The Representation of Object Distance: Evidence from Neuroimaging and Neuropsychology

Perceived distance in two-dimensional (2D) images relies on monocular distance cues. Here, we examined the representation of perceived object distance using a continuous carry-over adaptation design for fMRI. The task was to look at photographs of objects and make a judgment as to whether or not the item belonged in the kitchen. Importantly, this task was orthogonal to the variable of interest: the object's perceived distance from the viewer. In Experiment 1, whole brain group analyses identified bilateral clusters in the superior occipital gyrus (approximately area V3/V3A) that showed parametric adaptation to relative changes in perceived distance. In Experiment 2, retinotopic analyses confirmed that area V3A/B reflected the greatest magnitude of response to monocular changes in perceived distance. In Experiment 3, we report that the functional activations overlap with the occipito-parietal lesions in a patient with impaired distance perception, showing that the same regions monitor implied (2D) and actual (three-dimensional) distance. These data suggest that distance information is automatically processed even when it is task-irrelevant and that this process relies on superior occipital areas in and around area V3A

The social cerebellum: A large-scale investigation of functional and structural specificity and connectivity

The cerebellum has been traditionally disregarded in relation to nonmotor functions, but recent findings indicate it may be involved in language, affective processing, and social functions. Mentalizing, or Theory of Mind (ToM), is the ability to infer mental states of others and this skill relies on a distributed network of brain regions. Here, we leveraged large-scale multimodal neuroimaging data to elucidate the structural and functional role of the cerebellum in mentalizing. We used functional activations to determine whether the cerebellum has a domain-general or domain-specific functional role, and effective connectivity and probabilistic tractography to map the cerebello-cerebral mentalizing network. We found that the cerebellum is organized in a domain-specific way and that there is a left cerebellar effective and structural lateralization, with more and stronger effective connections from the left cerebellar hemisphere to the right cerebral mentalizing areas, and greater cerebello-thalamo-cortical and cortico-ponto-cerebellar streamline counts from and to the left cerebellum. Our study provides novel insights to the network organization of the cerebellum, an overlooked brain structure, and mentalizing, one of humans\u27 most essential abilities to navigate the social world

State-selective electron transfer and ionization in collisions of highly charged ions with ground-state Na(3s) and laser-excited Na∗(3 p)

Single electron transfer and ionization in collisions of N 5 + and Ne 8 + with ground state Na(3s) and laser excited Na∗(3p) are investigated both experimentally and theoretically at collision energies from 1 to 10 keV/amu, which includes the classical orbital velocity of the valence electron. State-selective partial cross sections are obtained using recoil-ion momentum spectroscopy in combination with a magneto-optically cooled Na atom target. A strong dependence of the cross sections on the collision energy is observed. In general, both the relative magnitude and the energy dependence are found to be in good agreement with classical-trajectory Monte Carlo calculations.Fil: Blank, Ingrid. University of Groningen; Países BajosFil: Otranto, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; ArgentinaFil: Meinema, C.. University of Groningen; Países BajosFil: Olson, R. E.. University of Missouri; Estados UnidosFil: Hoekstra, R.. University of Groningen; Países Bajo

A transformer model for learning spatiotemporal contextual representation in fMRI data

AbstractRepresentation learning is a core component in data-driven modeling of various complex phenomena. Learning a contextually informative representation can especially benefit the analysis of fMRI data because of the complexities and dynamic dependencies present in such datasets. In this work, we propose a framework based on transformer models to learn an embedding of the fMRI data by taking the spatiotemporal contextual information in the data into account. This approach takes the multivariate BOLD time series of the regions of the brain as well as their functional connectivity network simultaneously as the input to create a set of meaningful features that can in turn be used in various downstream tasks such as classification, feature extraction, and statistical analysis. The proposed spatiotemporal framework uses the attention mechanism as well as the graph convolution neural network to jointly inject the contextual information regarding the dynamics in time series data and their connectivity into the representation. We demonstrate the benefits of this framework by applying it to two resting-state fMRI datasets, and provide further discussion on various aspects and advantages of it over a number of other commonly adopted architectures

Improved Proper Name Recall in Aging after Electrical Stimulation of the Anterior Temporal Lobes

Evidence from neuroimaging and neuropsychology suggests that portions of the anterior temporal lobes (ATLs) play a critical role in proper name retrieval. We previously found that anodal transcranial direct current stimulation (tDCS) to the ATLs improved retrieval of proper names in young adults (Ross et al., 2010). Here we extend that finding to older adults who tend to experience greater proper-naming deficits than young adults. The task was to look at pictures of famous faces or landmarks and verbally recall the associated proper name. Our results show a numerical improvement in face naming after left or right ATL stimulation, but a statistically significant effect only after left-lateralized stimulation. The magnitude of the enhancing effect was similar in older and younger adults but the lateralization of the effect differed depending on age. The implications of these findings for the use of tDCS as tool for rehabilitation of age-related loss of name recall are discussed

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Connecting Earth Observation to High-Throughput Biodiversity Data

There is much interest in using Earth Observation (EO) technology to track biodiversity, ecosystem functions, and ecosystem services, understandable given the fast pace of biodiversity loss. However, because most biodiversity is invisible to EO, EO-based indicators could be misleading, which can reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing, and modern ecological modelling to extract much more of the information available in EO data. This approach is achievable now, 62 offering efficient and near-real time monitoring of management impacts on biodiversity and its functions and services

Connecting Earth observation to high-throughput biodiversity data

Understandably, given the fast pace of biodiversity loss, there is much interest in using Earth observation technology to track biodiversity, ecosystem functions and ecosystem services. However, because most biodiversity is invisible to Earth observation, indicators based on Earth observation could be misleading and reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing and modern ecological modelling to extract much more of the information available in Earth observation data. This approach is achievable now, offering efficient and near-real-time monitoring of management impacts on biodiversity and its functions and services

Efficacy and safety of larotrectinib in TRK fusion-positive primary central nervous system tumors

BACKGROUND Larotrectinib is a first-in-class, highly selective tropomyosin receptor kinase (TRK) inhibitor approved to treat adult and pediatric patients with TRK fusion-positive cancer. The aim of this study was to evaluate the efficacy and safety of larotrectinib in patients with TRK fusion-positive primary central nervous system (CNS) tumors. METHODS Patients with TRK fusion-positive primary CNS tumors from two clinical trials (NCT02637687, NCT02576431) were identified. The primary endpoint was investigator-assessed objective response rate (ORR). RESULTS As of July 2020, 33 patients with TRK fusion-positive CNS tumors were identified (median age: 8.9 years; range: 1.3-79.0). The most common histologies were high-grade glioma (HGG; n = 19) and low-grade glioma (LGG; n = 8). ORR was 30% (95% confidence interval [CI]: 16-49) for all patients. In all patients, the 24-week disease control rate was 73% (95% CI: 54-87). Twenty-three of 28 patients (82%) with measurable disease had tumor shrinkage. The 12-month rates for duration of response, progression-free survival, and overall survival were 75% (95% CI: 45-100), 56% (95% CI: 38-74), and 85% (95% CI: 71-99), respectively. Median time to response was 1.9 months (range 1.0-3.8 months). Duration of treatment ranged from 1.2-31.3+ months. Treatment-related adverse events were reported for 20 patients, with Grade 3-4 in 3 patients. No new safety signals were identified. CONCLUSIONS In patients with TRK fusion-positive CNS tumors, larotrectinib demonstrated rapid and durable responses, high disease control rate, and a favorable safety profile