Resolved magnetic-field structure and variability near the event horizon of Sagittarius A* Near a black hole, differential rotation of a magnetized accretion disk is thought to produce an instability that amplifies weak magnetic fields, driving accretion and outflow. These magnetic fields would naturally give rise to the observed synchrotron emission in galaxy cores and to the formation of relativistic jets, but no observations to date have been able to resolve the expected horizon-scale magnetic-field structure. We report interferometric observations at 1.3-millimeter wavelength that spatially resolve the linearly polarized emission from the Galactic Center supermassive black hole, Sagittarius A*. We have found evidence for partially ordered magnetic fields near the event horizon, on scales of ~6 Schwarzschild radii, and we have detected and localized the intrahour variability associated with these fields. Some relevant links: https://www.youtube.com/watch?v=Q1bSDnuIPbo https://www.youtube.com/watch?v=Q1bSDnuIPbo 10.1126/science.aac7087

Paper link: https://www.science.org/doi/10.1126/sciadv.abj7892 We present the first three-dimensional (3D) concordance maps of cyto- and fiber architecture of the human brain, combining histology, immunohistochemistry, and 7-T quantitative magnetic resonance imaging (MRI), in two individual specimens. These 3D maps each integrate data from approximately 800 microscopy sections per brain, showing neuronal and glial cell bodies, nerve fibers, and interneuronal populations, as well as ultrahigh-field quantitative MRI, all coaligned at the 200-μm scale to the stacked blockface images obtained during sectioning. These unprecedented 3D multimodal datasets are shared without any restrictions and provide a unique resource for the joint study of cell and fiber architecture of the brain, detailed anatomical atlasing, or modeling of the microscopic underpinnings of MRI contrasts. #histology #MRI #anatomy #staining

Idiomatic expressions (IE) are groups of words whose meaning is different from the sum of their components. Neural mechanisms underlying their processing are still debated, especially regarding lateralization, structures involved, and whether this neural network is independent of the spoken language. To investigate the neural correlates of IE processing in healthy Spanish speakers. 21 native speakers of Spanish were asked to select one of 4 possible meanings for IE or literal sentences. fMRI scans were performed in a 3.0T scanner and processed by SPM 12 comparing IE vs. literal sentences. Laterality indices were calculated at the group level. IE activated a bilateral, slightly right-sided network comprising the pars triangularis and areas 9 and 10. In the left hemisphere (LH): the pars orbitalis, superior frontal, angular and fusiform gyrus. In the right hemisphere (RH): anterior insula, middle frontal, and superior temporal gyrus. This network reveals the importance of the RH, besides traditional LH areas, to comprehend IE. This agrees with the semantic coding model: the LH activates narrow semantic fields choosing one single meaning and ignoring others, and the RH detects distant semantic relationships, activating diffuse semantic fields. It is also in line with the configuration hypothesis: both meanings, literal and figurative, are executed simultaneously, until the literal meaning is definitively rejected and the figurative one is accepted. Processing IE requires the activation of fronto-temporal networks in both hemispheres. The results concur with previous studies in other languages, so these networks are independent from the spoken language. Understanding these mechanisms sheds light on IE processing difficulties in different clinical populations and must be considered when planning resective surgery. #language #semantic #laterality

Habitual use of GPS negatively impacts spatial memory during self-guided navigation Global Positioning System (GPS) navigation devices and applications have become ubiquitous over the last decade. However, it is unclear whether using GPS affects our own internal navigation system, or spatial memory, which critically relies on the hippocampus. We assessed the lifetime GPS experience of 50 regular drivers as well as various facets of spatial memory, including spatial memory strategy use, cognitive mapping, and landmark encoding using virtual navigation tasks. We first present cross-sectional results that show that people with greater lifetime GPS experience have worse spatial memory during self-guided navigation, i.e. when they are required to navigate without GPS. In a follow-up session, 13 participants were retested three years after initial testing. Although the longitudinal sample was small, we observed an important effect of GPS use over time, whereby greater GPS use since initial testing was associated with a steeper decline in hippocampal-dependent spatial memory. Importantly, we found that those who used GPS more did not do so because they felt they had a poor sense of direction, suggesting that extensive GPS use led to a decline in spatial memory rather than the other way around. These findings are significant in the context of society’s increasing reliance on GPS. Paper link: https://www.nature.com/articles/s41598-020-62877-0 #memory #navigation #visual

Reproducible brain-wide association studies require thousands of individuals Magnetic resonance imaging (MRI) has transformed our understanding of the human brain through well-replicated mapping of abilities to specific structures (for example, lesion studies) and functions1,2,3 (for example, task functional MRI (fMRI)). Mental health research and care have yet to realize similar advances from MRI. A primary challenge has been replicating associations between inter-individual differences in brain structure or function and complex cognitive or mental health phenotypes (brain-wide association studies (BWAS)). Such BWAS have typically relied on sample sizes appropriate for classical brain mapping4 (the median neuroimaging study sample size is about 25), but potentially too small for capturing reproducible brain–behavioural phenotype associations5,6. Here we used three of the largest neuroimaging datasets currently available—with a total sample size of around 50,000 individuals—to quantify BWAS effect sizes and reproducibility as a function of sample size. BWAS associations were smaller than previously thought, resulting in statistically underpowered studies, inflated effect sizes and replication failures at typical sample sizes. As sample sizes grew into the thousands, replication rates began to improve and effect size inflation decreased. More robust BWAS effects were detected for functional MRI (versus structural), cognitive tests (versus mental health questionnaires) and multivariate methods (versus univariate). Smaller than expected brain–phenotype associations and variability across population subsamples can explain widespread BWAS replication failures. In contrast to non-BWAS approaches with larger effects (for example, lesions, interventions and within-person), BWAS reproducibility requires samples with thousands of individuals. Paper link: https://www.nature.com/articles/s41586-022-04492-9

Uncovering the architecture of white matter axons is fundamental to the study of brain networks. We developed a method for quantifying axonal orientations at a resolution of ~15 micrometers. This method is based on the common Nissl staining technique for postmortem histological slices. Nissl staining reveals the spatial organization of glial cells along axons. Using structure tensor analysis, we leveraged this patterned organization to uncover local axonal orientation. We used Nissl-based structure tensor analysis to extract fine details of axonal architecture and demonstrated its applicability in multiple datasets of humans and nonhuman primates. Nissl-based structure tensor analysis can be used to compare fine-grained features of axonal architecture across species and is widely applicable to existing datasets. Paper link: https://www.science.org/doi/10.1126/science.abj7960 #Neuroccino #glial #oligodenrocyte #whitematter

We reviewed the preprint a year ago (Links to preprint discussion https://www.youtube.com/watch?v=YoOl5R9_7C8) now the paper was just published! Here is the update on it. Post-mortem MRI provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy, and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes - Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank release includes twenty-one distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen non-human primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies. Paper link: https://elifesciences.org/articles/73153 The other preprint we mentioned about tissue optimisation can be found here: https://www.biorxiv.org/content/10.1101/2021.12.13.472113v1.full.pdf #diffusion #MRI #comparative #postmortem

Mammalian taxonomies are conventionally defined by morphological traits and genetics. How species differ in terms of neural circuits and whether inter-species differences in neural circuit organization conform to these taxonomies is unknown. The main obstacle for the comparison of neural architectures have been differences in network reconstruction techniques, yielding species-specific connectomes that are not directly comparable to one another. Here we comprehensively chart connectome organization across the mammalian phylogenetic spectrum using a common reconstruction protocol. We analyze the mammalian MRI (MaMI) data set, a database that encompasses high-resolution ex vivo structural and diffusion magnetic resonance imaging (MRI) scans of 124 species across 12 taxonomic orders and 5 superorders, collected using a single protocol on a single scanner. We assess similarity between species connectomes using two methods: similarity of Laplacian eigenspectra and similarity of multiscale topological features. We find greater inter-species similarities among species within the same taxonomic order, suggesting the connectome organization recapitulates traditional taxonomies defined by morphology and genetics. While all connectomes retain hallmark global features and relative proportions of connection classes, inter-species variation is driven by local regional connectivity profiles. By encoding connectomes into a common frame of reference, these findings establish a foundation for investigating how neural circuits change over phylogeny, forging a link from genes to circuits to behaviour. Preprint in BioRxiv: https://www.biorxiv.org/content/10.1101/2022.03.11.483995v1 #evolution #tractography #interspecies #connectomics #connectomes #comparative #neuroimaging #anatomy

Today we discussed a YouTube video: https://youtu.be/-J-9Ct0oFMU In this video, we combine three different thought experiments into a single narrative. Through which, we explore topics related to consciousness, perception, and what it means to be you. The individual thought experiments are reinterpretations of John Searle's 'The Chinese Room,' Frank Jackson's 'Mary's Room,' and Gilbert Harman's 'Brain in a Vat.'

The attribution of sentience or consciousness to plants is currently a topic of debate among biologists and philosophers. The claim that plants are conscious is based on three arguments: (i) plants, like all living organisms, are sentient (biopsychism); (ii) there is a strong analogy between the phloem transport system of plants and the nervous system of animals; and (iii) plants are the cognitive equals of sentient animals. On the basis of a model of consciousness that spells out criteria for assigning sentience to a living organism and presents a diagnostic evolutionary marker of consciousness, we argue that these arguments are flawed and discuss some of the ethical issues they raise. https://www.ingentaconnect.com/content/imp/jcs/2021/00000028/f0020001/art00002 #consciousness #evolution #Sentience #cognition #plants #plantscience #ethics

Paperlink: https://wires.onlinelibrary.wiley.com/doi/10.1002/wcs.1578 Are trees like cortical areas and roots like a neuronal network? Find out more: Consciousness and cognition in plants Unlike animal behavior, behavior in plants is traditionally assumed to be completely determined either genetically or environmentally. Under this assumption, plants are usually considered to be noncognitive organisms. This view nonetheless clashes with a growing body of empirical research that shows that many sophisticated cognitive capabilities traditionally assumed to be exclusive to animals are exhibited by plants too. Yet, if plants can be considered cognitive, even in a minimal sense, can they also be considered conscious? Some authors defend that the quest for plant consciousness is worth pursuing, under the premise that sentience can play a role in facilitating plant's sophisticated behavior. The goal of this article is not to provide a positive argument for plant cognition and consciousness, but to invite a constructive, empirically informed debate about it. After reviewing the empirical literature concerning plant cognition, we introduce the reader to the emerging field of plant neurobiology. Research on plant electrical and chemical signaling can help shed light into the biological bases for plant sentience. To conclude, we shall present a series of approaches to scientifically investigate plant consciousness. In sum, we invite the reader to consider the idea that if consciousness boils down to some form of biological adaptation, we should not exclude a priori the possibility that plants have evolved their own phenomenal experience of the world. #cognition #plants #neurobiology #Consciousness

Today's #Neuroccino is introducing #MethodsMonday with a book on #python #visualisations! We discuss the book 'Scientific Visualization: Python + Matplotlib' written by Nicolas P. Rougier, a researcher at the LaBRI in #Bordeaux. #OpenScience book: https://www.labri.fr/perso/nrougier/scientific-visualization.html Links shared in the chat: https://www.linkedin.com/learning/python-essential-training-2018/welcome?u=76208058 https://www.coursera.org/specializations/python https://www.codecademy.com/ https://www.mooc.org/ #bookreview #python

A low-cost and shielding-free ultra-low-field brain MRI scanner Magnetic resonance imaging is a key diagnostic tool in modern healthcare, yet it can be cost-prohibitive given the high installation, maintenance and operation costs of the machinery. There are approximately seven scanners per million inhabitants and over 90% are concentrated in high-income countries. We describe an ultra-low-field brain MRI scanner that operates using a standard AC power outlet and is low cost to build. Using a permanent 0.055 Tesla Samarium-cobalt magnet and deep learning for cancellation of electromagnetic interference, it requires neither magnetic nor radiofrequency shielding cages. The scanner is compact, mobile, and acoustically quiet during scanning. We implement four standard clinical neuroimaging protocols (T1- and T2-weighted, fluid-attenuated inversion recovery like, and diffusion-weighted imaging) on this system, and demonstrate preliminary feasibility in diagnosing brain tumor and stroke. Such technology has the potential to meet clinical needs at point of care or in low and middle income countries. Paper link: https://www.nature.com/articles/s41467-021-27317-1 #MRI #ULF #lowfield #accessibility

NATURE TECHNOLOGY FEATURE Terra takes the pain out of ‘omics’ computing in the cloud The web-based tool allows scalable, user-friendly computation across multiple data sets Biomedical research produces massive amounts of data. But actually sharing them can be a challenge. “It doesn’t matter how enthusiastic you are about sharing data, actually sharing data is logistically a pain,” says Elinor Karlsson, a geneticist at the University of Massachusetts Chan Medical School in Worcester. Karlsson is a co-lead of the genetics core for the Dog Aging Project, a longitudinal study funded by the US National Institutes of Health (NIH), that aims to understand the genetics of healthy ageing by analysing several thousand genome sequences and health data from 100,000 pets. The project involves researchers from multiple institutions, all of whom need to be able to access and analyse the data. Conventional data-sharing strategies — such as shared servers, data downloads and even shipping physical disk drives — simply weren’t up to the task, Karlsson says. Advances in DNA sequencing mean it’s much easier to collect genetic data than it is to analyse them. As data sets have ballooned, Karlsson says, “We went from it being inconvenient to copy data to my server, to being cost-prohibitive. Institutions didn’t have the resources to keep up.” So the project turned to a system that could: Terra. #omics #genetics #python Paper link: https://www.nature.com/articles/d41586-021-03822-7

Face-selective neurons are observed in the primate visual pathway and are considered as the basis of face detection in the brain. However, it has been debated as to whether this neuronal selectivity can arise innately or whether it requires training from visual experience. Here, using a hierarchical deep neural network model of the ventral visual stream, we suggest a mechanism in which face-selectivity arises in the complete absence of training. We found that units selective to faces emerge robustly in randomly initialized networks and that these units reproduce many characteristics observed in monkeys. This innate selectivity also enables the untrained network to perform face-detection tasks. Intriguingly, we observed that units selective to various non-face objects can also arise innately in untrained networks. Our results imply that the random feedforward connections in early, untrained deep neural networks may be sufficient for initializing primitive visual selectivity. Paper link: https://www.nature.com/articles/s41467-021-27606-9 #paperpitch #facerecognition #neuralnetworks