Come and join us! 
Monday mornings at 9:30 am Amsterdam time,
we discuss exciting new science from last week with colleagues,
students and everyone interested in the brain.
Previous events are available OnDemand on YouTube:  https://www.youtube.com/@CNSeminars

Paper link: https://doi.org/10.1371/journal.pbio.3002906 Short-range human cortico-cortical white matter fibers have thinner axons and are less myelinated compared to long-range fibers despite a similar g-ratio Abstract The size and complexity of the human brain require optimally sized and myelinated fibers. White matter fibers facilitate fast communication between distant areas, but also connect adjacent cortical regions via short association fibers. The difference in length and packing density of long and short association fibers pose different requirements on their optimal size and degree of myelination. The fundamental questions of (i) how thick the short association fibers are and (ii) how strongly they are myelinated as compared to long fibers, however, remain unanswered. We present a comprehensive two-dimensional transmission electron microscopic analysis of ~400,000 fibers of human white matter regions with long (corpus callosum) and short fibers (superficial white matter). Using a deep learning approach, we demonstrate a substantially higher fiber diameter and higher myelination thickness (both approximately 25% higher) in corpus callosum than in superficial white matter. Surprisingly, we do not find a difference in the ratio between axon diameter and myelin thickness (g-ratio), which is close to the theoretically optimal value of ~0.6 in both areas (0.54). This work reveals a fundamental principle of brain organization that provides a key foundation for understanding the human brain. Discussion papers we referred to: Diameter, Length, Speed, and Conduction Delay of Callosal Axons in Macaque Monkeys and Humans: Comparing Data from Histology and Magnetic Resonance Imaging Diffusion Tractography https://www.jneurosci.org/content/33/36/14501 Fiber composition of the human corpus callosum https://www.scopus.com/pages/publications/0027097055?inward

Paper link: https://www.nature.com/articles/s41593-025-02037-7 Abstract The adult brain’s capacity for cortical reorganization remains debated. Using longitudinal neuroimaging in three adults, followed before and up to 5 years after arm amputation, we compared cortical activity elicited by movement of the hand (before amputation) versus phantom hand (after amputation) and lips (before and after amputation). We observed stable cortical representations of both hand and lips in primary sensorimotor regions. By directly quantifying activity changes across amputation, we demonstrate that amputation does not trigger large-scale cortical reorganization. Presented by Lilit Dulyan, Radboud University

How are memories formed and stored in the brain? Uytiepo et al. used three-dimensional electron microscopy coupled with chemogenetic tagging and behavioral analysis to determine the structural changes supporting the acquisition of long-term fear memories, focusing on the Schaffer collateral synapses. Long-term memory acquisition was found to be associated with a selective increase in multisynaptic boutons without the involvement of simultaneous activation of synaptically connected neurons. These results challenge the general applicability of the Hebbian model and expand our understanding of the mechanisms responsible for memory formation. —Mattia Maroso Paper link: https://www.science.org/doi/10.1126/science.ado8316

Recent generations of language models have introduced Large Reasoning Models (LRMs) that generate detailed thinking processes before providing answers. While these models demonstrate improved performance on reasoning benchmarks, their fundamental capabilities, scaling properties, and limitations remain insufficiently understood. Current evaluations primarily focus on established math and coding benchmarks, emphasizing final answer accuracy. However, this evaluation paradigm often suffers from contamination and does not provide insights into the reasoning traces. In this work, we systematically investigate these gaps with the help of controllable puzzle environments that allow precise manipulation of complexity while maintaining consistent logical structures. This setup enables the analysis of not only final answers but also the internal reasoning traces, offering insights into how LRMs think. Through extensive experiments, we show that LRMs face a complete accuracy collapse beyond certain complexities. Moreover, they exhibit a counterintuitive scaling limit: their reasoning effort increases with problem complexity up to a point, then declines despite having remaining token budget. By comparing LRMs with their standard LLM counterparts under same inference compute, we identify three performance regimes: (1) low-complexity tasks where standard models outperform LRMs, (2) medium-complexity tasks where LRMs demonstrates advantage, and (3) high-complexity tasks where both models face complete collapse. We found that LRMs have limitations in exact computation: they fail to use explicit algorithms and reason inconsistently across scales. We also investigate the reasoning traces in more depth, studying the patterns of explored solutions and analyzing the models' computational behavior, shedding light on their strengths, limitations, and raising questions about their reasoning capabilities. Paper link: https://arxiv.org/abs/2506.06941

The arcuate fascicle (AF) is the main fibre tract in the brain for human language. It connects frontal and temporal language areas in the superior and middle temporal gyrus (MTG). The AF’s connection to the MTG was considered unique to humans and has influenced theories of the evolution of language. Here, using high-resolution diffusion MRI of post-mortem brains, we demonstrate that both wild and captive chimpanzees have a direct AF connection into the MTG, albeit weaker than in humans. This finding challenges the notion of a strictly human-specific AF morphology and suggests that language-related neural specialisation in humans likely evolved through gradual evolutionary strengthening of a pre-existing connection, rather than arising de novo. It is likely that this neural architecture supporting complex communication was already present in the last common ancestor of hominins and chimpanzees 7 million years ago, enabling the evolution of language processes in the human lineage. Paper link: https://www.nature.com/articles/s41467-025-59254-8#Sec27

Abstract Currently, we understand much about how children’s brains attend to and learn from information presented while they are alone, viewing a screen – but less about how interpersonal social influences are substantiated in the brain. Here, we consider research that examines how social behaviors affect not one, but both partners in a dyad. We review studies that measured interpersonal neural entrainment during early social interaction, considering two ways of measuring entrainment: concurrent entrainment (e.g., ‘when A is high, B is high’ – also known as synchrony) and sequential entrainment (‘changes in A forward-predict changes in B’). We discuss possible causes of interpersonal neural entrainment, and consider whether it is merely an epiphenomenon, or whether it plays an independent, mechanistic role in early attention and learning. Paper link: DOI: 10.1016/j.tics.2020.01.006

Synthetic Diffusion Tensor Imaging Maps Generated by 2D and 3D Probabilistic Diffusion Models: Evaluation and Applications Diffusion tensor imaging (DTI) is a key neuroimaging modality for assessing brain tissue microstructure, yet high-quality acquisitions are costly, time-intensive, and prone to artifacts. To address data scarcity and privacy concerns – and to augment the available data for training deep learning methods – synthetic DTI generation has gained interest. Specifically, denoising diffusion probabilistic models (DDPMs) have emerged as a promising approach due to their superior fidelity, diversity, controllability, and stability compared to generative adversarial networks (GANs) and variational autoencoders (VAEs). In this work, we evaluate the quality, fidelity and added value for downstream applications of synthetic DTI mean diffusivity (MD) maps generated by 2D slice-wise and 3D volume-wise DDPMs. We evaluate their computational efficiency and utility for data augmentation in two downstream tasks: sex classification and dementia classification using 2D and 3D convolutional neural networks (CNNs). Our findings show that 3D synthesis outperforms 2D slice-wise generation in downstream tasks. We present a benchmark analysis of synthetic diffusion-weighted imaging approaches, highlighting key trade-offs in image quality, diversity, efficiency, and downstream performance. Paper link: https://www.biorxiv.org/content/10.1101/2025.02.21.639511v1

Auditory and speech signals are undisputedly processed in both left and right hemispheres, but this bilateral allocation is likely unequal. The Asymmetric Sampling in Time (AST) hypothesis proposed a division of labor that has its neuroanatomical basis in the distribution of neuronal ensembles with differing temporal integration constants: left auditory areas house a larger proportion of ensembles with shorter temporal integration windows (tens of milliseconds), suited to process rapidly changing signals; right auditory areas host a larger proportion with longer time constants (∼150–300 ms), ideal for slowly changing signals. Here we evaluate the large body of findings that clarifies this relationship between auditory temporal structure and functional lateralization. In this reappraisal, we unpack whether this relationship is influenced by stimulus type (speech/nonspeech), stimulus temporal extent (long/short), task engagement (high/low), or (imaging) modality (hemodynamic/electrophysiology/behavior). We find that the right hemisphere displays a clear preference for slowly changing signals whereas the left-hemispheric preference for rapidly changing signals is highly dependent on the experimental design. We consider neuroanatomical properties potentially linked to functional lateralization, contextualize the results in an evolutionary perspective, and highlight future directions. Paper link: https://doi.org/10.1016/j.neubiorev.2025.106082

Electrophysiological signatures underlying variability in human memory consolidation We experience countless pieces of new information each day, but remembering them later depends on firmly instilling memory storage in the brain. Numerous studies have implicated non-rapid eye movement (NREM) sleep in consolidating memories via interactions between hippocampus and cortex. However, the temporal dynamics of this hippocampal-cortical communication and the concomitant neural oscillations during memory reactivations remains unclear. To address this issue, the present study used the procedure of targeted memory reactivation (TMR) following learning of object-location associations to selectively reactivate memories during human NREM sleep. Cortical pattern reactivation and hippocampal-cortical coupling were measured with intracranial EEG recordings in patients with epilepsy. We found that TMR produced variable amounts of memory enhancement across a set of object-location associations. Successful TMR increased hippocampal ripples and cortical spindles, apparent during two discrete sweeps of reactivation. The first reactivation sweep was accompanied by increased hippocampal-cortical communication and hippocampal ripple events coupled to local cortical activity (cortical ripples and high-frequency broadband activity). In contrast, hippocampal-cortical coupling decreased during the second sweep, while increased cortical spindle activity indicated continued cortical processing to achieve long-term storage. Taken together, our findings show how dynamic patterns of item-level reactivation and hippocampal-cortical communication support memory enhancement during NREM sleep. Paper link: https://www.nature.com/articles/s41467-025-57766-x#Abs1 Presenter: Dr Marcela Ovando-Tellez

At the heart of medicine lies physician–patient dialogue, where skillful history-taking enables effective diagnosis, management and enduring trust1,2. Artificial intelligence (AI) systems capable of diagnostic dialogue could increase accessibility and quality of care. However, approximating clinicians’ expertise is an outstanding challenge. Here we introduce AMIE (Articulate Medical Intelligence Explorer), a large language model (LLM)-based AI system optimized for diagnostic dialogue. AMIE uses a self-play-based3 simulated environment with automated feedback for scaling learning across disease conditions, specialties and contexts. We designed a framework for evaluating clinically meaningful axes of performance, including history-taking, diagnostic accuracy, management, communication skills and empathy. We compared AMIE’s performance to that of primary care physicians in a randomized, double-blind crossover study of text-based consultations with validated patient-actors similar to objective structured clinical examination4,5. The study included 159 case scenarios from providers in Canada, the United Kingdom and India, 20 primary care physicians compared to AMIE, and evaluations by specialist physicians and patient-actors. AMIE demonstrated greater diagnostic accuracy and superior performance on 30 out of 32 axes according to the specialist physicians and 25 out of 26 axes according to the patient-actors. Our research has several limitations and should be interpreted with caution. Clinicians used synchronous text chat, which permits large-scale LLM–patient interactions, but this is unfamiliar in clinical practice. While further research is required before AMIE could be translated to real-world settings, the results represent a milestone towards conversational diagnostic AI. Paper link: https://www.nature.com/articles/s41586-025-08866-7

Promoting Open Discussions of Scientific Failure within the Annual Society for Neuroscience Conference The annual Society for Neuroscience (SfN) meeting is a bonanza of scientific achievement: famous keynote speakers, beautiful scientific results, and award ceremonies. This focus is exciting and invigorating but glosses over the many failures, mistakes, and rejections that typically lead to scientific success. Our goal has been to create a space within the annual SfN meeting for open conversation about scientific failure and, by doing so, increase transparency, resilience, and mental well-being within our community. In this article, we share the materials that we have used at SfN during the past 4 years (2021–2024) to promote discussions of scientific failure, including formal storytelling, individual and interactive games, and confessionals. For each activity, we provide the rationale and practical guidance regarding logistics and usage. We hope this will aid scientists interested in adapting the activities for their own communities or local events. We end with a call for scientific institutions to commit to providing space for open discussions of failure within their educational programs and conferences. Paper link: https://www.eneuro.org/content/12/3/ENEURO.0524-24.2024

Paper link: https://direct.mit.edu/nol/article/5/3/676/114495/The-Contributions-of-the-Cerebellar-Peduncles-and Abstract Fluent speech production is a complex task that spans multiple processes, from conceptual framing and lexical access, through phonological encoding, to articulatory control. For the most part, imaging studies portraying the neural correlates of speech fluency tend to examine clinical populations sustaining speech impairments and focus on either lexical access or articulatory control, but not both. Here, we evaluated the contribution of the cerebellar peduncles to speech fluency by measuring the different components of the process in a sample of 45 neurotypical adults. Participants underwent an unstructured interview to assess their natural speaking rate and articulation rate, and completed timed semantic and phonemic fluency tasks to assess their verbal fluency. Diffusion magnetic resonance imaging with probabilistic tractography was used to segment the bilateral cerebellar peduncles (CPs) and frontal aslant tract (FAT), previously associated with speech production in clinical populations. Our results demonstrate distinct patterns of white matter associations with different fluency components. Specifically, verbal fluency is associated with the right superior CP, whereas speaking rate is associated with the right middle CP and bilateral FAT. No association is found with articulation rate in these pathways, in contrast to previous findings in persons who stutter. Our findings support the contribution of the cerebellum to aspects of speech production that go beyond articulatory control, such as lexical access, pragmatic or syntactic generation. Further, we demonstrate that distinct cerebellar pathways dissociate different components of speech fluency in neurotypical speakers. cerebellum, DTI, probabilistic tractography, speaking rate, speech production, white matter

Cell-based therapies hold great promise for brain repair after stroke. While accumulating evidence confirms the preclinical and clinical benefits of cell therapies, the underlying mechanisms by which they promote brain repair remain unclear. Here, we briefly review endogenous mechanisms of brain repair after ischaemic stroke and then focus on how different stem and progenitor cell sources can promote brain repair. Specifically, we examine how transplanted cell grafts contribute to improved functional recovery either through direct cell replacement or by stimulating endogenous repair pathways. Additionally, we discuss recently implemented preclinical refinement methods, such as preconditioning, microcarriers, genetic safety switches and universal (immune evasive) cell transplants, as well as the therapeutic potential of these pharmacologic and genetic manipulations to further enhance the efficacy and safety of cell therapies. By gaining a deeper understanding of post-ischaemic repair mechanisms, prospective clinical trials may be further refined to advance post-stroke cell therapy to the clinic. paper link: https://academic.oup.com/brain/article/147/10/3286/7698450

Paper link: https://pmc.ncbi.nlm.nih.gov/articles/PMC10570710 Neural evidence for procedural automatization during cognitive development: Intraparietal response to changes in very-small addition problem-size increases with age Cognitive development is often thought to depend on qualitative changes in problem-solving strategies, with early developing algorithmic procedures (e.g., counting when adding numbers) considered being replaced by retrieval of associations (e.g., between operands and answers of addition problems) in adults. However, algorithmic procedures might also become automatized with practice. In a large cross-sectional fMRI study from age 8 to adulthood (n = 128), we evaluate this hypothesis by measuring neural changes associated with age-related reductions in a behavioral hallmark of mental addition, the problem-size effect (an increase in solving time as problem sum increases). We found that age-related decreases in problem-size effect were paralleled by age-related increases of activity in a region of the intraparietal sulcus that already supported the problem-size effect in 8- to 9-year-olds, at an age the effect is at least partly due to explicit counting. This developmental effect, which was also observed in the basal ganglia and prefrontal cortex, was restricted to problems with operands ≤ 4. These findings are consistent with a model positing that very-small arithmetic problems–and not larger problems–might rely on an automatization of counting procedures rather than a shift towards retrieval, and suggest a neural automatization of procedural knowledge during cognitive development. Keywords: Development, Arithmetic, Procedure, Problem-size effect, FMRI

Adaptive deep brain stimulation (aDBS) is an emerging advancement in DBS technology; however, local field potential (LFP) signal rate detection sufficient for aDBS algorithms and the methods to set-up aDBS have yet to be defined. Here we summarize sensing data and aDBS programming steps associated with the ongoing Adaptive DBS Algorithm for Personalized Therapy in Parkinson’s Disease (ADAPT-PD) pivotal trial (NCT04547712). Sixty-eight patients were enrolled with either subthalamic nucleus or globus pallidus internus DBS leads connected to a Medtronic PerceptTM PC neurostimulator. During the enrollment and screening procedures, a LFP (8–30 Hz, ≥1.2 µVp) control signal was identified by clinicians in 84.8% of patients on medication (65% bilateral signal), and in 92% of patients off medication (78% bilateral signal). The ADAPT-PD trial sensing data indicate a high LFP signal presence in both on and off medication states of these patients, with bilateral signal in the majority, regardless of PD phenotype. Paper link: https://www.nature.com/articles/s41531-024-00772-5

Conducting Research with Highly Portable MRI in Community Settings: A Practical Guide to Navigating Ethical Issues and ELSI Checklist Highly portable and accessible MRI technology will allow researchers to conduct field-based MRI research in community settings. Previous guidance for researchers working with fixed MRI does not address the novel ethical, legal, and societal issues (ELSI) of portable MRI (pMRI). Our interdisciplinary Working Group (WG) previously identified 15 core ELSI challenges associated with pMRI research and recommended solutions. In this article, we distill those detailed recommendations into a Portable MRI Research ELSI Checklist that offers practical operational guidance for researchers contemplating using this technology. Paper link: https://www.cambridge.org/core/journals/journal-of-law-medicine-and-ethics/article/conducting-research-with-highly-portable-mri-in-community-settings-a-practical-guide-to-navigating-ethical-issues-and-elsi-checklist/0C7A788A41C1FA0D85E96CE27352C591 Octoberfest mobile scanning: https://www.nejm.org/doi/full/10.1056/NEJMc2306490

Human intraparietal sulcal morphology relates to individual differences in language and memory performance The sulco-gyral pattern is a qualitative feature of the cortical anatomy that is determined in utero, stable throughout lifespan and linked to brain function. The intraparietal sulcus (IPS) is a nodal associative brain area, but the relation between its morphology and cognition is largely unknown. By labelling the left and right IPS of 390 healthy participants into two patterns, according to the presence or absence of a sulcus interruption, here we demonstrate a strong association between the morphology of the right IPS and performance on memory and language tasks. We interpret the results as a morphological advantage of a sulcus interruption, probably due to the underlying white matter organization. The right-hemisphere specificity of this effect emphasizes the neurodevelopmental and plastic role of sulcus morphology in cognition prior to lateralisation processes. The results highlight a promising area of investigation on the relationship between cognitive performance, sulco-gyral pattern and white matter bundles. Paper link: https://www.nature.com/articles/s42003-024-06175-9

Paper link: https://www.eneuro.org/content/11/5/ENEURO.0408-23.2024 Abstract Singing-based treatments of aphasia can improve language outcomes, but the neural benefits of group-based singing in aphasia are unknown. Here, we set out to determine the structural neuroplasticity changes underpinning group-based singing-induced treatment effects in chronic aphasia. Twenty-eight patients with at least mild nonfluent poststroke aphasia were randomized into two groups that received a 4-month multicomponent singing intervention (singing group) or standard care (control group). High-resolution T1 images and multishell diffusion-weighted MRI data were collected in two time points (baseline/5 months). Structural gray matter (GM) and white matter (WM) neuroplasticity changes were assessed using language network region of interest-based voxel-based morphometry (VBM) and quantitative anisotropy-based connectometry, and their associations to improved language outcomes (Western Aphasia Battery Naming and Repetition) were evaluated. Connectometry analyses showed that the singing group enhanced structural WM connectivity in the left arcuate fasciculus (AF) and corpus callosum as well as in the frontal aslant tract (FAT), superior longitudinal fasciculus, and corticostriatal tract bilaterally compared with the control group. Moreover, in VBM, the singing group showed GM volume increase in the left inferior frontal cortex (Brodmann area 44) compared with the control group. The neuroplasticity effects in the left BA44, AF, and FAT correlated with improved naming abilities after the intervention. These findings suggest that in the poststroke aphasia group, singing can bring about structural neuroplasticity changes in left frontal language areas and in bilateral language pathways, which underpin treatment-induced improvement in speech production.

Paper link https://academic.oup.com/brain/article/146/3/1212/6661441?login=false Abstract There are currently no non-invasive imaging methods available for astrogliosis assessment or mapping in the central nervous system despite its essential role in the response to many disease states, such as infarcts, neurodegenerative conditions, traumatic brain injury and infection. Multidimensional MRI is an increasingly employed imaging modality that maximizes the amount of encoded chemical and microstructural information by probing relaxation (T1 and T2) and diffusion mechanisms simultaneously. Here, we harness the exquisite sensitivity of this imagining modality to derive a signature of astrogliosis and disentangle it from normative brain at the individual level using machine learning. We investigated ex vivo cerebral cortical tissue specimens derived from seven subjects who sustained blast-induced injuries, which resulted in scar-border forming astrogliosis without being accompanied by other types of neuropathological abnormality, and from seven control brain donors. By performing a combined post-mortem radiology and histopathology correlation study we found that astrogliosis induces microstructural and chemical changes that are robustly detected with multidimensional MRI, and which can be attributed to astrogliosis because no axonal damage, demyelination or tauopathy were histologically observed in any of the cases in the study. Importantly, we showed that no one-dimensional T1, T2 or diffusion MRI measurement can disentangle the microscopic alterations caused by this neuropathology. Based on these findings, we developed a within-subject anomaly detection procedure that generates MRI-based astrogliosis biomarker maps ex vivo, which were significantly and strongly correlated with co-registered histological images of increased glial fibrillary acidic protein deposition. Our findings elucidate the underpinning of MRI signal response from astrogliosis, and the demonstrated high spatial sensitivity and specificity in detecting reactive astrocytes at the individual level, and if reproduced in vivo, will significantly impact neuroimaging studies of injury, disease, repair and aging, in which astrogliosis has so far been an invisible process radiologically.

Paper link: https://academic.oup.com/brain/advance-article/doi/10.1093/brain/awae343/7916407 Abstract Although both central and peripheral inflammation have been observed consistently in depression, the relationship between the two remains obscure. Extra-axial immune cells may play a role in mediating the connection between central and peripheral immunity. This study investigates the potential roles of calvarial bone marrow and parameningeal spaces in mediating interactions between central and peripheral immunity in depression. PET was used to measure regional TSPO expression in the skull and parameninges as a marker of inflammatory activity. This measure was correlated with brain TSPO expression and peripheral cytokine concentrations in a cohort enriched for heightened peripheral and central immunity comprising 51 individuals with depression and 25 healthy controls. The findings reveal a complex relationship between regional skull TSPO expression and both peripheral and central immunity. Facial and parietal skull bone TSPO expression showed significant associations with both peripheral and central immunity. TSPO expression in the confluence of sinuses was also linked to both central and peripheral immune markers. Group-dependent elevations in TSPO expression within the occipital skull bone marrow were also found to be significantly associated with central inflammation. Significant associations between immune activity within the skull, parameninges, parenchyma and periphery highlight the role of the skull bone marrow and venous sinuses as pivotal sites for peripheral and central immune interactions.

Paper link: https://www.bmj.com/content/387/bmj-2024-081948 Objective To evaluate the cognitive abilities of the leading large language models and identify their susceptibility to cognitive impairment, using the Montreal Cognitive Assessment (MoCA) and additional tests. Design Cross sectional analysis. Setting Online interaction with large language models via text based prompts. Participants Publicly available large language models, or “chatbots”: ChatGPT versions 4 and 4o (developed by OpenAI), Claude 3.5 “Sonnet” (developed by Anthropic), and Gemini versions 1 and 1.5 (developed by Alphabet). Assessments The MoCA test (version 8.1) was administered to the leading large language models with instructions identical to those given to human patients. Scoring followed official guidelines and was evaluated by a practising neurologist. Additional assessments included the Navon figure, cookie theft picture, Poppelreuter figure, and Stroop test. Main outcome measures MoCA scores, performance in visuospatial/executive tasks, and Stroop test results. Results ChatGPT 4o achieved the highest score on the MoCA test (26/30), followed by ChatGPT 4 and Claude (25/30), with Gemini 1.0 scoring lowest (16/30). All large language models showed poor performance in visuospatial/executive tasks. Gemini models failed at the delayed recall task. Only ChatGPT 4o succeeded in the incongruent stage of the Stroop test. Conclusions With the exception of ChatGPT 4o, almost all large language models subjected to the MoCA test showed signs of mild cognitive impairment. Moreover, as in humans, age is a key determinant of cognitive decline: “older” chatbots, like older patients, tend to perform worse on the MoCA test. These findings challenge the assumption that artificial intelligence will soon replace human doctors, as the cognitive impairment evident in leading chatbots may affect their reliability in medical diagnostics and undermine patients’ confidence.

paper link: https://www.nature.com/articles/s41592-024-02472-7 In vivo imaging of the human brain with the Iseult 11.7-T MRI scanner The understanding of the human brain is one of the main scientific challenges of the twenty-first century. In the early 2000s, the French Atomic Energy Commission launched a program to conceive and build a human magnetic resonance imaging scanner operating at 11.7 T. We have now acquired human brain images in vivo at such a magnetic field. We deployed parallel transmission tools to mitigate the radiofrequency field inhomogeneity problem and tame the specific absorption rate. The safety of human imaging at such high field strength was demonstrated using physiological, vestibular, behavioral and genotoxicity measurements on the imaged volunteers. Our technology yields T2 and T2*-weighted images reaching mesoscale resolutions within short acquisition times and with a high signal and contrast-to-noise ratio.