| Global structure of new relational knowledge networks is represented in retrosplenial complex, and node-distance in hippocampus |
Feld, G. B. |
2026-07-25 |
PDF |
Much of our knowledge is structured in networks, but how the brain represents such networks remains unclear. In most nested knowledge structures a subset of the nodes will be highly connected to other nodes in the network. High levels of connection can exist either locally (high degree centrality) or at a global level (high closeness/betweenness centrality). Here, we explored how the human brain represents network structure using functional magnetic resonance imaging (fMRI) and a novel learning paradigm. During training, participants learned the transition structure for travel between a set of fictious partially connected alien planets. Despite encountering only individual connections, participants choices indicated they could infer the broader network structure. Next day, they viewed each stimulus during a cover task while undergoing fMRI. Representational-similarity analysis showed that shortest-path distances within the learned graph were encoded in the posterior hippocampus and right retrosplenial complex, whereas global connectivity (closeness/ betweenness centrality) was represented in the left retrosplenial complex. These findings extend the view that brain networks associated with spatial navigation also process abstract relational knowledge using principles akin to mapping physical space. The results are also consistent with proposals that the hippocampus represents distance information and that the retrosplenial cortex acts as hub for integrating recently acquired knowledge. |
| Deep Phenotyping with Global Brain Activity and Plasticity Mapping Identify the Dorsal Raphe-Basolateral Amygdala Circuit as a Mediator of Adaptive Stress Responses |
Mitra, S. |
2026-07-25 |
PDF |
Exposure to chronic environmental challenges triggers divergent behavioral trajectories across individuals. At the core, these different trajectories can be classified as individuals actively adapting to the challenges (responders) and those displaying a rigid, non-responsive phenotype (non-responders). The brain system-wide network configurations that dictate why individuals diverge along these differential coping strategies, which can also lead to disease vulnerability or resilience, remain poorly understood. Here, we paired machine-learning-based deep behavioral phenotyping with multi-modal whole-brain imaging, integrating longitudinal Manganese-Enhanced MRI (MEMRI) and post-challenge cFOS mapping, to chart the functional landscape of individual stress trajectories in mice subjected to chronic social defeat stress. High-dimensional behavioral phenotyping revealed that active stress adaptation is a complex trajectory marked by latent, pre-stress kinetic signatures in vigilance-like and locomotive behaviors. At the neural level, longitudinal MEMRI captured distinct, consolidated activity reconfigurations across canonical valence and stress-regulatory circuits that segregated responders from non-responders. Complementary whole-brain cellular cFOS network analysis after an additional acute challenge revealed that non-responders exhibited marked hyper-modularity and network fragmentation, whereas responders featured a tightly integrated functional module co-clustering the periaqueductal gray, ventral tegmental area, basolateral amygdala (BLA), and dorsal raphe (DR). Notably, functional network connectivity along the DR-BLA axis was completely lost in non-responsive animals. Finally, pathway-specific chemogenetic inhibition of BLA-projecting DR neurons during a social challenge significantly attenuated social avoidance and reversed anxiety-like behavioral deficits, effectively shifting active behavioral adaptation toward a non-responsive phenotype. Together, these findings demonstrate that individual stress-coping strategies are driven by coordinated, system-wide reconfigurations of activity and plasticity, identifying the DR-BLA circuit as a critical gatekeeper of adaptive stress responses. |
| A significant enrichment that is not: spatial nulls, co-expression, and the imaging transcriptomics of EEG alpha-power genetics |
Schenetti, J. |
2026-07-25 |
PDF |
Background. Imaging transcriptomics routinely asks whether a trait-associated gene set is over-expressed in a region of interest, and the field standard is to guard that inference with a spatial-autocorrelation-preserving spin test. Electroencephalographic (EEG) oscillatory power is among the most heritable human neurophysiological traits, and the cortical generators of the alpha rhythm have been characterised independently from resting-state magnetoencephalography - making this a natural test bed both for asking whether trait genetics is regionally organised, and for asking what such a test actually establishes. Objective. To test whether alpha-associated genetic signal is spatially enriched in the cortical generators of the alpha rhythm, and to evaluate that inference against complementary null models. Methods. MAGMA gene-based analysis of ENIGMA-EEG summary statistics for six phenotypes: central and occipital alpha power, occipital alpha peak frequency, and theta, beta and delta power. Regional transcription was obtained from the Allen Human Brain Atlas (AHBA) with abagen in the Glasser HCP-MMP1.0 atlas, with Schaefer-100 and Yan-600 as sensitivity analyses. Enrichment in the 41 cortical alpha-source regions was quantified with a threshold-free continuous score and a top-100 gene-set composite, and assessed against three complementary nulls: a spin test (10,000 rotations, cross-checked against brainsmash surrogates), a co-expression-aware gene-set null (10,000 matched random gene sets), and a positive control on a known expression gradient. Results. Judged by the field-standard spin test alone, this study would have reported a positive, biologically coherent finding: alpha-power genes are enriched in the cortical alpha generators (continuous p_spin = 0.022; top-100 p_spin = 0.030), with the spin result corroborated by an independent surrogate model (p = 0.018) and the pipeline validated by a positive control (p_spin = 2 x 10^-4). Three further tests dissolve that conclusion. First, it is not band-specific: theta, beta and delta enrich comparably or more strongly (top-100 beta p_spin = 0.011; delta 0.042; continuous theta 0.042). Second, it does not replicate across alpha phenotypes (occipital alpha continuous p_spin = 0.20; alpha peak frequency non-significant, p_spin >= 0.066). Third, against random gene sets of matched size the alpha set is unremarkable (p_geneset = 0.33) - the apparent enrichment is a generic property of arbitrary gene sets in this cortical territory, and is invisible to a spatial-only null. No test survived false-discovery-rate correction across the 24-cell phenotype x score x region-set grid (minimum q = 0.127), and nominal significance did not survive a change of parcellation. Conclusion. EEG alpha-power genetics shows no regionally specific transcriptomic signature in the cortical generators of the rhythm; the weak tendency that is present is shared across frequency bands, consistent with their known genetic correlation. Methodologically, this is a worked demonstration that correcting for spatial autocorrelation is necessary but not sufficient: a spin-significant, surrogate-corroborated, mechanistically plausible enrichment can be fully accounted for by gene-set co-expression. Enrichment claims in imaging transcriptomics should report a gene-set null alongside the spatial null. |
| Distinct forms of dopamine transmission control locomotion and learning |
McGregor, M. |
2026-07-25 |
PDF |
The neuromodulator dopamine is essential for voluntary movement and learning from experience. While these behaviors often occur simultaneously and rely on overlapping nigrostriatal dopamine circuits, they are also separable and can manifest independently. How a single neuromodulatory system controls such disparate aspects of behavior in parallel remains poorly understood. Here we show that striatal dopamine is released through two spatially and functionally distinct modes that are independently regulated and serve distinct behavioral roles. Eliminating dopamine release underlying bulk extracellular accumulation reveals a spatially restricted mode of transmission that maintains phasic dopamine receptor activation on striatal projection neurons. We find that selective loss of diffuse dopamine impairs striatal circuit excitability and reduces locomotion, while point-to-point transmission is sufficient to maintain striatal spine density and support motor and associative learning. We propose that the geometry of dopamine release determines its behavioral output, a principle that explains the breadth of dopamine's functions and more broadly elucidates how neurons multiplex different forms of information. |
| Live-imaging of endogenous neurofascins reveals glial adhesion shapes developing nodes of Ranvier |
Lyster-Binns, P. |
2026-07-25 |
PDF |
The organisation of myelinated axons into specialised domains is essential for saltatory conduction and depends on the polarised distribution of neuronal and glial cell-adhesion molecules, including neurofascins. However, how these domains assemble and refine in vivo remains unclear, as longitudinal imaging of endogenous proteins within intact nervous systems remains challenging. Here, we generated knock-in zebrafish in which endogenous neuronal and glial neurofascins are fused to fluorescent proteins, which enabled live-imaging without perturbing node assembly or introducing overexpression artefacts. Using these reporters, we visualised neuronal and glial neurofascin dynamics, and the formation of nodes of Ranvier and paranodes in vivo. We find that nascent nodes progressively compact in developing peripheral nerves, and that this process depends on glial neurofascin. Our novel toolkit for imaging endogenous neurofascins reveals a glia-dependent mechanism that shapes the developmental refinement of nodal architecture after their initial assembly. Our findings imply that glia-driven modulation of paranodes can be a mechanism for nervous systems to regulate circuit function. |
| Developmental tuning of functional manifold dimensionality across the human brain |
Busch, E. L. |
2026-07-25 |
PDF |
Neural representations vary in their complexity across brain regions and tasks. How this variation emerges over human development remains poorly understood. We estimated intrinsic dimensionality in five naturalistic fMRI datasets (N = 781 unique participants, aged 3 months to 53 years) with T-PHATE -- a nonlinear manifold learning method robust to noisy, autocorrelated signals. In adults, brain regions relevant to a task had higher-dimensional activity than task-irrelevant regions across auditory, visual, and audiovisual stimuli. The modulation of representational complexity by tasks was absent in infants, emerged in early childhood, and strengthened logarithmically through adolescence. It reflected a selective collapse in dimensionality in task irrelevant regions, relative to a resting-state baseline, rather than an expansion of dimensionality in task-relevant regions. Such compression followed a trajectory from global and nonselective in infants to local and precise by adulthood. These results identify selective compression as a developmental engine of functional specialization: rather than adding complexity where it is needed, the brain dynamically pares it away where it is not. |
| AI segmentation requires accounting for brain size to maintain performance on developmental MRI cohorts |
Dorfschmidt, L. |
2026-07-25 |
PDF |
The human brain undergoes rapid developmental changes through early life, underpinning the emergence of function but also marking a period of vulnerability to a range of neurodevelopmental disorders. With dynamic changes to brain size, morphology, and imaging contrast, consistent and accurate computational neuroanatomy remains a challenge. Deep learning tools for segmentation, like SynthSeg, offer robustness to heterogeneously acquired MRI contrast but remain unproven in early development. Here, we aggregated a large cohort (26k) of MRI scans spanning infant to adult development, and evaluated SynthSeg performance. Automated quality control scores, visual inspection, and spatial overlap with expert-segmented MRI scans revealed poor quality output segmentations during development. In the infant period only 36% of scans (1094/3069) passed automated QC. Rescaling infant scans to adult brain sizes significantly improved spatial overlap, and cropping scans to match adult fields of view retrieved automated quality control. Evaluation of the SynthSeg rescale + crop pipeline demonstrated visible and quantitative improvements in segmentation throughout infancy and childhood. There were marked increases in successful segmentations in infant scans, with 91% of scans now passing QC (2803/3069). These findings facilitate computational analysis of typical and disrupted neurodevelopment and should be considered when training the next generation of computational tools. |
| Humans could become the greatest driver of biosphere net gain in Earth history, but we are currently the second fastest driver of biosphere loss |
Wong Hearing, T. W. |
2026-07-25 |
PDF |
Human activity is transforming the shape, size, and resilience of Earths biosphere, degrading and augmenting Holocene baseline conditions at various scales, and replacing the wild biosphere with an anthropogenically modified one. We evaluate episodes of biosphere change throughout Earth history and compare them with contemporary and near-future anthropogenic changes, developing the concept of biosphere disruptors - agents that force global-scale macroevolutionary change. Transient disruptors are short-lived agents (mean 8.0x105 years), including massive volcanism and asteroid impacts. Persistent disruptors, including atmospheric and ocean oxygenation and land plant evolution, remain in the Earth System over long timescales (mean 1.6x108 years). In the geological record, transient disruptors are associated with temporary but sometimes massive biosphere degradation, whereas persistent disruptors are associated with sustained biosphere enhancement. Most anthropogenic biosphere impacts resemble those of past transient disruptors, globally degrading wild biomass and biodiversity. Humanity is driving the second highest rate of biosphere degradation in Earth history after the Cretaceous-Palaeogene bolide impact. However, humanity is the first disrupting agent capable of reflecting on and potentially transforming its impact on planetary habitability. If we can achieve this, humanity could drive the greatest rate of increase in planetary habitability in Earth history on centennial to millennial timescales. |
| Generative replay across hippocampal-neocortical circuits |
Shearer, C. M. |
2026-07-25 |
PDF |
To make flexible decisions, the brain needs to make inferences between events that were not directly experienced together. In sharp-wave ripple (SWR) events, during periods of rest and sleep, spiking activity in the hippocampus appears to support this process, by co-activating mnemonic representations of discrete cues and events that have not been experienced together. However, it remains unclear whether this 'generative replay' also occurs in other brain regions to update beliefs across the brain. To address this question, here we use multi-unit electrophysiology and calcium imaging in freely moving mice during a multi-day inference task. We show evidence for a putative anatomical pathway from the dorsal CA1 (dCA1) region of the hippocampus to primary visual cortex (V1), via the granular Retrosplenial Cortex (RSCg). We then characterise the neuronal activity across this pathway during an inference task and in subsequent periods of sleep. We show that during inference, mnemonic activity in V1 mirrors that observed in dCA1 to represent learned associations. In sleep, we show evidence for generative replay in V1, where co-activity can be observed between cells representing inferred relationships between cues that have not been directly experienced together. This activity in V1 is predicted by activity in dCA1, suggesting that the hippocampus coordinates generative replay across neocortical circuits. This coordinated generative replay may underpin the formation of a hierarchical generative model capable of predicting future scenarios that extend beyond direct experience. |
| Concept-Level Semantic Representations Remain Decodable in Chronic Post-Stroke Aphasia |
Swiderski, A. M. |
2026-07-25 |
PDF |
Aphasia is characterized by impaired word retrieval, yet most cognitive models of word production assume that underlying conceptual-semantic representations are largely preserved. This study investigated whether concept-level semantic structure remains decodable from BOLD signals in chronic post-stroke aphasia and which semantic models best explain neural representational geometry during covert semantic feature generation. Eight healthy adults and six individuals with chronic aphasia completed a dense-sampling fMRI protocol in which they viewed 57 pictured nouns while silently generating semantic features. Representational similarity analysis showed that an experiential model (Exp48) best matched neural geometry in both people with aphasia and controls, outperforming taxonomic (WordNet) and distributional (Word2Vec, GloVe) models. Using representational similarity decoding, concept identity was recovered well above chance in both groups. No relationship was found between decoding accuracy and language measures from individuals with aphasia. These findings suggest that experiential semantic structure remains robustly represented and decodable in chronic aphasia despite lesion-related language impairments, highlighting preserved conceptual representations alongside altered anatomy. |