bioRxiv Subject Collection: Neuroscience's Journal

Discovery of a pyrazolopyridine alkaloid inhibitor of ERO1A that mitigates neuronal ER stress and age-related decline
Targeting Endoplasmic Reticulum Oxidoreductase 1 Alpha (ERO1A) offers therapeutic potential for ER stress-related conditions, including motor neurone diseases and congenital muscle disorders. However, selective ERO1A inhibitors remain unavailable. Here, we developed a multi-modal discovery pipeline combining molecular docking with in vitro and in vivo assays, screening 401,824 natural products from the COCONUT database. We identified two compounds, S88 and geniposide, that inhibited ERO1A in vitro, reduced tunicamycin-induced ER stress markers in human neurons, and improved locomotion and neuromuscular junctions in UBQLN2ALS Drosophila. S88 maintained efficacy in late-stage disease and extended lifespan in a D-galactose aging model. In fly brains, S88 selectively reduced phosphorylated eIF2a; without lowering its downstream effector ATF4, suggesting engagement of alternative mechanisms preserving ATF4 homeostasis. These findings highlight S88 as a promising lead for treating ER stress-associated neuromuscular disorders and demonstrate the utility of this integrative discovery pipeline for identifying bioactive natural compounds with disease-modifying potential.

Neural processing of natural speech by children with developmental language disorder (DLD): EEG speech decoding, power and classifier investigations
The sensory/neural Temporal Sampling (TS) theory of developmental language disorder (DLD) is based on the sensory and linguistic impairments in rhythm processing that are found in children with both developmental dyslexia (DD) and DLD. These sensory/linguistic impairments include decreased sensitivity to amplitude rise times (ARTs), syllable stress patterns and speech rhythm. They are explained via a neural oscillatory speech processing framework drawn from the adult literature. Notably, at the neural level TS theory predicts impairments in the cortical tracking of different rates of amplitude modulation (AM) in the speech signal <10Hz. To date, the accuracy of low-frequency cortical tracking in natural continuous speech has not been measured in children with DLD. Here, EEG was recorded during story listening from children with and without DLD aged around 9 years, and decoding analyses in the delta, theta and alpha (control) bands were carried out. EEG power was computed in the delta, theta and gamma bands, as was phase-amplitude versus phase-phase coupling (PAC, PPC) between bands. The expectation that the accuracy of low-frequency decoding (delta, theta) of the speech signal would be impaired in DLD was not supported. Further, theta-delta and theta-gamma PAC were not atypical, contrary to prediction. EEG power in all bands was elevated for the DLD group, however. Receiving-operator-characteristic (ROC) curves estimated using support vector machine and logistic regression showed that these simple band power measures provided classifier models with the highest areas under the curves (AUC). The data are discussed using TS theory.

Transcriptomic and pathological analysis of the hnRNP network reveals glial involvement in FTLD pathological subtypes
Frontotemporal dementia (FTD) is a neurodegenerative disorder with a strong heritable component. Frontotemporal lobar degeneration (FTLD) refers to the pathological changes seen in FTD, characterised by atrophy of the frontal and temporal lobes and the presence of abnormal protein inclusions. In the case of FTLD with hyperphosphorylated TDP-43 positive inclusions (FTLD-TDP), five pathological subtypes (A, B, C, D, and E) are observed based on the types and distribution of inclusions found in the brain. In all subtypes, there tends to be a large variability in the number of pathological inclusions observed between cases, with limited correlation to clinical manifestations. TDP-43 is an RNA binding protein belonging to the heterogeneous nuclear ribonucleoprotein (hnRNP) family which along with other hnRNPs modulates multiple aspects of RNA processing. HnRNPs other than TDP-43 have been implicated in several neurological diseases, including ALS, FTLD-TDP, FTLD-FUS and Alzheimer's disease. Multiple hnRNPs have been found in pathological inclusions in specific subtypes of FTLD-TDP, suggesting potential roles in the disease process. The role of the hnRNP network in FTLD disease pathogenesis, however, has not yet been investigated. This study aimed to comprehensively evaluate the presence and expression of hnRNP proteins in two pathological subtypes of sporadic FTLD-TDP (A and C) as well as the genetic form FTLD-TDP A C9orf72 using immunohistochemistry and gene expression analysis by single-nuclei RNA-sequencing. We found that there was great variability in frequency of TDP-43 pathology across and within FTLD-TDP pathological subtypes. Finally, our findings suggest that distinct global transcriptomic profiles may underlie the different pathological subtypes of FTLD-TDP. The most prominent transcriptomic changes were observed in oligodendrocytes and astrocytes, involving multiple hnRNPs across FTLD subtypes compared to controls. Transcriptomic co-expression analysis further revealed that glial clusters were more strongly associated with RNA processing dysfunction and contribute to disease classification. Together, these findings highlight the involvement of the hnRNP network and glial-specific RNA processing alterations in FTLD-TDP pathophysiology, offering new insight into the molecular distinctions between pathological subtypes and potential targets for future investigation.

Reliability and signal comparison of OPM-MEG, fMRI & iEEG in a repeated movie viewing paradigm
Optically pumped magnetometers (OPMs) offer a promising advancement in noninvasive neuroimaging via magnetoencephalography (MEG), but establishing their reliability and comparability to existing methods remains an ongoing endeavor. Here, we evaluated OPM recordings by assessing their test-retest reliability and comparing them to functional magnetic resonance imaging (fMRI) and intracranial electroencephalography (iEEG) recordings in a repeated movie viewing paradigm. In 7 frequency bands ({delta}: 0.5-4 Hz, {theta}: 4-8 Hz, : 8-12 Hz, {beta}: 12-28 Hz, {gamma}1: 28-46 Hz, {gamma}2: 55-70 Hz, and HF: 64-116 Hz) we quantified the signal consistency (1) within individuals, (2) across subjects, and (3) across modalities. OPM exhibited widespread reliability, particularly in lower frequency bands; spatial patterns resembled those of fMRI and iEEG in visual and auditory regions. Cross-modal analyses revealed robust OPM-fMRI correspondence, including inverse correlations at low frequencies and positive correlations at higher frequencies, consistent with known relationships between oscillatory power and BOLD responses. Comparisons of signal-to-noise (SNR) estimates further revealed that in some regions, the SNR of cross-modal alignment exceeded within-modality reliability, suggesting that bridging between modalities can sometimes enhance SNR by attenuating reliably shared noise. Our findings demonstrate that OPM consistently captures stimulus-locked neural dynamics that converge with established modalities.

Context-Dependent Modulation of Astrocytic Ca2+ Signals by Mitochondria - A Computational Study
Mitochondria are one of the major regulators of intracellular Ca2+ in the cells, uptaking this ion through the mitochondrial Ca2+ uniporter (MCU) and releasing by the mitochondrial permeability transition pore (mPTP). Astrocytes respond to neurotransmitters and other stimuli by increasing the intracellular Ca2+ concentration, a process called 2+ signaling. However, it is not clear how mitochondria interact with the neurotransmitter-triggered Ca2+ responses in astrocytes. To explore this mechanisms, we expanded a previous compartmental model of astrocytes developed by our group including the mitochondrial MCU and mPTP mechanisms controlling the Ca2+ response. We simulate glutamatergic and dopaminergic inputs, modeled as Poisson processes, that promote the synthesis of IP3 through the PLC pathway. Here, we used a unipolar and a bifurcated-terminal morphology models and, with exception for the distal compartments, every other compartment have mitochondria. Simulations revealed that mitochondria modulate the Ca2+ response in a context-dependent manner. For weak glutamatergic input, they reduce the frequency of Ca2+ oscillations and the distance these signals propagate from the terminal regions. However, for strong glutamatergic input and in the presence of dopamine, mitochondria enhance the Ca2+ response by reducing the Ca2+-dependent IP3 degradation. Our findings provide computational evidence that mitochondria have a critical role in shaping the spatial organization of Ca2+ singling in astrocytes.

Compatibility of a competition model for explaining eyefixation durations during free viewing
Intersaccadic times or eye fixation durations (EFD) are relatively stable at around 250ms, equivalent to 4 saccades by second. However, the mean and standard deviation are not sufficient to describe the frequency histogram distribution of EFD. The exgaussian has been proposed for fitting the EFD histograms. Present report tries to adjust a competition model (C model) between the saccadic and the fixation network to the EFD histograms. This model is at a rather conceptual level (computational level in Marr classification). Both models were adjusted to EFD from an open database with data of 179473 eye fixations. The C model showed to be able, along with exgaussian model, to be compatible for explaining the EFD distributions. The two parameters of the C model can be ascribed to (i) a refractory period for new saccades modeled by a sigmoid equation (A parameter), while (ii) the ps parameter would be related to the continuous competition between the saccadic network related to the saliency map and the eye fixation network, and would be modeled through a geometric probability density function. The model suggests that competition between neural networks would be an organizational property of brain neural networks to facilitate the decision process for action and perception. In the visual scene scanning the C model dynamic justifies the early post-saccadic stability of the foveated image, and the subsequent exploration of a broad space in the observed image.

Impaired BDNF-TrkB trafficking and signalling in Down syndrome basal forebrain neurons
Brain derived neurotrophic factor (BDNF) and its receptor tropomyosin-related kinase B (TrkB) play crucial roles in neuronal development, synaptic transmission, and neuroplasticity. Deficits in BDNF/TrkB signalling and trafficking have been identified in several neurodegenerative diseases, including Alzheimer's disease (AD). Individuals with Down syndrome (DS) are at an increased risk of developing AD compared to the general population. Basal forebrain neurons (BFNs) are among the first to degenerate in AD and DS, but the mechanisms underlying their vulnerability remain unclear. Using BFNs derived from the Dp1Tyb mouse model of DS, we investigated neurotrophic signalling and trafficking deficits in AD-DS. We found enlarged early endosomes and elevated levels of active Rab5, a GTPase critical for early endosome formation, in Dp1Tyb BFNs. These abnormalities were associated with impaired transport of internalised TrkB from axon terminals to the soma. Using microfluidic devices, we demonstrated that axonal BDNF stimulation enhanced signalling endosome dynamics in wild-type but not Dp1Tyb BFNs, which is likely due to impaired axonal ERK1/2 signalling. Our findings establish a link between Rab5 hyperactivation, endosomal dysfunction, and impaired ERK1/2 signalling, highlighting the interplay between trafficking and neurotrophic signalling, and underscore the importance of targeting endolysosomal and signalling pathways to mitigate neuronal dysfunction in AD-DS.

Situation Models in the Brain are Used to Resolve Word References
Resolving the meaning of a pronoun requires retrieving information about a unique individual (a referent) from many remembered experiences and inferences throughout sensory and cognitive modalities, from vision and audition to episodic memory and social cognition. Here, we hypothesize that the functional neuroanatomy of pronoun interpretation involves interaction across distributed neural networks, during which each referent activates its own unique sensorimotor neural fingerprint associated with these experiences. To test this hypothesis, we collected fMRI data from 20 people watching a full-length movie, and developed a 3D branched convolutional neural network to distinguish movie characters from the fMRI signal across distributed sensorimotor regions. The same model distinguished the characters referenced by pronouns, using these same sensorimotor regions, supplemented by the hippocampus, precuneus, and medial prefrontal cortices. This work has far-reaching implications for understanding the relations among the many domains and modalities of neural representation required for ecological language comprehension. In particular, the demonstration that situation models, implemented in distributed sensory-motor and association cortices, are involved in resolving reference, suggests a whole brain distribution for language processing.

Genotype-Phenotype Distinctions in Spastic Paraplegia 4 Reveal HDAC6 as a Therapeutic Target
Spastic Paraplegia 4 (SPG4) is the most prevalent form of Hereditary Spastic Paraplegia (HSP), a neurodegenerative disorder characterized by progressive lower limb spasticity and debilitating gait impairment, primarily driven by axonal degeneration of corticospinal motor neurons (CSMNs). Caused by mutations in the SPAST gene encoding spastin, an AAA-ATPase involved in microtubule severing and intracellular organelle function, SPG4 accounts for 40-50% of autosomal dominant HSP cases, yet without effective treatments. Although reduced microtubule acetylation has emerged as a key pathological mechanism, whether and how distinct mutations lead to microtubule deacetylation and subsequent neurodegeneration remains unclear. To address this, we generated isogenic human induced pluripotent stem cell (hiPSC) lines with two distinct heterozygous SPAST mutations - SPASTWT/C448Y (missense) and SPASTWT/S245X (truncation). Employing an innovative differentiation protocol, we created human motor cortical organoids enriched in CSMNs, providing a robust platform to study SPG4 pathophysiology. These organoids revealed striking genotype-phenotype distinctions, with mutation-specific variations in CSMN loss, axonal degeneration and neuronal activities, mirroring clinical heterogeneity. Mechanistic studies identified aberrant activation of histone deacetylase 6 (HDAC6), a major neuronal microtubule deacetylase, as a key driver of SPG4 pathology. This dysregulation was specifically attributed to mutant M1-spastin, the longer isoform of spastin. Remarkably, pharmacological inhibition of HDAC6 with Tubastatin A restored microtubule acetylation status and mitigated axonal degeneration in both SPAST-mutant organoids, with corresponding improvements in corticospinal tract integrity and gait deficits validated in SPG4-transgenic mice. Collectively, our study establishes isogenic hiPSC-derived motor cortical organoids as a robust human model for corticospinal motor neuron degeneration and identifies HDAC6 hyperactivation as a central pathogenic mechanism and viable therapeutic target in SPG4.

AAV delivery of RNA editing machinery rescues SUDEP and seizure phenotype in a mouse model of Dravet Syndrome
Dravet syndrome (DS) is a severe childhood genetic epilepsy, caused by de novo heterozygous mutations in the SCN1A gene, resulting in a loss of function of the voltage-gated sodium ion channel, Nav1.1. Nav1.1 is expressed in the brain and at a lower level, in the heart. The disease manifests in the first year of life. Patients exhibit tonic-clonic seizures, febrile seizures, cognitive decline, development delays, ataxia, and in some cases sudden unexpected death from epilepsy (SUDEP). Here we have developed a novel AAV-F mediated CRISPR-Cas-inspired RNA targeting system (CIRTS) pre-clinical treatment to increase endogenous Scn1a to ameliorate the disease phenotype in a clinically relevant heterozygous loss of function mouse model of DS. We designed novel guide RNAs (gRNAs) to target the long non-coding RNA, (or natural antisense transcript) of Scn1a to increase the expression of Scn1a mRNA in DS mice. We show that intracerebroventricular and intravenous administration of AAV-F-CIRTS-gRNA9 to target the brain and the heart to neonatal Scn1a+/- mice resulted significant increase in survival and a reduction in SUDEP and spontaneous seizures. Furthermore, we have shown increased expression of endogenous Scn1a in treated AAV-F-CIRTS-gRNA9 Scn1a+/- mice. These findings provide proof of concept evidence that an AAV-F-CIRTS mediated therapy hold promise as a potential long-term treatment for DS.

Benchmarking the Impact of Anatomical Segmentation on In Vivo Magnetic Resonance Spectroscopy
Purpose: Estimation of metabolite concentrations in brain magnetic resonance spectroscopy (MRS) requires correction for differences in tissue water content, relaxation properties, and the proportions of gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). Accurate knowledge of the relative proportions of these tissue classes within the volume of interest is therefore essential for reliable quantification. Commonly used brain segmentation tools differ in their algorithms, priors, and implementation, potentially introducing variability in MRS-derived concentration estimates. This study investigates the impact of segmentation software on estimated absolute concentrations. Methods: Three segmentation software tools, ANTs, FSL, and SPM, were evaluated. Segmentations were applied to an in vivo test-retest MR dataset to assess (1) differences in estimated tissue fractions, and (2) how these differences propagate into tissue-corrected metabolite concentrations. As an additional validity check and biological benchmark of segmentation performance, age-related associations with GM and total creatine (tCr) were examined. Results: Significant differences (p < 0.0001) were observed in tissue fraction estimates between segmentation tools, leading to differences in metabolite concentration estimates of up to 9% under identical acquisition and modeling conditions. Although the strength of the correlation varied between segmentation methods, no statistically significant differences were found. Conclusion: The choice of segmentation methodology contributed substantially to variability in MRS 'absolute' metabolite concentration estimates. These results underscore the need for transparent segmentation reporting to ensure reproducibility and cross-study comparability in MRS research. Quantifying the segmentation-driven variability allows researchers to contextualize cross-study differences, helping determine whether observed effects are methodological or biologically meaningful.

Impaired Spatiotemporal Encoding of Social Behavior and Anxiety in the Prefrontal Cortex of Mice Lacking ASD-Risk Gene Shank3.
The prefrontal cortex is a central regulator of complex behaviors, including social interaction and anxiety-related behaviors. The prefrontal cortex encodes these behaviors using heterogeneous groups of neurons, or ensembles, which collectively process inputs and communicate with distributed brain regions. We examined whether loss of the Autism-risk gene Shank3 alters the recruitment of neurons encoding socioemotional behavior collectively, or if abnormal activity during specific behaviors might affect functionally or anatomically defined populations of neurons. To do this, we combined spatially-resolved microendoscopic calcium imaging across the prefrontal microcircuit with functionally defined labeling of neurons as control and mutant mice engaged in social interaction or anxiety-provoking behaviors. We then utilized a non-biased transcriptomic method to identify neurons activated by social interactions. We show that the recruitment of heterogeneous neuronal populations are altered in a cell type and spatially dependent manner by loss of Shank3, with impaired recruitment of behavior-specific activity patterns within superficial, but not deeper aspects of the prefrontal cortex.

Optogenetic inhibition reveals distinct contributions of medial prefrontal cortex to intertemporal choice in young and aged rats
The ability to choose adaptively between rewards differing in magnitude and delay (intertemporal choice) is critical for numerous life outcomes. Compared to younger adults, older adults tend to exhibit greater preference for large, delayed over small, immediate rewards (i.e., less delay discounting), which could lead to missed opportunities to obtain resources necessary for quality of life. Intertemporal choice is mediated by the prefrontal cortex, but how this is impacted by advanced age is not well understood. We used optogenetic inactivation to investigate contributions of medial prefrontal cortex (mPFC) during distinct components of an intertemporal choice task in young and aged rats. mPFC inactivation during deliberation (during decisions between small, immediate vs. large, delayed rewards) increased preference for large, delayed rewards in both age groups. In contrast, inactivation during delays prior to large reward delivery increased preference for large, delayed rewards only in aged rats. Choices were unaffected by inactivation during other task phases. Results suggest that mPFC integrates information regarding anticipated outcomes into the decision process across the whole lifespan, but that only in aging is mPFC critical for consolidating information regarding reward delays into the decision structure in order to modulate choice behavior.

Multiple Routes to Metacognitive Judgments of Working Memory in the Macaque Prefrontal Cortex
The ability to evaluate one' s own memory is known as metamemory. Whether metamemory is inherent to memory strength or requires additional computation in the brain remains largely unknown. We investigated the metacognitive mechanism of working memory (WM) using two-photon calcium imaging in the prefrontal cortex of macaque monkeys, who were trained to memorize spatial sequences of varying difficulties. In some trials, after viewing the sequence, monkeys could opt out of retrieval for a smaller reward, reflecting their confidence in WM (meta-WM). We discovered that PFC neurons encoded WM strength by jointly representing the remembered locations through population coding and their associated uncertainties. This WM strength faithfully predicted the monkeys' recall performance and opt-out decisions. In addition to memory strength, other factors--trial history and arousal--encoded in baseline activity predicted opt-out decisions, serving as cues for meta-WM. We identified a code of meta-WM itself that integrated WM strength and these cues. Importantly, WM strength, cues, and meta-WM were represented in different subspaces within the same PFC population. The dynamics and geometry of PFC activity implement metacognitive computations, integrating WM strength with cues into a meta-WM signal that guides behavior.

Cortex-wide laminar dynamics diverge during learning
Learning to link sensory information to motor actions involves dynamic coordination across cortical layers and regions. However, the involvement of a particular layer in learning, especially from a cortex-wide perspective, is relatively unknown. Using wide-field calcium imaging in mice as they learn a whisker-based go/no-go task, we tracked activity in layers 2/3 or 5 (L2/3 or L5) across 25 cortical areas. A surprising initial effect of learning was that activity in L5 but not in L2/3 was globally suppressed at auditory cue onset. As the texture comes into touch, we found that L2/3 displayed learning-related enhancements in higher order association areas rostrolateral (RL) and secondary somatosensory (S2), whereas L5 in these areas oppositely decreased. During texture touch, the barrel cortex (BC) displayed similar learning-related enhancement in both layers. As sensory information is transformed into a motor action, there was a frontal/posterior divergence that emerges after learning, in which L5 was enhanced in the frontal cortex and L2/3 was suppressed in the posterior cortex. In general, learning related correlations were often stronger between distant cortical layers than within the same column, suggesting that learning drives laminar interactions that transcend traditional columnar organization. Together, these results reveal that learning orchestrates a dynamic interplay of activity across space, time and cortical layers. Our findings emphasize the critical role of laminar architecture in shaping cortical plasticity and support the view that layer-specific circuits are fundamental to sensorimotor learning.