bioRxiv Subject Collection: Neuroscience's Journal

Emergence of Sparse Coding, Balance and Decorrelation from a Biologically-Grounded Spiking Neural Network Model of Learning in the Primary Visual Cortex
Many computational studies attempt to address the question of information representation in biological neural networks using an explicit optimization based on an objective function. These approaches begin with principles of information representation that are expected to be found in the network and from which learning rules can be derived. This study approaches the question from the opposite direction; beginning with a model built upon the experimentally observed properties of neural responses, homeostasis, and synaptic plasticity. The known properties of information representation are then expected to emerge from this substrate. A spiking neural model of the primary visual cortex (V1) was investigated. Populations of both inhibitory and excitatory leaky integrate-and-fire neurons with recurrent connections were provided with spiking input from simulated ON and OFF neurons of the lateral geniculate nucleus. This network was provided with natural image stimuli as input. All synapses underwent learning using spike-timing-dependent plasticity learning rules. A homeostatic rule adjusted the weights and thresholds of each neuron based on target homeostatic spiking rates and mean synaptic input values. These experimentally grounded rules resulted in a number of the expected properties of information representation. The network showed a temporally sparse spike response to inputs and this was associated with a sparse code with Gabor-like receptive fields. The network was balanced at both slow and fast time scales; increased excitatory input was balanced by increased inhibition. This balance was associated with decorrelated firing that was observed as population sparseness. This population sparseness was both the cause and result of the decorrelation of receptive fields. These observed emergent properties (balance, temporal sparseness, population sparseness, and decorrelation) indicate that the network is implementing expected principles of information processing: efficient coding, information maximization ('infomax'), and a lateral or single-layer form of predictive coding. These emergent features of the network were shown to be robust to randomized jitter of the values of key simulation parameters.

Accelerated amyloid deposition in SARS-CoV-2 infected mouse models of Alzheimer's disease
Familial Alzheimers disease (AD) involving known AD causing genes accounts for a small fraction of cases, the vast majority are sporadic. Neuroinflammation, secondary to viral infection, has been suggested as an initiating or accelerating factor. In this work we tested the hypothesis that SARS-CoV-2 (SCV2) viral infection accelerates the development of AD pathology in mouse models of AD. We profiled transcriptomic changes using transgenic APP/PSEN1 and P301S mouse models that develop AD pathology and k18hACE2 mice that express the humanized ACE2 receptor used by SCV2 to enter cells. This study identified the interferon and chemokine responses constituting key shared pathways between SCV2 infection and the development of AD pathology. Two transgenic mouse models of AD: APP/PSEN1 (develops amyloid pathology) and 3xTg AD (develops both amyloid and tau pathology) were crossed with k18-hACE2 mice to generate hybrid hACE2-3xTg and hACE2-APP/PSEN1 mice. Neuroinflammation and amyloid deposition in the brain of infected mice were imaged in vivo using molecular MRI (mMRI) probes and confirmed postmortem by histopathology. Results show that 11-14-month-old SCV2 infected hACE2-3xTg mice exhibit neuroinflammation 10 days post infection and 4-5-month-old hACE2-APP/PS1 hybrid mice develop amyloid deposits, while age-matched uninfected mice exhibit neither phenotype. This suggests that SCV2 infection could induce or accelerate AD when risk factors are present.

Comparable neural and behavioural performance in dominant and non-dominant hands during grasping tasks
Hand dominance has long been associated with differences in neural control and motor performance, with the dominant hand typically exhibiting better coordination in reaching tasks. However, the extent to which this dominance influences performance in finger force control remains unclear. This study aimed to examine the behavioural and neural features of the dominant and non dominant hands during grasping and lifting tasks in healthy young adults, focusing on the synergy index, EEG band power, and EEG EMG coherence as key measures. Twenty right handed adults (mean age = 26.95, STD = 2.68) participated in this study. Participants engaged in an experimental task where they grasped a handle for the initial five seconds, followed by lifting and holding it for an additional five seconds. There were two task conditions: fixed (thumb platform secured) and free (thumb platform movable). They performed 25 trials with both the dominant and non-dominant hands in the two task conditions, with the order of trials and hands block randomized to eliminate potential order effects. Contrary to the dynamic dominance hypothesis, we found statistical equivalence in the synergy index, EEG band power, and EEG EMG coherence between the dominant and non-dominant hands across both fixed and free task conditions. These findings suggest that both hands are capable of achieving similar levels of performance in tasks emphasizing steady state force maintenance, despite the typical advantages of the dominant hand in other motor tasks. While task-dependent modulations in behavioural and neural features were observed due to changes in friction, these adjustments were non different between the dominant and non dominant hands.

A decision-theoretic model of multistability: perceptual switches as internal actions
Perceptual multistability has been studied for centuries using a diverse collection of approaches. Insights derived from this phenomenon range from core principles of information processing, such as perceptual inference, to high-level concerns, such as visual awareness. The dominant computational explanations of perceptual multistability are based on the Helmholtzian view of perception as inverse inference. However, these approaches struggle to account for the crucial role played by value, e.g., with percepts paired with reward dominating for longer periods than unpaired ones. In this study, we formulate perceptual multistability in terms of dynamic, value-based, choice, employing the formalism of a partially observable Markov decision process (POMDP). We use binocular rivalry as an example, considering different explicit and implicit sources of reward (and punishment) for each percept. The resulting values are time-dependent and influenced by novelty as a form of exploration. The solution of the POMDP is the optimal perceptual policy, and we show that this can replicate and explain several characteristics of binocular rivalry, ranging from classic hallmarks such as apparently spontaneous random switches with approximately gamma-distributed dominance periods to more subtle aspects such as the rich temporal dynamics of perceptual switching rates. Overall, our decision-theoretic perspective on perceptual multistability not only accounts for a wealth of unexplained data, but also opens up modern conceptions of internal reinforcement learning in service of understanding perceptual phenomena, and sensory processing more generally.

SegCSR: Weakly-Supervised Cortical Surfaces Reconstruction from Brain Ribbon Segmentations
Deep learning-based cortical surface reconstruction (CSR) methods heavily rely on pseudo ground truth (pGT) generated by conventional CSR pipelines as supervision, leading to dataset-specific challenges and lengthy training data preparation. We propose a new approach for reconstructing multiple cortical surfaces using weak supervision from brain MRI ribbon segmentations. Our approach initializes a midthickness surface and then deforms it inward and outward to form the inner (white matter) and outer (pial) cortical surfaces, respectively, by jointly learning diffeomorphic flows to align the surfaces with the boundaries of the cortical ribbon segmentation maps. Specifically, a boundary surface loss drives the initialization surface to the target inner and outer boundaries, and an inter-surface normal consistency loss regularizes the pial surface in challenging deep cortical sulci. Additional regularization terms are utilized to enforce surface smoothness and topology. Evaluated on two large-scale brain MRI datasets, our weakly-supervised method achieves comparable or superior CSR accuracy and regularity to existing supervised deep learning alternatives.

Relaxation selective Intravoxel Incoherent Motion Imaging of Microvascular Perfusion and Fluid Compartments in the Human Choroid Plexus
The choroid plexus (ChP) plays an important role in the glymphatic system of the human brain as the primary source of the cerebrospinal fluid (CSF) production. Development of a non-invasive imaging technique is crucial for studying its function and age-related neurofluid dynamics. This study developed a relaxation-selective intravoxel incoherent motion (IVIM) technique to assess tissue and fluid compartments in the ChP in a prospective cross-sectional study involving 83 middle-aged to elderly participants (age: 61.5 {+/-} 17.1 years old) and 15 young controls (age: 30.7 {+/-} 2.9 years old). Using a 3T MRI scanner, IVIM, FLAIR-IVIM, LongTE-IVIM, and VASO-LongTE-IVIM were employed to measure diffusivity and volume fractions of fluid compartments and evaluate aging effects on microvascular perfusion and interstitial fluid (ISF). FLAIR-IVIM identified an additional ISF compartment with free-water-like diffusivity (2.4 {+/-} 0.9 x10-3 mm2/s). Older adults exhibited increased ChP volume (2320 {+/-} 812 mm3 vs 1470 {+/-} 403 mm3, p=0.0017), reduced perfusion (6.5 {+/-} 4.7 vs 3.6 {+/-} 2.9 x10-3 mm{superscript 2}/s, p=0.0088), decreased ISF volume fraction (0.58 {+/-} 0.09 vs 0.67 {+/-} 0.06, p=0.0042), and lower tissue diffusivity (1.16 {+/-} 0.14 vs 1.29 {+/-} 0.17 x10-3 mm{superscript 2}/s, p=0.031) compared to younger adults. Relaxation-selective IVIM may offers enhanced specificity for characterizing age-related changes in ChP structure and fluid dynamics.

Anti-obesity compounds, Semaglutide and LiPR, do not change the proportion of human and mouse POMC+ neurons
Anti-obesity medications (AOMs) have become one of the most prescribed drugs in human medicine. While AOMs are known to impact adult neurogenesis in the hypothalamus, their effects on the functional maturation of hypothalamic neurons remain unexplored. Given that AOMs target neurons in the Medial Basal Hypothalamus (MBH), which play a crucial role in regulating energy homeostasis, we hypothesized that AOMs might influence the functional maturation of these neurons, potentially rewiring the MBH. To investigate this, we exposed hypothalamic neurons derived from human induced pluripotent stem cells (hiPSCs) to Semaglutide and lipidized prolactin-releasing peptide (LiPR), two anti-obesity compounds. Contrary to our expectations, treatment with Semaglutide or LiPR during neuronal maturation did not affect the proportion of anorexigenic, Pro-opiomelanocortin-expressing (POMC+) neurons. Additionally, LiPR did not alter the morphology of POMC+ neurons or the expression of selected genes critical for the metabolism or development of anorexigenic neurons. Furthermore, LiPR did not impact the proportion of adult-generated POMC+ neurons in the mouse MBH. Taken together, these results suggest that AOMs do not influence the functional maturation of anorexigenic hypothalamic neurons.

Collablots: Quantification of collagen VI levels and its structural disorganisation in cell cultures from patients with collagen VI-related dystrophies
AimsThis study aims to develop a quantitative method for assessing collagen VI expression in cell cultures, which is crucial for the diagnosis and treatment of collagen VI-related dystrophies.

MethodsWe developed a combined in-cell western (ICW) and on-cell western (OCW) assay, that we have called collablot to quantify collagen VI and its organisation in the extracellular matrix of cell cultures from patients and healthy controls. To optimise it, we optimised cell density and the protocols to induce collagen expression in cultures, as well as the cell fixation and permeabilisation methods. This was completed with a thorough selection of collagen antibodies and a collagen hybridising peptide (CHP). We then used collablots to compare cultures from patients and controls and evaluate therapeutic interventions in the cultures.

ResultsCollablots enabled the quantification of collagen VI expression in both control and patient cells, aligning with immunocytochemistry findings and detecting variations in collagen VI expression following treatment of the cultures. Additionally, CHP analysis revealed a marked increase in collagen network disruption in patients compared to the controls.

ConclusionsThe collablot assay represents an optimal method for quantifying collagen VI expression and its organisation in culture and assessing the effect of therapies.

Key Points- Evaluating therapies for collagen VI-related dystrophies (COL6-RD) requires the quantification of collagen VI levels.
- Collablot assays are a novel method for quantifying collagen VI expression and its structural organisation in cell culture.
- Due to the significant role of phenotype heterogeneity in this complex disease, quantifying collagen alone might not be adequate for diagnosing COL6-RD, but the addition of a peptide to quantify collagen disorganisation could help in the characterisation of patient cultures.

The effect of speech masking on the human subcortical response to continuous speech
Auditory masking--the interference of the encoding and processing of an acoustic stimulus imposed by one or more competing stimuli--is nearly omnipresent in daily life, and presents a critical barrier to many listeners, including people with hearing loss, users of hearing aids and cochlear implants, and people with auditory processing disorders. The perceptual aspects of masking have been actively studied for several decades, and particular emphasis has been placed on masking of speech by other speech sounds. The neural effects of such masking, especially at the subcortical level, have been much less studied, in large part due to the technical limitations of making such measurements. Recent work has allowed estimation of the auditory brainstem response (ABR), whose characteristic waves are linked to specific subcortical areas, to naturalistic speech. In this study, we used those techniques to measure the encoding of speech stimuli that were masked by one or more simultaneous other speech stimuli. We presented listeners with simultaneous speech from one, two, three, or five simultaneous talkers, corresponding to a range of signal-to-noise ratios (SNR; Clean, 0, -3, and -6 dB), and derived the ABR to each talker in the mixture. Each talker in a mixture was treated in turn as a target sound masked by other talkers, making the response quicker to acquire. We found consistently across listeners that ABR wave V amplitudes decreased and latencies increased as the number of competing talkers increased.

Comparison of Transcriptional Activation by Corticosteroids of Human MR (Ile-180) and Human MR Haplotype (Ile180Val)
While the classical function of human mineralocorticoid receptor (MR) is to regulate sodium and potassium homeostasis through aldosterone activation of the kidney MR, the MR also is highly expressed in the brain, where the MR is activated by cortisol in response to stress. Here, we report the half-maximal response (EC50) and fold-activation by cortisol, aldosterone and other corticosteroids of human MR rs5522, a haplotype containing valine at codon 180 instead of isoleucine found in the wild-type MR (Ile-180). MR rs5522 (Val-180) has been studied for its actions in the human brain involving coping with stress and depression. We compared the EC50 and fold-activation by corticosteroids of MR rs5522 and wild-type MR transfected into HEK293 cells with either the TAT3 promoter or the MMTV promoter. Parallel studies investigated the binding of MR antagonists, spironolactone and progesterone, to MR rs5522. In HEK293 cells with the MMTV promotor, MR rs5522 had a slightly higher EC50 compared to wild-type MR and a similar level of fold-activation for all corticosteroids. In contrast, in HEK293 cells with the TAT3 promoter, MR 5522 had a higher EC50 (lower affinity) and higher fold-activation for cortisol compared to wild-type MR (Ile-180), while compared to wild-type MR, the EC50s of MR rs5522 for aldosterone and corticosterone were slightly lower and fold-activation was higher. Spironolactone and progesterone had similar antagonist activity for MR rs5522 and MR (Ile-180) in the presence of MMTV and TAT3 promoters in HEK293 cells.

Deep predictive coding networks partly capture neural signatures of short-term temporal adaptation in human visual cortex
Predictive coding is a leading theory of cortical function which posits that the brain continually makes predictions of incoming sensory stimuli using a hierarchical network of top-down and bottom-up connections. This theory is supported by prior work showing that PredNet, a deep learning network designed according to predictive coding principles, exhibits several characteristics of neural responses commonly observed in primate visual cortex. However, one ubiquitous neural phenomenon that has not yet been investigated is short-term visual adaptation: the adjustment of neural responses over time when exposed to static visual inputs that are either prolonged or directly repeated. Here, we examine whether PredNet exhibits two neural signatures of temporal adaptation previously observed in intracranial recordings of human participants viewing prolonged and repeated stimuli (Brands et al., 2024). We find that, like human visual cortex, PredNet adapts to static images, evidenced by subadditive temporal response summation: a non-linear accumulation of response magnitudes when prolonging stimulus durations, which results from neurally plausible transient-sustained dynamics in the unit activation time courses. However, PredNet activations also show a systematic response to stimulus offsets, which is absent in the human neural data. For repeated stimuli, PredNet shows slight response suppression for any two images presented in quick succession, but no repetition suppression, a comparatively stronger response reduction for identical than for non-identical image pairs that is robustly observed throughout human visual cortex. We show that these results are stable across multiple training datasets and two different types of loss computation. Lastly, in both PredNet and the neural data, we find a relationship between temporal adaptation and visual input properties, showing that temporally sustained activity is enhanced for more complex scenes containing clutter. All together, these results suggest that the emergent temporal dynamics in the PredNet only partly align with neural data and are linked to low-level properties of the visual input rather than high-level predictions arising from top-down processes.

Storage and transport of labile iron is mediated by lysosomes in axons and dendrites of hippocampal neurons
Iron dyshomeostasis in neurons, involving iron accumulation and abnormal redox balance, is implicated in neurodegeneration. In particular, labile iron, a highly reactive pool of intracellular iron, plays a prominent role in iron-induced neurological damage. However, the mechanisms governing the detoxification and transport of labile iron within neurons are not fully understood. This study investigates the storage and transport of labile ferrous iron Fe(II) in cultured primary rat hippocampal neurons. Iron distribution was studied using live cell confocal microscopy with a selective labile Fe(II) fluorescent dye, and synchrotron X-ray fluorescence microscopy (SXRF) for total iron distribution. Fluorescent labelling of the axon initial segment and of lysosomes allowed iron distribution to be correlated with these subcellular compartments. The results show that labile Fe(II) is stored in lysosomes within somas, axons and dendrites and that lysosomal labile Fe(II) is transported retrogradely and anterogradely along axons and dendrites. In addition, we have developed a methodological workflow to quantify labile Fe(II) relative to total iron in neurites. This method is based on correlative imaging of fluorescence microscopy of labile Fe(II) combined with quantitative elemental mapping of total iron by SXRF. Quantitative analysis revealed that after Fe(II) exposure, lysosomal Fe(II) accounts for a small but significant percentage of the total iron content in neurites. These result suggest that after exposure to labile Fe(II), iron is mainly present in a non-reactive form in neurons, while the smaller fraction of reactive labile Fe(II) is stored in lysosomes and can be transported along dendrites and axons.

The Functional Connectome Mediating Circadian Synchrony in the Suprachiasmatic Nucleus
Circadian rhythms in mammals arise from the spatiotemporal synchronization of [~]20,000 neuronal clocks in the Suprachiasmatic Nucleus (SCN). While anatomical, molecular, and genetic approaches have revealed diverse cell types and signaling mechanisms, the network wiring that enables SCN cells to communicate and synchronize remains unclear. To overcome the challenges of revealing functional connectivity from fixed tissue, we developed MITE (Mutual Information & Transfer Entropy), an information theory approach that infers directed cell-cell connections with high fidelity. By analyzing 3447 hours of continuously recorded clock gene expression from 9011 cells in 17 mice, we found that the functional connectome of SCN was highly conserved bilaterally and across mice, sparse, and organized into a dorsomedial and a ventrolateral module. While most connections were local, we discovered long-range connections from ventral cells to cells in both the ventral and dorsal SCN. Based on their functional connectivity, SCN cells can be characterized as circadian signal generators, broadcasters, sinks, or bridges. For example, a subset of VIP neurons acts as hubs that generate circadian signals critical to synchronize daily rhythms across the SCN neural network. Simulations of the experimentally inferred SCN networks recapitulated the stereotypical dorsal-to-ventral wave of daily PER2 expression and ability to spontaneously synchronize, revealing that SCN emergent dynamics are sculpted by cell-cell connectivity. We conclude that MITE provides a powerful method to infer functional connectomes, and that the conserved architecture of cell-cell connections mediates circadian synchrony across space and time in the mammalian SCN.

HighlightsWe developed MITE, an information theory method, to accurately infer directed functional connectivity among circadian cells.

SCN cell types with conserved connectivity patterns spatially organize into two regions and function as generators, broadcasters, sinks, or bridges of circadian information.

One-third of VIP neurons serve as hubs that drive circadian synchrony across the SCN.

Key connectivity features mediate the generation and maintenance of intercellular synchrony and daily waves of clock gene expression across the SCN.

LC3-associated endocytosis facilitates extracellular Tau aggregate internalization and degradation in microglia
BackgroundMicroglia, which are resident phagocytic cells in the brain, are involved in the active clearance of microbes, misfolded proteins, and cell debris, among others. In Alzheimers disease, microglia play a pivotal role in clearing extracellular amyloid-{beta} (A{beta}) plaques and intracellular Tau aggregates from the brain. Microglial cells have several mechanisms for Tau internalization, including macropinocytosis, heparan sulfate proteoglycans (HSPGs), dynamin- dependent endocytosis, and receptor-mediated endocytosis. Internalized Tau seeds either undergo proteasomal or lysosomal degradation or are exocytosed into the extracellular space via exosomes. Microtubule-associated protein 1 light chain 3 (LC3)-associated endocytosis (LANDO) is a recently discovered microglial mechanism for an effective clearance of A{beta} aggregates and alleviates neurodegeneration in murine Alzheimers disease. Several microglial receptors are reported to be involved in misfolded A{beta} and Tau aggregate internalization such as triggering receptor expressed on myeloid cell 2 (TREM-2), P2Y purinoceptor 12 (P2Y12R), C- X3-C motif chemokine receptor 1 (CX3CR1), etc.

MethodsIn this study, we report the LANDO of Tau monomers and aggregates by murine microglial cells, which are further degraded by lysosomal fusion. LANDO of extracellular Tau is demonstrated by several biochemical and cell-biology studies including western blotting, fluorescence and confocal imaging of microglial cells.

ResultsWe analyzed microglial activation by measuring the upregulation of Ionized Calcium- binding Adapter Molecule 1 (Iba-1) expression. Later, we demonstrated the LANDO of human full-length Tau species, where LC3 colocalizes with internalized Tau, followed by lysosomal degradation by microglia. The accumulation of internalized Tau in the perinuclear region of the cell in the presence of chloroquine supports phagolysosomal fusion and degradation.

ConclusionHence, we concluded that microglia internalize extracellular Tau species via LANDO, which further undergoes degradation via the lysosomal pathway.

Single-nucleus RNA sequencing of human periventricular white matter in vascular dementia
Vascular dementia (VaD) refers to a variety of dementias driven by cerebrovascular disease and is the second leading cause of dementia globally. VaD may be caused by ischemic strokes, intracerebral hemorrhage, and/or cerebral small vessel disease, commonly identified as white matter hyperintensities on MRI. The mechanisms underlying these white matter lesions in the periventricular brain are poorly understood. In this study we perform an extensive transcriptomic analysis on human postmortem periventricular white matter lesions in patients with VaD with the goal of identifying molecular pathways in the disease. We find increased cellular stress responses in astrocytes, oligodendrocytes, and oligodendrocyte precursor cells as well as transcriptional and translational repression in microglia in our dataset. We show that several genes identified by GWAS as being associated with white matter disease are differentially expressed in cells in VaD. Finally, we compare our dataset to an independent snRNAseq dataset of PVWM in VaD and a scRNAseq dataset on human iPSC-derived microglia exposed to oxygen glucose deprivation (OGD). We identify the increase of the heat shock protein response as a conserved feature of VaD across celltypes and show that this increase is not linked to OGD exposure. Overall, our study is the first to show that increased heat shock protein responses are a common feature of lesioned PVWM in VaD and may represent a potential therapeutic target.

Complex opioid driven modulation of glutamatergic and cholinergic neurotransmission in a GABAergic brain nucleus associated with emotion, reward and addiction.
The medial habenula (mHb)/interpeduncular nucleus (IPN) circuitry is resident to divergent molecular, neurochemical and cellular components which, in concert, perform computations to drive emotion, reward and addiction behaviors. Although housing one of the most prominent mu opioid receptor (mOR) expression levels in the brain, remarkably little is known as to how they impact mHb/IPN circuit function at the granular level. In this study, our systematic functional and pharmacogenetic analyses demonstrate that mOR activation attenuates glutamatergic signaling whilst producing an opposing potentiation of glutamatergic/cholinergic co-transmission mediated by mHb substance P and cholinergic neurons, respectively. Intriguingly, this latter non-canonical augmentation is developmentally regulated only emerging during later postnatal stages. Further, specific potassium channels act as a molecular brake on nicotinic receptor signaling in the IPN with the opioid mediated potentiation of this arm of neurotransmission being operational only following attenuation of Kv1 function. Thus, mORs play a remarkably complex role in modulating the salience of distinct afferent inputs and transmitter modalities that ultimately influences synaptic recruitment of common downstream GABAergic IPN neurons. Together, these observations provide a framework for future investigations aimed at identifying the neural underpinnings of maladaptive behaviors that can emerge when endogenous or exogenous opioids, including potent synthetic analogs such as fentanyl, modulate or hijack this circuitry during the vulnerable stages of adolescence and in adulthood.

Neural mechanisms underlying the effects of cognitive fatigue on physical effort-based decision-making
Fatigue is a state of exhaustion that influences our willingness to engage in effortful tasks. While both physical and cognitive exertion can cause fatigue, there is a limited understanding of how fatigue in one exertion domain (e.g., cognitive) affects decisions to exert in another (e.g., physical). We use functional magnetic resonance imaging (fMRI) to measure brain activity while human participants make decisions to exert prospective physical effort before and after engaging in a cognitively fatiguing working memory task. Using computational modeling of choice behavior, we show that fatiguing cognitive exertion increases participants subjective costs of physical effort compared to a baseline rested state. We describe how signals related to fatiguing cognitive exertion in the dorsolateral prefrontal cortex influence physical effort value computations instantiated by the insula, thereby increasing an individuals subjective valuation of prospective physical effort while cognitively fatigued. Our results support the idea of a general fatigue signal that integrates exertion-specific information to guide effort-based choice.

Default mode and motor networks facilitate early learning of implicit motor sequences: a multimodal MR spectroscopy and fMRI study
Learning new motor skills is a fundamental process that involves the sequencing of actions. Skill develops with practice and time, and manifests as performance that is fast and accurate. Although we know that learning can occur through an implicit process in the absence of conscious awareness, and across multiple temporal scales, the precise neural mechanisms mediating implicit motor sequence learning remain poorly understood. Similarly, the capacity for interventions with known influence on learning and memory, such as cardiovascular exercise, to facilitate implicit learning is yet to be clearly established. Here, we investigated the neuroplasticity of implicit motor sequence learning and the effect of acute exercise priming. Healthy adults (39.5% female) aged 22.55 {+/-} 2.69 years were allocated to either a high-intensity exercise (HIIT) group (n = 16) or to a very low-intensity control group (n = 17). Following exercise, participants performed a serial reaction time task. MR spectroscopy estimates of sensorimotor gamma-aminobutyric acid (GABA) were acquired before and after exercise, and during task performance, and resting-state fMRI was acquired at the end of the protocol. We show that early stages of learning are linked to default mode network connectivity, while the overall degree of learning following sustained practice is associated with motor network connectivity. Sensorimotor GABA concentration was linked to the early stages of learning, and GABA concentration was modulated following HIIT, although the two were not related. Overall, via integration of multiple neuroimaging modalities we demonstrate that interactions between hippocampal and motor networks underlie implicit motor sequence learning.

Key points summary- Motor learning occurs across different temporal scales and can arise implicitly in the absence of conscious awareness.
- Explicit motor learning is linked to the brains primary inhibitory neurotransmitter, GABA, and interactions across motor and hippocampal networks.
- Whether these same neural mechanisms are implicated in implicit learning is unclear. Similarly, the capacity to influence learning via priming with cardiovascular exercise is yet to be clearly established.
- We show that early implicit learning is underpinned by default mode network connectivity and sensorimotor GABA concentration, while total learning following sustained practice is linked to motor network connectivity. We also found that HIIT exercise elevated sensorimotor GABA concentration, but not the magnitude of implicit learning.
- Overall, our results highlight shared involvement of default mode and motor networks in implicit motor sequence learning.

Muscle length modulates recurrent inhibition and post-activation depression differently according to contraction type
It is well documented that, in soleus, motoneuron output and the effectiveness of activated Ia afferents to discharge -motoneurons both decrease during eccentric contractions. Evidence suggests that these regulations can be explained by (1) recurrent inhibition and (2) greater post-activation depression by primary afferent depolarization. However, the influence of muscle length on the regulation of the effectiveness of Ia afferents to discharge -motoneurons observed during eccentric contractions remains unclear. We conducted a study on 16 healthy young individuals. We used simple and conditioned Hoffmann reflex with different conditioning techniques such as paired H reflex, D1 method and heteronymous Ia facilitation coupled with electromyography during eccentric, isometric and concentric contractions at long, intermediate and short soleus muscle lengths. Our results confirm that during eccentric contraction the effectiveness of Ia afferents to discharge U-motoneurons decreases only at intermediate and short muscle lengths but is similar between all contraction types at long muscle length. Findings are similar for recurrent inhibition. Post-activation depression is significantly more pronounced during eccentric contractions compared with isometric and concentric contractions at long muscle length. Our analysis also shows that recurrent inhibition and post-activation depression are greater at long muscle length compared with short muscle length, whatever the contraction type. These new findings demonstrate an important influence of muscle length on the activity of spinal regulatory mechanisms and the effectiveness of activated Ia afferents to discharge -motoneurons during eccentric contractions.

Reduced and Redundant: Information Processing of Prediction Errors during Sleep
During sleep, the human brain transitions to a sentinel processing mode, enabling the continued processing of environmental stimuli despite the absence of consciousness. Going beyond prior research, we employed advanced information-theoretic analyses, including mutual information (MI) and co-information (co-I), alongside event-related potential (ERP) and temporal generalization analyses (TGA), to characterize auditory prediction error processing across wakefulness and sleep. We hypothesized that a shared neural code would be present across sleep stages, with deeper sleep being associated with reduced information content and increased information redundancy.

To investigate this, twenty-nine young healthy participants were exposed to an auditory local-global oddball paradigm during wakefulness and continued during an 8-hour sleep opportunity monitored via polysomnography. We focused on local mismatch responses to a deviating fifth tone following four standard tones.

ERP analyses showed that prediction error processing continued throughout all sleep stages (N1-N3, REM). Mutual information analyses revealed a substantial reduction in the amount of encoded prediction error information during sleep, although ERP amplitudes increased with deeper NREM sleep. In addition, co-information analyses showed that neural dynamics became increasingly redundant with increasing sleep depth. Temporal generalisation analyses revealed a largely shared neural code between N2 and N3 sleep, although it differed between wakefulness and sleep.

Here, we showed how the neural code of the sentinel processing mode changes from wake to light to deep sleep and REM, characterised by more redundant and less rich neural information in the human cortex as consciousness wanes. This altered stimulus processing reveals how neural information changes with the changes of consciousness states as we traverse the night.

Cell types associated with human brain functional connectomes and their implications in psychiatric diseases
Cell types are fundamental to the functional organization of the human brain, yet the specific cell clusters contributing to functional connectomes remain unclear. Using human whole-brain single-cell RNA sequencing data, we investigated the relationship between cortical cell cluster distribution and functional connectomes. Our analysis identified dozens of cell clusters significantly associated with resting-state network connectivity, with excitatory neurons predominantly driving positive correlations and inhibitory neurons driving negative correlations. Many of these cell clusters are also conserved in macaques. Notably, functional network connectivity is predicted by cellular communication among these clusters. We further identified cell clusters linked to various neuropsychiatric disorders, with several clusters implicated in multiple conditions. Comparative analysis of schizophrenia and autism spectrum disorder revealed distinct expression patterns, highlighting disease-specific cellular mechanisms. These findings underscore the critical role of specific cell clusters in shaping functional connectomes and their implications for neuropsychiatric diseases.

The intersection of inflammation and DNA damage as a novel axis underlying the pathogenesis of autism spectrum disorders
Autism spectrum disorders (ASD) affects 1 in 36 children and is characterized by repetitive behaviors and difficulties in social interactions and social communication. The etiology of ASD is extremely heterogeneous, with a large number of ASD cases that are of unknown or complex etiology, which suggests the potential contribution of epigenetic risk factors. In particular, epidemiological and animal model studies suggest that inflammation during pregnancy could lead to an increased risk of ASD in the offspring. However, the molecular mechanisms that contribute to ASD pathogenesis in relation to maternal inflammation during pregnancy in humans are underexplored. Several pro-inflammatory cytokines have been associated with increased autistic-like behaviors in animal models of maternal immune activation, including IL-17A. Using a combination of ASD patient lymphocytes and stem cell-derived human neurons exposed to IL-17A we discovered a shared molecular signature that highlights a metabolic and translational node that could lead to altered neuronal excitability. Further, our work on human neurons brings forward the possibility that defects in the DNA damage response could be underlying the effect of IL-17A on human excitatory neurons, linking exacerbated unrepaired DNA damage to the pathogenicity of maternal inflammation in connection to ASD.

ATF5-Dependent GDF15 Expression Mediates Anesthesia-Induced Neuroprotection Against Stroke
The incidence of perioperative stroke, a rare but severe complication, is increasing in aging populations. Although anesthetics such as sevoflurane may provide protective preconditioning against ischemic injury, clinical outcomes have been inconsistent. In this study, we demonstrated that sevoflurane-induced neuroprotection is associated with the upregulation of genes involved in the mitochondrial unfolded protein response (UPRmt) and mitochondrial bioenergetic metabolism. Our findings emphasize the critical role of ATF5, a key transcription factor, in mediating these protective effects. Specifically, we observed that sevoflurane preconditioning significantly upregulates ATF5 and its downstream target GDF15 - a regulator of mitochondrial function - in the cerebral cortex. Notably, we found that this mechanistic pathway was not activated in the brain of aged mice, suggesting that age-specific strategies may be necessary for reducing the risk of perioperative stroke. Considering the steadily increasing age of patients, therapeutic approaches that enhance mitochondrial function in the aged brain may provide additional protection against perioperative stroke.

Microglia from patients with multiple sclerosis display a cell-autonomous immune activation state
Aberrant and sustained activation of microglia is implicated in the progression and severity of multiple sclerosis (MS). However, whether intrinsic alterations in microglial function impact the pathogenesis of this disease remains unclear. We conducted transcriptomic and functional analyses of microglia-like cells (iMGLs) differentiated from induced pluripotent stem cells (iPSCs) from patients with MS (pwMS) to answer this question. We generated iPSCs from six pwMS showing increased microglial activity via translocator protein (TSPO)-PET imaging. We demonstrated that the differentiated iMGL transcriptional profile resembled the microglial signature found in MS lesions. Importantly, compared with healthy controls, MS iMGLs presented cell-autonomous differences in their regulation of inflammation, both in the basal state and following inflammatory lipopolysaccharide challenge. Through transcriptomic profiling, we showed that MS iMGLs display increased expression of genes known to be upregulated in MS microglia. Furthermore, upregulated genes in MS iMGLs were associated with immune receptor activation, antigen presentation, and the complement system, with known MS implications. Finally, functional analyses indicated that the transcriptional changes in MS iMGLs corresponded with alterations in the secretion of inflammatory cytokines and chemokines and increased phagocytosis. Together, our results provide evidence of putative cell-autonomous microglial activation in pwMS and identify transcriptomic and functional changes that recapitulate the phenotypes observed in vivo in microglia from pwMS. These findings indicate that MS disease-specific iPSCs are valuable tools for studying disease-specific microglial activation in vitro and highlight microglia as potential therapeutic targets in MS.

Stimulus-repetition effects on macaque V1 and V4 microcircuits explain gamma-synchronization increase
Under natural conditions, animals repeatedly encounter the same visual scenes, objects or patterns repeatedly. These repetitions constitute statistical regularities, which the brain captures in an internal model through learning. A signature of such learning in primate visual areas V1 and V4 is the gradual strengthening of gamma synchronization. We used a V1-V4 Dynamic Causal Model (DCM) to explain visually induced responses in early and late epochs from a sequence of several hundred grating presentations. The DCM reproduced the empirical increase in local and inter-areal gamma synchronization, revealing specific intrinsic connectivity effects that could explain the phenomenon. In a sensitivity analysis, the isolated modulation of several connection strengths induced increased gamma. Comparison of alternative models showed that empirical gamma increases are better explained by (1) repetition effects in both V1 and V4 intrinsic connectivity (alone or together with extrinsic) than in extrinsic connectivity alone, and (2) repetition effects on V1 and V4 population input rather than output gain. The best input gain model included effects in V1 granular and superficial excitatory populations and in V4 granular and deep excitatory populations. Our findings are consistent with gamma reflecting bottom-up signal precision, which increases with repetition and, therefore, with predictability and learning.