BMC Neuroscience

Alterations of fluorescence properties in retinal pigment epithelium (RPE) cells caused by diseases such as age-related macular degeneration (AMD) highlight the need for detailed analysis of the fluorescent RPE granules at the individual level. Precise segmentation and classification of these granules remain challenging due to their limited visual separability. In this study, we present Classi4RPE, a computational algorithm designed to accurately segment RPE granules and classify them into three categories -- lipofuscin (L), melanolipofuscin (ML), and melanin (M) -- based on fluorescence lifetime imaging data, which provide distinctive contrast. The method is implemented in a custom Python framework and employs seeded watershed segmentation to isolate individual granules. Lipofuscin granules are identified as hyperfluorescent structures with longer lifetimes, while granules with shorter lifetimes are further analyzed based on their spatial lifetime distribution from the center to edge, enabling discrimination of ML from other melanin-rich granules. Our approach achieves high performance, with mean sensitivities of 0.99 for L granules and 0.90 for ML granules, and corresponding specificities of 0.93 and 0.98, respectively, compared to manually annotated ground truth. These results demonstrate the potential of Classi4RPE to surpass human visual limitations and provide a robust tool for quantitative RPE analysis.

Organisms have spent their life histories exposed to background levels of natural ionizing radiation. To document the role that radiation plays, the deprivation of these natural levels has been studied by incubating organisms in the shielded space of underground laboratories. We report here on two studies (Study I and Study II) using Aedes aegypti for the first time as a model organism incubated 655 meters underground at the Waste Isolation Pilot Plant (WIPP) outside of Carlsbad, New Mexico, U.S.A. Male mosquitos were incubated at the surface exposed to natural background radiation, and were compared to two underground treatments in which incubators were supplemented with radiation sources used to mimic background and these groups were compared to the underground, radiation-deprived treatment. In Study I, the mosquitos incubated underground in the absence of natural radiation had higher levels of mortality compared to those incubated at the surface and PCA plots of the two transcriptomes were clearly differentiated. Study II was conducted the following year and the experiment was narrowed to include only the surface control and underground, radiation-deprived treatment which allowed for four biological replicates. Again, there was a higher level of mortality in the mosquitos grown underground compared mosquitos grown at the surface. Transcriptomes were not as clearly differentiated by PCA analysis and fecundity data were similar between the two groups. Functional analysis of transcriptomic DEGs from two independent studies suggested there are stress responses in radiation deprived mosquitoes. The absence of a secondary stressor in Study II is discussed as an explanation for the transcriptome differences in the two experiments.

SignificanceDigital Holographic Microscopy (DHM) provides label-free quantitative phase images (QPIs) of living cells and has become a powerful tool for studying cellular morphology and dynamics. While most DHM studies have focused on cell-level analysis, the quantitative characterization of neuronal network organization and maturation from DHM images remains largely unexplored, highlighting the need for dedicated computational approaches. AimWe aimed to develop an automated framework combining deep-learning-based image analysis and graph theory to quantitatively characterize the organization, connectivity, and maturation of neuronal networks in primary rat cortical cultures imaged by DHM. ApproachTwo U-Net convolutional neural networks were trained on manually annotated DHM phase images to segment neuronal cell bodies and neurites. The resulting segmentation maps were used to infer putative morphological connections between neurons and generate graph representations of neuronal networks, referred to as graph fingerprints. A panel of 18 connectomics-inspired graph features was then computed to characterize local and global properties of network organization across four stages of culture maturation. ResultsThe mean area under the receiver operating characteristic curves was 0.98 for cell-body and 0.91 for neurite segmentation, indicating near-perfect identification. Graph-theoretical analysis revealed reproducible topological changes during network maturation in vitro, including increased density, reduced modularity, and progressive network integration. Correlation analysis showed that the 18 graph features grouped into two highly correlated families. A Random Forest classifier identified density and modularity as the most informative descriptors, achieving an accuracy of 87% in classifying maturation stages of neuronal cultures. ConclusionsOur results demonstrate that combining DHM, deep-learning-based segmentation, and graphtheoretical analysis enables quantitative characterization of neuronal network organization and maturation from label-free phase images. This framework provides a foundation for future studies of pharmacological experiments, neuronal network phenotyping, and human induced pluripotent stem cell (hiPSC)-derived neuronal cultures, where quantitative assessment of network organization remains a major challenge.

Valproic acid (VPA) is a widely used antiepileptic drug that also increases the risk of neurodevelopmental disorders in the offspring of exposed mothers. Prenatal exposure to VPA is a widely used rodent model of autism spectrum disorder (ASD). Anatomical, functional and molecular alterations in the retinas of various ASD model animals have been described in the literature, but the impact on the neural composition of the retina remains unclear. We examined whether and how the density and spatial regularity of selected retinal neurons are altered in the VPA induced model of ASD. Whole-mount retinas of 2-month-old VPA-treated and control animals were immunolabeled for S-cones, horizontal cells, AII amacrine cells, and parvalbumin-positive wide-field amacrines (PV-wfACs), and the positions of labelled cells mapped in various regions of interest (n = 39 for treated, n = 32 for control animals) across the retinas. Multivariate analysis of variance revealed a significant overall effect of VPA on cell densities (p = 6.1x10-7, 2 = 0.43), driven mainly by reduced AII amacrine density, while horizontal cells showed a modest reduction and S-cones were unaffected. After adjusting for retinal location, analysis of covariance indicated a 7% decrease in AII cells and a 15% increase in PV-wfACs. Regularity indices calculated from nearest neighbor distances or Voronoi-domain areas of cell mosaics were largely unchanged. These findings suggest that prenatal VPA exposure selectively alters inhibitory inner retinal circuitry in the rat ASD model at the time of cell differentiation, but self-organizing mechanisms responsible for spatial order are not affected. Lay SummaryValproic acid (VPA) is a medicine for epilepsy, but it can also raise the risk of autism in children when taken during pregnancy. In rats exposed to VPA before birth, we found changes in certain nerve cells of the retina: one type of cell important for night vision was reduced, while another type increased slightly, while most other cells stayed the same. This suggests that the changes in development that lead to autism may also be reflected in the structure and function of the eye.

Quantifying blood-brain barrier (BBB) integrity from fluorescence microscopy remains limited by subjective scoring and categorical classification methods that lack reproducibility. For objective and consistent BBB phenotyping, we present two semi-automated image-analysis pipelines that replace manual scoring with quantitative, continuous-variable measurements. Our in vitro pipeline, implemented in Python, quantifies the connectivity of tight junction structures by measuring discrete ZO-1 fragment objects within manually traced junction regions. It outputs continuous metrics including average fragment area, total junctional area, and a junctional fragmentation ratio that captures degree of ZO-1 continuity versus discontinuity. In human brain microvascular endothelial cells subjected to glycocalyx component knockdown, the pipeline detected significantly reduced fragment area (37% decrease for both CD44 and syndecan-1 (SDC1) knockdown, p = 0.0148 and 0.0084) and junctional fragmentation ratio (p = 0.0061 and 0.0137). Our in vivo pipeline integrates ilastik-based pixel classification with FIJI macro automation to quantify vascular marker colocalization and to separate vessel signal from microglial contamination within a single fluorescence channel, eliminating the need for dedicated counterstains. Applied across four mouse cohorts [young, aged, Alzheimer's, traumatic brain injury (TBI)] and three brain regions [prefrontal cortex (PFC), hippocampus, midbrain], the pipeline revealed concurrent ZO-1 loss and ICAM-1 elevation in the PFC and hippocampus of aged and Alzheimer's mice, with Alzheimer's-specific doubling of eNOS occurring in the PFC (p = 0.0013). TBI mice showed persistent ZO-1 loss with transient ICAM-1 and eNOS changes. Both deterministic pipelines are available on GitHub and designed for adoption beyond the specific markers and systems analyzed here.

The use of meditation as a tool to improve human wellbeing is receiving considerable scientific interest. However, most existing research has focused on concentration-based practices. One powerful alternative is jhana meditation, which leads to states characterised by self-reinforcing bliss, potentially useful for a variety of clinical and scientific domains. However, our understanding of these states is limited by small amounts of data and poor access to experts. To enable new insights, here we release the largest to date and first open-access dataset of electroencephalographic and physiological recordings in expert Jhana meditators. This includes 100+ hours of data in N=26 subjects across three retreats, alongside a detailed description and example code illustrating analysis of the data. This open dataset release can enable wider collaboration and has the potential to move us closer to an understanding of endogenously generated altered states of consciousness.

Over the last decade, pre-clinical research has witnessed the advancement of human induced pluripotent stem-cell derived 3D brain organoid models and their differentiation into specific brain regions. In the realm of Parkinsons disease research, development of midbrain-specific organoids has enabled studies of this neurodegenerative disorder in patient derived 3D organoid models that attempt to recapitulate the human brain complexity. Within this line of research, neural functionality of the organoid models is established through electrophysiology. As a novel methodological approach, this study aimed to establish whether clustering of electrophysiological activity originating from midbrain organoids would aid in identifying different types of action-potential waveforms exhibited by neurons within the organoid model. Long-term extracellular electrophysiological recordings were conducted by use of a multi-electrode array device. The local field potential signal was spike-sorted, and the extracted putative neuron units were clustered into groups of spike waveform profiles. After establishing this methodological analysis pipeline, the clusters of waveform types were further analyzed in terms of electrophysiology. Results revealed that the clustering approach was successful at identifying three types of spike waveforms categories. Furthermore, it was proposed that one spike waveform profile potentially originated from dopaminergic neurons, which were one on the neural cells populating the organoid models. Overall, this study has successfully established a new methodological clustering approach to analyze electrophysiological data recoded from 3D organoid models in the context of Parkinsons disease modelling and organoid model development research.

Animals balance staying in a favorable environment with exploring new ones. In C. elegans chemotaxis, the process by which worms migrate toward an attractant has been extensively studied. However, what happens after they reach it remains largely unexplored, partly because conventional assays immobilize worms at the point of arrival. Here, we quantitatively analyzed chemotactic behavior upon reaching an attractive odor source using an immobilization-free chemotaxis assay. We observed that 62% animals left the isoamyl alcohol region after initially approaching it, a behavior we termed "leaving behavior." Quantitative analysis revealed that leaving behavior represents a distinct locomotor state compared with free-moving, high-concentration odor avoidance, and approach behavior. To test whether leaving behavior is related to olfactory adaptation, we analyzed mutants in adaptation-related genes. The proportion of leaving behavior was significantly increased in egl-4 loss-of-function mutants compared with wild-type animals, whereas arr-1 mutants showed no significant difference. These results suggest that egl-4 negatively regulates leaving behavior, suggesting a role for this kinase in stabilizing post-arrival behavioral states beyond its known function in olfactory adaptation. Our findings indicate that chemotaxis involves dynamic behavioral transitions even after reaching an attractant, consistent with an exploration-exploitation trade-off framework.

Defects in Drosophila Cu2+/Zn2+ superoxide dismutase (encoded by the gene Sod1) lead to elevated oxidative stress and a drastically shortened lifespan. To contrast the effects of aging and oxidative stress on nerve conduction, synaptic transmission, and muscle excitability, we developed an easily accessible adult abdominal neuromuscular preparation, utilizing the male-specific Muscle of Lawrence (MOL) in Drosophila. The large size of MOL facilitated analyses of presynaptic nerve signals and postsynaptic responses that could result in sizable excitatory junctional potentials (EJPs) evoking full-blown muscle action potentials (APs) which were terminated rapidly by a characteristic afterhyperpolarization (AHP). Aged wild-type (WT) individuals (80 days or older) exhibited diminished neuromuscular transmission, mainly reflecting declines in motor axon conduction, with synaptic transmission remaining largely intact (since robust EJPs could still be evoked when nerve terminals were directly stimulated electrotonically). Additionally, muscle APs showed enhanced depolarizing peaks and weakened AHPs during current injection, suggesting weakening in repolarizing K+ currents. Chronologically younger Sod1 mutants (up to 30 days) displayed similar trends of neuromuscular changes, confirming a major role of oxidative stress in aging. However, certain distinctions exist in muscle membrane properties and transmitter release machinery. A clear increase in muscle membrane resistance was seen in Sod1 but not in aged WT. Additionally, unlike normal spontaneous release of synaptic vesicles leading to miniature EJPs (mEJPs), extremely enlarged spontaneous transmitter discharges occurred in aged WT but was never seen in Sod1, indicating a distinct, aging-specific alteration in transmitter release regulation. Notably, our work revealed considerable variation among individuals, ranging from transmission failure to largely intact neuromuscular functions, demonstrating the stochastic nature of functional declines due to aging and oxidative stress. Moreover, this study uncovered a well-defined common vulnerability, i.e. weakening of the Ca2+-activated BK current that caused drastic reduction in AHP in both aged WT and Sod1 mutants, as confirmed by their diminishing sensitivity to the BK channel blocker paxilline, which caused striking alterations in the AHP in WT control.

Optical recording from large numbers of neurons is an indispensable technique for studying neuronal ensembles. We use optical sectioning through pinhole illumination to reduce the background fluorescence (F0) and increase the optical signal ({Delta}F/F0) in ex vivo brain slices densely labeled with GCaMP6f, allowing an ordinary fluorescence microscope to capture calcium transients from over 300 individual CA1 neurons - a marked increase compared to ordinary wide field fluorescence illumination. Multiple layers of overlapping neurons can be identified by their locations and the shape in space of their {Delta}F/F0 images. A single pinhole mask was placed at the field stop of a wide field illuminator, and the image of the pinhole was projected onto the tissue by a 20X NA 0.95 water immersion objective (Olympus). This created an illuminated disk with a diameter of [~]200 m and optical sections of hippocampal CA1 pyramidal layer tissue [~]100 m thick. This illumination blocked a large fraction of the F0, which in turn increased the {Delta}F/F0 5-10-fold compared to that of wide field illumination. When putative pyramidal neurons fire sparsely in the brain slice, up to 300 partially superimposed neurons can be identified by their shape and spatial location in the thick ([~]480 m) ex vivo slice in the CA1 area surrounding the pinhole image. The signal-to-noise ratio was adequate even at a low excitation light level of [~]20k photoelectrons per pixel well on the camera, allowing for 3,000 seconds of total recording time without significant bleaching. This pinhole "half confocal" method has created a useful way to sample calcium transient signals in thick tissue with a large population of neurons densely labeled with GCaMP-6f.

Traumatic brain injury (TBI) has long-term consequences that include chronic traumatic encephalopathy (CTE) and an elevated risk for Alzheimer Disease (AD). These dementias ultimately manifest as tauopathies but may begin with acute neuronal dysfunction including post-traumatic seizures. Provocative evidence suggests that these prodromal seizures are a viable target to mitigate the later onset of dementias, and anti-epileptic drugs (AED) that increase the threshold of action potentials have indeed been shown to mitigate later tauopathies[1, 2]. Here, we test whether AEDs and other compounds that modulate synaptic transmission, applied immediately after TBI, can also act as prophylactics that block subsequent CTE-like tau aggregation and neurodegeneration in a larval zebrafish model. Levetiracetam (LEV) is an AED that modulates synaptic vesicle release. Application of LEV immediately following TBI abrogated TBI-induced tau tau aggregation (IC50 = 3.168 x10-3 mM) and cell death in the larval zebrafish TBI model. We next considered a polypharmacy approach involving mGluR2, because mGluR2 positively allosteric modulators (PAMs) such as JNJ-42153605 have previously been able to improve LEVs action in reducing some recalcitrant forms of seizure in a mouse model. We found that JNJ-42153605 was itself effective at blocking TBI-induced tau aggregation (IC50 = 8.691 x10-5 mM). Moreover, a subeffective dose of JNJ-42153605 (10-5 mM) was able to substantially improve the efficacy of LEV (~16-fold) in its prophylactic actions. Thus, LEV and JNJ-42153605 applied briefly after TBI offer a potent polypharmacy approach, at least in our preclinical animal model, to tackle the later tau aggregation and neurodegeneration that follows from TBI neurotrauma. These results warrant further investigation, including testing into mammalian TBI models (with longer disease course).

Tonic glutamate signaling by ambient levels of extracellular glutamate has been implicated in development, brain injury, pathologies, and physiological activity. However, it has been difficult to assay extracellular glutamate changes with spatial and temporal resolution. Here, we utilize the rarely used ratiometric excitations properties of the fluorescence glutamate sensor iGluSnFr to enable the characterization of ambient glutamate levels in acute brain slices. This ratiometric imaging enables a spatial, temporal and calibratable assay of ambient glutamate and demonstrates regional differences in ambient glutamate and sensitivity to glutamate transporters and system Xc inhibition.

While a growing number of studies have linked environmental exposures and Parkinsons disease (PD)1-3, the impact of many pesticides remains understudied4,5; for example, neonicotinoids are the most used insecticides in the world, but research into their contribution to PD is limited to a handful of studies6-8. Newer pesticides, such as the butenolide flupyradifurone (FPF), specifically developed to overcome increased pest resistance9 and spurred on by tighter restrictions on neonicotinoids such as imidacloprid (IMI)10, are even less studied. New approach methodologies (NAMs) that allow for rapid evaluation of pesticide exposures are needed to evaluate potential links between the growing number of pesticides and PD11. To this end, we exposed the model nematode Caenorhabditis elegans12 to IMI and FPF. Due to its high degree of tractability, and conservation of many genetic, neuronal, and toxic mode of action processes, C. elegans has been invaluable in both elucidating mechanisms and novel therapeutic targets for PD that can be validated in other models13, and as a complementary tool for early toxicity screening14. Along this line, we found that exposure to IMI, and to a greater extent FPF, in young adult animals causes significant dendritic blebbing, an early sign of neurodegeneration, exclusively in dopaminergic neurons. Blebbing was accompanied by impairment of dopamine-mediated behaviors, changes in neuronal mitochondrial morphology, and elevation of pathways related to reactive oxygen species (ROS). We were able to reduce the blebbing caused by IMI and FPF two ways: 1) pharmacologically via administration of the antioxidant N-acetyl cysteine (NAC); 2) genetically via knockout of a MAP kinase (MAPK) stress response pathway. This suggests that oxidative stress is a key mediator of this insecticide-induced dopaminergic neurodegeneration.

Purpose: Animal models of myopia typically induce monocular refractive shifts via form deprivation (FD) or lens-induced myopia (LIM), modeling susceptibility to myopia, but with potentially limited applicability to childhood myopia. Here we describe a novel, genetically diverse mouse model of naturally occurring refractive error (NORE) with three distinct refractive phenotypes: hyperopic, myopic, and intermediate. Methods: C57BL/6J mice were mated to 129S2/SvPasCrl mice to create F1 or F2 offspring. Refractive errors in male and female F1 (N=21) and F2 (N=101) mice were assessed on postnatal days (P) 28 and 42 using photorefractometry. In a subset of mice (N=30 - 40), corneal radius of curvature, axial ocular dimensions, retinal and visual function were assessed. Results: F2 mice were classified as NORE with either hyperopic (RE [&ge;] 0 diopters (D) at P28 and P42), myopic (RE<0D at P28 and P42) or intermediate (RE<0D at P28 and RE [&ge;] 0D at P42) refractions based on individual trajectories. All ocular parameters changed with age, with significantly slower growth in axial length and vitreous chamber depth in the intermediate versus myopic mice (p<0.05). Lens thickness was smaller in the myopic group at P28. Differences in refraction were not attributed to variances in retinal function or dopamine signaling. Conclusions: NORE mice represent a novel, genetically diverse wild-type mouse model that, unlike traditional models, does not require interventions such as FD or LIM to induce myopia. NORE mice provide a valuable tool for future investigations of genetic and environmental mechanisms and targeted therapeutic strategies for refractive errors.

IntroductionThe proteasome is a critical cellular degradative machinery impaired in late-stage Alzheimers disease (AD). However, the status and activity of the proteasome in early-stage sporadic AD (sAD) is unknown. MethodsA cellular model of human early-stage sAD was generated from sAD patient iPSC-derived cortical neurons by dual-SMAD inhibition. The iPSCs, neuroprogenitors, and cortical neurons were validated by the expressions of key markers. The level of total intraneuronal A{beta} was measured by ELISA. Composition and native proteolytic activities of the proteasome in control and sAD cortical neurons were measured using complementary fluorogenic probes. ResultsControl and sAD patients iPSCs expressed pluripotent markers OCT4, NANOG, and SSEA4 which induced into neuroprogenitors expressing NESTIN and PAX6. The neuroprogenitors terminally differentiated into cortical neurons expressing neuronal markers MAP2 and TUJ1, and cortical layer marker TBR1. The level of intraneuronal A{beta} in the sAD cortical neurons was significantly higher compared to control. Control and sAD cortical neurons expressed native 30S, 26S, and 20S proteasome assemblies with the sAD cortical neurons displaying higher 20S assemblies. Increased active 20S assemblies was associated with higher {beta}1, {beta}2, and {beta}5 proteolytic sites activities. DiscussionThe significant elevation in the proteolytic activities of the {beta}1, {beta}2, and {beta}5 subunits of 20S proteasome in sAD cortical neurons suggests that this may be a possible compensatory response to elevated intraneuronal A{beta}. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/734021v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1d8c382org.highwire.dtl.DTLVardef@b92e8org.highwire.dtl.DTLVardef@1d9c699org.highwire.dtl.DTLVardef@7d826d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Traumatic brain injury (TBI) induces rapid neuroinflammatory responses not only in the brain but also in anatomically and immunologically connected central nervous system (CNS) compartments, including the retina. In our study, we investigated retinal microglial activation, retinal ganglion cell (RGC) calcium dynamics, and caspase-3 activation in adult mice subjected to severe traumatic brain injury using the Marmarou impact-acceleration model at 24 and 48 h post-injury. Carrying out Ca{superscript 2}-imaging, immunohistochemistry, and ex vivo time-lapse microscopy, we found robust microglial activation in both the superficial and deep retinal layers following TBI, accompanied by increased microglial motility. RGCs exhibited a transient surge in degeneration-induced spontaneous activity at 24 h, followed by a marked reduction below control levels at 48 h, consistent with early degenerative changes. Activated caspase-3 levels were significantly elevated in both microglia and other retinal cell types at both time points, indicating ongoing apoptotic effects. Together, these findings demonstrate that TBI rapidly triggers inflammatory and apoptotic mechanisms in the retina, which are detectable within the first 48 hours. Our results highlight the retina as a sensitive indicator of early CNS pathology after traumatic injury and underscore the potential of retinal analysis for monitoring TBI-induced neurodegeneration for future clinical implementation. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/734783v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@5bc694org.highwire.dtl.DTLVardef@14a4ce4org.highwire.dtl.DTLVardef@fe2d32org.highwire.dtl.DTLVardef@149419d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Motivation: Linkage disequilibrium score (LDSC) regression is a popular method to estimate heritability for complex traits using summary statistics and linkage disequilibrium (LD) reference panels, offering a practical alternative to methods requiring individual-level data. Despite its widespread use, LDSC regression can produce biased heritability estimates. The properties of LDSC regression were investigated using summary statistics from several large-scale Alzheimer's disease (AD) studies and a variety of LD reference panels. These heritability estimates were compared with those obtained from individual-level data. Results: When LDSC regression was applied to summary statistics obtained from meta-analysis, it led to an underestimation of heritability. This can occur if meta-analysis is used to combine studies of different ancestries leading to the caveat of the lack of an appropriate LD reference panel. Additionally meta-analyses often include studies with different phenotype definitions, that not only impacts heritability estimates but also makes them uninterpretable. Summary statistics generated from imputed variants, even those with high imputation accuracy, can lead to underestimation of heritability. For example, the heritability estimates for AD were reduced from 0.265 (se 0.148) to 0.160 (se 0.041) when imputed variants (INFO>0.9) were included compared to analyzing only genotype array variants. A decrease in heritability estimates was also observed when individual-level imputed variant data were analyzed using GCTA-GREML. Our findings highlight the caveats of estimating heritability using meta-analysis summary statistics or imputed data instead of genotyped or sequence data.

INTRODUCTIONDistinguishing healthy brain aging from early neurodegenerative disruption remains a major challenge in Alzheimers disease. METHODSUsing resting-state fMRI from the Alzheimers Disease Neuroimaging Initiative (357 participants; cognitively normal, mild cognitive impairment, Alzheimers disease), we trained a Hidden Markov Model exclusively on cognitively normal adults to define latent connectivity states. A generalized additive model estimated an age-adjusted reference trajectory of transition entropy, and subject-specific deviations from this trajectory were quantified. RESULTSMild cognitive impairment and Alzheimers disease showed progressively greater deviation from the normative reference, with the strongest disruption in Alzheimers disease. A single absolute-deviation score retained much of the predictive information contained in higher-dimensional dynamic features. DISCUSSIONThese findings suggest Alzheimers disease is associated with measurable departure from healthy dynamic brain aging, providing an interpretable framework for future longitudinal and clinically validated studies.

The behavioural activity of freely moving animals is a confounding factor that affects the recording, analysis, and final results of animal EEG experiments. Along with the lack of standardisation in animal in vivo electrophysiology experiments, this could lead to huge inconsistencies, especially in the analysis of centrally acting drugs. Therefore, the main aim of this paper is to investigate the effects of behavioural activity versus inactivity on the multichannel EEG in freely moving rats. In a large sample (n = 116) of waking recordings from 12 cortical electrodes (ECoG) in Wistar rats, we evaluated behavioural activity-related changes in the power spectrum, current source density, and power-based global functional connectivity (GFC) in a 3D rat brain model, according to the TOHOKU Rat Brain Atlas. The main findings were that behavioural activity induced 1) a robust power increase in 6-8 Hz, peaking at 7 Hz with maximum changes over the parietal and temporal cortex, 2) an increase in gamma power (30-80 Hz) across the whole brain, 3) a decrease in delta (1-4 Hz) and beta (12-30 Hz) power across the whole cortex. Changes were also localised in subcortical regions, particularly in the diencephalon/thalamus. The GFC analysis showed a similar pattern of power changes across the 6-8 Hz, delta, and beta bands; however, GFC in the gamma band decreased. Again, the GFC analysis revealed changes in connectivity within subcortical structures, primarily in the thalamus. None of the measures was affected in the alpha band (8-12 Hz). These findings emphasise behavioural state as a critical factor influencing EEG outcomes, with important implications for the standardisation and translational validity of preclinical neurophysiological studies.

BackgroundConventional rodent models for the study of corneal pain commonly evoke eye blink reflex using methods that indiscriminately activate polymodal nociceptors, mechanoreceptors, and thermoreceptors at temporal resolutions that dont closely match the sub-second timescale of underlying neural dynamics. New methodWe introduce a novel automated behavioral paradigm for detecting blink reflexes in transgenic TRPV1-ChR2-EYFP mice, enabled by cell-type-specific, millisecond-precision optogenetic stimulation of corneal nociceptors (490 nm light). Using multi-feature quantification, we achieve robust automated detection using univariate and multivariate classifiers. ResultsTRPV1-ChR2-EYFP mice exhibited blink reflexes to high-intensity blue light (490 nm, 10 ms pulses) in a threshold-dependent manner (N=3). Blink probability was 77.1 {+/-} 17.1% at high intensity (2.77 mW/mm2) versus 4.2 {+/-} 4.2% at low intensity (0.46 mW/mm2). Red light (638 nm) produced no intensity-dependent change. Noxious air puff evoked blinks in >95% of trials under all conditions. DeepLabCut-based pose estimation extracted six features quantifying the blink reflex, enabling automated detection with [&ge;]98% accuracy using univariate and multivariate classifiers. Comparison with existing methodsUnlike conventional air puff paradigms, this optogenetic approach enables precise, cell-type-specific stimulation of corneal nociceptors, supporting automated analysis of blink responses at sub-second resolution. ConclusionsThis video tracking behavioral method using machine learning algorithms that accurately classify blink versus no-blink enables high-throughput and observer-independent empirical assessment of blink reflex, suggestive of corneal pain. Moreover, inducing blink reflex in TRPV1-ChR2 mice using high-intensity blue light also demonstrates nociceptive-specific behavioral responses analogous to somatosensory optogenetically-evoked hindpaw pain in the same animal genotype.