Progress in Neurobiology

Intrinsic neural timescale (INT) quantifies the persistence of spontaneous neural dynamics and offers a principled metric for characterizing brain-wide temporal organization. Although a hierarchy of INTs has been established during rest, how task engagement reconfigures this organization and how it is constrained by the structural connectome (SC) remain poorly understood. Here, we systematically mapped whole-brain INT using high-resolution fMRI data from the Human Connectome Project during rest and seven tasks spanning working memory, gambling, motor, language, social, relational, and emotion domains. Task engagement induced robust, regionally heterogeneous changes in INT while largely preserving the brain-wide temporal hierarchy across cognitive states. SC-INT coupling remained strong but consistently decreased during tasks, indicating that anatomical architecture continues to constrain INT, although its influence is attenuated under task demands. To investigate these findings mechanistically, we employed a multiscale, whole-brain neuronal-network model, which revealed that INT increase and peak within a broad critical-like regime. Strong SC-INT coupling, as observed empirically, emerged in the subcritical regime, weakened progressively with increasing network excitability, and reversed in the supercritical regime. These results demonstrate that task engagement reconfigures INTs while maintaining their hierarchical organization, suggesting that both resting and task states operate largely within a common subcritical dynamical regime.

The gastric network, comprised of brain regions whose activity synchronizes with the stomach's slow-wave rhythm, offers a unique window into the brain-body interaction involved in interoceptive processing. While previous work has established the existence of this network, its intrinsic organization and temporal unfolding remain poorly understood. Here, we reanalyzed resting-state fMRI-electrogastrogram data from 43 healthy adults of both sexes to characterize the time-averaged architecture and time-varying reconfiguration of the gastric network. We identified regions exhibiting phase-locked synchronization with the stomach slow electrical rhythm (0.05 Hz) and characterized cortical parcels comprising this network. Time-averaged graph-theoretical analysis revealed a fixed unimodal organization of functional communities, with primary visual, default mode network (DMN) and dorsal attention regions emerging as the principal time-averaged hubs. Next, we applied edge-centric functional connectivity (eFC) to capture the network state during transient high-amplitude "bursts". Time-varying community detection revealed communities whose compositions formed integrative combinations of DMN, visual, attentional and control elements. Edge-derived hubs shifted away from primary visual dominancy in the time-averaged analysis, and were instead directed by DMN regions, suggesting that moments of heightened connectivity in the network are coordinated by multisensory integration rather than passive sensory processing. These findings demonstrate that the gastric network is not merely a time-averaged, sensory-bound system, but rather a flexible and dynamically reconfiguring interoceptive network whose organization is selectively coordinated by transient cofluctuation events. This work provides a comprehensive network analysis of gastric-brain coupling and reveals a temporally structured mode of interoceptive integration that may support adaptive physiological and cognitive regulation.

Circadian disruption, notably sleep disturbances, serves as an early indicator of Alzheimers disease (AD), preceding cognitive symptoms like memory loss. The suprachiasmatic nucleus (SCN) governs biological rhythms and receives direct retinal input via melanopsin-expressing retinal ganglion cells (mRGCs) to synchronize with environmental light cycles. The anatomical and functional basis for circadian disruption in AD remains unclear. Here, we explored the multi-level relationships between gene expression, the SCN connectome, and regulations of sleep and circadian rhythms in the APP/PS1 mouse model. The sleep architecture of APP/PS1 mice displayed significantly reduced rapid eye movement sleep (REM), associated with a reduced daily core body temperature amplitude and locomotor hyperactivity. Lastly, APP/PS1 mice showed an impaired response to acute light pulse stimulation and present hyperactivity of mRGCs at a young age and hypoactivity of these cells at older ages. These physiological functions are known to be, at least in part, regulated by the SCN, the main target of mRGCs. We noted several modifications in SCN connectomics using serial blockface electron microscopy (SBEM), including a reduction of the dendro-dendritic chemical synapse (DDCS) network that receives a large part of the retinal input and is thought to be crucial for synchronicity between SCN neurons. In addition, we observed multiple signs of dystrophy, including modifications of the shape of dendrites and cell soma, accumulation of aggregated lysosomes, and swelling of axons. At the same time, we investigated the changes in gene expression using spatial transcriptomics. The SCN presents changes in the expression of genes associated with synapse formation, cell adhesion, and neurite growth. These results suggest that, despite the absence of amyloid plaques in the ventral hypothalamus, the SCN of APP/PS1 mice still undergo profound gene expression changes, impacting connectomics and physiological functions. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=157 SRC="FIGDIR/small/744599v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@ceedb0org.highwire.dtl.DTLVardef@156cfaaorg.highwire.dtl.DTLVardef@5bc262org.highwire.dtl.DTLVardef@36df4d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Episodic memory decline is a common feature of cognitively normal aging, but its extent varies markedly across individuals. Although entorhinal tau pathology is thought to be a key contributor to episodic memory impairment, the neural mechanisms linking early tau accumulation to memory differences remain unclear. Grid-cell computations in the entorhinal cortex, which provide scaffolds for organizing experiences into episodic memories, offer one candidate mechanism. Here, we combined virtual-reality functional MRI, multivariate analysis, tau PET, and delayed word-list recall in cognitively normal older adults to test whether tau-related alterations in entorhinal coding are associated with worse episodic memory. Weaker left entorhinal grid-cell-like signal was associated with poorer memory performance, and individuals with higher left entorhinal tau burden showed weaker grid-cell-like signal. This association was specific to the canonical six-fold signal and was not explained by entorhinal volume, mean diffusivity, or intracortical myelination. A cross-sectional Bayesian mediation analysis further demonstrated that bilateral medial temporal tau burden is related to memory indirectly through left entorhinal grid-cell-like signal. Together, these findings provide evidence that entorhinal grid codes may constitute a functional pathway linking tau accumulation to memory variability in normal aging.

Chronic pain mechanisms are complex, spanning multiple brain regions and networks. We ask whether resting brain activity carries a readout of that state. From a few minutes of resting-state electroencephalography (EEG), we generate a spectrogram to represent how each region of the cortex oscillates across frequency and time and pass it through CREST (Cortical Resting-state EEG Spatial Transformer): a frozen image-recognition network that reads each region as an image--here, a spectrogram--paired with a graph model that weighs the 56 cortical regions together to classify chronic-pain status. Across 125 people (74 with chronic pain, 51 healthy controls), evaluated through a leave-one-subject-out cross-validation, CREST separates the two groups with an area under the receiver operating characteristic curve (AUROC) = 0.782 (permutation p < 0.005). Control experiments implicate each persons individual alpha rhythm. Clinical relevanceA resting-state EEG readout of chronic MSK pain could clarify pathophysiology and inform treatment.

Alzheimer's disease (AD) pathology involves amyloid deposition, reactive gliosis, and localized tissue alterations that coexist within the same brain regions, creating heterogeneous microstructural environments within individual imaging voxels. Conventional diffusion MRI averages these environments into aggregate measures, potentially obscuring their distinct contributions. Frequency-dependent multidimensional MRI ({omega}MD-MRI) resolves distributions of water components with different diffusion length scales, anisotropies, and relaxation properties, providing sensitivity to microstructural restriction, heterogeneity, and shape-size correlations within a voxel. Whether these measurements reveal microstructural complexity associated with AD pathology remains unclear. Here, we performed {omega}MD-MRI on ex vivo brain specimens from approximately 8-month-old 5xFAD and wild-type mice and interpreted the imaging findings alongside complementary histology. {omega}MD-MRI revealed widespread but spatially nonuniform differences between 5xFAD and wild-type brains. Measurements sensitive to microstructural restriction, heterogeneity, and shape-size correlations consistently indicated greater microstructural heterogeneity in 5xFAD brains, with the most prominent differences in the hippocampal formation and major cerebral white matter tracts. Complementary qualitative histology demonstrated extensive amyloid deposition and glial activation in affected regions, while overall cytoarchitecture and myelin organization remained largely preserved. Thus, the {omega}MD-MRI abnormalities occurred in tissue characterized by multiple coexisting pathological and relatively preserved microstructural environments rather than widespread structural degeneration. These findings demonstrate that {omega}MD-MRI can reveal the spatial and microstructural heterogeneity associated with amyloid pathology and provide a more comprehensive characterization of AD-related tissue alterations.

Cholesterol efflux is an important determinant of cellular lipid homeostasis. However, how microglial excessive cholesterol accumulation affects neuronal synaptic integrity remains poorly understood, particularly in the context of Alzheimer's disease. Here, we utilized a conditional knockout mouse model targeting the cholesterol transporters ABCA1 and ABCG1 in microglia. The microglia-specific ABCA1/ABCG1 deficiency triggered marked cholesterol accumulation, microglial hypertrophy, downregulation of the homeostatic marker P2ry12, and upregulation of the reactivity-associated marker CD11b, indicating shift toward a reactive phenotype. This phenotype was accompanied by increased reactive oxygen species, consistent with enhanced oxidative stress in ABCA1/ABCG1-deficient microglia compared with control. Using organotypic hippocampal slice cultures, we investigated the downstream neuronal outcomes of microglial ABCA1/ABCG1 deficiency. Under basal conditions, microglial ABCA1/ABCG1 knockdown did not significantly alter dendritic spine density in CA1 pyramidal neurons. However, upon exposure to amyloid-beta (A{beta}) stress, microglial ABCA1/ABCG1 deficiency markedly exacerbated dendritic spine loss in CA1 pyramidal neurons. Taken together, our findings highlight an important role for ABCA1/ABCG1-dependent cholesterol efflux in maintaining microglial homeostasis and limiting neuronal synaptic vulnerability to A{beta}-associated stress. These results support further investigation of microglial cholesterol transport as a potential target for preserving synaptic resilience in Alzheimer's disease.

Damage to the primary visual cortex causes loss of conscious vision, yet some patients retain the ability to respond to stimuli despite reporting no visual experience. Why similar lesions produce such different behavioral phenotypes remains unclear. While research to date has focused primarily on spared pathways that bypass V1, here we asked whether these divergent outcomes are also linked to the brain's intrinsic functional architecture. In the largest resting-state fMRI cohort of patients with unilateral V1 damage reported to date, we quantified information sharing between regions across cortical and subcortical parcels in blindsight-positive and blindsight-negative patients, as well as in age-matched healthy controls. Despite comparable lesions, the two patient groups displayed distinct hierarchical patterns on the cortex: B+ patients preserved a sensory-to-association organization as in healthy controls, whereas B- patients exhibited a marked flattening of this hierarchy. The effect was driven by abnormally low shared-information coupling within unimodal cortices and scaled continuously with single-subject behavioral blind-field detection performance. A thalamic region consistent with the pulvinar, linking the contralesional visual cortex and the frontal eye field, discriminated B+ from B- patients. These findings highlight the system-level consequences of V1 damage supporting blindsight, suggesting that the unimodal-transmodal axis might track not only global states of consciousness, but also whether sensory information can guide behavior without awareness.

Molecular staging of Alzheimer's disease (AD) increasingly defines transition boundaries along single-cell pseudo-progression trajectories, yet whether such boundaries reproduce across brain regions, cohorts and molecular modalities is rarely tested. We present a permutation-controlled audit that combines nine boundary-detection algorithms with a fixed marker panel and four orthogonal reproducibility axes-algorithmic consensus, region, cohort and modality. On synthetic data with planted ground-truth boundaries the audit reaches 100% sensitivity and 94% specificity, rejecting four distinct artefact classes each by a different axis. Applied to the Seattle Alzheimer's Disease Brain Cell Atlas middle temporal gyrus, it localizes a transition that is robust across algorithms and recovered in most cell types but does not generalize: its leading marker is attenuated or absent in prefrontal cortex, entorhinal cortex and cerebrospinal fluid, and an apparent cross-region conservation of glial metabolic genes proves to be a global-expression offset rather than a shared program. The same audit nonetheless certifies an externally validated marker (astrocytic PTGDS) as reproducible across regions and modalities, showing that it separates generalizable anchors from dataset-specific ones rather than rejecting all signals. We provide this four-axis audit as a transferable, code-available standard to apply before a trajectory boundary is read as a biological stage, in AD and other progressive proteinopathies.

Lesion Network Mapping (LNM) is a framework used for identifying symptom-related brain circuits by projecting lesion locations onto a normative connectome. Recent methodological investigations have raised concerns about the biological interpretation and specificity of the circuits derived using this method, with published LNM maps often showing high similarity across clinically unrelated conditions. Specificity testing has subsequently been put forward as the decisive step to ensure specificity to the symptom in question, accompanied by the argument that this step was not evaluated in the original methodological investigation. Yet, sensitivity testing, specificity testing, case-control LNM, permutation of group labels, and symptom-based LNM involve related operations on connectivity matrix C. We expand on specificity testing in LNM, clarify its relationship to other LNM steps and variants, and examine the persistent repetition among LNM specificity networks across studies. These considerations advance our understanding of the disease-specificity limitation of LNM and encourage the development of new methodological approaches for identifying brain circuits underlying psychiatric and neurological disorders.

Pathophysiological mechanisms underlying the transition from acute to chronic neuropathic pain remain incompletely understood. The somatosensory and insular cortices are key cortical components of the pain matrix. We examined changes in activation of these cortical regions during the transition from acute to chronic neuropathic pain. The right sciatic nerve was ligated in activity reporter TRAP mice using standard procedures. Mechanical allodynia was confirmed after CCI or sham surgery using von Frey monofilaments applied to the hind paws. To label active neurons, 4-hydroxytamoxifen was administered to separate cohorts at 1, 3, and 6 weeks following nerve ligation. Passive tissue clearing of brain sections and confocal imaging was used to assess active neurons. Progressive reduction of ipsilateral hind paw in CCI mice indicated mechanical allodynia development. CCI mice showed robust neuronal activation in the bilateral somatosensory and insular cortices. The somatosensory cortical activation peaked at 3 weeks post-CCI, whereas insular cortical activity increased during the transition from acute to chronic neuropathic pain. These studies revealed that CCI induced progressive mechanical allodynia and distinct temporal patterns of cortical neuronal activation, with transient peak neuronal activity in the somatosensory cortex and sustained, increasing activation in the insular cortex during acute-to-chronic pain transformation.

Working memory is capacity-limited, but interactions with episodic memory may offset this constraint. We tested moment-by-moment contributions of episodic representations to working memory by combining the N-back and Mnemonic Similarity tasks. Thirty-one participants, undergoing eye-tracking, first encoded items in a one-back task, classifying them as "same" or "similar" to their predecessor. In a subsequent two-back task, mnemonic discrimination showed a graded, item-specific benefit of prior experience: performance was best for previously compared items, whereas recognition of identical repeats was unaffected. Successful discrimination of previously compared items was accompanied by greater pupil dilation, gradually emerging gaze patterns resembling those elicited by their similar pair-mate, and higher gaze-similarity between one-back and two-back target viewing. Diverging gaze patterns between pair-mates during one-back further predicted two-back discrimination. These findings challenge working memory's characterization as an isolated system, demonstrating how it recruits episodic computations - encoding distinct traces, predicting upcoming content, and reinstating it at retrieval.

Pain promotes protective behavior but can interfere with other biologically important goals. Survival may require overcoming pain to obtain rewards, secure resources or escape danger, yet evidence for pain modulation by competing demands and endogenous modulatory systems during goal pursuit is lacking. We developed a paradigm in which participants chose whether to pursue monetary rewards despite painful heat stimulation during fMRI, under placebo or opioid receptor blockade with naloxone. Actively pursuing motivational goals during painful stimulation reduced perceived pain and increased fMRI signal in pain-modulatory cortical regions, including multiple subregions of the rostral anterior cingulate cortex (rACC) and dorsolateral prefrontal cortex, alongside enhanced rACC-periaqueductal gray coupling, consistent with recruitment of the descending pain modulatory system. Behavioral and neural effects were attenuated by naloxone, supporting a mediating role for endogenous opioids. These findings provide convergent evidence that active goal pursuit engages opioidergic pain modulatory mechanisms to reduce pain in humans.

Migraine is a leading cause of disability, yet preventive treatment remains largely empirical despite the availability of several mechanistically distinct therapies. Genetic data can clarify mechanisms and therapeutic hypotheses when association signals are integrated with molecular and clinical data. We meta-analyzed migraine GWAS data from 12 European ancestry cohorts (206,893 cases and 2,093,175 controls) and four African ancestry cohorts (22,115 cases and 178,626 controls). We identified 311 lead variants in European-ancestry analyses and 316 lead variants in trans-ancestry analysis. Fine-mapping and transcriptome-wide analyses prioritized variants and genes implicated in sensory neuronal signaling, vascular tone, and immune regulation, with convergent evidence at several established loci including TRPM8 and PHACTR1. Drug-repurposing analyses identified therapeutic targets and compounds, including established migraine treatments and candidates requiring experimental validation. Genetic correlations, Mendelian randomization, and a phenome-wide scan linked migraine liability to psychiatric, pain, and gastrointestinal phenotypes. Together, these findings expand the known genetic architecture of migraine across ancestries and provide a genetics-led map connecting association signals with biological pathways, multimorbidity and candidate therapeutic mechanisms, providing a foundation for future functional and translational studies.

Although the brain was traditionally considered immune-privileged, recent studies show immune factors play key roles in brain function. Dysfunction of these factors is linked to neurodevelopmental disorders, but mechanisms remain unclear. Using a maternal immune activation (MIA) mouse model, we investigated immune-related genes in neurodevelopmental disorder pathogenesis. MIA mice showed increased locomotor activity and disrupted prepulse inhibition. RNA-seq and qPCR analyses revealed persistent increases in major histocompatibility complex class II (MHCII) expression and persistent decreases in GABAergic synapse-related gene expression, particularly glutamate decarboxylase (Gad) expression, in dopaminergic regions. These expressions were negatively correlated, and immunohistochemistry showed MHCII at postsynaptic GABAergic synapses on dopaminergic neurons. Patch-clamp recordings confirmed reduced mIPSC frequency in MIA mice. MHCII knockout mice showed opposite phenotypes, while MHCII overexpression in dopaminergic neurons decreased Gad expression. These results suggest MIA-induced MHCII upregulation enhances pruning of GABAergic synapses on dopaminergic neurons, leading to behavioral deficits.

Past studies using transcranial magnetic stimulation have shown larger motor-evoked potentials when people observe someone lifting a heavy object than when they observe someone lifting a light one. This means that observers may engage their own motor system in proportion to the perceived effort. However, the different responses during the observation of light and heavy objects may have been influenced by predictable trial sequences within blocked presentation, making it unclear whether corticospinal excitability reflects online processing of kinematics or is affected by top-down expectations. In this Registered Report, 57 right-handed participants passively observed videos of a precision grip and lift of heavy and light objects while receiving a single-pulse TMS to the left primary motor cortex during the lift phase of the movement. Motor-evoked potentials were recorded from the right first dorsal interosseous muscle. The study compared two main observation contexts: a predictable trial sequence in which repeated videos of the same lifts were presented in a blocked order, and an unpredictable one in which videos were presented semi-randomly and participants could rely only on kinematic cues to perceive the weight of the lifted object. In both conditions, the same videos of lifts of equivalent-looking heavy and light objects were used and only the order of presentation differed. Contrary to our predictions, in the blocked (predictable) condition, there was no significant difference in MEPs elicited by light and heavy lifts. In the unpredictable condition, participants showed greater corticospinal excitability during the observation of the light lifts compared to the heavy lifts. This suggests that in the absence of predictable information, the corticospinal system was sensitive to the observed kinematics, but contrary to previous findings, its excitability varied inversely with the object weight.

BackgroundLocomotor adaptation is essential for adjusting walking patterns to complex environments. This study investigated locomotor adaptation deficits in people with Parkinsons disease (PD) and examined oscillatory activity in the globus pallidus internus (GPi) during walking adaptation. We hypothesized that elevated beta-band activity in the GPi is associated with reduced locomotor adaptability in PD. MethodsTwelve PD patients with GPi deep brain stimulation (DBS) (eleven bilateral and one unilateral) were included. Local field potentials (LFPs) were recorded from DBS electrodes during split-belt treadmill walking. Patients were tested in the medication-off, DBS-off state. Locomotor adaptation was measured as the change in step length asymmetry during split-belt walking, with smaller changes indicating greater adaptation deficits. ResultsWe found that GPi high beta (20-30 Hz) and low gamma (30-60 Hz) oscillations were modulated during split-belt walking. Compared to adapters, non-adapters showed decreased movement-related beta suppression during walking. Across participants, beta activity in the GPi contralateral to the fast leg was negatively associated with adaptation magnitude (Spearmans {rho} = -0.65 to -0.75). ConclusionsGPi oscillations are dynamically modulated during locomotor adaptation in PD. Increased beta activity may underlie impaired sensorimotor adaptation during walking. These findings provide novel insight into basal ganglia mechanisms of gait adaptation in PD and suggest that elevated GPi beta activity may serve as a marker of locomotor adaptation deficits.

Pain is a conscious perceptual experience characterized by its aversive quality and consequent motivation to quench pain perception. The anterior cingulate cortex (ACC) critically contributes to the emotional dimension of pain. In both humans and rodents, ACC neural activity increases during acute and chronic pain, whereas ACC lesioning or excitability reduction decreases emotional reactivity during pain. However, the ACC is connected to many brain regions and is engaged during experiences beyond pain. Thus, it remains unclear through which circuit mechanisms the ACC shapes pain experience, and how specific those circuits are to nociception. Here, we show that excitatory input from the ACC to the dorsolateral periaqueductal gray (dlPAG) facilitates the affective-motivational dimension of pain. We first examined ACC[-&gt;]dlPAG connectivity using histology, optogenetics, and electrophysiology. We found that the axons of layer 5 ACC neurons terminate in the dlPAG and monosynaptically excite Slc17a6+ (VGLUT2-expressing) dlPAG neurons. Second, we genetically targeted ACC[-&gt;]dlPAG neurons with viral vectors to express the inhibitory DREADD hM4Di and then exposed the animals to an array of pain tests. We found that, across acute and chronic pain states, inhibition of the ACC[-&gt;]dlPAG pathway reduced affective-motivational but not reflexive pain behaviors. Third, we used fiber photometry to record neural calcium activity in the ACC in behaving mice and found that ACC[-&gt;]dlPAG neurons are engaged during a broad array of aversive experiences, rather than exclusively during pain, and exhibit task-specific activity patterns. Collectively, these results uncover the direct contribution of ACC[-&gt;]dlPAG neural activity to pain unpleasantness and the necessity of this pathway for generating aversive behavioral responses in general, rather than specifically for encoding the unpleasant quality of noxious stimuli.

During wakefulness, we are used to perceive the environment through our senses, act on it and take these inputs to update our experiences and build the perceptions. When the inputs are not longer accurate or structured, people would sometimes have hallucinatory experiences. Whether such experiences are associated with distinct patterns of thought, and how they relate to large scale brain dynamics, remains unclear. To address these questions, we combined experience sampling protocol with EEG recording during multimodal Ganzfeld, where participants were exposed to unstructured, uniform visual and auditory stimulation. Participants repeatedly reported the complexity of their visual experiences together with ongoing thoughts related to perceptual belief, prediction perception mismatch, active updating, and prior mentation. EEG microstates were extracted to characterize the temporal dynamics of large-scale brain networks. We found that visual complexity was related to all four dimensions, but partly distinct in simple and complex visual experiences. These phenomenological changes were accompanied by distinct, and often nonlinear, dynamics of large-scale brain networks involved in visual processing, salience detection, and internally directed cognition. It also indicates that this paradigm might be a valuable model for investigating the mechanisms underlying hallucinatory experiences in psychosis.

Adaptive behavior requires updating responses when contingencies change while preserving prior associations and the capacity to learn a new. How this trade-off is resolved remains unknown. Here, we combined in vivo imaging of apical tuft spines in the secondary motor cortex (M2) with biologically constrained network modeling in mice performing a cross-modal rule-switch task. M2 inactivation impaired rule-switching but not learning or maintenance, identifying it as a conflict resolution substrate. Adaptation was accompanied by elevated spine turnover concentrated within stable dendritic hotspots, in which the formation, elimination and clustering of new spines were coupled and pre-existing spines were lost early. A network model reproduces these dynamics and predicts that dendritic hotspots are critical for resource-efficient adaptation. Within these reusable domains, spines encoding the prior rule are replaced by newly-relevant ones via sharing of plasticity-related resources. Preventing reuse increases both the plasticity and the engram size requirements to encode the two rules. We propose that dendritic hotspots provide a mechanistic substrate for efficient adaptive learning.