precision temporal alignment across modalities, including dual-wavelength hemodynamic correction, pupil and orofacial tracking, locomotion sensing, and VR rendering. Main resultsThe platform achieves stable hardware-level synchronization across neural imaging, behavioural recordings, and VR rendering without reliance on software timestamps. It supports widefield imaging rates up to 100 Hz and integrates seamlessly with both ViRMEn and Blender VR engines, exhibiting a mean locomotion-to-VR update latency of [~]1.5 ms. Multimodal recordings during VR navigation demonstrate robust temporal alignment between cortical activity, facial dynamics, pupil signals, and locomotion. SignificanceThis system provides a deterministic multimodal framework for studying brain-behaviour relationships during active behaviour. By enabling millisecond-precision synchronization across neural imaging, behaviour, and virtual environments, this platform enables causal investigation of brain-behaviour interactions at millisecond precision and provides a foundation for next-generation closed-loop neuroengineering experiments.

Basal forebrain cholinergic neurons project widely to the cerebral cortex and participate in cerebrovascular regulation. Although cholinergic axons are distributed around the cerebrovasculature, their functional relationship with arteriolar dynamics remains unclear. In this study, we established an in vivo two-photon imaging approach to simultaneously measure Ca2+ signals in cholinergic axonal varicosities and arteriolar diameters in urethane-anesthetized mice. An adeno-associated virus (AAV) vector (rAAV-ChAT-jGCaMP8s) was injected into the nucleus basalis of Meynert. In vivo imaging of the frontal cortex revealed bead-shaped GCaMP signals around the arterioles. Pinch stimulation transiently increased Ca2+ signals in periarteriolar varicosities, followed by arteriolar dilation, with an approximately 2-s delay between their peaks. Linear regression analysis disclosed a significant relationship between the magnitudes of these changes. This approach enabled simultaneous evaluation of cholinergic axonal activity and arteriolar dynamics in vivo, providing a tool to investigate the cholinergic regulation of cerebrovasculature. HighlightsO_LIAAV-ChAT-GCaMP enables selective imaging of cholinergic projections C_LIO_LITwo-photon imaging reveals bead-shaped Ca2+ signals around arterioles C_LIO_LISensory stimulation increases periarteriolar cholinergic axonal Ca2+ signals C_LIO_LIAxonal Ca2+ signals are associated with arteriole dilation C_LI

Dynamic FGF/ERK signaling plays key roles in development, regeneration, and disease. We recently developed a zebrafish-optimized optogenetic tool, bOpto-FGF, that enables reversible activation of FGF/ERK signaling in response to blue light ([~]455 nm) by fusing a zebrafish receptor tyrosine kinase domain to the blue light-dimerizing LOV domain. Previously, this tool was introduced into zebrafish embryos by mRNA injection. Here, we develop a novel transgenic zebrafish ubiquitously expressing bOpto-FGF, Tg(ubi:bOpto-FGF), to streamline experimental workflows. We demonstrate robust blue light-mediated activation of FGF/ERK signaling in gastrulation-stage Tg(ubi:bOpto-FGF) homozygous and heterozygous embryos. Light-mediated signaling activation is more spatially uniform in transgenics compared to embryos injected with bOpto-FGF mRNA. Tg(ubi:bOpto-FGF) heterozygotes are light-responsive from late blastula stages through at least 24 hours post-fertilization. Finally, ectopic signaling in response to continuous light exposure starting at late blastula stage is activated within 3 minutes and maintained for at least 75 minutes. This transgenic line provides a powerful and convenient new strategy for experimental manipulation of FGF/ERK signaling dynamics in the vertebrate zebrafish model.

Visual prostheses face a critical miniaturisation challenge: converting photoreceptor signals to biologically appropriate retinal ganglion cell (RGC) stimulation patterns within the spatial constraints of intraocular implants. Existing systems rely on external microcontrollers for signal processing, limiting scalability for high-density pixel arrays. This paper presents an integrated per-pixel circuit architecture that directly converts photocurrent into frequency-modulated current pulses that match RGC activation thresholds. The design targets are established through NEURON computational modelling of red-green colour-opponent midget RGCs, identifying stimulation thresholds of +0.1nA to +3.5nA for depolarisation and -0.1nA for repolarisation. The proposed circuit combines a transimpedance amplifier, a voltage-controlled oscillator with a Schmitt trigger, and a current-controlled output stage to generate biphasic pulses within these thresholds. A complementary output provides lateral inhibition, reducing crosstalk between adjacent RGC stimulation sites. Photoreceptor integration is achieved using P3HT:PCBM organic photodiodes for cone-associated RGCs and phototransistors for rod-associated RGCs, validated through OghmaNano finite element simulations. The photodiode circuit produces output frequencies of 2.5Hz (dark) to 600Hz (100 W/m2), matching reported RGC response ranges. This architecture eliminates external processing requirements, enabling scalable high-density retinal prostheses design.

IntroductionMagnetic resonance imaging (MRI) is central to neurological care, yet access remains profoundly inequitable in low- and middle-income countries, especially in rural health facilities where high costs and fragile electricity supply limit services. Ultra-low-field (ULF) portable MRI offers a way to expand access, but deployment in weak-grid settings requires robust affordable power. We characterized the power needs of a 0.064T portable ULF MRI system and assessed the feasibility of a solar-powered MRI-capable facility in a rural Zimbabwean clinic, which we believe to be the first of its kind in the world. MethodsWe measured the power draw of an ultra-low-field MRI session from a portable photovoltaic (PV) battery kit in the UK, quantifying scan, standby and energy use. We then monitored a PV-battery micro-grid supplying a protected circuit at an MRI-capable clinic in Shurugwi, Zimbabwe. Inverter telemetry was used to derive PV generation, load, battery state of charge (SoC) and grid import for working days in October-November 2025, spanning the end of the dry season and onset of the rainy season. ResultsIn the portable configuration, a 64-minute MRI session consumed [~]0.21 kWh, with standby demand of [~]1.44 kWh per 24 hours. In clinic, mean PV generation was 9.10 kWh (SD=1.34) and load 9.91 kWh, with zero recorded grid import and minimum daily SoC typically [&ge;]60%, including during the early rainy season. ConclusionAn affordable PV-battery micro-grid can reliably support ULF MRI and associated research power loads in a rural, weak-grid clinic, offering a reproducible blueprint to narrow diagnostic equity gaps in resource-limited settings.

Statistical parametric mapping (SPM) software was implemented in the early 1990s so that neuroscientists could test spatially extended hypotheses using functional imaging data, usually in 3D space and allowing for a mass univariate approach to hypothesis testing that is agnostic to where any significant effects may lie. Here, we apply the same approach to gaze duration data, i.e. visual fixations, collected using a virtual reality headset, which extends across a large 2D area of visual space, measuring 32{degrees} either side of central fixation and 24{degrees} above and below this point. In order to evaluate this novel method, we measured the locus of average gaze in a group of 17 patients with hemispatial inattention to the left, a neurological condition caused by damage to the right parieto-frontal brain networks, that induces a systematic bias in lateralised visual attention. This causes people to experience difficulty in paying attention to one side of space, both in their extrapersonal world and relative to their own bodies. We used a free visual exploration paradigm (viewing multiple naturalistic scenes for 7 seconds), which is sensitive to spatial biases encountered in this condition. 23 age-matched and neurologically healthy controls also took part. The visual stimuli were original and mirror flipped versions (Left to Right ie L-R) to correct for any lateralised informational biases inherent in the images. When compared with age-matched controls, the patients exhibited an average spatial shift of attention of 18{degrees} to the right of the midline. We demonstrated this approach using patients with hemispatial inattention, but it can be applied to any fixation-based or dwell time data. This is an advance on current methods that generated visual heatmaps or attentional maps, as our technique allows formal testing of spatially extended hypotheses on gaze duration data using a standard, frequentist statistical approach.

Background and ObjectiveGlioblastoma outcome prediction remains difficult because clinically relevant signals are distributed across heterogeneous imaging and genomic modalities, cohorts are small, and conventional neural predictors do not quantify their own uncertainty. This study evaluates a hybrid neural-Bayesian belief network framework for uncertainty-aware multimodal glioblastoma prediction and examines how modality selection, model family, and structure-aware regularization affect predictive performance and confidence quality. MethodsThe framework was evaluated on the TCGA-GBM radiogenomic cohort using four input modalities (T1Gd, FLAIR, mRNA, and CNA), five model families, five structural-weight settings, and 15 view subsets. A secondary benchmark on the UCI Human Activity Recognition dataset was included to assess whether observed limitations were specific to the glioblastoma setting. ResultsCNA features consistently reduced performance in most multimodal settings, and selective fusion excluding CNA outperformed both the full four-view baseline and imaging-only alternatives. Model families showed clear differences in uncertainty behaviour: non-Bayesian families achieved the strongest predictive accuracy, whereas the Bayesian family achieved the lowest calibration error over a narrower confidence range. Bayesian belief network regularization produced consistent directional improvements without supporting reliable structure-discovery claims, as learned graph structures were not reproducible across folds. On the secondary bench-mark, the same framework achieved much higher predictive performance, indicating that the glioblastoma performance ceiling primarily reflects data limitations rather than an architectural constraint. ConclusionsIn small-sample radiogenomic prediction, modality choice is at least as important as model choice, and uncertainty quality differs substantially across uncertainty-aware model families. The proposed framework provides a practical basis for comparing accuracy, calibration, modality selection, and structure-aware regularization in multimodal biomedical prediction.

Neuroimaging based pain decoding faces two underappreciated challenges: between subject variability that prevents classifiers from generalizing across patients, and within session cross validation designs that inflate reported accuracy by conflating within person and between person variance. Here we address both using portable functional near infrared spectroscopy (fNIRS) during pharmacologically verified local nerve anesthesia. Twentyfive patients with clinically painful teeth underwent 36 channel bilateral fNIRS during percussion before ("Pre") and after ("Post") local nerve anesthesia. In 13 block-success patients, a paired Pre versus Post comparison with healthy tooth control identified three temporal hemodynamic response function (HRF) features (late slope, mean first derivative, and baseline normalized amplitude) whose analgesia interaction effects (d = 0.63 to 0.79) exceeded that of raw general linear model (GLM) amplitude (d = 0.56), with a significant difference-in-differences interaction (p = 0.011). Per-patient calibration with these features yielded leave one subject out (LOSO) AUC = 0.68 to 0.76 for nonlinear classifiers (permutation p = 0.002), with HbO-specific feature selection achieving the best performance (RF AUC = 0.760); a healthy tooth negative control was non-significant. End to end deep learning on raw time series (CNN LSTM AUC = 0.719) was competitive with feature based classifiers, while linear models did not reach significance. Critically, head to head comparison of within-session CV and LOSO on the same data revealed mean inflation of +0.13 AUC across all model types, including deep learning, demonstrating that high within session accuracy alone does not establish subject-independent validity. Exploratory analyses suggested complementary roles for oxyhemoglobin (HbO; within patient analgesia detection) and deoxyhemoglobin (HbR; cross patient information), and that trial to trial response variability may complement amplitude for cross patient pain detection. These results show that per patient calibration with temporal HRF features supports subject independent analgesic-state detection under strict LOSO evaluation, and that within-session validation (standard in the fNIRS pain- decoding literature) can substantially overestimate performance.

PurposeAlthough electroretinography (ERG) is vital for evaluating retinal function, conventional corneal electrodes slide or detach in animals. This study aimed to investigate the effectiveness of a novel approach to ERG recording using a metal eyelid speculum for both active and reference electrodes in conjunction with a skin electrode-based ERG device. MethodsWe tested a stainless-steel eyelid speculum as both active and reference electrodes with a skin-electrode ERG system (HE-2000vet) in six healthy Japanese White rabbits. Dark-adapted rod and maximal responses and light-adapted cone and 30 Hz flicker ERGs were recorded in three weekly sessions. ResultsReproducible waveforms with identifiable a- and b-waves were obtained in every eye; rod b-waves reached 50-90 {micro}V and cone b-waves 40-55 {micro}V. Intraclass correlation coefficients revealed substantial interocular agreement and moderate-to-substantial inter-session reproducibility for b-wave amplitude and implicit time, whereas a-wave metrics were less reliable owing to lower amplitudes. The advantages of speculum electrode over corneal electrodes are that it requires no fur shaving, maintains stable contact regardless of globe orientation, and allows real-time observation. ConclusionsThis study demonstrated that an eyelid-speculum electrode is a practical, non-invasive alternative for veterinary and experimental ERG recordings, producing signal quality sufficient for longitudinal and interocular analyses while avoiding cosmetic and technical drawbacks of conventional methods.