bioRxiv Subject Collection: Neuroscience's Journal

Alterations and Imbalance of Dorsal and Ventral Mossy Cells in a Mouse Model of Epilepsy
Mossy cells (MCs) in the hilus of the dentate gyrus (DG) are important for regulating activity of dentate granule cells and are particularly vulnerable to excitotoxic damage in epilepsy. Recent studies have demonstrated that MCs in the dorsal and ventral DG differ in the patterns of their axonal projections and neurochemical identities. Such differences raised questions about the vulnerability and plasticity of dorsal and ventral MCs in epilepsy and led to this study using a mouse pilocarpine model of epilepsy. Dorsal MCs were labeled by transfection of Cre-dependent eYFP in the dorsal DG of Calcrl-Cre mice that express Cre selectively in MCs. Ventral MCs were labeled with calretinin (CR), which labels ventral but not dorsal MCs. At 6-8 weeks after pilocarpine treatment, MC loss and axonal projections of remaining MCs were studied in control and pilocarpine-treated mice with confocal microscopy. Dorsal MCs were severely depleted, but many ventral MCs remained, and quantitative analysis of GluA2-labeled hilar neurons demonstrated a proportionally greater loss of dorsal MCs (77.6% loss) than ventral MCs (21.5% loss). Loss of dorsal MCs led to a marked reduction in the dorsal commissural pathway, while the remaining ventral MCs maintained a prominent, though reduced, ventral to dorsal association pathway. In pilocarpine-treated animals, a plexus of CR-labeled fibers extended into the middle molecular layer, suggesting axonal sprouting of remaining ventral MCs, with some of these fibers in contact with parvalbumin-labeled dendrites. These findings suggest that dorsal and ventral MCs differ in their vulnerability to seizure-induced damage in this animal model, creating an imbalance between the dorsal and ventral MC pathways that could alter the excitatory/inhibitory balance within the dentate gyrus.

Autophagic stress activates distinct compensatory secretory pathways in neurons
Autophagic dysfunction is a hallmark of neurodegenerative disease, leaving neurons vulnerable to the accumulation of damaged organelles and proteins. However, the late onset of diseases suggests that compensatory quality control mechanisms may be engaged to delay the deleterious effects induced by compromised autophagy. Neurons expressing common familial Parkinson's disease (PD)-associated mutations in LRRK2 kinase exhibit defective autophagy. Here, we demonstrate that both primary murine neurons and human iPSC-derived neurons harboring pathogenic LRRK2 upregulate the secretion of extracellular vesicles. We used unbiased proteomics to characterize the secretome of LRRK2G2019S neurons and found that autophagic cargos including mitochondrial proteins were enriched. Based on these observations, we hypothesized that autophagosomes are rerouted toward secretion when cell-autonomous degradation is compromised, likely to mediate clearance of undegraded cellular waste. Immunoblotting confirmed the release of autophagic cargos and immunocytochemistry demonstrated that secretory autophagy was upregulated in LRRK2G2019S neurons. We also found that LRRK2G2019S neurons upregulate the release of exosomes containing miRNAs. Live-cell imaging confirmed that this upregulation of exosomal release was dependent on hyperactive LRRK2 activity, while pharmacological experiments indicate that this release staves off apoptosis. Finally, we show that markers of both vesicle populations are upregulated in plasma from mice expressing pathogenic LRRK2. In sum, we find that neurons expressing pathogenic LRRK2 upregulate the compensatory release of secreted autophagosomes and exosomes, to mediate waste disposal and transcellular communication, respectively. We propose that this increased secretion contributes to the maintenance of cellular homeostasis, delaying neurodegenerative disease progression over the short term while potentially contributing to increased neuroinflammation over the longer term.

Trial-by-trial learning of successor representations in human behavior
Decisions in humans and other organisms depend, in part, on learning and using models that capture the statistical structure of the world, including the long-run expected outcomes of our actions. One prominent approach to forecasting such long-run outcomes is the successor representation (SR), which predicts future states aggregated over multiple timesteps. Although much behavioral and neural evidence suggests that people and animals use such a representation, it remains unknown how they acquire it. It has frequently been assumed to be learned by temporal difference bootstrapping (SR-TD(0)), but this assumption has largely not been empirically tested or compared to alternatives including eligibility traces (SR-TD({lambda} > 0)). Here we address this gap by leveraging trial-by-trial reaction times in graph sequence learning tasks, which are favorable for studying learning dynamics because the long horizons in these studies differentiate the transient update dynamics of different learning rules. We examined the behavior of SR-TD({lambda}) on a probabilistic graph learning task alongside a number of alternatives, and found that behavior was best explained by a hybrid model which learned via SR-TD({lambda}) alongside an additional zeroth-order predictive model. The relatively large {lambda} we estimate indicates a predominant role of eligibility trace mechanisms over the bootstrap-based chaining typically assumed. Our results provide insight into how humans learn predictive representations, and demonstrate that people simultaneously learn the SR alongside lower-order predictions.

Development of the Left Arcuate Fasciculus is Linked to Learning Gains in Reading, but not Math
Past studies leveraging cross-sectional data have raised questions surrounding the relationship between diffusion properties of the white matter and academic skills. Some studies have suggested that white matter properties serve as static predictors of academic skills, whereas other studies have observed no such relationship. On the other hand, longitudinal studies have suggested that within-individual changes in the white matter are linked to learning gains over time. In the present study, we look to replicate and extend the previous longitudinal results linking longitudinal changes in the white matter properties of the left arcuate fasciculus to individual differences in reading development. To do so, we analyzed diffusion MRI data, along with reading and mathematics scores in a longitudinal sample of 340 students as they progressed from 1st grade into 4th grade. Longitudinal growth models revealed that year-to-year within-individual changes in reading scores, but not math, were related to the development of the left arcuate fasciculus. These findings provide further evidence linking the dynamics of white matter development and learning in a unique sample and highlight the importance of longitudinal designs.

Neural Representation of Time across Complementary Reference Frames
Humans conceptualize time in terms of space, allowing flexible time construals from various perspectives. We can travel internally through a timeline to remember the past and imagine the future (i.e., mental time travel) or watch from an external standpoint to have a panoramic view of history (i.e., mental time watching). However, the neural mechanisms that support these flexible temporal construals remain unclear. To investigate this, we asked participants to learn a fictional religious ritual of 15 events. During fMRI scanning, they were guided to consider the event series from either an internal or external perspective in different tasks. Behavioral results confirmed the success of our manipulation, showing the expected symbolic distance effect in the internal-perspective task and the reverse effect in the external-perspective task. We found that the activation level in the posterior partial cortex correlated positively with sequential distance in the external-perspective task but negatively in the internal-perspective task. In contrast, the activation level in the anterior hippocampus positively correlated with sequential distance regardless of the observer's perspectives. These results suggest that the hippocampus stores the memory of the event sequences allocentrically in a perspective-agnostic manner. Conversely, the posterior parietal cortex retrieves event sequences egocentrically from the optimal perspective for the current task context. Such complementary allocentric and egocentric representations support both the stability of memory storage and the flexibility of time construals.

Brain functional connectivity as a mediator between hematological metrics and cognitive decline in children with beta-thalassemia major
Children with beta-thalassemia major (beta-TM) are at risk of cognitive impairment, particularly in learning and memory. While cognitive deficits in the general population have been extensively studied, brain-based predictors for beta-TM children remain unexplored. This study used connectome-based predictive modeling (CPM) to examine whole-brain functional connectivity in 60 participants to predict cognitive performance. Beta-TM children showed impaired cognitive abilities, as evidenced by lower Wechsler Intelligence Scale scores compared to controls. The identified brain regions, though not typically linked to cognitive performances, exhibited functional connectivity patterns associated with {beta}-TM, as confirmed by network-based statistics. Correlations between task performance, functional connectivity identified by the CPM, and hematological metrics were also examined. Significant correlations were found between the strength of functional network identified by CPM and hematological metrics, particularly hemoglobin levels and red blood cell distribution width. The study demonstrates that hematological factors influence cognitive performance indirectly through specific functional connectivity, providing new insights into the neural underpinnings of cognitive deficits in children with beta-thalassemia major.

Altered basal forebrain regulation of intrinsic brain networks in depressive and anxiety disorders
Altered connectivity both within and between the default mode and salience networks have been observed across depressive and anxiety disorders. Recent work has highlighted the importance of subcortical regions, including subdivisions of the basal forebrain, in coordinating activity of these networking. However, the influence of specific basal forebrain subregions on intrinsic networks across these disorders remains unknown. Using ultra-high field (7-Tesla) functional magnetic resonance imaging, we examined the resting-state effective connectivity of three basal forebrain subregions in a transdiagnostic group of 70 individuals with depressive and anxiety disorders compared to 78 healthy controls. We explored connectivity between these subregions and regions of the salience network (anterior insula and dorsal anterior cingulate) and default mode network (ventromedial prefrontal cortex, posterior cingulate cortex, and inferior parietal lobule). Clinical participants showed increased inhibitory connectivity from the nucleus basalis of Meynert to regions of the default mode network and dorsal anterior cingulate. Increased inhibitory connectivity was also observed from the ventral pallidum to regions of the posterior default mode network. These changes in the basal forebrain's regulation of large-scale cortical networks across depressive and anxiety disorders may suggest novel mechanistic avenues for pharmacological treatments, including cholinergic system targeting.

A unified central thalamus mechanism underlying diverse recoveries in disorders of consciousness
Disorders of consciousness (DoC) encompass a range of states characterized by prolonged altered awareness due to heterogeneous brain damage and are associated with highly diverse prognoses. However, the neural mechanisms underlying such diverse recoveries in DoC remain unclear. To address this issue, we analysed neuronal spiking activities recorded from the central thalamus (CT), a key hub in arousal regulation, in a cohort of 23 DoC patients receiving deep brain stimulation treatment. Using machine learning techniques, we identified a core set of electrophysiological features of the CT, particularly the theta rhythm, that could account for individual recovery outcomes across highly varied etiologies (trauma, brainstem hemorrhage, and anoxia), clinical baselines and patient ages. These features also correctly identified one subgroup of patients who exhibited poor initial clinical manifestations but recovered unexpectedly. Simulating a conductance-based model further revealed the neurodynamics of the theta rhythm in the CT during different stages of consciousness recovery. Taken together, these findings uncover a previously unknown, unified CT mechanism that governs the recoveries in DoC.

Speech-in-noise perception across the lifespan: A comparative study in Mongolian gerbils and humans
Many elderly listeners have difficulties with speech-in-noise perception, even if auditory thresholds in quiet are normal. The mechanisms underlying this compromised speech perception with age are still not understood. For identifying the physiological causes of these age-related speech perception difficulties, an appropriate animal model is needed enabling the use of invasive methods. In a comparative behavioral study, we used young-adult and quiet-aged Mongolian gerbils as well as young and elderly human subjects to investigate the age-related changes in speech-in-noise perception evaluating whether gerbils are an appropriate animal model for the age-related decline in speech-in-noise processing of human listeners. Gerbils and human subjects had to report a deviant consonant-vowel-consonant combination (CVC) or vowel-consonant-vowel combination (VCV) in a sequence of CVC or VCV standards, respectively. The logatomes were spoken by different speakers and masked by a steady-state speech-shaped noise. Response latencies were measured to generate perceptual maps employing multidimensional scaling, visualizing the subjects' internal representation of the sounds. By analyzing response latencies for different types of vowels and consonants, we investigated whether aging had similar effects on speech-in-noise perception in gerbils compared to humans. For evaluating peripheral auditory function, auditory brainstem responses and audiograms were measured in gerbils and human subjects, respectively. We found that the overall phoneme discriminability in gerbils was independent of age, whereas consonant discriminability was declined in humans with age. Response latencies were generally longer in aged than in young gerbils and humans, respectively. Response latency patterns for the discrimination of different vowel or consonant types were different between species, but both gerbils and humans made use of the same articulatory features for phoneme discrimination. The species-specific response latency patterns were mostly unaffected by age across vowel types, while there were differential aging effects on the species-specific response latency patterns of different consonant types.

Field EPSPs of dentate gyrus granule cells studied by selective optogenetic activation of hilar mossy cells in hippocampal slices.
Glutamatergic dentate gyrus (DG) mossy cells (MCs) innervate the primary DG cell type, granule cells (GCs). Numerous MC synapses are on GC proximal dendrites in the inner molecular layer (IML). However, field recordings of the GC excitatory postsynaptic potential (fEPSPs) have not been used to study this pathway selectively. Here we describe methods to selectively activate MC axons in the IML using mice with Cre recombinase expressed in MCs. Slices were made after injecting adeno-associated virus (AAV) encoding channelrhodopsin (ChR2) in the DG. In these slices, we show that fEPSPs could be recorded reliably in the IML in response to optogenetic stimulation of MC axons. Furthermore, fEPSPs were widespread across the septotemporal axis. However, fEPSPs were relatively weak because they were small in amplitude and did not elicit a significant population spike in GCs. They also showed little paired pulse facilitation. We confirmed the extracellular findings with patch clamp recordings of GCs despite different recording chambers and other differences in methods. Together the results provide a simple method for studying MC activation of GCs and add to the evidence that this input is normally weak but widespread across the GC population.

Investigating the Impact of Habitual Sleep Quality on Episodic Memory Performance: An EEG-Based Representational Similarity Analysis
Sleep is crucial for episodic memory consolidation, yet the impact of habitual sleep quality on memory performance remains underexplored. This study investigates the relationship between sleep quality and episodic memory retrieval using EEG-based representational similarity analysis (RSA). Thirty-six participants wore wrist accelerometers for one week to capture habitual sleep patterns, including total sleep time and restlessness. Memory performance was assessed through a paired associate learning task, with EEG data recorded during encoding and retrieval phases. RSA was applied to EEG oscillatory power across time-frequency windows to examine the neural similarity between encoding and retrieval. The results showed both positive and negative correlations between sleep metric and memory performance, with sleep restlessness being linked to both increases and decreases in neural similarity across specific clusters. These findings emphasize the important role of sleep quality in shaping the neural processes underlying episodic memory retrieval, indicating a strong connection between sleep patterns and memory function.

Behavioral and neural evidence for perceptual predictions in social interactions
The ability to predict others' behavior is crucial for social interactions. The goal of the present study was to test whether predictions are derived during observation of social interactions and whether these predictions influence how the whole-body emotional expressions of the agents are perceived. Using a novel paradigm, we induced social predictions in participants by presenting them with a short video of a social interaction in which a person approached another person and greeted him by touching the shoulder in either a neutral or an aggressive fashion. The video was followed by a still image showing a later stage in the interaction and we measured participants' behavioral and neural responses to the still image, which was either congruent or incongruent with the emotional valence of the touching. We varied the strength of the induced predictions by parametrically reducing the saliency of emotional cues in the video. Behaviorally, we found that reducing the emotional cues in the video led to a significant decrease in participants' ability to correctly judge the appropriateness of the emotional reaction in the image. At the neural level, EEG recordings revealed that observing an angry reaction elicited significantly larger N170 amplitudes than observing a neutral reaction. This emotion effect was only found in the high prediction condition (where the context in the preceding video was intact and clear), not in the mid and low prediction conditions. We further found that incongruent conditions elicited larger N300 amplitudes than congruent conditions only for the neutral images. Our findings provide evidence that viewing the initial stages of social interactions triggers predictions about their outcome in early cortical processing stages.

Sex-specific attenuation of photoreceptor degeneration by reserpine in a rhodopsin P23H rat model of autosomal dominant retinitis pigmentosa
Inherited retinal degenerations (IRDs) constitute a group of clinically and genetically diverse vision-impairing disorders. Retinitis pigmentosa (RP), the most common form of IRD, is characterized by gradual dysfunction and degeneration of rod photoreceptors, followed by the loss of cone photoreceptors. Recently, we identified reserpine as a lead molecule for maintaining rod survival in mouse and human retinal organoids as well as in the rd16 mouse, which phenocopy Leber congenital amaurosis caused by mutations in the cilia-centrosomal gene CEP290 (Chen et al. eLife 2023;12:e83205. DOI: https://doi.org/10.7554/eLife.83205). Here, we show the therapeutic potential of reserpine in a rhodopsin P23H rat model of autosomal dominant RP. At postnatal day (P) 68, when males and females are analyzed together, the reserpine-treated rats exhibit higher rod-derived scotopic b-wave amplitudes compared to the controls with little or no change in scotopic a-wave or cone-derived photopic b-wave. Interestingly, the reserpine-treated female rats display enhanced scotopic a- and b-waves and photopic b-wave responses at P68, along with a better contrast threshold and increased outer nuclear layer thickness. The female rats demonstrate better preservation of both rod and cone photoreceptors following reserpine treatment. Retinal transcriptome analysis reveals sex-specific responses to reserpine, with significant upregulation of phototransduction genes and proteostasis-related pathways, and notably, genes associated with stress response. This study builds upon our previously reported results reaffirming the potential of reserpine for gene-agnostic treatment of IRDs and emphasizes the importance of biological sex in retinal disease research and therapy development.

Systematic review and meta-analysis of bulk RNAseq studies in human Alzheimer's disease brain tissue
Objective: To systematically review and meta-analyze bulk RNA sequencing studies comparing Alzheimer's disease (AD) patients with controls in human brain tissue, assessing study quality and identifying key genes and pathways. Methods: We searched PubMed, Web of Science, and Scopus on September 23, 2023, for studies using bulk RNAseq on primary human brain tissue from AD patients and controls. Excluded were non-primary tissue, re-analyses without new data, limited RNA types and gene panels. Quality was assessed with a 10-category tool. Meta-analysis used high-quality datasets. Results: From 3,266 records, 24 studies met criteria. Meta-analysis found 571 differentially expressed genes (DEGs) in temporal lobe and 189 in frontal lobe; overlapping pathways included "Tube morphogenesis" and "Neuroactive ligand-receptor interaction." Limitations: Study heterogeneity and limited data tables constrained the review. Conclusions: Rigorous methods are vital in AD transcriptomic studies. Findings enhance understanding of transcriptomic changes, aiding biomarker and therapeutic development.

Transcriptional Regulation of human NMNAT2: Insights from 3D Genome Sequencing and Bioinformatics
Nicotinamide mononucleotide adenylyl transferases 2 (NMNAT2) is a crucial nicotinamide adenine dinucleotide (NAD)-synthesizing enzyme essential for neuronal health. In the Religious Orders Study/Memory and Aging Project (ROSMAP), human brain levels of NMNAT2 mRNA positively correlated with cognitive capabilities in older adults. NMNAT2 mRNA abundance is significantly reduced following various insults or proteinopathies. To elucidate the transcriptional regulation of NMNAT2, we employed circular chromosome conformation capture followed by high-throughput sequencing (4C-seq) to identify potential NMNAT2 enhancer and silencer regions by determining genomic regions interacting with the NMNAT2 promoter in human SH-SY5Y cells. We discovered distinct NMNAT2 promoter interactomes in undifferentiated versus neuron-like SH-SY5Y cells. Utilizing bioinformatics analyses, we identified putative transcriptional factors and NMNAT2-associated genes. Notably, the mRNA levels of many of these genes showed a significant correlation with NMNAT2 mRNA levels in single-nuclei RNA-seq datasets from ~400 human subjects in ROSMAP. Additionally, using CRISPR-Cas9 strategies, we confirmed the requirement of two specific genomic regions within the interactomes and four transcription factors in regulating NMNAT2 transcription. In summary, our study identifies genomic loci containing NMNAT2 regulatory elements and predicts associated genes and transcription factors through computational analyses.

Deep Multimodal Representations and Classification of First-Episode Psychosis via Live Face Processing
Schizophrenia is a severe psychiatric disorder associated with a wide range of cognitive and neurophysiological dysfunctions and long-term social difficulties. In this paper, we test the hypothesis that integration of multiple simultaneous acquisitions of neuroimaging, behavioral, and clinical information will be better for prediction of early psychosis than unimodal recordings. We propose a novel framework to investigate the neural underpinnings of the early psychosis symptoms (that can develop into Schizophrenia with age) using multimodal acquisitions of neural and behavioral recordings including functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), and facial features. Our data acquisition paradigm is based on live face-to-face interaction in order to study the neural correlates of social cognition in first-episode psychosis (FEP). We propose a novel deep representation learning framework, Neural-PRISM, for learning joint multimodal compressed representations combining neural as well as behavioral recordings. These learned representations are subsequently used to describe, classify, and predict the severity of early psychosis in patients, as measured by the Positive and Negative Syndrome Scale (PANSS) and Global Assessment of Functioning (GAF) scores. We found that incorporating joint multimodal representations from fNIRS and EEG along with behavioral recordings enhances classification between typical controls and FEP individuals. Additionally, our results suggest that geometric and topological features such as curvatures and path signatures of the embedded trajectories of brain activity enable detection of discriminatory neural characteristics in early psychosis.

Decoding the Neural Dynamics of Headed Syntactic Structure Building
The brain builds hierarchical phrases during language comprehension; however, the representational details and dynamics of the phrase-building process remain underspecified. This study directly probes whether the neural code of a phrase involves reactivating the syntactic property of a key subcomponent (the phrasal head). To this end, we train a part-of-speech sliding-window neural decoder (verb vs. adverb) on EEG signals recorded while participants (N = 30) read sentences in a controlled experiment. The decoder reaches above-chance performance that is spatiotemporally consistent and generalizes to unseen data across sentence positions. Appling the decoder to held-out data yields predicted activation levels for the verbal head of a verb phrase at a distant non-head word (adverb); the critical adverb appeared either at the end of a verb phrase, or at a sequentially and lexically matched position with no verb phrase boundary. There is stronger verb activation beginning at ~600 milliseconds at the critical adverb when it appears at a verb phrase boundary; this effect is not modulated by the strength of conceptual association between the two subcomponents in the verb phrase nor does it reflect word predictability. Time-locked analyses additionally reveal a negativity waveform component and increased beta-delta inter-trial phase coherence, both previously linked to linguistic composition, in a similar time window. With a novel application of neural decoding, our findings delineate the temporal dynamics by which the brain encodes phrasal representations by, in part, reactivating the representation of key subcomponents. We thus establish a link between cognitive accounts of phrase structure representations and electrophysiological dynamics.

Multi-dimensional social relationships shape social attention in monkeys
Social relationships guide individual behavior and ultimately shape the fabric of society. Primates exhibit particularly complex, differentiated, and multidimensional social relationships, which form interwoven social networks, reflecting both individual social tendencies and specific dyadic interactions. How the patterns of behavior that underlie these social relationships emerge from moment-to-moment patterns of social information processing remains unclear. Here, we assess social relationships among a group of four monkeys, focusing on aggression, grooming, and proximity. We show that individual differences in social attention vary with individual differences in patterns of general social tendencies and patterns of individual engagement with specific partners. Oxytocin administration altered social attention and its relationship to both social tendencies and dyadic relationships, particularly grooming and aggression. Our findings link the dynamics of visual information sampling to the dynamics of primate social networks.