I always assumed that brain function had to line up with cytoarchitectonics.

It turns out I was wrong.

Human cortex, especially PFC, is tiled by chains of functional patches that subdivide and interlink architectonic areas into parallel processing streams.

www.biorxiv.org/content/10.6...

Wow, congratulations, Helena 👏. This is awesome 🎈

Infra-slow brain-heart-gut electrophysiological interactions reveal a coordinated multisystem physiological network in humans www.biorxiv.org/content/10.64898/2026.04...

The supply of blood to brain tissue is thought to depend on the overall neural activity in that tissue, and this dependence is thought to differ across brain regions and across brain states. However, studies supporting these views have measured neural activity as a bulk quantity and related it to blood supply following disparate events in different regions. Here we measure fluctuations in neuronal activity and blood volume across the mouse brain, and find that their relationship is consistent across brain states and brain regions but differs in two opposing brainwide neural populations. Functional ultrasound imaging (fUSI) revealed that whisking, a marker of arousal, is associated with brainwide fluctuations in blood volume. Simultaneous fUSI and Neuropixels recordings showed that neurons that increase activity with whisking have distinct haemodynamic response functions compared with those that decrease activity. Their summed contributions predicted blood volume across states.Brainwide Neuropixels recordings revealed that these opposing populations coexist in the entire brain. Their differing contributions to blood volume largely explain the apparent differences in blood volume fluctuations across regions. The mouse brain thus contains two neural populations with opposite relations to brain state and distinct relationships to blood supply, which together account for brainwide fluctuations in blood volume.

How does blood flow relate to brain activity? We discovered that it reflects two neural populations affected oppositely by arousal. Together, they explain neurovascular coupling in all brain regions and brain states!

Out today in Nature: rdcu.be/fdC2A

@uclbrainscience.bsky.social

Delivering tactile stimuli via mobile browsers: A method for remote multisensory research - Behavior Research Methods Online methods are becoming an essential part of the behavioral scientist’s toolkit. While the remote presentation of visual and auditory stimuli has been shown to be reasonably accurate (Bridges et a...

Do you want to use vibration stimuli in remote research studies? 👀 📳🤳🏼

Our latest paper in Behaviour Research Methods might be of interest to you!

Coauthors include: @kalvinroberts.bsky.social @peircej.bsky.social @multisensorylab.bsky.social

link.springer.com/article/10.3...

Delighted to share our discoveries about one of the brain's neurotransmitter systems:
www.biorxiv.org/content/10.6...

Together with colleagues at the @alleninstitute.org, we have learned a lot about a tiny cluster of neurons in the brainstem locus coeruleus (LC) that releases norepinephrine (NE). 1

Topographic organization of LC-NE axons.

This example neuron has a massive projection to the cerebral cortex, but you’ll notice it doesn’t go everywhere in the brain. By analyzing many individual neurons (below), we found a beautiful topographic organization: dorsal cells sent axons to the front of the brain, ventral cells to the back. 6

Want to explore connectivity & projection patterns yourself, like we do here? We released brain_street_view to let you pick any injection site in the Allen Connectivity Atlas and visualize where it projects in your favorite region of interest: github.com/Julie-Fabre/brain_street_view

GastroPy is now out in early beta! Please to share our Python toolbox for electrogastrography and stomach-brain coupling analyses. It includes tools for cleaning, visualising, and analysing EGG data, plus fMRI stomach-brain coupling workflows. Docs, code, and preprint below. osf.io/preprints/ps...

Ich finde, es ist zumindest ein Upgrade von "in Bearbeitung" oder "Begutachtung" 🙈

Microsoft Virtual Events Powered by Teams Microsoft Virtual Events Powered by Teams

What needs to be considered when assessing cortisol outside the laboratory? 🥼🧪

Together with Robert Richer (@richrobe.bsky.social), Luca Abel and Nicolas Rohleder, I will be presenting challenges and solutions in a free webinar organised by Tecan on 28 April, 4-5 PM.

More info and registration ⬇️

We develop a new TMS targeting algorithm and test it in an open label trial in a treatment-resistant depression population with high comorbidities. Preprints by @rubykong92.bsky.social Phern-Chern Tor
1. doi.org/10.1101/2025...
2. doi.org/10.64898/202...

Our new approach ...

Thanks. So, relaxation would be an absence of arousal? But it does not seem to affect the subjective experience of the intervention (absolute values are essentially the same), which is why I was wondering about the conclusion.

Interesting, thanks for sharing the thread! Was that also reflected in subjective ratings of relaxation? I took a quick look, but I was not sure if this was fully captured by the design.

The effect of glucose on cardiac reactivity to a standardized massage in healthy adults Cardiac reactivity reflects autonomic nervous system regulation, yet its determinants and modulators remain incompletely understood. Although glucose …

Very happy that our work on how glucose impacts cardiac reactivity to relaxation is now published #OpenAccess in the International Journal of Psychophysiology featuring a wonderful illustration by @sophieelschner.bsky.social !

🧃💆🫀

Short paper 🧵

Stormy and sunny skies (top) illustrate differing personal circumstances. A dial (centre) indicates emotion regulation ability that may vary between individuals. The heads of three individuals (bottom) contain many colored blocks that depict cortical components involved in emotion regulation. Credit: Ruien Wang.

Why do people vary in successfully managing their #emotions? This study shows how large-scale #brain organization predicts #emotion regulation success & lower daily distress, offering a holistic neurobiological framework @plosbiology.org 🧪 plos.io/486B6b5

An international mega-analysis of psychedelic drug effects on brain circuit function - Nature Medicine Analysis of neuroimaging datasets across five major psychedelics revealed a shared brain signature and provides a comprehensive insight into how these drugs reorganize brain architecture.

This paper has been a long time coming. Instead of reanalyzing the same old resting-state fMRI datasets, we combined nearly all datasets around the world. Note that we didn't exactly find indisputable evidence for "default mode network disintegration."
www.nature.com/articles/s41...

JAMA Psychiatry: RCT: A Ketogenic Diet for Treatment-Resistant Depression. Population: 26 men, 61 women, 1 nonbinary, mean age 42.1. Intervention: 88 participants randomized, 44 ketogenic diet group, 44 phytochemical group. Graph showing PHQ-9 score vs time since randomization.

A 6-week #KetogenicDiet produced modest improvement in depressive symptoms vs control in adults with #TreatmentResistantDepression, with no difference in secondary outcomes and uncertain clinical relevance. ja.ma/4sTC96t

Major Depressive Disorder is characterized by a disrupted heart-brain relationship, where cardiac dysregulation (faster heart rate, reduced HRV) is linked to reduced insula gray matter volume.

🧵 I gave Claude two things: a short paper (doi.org/10.1073/pnas...) and a raw behavioural dataset with 3 lines of variable descriptions.

Then I asked it to fit three computational RL models described only by equations in the manuscript. No code, no toolbox, no guidance on the fitting procedure. 1/3

Opportunities and pitfalls of data contextualization in neuroimaging - Nature Reviews Neuroscience Despite rapid exploitation of the opportunities that contextualization of brain maps affords, potential limitations have received little attention. In this Roadmap, Royer et al. provide practical guid...

Correlating brain maps across datasets is everywhere in neuroimaging. Here we ask: when you contextualize a brain map against genes, metabolism, or connectivity... What can you really conclude? How can we do better? We explore these questions here: tinyurl.com/2dudkevc

New paper in Molecular Psychiatry:

In patients with anxiety + depression, targeting a novel “anxiosomatic” circuit (dmPFC) outperforms standard dlPFC for anxiety—and is equally effective for depression.

Free link: rdcu.be/faL22
Full link: lnkd.in/e4WZTncu

But the bigger story is the pipeline
1/n

Congratulations, Johannes 👏. Exciting work.

Low-intensity focused ultrasound to human amygdala reveals a causal role in ambiguous emotion processing and alters local and network activity The amygdala shows abnormal metabolism in depression, a disorder marked by altered emotion, motivation, and learning. Yet its causal role in these pro…

Very happy our first paper using ultrasound stimulation (TUS) to stimulate the human amygdala (BLA) got out in @cp-neuron.bsky.social today! 🎉🥳🔊Great FUN with co-first authors @mirunmigyu.bsky.social @lilweb.bsky.social in @mkflugge.bsky.social 's lab!
www.sciencedirect.com/science/arti...

Immersive NREM2 dreaming preserves subjective sleep depth against declining sleep pressure Perceived sleep depth is generally thought to reflect reduced brain activity. This study shows that this relationship weakens during dreaming, suggesting that dreaming helps sustain the subjective exp...

Vivid dreaming makes sleep feel deeper journals.plos.org/plosbiology/...

How do we define "good" fMRI data? Especially with resting state, there are circularity risks if we evaluate data quality as showing the networks we expect to see. Javier Gonzalez-Castillo (& me & others) developed pBOLD, a new metric that uses multi-echo info. www.biorxiv.org/content/10.6... 1/8

Role of dopamine in the development of impaired counterregulation and impaired awareness of hypoglycemia Macon and Devore et al. developed a rodent model of hypoglycemia-associated autonomic failure (HAAF). They demonstrate that the dopamine antagonist, metoclopramide, restores normal awareness and counterregulatory responses to hypoglycemia. These findings identify dopamine signaling as an important mediator of HAAF and dopamine antagonism as a potential treatment strategy for HAAF.

Online now: Role of dopamine in the development of impaired counterregulation and impaired awareness of hypoglycemia

What's the relationship of apathy to depression and anhedonia? Sijia Zhao led our work on this to show that many individuals qualify for the diagnostic criteria of 2 or even 3 of these syndromes. But factor analysis reveals that the syndromes are highly dissociable
jnnp.bmj.com/content/earl...

Symptom-specific genetics reveal heterogeneity within major depressive disorder Background Major Depressive Disorder (MDD) is clinically and biologically heterogeneous. Here, we leveraged the genetics of individual depressive symptoms to dissect the disorder’s underlying heterogeneity. Methods We utilized the BIObanks Netherlands Internet Collaboration (BIONIC). A series of genome-wide association studies (effective- N range: 14,407 - 47,110) compared controls (N=48,286) with partially different subsets of lifetime MDD cases (range: 3,892–15,577), each endorsing one of 12 individual DSM-based depressive symptoms. Results were combined in genetic correlations that informed factor analyses with Genomic Structural Equation Modeling, decomposing underlying MDD liability dimensions. The identified factors were assessed and further characterized using multivariate regression of neurodevelopmental/psychiatric and cardiometabolic traits. Results All symptoms demonstrated substantial SNP-based heritability ( h²SNP: 0.088 – 0.127). Despite high between-symptom genetic correlations, factor analyses yielded two highly correlated ( rg =0.85) but still distinct latent factors: factor 1 (F1), capturing appetite/weight loss, insomnia, guilt/worthlessness, psychomotor slowing and suicidality, and factor 2 (F2), reflecting concentration problems, anhedonia, depressed mood, appetite/weight gain and fatigue. Overall, F1 had a stronger genetic overlap with neurodevelopmental/psychiatric phenotypes (e.g., autism: standardized estimate β =0.45, p =4.49×10⁻⁴; schizophrenia: β =0.40, p =1.73×10⁻⁴), while F2 significantly overlapped with cardiometabolic traits (e.g., metabolic syndrome: β =0.44, p =8.69×10⁻⁴; coronary artery disease: β =0.31, p =0.009). Conclusions We identified two genetic dimensions of MDD, each linked to partially distinct clinical manifestations and underlying biology, with one reflecting neurodevelopmental/psychiatric liabilities and the other capturing a strong cardiometabolic vulnerability. Disentangling such distinct dimensions may help guide patient stratification and targeted treatment, thereby advancing precision psychiatry. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement YM is partially supported by Amsterdam UMC StarterGrant (Ronde2), Amsterdam Neuroscience (PoC funding 2024-2026), and the Immuno MIND consortium, funded by UK Research and Innovation as part of the UK national Mental Health Platform. HMvL was supported in part by a VENI grant from the Talent Program of the Netherlands Organization of Scientific Research (NWO-ZonMW 09150161810021) and by NIMH grant R01MH125902. We are very grateful to everyone who participated in this research or worked on this project and its contributing studies. Funding for the BIONIC project was awarded to Dorret Boomsma and Brenda Penninx by the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL: 184.021.007; 184.033.111). Below are cohort-specific funding declarations and acknowledgements. We would like to thank the research participants and employees of 23andMe for making this work possible. Lifelines The Lifelines initiative has been made possible by subsidy from the Dutch Ministry of Health, Welfare and Sport, the Dutch Ministry of Economic Affairs, the University Medical Center Groningen (UMCG), Groningen University and the Provinces in the North of the Netherlands (Drenthe, Friesland, Groningen). NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation. VENI grant from the Talent Program of the Netherlands Organisation for Scientific Research (NWO-ZonMW 09150161810021). We thank Trynke de Jong for the contribution to Lifelines data collection. We thank Martje Bos and Victoria Trindade Pons for their help in preparing the Lifelines phenotype data. MooDFOOD European Union FP7 funding for MooDFOOD Project Multi-country cOllaborative project on the rOle of Diet, FOod-related behaviour, and Obesity in the prevention of Depression (grant agreement no. 613598). TRAILS Participating centers of the TRacking Adolescents Individual Lives Survey (TRAILS) include the University Medical Center and University of Groningen, the University of Utrecht, the Radboud Medical Center Nijmegen, and the Parnassia Group, all in the Netherlands. TRAILS has been financially supported by various grants from the Netherlands Organization for Scientific Research NWO (Medical Research Council program grant GB-MW 940-38-011; ZonMW Brainpower grant 100-001-004; ZonMw Risk Behavior and Dependence grant 60-60600-97-118; ZonMw Culture and Health grant 261-98-710; Social Sciences Council medium-sized investment grants GB-MaGW 480-01-006 and GB-MaGW 480-07-001; Social Sciences Council project grants GB-MaGW 452-04-314 and GB-MaGW 452-06-004; ZonMw Longitudinal Cohort Research on Early Detection and Treatment in Mental Health Care grant 636340002; NWO large-sized investment grant 175.010.2003.005; NWO Longitudinal Survey and Panel Funding 481-08-013 and 481-11-001; NWO Vici 016.130.002, 453-16-007/2735, and Vi.C.191.021; NWO Gravitation 024.001.003), the Dutch Ministry of Justice (WODC), the European Science Foundation (EuroSTRESS project FP-006), the European Research Council (ERC-2017-STG-757364 and ERC-CoG-2015-681466), Biobanking and Biomolecular Resources Research Infrastructure BBMRI-NL (CP 32), the Gratama foundation, the Jan Dekker foundation, the participating universities, and Accare. Statistical analyses are carried out on the Genetic Cluster Computer (http://www.geneticcluster.org), which is financially supported by the Netherlands Scientific Organization (NWO 480-05-003) along with a supplement from the Dutch Brain Foundation. LASA The Longitudinal Aging Study Amsterdam is largely supported by grants from the Netherlands Ministry of Health, Welfare and Sport, Directorate of Long-Term Care. NQplus NQplus was core funded by ZonMw (ZonMw, Grant 91110030); add-on funding was provided by ZonMW Gezonde Voeding (ZonMw, Grant 115100007), BBMRI (Grant BBMRI-NL RP9 and CP2011-38) and Wageningen University and Research. MOTAR The MOTAR study was funded by NWO VICI grant number 91811602 of B.W.J.H. Penninx. NWO had no role in the design of the study, the collection, analysis and interpretation of the data, or in the preparation, review, or approval of the manuscript. The Hoorn Studies The GWAS in the Hoorn studies was supported by the Amsterdam University Medical Center, a grant from the Foundation for the National Institutes of Health through the Accelerating Medicines Partnership (no. HART17AMP) and the Dutch String of Pearls Initiative. We appreciate the cooperation of the participants and research assistants who have been involved in the Hoorn Study and New Hoorn Study. We would like to thank Tootje Hoovers and Jolanda Bosman as well as all the researchers previously involved for the organization of both studies. Netherlands Twin Register NTR acknowledges funding from the Netherlands Organization for Scientific Research (NWO): Biobanking and Biomolecular Research Infrastructure (BBMRI-NL, 184.033.111) and the BBMRI-NL funded BIOS Consortium (NWO184.021.007); The Netherlands Twin Register is supported by grant NWO 480-15-001/674: Netherlands Twin Registry Repository: researching the interplay between genome and environment, the Avera Institute for Human Genetics and by multiple grants from the Netherlands Organization for Scientific Research (NWO). Genotyping was made possible by grants from NWO/SPI 56-464-14192, Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health, Rutgers University Cell and DNA Repository (NIMH U24 MH 068457-06), the Avera Institute, Sioux Falls (USA) and the National Institutes of Health (NIH R01 HD042157-01A1, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995) and European Research Council (ERC-230374). DIB acknowledges the Royal Netherlands Academy of Science Professor Award (PAH/6635). Nijmegen Biomedical Study The Nijmegen Biomedical Study is a population-based survey conducted at the Department for Health Evidence and the Department of Laboratory Medicine of the Radboud university medical center. Principal investigators of the Nijmegen Biomedical Study are L.A.L.M. Kiemeney, A.L.M. Verbeek, D.W. Swinkels en B. Franke. Doetinchem Cohort Study The Doetinchem Cohort Study is supported by the Dutch Ministry of Health, Welfare and Sport and the National Institute for Public Health and the Environment. We thank the respondents, epidemiologists and fieldworkers of the Municipal Health Service in Doetinchem for their contribution to the data collection for this study. The authors want to acknowledge the logistic management which was provided by P Vissink, and the data managers J van der Laan, R J de Kleine, I Toxopeus. Further, we thank all (senior) researchers who contributed to the data for collection, in particular in (alphabetical order): J M A de Boer, H B Bueno de Mesquita, P Engelfriet, G C Herber-Gast, G Hulsegge, D Kromhout, L Launer, A C J Nooyens, M C Ocke, S H van Oostrom, K Proper, J C Seidell, H A Smit, W G C Wendel-Vos. NESDA & NESDAsib The infrastructure for the NESDA study (www.nesda.nl) is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (ZonMw, grant number 10-0001002) and financial contributions by participating universities and mental health care organizations (VU University Medical Center, GGZ inGeest, Leiden University Medical Center, Leiden University, GGZ Rivierduinen, University Medical Center Groningen, University of Groningen, Lentis, GGZ Friesland, GGZ Drenthe, Rob Giel Onderzoekscentrum). NESDO The infrastructure for NESDO is funded through the Fonds NutsOhra, Stichting tot Steun VCVGZ, NARSAD The Brain and Behaviour Research Fund, and the participating universities and mental health care organizations (VU University Medical Center, Leiden University Medical Center, University Medical Center Groningen, Radboud University Nijmegen Medical Center, and GGZ inGeest, GGNet, GGZ Nijmegen, GGZ Rivierduinen, Lentis, and Parnassia). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All relevant ethical regulations for working with human participants were followed in the conduct of the study, and written informed consent was obtained from all participants. The Medical Ethics Review Committee of the VU University Medical Center (IRB00002991) waived ethical approval for this work, 2014.449. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Summary statistics and analysis code will be made publicly available upon publication.

📣 Preprint: "Symptom-specific genetics reveal heterogeneity within major depressive disorder" led by @goulaan.bsky.social. We used #genetics of individual #depression symptoms from the #BIONIC 🇳🇱 project to decompose #MDD. bit.ly/3Nt43qA

Work by our excellent @neuromadlab.bsky.social team, led by @lhkal.bsky.social and @akuehnel.bsky.social.