bioRxiv Subject Collection: Neuroscience's Journal

Transcriptomic Analysis Identifies Candidate Genes for Differential Expression during Xenopus laevis Inner Ear Development
BackgroundThe genes involved in inner ear development and maintenance of the adult organ have yet to be fully characterized. Previous genetic analysis has emphasized the early development that gives rise to the otic vesicle. This study aimed to bridge the knowledge gap and identify candidate genes that are expressed as the auditory and vestibular sensory organs continue to grow and develop until the systems reach postmetamorphic maturity.

MethodsAffymetrix microarrays were used to assess inner ear transcriptome profiles from three Xenopus laevis developmental ages where all eight endorgans comprise mechanosensory hair cells: larval stages 50 and 56, and the post-metamorphic juvenile. Pairwise comparisons were made between the three developmental stages and the resulting differentially expressed X. laevis Probe Set IDs (Xl-PSIDs) were assigned to four groups based on differential expression patterns. DAVID analysis was undertaken to impart functional annotation to the differentially regulated Xl-PSIDs.

ResultsAnalysis identified 1510 candidate genes for differential gene expression in one or more pairwise comparison. Annotated genes not previously associated with inner ear development emerged from this analysis, as well as annotated genes with established inner ear function, such as oncomodulin, neurod1, and sp7. Notably, 36% of differentially expressed Xl-PSIDs were unannotated.

ConclusionsResults draw attention to the complex gene regulatory patterns that characterize Xenopus inner ear development, and underscore the need for improved annotation of the X. laevis genome. Outcomes can be utilized to select candidate inner ear genes for functional analysis, and to promote Xenopus as a model organism for biomedical studies of hearing and balance.

Mechanisms of alcohol influence on fear conditioning: a computational model
A connection between stress-related illnesses and alcohol use disorders is extensively documented. Fear conditioning is a standard procedure used to study stress learning and links it to the activation of amygdala circuitry. However, the connection between the changes in amygdala circuit and function induced by alcohol and fear conditioning is not well established. We introduce a computational model to test the mechanistic relationship between amygdala functional and circuit adaptations during fear conditioning and the impact of acute vs. repeated alcohol exposure. In accordance with experiments, both acute and prior repeated alcohol decreases speed and robustness of fear extinction in our simulations. The model predicts that, first, the delay in fear extinction in alcohol is mostly induced by greater activation of the basolateral amygdala (BLA) after fear acquisition due to alcohol-induced modulation of synaptic weights. Second, both acute and prior repeated alcohol shifts the amygdala network away from the robust extinction regime by inhibiting the activity in the central amygdala (CeA). Third, our model predicts that fear memories formed in acute or after chronic alcohol are more connected to the context. Thus, the model suggests how circuit changes induced by alcohol may affect fear behaviors and provides a framework for investigating the involvement of multiple neuromodulators in this neuroadaptive process.

The brainstem's red nucleus was evolutionarily upgraded to support goal-directed action
The red nucleus is a large brainstem structure that coordinates limb movement for locomotion in quadrupedal animals (Basile et al., 2021). The humans red nucleus has a different pattern of anatomical connectivity compared to quadrupeds, suggesting a unique purpose (Hatschek, 1907). Previously the function of the human red nucleus remained unclear at least partly due to methodological limitations with brainstem functional neuroimaging (Sclocco et al., 2018). Here, we used our most advanced resting-state functional connectivity (RSFC) based precision functional mapping (PFM) in highly sampled individuals (n = 5) and large group-averaged datasets (combined N [~] 45,000), to precisely examine red nucleus functional connectivity.

Notably, red nucleus functional connectivity to motor-effector networks (somatomotor hand, foot, and mouth) was minimal. Instead, red nucleus functional connectivity along the central sulcus was specific to regions of the recently discovered somato-cognitive action network (SCAN; (Gordon et al., 2023)). Outside of primary motor cortex, red nucleus connectivity was strongest to the cingulo-opercular (CON) and salience networks, involved in action/cognitive control (Dosenbach et al., 2007; Newbold et al., 2021) and reward/motivated behavior (Seeley, 2019), respectively. Functional connectivity to these two networks was organized into discrete dorsal-medial and ventral-lateral zones. Red nucleus functional connectivity to the thalamus recapitulated known structural connectivity of the dento-rubral thalamic tract (DRTT) and could prove clinically useful in functionally targeting the ventral intermediate (VIM) nucleus. In total, our results indicate that far from being a motor structure, the red nucleus is better understood as a brainstem nucleus for implementing goal-directed behavior, integrating behavioral valence and action plans.

Pharmacological inhibition of mTORC1 reduces neural death and damage volume after MCAO by modulating microglial reactivity
Ischemic stroke is a sudden and acute disease characterized by neuronal death, glia activation, and a severe inflammatory process. Neuroinflammation is an early event after cerebral ischemia, with microglia playing a leading role. Microglial activation involves functional and morphological changes that drive a wide variety of phenotypes. In this context, deciphering the molecular mechanisms underlying such microglial activation is essential to devise strategies to protect neurons and maintain certain brain functions affected by early neuroinflammation after ischemia.

Here, we studied the role of mammalian target of rapamycin (mTOR) activity in the microglial response using a murine model of cerebral ischemia in the acute phase. We also determined the therapeutic relevance of the pharmacological administration of rapamycin, a mTOR inhibitor, before and after ischemic injury.

Our data show that rapamycin, administered before or after brain ischemia induction, reduced the volume of brain damage and neuronal loss by attenuating the microglial response. Therefore, our findings indicate that the pharmacological inhibition of mTORC1 in the acute phase of ischemia may provide an alternative strategy to reduce neuronal damage through attenuation of the associated neuroinflammation.

Transcranial direct current stimulation alters cerebrospinal fluid-interstitial fluid exchange in mouse brain
BackgroundTranscranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique that has gained prominence recently. Clinical studies have explored tDCS as an adjunct to neurologic disease rehabilitation, with evidence suggesting its potential in modulating brain clearance mechanisms. The glymphatic system, a proposed brain waste clearance system, posits that cerebrospinal fluid-interstitial fluid (CSF-ISF) exchange aids in efficient metabolic waste removal. While some studies have linked tDCS to astrocytes inositol trisphosphate (IP3)/Ca2+ signaling, the impact of tDCS on CSF-ISF exchange dynamics remains unclear.

HypothesistDCS influences the dynamics of CSF-ISF exchange through astrocytic IP3/Ca2+ signaling.

MethodsIn this study, we administered tDCS (0.1mA for 10 minutes) to C57BL/6 mice anesthetized with ketamine-xylazine (KX). The anode was positioned on the cranial bone above the cortex, and the cathode was inserted into the neck. Following tDCS, we directly assessed brain fluid dynamics by injecting biotinylated dextran amine (BDA) as a CSF tracer into the cisterna magna (CM). The brain was then extracted after either 30 or 60 minutes and fixed. After 24 hours, the sectioned brain slices were stained with Alexa 594-conjugated streptavidin (SA) to visualize BDA using immunohistochemistry. We conducted Electroencephalography (EEG) recordings and aquaporin 4 (AQP4)/CD31 immunostaining to investigate the underlying mechanisms of tDCS. Additionally, we monitored the efflux of Evans blue, injected into the cisterna magna, using cervical lymph node imaging. The experiments were subsequently repeated with inositol trisphosphate receptor type 2 (IP3R2)-knockout mice.

ResultsPost-tDCS, we observed an increased CSF tracer influx, indicating a modulation of CSF-ISF exchange by tDCS. Additionally, tDCS appeared to enhance the brains metabolic waste efflux. EEG recordings showed an increase in delta wave post-tDCS. But no significant change in AQP4 expression was detected 30 minutes post-tDCS.

ConclusionOur findings suggest that tDCS augments the glymphatic systems influx and efflux. Through astrocyte IP3/Ca2+ signaling, tDCS was found to modify the delta wave, which correlates positively with brain clearance. This study underscores the potential of tDCS in modulating brain metabolic waste clearance.

Extinction Training Suppresses Activity of Fear Memory Ensembles Across the Hippocampus and Alters Transcriptomes of Fear-Encoding Cells
Contextual fear conditioning has been shown to activate a set of "fear ensemble" cells in the hippocampal dentate gyrus (DG) whose reactivation is necessary and sufficient for expression of contextual fear. We previously demonstrated that extinction learning suppresses reactivation of these fear ensemble cells and activates a competing set of DG cells - the "extinction ensemble." Here, we tested whether extinction was sufficient to suppress reactivation in other regions and used single nucleus RNA sequencing (snRNA-seq) of cells in the dorsal dentate gyrus to examine how extinction affects the transcriptomic activity of fear ensemble and fear recall-activated cells. Our results confirm the suppressive effects of extinction in the dorsal and ventral dentate gyrus and demonstrate that this same effect extends to fear ensemble cells located in the dorsal CA1. Interestingly, the extinction-induced suppression of fear ensemble activity was not detected in ventral CA1. Our snRNA-seq analysis demonstrates that extinction training markedly changes transcription patterns in fear ensemble cells and that cells activated during recall of fear and recall of extinction have distinct transcriptomic profiles. Together, our results indicate that extinction training suppresses a broad portion of the fear ensemble in the hippocampus, and this suppression is accompanied by changes in the transcriptomes of fear ensemble cells and the emergence of a transcriptionally unique extinction ensemble.

Neurotransmitter Genes in the Nucleus Accumbens that Are Involved in the Development of Behavioral Pathology After Positive Fighting Experiences and Their Deprivation. A Conceptual Paradigm for Neurogenomic Data Analysis
It has been shown earlier that repeated positive fighting experience in daily agonistic interactions is accompanied by the development of psychosis-like behavior with signs of an addiction-like state associated with changes in the expression of genes encoding the proteins involved in the main neurotransmitter events in some brain regions of aggressive male mice. Fighting deprivation (a no-fight period of 2 weeks) causes a significant increase in their aggressiveness. This paper is aimed at studying--after a period of fighting deprivation--the involvement of genes (associated with neurotransmitter systems within the nucleus accumbens) in the above phenomena. The nucleus accumbens is known to participate in reward-related mechanisms of aggression. We found the following differentially expressed genes (DEGs), whose expression significantly differed from that in controls and/or mice with positive fighting experience in daily agonistic interactions followed by fighting deprivation: catecholaminergic genes Th, Drd1, Drd2, Adra2c, Ppp1r1b, and Maoa; serotonergic genes Maoa, Htr1a, Htr1f, and Htr3a; opioidergic genes Oprk1, Pdyn, and Penk; and glutamatergic genes Grid1, Grik4, Grik5, Grin3a, Grm2, Grm5, Grm7, and Gad1. The expression of DEGs encoding proteins of the GABAergic system in experienced aggressive male mice mostly returned to control levels after fighting deprivation except for Gabra5. In light of the conceptual paradigm for analyzing data that was chosen in our study, the aforementioned DEGs associated with the behavioral pathology can be considered responsible for consequences of aggression followed by fighting deprivation, including mechanisms of an aggression relapse.

Decoding of resting-state using task-based multivariate pattern analysis supports the Incentive-Sensitization Theory in nicotine use disorder
BackgroundThe Incentive-Sensitization Theory postulates that addiction is primarily driven by the sensitization of the brains reward system to addictive substances, such as nicotine. According to this theory, exposure to such substances leads to an increase in wanting, while liking the experience remains relatively unchanged. Although this candidate mechanism has been well substantiated through animal brain research, its translational validity for humans has only been partially demonstrated so far, with evidence from human neuroscience data being very limited.

MethodsFrom fMRI data of N=31 individuals with Nicotine Use Disorder, we created multivoxel patterns capable of capturing wanting and liking-related dimensions from a smoking cue-reactivity task. Using these patterns, we then designed a novel resting-state reading method to evaluate how much wanting or liking still persist as a neural trace after watching the cues.

ResultsWe found that the persistence of wanting-related brain patterns at rest increases with longer smoking history but this was not the case for liking-related patterns. Interestingly, such behavior has not been observed for non-temporal measures of smoking intensity.

ConclusionThis study provides basic human neuroscience evidence that the dissociation between liking and wanting escalates over time, further substantiating the Incentive-Sensitization Theory, at least for Nicotine Use Disorder. These results suggest that treatment approaches could be personalized to account for the variability in individuals neural adaptation to addiction by considering how individuals differ in the extent to which their incentive salience system is sensitized.

Spatially Resolved Transcriptomic Signatures of Hippocampal Subregions and Arc-Expressing Ensembles in Active Place Avoidance Memory
The rodent hippocampus is a spatially organized neuronal network that supports the formation of spatial and episodic memories. We conducted bulk RNA sequencing and spatial transcriptomics experiments to measure gene expression changes in the dorsal hippocampus following recall of active place avoidance memory. Our analysis focused on two specific levels of spatial resolution: hippocampal subregions and Immediate Early Gene (IEG) expressing cellular assemblies. Through bulk RNA sequencing, we examined the gene expression changes following memory recall across the functionally distinct subregions of the dorsal hippocampus. We found that training induced differentially expressed genes (DEGs) in the CA1 and CA3 hippocampal subregions were enriched with genes involved in synaptic transmission and synaptic plasticity, while DEGs in the dentate gyrus (DG) were enriched with genes involved in energy balance and ribosomal function. Through spatial transcriptomics, we examined gene expression changes following memory recall in putative memory-associated neuronal ensembles marked by the expression of the IEGs Arc, Egr1, and c-Jun. Within samples from both trained and untrained mice, the subpopulations of spatial transcriptomic spots marked by these IEGs were functionally and spatially distinct from one another. In only the hippocampus of trained mice, DEGs detected between Arc+ and Arc-spots were enriched in several memory-related gene ontology terms, including "regulation of synaptic plasticity" and "memory." Our results suggest that memory recall is supported by region-specific gene expression changes and transcriptionally distinct IEG expressing ensembles of neurons in the hippocampus.

Human DDIT4L intron retention contributes to cognitive impairment and amyloid plaque formation.
Cognitive impairment and amyloid plaques are the most important clinical and neuropathological feature for dementia, especially in Alzheimers disease (AD). However, the etiology of dementia is complicated. The present study reveals that an aberrant splicing of DDIT4L, the isoform DDIT4L intron retention (DIR), occurs in AD patients. Homozygous DIR-knock-in (KI) mice showed DIR expression in hippocampal neurons, marked cognitive impairment, augmented A{beta} deposition and enhanced Tau phosphorylation. The DIR colocalized with thioflavin S-positive plaques and gelsolin in AD patients. The DIR induced A{beta} deposition and cognitive impairment by interacting with gelsolin. Moreover, DIR interacted with GluA1, the subunit of the AMPA receptor, contributing to synaptic deficiency and cognitive impairment. Furthermore, an anti-DIR monoclonal antibody (mAb) alleviated cognitive impairment and reduced A{beta} deposition and Tau phosphorylation. Thus, DIR contributes to cognitive impairment and amyloid plaques, and could be a potential therapeutic target for dementia.

Basolateral amygdala population coding of a cued reward seeking state depends on orbitofrontal cortex
Basolateral amygdala (BLA) neuronal responses to conditioned stimuli are closely linked to the expression of conditioned behavior. An area of increasing interest is how the dynamics of BLA neurons relate to evolving behavior. Here, we recorded the activity of individual BLA neurons across the acquisition and extinction of conditioned reward seeking and employed population-level analyses to assess ongoing neural dynamics. We found that, with training, sustained cue-evoked activity emerged that discriminated between the CS+ and CS-and correlated with conditioned responding. This sustained population activity continued until reward receipt and rapidly extinguished along with conditioned behavior during extinction. To assess the contribution of orbitofrontal cortex (OFC), a major reciprocal partner to BLA, to this component of BLA neural activity, we inactivated OFC while recording in BLA and found blunted sustained cue-evoked activity in BLA that accompanied reduced reward seeking. Optogenetic disruption of BLA activity and OFC terminals in BLA also reduced reward seeking. Our data suggest that sustained cue-driven activity in BLA, which in part depends on OFC input, underlies conditioned reward-seek-ing states.

Single-Nuclei RNA Sequencing Identifies Type C Low-Threshold Mechanoreceptors as Key Players in Paclitaxel-Induced Peripheral Neuropathy
Neuropathic pain triggered by chemotherapy poses a significant clinical challenge. Investigating cell type-specific alterations through single-cell transcriptome analysis holds promise in understanding symptom development and pathogenesis. In this study, we performed single nuclei RNA (snRNA) sequencing of dorsal root ganglions (DRG) to explore the molecular mechanism underlying paclitaxel-induced neuropathic pain. Mouse exposed to repeated paclitaxel doses developed persistent pain hypersensitivity lasting at least 21 days. The snRNA sequencing unveiled seven major cell types within DRGs, with neurons further subdivided into 12 distinct subclusters using known markers. Notably, type C low-threshold mechanoreceptors (C_LTMR) exhibited the most pronounced transcriptomic changes post-paclitaxel administration. Differential gene expression and Gene Ontology (GO) analysis highlighted suppressed potassium-related currents, microtubule transport, and mitochondrial functions in C_LTMR following paclitaxel treatment. Meanwhile, Gene Set Enrichment Analysis (GSEA) suggested increased Interleukin 17 production in C_LTMR after paclitaxel exposure. Pseudo-time analysis uncovered nine distinct states (state 1 to 9) of C_LTMR. State 1 exhibits higher prevalence in paclitaxel-treated mice and altered neurotransmission properties, likely contributing to paclitaxel-induced pain hypersensitivity. This comprehensive exploration sheds light on the molecular mechanisms driving paclitaxel-induced neuropathic pain, offering potential avenues for therapeutic intervention.

Spindle Oscillation Emerges at the Critical State of the Electrically Coupled Network in Thalamic Reticular Nucleus
AO_SCPLOWBSTRACTC_SCPLOWSpindle oscillation is a waxing-and-waning neural oscillation observed in the brain, initiated at the thalamic reticular nucleus (TRN) and typically occurring at 7 - 15 Hz. Recent experiments revealed that in the adult brain, electrical synapses, rather than chemical synapses, are dominating between TRN neurons, indicating that the traditional view of spindle generation via chemical synapses in the TRN needs to be revised. Here, based on the known experimental data, we develop a computational model of the TRN network, in which heterogeneous neurons are connected by electrical synapses. The model consists of two driving forces competing to shape the network dynamics: electrical synapses tend to synchronize neurons, while heterogeneity tends to desynchronize neurons. We demonstrate that the interplay between two forces leads to a network state where multiple synchronized clusters with slightly different oscillation frequencies coexist. In this state, the superposition of neuronal activities gives rise to spindle oscillation, as observed in local field potentials in experiments. Notably, we discover that when TRN neurons generate spindle oscillation, the network operates at the critical state, known for facilitating efficient information processing in complex systems. Our study sheds light on the underlying mechanism of spindle oscillation and its functional significance in neural information processing.

Saturated fatty acid-Coenzyme A supplementation restores neuronal energy levels and protein homeostasis in hereditary spastic paraplegia
Hereditary Spastic Paraplegia (HSP) type 54 is a complex childhood autosomal recessive neurodegenerative disorder characterized by impairments in both neuromuscular and cognitive functions. This condition arises from mutations in the DDHD2 gene, which encodes for the phospholipase A1 enzyme DDHD2. Previous research has indicated that loss of DDHD2 results in lipid droplet accumulation in the brain, progressive apoptosis of motor neurons in the spinal cord, a reduction in cardiolipin content, and an increase in reactive oxygen species. However, the precise underlying mechanisms of HSP54 remains unclear. Our recent study demonstrated a robust increase in saturated free fatty acids (sFFAs), particularly myristic acid, during neuronal stimulation and memory acquisition in vivo in the brains of mice and in vitro in primary neurons. This activity- dependent increase of sFFAs was blocked in DDHD2 knockout mice (DDHD2-/-), suggesting that disturbed production of sFFAs underlies the neuronal pathology of HSP54. Here, using electron microscopy (EM) and live-cell confocal imaging, mass spectrometry and proteomics, electric field stimulation, as well as fluorometric and mitochondrial function assays in cultured primary neurons, we discovered that loss of DDHD2 leads to reduced levels of acetyl-coenzyme A (CoA) and ATP. Additionally, DDHD2 deficiency results in impaired respiratory function, altered mitochondrial morphology and distribution, a significant defect in synaptic vesicle recycling with an accumulation of large bulk endosomes in the presynapses, as well as an imbalance in global protein homeostasis. Our study further reveals that the combined administration of myristic acid and CoA (Myr-CoA) fully rescues mitochondrial function and ATP production within 48 hours. This intervention also leads to a marked restoration of neuronal protein homeostasis, providing the first demonstration of a potential combinatory therapeutic intervention for HSP54. Our findings demonstrate that the sFFAs released by the activity of DDHD2 play a central role in maintaining neuronal energy levels, synaptic function, and protein balance. The requirement for DDHD2 lipase activity in these processes can, therefore, be bypassed by supplementation of a preconjugated Myr-CoA.

Rab10 regulates neuropeptide release by maintaining Ca2+ homeostasis and protein synthesis
Dense core vesicles (DCVs) transport and release various neuropeptides and neurotrophins that control diverse brain functions, but the DCV secretory pathway remains poorly understood. Here, we tested a prediction emerging from invertebrate studies about the crucial role of the intracellular trafficking GTPase Rab10, by assessing DCV exocytosis at single- cell resolution upon acute Rab10 depletion in mature mouse hippocampal neurons, to circumvent potential confounding effects of Rab10s established role in neurite outgrowth.

We observed a significant inhibition of DCV exocytosis in Rab10-depleted neurons, whereas synaptic vesicle exocytosis was unaffected. However, rather than a direct involvement in DCV trafficking, this effect was attributed to two ER-dependent processes, ER-regulated intracellular Ca2+ dynamics and protein synthesis. Gene ontology analysis of differentially expressed proteins upon Rab10 depletion identified substantial alterations in synaptic and ER/ribosomal proteins, including the Ca2+-pump SERCA2. In addition, ER morphology and dynamics were altered, ER Ca2+ levels were depleted and Ca2+ homeostasis was impaired in Rab10-depleted neurons. However, Ca2+ entry using a Ca2+ ionophore still triggered less DCV exocytosis. Instead, leucine supplementation, which enhances protein synthesis, largely rescued DCV exocytosis deficiency. We conclude that Rab10 is required for neuropeptide release by maintaining Ca2+ dynamics and regulating protein synthesis. Furthermore, DCV exocytosis appeared more dependent on (acute) protein synthesis than synaptic vesicle exocytosis.

Predictive coding in the auditory brainstem
Predictive coding is an influential concept in sensory and cognitive neuroscience. It is often understood as involving top-down prediction of bottom-up sensory patterns, but the term also applies to feed-forward predictive mechanisms, for example in the retina. Here, I discuss a recent model of low-level predictive processing in the auditory brainstem that is of the feed-forward flavor. Past sensory input from the cochlea is delayed and compared with the current input, via a predictive model that is tuned with the objective of minimizing prediction error. This operation is performed independently within each peripheral channel, with parameters determined from information within that channel. The result is a sensory representation that is invariant to a certain class of interfering sounds (harmonic, quasi-harmonic, or spectrally sparse), thus contributing to Auditory Scene Analysis. The purpose of this paper is to discuss that model in the light of predictive coding, and examine how it might fit within a wider hierarchical model that supports the perceptual representation of objects and events in the world.

Translating phenotypic prediction models from big to small anatomical MRI data using meta-matching
Individualized phenotypic prediction based on structural MRI is an important goal in neuroscience. Prediction performance increases with larger samples, but small-scale datasets with fewer than 200 participants are often unavoidable. We have previously proposed a "meta-matching" framework to translate models trained from large datasets to improve the prediction of new unseen phenotypes in small collection efforts. Meta-matching exploits correlations between phenotypes, yielding large improvement over classical machine learning when applied to prediction models using resting-state functional connectivity as input features. Here, we adapt the two best performing meta-matching variants ("meta-matching finetune" and "meta-matching stacking") from our previous study to work with T1-weighted MRI data by changing the base neural network architecture to a 3D convolution neural network. We compare the two meta-matching variants with elastic net and classical transfer learning using the UK Biobank (N = 36,461), Human Connectome Project Young Adults (HCP-YA) dataset (N = 1,017) and HCP-Aging dataset (N = 656). We find that meta-matching outperforms elastic net and classical transfer learning by a large margin, both when translating models within the same dataset, as well as translating models across datasets with different MRI scanners, acquisition protocols and demographics. For example, when translating a UK Biobank model to 100 HCP-YA participants, meta-matching finetune yielded a 136% improvement in variance explained over transfer learning, with an average absolute gain of 2.6% (minimum = -0.9%, maximum = 17.6%) across 35 phenotypes. Overall, our results highlight the versatility of the meta-matching framework.

BCI Toolbox: An Open-Source Python Package for the Bayesian Causal Inference Model
Psychological and neuroscientific research over the past two decades has shown that the Bayesian causal inference (BCI) is a potential unifying theory that can account for a wide range of perceptual and sensorimotor processes in humans. Therefore, we introduce the BCI Toolbox, a statistical and analytical tool in Python, enabling researchers to conveniently perform quantitative modeling and analysis of behavioral data. Additionally, we describe the algorithm of the BCI model and test its stability and reliability via parameter recovery. The present BCI toolbox offers a robust platform for BCI model implementation as well as a hands-on tool for learning and understanding the model, facilitating its widespread use and enabling researchers to delve into the data to uncover underlying cognitive mechanisms.

ABCA7-dependent Neuropeptide-Y signalling is a resilience mechanism required for synaptic integrity in Alzheimer's disease
Alzheimers disease (AD) remains a complex challenge characterized by cognitive decline and memory loss. Genetic variations have emerged as crucial players in the etiology of AD, enabling hope for a better understanding of the disease mechanisms; yet the specific mechanism of action for those genetic variants remain uncertain. Animal models with reminiscent disease pathology could uncover previously uncharacterized roles of these genes. Using CRISPR/Cas9 gene editing, we generated a knockout model for abca7, orthologous to human ABCA7 - an established AD-risk gene. The abca7+/- zebrafish showed reduced astroglial proliferation, synaptic density, and microglial abundance in response to amyloid beta 42 (A{beta}42). Single-cell transcriptomics revealed abca7-dependent neuronal and glial cellular crosstalk through neuropeptide Y (NPY) signaling. The abca7 knockout reduced the expression of npy, bdnf and ngfra, which are required for synaptic integrity and astroglial proliferation. With clinical data in humans, we showed reduced NPY in AD correlates with elevated Braak stage, predicted regulatory interaction between NPY and BDNF, identified genetic variants in NPY associated with AD, found segregation of variants in ABCA7, BDNF and NGFR in AD families, and discovered epigenetic changes in the promoter regions of NPY, NGFR and BDNF in humans with specific single nucleotide polymorphisms in ABCA7. These results suggest that ABCA7-dependent NPY signaling is required for synaptic integrity, the impairment of which generates a risk factor for AD through compromised brain resilience.

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