bioRxiv Subject Collection: Neuroscience's Journal

Continual familiarity decoding from recurrent connections in spiking networks
Familiarity memory enables recognition of previously encountered inputs as familiar without recalling detailed stimuli information, which supports adaptive behavior across various timescales. We present a spiking neural network model with lateral connectivity shaped by unsupervised spike-timing-dependent plasticity (STDP) that encodes familiarity via local plasticity events. We show that familiarity can be decoded from network activity using both frequency (spike count) and temporal (spike synchrony) characteristics of spike trains. Temporal coding demonstrates enhanced performance under sparse input conditions, consistent with the principles of sparse coding observed in the brain. We also show how connectivity structure supports each decoding strategy, revealing different plasticity regimes. Our approach outperforms LSTM in temporal generalizability on the continual familiarity detection task, with input stimuli being naturally encoded in the recurrent connectivity without a separate training stage.

Frontoparietal activity related to neuropsychological assessment of working memory
Executive functions, including working memory, are typically assessed clinically with neuropsychological instruments. In contrast, computerized tasks are used to test these cognitive functions in laboratory human and animal studies. Little is known of how neural activity captured by laboratory tasks relates to ability measured by clinical instruments and, by extension, clinical diagnoses of pathological conditions. We therefore sought to determine what aspects of neural activity elicited in laboratory tasks are predictive of performance in neuropsychological instruments. We recorded neural activity from intracranial electrodes implanted in human epilepsy patients as they performed laboratory working memory tasks. These patients had completed neuropsychological instruments preoperatively, including the Weschler Adult Intelligent Scale and the Wisconsin Card Sorting test. Our results revealed that increased high-gamma (70-150 Hz) power in the prefrontal and parietal cortex after presentation of visual stimuli to be remembered was indicative of lower performance in the neuropsychological tasks. On the other hand, we observed a positive correlation between high-frequency power amplitude in the delay period of the laboratory tasks and neuropsychological performance. Our results demonstrate how neural activity around task events relates to executive function and may be associated with clinical diagnosis of specific cognitive deficits.

Neuron type-specific mRNA translation programs provide a gateway for memory consolidation.
Long-term memory consolidation is a dynamic process that requires a heterogeneous ensemble of neurons, each with a highly specialized molecular environment. Considerable effort has been placed into understanding how the molecular mechanisms in specific neuron types are modified in memory, but these studies are often undertaken hours or days after training, when memory is already consolidated. Studies have shown that protein synthesis is elevated during the early stages of consolidation, but there is limited information as to how it impacts neuronal function. We hypothesize that mRNAs being translated during the early stages of consolidation could provide clues as to how diverse neurons involved in memory formation restructure their molecular architecture to support memory formation. Here, we generate a landscape of the translatome of three neuron types in the dorsal hippocampus during the first hour of contextual memory consolidation. Our results show that these neurons share a common backbone of readily translated mRNAs. However, excitatory neurons undergo deep reconfiguration of proteostatic control, whereas interneurons modify their synaptic transmission. We demonstrate that the translational control in these neurons requires GADD34, which promotes translation initiation. Finally, we show that the differential expression of mRNAs by neurons during early consolidation can be explained by features hard coded in the mRNA, suggesting ubiquitous mechanisms controlling activity-dependent neuronal translation. Altogether, our work uncovers previously unknown checkpoints controlling activity-dependent translation in neurons and provides a large, readily available resource for further investigations of memory formation in health and disease.

Audiovisual gamma stimulation enhances hippocampal neurogenesis and neural circuit plasticity in aging mice
Gamma oscillations are disrupted in various neurological disorders, including Alzheimer's disease (AD). In AD mouse models, non-invasive audiovisual stimulation (AuViS) at 40 Hz enhances gamma oscillations, clears amyloid-beta, and improves cognition. We investigated mechanisms of circuit remodeling underlying these restorative effects by leveraging the sensitivity of hippocampal neurogenesis to activity in middle-aged wild-type mice. AuViS increased progenitor cell proliferation, neuronal differentiation and morphological maturation of newborn granule cells, promoting their synaptic integration. While visual or auditory stimuli alone induced dendritic growth, axonal changes required combined audiovisual stimulation. The actions of AuViS involved neurotrophin pathways, as shown by the lack of effect upon TrkB signaling blockade. These results reveal widespread plasticity mechanisms triggered by AuViS, a therapeutic approach currently proposed for treating neurological disorders in humans.

MiRNA-501-3p and MiRNA-502-3p: A Promising Biomarker Panel for Alzheimer's Disease
INTRODUCTION: Alzheimers disease (AD) lacks a less invasive and early detectable biomarker. Here, we investigated the biomarker potential of miR-501-3p and miR-502-3p using different AD sources. METHODS: MiR-501-3p and miR-502-3p expressions were evaluated in AD CSF exosomes, serum exosomes, familial and sporadic AD fibroblasts and B-lymphocytes by qRT-PCR analysis. Further, miR-501-3p and miR-502-3p expressions were analyzed in APP, Tau cells and media exosomes. RESULTS: MiR-501-3p and miR-502-3p expressions were significantly upregulated in AD CSF exosomes relative to controls. MiRNA levels were high in accordance with amyloid plaque and NFT density in multiple brain regions. Similarly, both miRNAs were elevated in AD and MCI serum exosomes compared to controls. MiR-502-3p expression was high in fAD and sAD B-lymphocytes. Finally, miR-501-3p and miR-502-3p expression were elevated intracellularly and secreted extracellularly in response to APP and Tau pathology. DISCUSSION: These results suggest that miR-501-3p and miR-502-3p could be promising biomarkers for AD.

MicroRNA-502-3p modulates the GABA A subunits, synaptic proteins and mitochondrial morphology in hippocampal neurons
MicroRNA-502-3p (MiR-502-3p), a synapse enriched miRNA is considerably implicated in Alzheimers disease (AD). Our previous study found the high expression level of miR-502-3p in AD synapses relative to controls. Further, miR-502-3p was found to modulate the GABAergic synapse function via modulating the GABA A receptor subunit -1 (GABRA1) protein. The current study is attempted to examine the impact of miR-502-3p on other GABA subunit proteins, synaptic proteins, mitochondrial morphology and other hippocampal neuron genes. Mouse hippocampal neuronal (HT22) cells were transfected with miR-502-3p overexpression (OE) vector, miR-502-3p sponge (suppression) vector and scramble control vector. MiR-502-3p vectors transfection was confirmed by fluorescence microscopy. MiR-502-3p expression and GABRA1 expression was confirmed by qRT-PCR and miRNAScope in-situ hybridization. GABA A subunit and synaptic proteins were studied by immunoblotting analysis and mitochondrial morphology was analyzed by transmission electron microscopy (TEM) analysis. Further, Affymetrix gene array analysis was conducted in miR-502-3p overexpressed and suppressed cells. Our results observed that elevated miR-502-3p, negatively modulates the GABRA1 level. The levels of GABA A subunit and synaptic proteins were reduced by ectopic expression of miR-502-3p and increase by miR-502-3p suppression. The mitochondrial morphology was found to be improved in-terms of their number and length in miR-502-3p suppressed cells. Further, Gene array analysis unveiled the deregulation of several genes by miR-502-3p, which are associated with oxidative stress, immune response and synaptic function. These results provide new insights and an update to understand the biological roles of miR-502-3p in regulation of neuron function and synaptic activity.

Constructing Biologically Constrained RNNs via Dale's Backprop and Topologically-Informed Pruning
Recurrent neural networks (RNNs) have emerged as a prominent tool for modeling cortical function, and yet their conventional architecture is lacking in physiological and anatomical fidelity. In particular, these models often fail to incorporate two crucial biological constraints: i) Dale's law, i.e., sign constraints that preserve the "type" of projections from individual neurons, and ii) Structured connectivity motifs, i.e., highly sparse yet defined connections amongst various neuronal populations. Both constraints are known to impair learning performance in artificial neural networks, especially when trained to perform complicated tasks; but as modern experimental methodologies allow us to record from diverse neuronal populations spanning multiple brain regions, using RNN models to study neuronal interactions without incorporating these fundamental biological properties raises questions regarding the validity of the insights gleaned from them. To address these concerns, our work develops methods that let us train RNNs which respect Dale's law whilst simultaneously maintaining a specific sparse connectivity pattern across the entire network. We provide mathematical grounding and guarantees for our approaches incorporating both types of constraints, and show empirically that our models match the performance of RNNs trained without any constraints. Finally, we demonstrate the utility of our methods for inferring multi-regional interactions by training RNN models of the cortical network to reconstruct 2-photon calcium imaging data during visual behaviour in mice, whilst enforcing data-driven, cell-type specific connectivity constraints between various neuronal populations spread across multiple cortical layers and brain areas. In doing so, we find that the interactions inferred by our model corroborate experimental findings in agreement with the theory of predictive coding, thus validating the applicability of our methods.

Eyes-closed resting state EEG reveals clearer and more stable group differences between autistic and neurotypical individuals than eyes-open resting state EEG
Background: Resting-state electroencephalography (rs-EEG) has been widely used to explore neural dynamics in Autism Spectrum Condition (ASC). However, inconsistencies in findings across studies remain a challenge, partly due to variations in brain state, such as eye conditions (eyes-open vs. eyes-closed). This study aims to examine rs-EEG differences between ASC and neurotypical (NT) participants, focusing on the influence of eye condition. Methods: A total of 300 participants (126 ASC) were included. Rs-EEG data were analysed across eyes-open, eyes-closed, and difference between eye conditions, with 726 variables assessed per participant. Linear regression and effect size (partial2 ) were used to identify group differences, complemented by cluster-based permutation testing and bootstrapped split-half validation for reliability. Results: Group differences were most pronounced in the eyes-closed condition, particularly for relative power and multiscale entropy (MSE). Compared to neurotypical participants, ASC participants exhibited reduced frontal coarse-scale MSE, increased delta power, and decreased alpha power, suggesting altered local-global neural dynamics. Cross-validation revealed greater reliability of effects in the eyes-closed condition compared to eyes-open or difference between eye conditions. Conclusions: Eye condition plays a critical role in detecting rs-EEG differences between ASC and NT groups, with the eyes-closed condition yielding more consistent and pronounced effects. These findings highlight the importance of controlling brain state in rs-EEG studies and suggest that integrating eye condition effects with other biomarkers may improve identification of neural differences associated with ASC.

Glucocerebrosidase Deficiency Dysregulates Human Astrocyte Lipid Metabolism
Background: Deficiency in the lysosomal enzyme, glucocerebrosidase (GCase), caused by mutations in the GBA1 gene, is the most common genetic risk factor for Parkinson's disease (PD). However, the consequence of reduced enzyme activity within neural cell sub-types remains ambiguous. Thus, the purpose of this study was to define the effect of GCase deficiency specifically in human astrocytes and test their non-cell autonomous influence upon dopaminergic neurons in a midbrain organoid model of PD. Methods: Wild-type (GBA+/+), N370S mutant (GBA+/N370), and GBA1 knockout (GBA-/-) astrocytes were rapidly and directly induced from human pluripotent stem cells (hPSCs) via transcription factor-based differentiation. These astrocytes were extensively characterized for GCase-dependent phenotypes using immunocytochemistry, organoid coculture, enzymatic assays, lipid tracers, transcriptomics, and lipidomics. Results: hPSC lines were rapidly induced into astrocytes and enzymatic assays confirmed that GBA-/- astrocytes completely lacked GCase activity, while GBA+/N370 preserved partial activity. GBA-/-, but not GBA+/N370S, exhibited lysosomal alterations, with enlarged lysosomes and glucosylceramide (GlcCer) accumulation. GCase deficiency also exacerbated TNF-alpha-induced secretion of the inflammatory biomarker, CCL2. In midbrain organoids, GCase activity did not modulate the ability of astrocytes to support dopamine neuron production and survival. Lipidomics revealed a GBA-/--specific increase in sphingomyelin, and a decrease of triglycerides. Direct rescue of GCase activity with GBA1 mRNA treatment reduced GlcCer accumulation. Astrocytes exhibited a relatively high uptake and storage of fatty acid analogs as lipid droplets, in comparison to neurons, and this process was impaired in GBA-/- astrocytes. Lastly, GBA-/- astrocytes accumulate neuronal membrane-derived GlcCer. These findings highlight the critical role of astrocytic GCase in lipid metabolism and its neuronal influence. Conclusion: GCase deficiency does not inhibit human astrocyte differentiation nor cause a non-cell autonomous neurotoxic effect upon dopaminergic neurons within midbrain organoids. However, it does elicit enhanced inflammatory reactivity, accumulation of GlcCer, and a distinct lipidomic profile, indicating impaired lipid metabolism in astrocytes that can dysregulate neuron-astrocyte intercellular signaling. Overall, these insights underscore dysfunctional astrocyte lipid metabolism as a high priority therapeutic target in Parkinson's disease and related neurodegenerative disorders.

CO2-dependent opening of Connexin 43 hemichannels
Sequence and structure comparisons between alpha and beta connexins, Cx43 and Cx26, revealed that Cx43 has a motif, the carbamylation motif, that confers CO2-sensitivity on a subset of beta connexins. By using a fluorescent dye loading assay, whole cell patch clamp recordings and real time measurement of ATP release via GRABATP we have demonstrated that Cx43 hemichannels open in a highly CO2 sensitive manner over the range 20 to 70 mmHg. Mutational analysis confirms that the equivalent residues to those in Cx26 that have been shown to be involved in mediating the effects of CO2 on gating of hemichannels and gap junction channels, also mediate Cx43 hemichannel gating. Our data predicts that Cx43 will be partially open and able to release ATP at resting physiological levels of PCO2. We have tested this prediction in acute hippocampal slices, by showing that CO2-dependent enhancement of synaptic transmission can be blocked by the Cx43-selective mimetic peptide Gap26. Our data resolves an inconsistency in the literature between in vivo studies suggesting that Cx43 hemichannels are at least partially open at rest, and in vitro studies, performed in the absence of HCO3-/CO2 buffering that show Cx43 hemichannels are shut. Our evidence suggests that the ancestral gene that duplicated to give the alpha and beta connexin clades must have possessed the carbamylation motif. CO2 sensitivity is thus a fundamental ancient characteristic of several connexins that has been lost in more recently derived members of this gene family.

Peripheral alcohol metabolism dictates ethanol consumption and drinking microstructure in mice
Background: Ethanol metabolism is intimately linked with the physiological and behavioral aspects of ethanol consumption. Ethanol is mainly oxidized by alcohol dehydrogenase (ADH) to acetaldehyde and further to acetate via aldehyde dehydrogenases (ALDHs). Understanding how ethanol and its metabolites work together to initiate and drive continued ethanol consumption is crucial for identifying interventions for alcohol use disorder (AUD). Therefore, the goal of our study was to determine how ADH1, which is mainly peripherally-expressed and metabolizes >90% of ingested ethanol, modulates ethanol metabolite distribution and downstream behaviors. Methods: Ethanol consumption in drinking-in-the-dark (DID) and two-bottle choice (2BC) drinking paradigms, ethanol metabolite concentrations, and lickometry were assessed after ADH1 inhibition and/or in Adh1-knockout (Adh1 KO) mice. Results: We found that Adh1 KO mice of both sexes exhibited decreased ethanol consumption and preference compared to wild-type (WT) mice in DID and 2BC. ADH1 inhibitor fomepizole (4-MP) also significantly decreased normal and sweetened ethanol consumption in DID studies. Measurement of ethanol and its metabolites revealed that ethanol was increased at 1h but not 15 min, peripheral acetaldehyde was slightly decreased at both time points, and ethanol-induced increases in acetate were abolished after ethanol administration in Adh1 KO mice compared to controls. Similarly, ethanol accumulation as a function of consumption was 2-fold higher in Adh1 KO or 4-MP treated mice compared to controls. We then used lickometry to determine how this perturbation in ethanol metabolism affects drinking microstructure. Adh1 KO mice consume most of their ethanol in the first 30 min like WT mice but display altered temporal shifts in drinking behaviors and do not form normal bout structures, resulting in lower ethanol consumption. Conclusions: Our study demonstrates that ADH1-mediated ethanol metabolism is a key determinant of ethanol consumption, highlighting a fundamental knowledge gap around how ethanol and its metabolites drive ethanol consumption.

Astrocyte and mitochondrial footprints in brain-derived extracellular vesicles predict tau pathology
Tauopathies are neurodegenerative disorders characterized by abnormal tau aggregation, with primary 3R (e.g., Picks disease, PiD) and 4R (e.g., progressive supranuclear palsy, PSP) variants posing a significant diagnostic challenge. Here, we examined brain-derived extracellular vesicles (BD-EVs) isolated from the prefrontal cortex of PiD (3R), PSP (4R), and non-demented controls (CTRL) to determine if these vesicles reflect disease-specific proteomic signatures. We found that while tau pathology does not substantially alter BD-EV concentration or the enrichment of core vesicular markers, it does influence their size distribution and protein cargo. BD-EV samples from PiD patients exhibited a greater abundance of small vesicles and distinct protein profiles when compared to PSP and CTRL. Weighted Gene Co-expression Network Analysis (WGCNA) identified four key protein modules to account for variance between patient groups Endoplasmic Reticulum, Mitochondria, Microtubules, and Trivalent Inorganic Cation Transport. In PiD, astrocyte-derived mitochondrial proteins were significantly elevated, whereas neuronal microtubule-related proteins were diminished relative to both PSP and CTRL. Notably, changes in the mitochondrion and microtubule modules enhanced the detection of PiD pathology. Cellular origin annotation revealed a marked shift in BD-EV composition: PiD samples exhibited an increased astrocytic signature, while both PiD and PSP showed a reduction in neuronal proteins compared to CTRL. Crucially, the enrichment of astrocytic mitochondrial and endoplasmic reticulum proteins, alongside reduced neuronal proteins, correlated strongly with the severity of tau pathology (AT8-stained aggregates) in patient brains. These findings demonstrate that BD-EVs capture tau isoform-specific cellular and molecular alterations, offering a window into disease mechanisms at the neuron-glia interface. By linking distinct protein signatures and their cellular origins to tau pathology severity, our results highlight the potential of BD-EV profiling as a biomarker strategy for distinguishing between and monitoring the progression of 3R and 4R tauopathies.

EEG correlates of active removal from working memory
The removal of no-longer-relevant information from visual working memory (WM) is important for the functioning of WM, given its severe capacity limitation. Previously, with an "ABC-retrocuing" WM task, we have shown that removing information can be accomplished in different ways: by simply withdrawing attention from the newly irrelevant memory item (IMI; i.e., via "passive removal"); or by or "actively" removing the IMI from WM (Shan and Postle, 2022). Here, to investigate the neural mechanisms behind active removal, we recorded electroencephalogram (EEG) signals from human subjects (both sexes) performing the ABC-retrocuing task. Specifically, we tested the hijacked adaptation model, which posits that active removal is accomplished by a top-down-triggered down-modulation of the gain of perceptual circuits, such that sensory channels tuned to the to-be-removed information become less sensitive. Behaviorally, analyses revealed that, relative to passive removal, active removal produced a decline in the familiarity landscape centered on the IMI. Neurally, we focused on two epochs of the task, corresponding to the triggering, and to the consequence, of active removal. With regard to triggering, we observed a stronger anterior-to-posterior traveling wave for active versus passive removal. With regard to the consequence(s) of removal, the response to a task-irrelevant "ping" was reduced for active removal, as assessed with ERP and with posterior-to-anterior traveling waves, suggesting that active removal led to decreased excitability in perceptual circuits centered on the IMI.

Noise Correlations in Balanced Networks with Unreliable Synapses
Synaptic physiology is highly stochastic in the neocortex: immediately following an action potential, individual synapses release neurotransmitter unreliably, sometimes even failing to release any vesicles. However, theoretical models of neuronal networks typically neglect this well-established feature of biology, especially recurrent networks. In this work, to better understand the effects of synaptic unreliability in recurrent networks, we describe neuronal variability in a balanced network model of non-leaky integrate-and-fire neurons incorporating a simple Bernoulli model of synaptic release. For arbitrary network size, synaptic unreliability contributes non-negligibly to spike count variability. Most notably, this additional noise is overshadowed by effects on noise correlations. In particular, we find that feedforward and recurrent synaptic reliability have opposite influences on noise correlations: while increased reliability of synaptic input from neurons outside of the network increase correlations, reliability of recurrent synapses de-correlates population activity. We explain this dichotomy by examining the average input currents to cell pairs, and verify this effect with simulations of exponential integrate-and-fire neurons with adaptation and conductance-based synapses. Overall, our results emphasize the importance of synaptic unreliability in the study of noise correlations.

Dynamic face-related eye movement representations in the human ventral pathway
Multiple brain areas along the ventral pathway have been known to represent face images. Here, in a magnetoencephalography (MEG) experiment, we show dynamic representations of face-related eye movements in the ventral pathway in the absence of image perception. Participants followed a dot presented on a uniform background, the movement of which represented gaze tracks acquired previously during their free-viewing of face and house pictures. We found a dominant role of the ventral stream in representing face-related gaze tracks, starting from the orbitofrontal cortex (OFC) and anterior temporal lobe (ATL), and extending to the medial temporal and ventral occipitotemporal cortex. Our findings show that the ventral pathway represents the gaze tracks used to explore faces, by which top-down prediction of face category in OFC and ATL may guide, via the medial temporal cortex or directly, face perception in the ventral occipitotemporal cortex.

Characterizing Oligodendrocyte-Lineage Cells and Myelination in the Basolateral Amygdala: Insights from a Novel Methodology in Postmortem Human Brain
The basolateral amygdala (BLA) plays a key role in the pathophysiology of depressive disorders and trauma, yet oligodendrocyte-lineage cells and myelin in this brain region remain understudied in humans. This might be due, at least in part, to the lack of a cost-effective, antibody-based method to isolate oligodendrocytes (OL) and OL precursor cells (OPC) from postmortem brain tissue that is compatible with molecular biology applications. This study aimed to: 1) create and validate a method for isolating OPC and OL nuclei from frozen postmortem grey matter; 2) compare OPC and OL gene expression in the BLA between subjects having died with depression and matched controls; and 3) provide histological characterizations of OPC, OL, and myelin in the BLA. Frozen left-hemisphere BLA samples were obtained from brain donors with well-characterized phenotypic information. Immunolabeled nuclei were sorted into OPC (SOX10+/CRYAB-) and OL (SOX10+/CRYAB+) populations, and RNA was measured using a custom Nanostring codeset. Fluorescence in situ hybridization was used to determine OPC (PDGFR+) and OL (MYRF+) densities, and immunofluorescence was used to label axons (NF-H) and myelin (MBP) for myelin area fraction. The method successfully isolated OPC and OL nuclei with correct transcriptomic profiles. While no significant group differences were observed in gene expression, cell densities, or myelin coverage, we did observe significant age-related patterns. Moreover, a strong significant correlation between OL density and myelin area fraction was identified. This study provides a novel sorting method and a comprehensive characterization of OL-lineage gene expression, cell densities, and myelin in the human BLA.

Integrated Multi-Omics Analyses of Synaptosomes Revealed Synapse-Centered Novel Targets in Alzheimer's Disease
Synapse dysfunction is an early event in Alzheimers disease (AD) caused by various factors such as Amyloid beta, p-tau, inflammation, and aging. However, the exact molecular mechanism of synapse dysfunction in AD is largely unknown. To understand this, we comprehensively analyzed the synaptosome fraction in postmortem brain samples from AD patients and cognitively normal individuals. We conducted high-throughput transcriptomic analyses to identify changes in microRNA (miRNA) and mRNA levels in synaptosomes extracted from the brains of both unaffected individuals and those with Alzheimer's disease (AD). Additionally, we performed mass spectrometry analysis of synaptosomal proteins in the same sample group. These analyses revealed significant differences in the levels of miRNAs, mRNAs, and proteins between the groups. To further understand the pathways or molecules involved, we used an integrated omics approach and studied the molecular interactions of deregulated synapse miRNAs, mRNAs, and proteins in the samples from individuals with AD and the control group, which demonstrated the impact of deregulated miRNAs on their target mRNAs and proteins. Furthermore, the DIABLO analysis highlighted complex relationships between mRNAs, miRNAs, and proteins that could be key in understanding the pathophysiology of AD. Our study identified synapse-centered novel candidates that could be critical in restoring synapse dysfunction in AD.

Risk preferences causally rely on parietal magnitude representations: Evidence from combined TMS-fMRI
Risk preferences have traditionally been considered as stable traits that reflect subjective-valuation processes in prefrontal areas. More recently, however, it has been suggested that risk preferences may also be shaped by how choice problems are perceived and processed in perceptual brain regions. Specifically, the acuity of the parietal approximate number system (ANS), which encodes payoff magnitudes for different choice options, has been shown to correlate with both risk preferences and choice consistency. However, this correlational relationship leaves open the question whether parietal magnitude representations in fact causally underlie choice. Here, we provide direct evidence for such a key causal role of parietal magnitude representations in economic choice, using continuous theta-burst transcranial magnetic stimulation (cTBS), combined with functional MRI (fMRI) and numerical population receptive field (nPRF) modeling. Our stimulation protocol targeted numerosity-tuned regions in the right parietal cortex, identified through nPRF modeling of individual fMRI data (n=35; within-subject design). The stimulation successfully perturbed neural processing, as evidenced by decreased amplitude of numerical magnitude-tuned responses and less accurate multivariate decoding of presented magnitudes from unseen data that were not used for model fitting. In line with a perceptual account of risky choice, the reduction in neural information capacity was also reflected in noisier behavioral responses. Moreover, a computational cognitive model fitted to choice behavior revealed that perturbing the ANS specifically increased the noisiness of small-magnitude representations. This perturbation made small magnitudes to be perceived as larger than they actually are, leading to more risk-seeking behavior. Finally, individual estimates of the cTBS effect on cognitive noise correlated with the corresponding decrease in amplitude of numerical magnitude-tuned fMRI responses, further solidifying the role of the parietal ANS in economic choice. In conclusion, our study demonstrates that the precision of parietal magnitude representations causally influences economic decision-making, with noisier encoding promoting biased risk-taking as formalized in recent perceptual models of risky choice.

Cerebellar transcranial alternating current stimulation in the theta band facilitates extinction of learned fear responses
Fear extinction is a major component of exposure therapy for anxiety disorders. There is initial evidence that the cerebellum contributes to fear extinction learning, i.e., the ability to learn that certain stimuli are no longer associated with an aversive outcome. So far, however, knowledge of the cerebellum's role in extinction is scarce. In the present study, 6 Hz cerebellar transcranial alternating current stimulation (ctACS) was used to modulate cerebellar function during extinction learning in young and healthy human participants in an MRI study. A two-day differential fear conditioning paradigm was used with acquisition and extinction training being performed on day 1, and fear extinction recall being tested on day 2. 6 Hz ctACS reduced spontaneous recovery of the initial fear association during recall, stabilizing extinction effects compared to sham ctACS. fMRI data during recall revealed significantly reduced activation in cortical areas involved in initial fear acquisition, such as the anterior cingulate and insula, in the verum ctACS group compared to the sham group. During extinction training, on the other hand, the verum group exhibited more widespread cerebral activation compared to the sham group. Group differences were significant in occipital cortical areas. Although direct stimulation effects cannot be excluded, increased activation in the visual cortex may reflect enhanced encoding and processing of visual information during fear extinction learning. The findings suggest that theta-range oscillatory interactions between the cerebellum and cortical areas support extinction processes and provide causal evidence of the cerebellar role in the human fear extinction network.

Deciphering Brain Organoids Heterogeneity by Identifying Key Quality Determinants
Brain organoids derived from human pluripotent stem cells (hPSCs) hold immense potential for modeling neurodevelopmental processes and disorders. However, undefined organoid selection criteria for analysis and their variability hinder reproducibility. As part of the Bavarian ForInter consortium, we generated 72 brain organoids from distinct hPSC lines. We conducted a comprehensive analysis of their morphological and cellular characteristics at an early stage of their development. In our assessment, the Feret diameter emerged as a reliable, single parameter that characterizes brain organoid quality. Transcriptomic analysis further confirmed the reliability of this marker and identified a negative impact of mesenchymal cells on the abundance of organoid formation. High-quality organoids consistently displayed a lower mesenchymal cell presence. These findings offer a framework for enhancing brain organoid standardization and reproducibility, underscoring the need for morphological quality controls and the consideration of mesenchymal cell influence on organoid-based modeling.

Narrative 'twist' shifts within-individual neural representations of dissociable story features
Given the same external input, one's understanding of that input can differ based on internal contextual knowledge. Where and how does the brain represent latent belief frameworks that interact with incoming sensory information to shape subjective interpretations? In this study, participants listened to the same auditory narrative twice, with a plot twist in the middle that dramatically shifted their interpretations of the story. Using a robust within-subject whole-brain approach, we leveraged shifts in neural activity between the two listens to identify where latent interpretations are represented in the brain. We considered the narrative in terms of its hierarchical structure, examining how global situation models and their subcomponents-namely, episodes and characters-are represented, finding that they rely on partially distinct sets of brain regions. Results suggest that our brains represent narratives hierarchically, with individual narrative elements being distinct and dynamically updated as a part of changing interpretations of incoming information.

Circadian and circatidal oscillations of clock gene expression in brains of Eurydice pulchra and Parhyale hawaiensis.
Coastal organisms express daily and tidal rhythms of physiology and behaviour to adapt to their intertidal environments. Although the molecular-genetic basis of the circadian clocks driving daily rhythms is well understood, the nature and mechanism of circatidal clocks remain a mystery. Using fluorescent in situ hybridisation, we mapped discrete clusters of putative clock cells co-expressing canonical circadian clock genes across the brains of the intertidal crustaceans Eurydice pulchra and Parhyale hawaiensis. Tidally rhythmic, field-collected E. pulchra exhibited ~12-hour and ~24-hours rhythms of gene expression in discrete cell groups. Laboratory-reared P. hawaiensis entrained to 24-hour light:dark cycles (LD) and exhibiting daily behaviour exhibited robust 24-hour rhythms of gene expression in several cell groups. In P. hawaiensis showing circatidal behaviour following tidal entrainment by agitation cycles under LD, circadian gene expression was evident in some of the daily rhythmic cell groups, but cells in the dorsal-lateral cluster exhibited robust ~12-hour, i.e., circatidal, transcriptional rhythms. This oscillation was phased to the prior tidal agitation, not to LD. These brain networks of cell groups with circadian or circatidal periodicities tracking LD or tidal agitation, respectively, reveal a neural substrate for the interactive generation of rhythms appropriate to complex intertidal habitats.

Acoustic features of and behavioral responses to emotionally intense mouse vocalizations
Social vocalizations contain cues that reflect the motivational state of a vocalizing animal. Once perceived, these cues may in turn affect the internal state and behavioral responses of listening animals. Using the CBA/CAJ mouse model of acoustic communication, this study examined acoustic cues that signal intensity in male-female interactions, then compared behavioral responses to intense mating vocal sequences with those from another intense behavioral context, restraint. Experiment I in this study examined behaviors and vocalizations associated with male-female social interactions. Based on several behaviors, we distinguished more general, courtship-type interactions from mating interactions involving mounting or attempted mounting behaviors. We then compared vocalizations between courtship and mating. The increase in behavioral intensity from courtship to mating was associated with altered syllable composition, more harmonic structure, lower minimum frequency, longer duration, reduced inter-syllable interval, and increased sound intensity. We then used these features to construct highly salient playback stimuli associated with mating. In Experiment II, we compared behavioral responses to playback of these mating sequences with responses to playback of aversive vocal sequences produced by restrained mice, described in previous studies. Subjects were females in estrus and males. We observed a range of behavioral responses. Some (e.g., Attending and Stretch-Attend) showed similar responses across playback type and sex, while others were context dependent (e.g., Flinching, Locomotion). Still other behaviors showed either an effect of sex (e.g., Self-Grooming, Still-and-Alert) or an interaction between playback type and sex (Escape). These results demonstrate both state-dependent features of mouse vocalizations and their effectiveness in evoking a range of behavioral responses, independent of contextual cues provided by other sensory stimuli or behavioral interactions.

Characterization of auditory responsive neurons in the mouse superior colliculus to naturalistic sounds
Locating the source of a specific sound in a complex environment and determining its saliency is critical for survival. The superior colliculus (SC), a sensorimotor midbrain structure, plays an important role in sound localization and has been shown to have a topographic map of the auditory space in a range of species. In mice, previous studies using broadband white noise stimuli found that neurons use high-frequency monaural spectral cues and interaural level differences (ILDs) to compute spatially restricted receptive fields (RFs), and that these RFs are organized topographically along the azimuth. However, in a naturalistic environment, the auditory stimuli that an animal encounters may have rich spectral components; however, these sound sources can still be localized efficiently. It remains unknown whether and how the SC neurons respond to naturalistic sounds and, in turn, compute a spatially restricted RF. Here, we show results from large-scale in vivo physiological recordings of SC neurons in response to white noise, naturalistic ultrasonic pup calls and chirps. We find that mouse SC auditory neurons respond to pup calls with distinct temporal patterns and a spatial preference predominantly at ~60 degrees in contralateral azimuth. In addition, we categorized auditory SC neurons based on their spectrotemporal receptive field patterns and demonstrated that there are at least 4 distinct subtypes of auditory responsive SC neurons.

Selective Targeting of Pathogenic Tau Seeds via a Novel VHH
In Alzheimer's disease (AD) and related tauopathies, progressive pathology has been linked to prion mechanisms, whereby ordered tau assemblies, or ''seeds,'' form in one cell and transit to neighboring or connected cells where they serve as templates for their own replication. Despite intensive efforts to develop early diagnosis and effective treatment, none has emerged. This is due partly to the structural heterogeneity of tau seeds and limitations in selectively targeting their pathogenic conformations. Here we report the discovery of a camelid variable heavy domain of heavy chain (VHH) that preferentially binds tau seeds of AD, corticobasal degeneration (CBD), and PS19 tauopathy mouse brains. From a published synthetic VHH yeast display library, we identified VHH clones that bound 2N4R tau monomer. After counter-screening for immunoprecipitation of seeding from human brain, we identified two seed-selective anti-tau VHH--VHH(510) and VHH(50)--that preferentially bound pathological tau. We enhanced the stability of these VHHs through framework mutations without affecting their seed-binding characteristics. We characterized VHH(510) in detail, determining that it binds the carboxy terminus of tau, maintains robust seed avidity even in the presence of competing monomer, and stains pathological tau inclusions in mouse and human AD tissues. These results highlight the power of seed-selective VHH to bind pathogenic tau, paving the way for future therapeutic and diagnostic applications across a wide range of neurodegenerative disorders.

Title: Cell-autonomous and non-cell-autonomous effects of TRIM72 on ALS disease progression
Dysfunction of RNA-binding proteins, including TDP-43 and FUS, has been associated with amyotrophic lateral sclerosis (ALS); however, the underlying mechanisms are largely unknown. Here, we reported that a neuronal upregulation of TRIM72 (Tripartite Motif Containing 72) in FUS mutation knockin ALS models slows disease progression. TRIM72 interacts with Commander, a protein complex for recycling of membrane proteins, facilitating membrane repair and antioxidation. Exosomal TRIM72 is detected in ALS patient cerebrospinal fluid (CSF) and extracellular application of exosomal TRIM72 protects cell from membrane damage. In a sporadic ALS cohort, CSF TRIM72 level associates ALS disease progression. AAV-mediated neuronal expression of TRIM72 slows down the disease progressions in ALS models and in an ALS patient without adverse effects over a year treatment course. Taken together, our results suggest a universal neuronal protection of a TRIM family protein in cell-autonomous and non-cell-autonomous manners in ALS.

dlmoR: An open-source R package for the dim-light melatonin onset (DLMO) hockey-stick method
The dim-light melatonin onset (DLMO) is a commonly used circadian phase marker indicating the start time of evening melatonin synthesis in humans. Several quantitative techniques have been developed to determine DLMO from melatonin time-series, including fixed- or variable-threshold techniques and the hockey-stick method developed by Danilenko and colleagues (2014). Here, we introduce dlmoR, an open-source implementation of the hockey-stick method implemented in the R programming language and licensed under the permissive MIT License. Our clean-room implementation followed the algorithm description from the original article, supported by iterative validation against the existing binary executable software. We benchmark our implementation using a total of 112 melatonin time-series data sets from two different studies (Blume et al, 2024; Heinrichs and Spitschan, 2024), and find high agreement between our implementation and the reference implementation. The mean DLMO point discrepancy between implementations was -2.1 +/- 11.1 minutes for the Blume et al. (2024) dataset and -1.482 +/- 21.7 for the Heinrichs and Spitschan (2024) dataset. Circular correlation coefficients were 0.986 and 0.964, respectively, and paired t-tests (p > 0.05) were not significant, suggesting no systematic difference or bias between the methods. dlmoR allows for the programmatic and batchable analysis of evening melatonin concentration data, enabling transparency and reproducibility of analytic techniques.

BDNF in Ventrolateral Orbitofrontal Cortex to Dorsolateral Striatum Circuit Moderates Alcohol Consumption and Gates Alcohol Habit
BDNF plays a crucial role in shaping the structure and function of neurons. BDNF signaling in the dorsolateral striatum (DLS) is part of an endogenous pathway that protects against the development of alcohol use disorder (AUD). Dysregulation of BDNF levels in the cortex or dysfunction of BDNF/TrkB signaling in the DLS results in the escalation of alcohol drinking and compulsive alcohol use. The major source of BDNF in the striatum is the prefrontal cortex. We identified a small ensemble of BDNF-positive neurons in the ventrolateral orbitofrontal cortex (vlOFC), a region involved in AUD, that extend axonal projections to the DLS. We speculated that BDNF in vlOFC-to-DLS circuit may play a role in limiting alcohol drinking and that heavy alcohol use disrupts this protective pathway. We found that BDNF expression is reduced in the vlOFC of male but not female mice after long-term cycles of binge alcohol drinking and withdrawal. We discovered that overexpression of BDNF in vlOFC-to-DLS but not in vlOFC-to-dorsomedial striatum (DMS) or M2 motor cortex-to-DLS circuit reduces alcohol but not sucrose intake and preference. The DLS plays a major role in habitual behaviors. We hypothesized that BDNF in vlOFC-to-DLS circuitry controls alcohol intake by gating habitual alcohol seeking. We found that BDNF over-expression in vlOFC-to-DLS circuit and systemic administration of BDNF receptor TrkB agonist, LM22A-4, biases habitually trained mice towards goal-directed alcohol seeking. Together, our data suggest that BDNF in a small ensemble of vlOFC-to-DLS neurons gates alcohol intake by attenuating habitual alcohol seeking.

Smooth pursuit eye movements contribute to long-latency reflex modulation in the lower extremity
Somatosensory mediated reactions play a fundamental role in adapting to environmental changes, particularly through long-latency responses (LLRs). We investigated how smooth pursuit eye movements (SPEM), which are slow eye movements used to track moving objects, influence LLRs of the upper and lower limb during mechanical interactions with moving objects. Seventeen participants stabilized their limb in anticipation of a collision with a virtual object approaching at 25 cm/s while standing. This task occurred while subjects either visually pursued the object or fixated a central location. Mechanical perturbations were applied at two time points: approximately 200ms and 60ms before the anticipated collision. On a random subset of trials, the robot applied a mechanical perturbation either 200ms (early) or 60ms (late) before the anticipated collision. As in previous studies LLRs were observed in leg muscles to upper limb displacement. Moreover, the leg LLRs were modulated by gaze, being larger during pursuit than fixation but only during late perturbations. This timing-specific modulation aligns with previous reports of policy transitions in feedback control roughly 60ms before impact. Upper limb LLRs were not impacted by gaze indicating a prioritization on postural control circuits. This work extends our understanding of the neural mechanisms underlying sensorimotor integration and highlights the sophisticated nature of the human motor control system in coordinating eye movements with whole-body postural responses.

A common neuronal basis for Pavlovian and instrumental learning in amygdala circuits
Reward-predictive Pavlovian cues can selectively invigorate instrumental behaviors. Accumulating evidence pinpoints the basolateral amygdala (BLA) as a key brain structure to assign outcome-specific motivational significance to Pavlovian cues or Instrumental actions. However, whether neuronal representations of Pavlovian and Instrumental learnings are processed in different BLA circuits and how the resulting memories interact is unknown. Here, we used calcium imaging and optogenetic manipulation of the BLA neurons in mice that acquired and expressed Pavlovian and Instrumental behaviors in a multi-phase behavioral task called specific Pavlovian to Instrumental Transfer (sPIT). We first confirmed that Pavlovian cues selectively invigorate instrumental actions and showed that this effect, referred as the sPIT effect, depends on BLA activity. Then, by tracking the activity of single BLA neurons across days, we found that BLA neurons integrate common reward-anticipation information relevant for Pavlovian and instrumental learning. Interestingly, this reward-anticipation information re-emerged during subsequent memory transfer and covaried with sPIT effect. These findings reveal that the BLA encodes an outcome-specific motivational state that generalizes across Pavlovian and instrumental behaviors to promote and guide reward-seeking behavior.

In vivo Quantification of White Matter Pathways in the Human Hippocampus
The hippocampus is a key structure in cognition. Although much research has focused on defining the functions of its anatomically distinct subfields, the communication among these subfields within the hippocampal circuit, supported by white matter pathways, is theoretically key to emergent cognitive function. Yet, hippocampal white matter connections in humans have not been fully explored in vivo. By leveraging diffusion weighted imaging and a large healthy sample (N=831), we developed a processing pipeline for in vivo quantification of human hippocampal pathways. We provided evidence for monosynaptic and trisynaptic pathway-related connections in humans, supporting the described hippocampal circuit in ex vivo and animal studies. In addition to hemispheric and sex differences, the individual variability in hippocampal pathways was linked to cognitive abilities. Thus, in vivo characterization of human hippocampal pathways highlights the individual differences within these structures and paves the way for their implications in cognition, aging, and diseases.

Conflict of interestThe authors declare no conflicts of interest.

Prolyl isomerase FKBP12 reduces axon growth and negatively regulates microtubule polymerization by inhibiting CRMP2A
Prolyl isomerases are enzymes catalyzing conformational change of the peptide bond between proline and the preceding amino acid, regulating the function and stability of their substrates. We have previously identified CRMP2A - the longer isoform of a microtubule-associated protein Collapsin response mediator protein 2 - as a substrate of the phospho-specific prolyl isomerase Pin1. CRMP2A is negatively regulated and destabilized by CDK5 phosphorylation in the distal axons and growth cones. Pin1 specifically binds to phosphorylated CRMP2A and stabilizes it by inducing conformational changes. However, the conformational regulation of unphosphorylated CRMP2 remains unknown. Here, we show that the prolyl isomerase FKBP12 specifically binds to unphosphorylated CRMP2A and regulates its activity. Using in vitro microtubule polymerization assays we demonstrate that CRMP2A promotes microtubule growth and that this function is inhibited by FKBP12. Next, using GFP-EB3 microtubule plus-end tracking assay, we demonstrate that FKBP12 inhibits CRMP2A-mediated microtubule polymerization also in cells. Furthermore, we show that FKBP12 co-localizes with unphosphorylated CRMP2A in growth cones and that expression of FKBP12 reduces axon growth in microfluidic chambers, while FKBP12 knockdown enhances it. Together, we demonstrate that FKBP12 is a negative regulator of microtubule dynamics and axon growth. Moreover, we show that two prolyl isomerases can differentially (positively or negatively) regulate activity of a common substrate depending on its phosphorylation. This provides an additional layer of phosphorylation-dependent or -independent control of protein activity, microtubule dynamics, and neuronal growth. Given the broad substrate specificity of FKBP12 and Pin1, this regulatory mechanism likely contributes to the modulation of diverse proteins and cellular processes in the nervous system and beyond.

Self-supervision deep learning models are better models of human high-level visual cortex: The roles of multi-modality and dataset training size
With the rapid development of Artificial Neural Network based visual models, many studies have shown that these models show unprecedented potence in predicting neural responses to images in visual cortex. Lately, advances in computer vision have introduced self-supervised models, where a model is trained using supervision from natural properties of the training set. This has led to examination of their neural prediction performance, which revealed better prediction of self-supervised than supervised models for models trained with language supervision or with image-only supervision. In this work, we delve deeper into the models ability to explain neural representations of object categories. We compare models that differed in their training objectives to examine where they diverge in their ability to predict fMRI and MEG recordings while participants are presented with images of different object categories. Results from both fMRI and MEG show that self-supervision was advantageous in comparison to classification training. In addition, language supervision is a better predictor for later stages of visual perception, while image-only supervision shows a consistent advantage over a longer duration, beginning from 80ms after exposure. Examination of the effect of data size training revealed that large dataset did not necessarily improve neural predictions, in particular in visual self-supervised models. Finally, examination of the correspondence of the hierarchy of each model to visual cortex showed that image-only self-supervision led to better correspondence than image only models. We conclude that while self-supervision shows consistently better prediction of fMRI and MEG recordings, each type of supervision reveals a different property of neural activity, with language-supervision explaining later onsets, while image-only self-supervision explains long and very early latencies of the neural response, with the model hierarchy naturally sharing corresponding hierarchical structure as the brain.

EEG-Informed fMRI Analysis Reveals Neurovascular Coupling in Motor Execution and Imagery
The complementary strengths of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) have driven extensive research into integrating these two noninvasive modalities to better understand the neural mechanisms underlying cognitive, sensory, and motor functions. However, the precise neural patterns associated with motor functions, especially imagined movements, remain unclear. Specifically, the correlations between electrophysiological responses and hemodynamic activations during executed and imagined movements have not been fully elucidated at a whole-brain level. In this study, we employed an EEG-informed fMRI approach on concurrent EEG-fMRI data to map hemodynamic changes associated with dynamic EEG temporal features during motor-related brain activities. We localized and differentiated the hemodynamic activations corresponding to continuous EEG temporal dynamics across multiple motor execution and imagery tasks. Validation against conventional block fMRI analysis demonstrated high precision in identifying regions specific to motor activities, underscoring the accuracy of the EEG-driven model. Beyond the expected sensorimotor activations, the integrated analysis revealed supplementary coactivated regions showing significant negative covariation between blood oxygenation level-dependent (BOLD) activities and sensorimotor EEG alpha power, including the cerebellum and insular cortex. These findings confirmed both the colocalization of EEG and fMRI activities in sensorimotor regions and a negative covariation between EEG alpha band power and BOLD changes. Moreover, the results provide novel insights into neurovascular coupling during motor execution and imagery on a brain-wide scale, advancing our understanding of the neural dynamics underlying motor functions.

HighlightsO_LIMovement-related EEG alpha activity negatively covaries with BOLD responses
C_LIO_LIEEG-informed fMRI maps the neurovascular correlates across the entire brain
C_LIO_LIA unified model disentangles multiple motor-related brain activations
C_LIO_LIEEG-informed fMRI results highly overlap with conventional block fMRI results
C_LI

Spinal Cord Ultrasound Stimulation Modulates Corticospinal Excitability
Background: Low-intensity focused ultrasound (LIFU) offers superior tissue penetration and enables precise neuromodulation of cortical and subcortical circuits. However, its effects on neural activity in the human spinal cord remain largely unexplored. Objective: To investigate the effects of LIFU on spinal cord neuromodulation under varying conditions of intensity (spatial-peak pulse-average intensity, ISPPA), duty cycle (DC), and pulse repetition frequency (PRF). Methods: Thirty-six healthy human volunteers participated in the study. A 500 kHz ultrasound transducer with a focal depth exceeding 100 mm was used to target the C8 spinal cord. Transcranial magnetic stimulation (TMS) was applied to the primary motor cortex (M1) hotspot corresponding to the first dorsal interosseous (FDI) muscle, innervated by the C8 nerve. A 500 ms-duration LIFU was delivered to the C8 spinal cord 400 ms prior to single-pulse TMS over the FDI hotspot. Spinal cord ultrasound stimulation (SCUS) was administered with varying acoustic parameters: intensities (ISPPA: 2.5 and 10 W/cm2), DCs (10% and 30%), and PRFs (500 and 1000 Hz). Changes in corticospinal excitability were assessed by comparing TMS-elicited motor-evoked potentials (MEPs) between active and sham SCUS conditions. Results: SCUS with an ISPPA of 10 W/cm2, a DC of 30%, and a PRF of 1000 Hz significantly reduced MEP amplitudes compared to sham stimulation. However, at the high intensity (ISPPA of 10 W/cm2), varying the DC between 10% and 30% did not affect MEP amplitudes. Additionally, while a PRF of 1000 Hz decreased MEP amplitudes at 10 W/cm2, a PRF of 500 Hz did not produce significant changes. Conclusions: The results indicate that ultrasound stimulation of the spinal cord can suppress corticospinal drive to muscles, especially when utilizing high intensity and high PRF parameters. This suggests that ultrasound stimulation may provide a novel method for modulating human spinal neural activity.

Integrating explicit reliability for optimal choices: effect of trustworthiness on decisions and metadecisions
In everyday life, decision-makers need to integrate information from various sources which differ in how reliable the correct information is provided. The present study addressed whether people can optimally use explicit information about the trustworthiness of the information source and whether people know how information sources affect their decisions. In each trial, we presented a sequence of six information sources which indicated a correct colour (red or blue) each with a different level of reliability. Each source was explicitly labelled the reliability percentage, i.e., the likelihood that a source provides correct information. Participants were asked to decide which colour was more likely to be correct. In the first series of three experiments, we found that participants failed to make use of explicit reliability cues optimally. In particular, participants were less able to use reliably wrong information sources (reliability below 50%) than reliably correct information sources (reliability above 50%), even though these two types of information sources were equally informative. In addition, participants failed to ignore the colour displayed by unreliable sources (50% reliability), although these sources gave just random information for a binary decision. In the second series of two experiments, we asked participants, after each choice, to report their subjective feelings of whether they followed or opposed a colour suggested by sources with a specific reliability percentage. We found that the ratings of the participants influence report tracked the amount of evidence which supported the choice they just made. Further, participants were able to introspect their own choice bias guided by unreliable information sources. These findings suggest that human choice behaviour deviates from Bayesian integration. However, people have a good metacognitive monitoring of how their decisions are driven by external stimuli.

Individualized Phenotyping of Functional ALS Pathology in Sensorimotor Cortex
Amyotrophic Lateral Sclerosis (ALS) is a progressive neurodegenerative disease characterized by the loss of motor neurons in primary motor cortex (MI), leading to muscle weakness, atrophy, and death within a median of three years. Even though ALS is characterized by different disease subtypes affecting different body parts, individiualized phenotyping of functional ALS pathology has so far not been achieved. We recorded 7 Tesla functional MRI (7T-fMRI) data while ALS patients and matched controls moved affected and non-affected body parts in the MR scanner. We applied robust Shared Response Modeling (rSRM) for capturing ALS-specific shared responses for group classification , and Partial Least Squares (PLS) regression for relating the latent variables to clinical subtypes and the degree of disease progression. We show that both functional connectivity and functional activation in MI are a predictor for disease onset site. However, disease severity could best be predicted by functional connectivity rather than pure activation changes. Critically, we show that functionally disease-defining information in MI is not strongest in the area that is behaviorally first-affected, deviating from the behavioral phenotype of the patients. When computing the model weight distribution of the King stage classification and projecting them back into voxel space, the highest mean weights are present in the foot and tongue/face regions that seem to drive disease progress. Our data highlight the importance of 7T-fMRI task-based functional connectivity measures for classifying ALS-patients, and provide evidence that a single 7T-MRI scan can be used for identifying a disease signature of each individual ALS patient.

Atlas of plasma metabolic markers linked to human brain morphology
Background: Metabolic processes form the basis of the development, functioning and maintenance of the brain. Despite accumulating evidence of the vital role of metabolism in brain health, no study to date has comprehensively investigated the link between circulating markers of metabolic activity and in vivo brain morphology in the general population. Methods: We performed uni- and multivariate regression on metabolomics and MRI data from 24,940 UK Biobank participants, to estimate the individual and combined associations of 249 circulating metabolic markers with 91 measures of global and regional cortical thickness, surface area and subcortical volume. We investigated similarity of the identified spatial patterns with brain maps of neurotransmitters, and used Mendelian randomization to uncover causal relationships between metabolites and the brain. Results: Intracranial volume and total surface area were highly significantly associated with circulating lipoproteins and glycoprotein acetyls, with correlations up to .15. There were strong regional associations of individual markers with mixed effect directions, with distinct patterns involving frontal and temporal cortical thickness, brainstem and ventricular volume. Mendelian randomization provided evidence of bidirectional causal effects, with the majority of markers affecting frontal and temporal regions. Discussion: The results indicate strong bidirectional causal relationships between circulating metabolic markers and distinct patterns of global and regional brain morphology. The generated atlas of associations provides a better understanding of the role of metabolic pathways in structural brain development and maintenance, in both health and disease.

Lower slow wave sleep and rapid eye-movement sleep are associated with brain atrophy of AD-vulnerable regions
Study objectives: Sleep deficiency is associated with Alzheimer's disease (AD) pathogenesis. We examined the association of sleep architecture with anatomical features observed in AD: (1) atrophy of hippocampus, entorhinal, inferior parietal, parahippocampal, precuneus, and cuneus regions (AD-vulnerable regions) and (2) cerebral microbleeds. Methods: In 271 participants of the Atherosclerosis Risk in the Communities Study, we examined the association of baseline sleep architecture with anatomical features identified on brain MRI 13~17 years later. Sleep architecture was quantified as the proportion of slow wave sleep (SWS), proportion of rapid eye-movement sleep (REM), and arousals index using polysomnography. Outcomes included (1) volumetric measurements of each AD-vulnerable region and (2) the presence of any cerebral microbleeds (CMBs) and that of lobar CMBs, which are more specifically associated with AD. We analyzed the association of each sleep predictor with each MRI outcome, adjusting for covariates. Results: Having less SWS was associated with smaller inferior parietal region (beta=-44.19 mm3 [95%CI=-76.63,-11.76]) and cuneus (beta=-11.99 mm3 [-20.93,-3.04]) after covariate adjustment. Having less REM was associated with smaller inferior parietal region (beta=-75.52 mm3 [-129.34, -21.70]) and precuneus (beta=-31.93 mm3 [-63.79,-0.07]). After FDR adjustments, lower SWS and REM, respectively, were associated with smaller inferior parietal region. Arousal index was not associated with the volumes of AD-vulnerable regions. None of the sleep architecture variables were associated with CMBs or lobar CMBs. Conclusions: Sleep deficiency is associated with the atrophy of the inferior parietal region, which is observed in early AD. Sleep architecture may be a modifiable risk factor for AD. Key words: sleep architecture, brain atrophy, inferior parietal region, Alzheimer's disease, cerebral microbleeds