The Kavli Foundation

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.

Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function.

Researchers propose building technologies to enable comprehensive mapping of neural circuit activity to understand brain function and disease.

The microbiome presents great opportunities for understanding and improving the world around us and elucidating the interactions that compose it. The microbiome also poses tremendous challenges for mapping and manipulating the entangled networks of interactions among myriad diverse organisms. Here, we describe the opportunities, technical needs, and potential approaches to address these challenges, based on recent and upcoming advances in measurement and control at the nanoscale and beyond. These technical needs will provide the basis for advancing the largely descriptive studies of the microbiome to the theoretical and mechanistic understandings that will underpin the discipline of microbiome engineering. We anticipate that the new tools and methods developed will also be more broadly useful in environmental monitoring, medicine, forensics, and other areas.

The brain is a complex system comprising a myriad of interacting elements, posing significant challenges in understanding its structure, function, and dynamics. Network science has emerged as a powerful tool for studying such intricate systems, offering a framework for integrating multiscale data and complexity. Here, we discuss the application of network science in the study of the brain, addressing topics such as network models and metrics, the connectome, and the role of dynamics in neural networks. We explore the challenges and opportunities in integrating multiple data streams for understanding the neural transitions from development to healthy function to disease, and discuss the potential for collaboration between network science and neuroscience communities. We underscore the importance of fostering interdisciplinary opportunities through funding initiatives, workshops, and conferences, as well as supporting students and postdoctoral fellows with interests in both disciplines. By uniting the network science and neuroscience communities, we can develop novel network-based methods tailored to neural circuits, paving the way towards a deeper understanding of the brain and its functions.

Abstract Interest in building dedicated quantum information science and engineering (QISE) education programs has greatly expanded in recent years. These programs are inherently convergent, complex, often resource intensive and likely require collaboration with a broad variety of stakeholders. In order to address this combination of challenges, we have captured ideas from many members in the community. This manuscript not only addresses policy makers and funding agencies (both public and private and from the regional to the international level) but also contains needs identified by industry leaders and discusses the difficulties inherent in creating an inclusive QISE curriculum. We report on the status of eighteen post-secondary education programs in QISE and provide guidance for building new programs. Lastly, we encourage the development of a comprehensive strategic plan for quantum education and workforce development as a means to make the most of the ongoing substantial investments being made in QISE.

As neuroscience projects increase in scale and cross international borders, different ethical principles, national and international laws, regulations, and policies for data sharing must be considered. These concerns are part of what is collectively called data governance. Whereas neuroscience data transcend borders, data governance is typically constrained within geopolitical boundaries. An international data governance framework and accompanying infrastructure can assist investigators, institutions, data repositories, and funders with navigating disparate policies. Here, we propose principles and operational considerations for how data governance in neuroscience can be navigated at an international scale and highlight gaps, challenges, and opportunities in a global brain data ecosystem. We consider how to approach data governance in a way that balances data protection requirements and the need for open science, so as to promote international collaboration through federated constructs such as the International Brain Initiative (IBI).

Working memory provides flexible storage of information in service of upcoming behavioral goals. Some models propose specific fixed loci and mechanisms for the storage of visual information in working memory, such as sustained spiking in parietal and prefrontal cortex during working memory maintenance. An alternative view is that information can be remembered in a flexible format that best suits current behavioral goals. For example, remembered visual information might be stored in sensory areas for easier comparison to future sensory inputs, or might be re-coded into a more abstract action-oriented format and stored in motor areas. Here, we tested this hypothesis using a visuo-spatial working memory task where the required behavioral response was either known or unknown during the memory delay period. Using functional magnetic resonance imaging (fMRI) and multivariate decoding, we found that there was less information about remembered spatial position in early visual and parietal regions when the required response was known versus unknown. Furthermore, a representation of the planned motor action emerged in primary somatosensory, primary motor, and premotor cortex during the same task condition where spatial information was reduced in early visual cortex. These results suggest that the neural networks supporting working memory can be strategically reconfigured depending on specific behavioral requirements during a canonical visual working memory paradigm.

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are two noninvasive methods commonly used to study neural mechanisms supporting visual attention in humans. Studies using these tools, which have complementary spatial and temporal resolutions, implicitly assume they index similar underlying neural modulations related to external stimulus and internal attentional manipulations. Accordingly, they are often used interchangeably for constraining understanding about the impact of bottom-up and top-down factors on neural modulations. To test this core assumption, we simultaneously manipulated bottom-up sensory inputs by varying stimulus contrast and top-down cognitive modulations by changing the focus of spatial attention. Each of the male and female subjects participated in both fMRI and EEG sessions performing the same experimental paradigm. We found categorically different patterns of attentional modulation on fMRI activity in early visual cortex and early stimulus-evoked potentials measured via EEG (e.g., the P1 component and steady-state visually-evoked potentials): fMRI activation scaled additively with attention, whereas evoked EEG components scaled multiplicatively with attention. However, across longer time scales, a contralateral negative-going potential and oscillatory EEG signals in the alpha band revealed additive attentional modulation patterns like those observed with fMRI. These results challenge prior assumptions that fMRI and early stimulus-evoked potentials measured with EEG can be interchangeably used to index the same neural mechanisms of attentional modulations at different spatiotemporal scales. Instead, fMRI measures of attentional modulations are more closely linked with later EEG components and alpha-band oscillations. Considered together, hemodynamic and electrophysiological signals can jointly constrain understanding of the neural mechanisms supporting cognition.

In the past 50 years, cosmology has gone from a field known for the errors being in the exponents to a precision science. The transformation—powered by ideas, technology, a paradigm shift, and culture change—has revolutionized our understanding of the Universe, with the Lambda cold dark matter (ΛCDM) paradigm as its crowning achievement. I chronicle the journey of precision cosmology and finish with thoughts about the next cosmological paradigm.

Foreword The Global Future Council on Neurotechnologies represents a diverse group of experts drawn from psychiatry, psychology, brain science, technology, advocacy and the public sector. They are passionate about stimulating the global conversation on mental healthcare gaps and the best ways to address those gaps through emerging technologies. Mental health disorders are among the […]

When a behaviorally relevant stimulus has been previously associated with reward, behavioral responses are faster and more accurate compared to equally relevant but less valuable stimuli. Conversely, task-irrelevant stimuli that were previously associated with a high reward can capture attention and distract processing away from relevant stimuli (e.g., seeing a chocolate bar in the pantry when you are looking for a nice, healthy apple). Although increasing the value of task-relevant stimuli systematically up-regulates neural responses in early visual cortex to facilitate information processing, it is not clear whether the value of task-irrelevant distractors influences behavior via competition in early visual cortex or via competition at later stages of decision-making and response selection. Here, we measured functional magnetic resonance imaging (fMRI) in human visual cortex while subjects performed a value-based learning task, and we applied a multivariate inverted encoding model (IEM) to assess the fidelity of distractor representations in early visual cortex. We found that the fidelity of neural representations related to task-irrelevant distractors increased when the distractors were previously associated with a high reward. This finding suggests that value-driven attentional capture begins with sensory modulations of distractor representations in early areas of visual cortex.

Abstract Current theories propose that the short-term retention of information in working memory (WM) and the recall of information from long-term memory (LTM) are supported by overlapping neural mechanisms in occipital and parietal cortex. However, the extent of the shared representations between WM and LTM is unclear. We designed a spatial memory task that allowed us to directly compare the representations of remembered spatial information in WM and LTM with carefully matched behavioral response precision between tasks. Using multivariate pattern analyses on functional magnetic resonance imaging data, we show that visual memories were represented in a sensory-like code in both memory tasks across retinotopic regions in occipital and parietal cortex. Regions in lateral parietal cortex also encoded remembered locations in both tasks, but in a format that differed from sensory-evoked activity. These results suggest a striking correspondence in the format of representations maintained in WM and retrieved from LTM across occipital and parietal cortex. On the other hand, we also show that activity patterns in nearly all parietal regions, but not occipital regions, contained information that could discriminate between WM and LTM trials. Our data provide new evidence for theories of memory systems and the representation of mnemonic content.

BACKGROUND: Neurofibromatosis Type 1 (NF1) is a genetic disorder that disrupts central nervous system development and neuronal function. Cognitively, NF1 is characterized by difficulties with executive control and visuospatial abilities. Little is known about the neural substrates underlying these deficits. The current study utilized Blood-Oxygen-Level-Dependent (BOLD) functional MRI (fMRI) to explore the neural correlates of spatial working memory (WM) deficits in patients with NF1. METHODS: = 33.08; 64% male) during an in-scanner visuo-spatial WM task. Whole brain functional and psycho-physiological interaction analyses were utilized to investigate neural activity and functional connectivity, respectively, during visuo-spatial WM performance. Participants also completed behavioral measures of spatial reasoning and verbal WM. RESULTS: Relative to healthy controls, participants with NF1 showed reduced recruitment of key components of WM circuitry, the left dorsolateral prefrontal cortex and right parietal cortex. In addition, healthy controls exhibited greater simultaneous deactivation between the posterior cingulate cortex (PCC) and temporal regions than NF1 patients. In contrast, NF1 patients showed greater PCC and bilateral parietal connectivity with visual cortices as well as between the PCC and the cerebellum. In NF1 participants, increased functional coupling of the PCC with frontal and parietal regions was associated with better spatial reasoning and WM performance, respectively; these relationships were not observed in controls. CONCLUSIONS: Dysfunctional engagement of WM circuitry, and aberrant functional connectivity of 'task-negative' regions in NF1 patients may underlie spatial WM difficulties characteristic of the disorder.

The Human BioMolecular Atlas Program (HuBMAP) aims to construct a 3D Human Reference Atlas (HRA) of the healthy adult body. Experts from 20+ consortia collaborate to develop a Common Coordinate Framework (CCF), knowledge graphs and tools that describe the multiscale structure of the human body (from organs and tissues down to cells, genes and biomarkers) and to use the HRA to characterize changes that occur with aging, disease and other perturbations. HRA v.2.0 covers 4,499 unique anatomical structures, 1,195 cell types and 2,089 biomarkers (such as genes, proteins and lipids) from 33 ASCT+B tables and 65 3D Reference Objects linked to ontologies. New experimental data can be mapped into the HRA using (1) cell type annotation tools (for example, Azimuth), (2) validated antibody panels or (3) by registering tissue data spatially. This paper describes HRA user stories, terminology, data formats, ontology validation, unified analysis workflows, user interfaces, instructional materials, application programming interfaces, flexible hybrid cloud infrastructure and previews atlas usage applications.

Although attention is known to improve the efficacy of sensory processing, the impact of attention on subjective visual appearance is still a matter of debate. Although recent studies suggest that attention can alter the appearance of stimulus contrast, others argue that these changes reflect response bias induced by attention cues. Here, we provide evidence that attention has effects on both appearance and response bias. In a comparative judgment task in which subjects reported whether the attended or unattended visual stimulus had a higher perceived contrast, attention induced substantial baseline-offset response bias as well as small but significant changes in subjective contrast appearance when subjects viewed near-threshold stimuli. However, when subjects viewed suprathreshold stimuli, baseline-offset response bias decreased and attention primarily changed contrast appearance. To address the possibility that these changes in appearance might be influenced by uncertainty due to the attended and unattended stimuli having similar physical contrasts, subjects performed an equality judgment task in which they reported if the contrast of the two stimuli was the same or different. We found that, although there were still attention-induced changes in contrast appearance at lower contrasts, the robust changes in contrast appearance at higher contrasts observed in the comparative judgment task were diminished in the equality judgment task. Together, these results suggest that attention can impact both response bias and appearance, and these two types of attention effects are differentially mediated by stimulus visibility and uncertainty. Collectively, these findings help constrain arguments about the cognitive penetrability of perception.

When viewing familiar stimuli (e.g., common words), processing is highly automatized such that it can interfere with the processing of incompatible sensory information. At least two mechanisms may help mitigate this interference. Early selection accounts posit that attentional processes filter out distracting sensory information to avoid conflict. Alternatively, late selection accounts hold that all sensory inputs receive full semantic analysis and that frontal executive mechanisms are recruited to resolve conflict. To test how these mechanisms operate to overcome conflict induced by highly automatized processing, we developed a novel version of the color-word Stroop task, where targets and distractors were simultaneously flickered at different frequencies. We measured the quality of early sensory processing by assessing the amplitude of steady-state visually evoked potentials (SSVEPs) elicited by targets and distractors. We also indexed frontal executive processes by assessing changes in frontal theta oscillations induced by color-word incongruency. We found that target- and distractor-related SSVEPs were not modulated by changes in the level of conflict whereas frontal theta activity increased on high compared to low conflict trials. These results suggest that frontal executive processes play a more dominant role in mitigating cognitive interference driven by the automatic tendency to process highly familiar stimuli.

Visual acuity is better for vertical and horizontal compared to other orientations. This cross-species phenomenon is often explained by "efficient coding," whereby more neurons show sharper tuning for the orientations most common in natural vision. However, it is unclear if experience alone can account for such biases. Here, we measured orientation representations in a convolutional neural network, VGG-16, trained on modified versions of ImageNet (rotated by 0°, 22.5°, or 45° counterclockwise of upright). Discriminability for each model was highest near the orientations that were most common in the network's training set. Furthermore, there was an overrepresentation of narrowly tuned units selective for the most common orientations. These effects emerged in middle layers and increased with depth in the network, though this layer-wise pattern may depend on properties of the evaluation stimuli used. Biases emerged early in training, consistent with the possibility that nonuniform representations may play a functional role in the network's task performance. Together, our results suggest that biased orientation representations can emerge through experience with a nonuniform distribution of orientations, supporting the efficient coding hypothesis.

Decision-making becomes slower when more choices are available. Existing models attribute this slowing to poor sensory processing, to attenuated rates of sensory evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). However, studies have not isolated the effects of having more choices on sensory and decision-related processes from changes in task difficulty and divided attention. Here, we controlled task difficulty while independently manipulating the distribution of attention and the number of choices available to male and female human observers. We used EEG to measure steady-state visually evoked potentials (SSVEPs) and a frontal late positive deflection (LPD), EEG markers of sensory and postsensory decision-related processes, respectively. We found that dividing attention decreased SSVEP and LPD amplitudes, consistent with dampened sensory responses and slower rates of evidence accumulation, respectively. In contrast, having more choices did not alter SSVEP amplitude and led to a larger LPD. These results suggest that having more options largely spares early sensory processing and slows down decision-making via a selective increase in decision thresholds. SIGNIFICANCE STATEMENT When more choices are available, decision-making becomes slower. We tested whether this phenomenon is due to poor sensory processing, to reduced rates of evidence accumulation, or to increases in the amount of evidence required before committing to a decision (a higher decision threshold). We measured choice modulations of sensory and decision-related neural responses using EEG. We also minimized potential confounds from changes in the distribution of attention and task difficulty, which often covary with having more choices. Dividing attention reduced the activity levels of both sensory and decision-related responses. However, having more choices did not change sensory processing and led to larger decision-related responses. These results suggest that having more choices spares sensory processing and selectively increases decision thresholds.

Rapid anthropogenic environmental changes, including those due to habitat contamination, degradation, and climate change, have far-reaching effects on biological systems that may outpace animals' adaptive responses. Neurobiological systems mediate interactions between animals and their environments and evolved over millions of years to detect and respond to change. To gain an understanding of the adaptive capacity of nervous systems given an unprecedented pace of environmental change, mechanisms of physiology and behavior at the cellular and biophysical level must be examined. While behavioral changes resulting from anthropogenic activity are becoming increasingly described, identification and examination of the cellular, molecular, and circuit-level processes underlying those changes are profoundly underexplored. Hence, the field of neuroscience lacks predictive frameworks to describe which neurobiological systems may be resilient or vulnerable to rapidly changing ecosystems, or what modes of adaptation are represented in our natural world. In this review, we highlight examples of animal behavior modification and corresponding nervous system adaptation in response to rapid environmental change. The underlying cellular, molecular, and circuit-level component processes underlying these behaviors are not known and emphasize the unmet need for rigorous scientific enquiry into the neurobiology of changing ecosystems.