bioRxiv Subject Collection: Neuroscience's Journal

Open-source, high performance miniature multiphoton microscopy systems for freely behaving animals
Here we describe the development of the UCLA 2P Miniscope, an easily adopted, open-source miniature 2-photon microscope capable of recording calcium dynamics from neurons located in deep structures and in dendrites over a 445 {micro}m x 380 {micro}m field of view (FOV) during free behavior. The system weighs approximately 4g and utilizes two on-board silicon-based photon detectors for highly sensitive measurements. All hardware is designed for high performance and ease of assembly, while minimizing cost. To test the 2P miniature microscope, we recorded in three experimental conditions to highlight its capabilities during free behavior in mice. First, we recorded calcium dynamics from place cells in hippocampal area CA1. Next, we resolved calcium transients from dendrites in retrosplenial cortex during 30 minutes of free behavior. Last, we recorded dentate granule cell activity at a depth of over 620 {micro}m, through an intact hippocampal CA1 during an open field behavior. The dentate granule cell recordings, to our knowledge, are the first optical recordings from these neurons ever performed in the intact hippocampus during free behavior. The miniature microscope itself and all supporting equipment are open-source and all files needed for building the scope can be accessed through the UCLA Golshani Lab GitHub repository.

The subcommissural organ regulates brain development via secreted peptides
The subcommissural organ (SCO) is a gland located at the entrance of the aqueduct of Sylvius in the brain. It exists in species as distantly related as amphioxus and humans, but its function is largely unknown. To explore its function, we compared transcriptomes of SCO and non-SCO brain regions and found three genes, Sspo, Car3, and Spdef, that are highly expressed in the SCO. Mouse strains expressing Cre recombinase from endogenous promoter/enhancer elements of these genes were used to genetically ablate SCO cells during embryonic development, resulting in severe hydrocephalus and defects in neuronal migration and development of neuronal axons and dendrites. Unbiased peptidomic analysis revealed enrichment of three SCO-derived peptides, namely thymosin beta 4, thymosin beta 10, and NP24, and their reintroduction into SCO-ablated brain ventricles substantially rescued developmental defects. Together, these data identify a critical role for the SCO in brain development.

fMROI: a simple and adaptable toolbox for easy region-of-interest creation
This study introduces fMROI, an open-source software designed for creating regions-of-interest (ROIs) and visualizing magnetic resonance imaging data. fMROI offers a user-friendly graphical interface that simplifies the creation of complex ROIs. It is compatible with various operating systems and enables the integration of user-specified algorithms. Comparative analysis against popular neuroimaging software demonstrates the feasibility, applicability, and ease of use of fMROI. Notably, fMROI's interactive graphical interface with a real-time viewer allows users to identify inconsistencies and design more accurate ROIs, saving significant time by avoiding errors before storing ROIs as NIfTI files. Additionally, fMROI supports automation through command-line accessibility, making it ideal for large-scale analyses. As an open-source platform, fMROI provides a valuable resource for researchers in the neuroimaging community, facilitating efficient ROI creation and streamlining neuroimage analysis.

Synaptic-dependent developmental dysconnectivity in 22q11.2 deletion syndrome
Chromosome 22q11.2 deletion is among the strongest known genetic risk factors for neuropsychiatric disorders, including autism and schizophrenia. Brain imaging studies have reported disrupted large-scale functional connectivity in people with 22q11 deletion syndrome (22q11DS). However, the significance and biological determinants of these functional alterations remain unclear. Here, we use a cross-species design to investigate the developmental trajectory and neural underpinnings of brain dysconnectivity in 22q11DS. We find that LgDel mice, an established mouse model of 22q11DS, exhibit age-specific patterns of functional MRI (fMRI) dysconnectivity, with widespread fMRI hyper-connectivity in juvenile mice reverting to focal hippocampal hypoconnectivity over puberty. These fMRI connectivity alterations are mirrored by co-occurring developmental alterations in dendritic spine density, and are both transiently normalized by developmental GSK3{beta} inhibition, suggesting a synaptic origin for this phenomenon. Notably, analogous hyper- to hypoconnectivity reconfiguration occurs also in human 22q11DS, where it affects hippocampal and cortical regions spatially enriched for synaptic genes that interact with GSK3{beta}, and autism-relevant transcripts. Functional dysconnectivity in somatomotor components of this network is predictive of age-dependent social alterations in 22q11.2 deletion carriers. Taken together, these findings suggest that synaptic-related mechanisms underlie developmentally mediated functional dysconnectivity in 22q11DS.

TDP43 proteinopathy exhibits disease, tissue, and context-specific cryptic splicing signatures
Mislocalization of the nuclear protein TAR DNA-binding protein 43 (TDP43) is a hallmark of ALS and FTD which leads to de-repression and inclusion of cryptic exons. These cryptic exons represent promising biomarkers of TDP43 pathology in a spectrum of neurodegenerative diseases. However, most cryptic exons to date have been identified from in vitro models or a single cortical FTD dataset, limiting our understanding of tissue and cell-specific splices as well as differences between in vitro and in vivo processes. We meta-analyzed published bulk RNAseq datasets representing 1,778 RNAseq profiles of ALS and FTD post-mortem tissue, and in vitro models with experimentally depleted TDP43. We identified 142 cryptic splices, including 76 novel events, and identified cryptic splicing signatures with distinct cortical and spinal cord enrichment, among other context-specific profiles. Using RNAseq and RT-qPCR, we validated a subset of these splices in an independent spinal cord cohort, and demonstrated a correlation of TDP43 pathology severity with degree of cryptic splicing. Leveraging multiple public single-nucleus RNAseq datasets of ALS and FTD motor and frontal cortex, we confirmed the elevation of cortical-enriched splices in disease and localized them to layer-specific neuronal populations. This catalog of cryptic splices could inform efforts to develop biomarkers for tissue-specific and cell type-specific TDP43 pathology.

An Open Resource: MR and light sheet microscopy stereotaxic atlas of the mouse brain
We have combined MR histology and light sheet microscopy (LSM) of five postmortem C57BL/6J mouse brains in a stereotaxic space based on micro-CT yielding a multimodal 3D atlas with the highest spatial and contrast resolution yet reported. Brains were imaged in situ with multi gradient echo (mGRE) and diffusion tensor imaging (DTI) at 15 um resolution (~ 2.4 million times that of clinical MRI). Scalar images derived from the average DTI and mGRE provide unprecedented contrast in 14 complementary 3D volumes, each highlighting distinct histologic features. The same tissues scanned with LSM and registered into the stereotaxic space provide 17 different molecular cell type stains. The common coordinate framework labels (CCFv3) complete the multimodal atlas. The atlas has been used to correct distortions in the Allen Brain Atlas and harmonize it with Franklin Paxinos. It provides a unique resource for stereotaxic labeling of mouse brain images from many sources.

Mu Suppression During Action Observation Only in the Lower, not in the Higher, Frequency Subband
Mu suppression - desynchronization of neural oscillations in central EEG electrodes during action execution and observation - has been widely accepted as a marker for neural mirroring. It has been conventionally and predominantly quantified in the 8-13 Hz range, corresponding to the alpha frequency band, although few studies reported differences in lower and higher subbands that together constitute the mu frequency band. In the present study, we adopted a data-driven approach to examine the spectral and temporal dynamics of mu suppression when participants watched videos depicting hand and face actions and artificial pattern movements. Our analyses in central EEG electrodes revealed that neural oscillations were significantly suppressed during action observation only in the lower (8-10.5 Hz), not in the higher (10.5-13 Hz), subband. No such subband differentiation was observed for the alpha oscillations in the occipital electrodes. In addition, in the lower subband, significantly stronger suppressions were selective for hand actions in the central EEG electrodes placed over the hand region of the sensorimotor cortices and for facial actions in the frontotemporal electrodes placed over the face region of the sensorimotor cortices. In the higher subband, such stimulus selectivity was only observed for facial actions in the frontotemporal electrodes. Furthermore, the neural oscillations in the lower, but not the higher, subband followed the precise temporal patterning of biological motion in the videos. These results indicate that neural oscillations in the lower subband show the characteristics of neural mirroring processes, whereas those in the higher subband might reflect other mechanisms.

Carbon dioxide shapes parasite-host interactions in a human-infective nematode
Skin-penetrating nematodes infect nearly one billion people worldwide. The developmentally arrested infective larvae (iL3s) seek out hosts, invade hosts via skin penetration, and resume development inside the host in a process called activation. Activated infective larvae (iL3as) traverse the host body, ending up as parasitic adults in the small intestine. Skin-penetrating nematodes respond to many chemosensory cues, but how chemosensation contributes to host seeking, intra-host development, and intra-host navigation - three crucial steps of the parasite-host interaction - remains poorly understood. Here, we investigate the role of carbon dioxide (CO2) in promoting parasite-host interactions in the human-infective threadworm Strongyloides stercoralis. We show that S. stercoralis exhibits life-stage-specific preferences for CO2: iL3s are repelled, non-infective larvae and adults are neutral, and iL3as are attracted. CO2 repulsion in iL3s may prime them for host seeking by stimulating dispersal from host feces, while CO2 attraction in iL3as may direct worms toward high-CO2 areas of the body such as the lungs and intestine. We also identify sensory neurons that detect CO2; these neurons are depolarized by CO2 in iL3s and iL3as. In addition, we demonstrate that the receptor guanylate cyclase Ss-GCY-9 is expressed specifically in CO2-sensing neurons and is required for CO2-evoked behavior. Ss-GCY-9 also promotes activation, indicating that a single receptor can mediate both behavioral and physiological responses to CO2. Our results illuminate chemosensory mechanisms that shape the interaction between parasitic nematodes and their human hosts and may aid in the design of novel anthelmintics that target the CO2-sensing pathway.

Target location and age-related dynamics affect conjunction visual search dynamics
Recent findings suggest that conjunction visual search can be explained through the serial processing of features. However, the roles of several critical factors, including target location in the visual field and age, have yet to be explored. Given their significance in visual search, we aim to investigate their impact on search time and accuracy in a conjunction visual search task. Participants engaged in target-present and target-absent trials, revealing distinct patterns in search times. In target-present trials, efficient processing was evident with faster search times, while target-absent trials demonstrated longer search times, indicating heightened cognitive load. Participants exhibited prolonged search times in target-absent trials, correlating with set size, while accuracy remained consistent. Conversely, target-present trials showed decreasing accuracy with larger set sizes, indicating increased cognitive load. The study further explores the impact of target distance from the central visual field on conjunction visual processing, revealing increased search times with greater distances and set sizes, emphasizing the intricate interplay between spatial factors and set size in target localization. Age-related dynamics were observed, with increasing age correlating with elevated search times in target-absent trials, suggesting challenges in declaring non-existence. However, accuracy in declaring absence improved with age, demonstrating nuanced interactions with set size. This comprehensive examination contributes to understanding cognitive mechanisms in visual processing.

Relationships between balance performance and connectivity of motor cortex with primary somatosensory cortex and cerebellum in middle aged and older adults
Connectivity of somatosensory cortex (S1) and cerebellum with the motor cortex (M1) is critical for balance control. While both S1-M1 and cerebellar-M1 connections are affected with aging, the implications of altered connectivity for balance control are not known. We investigated the relationship between S1-M1 and cerebellar-M1 connectivity and standing balance in middle-aged and older adults. Our secondary objective was to investigate how cognition affected the relationship between connectivity and balance. Our results show that greater S1-M1 and cerebellar-M1 connectivity was related to greater postural sway during standing. This may be indicative of an increase in functional recruitment of additional brain networks to maintain upright balance despite differences in network connectivity. Also, cognition moderated the relationship between S1-M1 connectivity and balance, such that those with lower cognition had a stronger relationship between connectivity and balance performance. It may be that individuals with poor cognition need increased recruitment of brain regions (compensation for cognitive declines) and in turn, higher wiring costs, which would be associated with increased functional connectivity.

Trauma Under Psychedelics: MDMA Shows Protective Effects During the Peritraumatic Period
Traumatic events (TEs) play a causal role in the etiology of psychopathologies such as depression and posttraumatic stress disorder (PTSD). Recent research has highlighted the therapeutic potential of psychoactive substances and especially 3,4-methylenedioxymethamphetamine (MDMA), in alleviating trauma symptoms in chronic patients. However, little is known regarding the consequences of trauma that is acutely experienced under the influence of psychoactive substances. Here we investigated the acute experiences and peritraumatic processing of 657 survivors from the high-casualty terror attack at the Supernova music festival in Israel on October 7th, 2023. Data were collected four to twelve weeks following the TE. Approximately two-thirds of survivors were under the influence of psychoactive substances at the time of the TE, offering a tragic and unique natural experiment on the impact of psychoactive compounds on TE processing. Our findings reveal that individuals who experienced the trauma while under the influence of MDMA demonstrated significantly improved intermediate outcomes compared to those who were under the influence of other substances or no substances at all. Specifically, the MDMA group reported increased feelings of social support, more social interactions and enhanced quality of sleep during the peritraumatic period, yielding reduced levels of mental distress and reduced PTSD symptom severity. These novel findings suggest that the influence of MDMA during the TE may carry protective effects into the peritraumatic period, possibly mediated through the known effects of MDMA in reducing negative emotions and elevating prosociality. These protective effects in turn may mitigate the development of early psychopathology-related symptoms. Current preliminary results underscore the need for further understanding of the cognitive and physiological processes by which psychedelic substances intersect with trauma recovery processes.

Enhancing Prediction of Human Traits and Behaviors through Ensemble Learning of Traditional and Novel Resting-State fMRI Connectivity Analyses
Recent efforts in cognitive neuroscience have focused on leveraging resting-state functional connectivity (RSFC) data from fMRI to predict human traits and behaviors more accurately. Traditional methods typically analyze RSFC by correlating averaged time-series data between regions of interest (ROIs) or networks, a process that may overlook critical spatial signal patterns. To address this limitation, we introduced a novel linear regression technique that estimates RSFC by predicting spatial brain activity patterns in a target ROI from those in a seed ROI. We applied both traditional and our novel RSFC estimation methods to a large-scale dataset from the Human Connectome Project, analyzing resting-state fMRI data to predict sex, age, personality traits, and psychological task performance. Additionally, we developed an ensemble learner that integrates these methods using a weighted average approach to enhance prediction accuracy. Our findings revealed that hierarchical clustering of RSFC patterns using our novel method displays distinct whole-brain grouping patterns compared to the traditional approach. Importantly, the ensemble model outperformed the traditional RSFC method in predicting human traits and behaviors. Notably, the predictions from the traditional and novel methods showed relatively low similarity, indicating that our novel approach captures unique and previously undetected information about human traits and behaviors through fine-grained local spatial patterns of neural activation. These results highlight the potential of combining traditional and innovative RSFC analysis techniques to enrich our understanding of the neural basis of human traits and behaviors.

Motion vision is tuned to maximize sensorimotor energy transfer in blowfly flight
Biological sensors have evolved to act as matched filters that respond preferentially to the stimuli they expect to receive during ecologically relevant tasks. For instance, insect visual systems are tuned to detect stimuli ranging from the small-target motion of mates or prey to the polarization pattern of the sky. In flies, individually identified neurons called lobula plate tangential cells respond to optic flow fields matched to specific self-motions, forming the output layer of what is presently nature's best-understood deep convolutional neural network. But what functional principle does their tuning embed, and how does this aid motor control? Here we test the hypothesis that evolution co-tunes physics and physiology by aligning the preferred directions of an animal's sensors to the most dynamically-significant directions of its motor system. We build a state-space model of blowfly flight by combining visual electrophysiology, synchrotron-based X-ray microtomography, high-speed videogrammetry, and computational fluid dynamics. We then apply control-theoretic tools to show that the tuning of the fly's widefield motion vision system maximizes the flow of energy from control inputs and disturbances to sensor outputs, rather than optimizing state estimation as is the conventional approach to sensor placement in engineering. We expect the same functional principle to apply across sensorimotor systems in other organisms, with implications for the design of novel control architectures for robotic systems combining high performance with low computational load and low power consumption.

LRRK2 kinase inhibition protects against Parkinson's disease-associated environmental toxicants
Idiopathic Parkinson's disease (PD) is epidemiologically linked with exposure to toxicants such as pesticides and solvents, which comprise a wide array of chemicals that pollute our environment. While most are structurally distinct, a common cellular target for their toxicity is mitochondrial dysfunction, a key pathological trigger involved in the selective vulnerability of dopaminergic neurons. We and others have shown that environmental mitochondrial toxicants such as the pesticides rotenone and paraquat, and the organic solvent trichloroethylene (TCE) appear to be influenced by the protein LRRK2, a genetic risk factor for PD. As LRRK2 mediates vesicular trafficking and influences endolysosomal function, we postulated that LRRK2 kinase activity may inhibit the autophagic removal of toxicant damaged mitochondria, resulting in elevated oxidative stress. Conversely, we suspected that inhibition of LRRK2, which has been shown to be protective against dopaminergic neurodegeneration caused by mitochondrial toxicants, would reduce the intracellular production of reactive oxygen species (ROS) and prevent mitochondrial toxicity from inducing cell death. To do this, we tested in vitro if genetic or pharmacologic inhibition of LRRK2 (MLi2) protected against ROS caused by four toxicants associated with PD risk -- rotenone, paraquat, TCE, and tetrachloroethylene (PERC). In parallel, we assessed if LRRK2 inhibition with MLi2 could protect against TCE-induced toxicity in vivo, in a follow up study from our observation that TCE elevated LRRK2 kinase activity in the nigrostriatal tract of rats prior to dopaminergic neurodegeneration. We found that LRRK2 inhibition blocked toxicant-induced ROS and promoted mitophagy in vitro, and protected against dopaminergic neurodegeneration, neuroinflammation, and mitochondrial damage caused by TCE in vivo. We also found that cells with the LRRK2 G2019S mutation displayed exacerbated levels of toxicant induced ROS, but this was ameliorated by LRRK2 inhibition with MLi2. Collectively, these data support a role for LRRK2 in toxicant-induced mitochondrial dysfunction linked to PD risk through oxidative stress and the autophagic removal of damaged mitochondria.

Foraging Under Uncertainty Follows the Marginal Value Theorem with Bayesian Updating of Environment Representations
Foraging theory has been a remarkably successful approach to understanding the behavior of animals in many contexts. In patch-based foraging contexts, the marginal value theorem (MVT) shows that the optimal strategy is to leave a patch when the marginal rate of return declines to the average for the environment. However, the MVT is only valid in deterministic environments whose statistics are known to the forager; naturalistic environments seldom meet these strict requirements. As a result, the strategies used by foragers in naturalistic environments must be empirically investigated. We developed a novel behavioral task and a corresponding computational framework for studying patch-leaving decisions in head-fixed and freely moving mice. We varied between-patch travel time, as well as within-patch reward depletion rate, both deterministically and stochastically. We found that mice adopt patch residence times in a manner consistent with the MVT and not explainable by simple ethologically motivated heuristic strategies. Critically, behavior was best accounted for by a modified form of the MVT wherein environment representations were updated based on local variations in reward timing, captured by a Bayesian estimator and dynamic prior. Thus, we show that mice can strategically attend to, learn from, and exploit task structure on multiple timescales simultaneously, thereby efficiently foraging in volatile environments. The results provide a foundation for applying the systems neuroscience toolkit in freely moving and head-fixed mice to understand the neural basis of foraging under uncertainty.

Multiple molecular links between the circadian clock and memory centers in honey bees
Time and memory are intimately linked: the capability to learn and recall varies over the day and humans and many animals can associate important events with the time of day. However, how the circadian clock and memory centers are connected is not well understood. We time-trained honey bee foragers and used RNA-sequencing and RNAscope imaging to analyze gene expression changes in focal populations of mushroom body neurons. Thus, we identified three candidate functional modules of time-memory: synchronized peak-level expression of memory-related genes during training time, anticipatory activation of transcription in pdfr-expressing neurons, and cry2 and per co-expressing neurons that might represent local clocks. The complex interactions between the clock and memory centers, which appear to be more similar to mammals than other insects, might have been facilitated to optimize social foraging in honey bees.

Decoding Arc Transcription: A Live-Cell Study of Stimulation Patterns and Transcriptional Output
Activity-regulated cytoskeleton-associated protein (Arc) plays a crucial role in synaptic plasticity, a process integral to learning and memory. Arc transcription is induced within a few minutes of stimulation, making it a useful marker for neuronal activity. However, the specifics of the neuronal activity that triggers Arc transcription remain unknown because it has not been possible to observe mRNA transcription in live cells in real time. Using a genetically encoded RNA indicator (GERI) mouse model that expresses endogenous Arc mRNA tagged with multiple GFPs, we investigated Arc transcriptional activity in response to various electrical stimulation patterns. In dissociated hippocampal neurons, we found that the pattern of stimulation significantly affects Arc transcription. Specifically, a 10 Hz burst stimulation induced the highest rate of Arc transcription. Concurrently, the amplitudes of nuclear calcium transients also reached their peak with 10 Hz stimulation, indicating a correlation between calcium concentration and transcription. However, our dual-color single-cell imaging revealed that there were no significant differences in calcium amplitudes between Arc-positive and Arc-negative neurons upon 10 Hz burst stimulation, suggesting the involvement of other factors in the induction of Arc transcription. Our live-cell RNA imaging provides a deeper insight into the complex regulation of transcription by activity patterns and calcium signaling pathways.

Neurofilament accumulation disrupts autophagy in giant axonal neuropathy
Neurofilament accumulation is a marker of several neurodegenerative diseases, but it is the primary pathology in Giant Axonal Neuropathy (GAN). This childhood onset autosomal recessive disease is caused by loss-of-function mutations in gigaxonin, the E3 adaptor protein that is essential for neurofilament degradation. Using a combination of genetic and RNA interference (RNAi) approaches, we found that dorsal root ganglia from mice lacking gigaxonin have impaired autophagy and lysosomal degradation through two mechanisms. First, neurofilament accumulations interfere with the distribution of autophagic organelles, impairing their maturation and fusion with lysosomes. Second, the accumulations sequester the chaperone 14-3-3, a protein responsible for the localization of the transcription factor EB (TFEB), a key regulator of autophagy. This dual disruption of autophagy likely contributes to the pathogenesis of other neurodegenerative diseases with neurofilament accumulations.

The psychedelic, DOI, increases dopamine release in nucleus accumbens to predictable rewards and reward cues
Psychedelics produce lasting therapeutic responses in neuropsychiatric diseases suggesting they may disrupt entrenched associations and catalyze learning. Here, we examine psychedelic effects on dopamine signaling in the nucleus accumbens (NAc) core, a region extensively linked to reward learning, motivation, and drug-seeking. We measure phasic dopamine transients following acute psychedelic administration during well learned Pavlovian tasks in which sequential cues predict rewards. We find that the psychedelic 5-HT2A/2C agonist, DOI, increases dopamine signaling to rewards and proximal reward cues but not to the distal cues that predict these events. We determine that the elevated dopamine produced by psychedelics to reward cues occurs independently of psychedelic-induced changes in reward value. The increased dopamine associated with predictable reward cues supports psychedelic-induced increases in prediction error signaling. These findings lay a foundation for developing psychedelic strategies aimed at engaging error-driven learning mechanisms to disrupt entrenched associations or produce new associations.

Deep convolutional neural network with face identity recognition experience exhibits brain-like neural representations of personality traits
Faces contain both identity and personality trait information. Previous studies have found that convolutional neural networks trained for face identity recognition spontaneously generate personality trait information. However, the successful classification of different personality traits does not necessarily mean that convolutional neural networks adopt brain-like representation mechanisms to achieve the same computational goals. Our study found that convolutional neural network with visual experience in face identity recognition (VGG-face) exhibited brain-like neural representations of personality traits, including coupling effects and confusion effects, while convolutional neural networks with the same network architecture but lacked visual experience for face identity recognition (VGG-16 and VGG-untrained) did not exhibit brain-like effects. In addition, compared to the VGG-16 and the VGG-untrained, the VGG-face exhibited higher similarity in neural representations with the human brain across all individual personality traits. In summary, these findings revealed the necessity of visual experience in face identity recognition for developing face personality traits judgment.

Dendrite injury, but not axon injury, triggers neuroprotection in Drosophila models of neurodegenerative disease.
Dendrite defects and loss are early cellular alterations observed across neurodegenerative diseases that play a role in early disease pathogenesis. Dendrite degeneration can be modeled by expressing pathogenic polyglutamine disease transgenes in Drosophila neurons in vivo. Here, we show that we can protect against dendrite loss in neurons modeling neurodegenerative polyglutamine diseases through injury to a single primary dendrite branch. We find that this neuroprotection is specific to injury-induced activation of dendrite regeneration: neither injury to the axon nor injury just to surrounding tissues induces this response. We show that the mechanism of this regenerative response is stabilization of the actin (but not microtubule) cytoskeleton. We also demonstrate that this regenerative response may extend to other neurodegenerative diseases. Together, we provide evidence that activating dendrite regeneration pathways has the potential to slow or even reverse dendrite loss in neurodegenerative disease.

Whole-Brain Dynamics Disruptions in the Progression of Alzheimer's Disease: Understanding the Influence of Amyloid-Beta and Tau
INTRODUCTION: Alzheimer's disease (AD) affects brain structure and function along its evolution, but brain network dynamic changes remain largely unknown. METHODS: To understand how AD shapes brain activity, we investigated the spatiotemporal dynamics and resting state functional networks using the intrinsic ignition framework, which characterizes how an area transmits neuronal activity to others, resulting in different degrees of integration. Healthy participants, MCI, and AD patients were scanned using resting state fMRI. Mixed effects models were used to assess the impact of ABeta and tau, at the regional and whole-brain levels. RESULTS: Dynamic complexity is progressively reduced, with Healthy participants showing higher metastability (i.e., a more complex dynamical regime over time) than observed in the other stages, while AD subjects showed the lowest. DISCUSSION: Our study provides further insight into how AD modulates brain network dynamics along its evolution, progressively disrupting the whole-brain and resting state network dynamics.

Control of behavioral uncertainty by divergent frontal circuits
Both ambiguous inference from current input and internal belief from prior input causes uncertainty. The uncertainty is typically manifested as a normal distribution at behavioral level when only current inference is manipulated as variable. When prior belief is varying, some decision relevant neural representations are dissociated. Under this circumstance, it is unclear how to describe the uncertainty and how dissociated neural representations cooperate to control the uncertainty. By simulating an unpredictable environment, which incurs conflicting valence-dependent prior beliefs, we found that a behavioral outcome, waiting time, does not follow a normal, but a log-normal distribution. By combining electrophysiological recordings, computational modeling, optogenetic manipulation, scRNA-seq and MERFISH, we showed that the formation of this behavioral outcome requires the temporally hierarchical cooperation of the neural representation of decision confidence and B230216N24Rik marked neural representation of positive and negative belief in the medial prefrontal cortex (mPFC). In summary, our results provide a mechanistic link between the dynamics of valence-dependent prior beliefs and behavioral uncertainty.

Protective role of Pten downregulation in Huntington's Disease models
Huntington's disease (HD) is a dominantly inherited neurodegenerative disorder that stems from the expansion of CAG repeats within the coding region of the Huntingtin gene. Currently, there exists no effective therapeutic intervention that can prevent the progression of the disease. Our investigation aims to identify a novel genetic modifier with therapeutic potential. We employ transgenic flies containing Htt93Q and Htt138Q.mRFP constructs, which encode mutant pathogenic Huntingtin proteins featuring 93 and 138 polyglutamine (Q) repeats, respectively. The resultant mutant protein causes the loss of photoreceptor neurons in the eye and a progressive loss of neuronal tissues in the brain and motor neurons in Drosophila. Several findings have demonstrated the association of HD with growth factor signaling defects. Phosphatase and tensin homolog (Pten) have been implicated in the negative regulation of insulin signaling/receptor tyrosine signaling pathway which regulates the growth and survival of cells. In the present study, we downregulated Pten and found a significant improvement in morphological phenotypes in the eye, brain, and motor neurons. These findings were further correlated with the enhancement of the functional vision and climbing ability of the flies. We also noted the reduction in both poly(Q) aggregate levels and caspase activity which are involved in the apoptotic pathway. Moreover, we elucidated the protective role of Pten inhibition through the utilization of VO-OHpic (referred to as PTENi). In alignment with the genetic modulation of Pten, pharmaceutical inhibition of Pten improved the climbing ability of flies and reduced the poly(Q) aggregates and apoptosis levels. A similar reduction in poly(Q) aggregates was observed in the mouse neuronal inducible HD cell line model. Our study illustrates that Pten inhibition is a potential therapeutic approach for HD.