BMC Neuroscience

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.

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.

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.

A test technique for measuring high-frequency transient current components in deep brain tissue is presented. The technique applies a voltage pulse with a high value in dV/dt, generating a corresponding current pulse with high dI/dt that can elicit measurable transient current responses from the electrode/tissue interface and adjacent brain tissue; responses are analyzed in the frequency domain by Fast Fourier Transform at a 200 kHz sampling frequency. The method was motivated by prior evidence that ferritin and neuromelanin in catecholaminergic tissue may support high-frequency conduction properties that have not previously been characterized in vivo. The protocol was applied in 277 measurements across five Sprague Dawley rats at cortical and basal ganglia locations in different locations in the brain. Preliminary spectral results show differences between catecholaminergic regions and cortical tissue that support further development and validation of the method.

The kynurenine pathway metabolizes tryptophan into 3-hydroxykynurenine (3-HK), a precursor for ommochrome eye pigments synthesized via the cardinal (cd) gene in mosquitoes. While cd disruption was presumed neutral, we observed fitness costs in Anopheles stephensi knock-in but not knock-out cd mutants. Here we investigated this anomaly further by assessing survival, fecundity, and midgut integrity across multiple cd mutant lines. Heterozygous knock-in lines, expressing a fluorescent marker and guide RNA for CRISPR/Cas9, exhibited reduced survival post-blood feeding, larva-to-adult survival deficits, and midgut barrier dysfunction, whereas knock-outs showed no such costs. Oral supplementation with xanthurenic acid partially rescued knock-in mortality, implicating oxidative stress linked to 3-HK metabolism. Expression analyses suggest transgene insertion effects, rather than cd disruption, underlie these fitness costs. These findings highlight the importance of evaluating insertional effects in gene drive target selection and support cd as a viable target for genetic control strategies in An. stephensi.

Sleep is a ubiquitous, yet highly variable, behavior across species. The duration and timing of sleep are influenced by ecological demands and dietary context. In the mosquito Aedes aegypti, a blood-feeding insect with specialized nutritional requirements, the relationship between feeding and sleep remains poorly understood. Here, we investigated how blood-derived dietary protein influences sleep regulation. Using postural analysis, videography, and arousal-threshold assays, we established that immobility bouts of greater than 10 minutes reliably define sleep in Ae. aegypti. Mosquitoes lacking the circadian clock gene cycle still maintained daily sleep rhythms but exhibited reduced sleep duration and heightened overall activity. Infrared activity monitoring revealed that blood-fed females showed a marked increase in sleep beginning immediately after feeding and persisting for several days, accompanied by reduced locomotor activity. Notably, this sleep elevation lasted well beyond the cessation of previously reported host-seeking phases, raising the possibility of distinct phases of opportunistic versus targeted host pursuit. To determine the dietary basis of this effect, we tested mosquitoes fed a bovine serum albumin (BSA)-based diet. BSA feeding alone was sufficient to mimic the sleep-promoting and activity-reducing effects of blood, suggesting dietary protein is a major nutritional regulator. Moreover, RNAi-mediated knockdown of the leucokinin receptor (Lkr), which has previously been associated with fluid homeostasis and feeding behavior, resulted in enhanced sleep and reduced activity, implicating mosquito LK signaling in the modulation of postprandial sleep. Together, these findings demonstrate that blood-derived proteins drive sustained increases in sleep and reductions in locomotor activity in Ae. aegypti. This work positions Ae. aegypti as a model for dissecting nutrient-specific regulation of sleep and highlights potential adaptive functions of protein-induced quiescence, such as energy conservation and predator avoidance. More broadly, it provides insight into how specialized diets shape the neural and behavioral architecture of sleep.

Many nonhuman primate species recapitulate the neuropathological features of sporadic Alzheimer's disease (AD) to varying degrees. As with humans, the assessment of AD-related pathology in nonhuman primates has historically relied on the use of postmortem brain tissues. In vivo alternatives, such as PET imaging tracers and fluid biomarkers, have been developed for use in humans but require further validation in nonhuman primates before replacing postmortem analyses. Here we employed the Nucleic Acid-Linked Immuno-Sandwich Assay (NULISATM) CNS Disease panel to compare age-related changes in plasma biomarkers in two nonhuman primate species (rhesus monkeys and baboons). In addition, we examined whether amyloid and tau biomarkers were associated with brain atrophy, as measured by gray matter volume. We found significant associations between age and multiple biomarkers of neurodegeneration for both species, as well as significant differences in the patterns of these associations between the two species. For the phosphorylated tau measures, though rhesus monkeys had higher values, baboons showed significant and stronger associations with age. By contrast, rhesus monkeys exhibited an earlier age-related decline in A{beta}42/A{beta}40 ratio than baboons. Finally, in both species, lower A{beta}42/A{beta}40 ratios were associated with lower gray matter volumes. This is the first systematic comparative study of age-related changes in neurodegeneration biomarkers in two closely related nonhuman primates using comparable age ranges and sample sizes, and the same multiplex assay. Future studies should examine longitudinal changes in these biomarkers as well as validate the plasma findings using cerebral spinal fluid.

The ultimate cause of blindness in glaucoma is the death of retinal ganglion cells, and understanding the mechanism behind retinal ganglion cell loss during glaucoma could lead to the development of novel treatments for glaucoma. Endothelin-1 has been shown to mediate retinal ganglion cell death during glaucoma through impairment of mitochondrial function. Retinal ganglion cells are highly metabolically active, and susceptible to oxidative damage and decreased respiratory capacity. Mitophagy is the process whereby damaged mitochondria are degraded to prevent further propagation of oxidative damage. The current study evaluates the effect of endothelin-1 on mitophagy in retinal ganglion cells. Electron microscopy revealed endothelin-1 administration lead to a decrease in healthy mitochondria in the optic nerve. The MitoQC mouse was used to evalute mitophagy in response to endothelin-1, along with immunohistochemical analysis of mitophagy proteins. Mitophagy follows different trends in the optic nerve and retinal ganglion cell bodies following endothelin-1 administration, mitophagy was increased in the optic nerve but decreased in the retina following endothelin administration. With elevation of intraocular pressure, mitophagy was increased in the retina but decreased in the optic nerve. In retinal ganglion cells, parkin expression and activation was unchanged 24 hours after endothelin-1 administration, but was decreased 72 hours following endothelin-1 administration. Taken together, these results suggest that endothelin-1 impacts mitophagy through parkin-independent mechanisms in retinal ganglion cell bodies, and the ganglion cell bodies and optic nerve appear to have different responses to endothelin-1.

Cav1.2 is an L-type voltage-gated Ca2+ channel (VGCC) that supports Ca2+ influx in response to membrane depolarization. Ca2+ entering via Cav1.2 alters gene expression, activates Ca2+-dependent enzymes and has been implicated in synaptic plasticity. ORL-1 is a Gi/o-coupled G protein-coupled receptor (GPCR) that is expressed in the peripheral and central nervous systems. Both Cav1.2 and ORL-1 are expressed in the hippocampus, where they have been implicated in learning and memory. It is well-documented that ORL-1 interacts with another VGCC, Cav2.2. However, less is known about potential interactions between Cav1.2 and ORL-1. Here, we examine the interplay between Cav1.2 (Cav1c, Cav2{delta}-1, Cav{beta}1) and ORL-1 co-expressed in tsA-201 cells by using biochemical, electrophysiological and confocal imaging analysis. Co-immunoprecipitations revealed that ORL-1 independently interacts with Cav1c and Cav2{delta}-1 subunits of the Cav1.2 channel complex. Electrophysiological recordings revealed that co-expression with ORL-1 reduced Cav1.2 peak current density without altering its biophysical properties. Acute perfusion with the ORL-1 receptor agonist nociceptin (1 M) did not alter Cav1.2 current density. Confocal imaging experiments revealed that ORL-1 significantly decreases Cav1.2 plasma membrane expression by disrupting forward trafficking. Interestingly, ORL-1 did not affect Cav1.2 endocytosis. Overall, our results demonstrate a previously unrecognized interaction between ORL-1 and Cav1.2 that alters Cav1.2 membrane expression without affecting biophysical properties.

Spectral bleed-through remains a persistent practical problem in multichannel fluorescence microscopy. Signal from one fluorophore can be recorded in the detection channel of another, thereby biasing intensity measurements, inflating apparent colocalization, and complicating the interpretation of dynamic microscopy data. Although many correction strategies exist, routine workflows often remain fragmented across ad hoc scripts, manually tuned graphical procedures, or method-specific blind-unmixing implementations with limited provenance. Here we present spectral-unmixing, an open-source Python package for reproducible linear spectral unmixing in multidimensional microscopy stacks. The package unifies directed two-channel correction with multiple alpha-estimation strategies, optional bidirectional two-channel correction through explicit inversion of a 2 x 2 mixing model, and PICASSO-family blind unmixing for multichannel data. Microscopy inputs are normalized at the API boundary to canonical TZCY X stacks, allowing the same unmixing code to be applied across file formats without manual axis handling. Machine-readable sidecar reports preserve the effective processing configuration and estimated coefficients for every output, so that workflows can be audited and reproduced. Synthetic and real-data-derived benchmarks show that the implemented workflows accurately estimate and correct bleed-through when their model assumptions are satisfied. In fixed-alpha two-channel simulations, the mean-ratio and linear-fit estimators recovered {approx} 0.283 for a ground-truth value of 0.28 and reduced target-channel normalized root mean squared error from approximately 0.029 to 0.003. In time-varying simulations, per-time-point estimation tracked coefficient drift substantially better than reference-time-point estimation. Bidirectional inversion recovered reciprocally mixed channels accurately when coefficients were known or well estimated. PICASSO-family benchmarks further showed a practical trade-off between reducing residual inter-channel dependence and preserving fluorophore identity, with MATLAB-style workflows behaving more conservatively and source-sink formulations providing stronger dependence suppression when meaningful directional priors are available. Together, these elements make spectral-unmixing a practical, transparent, and extensible platform for reproducible spectral unmixing of fluorescence microscopy data in neuroscience and other quantitative bioimage-analysis settings.

Background: Alzheimer's disease (AD) is clinicopathologically heterogeneous. A proportion of patients living with AD present clinically at a younger onset of cognitive symptoms before 65 years old and/or non-amnestic clinical syndromes. Neuropathologically, corticolimbic distribution of neurofibrillary tangle pathology occurs on a continuum with some cases having greater cortical tau pathology relative to limbic regions and others with relatively restricted accumulation in limbic structures. These patterns of corticolimbic tangle distribution are associated with clinical presentation and age at onset. This study sought to examine protein expression differences across the spectrum of clinicopathologic heterogeneity using the NULISA targeted proteomics platform. Methods: A series of thirteen neuropathologically diagnosed AD cases from Mayo Clinic prospectively followed research studies were selected to reflect heterogeneity of clinical syndromes and corticolimbic distribution of tangle pathology. Frozen postmortem brain tissue samples were isolated from inferior parietal cortex and homogenized in RIPA buffer for analysis using Alamar Biosciences NULISA CNS disease 120 panel. Applying a conservative detection threshold of 75% level of detection for the novel application of NULISA in human brain, we evaluated levels of 69 of 129 protein targets across samples. We examined associations between age at onset cognitive symptoms and corticolimbic distribution of tangles (CLix) separately with individual protein targets using linear regression analysis. Results: AD cases with a younger age at onset had higher measured levels of ubiquitin, while older age was associated with higher levels of total tau, CRH, and NPTX2. Investigations of corticolimbic heterogeneity revealed AD cases with lower CLix score (i.e., cortical predominant distribution of tau) had higher measured p-tau181, p-tau231, ubiquitin, and p62. AD cases with higher CLix (i.e., relative cortical sparing) had higher levels of total tau, CRH, NPTX2, MDH1, and HBA1. Brain-derived total tau consistently showed a stronger association in both models. Conclusion: This work demonstrates the utility of postmortem proteomics for investigating biomarkers associated with AD clinicopathologic heterogeneity. We observed proteomic differences in synapse integrity, tau post-translational modification, and ubiquitination associated with age at symptomatic onset and corticolimbic distribution of tangle pathology.

Digital technologies can support meaningful social interaction by providing personally relevant prompts for memory, communication, and shared reflection. In later life, mobile phone photography may offer an accessible medium through which older adults and caregivers construct stories, express meaning, and participate in relational engagement. However, limited psychophysiological evidence is available on how digital photo supported storytelling engages cognitive and social processes in older adult caregiver dyads. This study examined alpha band EEG dynamics during digital photo elicited storytelling in two museum settings. Thirty two older adult caregiver dyads completed cognitive and psychological screening and participated in a museum-based storytelling protocol. During the museum visit, participants used mobile-phone photography to capture personally meaningful objects, scenes, or exhibition spaces. Each participant then selected one photograph as a digital prompt for a structured but naturalistic storytelling interaction. EEG was recorded during eyes closed resting, eyes open resting, storytelling, and listening conditions. Relative alpha power was analyzed using a predefined 10 electrode sensor level set. Task related alpha modulation was examined relative to eyes open resting. Associations between Cz alpha power and MoCA scores were tested, and dyad level alpha band inter brain similarity was explored using spatial alpha power patterns with within site shuffled dyad surrogate comparisons. Alpha power was higher during eyes closed resting and lower during storytelling and listening relative to eyes-open resting, indicating task-related alpha modulation during digital photo supported narrative interaction. Associations between MoCA scores and Cz alpha power were weak, condition-specific, and did not survive false discovery rate correction. During storytelling, dyad level alpha-band inter brain similarity was modestly higher than within site shuffled dyad estimates, but this effect did not remain significant after correction across conditions. These findings suggest that digital photo elicited storytelling can provide a meaningful medium for studying cognitive and social engagement in older adult caregiver dyads. Alpha band EEG activity was sensitive to storytelling and listening, although cognition related and dyadic similarity effects were modest. The study contributes to research on technology supported human behavior by showing how digital image prompts can structure naturalistic social interaction while enabling psychophysiological measurement in real-world contexts.

Modern cochlear implants (CIs) use pulsatile stimulation to restore hearing for individuals with severe hearing loss. CIs provide robust speech recognition in quiet but poorly represent temporal fine structure (TFS), needed for challenging listening situations. Analog stimulation preserves the acoustic waveform and may better encode TFS, yet it has not been evaluated combined with modern current-focusing strategies. We compared neural responses in the inferior colliculus (IC) evoked by CI stimuli consisting of 100 pulses/s biphasic pulse trains and 100 cycles/s sinusoidal analog stimulation with monopolar, bipolar, and tripolar electrode configurations in urethane-anesthetized guinea pigs. Following cochlear implantation, multiunit activity was recorded from the tonotopic axis of the central nucleus of the IC using 16-channel silicon probes. Detection thresholds, spread of excitation, vector strength, sustained response percentage, and temporal response properties were quantified. Analog stimulation consistently evoked significantly lower activation thresholds than pulsatile stimulation while maintaining comparable or sometimes narrower spatial selectivity across stimulation modes. In contrast, analog stimulation generated lower vector strength, larger tonic response components, and a pronounced level-dependent polarity effect. At low stimulus levels, responses were dominated by the cathodic phase of the sinusoidal waveform, whereas increasing stimulus level responses were elicited by both phases, producing synchronization at twice the stimulus frequency. These findings demonstrate that stimulation waveform strongly influences temporal coding while having relatively little effect on the spatial distribution of neural activation. These results provide a physiological basis for reexamining analog stimulation as an alternative strategy for cochlear implant sound coding.

The hippocampus is characterized by a stereotypical macroscopic structure, where the nuclei are densely and heterogeneously packed among different subregions of the hippocampus. Despite the fact that tissue-specific cellular organization has been implicated in neural function, it has been technically challenging to quantitatively analyze mesoscopic cellular organization in the hippocampus due to its high cellular density. To overcome this technical hurdle, we developed Computational Biophysical Histomorphometry Software (CBHS), an automated image-analysis pipeline, aimed at quantifying nuclear shape and the order of the cellular ensemble in high-density areas. When applied to the subfields of hippocampus, we found that denser regions, most notably the dentate gyrus, were the most positionally, but least orientationally ordered. Nuclear shape exhibited a dependence on the local environment in a packing-dependent manner. This association was cell-type specific, with neurons, but not astrocytes displaying nuclear shape that varied with neighbour proximity, although astrocytes demonstrated greater intrinsic shape variance. The results reveal the presence of reproducible mesoscale cell packing order in hippocampal tissue, and are consistent with a nucleus-driven mechanical coupling between neighbouring cells. The present study provides a quantitative framework with which to understand mesoscopic tissue organization, thus enabling the formulation of testable hypotheses for future investigation.

Objective: Pediatric epilepsy patients undergoing stereo-electroencephalography (sEEG) for ictal onset evaluation provide a rare window to study the developing brain. While methodological frameworks for task-based sEEG research are well-established in adults, pediatric-specific guidance remains underdeveloped. Furthermore, many pediatric epilepsy patients have comorbidities that might typically exclude them from participating in research. We examine factors that influence research participation and discuss considerations for conducting sEEG research in children. Methods: Here, we present a retrospective analysis of task-based research participation patterns from an NIH-funded study of speech and language representations (1R01DC018579) in 66 patients (ages 4-24) undergoing sEEG monitoring at Texas Children's Hospital to determine whether specific comorbidities influenced research participation. Results: Eighty-nine percent (n=66) of patients approached for consent agreed to participate in the study. Despite high rates of comorbidities including neurocognitive disorder (66.67%), language delay (31.75%), global developmental delay (23.81%), mood disorders (33.33%), ADHD (46.03%), autism spectrum disorder (14.29%) or other cognitive/intellectual disabilities (36.51%), all participants engaged in at least one task. While the majority of these diagnoses did not appear to influence subject participation, global developmental delay was associated with a significant reduction in time spent on active tasks. Discussion: Despite high prevalence of neuropsychological comorbidities among participants, our evidence suggests that these participants contribute meaningfully to studies investigating important developmental questions. We suggest strategies for tailoring task-based research to accommodate the unique needs of individuals in this population. Such practices are important for ensuring that research studies reflect the true diversity of the population.

Background and objectives: In recent years, the need to develop analytical strategies for healthy aging has assumed great importance. In this study, we introduce DyViA, a generative artificial intelligence (genAI) platform that can construct personalized trajectories capable of predicting the plausible progression of selected phenotypes with advancing age. Research design and methods: DyViA presents a suite of deep learning models covering two major GenAI approaches: DyViA-Diff, a new diffusion model; and DyViA-mGAN, an improved version of a recent Generative Adversarial Network model. It demonstrated the dynamic progression of femoral neck bone mineral density (BMD) using data from a longitudinal cohort study of women in the U.S. of age 65 years or above. Results: Using very few initial measurements, DyViA generated individual-specific continuous trajectories of BMD, with a corresponding region of acceptable predictions, from 66 to 89 years. The results were subjected to rigorous quality-control and comparative analysis across multiple methods. While DyViA-Diff is the superior model with more coherent and accurate predictions, DyViA-mGAN allows for encoding population- and individual-level effects with a better control. Discussion and implications: Given the prevalence of osteoporosis in the aging population, the main impact of DyViAs genAI-driven contribution in the form of personalized, plausible models of BMD progression with age lies in the systematic yet rigorous transition from otherwise static models of inference about a clearly dynamic phenomenon to a continuous one. The foresight offered by DyViAs outputs empowers an individual by conferring a certain degree of strategic preparedness in the course of aging.

Automated platforms such as Chi.Bio enable simultaneous monitoring of optical density and fluorescent reporter expression in 20 ml reactor cultures with controllable pump systems. As such, they provide an appealing option for contemporary gene expression quantification, quantitative physiology, and laboratory evolution and ecology experiments. While optical density calibration for this device is well established, no equivalent calibration framework exists for fluorescence, making quantitative comparison with reference instruments unreliable. Here, we characterize Chi.Bio fluorescence capabilities using fluorescent calibration microspheres and fixed GFP-expressing S. cerevisiae and E. coli cells, compared with orthogonal plate-reader measurements. We show that microsphere fluorescence is detectable and scales linearly with concentration, whereas the GFP signal from both species falls below the device detection limit. Comparison of background-correction strategies indicates that direct subtraction of a non-fluorescent control measured within the same device yields more reliable fluorescence estimates than the commonly used on-line normalization method. Knowledge of these sensitivity boundaries of the device provides practical guidelines for experimental design of future studies.

Neurophysiology datasets are becoming increasingly complex, combining behavioral measurements with high-dimensional neuronal activity recordings coming from optical and/or electrophysiological measurements. The Neurodata Without Borders (NWB) standard has emerged in the community as the format of record. While standardized and widely used preprocessing tools generating NWB files have been developed, extensible frameworks for scientific analysis downstream of the NWB ecosystem are still under-represented. We present CICADA, a Python framework dedicated to analysis of neurophysiological data in the standardized NWB format. The toolbox is built as three hierarchically-organized packages: cicada-nwb (NWB access layer), cicada-analysis (plugin-based analysis engine and tool library), and cicada-gui (PyQt5 desktop application at the head of the pipeline). Beyond this architectural separation, CICADA is built around a central design principle: supporting a continuum from turnkey use to full modularity. Researchers can use the complete GUI-driven cicada-gui workflow without writing code, programmatically use existing analysis plugins from cicada-analysis, contribute to new analysis plugins, reuse utilities from cicada-tools, or build entirely custom pipelines on top of the cicada-nwb access layer alone. The same analysis plugin runs identically in interactive GUI and parameter-configured headless modes, enabling reproducible multi-session, multi-animal group analyses. We illustrate the versatility of CICADA with example analyses of behavioral, calcium imaging (two-photon and widefield) and extracellular electrophysiology datasets from rodent laboratories. CICADA is open source, actively maintained, and designed so that any laboratory can contribute at any level of the stack without modifying the core framework.

This study aimed to explore night-to-night variability of multiscale sleep patterns by analyzing subcutaneous electroencephalography (sqEEG) from 20 healthy participants over one year (205-388 nights per participant, 6,429 nights in total). We utilized the time series of aperiodic slopes, sigma and slow-wave power as a new whole-night unit of sleep macrostructure. Using dynamic time warping, we calculated the distances (differences) between those time series to assess night-to-night sleep macrostructure dissimilarity. We found that the overall sleep macrostructural patterns were relatively similar across nights (20% dissimilarity), while their temporal alignment was quite variable (time series warped by ~60% for the best alignment). Lower variation in macrostructure dissimilarity was associated with better subjective sleep quality (r=-0.25). Then, we qualitatively compared yearlong variation in macroscale, microscale (sleep stage proportions, mean spectral power) and mesoscale (sleep cycle duration) metrics. We found that intra-individual night-to-night variation was '"low (coefficients of variation < 20%) for spectral power, sleep duration, N2 and REM sleep; ''medium'' (20-40%) - for N3 and macrostructure dissimilarity; and "high" (>40%) - for sleep cycle duration, wake and N1. In summary, different sleep metrics showed differential night-to-night variability, which was more metric-specific than scale-dependent. This might reflect a distinction between more trait-like versus more dynamically varying features of sleep, although this assumption needs further clarification.

Neurodegenerative diseases are complex disorders characterised by progressive neuronal loss and widespread transcriptomic dysregulation; however, the coordinated interactions among coding and non-coding RNAs that contribute to disease progression remain incompletely understood. In this study, RNA-seq datasets from disease-relevant neuronal populations and brain regions representing Alzheimer's disease (AD), Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS) were analysed using an integrative network-based framework. Differential expression analysis coupled with weighted gene co-expression network analysis identified modules significantly correlated with disease and prioritised highly connected hub genes. Integration of these hub genes with curated RNA interaction database enabled the construction of candidate lncRNA-miRNA-mRNA regulatory networks. Functional enrichment analysis revealed Gene Ontology biological processes associated with synaptic signalling, mitochondrial function, RNA metabolism and neuroinflammatory responses across neurodegenerative conditions. The inferred regulatory networks suggested both disease-specific and shared post-transcriptional regulatory modules involving key hub genes and non-coding RNAs. Additionally, putative sequence variants were identified within untranslated regions of selected hub genes, suggesting potential alterations in miRNA-mediated regulations. Therefore, this study provides a systems-level view of transcriptomic dysregulation across major neurodegenerative diseases and identifies candidate regulatory interactions and molecular targets for future functional investigation