The BRAIN Initiative: developing technology to catalyse neuroscience discovery

The evolution of the field of neuroscience has been propelled by the advent of novel technological capabilities, and the pace at which these capabilities are being developed has accelerated dramatically in the past decade. Capitalizing on this momentum, the United States launched the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative to develop and apply new tools and technologies for revolutionizing our understanding of the brain. In this article, we review the scientific vision for this initiative set forth by the National Institutes of Health and discuss its implications for the future of neuroscience research. Particular emphasis is given to its potential impact on the mapping and study of neural circuits, and how this knowledge will transform our understanding of the complexity of the human brain and its diverse array of behaviours, perceptions, thoughts and emotions.     

Interactions between attention and memory

Attention and memory cannot operate without each other. In this review, we discuss two lines of recent evidence that support this interdependence. First, memory has a limited capacity, and thus attention determines what will be encoded. Division of attention during encoding prevents the formation of conscious memories, although the role of attention in formation of unconscious memories is more complex. Such memories can be encoded even when there is another concurrent task, but the stimuli that are to be encoded must be selected from among other competing stimuli. Second, memory from past experience guides what should be attended. Brain areas that are important for memory, such as the hippocampus and medial temporal lobe structures, are recruited in attention tasks, and memory directly affects frontal-parietal networks involved in spatial orienting. Thus, exploring the interactions between attention and memory can provide new insights into these fundamental topics of cognitive neuroscience.     

A comparison of the HUPO Brain Proteome Project pilot with other proteomics studies

The pilot phase of the Brain Proteome Project (BPP), the Human Proteome Organization (HUPO) initiative that focuses on studies of the brain of both humans and mice, has now been completed. Participating laboratories studied the proteomes of two human samples derived from biopsy and autopsy as well as three mouse samples from various developmental stages. With the combined and centrally reprocessed data now available, a comparison in terms of protein identifications and project organization is made between the HUPO BPP pilot and three other proteomics studies: the HUPO Plasma Proteome Project (PPP) pilot, a proteome of human blood platelets and a recently published comprehensive mouse proteome. Finally, as any comparison between large-scale proteomics datasets is decidedly non-trivial, we also evaluate and discuss several ways to go about comparing such different result sets.     

Research project: Charleston Bioengineered Kidney Project

The goal of Charleston Bioengineered Kidney Project is to engineer a functional living human kidney suitable for surgical implantation using principles of directed tissue self-assembly and tissue fusion. This is a multidisciplinary project which incorporates multiple innovative bioengineering technologies and expertise from a broad spectrum of disciplines. The conceptual framework, engineering principles, design, potential cell source as well as the first preliminary data demonstrating the feasibility of the proposed Charleston Bioengineered Kidney Project are outlined. The potential challenges are described. Finally, the experts' opinion about the proposed project is also presented.     

Early genomics of learning and memory: a review

The characterization of the molecular mechanisms whereby our brain codes, stores and retrieves memories remains a fundamental puzzle in neuroscience. Despite the knowledge that memory storage involves gene induction, the identification and characterization of the effector genes has remained elusive. The completion of the Human Genome Project and a variety of new technologies are revolutionizing the way these mechanisms can be explored. This review will examine how a genomic approach can be used to dissect and analyze the complex dynamic interactions involved in gene regulation during learning and memory. This innovative approach is providing information on a new class of genes associated with learning and memory in health and disease and is elucidating new molecular targets and pathways whose pharmacological modulation may allow new therapeutic approaches for improving cognition.     

The difficult legacy of Turing’s wager

Neuron modeling may be said to have originated with the Hodgkin and Huxley action potential model in 1952 and Rall’s models of integrative activity of dendrites in 1964. Over the ensuing decades, these approaches have led to a massive development of increasingly accurate and complex data-based models of neurons and neuronal circuits. ModelDB was founded in 1996 to support this new field and enhance the scientific credibility and utility of computational neuroscience models by providing a convenient venue for sharing them. It has grown to include over 1100 published models covering more than 130 research topics. It is actively curated and developed to help researchers discover and understand models of interest. ModelDB also provides mechanisms to assist running models both locally and remotely, and has a graphical tool that enables users to explore the anatomical and biophysical properties that are represented in a model. Each of its capabilities is undergoing continued refinement and improvement in response to user experience. Large research groups (Allen Brain Institute, EU Human Brain Project, etc.) are emerging that collect data across multiple scales and integrate that data into many complex models, presenting new challenges of scale. We end by predicting a future for neuroscience increasingly fueled by new technology and high performance computation, and increasingly in need of comprehensive user-friendly databases such as ModelDB to provide the means to integrate the data for deeper insights into brain function in health and disease.     

Behavioral barcoding in the cloud: embracing data-intensive digital phenotyping in neuropharmacology

For decades, studying the behavioral effects of individual drugs and genetic mutations has been at the heart of efforts to understand and treat nervous system disorders. High-throughput technologies adapted from other disciplines (e.g., high-throughput chemical screening, genomics) are changing the scale of data acquisition in behavioral neuroscience. Massive behavioral datasets are beginning to emerge, particularly from zebrafish labs, where behavioral assays can be performed rapidly and reproducibly in 96-well, high-throughput format. Mining these datasets and making comparisons across different assays are major challenges for the field. Here, we review behavioral barcoding, a process by which complex behavioral assays are reduced to a string of numeric features, facilitating analysis and comparison within and across datasets.     

Unsupervised quantification of naturalistic animal behaviors for gaining insight into the brain

Neural computation has evolved to optimize the behaviors that enable our survival. Although much previous work in neuroscience has focused on constrained task behaviors, recent advances in computer vision are fueling a trend toward the study of naturalistic behaviors. Automated tracking of fine-scale behaviors is generating rich datasets for animal models including rodents, fruit flies, zebrafish, and worms. However, extracting meaning from these large and complex data often requires sophisticated computational techniques. Here we review the latest methods and modeling approaches providing new insights into the brain from behavior. We focus on unsupervised methods for identifying stereotyped behaviors and for resolving details of the structure and dynamics of behavioral sequences.     

Connecting the dots in ethology: applying network theory to understand neural and animal collectives

A major goal shared by neuroscience and collective behavior is to understand how dynamic interactions between individual elements give rise to behaviors in populations of neurons and animals, respectively. This goal has recently become within reach, thanks to techniques providing access to the connectivity and activity of neuronal ensembles as well as to behaviors among animal collectives. The next challenge using these datasets is to unravel network mechanisms generating population behaviors. This is aided by network theory, a field that studies structure–function relationships in interconnected systems. Here we review studies that have taken a network view on modern datasets to provide unique insights into individual and collective animal behaviors. Specifically, we focus on how analyzing signal propagation, controllability, symmetry, and geometry of networks can tame the complexity of collective system dynamics. These studies illustrate the potential of network theory to accelerate our understanding of behavior across ethological scales.     

编者按: 神奇的“胶水”细胞

胶质细胞是一类神经系统中区别于神经元的一大类细胞，其数量是神经元的10~50倍。而且在相当长的一段时间胶质细胞也被认为是神经系统中的一种“胶水”，仅起到黏结神经元和填充神经系统的作用。随着近几十年神经科学的发展，神经生物学家们发现，胶质细胞的功能多种多样，并参与记忆、认知、神经发育性和退行性疾病，甚至衰老等高级功能。通过PubMed查询，中国胶质细胞相关论文的十年增长率为270%，远远高于全球平均增长率140%，说明中国在胶质细胞方面的研究势头非常强劲。本期《生物化学与生物物理进展》刊出了围绕胶质细胞的20余篇论文。涵盖胶质细胞的生理功能和病理功能的各个方面。本期的刊行将有利于推动国内胶质细胞科学研究，并为中国脑计划提供参考。     

International Symposium on High Performance Proteomics 2007: a contribution to Proteomics May 14-16, 2007 Dortmund, Germany

The symposium High Performance Proteomics was held in Dortmund on May 14-16, 2007, to celebrate the opening of the Zentrum für Angewandte Proteomik as well as the 6(th) anniversary of the German Human Brain Proteome Project. It offered an outstanding opportunity to obtain a broad overview about all fields of proteomics and related fields, combining the expertise of biochemists, physicians, bioinformatics, mathematicians and other researchers in Life Sciences. The main topics were the presentation of state-of-the-art proteomics technologies as well as possible transfer models for industrial applications. An accompanying industrial exhibition, as well as a discussion panel, offered the possibility to get in contact with colleagues and potential industrial partners. A visit to the former colliery Zeche Zollern and the social event at the Harenberg City-Center with an excellent view around Dortmund also left time for further communication between the more than 200 attendees.     

人类脑计划与神经信息学

了解脑及其功能是21世纪科学的重大挑战之一。神经信息学是神经科学与信息科学相结合的交叉学科。目前的“人类脑计划”旨在加强脑功能的基础研究,并开发用于分析、整合、合成、建模、模拟与提供各种数据的工具。中国应参与人类脑计划,为发展神经信息学作出贡献。     

Interrogating rodents regarding their object and spatial memory

Today, neuroscientists have access to a host of advanced techniques -- ranging from targeted genetic interventions to brain imaging -- that are rapidly providing new insights. Ultimately, however, memory must be inferred from its behavioral read-out. Thus, to fully utilize the advanced technologies available today, we must select the most appropriate behavioral procedures from those currently available, or else devise novel behavioral techniques to meet a specific demand. If we merely use standard tests of memory in a non-optimal way, we risk collecting incomplete information and reaching erroneous conclusions. Relevant to these issues, there have been substantial developments in the methods used to evaluate two of the most frequently studied forms of memory in the rodent -- recognition memory and spatial memory.     

Frontiers in Neurodegeneration – New Insights and Prospects – 20th HUPO BPP Workshop

The HUPO Brain Proteome Project (HUPO BPP) held its 20th workshop in Yokohama, Japan, September 15, 2013. The focus of the autumn workshop was on new insights and prospects of neurodegenerative diseases.     

The Selective Allure of Neuroscientific Explanations

Some claim that recent advances in neuroscience will revolutionize the way we think about human nature and legal culpability. Empirical support for this proposition is mixed. Two highly-cited empirical studies found that irrelevant neuroscientific explanations and neuroimages were highly persuasive to laypersons. However, attempts to replicate these effects have largely been unsuccessful. Two separate experiments tested the hypothesis that neuroscience is susceptible to motivated reasoning, which refers to the tendency to selectively credit or discredit information in a manner that reinforces preexisting beliefs. Participants read a newspaper article about a cutting-edge neuroscience study. Consistent with the hypothesis, participants deemed the hypothetical study sound and the neuroscience persuasive when the outcome of the study was congruent with their prior beliefs, but gave the identical study and neuroscience negative evaluations when it frustrated their beliefs. Neuroscience, it appears, is subject to the same sort of cognitive dynamics as other types of scientific evidence. These findings qualify claims that neuroscience will play a qualitatively different role in the way in which it shapes people’s beliefs and informs issues of social policy.     

Process analytics 4.0: A paradigm shift in rapid analytics for biologics development

Analytical testing of product quality attributes and process parameters during the biologics development (Process analytics) has been challenging due to the rapid growth of biomolecules with complex modalities to support unmet therapeutic needs. Thus, the expansion of the process analytics tool box for rapid analytics with the deployment of cutting-edge technologies and cyber-physical systems is a necessity. We introduce the term, Process Analytics 4.0; which entails not only technology aspects such as process analytical technology (PAT), assay automation, and high-throughput analytics, but also cyber-physical systems that enable data management, visualization, augmented reality, and internet of things (IoT) infrastructure for real time analytics in process development environment. This review is exclusively focused on dissecting high-level features of PAT, automation, and data management with some insights into the business aspects of implementing during process analytical testing in biologics process development. Significant technological and business advantages can be gained with the implementation of digitalization, automation, and real time testing. A systematic development and employment of PAT in process development workflows enable real time analytics for better process understanding, agility, and sustainability. Robotics and liquid handling workstations allow rapid assay and sample preparation automation to facilitate high-throughput testing of attributes and molecular properties which are otherwise challenging to monitor with PAT tools due to technological and business constraints. Cyber-physical systems for data management, visualization, and repository must be established as part of Process Analytics 4.0 framework. Furthermore, we review some of the challenges in implementing these technologies based on our expertise in process analytics for biopharmaceutical drug substance development.     

Clinical aspects of neurodegenerative diseases - 15th HUPO BPP Workshop April 8-9, 2011, Bochum, Germany

The HUPO Brain Proteome Project (HUPO BPP) held its 15th workshop in Bochum, Germany, from April 8th to 9th, 2011 directly after the Proteomic Forum 2011 in Berlin. Like on every spring workshop, the focus was more on clinical aspects, so that especially clinicians participated in this workshop.     

The long hard road to the doability of interdisciplinary research projects: the case of biosocial criminology

This paper combines Bourdieu’s Field Theory with the concept of “doability” to investigate an interdisciplinary scientific project, namely biosocial criminology. Biosocial criminologists seek to incorporate genetic and neuroscientific findings in criminology. Drawing on literature analysis and semi-structured interviews, I show how the doability of this interdisciplinary research project, which is mainly determined by considerations surrounding data and technologies, is a function of biosocial researchers’ position within the scientific field. This is made apparent at two different levels. First, the availability of genetic data, which is attributable to behavior geneticists’ “generosity” and inter-field exchanges, largely explains why biosocial criminologists mostly focused on genetic factors of crime and neglected neuroscience, a more costly area of endeavor. Second, the problem of doability prevents biosocial criminologists from performing any kind of genetic research. Because behavior geneticists’ generosity has its limits too, biosocial criminologists cannot resort to the most advanced methodological designs.