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Studies in the basic neurosciences are heavily reliant upon rat and mouse models. The brain is one of the most distinguishing features of the human species, but is enough being done to fully understand the evolution of the human brain and brain diversity in general? Without a clear understanding of the evolution of the nervous system we may be investing a great deal of effort into some limited specific animal models that may prove to be erroneous in terms of the overall usefulness in clinically applied research. Here we present an analysis that demonstrates that 75% of our research efforts are directed to the rat, mouse and human brain, or 0.0001% of the nervous systems on the planet. This extreme bias in research trends may provide a limited scope in the discovery of novel aspects of brain structure and function that would be of importance in understanding both the evolution of the human brain and in selecting appropriate animal models for use in clinically related research. We offer examples both from the historical and recent literature indicating the usefulness of comparative neurobiological investigation in elucidating both normal and abnormal structure and function of the brain.

The rapidly growing field of cognitive neuroscience holds the promise of explaining the operations of the mind in terms of the physical operations of the brain. Some suggest that our emerging understanding of the physical causes of human (mis)behaviour will have a transformative effect on the law. Others argue that new neuroscience will provide only new details and that existing legal doctrine can accommodate whatever new information neuroscience will provide. We argue that neuroscience will probably have a transformative effect on the law, despite the fact that existing legal doctrine can, in principle, accommodate whatever neuroscience will tell us. New neuroscience will change the law, not by undermining its current assumptions, but by transforming people's moral intuitions about free will and responsibility. This change in moral outlook will result not from the discovery of crucial new facts or clever new arguments, but from a new appreciation of old arguments, bolstered by vivid new illustrations provided by cognitive neuroscience. We foresee, and recommend, a shift away from punishment aimed at retribution in favour of a more progressive, consequentialist approach to the criminal law.

The investigation of cultural phenomena using neuroscientific methods—cultural neuroscience (CN)—is receiving increasing attention. Yet it is unclear whether the integration of cultural study and neuroscience is merely additive, providing additional evidence of neural plasticity in the human brain, or truly synergistic, yielding discoveries that neither discipline could have achieved alone. We discuss how the parent fields to CN: cross-cultural psychology, psychological anthropology and cognitive neuroscience inform the investigation of the role of cultural experience in shaping the brain. Drawing on well-established methodologies from cross-cultural psychology and cognitive neuroscience, we outline a set of guidelines for CN, evaluate 17 CN studies in terms of these guidelines, and provide a summary table of our results. We conclude that the combination of culture and neuroscience is both additive and synergistic; while some CN methodologies and findings will represent the direct union of information from parent fields, CN studies employing the methodological rigor required by this logistically challenging new field have the potential to transform existing methodologies and produce unique findings.

Since the discovery of small-world and scale-free networks the study of complex systems from a network perspective has taken an enormous flight. In recent years many important properties of complex networks have been delineated. In particular, significant progress has been made in understanding the relationship between the structural properties of networks and the nature of dynamics taking place on these networks. For instance, the 'synchronizability' of complex networks of coupled oscillators can be determined by graph spectral analysis. These developments in the theory of complex networks have inspired new applications in the field of neuroscience. Graph analysis has been used in the study of models of neural networks, anatomical connectivity, and functional connectivity based upon fMRI, EEG and MEG. These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity. This small-world structure is hypothesized to reflect an optimal situation associated with rapid synchronization and information transfer, minimal wiring costs, as well as a balance between local processing and global integration. The topological structure of functional networks is probably restrained by genetic and anatomical factors, but can be modified during tasks. There is also increasing evidence that various types of brain disease such as Alzheimer's disease, schizophrenia, brain tumours and epilepsy may be associated with deviations of the functional network topology from the optimal small-world pattern.

An initiative of the NIH Blueprint for neuroscience research, the Neuroscience Information Framework (NIF) project advances neuroscience by enabling discovery and access to public research data and tools worldwide through an open source, semantically enhanced search portal. One of the critical components for the overall NIF system, the NIF Standardized Ontologies (NIFSTD), provides an extensive collection of standard neuroscience concepts along with their synonyms and relationships. The knowledge models defined in the NIFSTD ontologies enable an effective concept-based search over heterogeneous types of web-accessible information entities in NIF’s production system. NIFSTD covers major domains in neuroscience, including diseases, brain anatomy, cell types, sub-cellular anatomy, small molecules, techniques, and resource descriptors. Since the first production release in 2008, NIF has grown significantly in content and functionality, particularly with respect to the ontologies and ontology-based services that drive the NIF system. We present here on the structure, design principles, community engagement, and the current state of NIFSTD ontologies.

Background

Coppicing was one of the most important forest management systems in Europe documented in prehistory as well as in the Middle Ages. However, coppicing was gradually abandoned by the mid-20th century, which has altered the ecosystem structure, diversity and function of coppice woods.

Methodology/Principal Findings

Our aim was to disentangle factors shaping the historical growth dynamics of oak standards (i.e. mature trees growing through several coppice cycles) in a former coppice-with-standards in Central Europe. Specifically, we tried to detect historical coppicing events from tree-rings of oak standards, to link coppicing events with the recruitment of mature oaks, and to determine the effects of neighbouring trees on the stem increment of oak standards. Large peaks in radial growth found for the periods 1895–1899 and 1935–1939 matched with historical records of coppice harvests. After coppicing, the number of newly recruited oak standards markedly grew in comparison with the preceding or following periods. The last significant recruitment of oak standards was after the 1930s following the last regular coppicing event. The diameter increment of oak standards from 1953 to 2003 was negatively correlated with competition indices, suggesting that neighbouring trees (mainly resprouting coppiced Tilia platyphyllos) partly suppressed the growth of oak standards. Our results showed that improved light conditions following historical coppicing events caused significant increase in pulses of radial growth and most probably maintained oak recruitment.

Conclusions/Significance

Our historical perspective carries important implications for oak management in Central Europe and elsewhere. Relatively intense cutting creating open canopy woodlands, either as in the coppicing system or in the form of selective cutting, is needed to achieve significant radial growth in mature oaks. It is also critical for the successful regeneration and long-term maintenance of oak populations.

Cognitive neuroscience aims to map mental processes onto brain function, which begs the question of what “mental processes” exist and how they relate to the tasks that are used to manipulate and measure them. This topic has been addressed informally in prior work, but we propose that cumulative progress in cognitive neuroscience requires a more systematic approach to representing the mental entities that are being mapped to brain function and the tasks used to manipulate and measure mental processes. We describe a new open collaborative project that aims to provide a knowledge base for cognitive neuroscience, called the Cognitive Atlas (accessible online at http://www.cognitiveatlas.org), and outline how this project has the potential to drive novel discoveries about both mind and brain.

Recent development in diffusion spectrum brain imaging combined to functional simulation has the potential to further our understanding of how structure and dynamics are intertwined in the human brain. At the intra-individual scale, neurocomputational models have already started to uncover how the human connectome constrains the coordination of brain activity across distributed brain regions. In parallel, at the inter-individual scale, nascent social neuroscience provides a new dynamical vista of the coupling between two embodied cognitive agents. Using EEG hyperscanning to record simultaneously the brain activities of subjects during their ongoing interaction, we have previously demonstrated that behavioral synchrony correlates with the emergence of inter-brain synchronization. However, the functional meaning of such synchronization remains to be specified. Here, we use a biophysical model to quantify to what extent inter-brain synchronizations are related to the anatomical and functional similarity of the two brains in interaction. Pairs of interacting brains were numerically simulated and compared to real data. Results show a potential dynamical property of the human connectome to facilitate inter-individual synchronizations and thus may partly account for our propensity to generate dynamical couplings with others.

Behavioral and Brain Functions (BBF) is an Open Access, peer-reviewed, online journal considering original research, review, and modeling articles in all aspects of neurobiology or behavior, favoring research that relates to both domains. Behavioral and Brain Functions is published by BioMed Central. The greatest challenge for empirical science is to understand human behavior; how human behavior arises from the myriad functions such as attention, language, memory and emotion; how these functions are reflected in brain structures and functions; and how the brain and behavior are altered in disease. Behavioral and Brain Functions covers the entire area of behavioral and cognitive neuroscience – an area where animal studies traditionally play a prominent role. Behavioral and Brain Functions is published online, allowing unlimited space for figures, extensive datasets to allow readers to study the data for themselves, and moving pictures, which are important qualities assisting communication in modern science.

A number of modern digital anatomy techniques, based on structural MR brain images, have recently become applicable to the non-human primate brain. Such voxel-based quantitative techniques require a species-specific standardized brain template. Here we present a brain template for the Japanese macaque (Macaca fuscata). The template was designed to be used as a tool for spatially normalising Japanese macaque brains into a standard space. Although this species of macaque monkey is widely used in neuroscience research, including studies of higher cognitive brain functions, no standard MRI template of its brain is presently available. The template presented here is based on T1/T2* weighted, high-resolution 4 T MR images obtained from 16 male adult Japanese macaque monkeys. T1/T2* images were used to correct the signal inequalities resulting from the use of a surface coil. Based on these images, population-averaged probability maps were created for grey matter, white matter and cerebrospinal fluid. The new template presented here should facilitate future brain research using the Japanese macaque monkey. Whole brain templates are available at http://brainatlas.brain.riken.jp/jm/modules/xoonips/listitem.php?index_id=9.

In recent years, an array of brain mapping techniques has been successfully employed to link individual differences in circuit function or structure in the living human brain with individual variations in the human genome. Several proof-of-principle studies provided converging evidence that brain imaging can establish important links between genes and behaviour. The overarching goal is to use genetically informed brain imaging to pinpoint neurobiological mechanisms that contribute to behavioural intermediate phenotypes or disease states. This special issue on “Linking Genes to Brain Function in Health and Disease” provides an overview over how the “imaging genetics” approach is currently applied in the various fields of systems neuroscience to reveal the genetic underpinnings of complex behaviours and brain diseases. While the rapidly emerging field of imaging genetics holds great promise, the integration of genetic and neuroimaging data also poses major methodological and conceptual challenges. Therefore, this special issue also focuses on how these challenges can be met to fully exploit the synergism of genetically informed brain imaging.

Measurements of human brain function in children are of increasing interest in cognitive neuroscience. Many techniques for brain mapping used in children, including functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG), magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS), use probes placed on or near the scalp. The distance between the scalp and the brain is a key variable for these techniques because optical, electrical and magnetic signals are attenuated by distance. However, little is known about how scalp-brain distance differs between different cortical regions in children or how it changes with development. We investigated scalp-brain distance in 71 children, from newborn to age 12 years, using structural T1-weighted MRI scans of the whole head. Three-dimensional reconstructions were created from the scalp surface to allow for accurate calculation of brain-scalp distance. Nine brain landmarks in different cortical regions were manually selected in each subject based on the published fNIRS literature. Significant effects were found for age, cortical region and hemisphere. Brain-scalp distances were lowest in young children, and increased with age to up to double the newborn distance. There were also dramatic differences between brain regions, with up to 50% differences between landmarks. In frontal and temporal regions, scalp-brain distances were significantly greater in the right hemisphere than in the left hemisphere. The largest contributors to developmental changes in brain-scalp distance were increases in the corticospinal fluid (CSF) and inner table of the cranium. These results have important implications for functional imaging studies of children: age and brain-region related differences in fNIRS signals could be due to the confounding factor of brain-scalp distance and not true differences in brain activity.

Background

Understanding the mechanisms underlying generation of neuronal variability and complexity remains the central challenge for neuroscience. Structural variation in the neuronal genome is likely to be one important mechanism for neuronal diversity and brain diseases. Large-scale genomic variations due to loss or gain of whole chromosomes (aneuploidy) have been described in cells of the normal and diseased human brain, which are generated from neural stem cells during intrauterine period of life. However, the incidence of aneuploidy in the developing human brain and its impact on the brain development and function are obscure.

Methodology/Principal Findings

To address genomic variation during development we surveyed aneuploidy/polyploidy in the human fetal tissues by advanced molecular-cytogenetic techniques at the single-cell level. Here we show that the human developing brain has mosaic nature, being composed of euploid and aneuploid neural cells. Studying over 600,000 neural cells, we have determined the average aneuploidy frequency as 1.25–1.45% per chromosome, with the overall percentage of aneuploidy tending to approach 30–35%. Furthermore, we found that mosaic aneuploidy can be exclusively confined to the brain.

Conclusions/Significance

Our data indicates aneuploidization to be an additional pathological mechanism for neuronal genome diversification. These findings highlight the involvement of aneuploidy in the human brain development and suggest an unexpected link between developmental chromosomal instability, intercellural/intertissular genome diversity and human brain diseases.

Cognitive Neuroscience is an interdisciplinary area of research that combines measurement of brain activity (mostly by means of neuroimaging) with a simultaneous performance of cognitive tasks by human subjects. These investigations have been successful in the task of connecting the sciences of the brain (Neurosciences) and the sciences of the mind (Cognitive Sciences). Advances on this kind of research provide a map of localization of cognitive functions in the human brain. Do these results help us to understand how mind relates to the brain? In my view, the results obtained by the Cognitive Neurosciences lead to new investigations in the domain of Molecular Neurobiology, aimed at discovering biophysical mechanisms that generate the activity measured by neuroimaging instruments. In this context, I argue that the understanding of how ionic/molecular processes support cognition and consciousness cannot be made by means of the standard reductionist explanations. Knowledge of ionic/molecular mechanisms can contribute to our understanding of the human mind as long as we assume an alternative form of explanation, based on psycho-physical similarities, together with an ontological view of mentality and spirituality as embedded in physical nature (and not outside nature, as frequently assumed in western culture).

Curiosity is one of the most basic biological drives in both animals and humans, and has been identified as a key motive for learning and discovery. Despite the importance of curiosity and related behaviors, the topic has been largely neglected in human neuroscience; hence little is known about the neurobiological mechanisms underlying curiosity. We used functional magnetic resonance imaging (fMRI) to investigate what happens in our brain during the induction and subsequent relief of perceptual curiosity. Our core findings were that (1) the induction of perceptual curiosity, through the presentation of ambiguous visual input, activated the anterior insula and anterior cingulate cortex (ACC), brain regions sensitive to conflict and arousal; (2) the relief of perceptual curiosity, through visual disambiguation, activated regions of the striatum that have been related to reward processing; and (3) the relief of perceptual curiosity was associated with hippocampal activation and enhanced incidental memory. These findings provide the first demonstration of the neural basis of human perceptual curiosity. Our results provide neurobiological support for a classic psychological theory of curiosity, which holds that curiosity is an aversive condition of increased arousal whose termination is rewarding and facilitates memory.

Sigmund Freud, the founder of psychoanalysis, was initially a neuroscientist but abandoned neuroscience completely after he made a last attempt to link both in his writing, “Project of a Scientific Psychology,” in 1895. The reasons for his subsequent disregard of the brain remain unclear though. I here argue that one central reason may be that the approach to the brain during his time was simply not appealing to Freud. More specifically, Freud was interested in revealing the psychological predispositions of psychodynamic processes. However, he was not so much focused on the actual psychological functions themselves which though were the prime focus of the neuroscience at his time and also in current Cognitive Neuroscience. Instead, he probably would have been more interested in the brain’s resting state and its constitution of a spatiotemporal structure. I here assume that the resting state activity constitutes a statistically based virtual structure extending and linking the different discrete points in time and space within the brain. That in turn may serve as template, schemata, or grid for all subsequent neural processing during stimulus-induced activity. As such the resting state’ spatiotemporal structure may serve as the neural predisposition of what Freud described as “psychological structure.” Hence, Freud and also current neuropsychoanalysis may want to focus more on neural predispositions, the necessary non-sufficient conditions, rather than the neural correlates, i.e., sufficient, conditions of psychodynamic processes.

Despite great advances in basic neuroscience knowledge, the improved understanding of brain functioning has not yet led to the introduction of truly novel pharmacological approaches to the treatment of central nervous system disorders. This situation has been partly attributed to the difficulty of predicting efficacy in patients based on results from preclinical studies. To address these issues, this review critically discusses the traditional role of animal models in drug discovery, the difficulties encountered, and the reasons why this approach has led to suboptimal utilization of the information animal models provide. The discussion focuses on how animal models can contribute most effectively to translational medicine and drug discovery and the changes needed to increase the probability of achieving clinical benefit. Emphasis is placed on the need to improve the flow of information from the clinical/human domain to the preclinical domain and the benefits of using truly translational measures in both preclinical and clinical testing. Few would dispute the need to move away from the concept of modeling CNS diseases in their entirety using animals. However, the current emphasis on specific dimensions of psychopathology that can be objectively assessed in both clinical populations and animal models has not yet provided concrete examples of successful preclinical-clinical translation in CNS drug discovery. The purpose of this review is to strongly encourage ever more intensive clinical and preclinical interactions to ensure that basic science knowledge gained from improved animal models with good predictive and construct validity readily becomes available to the pharmaceutical industry and clinical researchers to benefit patients as quickly as possible.

Atlases of the human brain have an important impact on neuroscience. The emergence of ever more sophisticated imaging techniques, brain mapping methods and analytical strategies has the potential to revolutionize the concept of the brain atlas. Atlases can now combine data describing multiple aspects of brain structure or function at different scales from different subjects, yielding a truly integrative and comprehensive description of this organ. These integrative approaches have provided significant impetus for the human brain mapping initiatives, and have important applications in health and disease.

One of the earliest and most consistent findings in behavioral neuroscience research is that learning changes the brain. Here we consider how learning as an aspect of coping in the context of stress exposure induces neuroadaptations that enhance emotion regulation and resilience. A systematic review of the literature identified 15 brain imaging studies in which humans with specific phobias or post-traumatic stress disorder (PTSD) were randomized to stress exposure therapies that diminished subsequent indications of anxiety. Most of these studies focused on functional changes in the amygdala and anterior corticolimbic brain circuits that control cognitive, motivational, and emotional aspects of physiology and behavior. Corresponding structural brain changes and the timing, frequency, and duration of stress exposure required to modify brain functions remain to be elucidated in future research. These studies will advance our understanding of coping as a learning process and provide mechanistic insights for the development of new interventions that promote stress coping skills.

Defining the structural and functional connectivity of the human brain (the human “connectome”) is a basic challenge in neuroscience. Recently, techniques for noninvasively characterizing structural connectivity networks in the adult brain have been developed using diffusion and high-resolution anatomic MRI. The purpose of this study was to establish a framework for assessing structural connectivity in the newborn brain at any stage of development and to show how network properties can be derived in a clinical cohort of six-month old infants sustaining perinatal hypoxic ischemic encephalopathy (HIE). Two different anatomically unconstrained parcellation schemes were proposed and the resulting network metrics were correlated with neurological outcome at 6 months. Elimination and correction of unreliable data, automated parcellation of the cortical surface, and assembling the large-scale baby connectome allowed an unbiased study of the network properties of the newborn brain using graph theoretic analysis. In the application to infants with HIE, a trend to declining brain network integration and segregation was observed with increasing neuromotor deficit scores.

To celebrate the first 10 years of Nature Reviews Neuroscience, we invited the authors of the most cited article of each year to look back on the state of their field of research at the time of publication and the impact their article has had, and to discuss the questions that might be answered in the next 10 years. This selection of highly cited articles provides interesting snapshots of the progress that has been made in diverse areas of neuroscience. They show the enormous influence of neuroimaging techniques and highlight concepts that have generated substantial interest in the past decade, such as neuroimmunology, social neuroscience and the `network approach' to brain function. These advancements will pave the way for further exciting discoveries that lie ahead.

This article provides the beginning neuroeconomist with an introductory overview to the different methods used in human neuroscience. It describes basic strengths and weaknesses of each technique, points to examples of how each technique has been used in neuroeconomic studies, and provides key tutorial references that contain more detailed information. In addition to this overview, the article presents a framework that organizes human neuroscience methods functionally, according to whether they provide tests of the association between brain activity and cognition or behavior, or whether they test the necessity or the sufficiency of brain activity for cognition and behavior. This framework demonstrates the utility of a multi-method research approach, since converging evidence from tests of association, necessity and sufficiency provides the strongest inference regarding brain-behavior relationships. Set against this goal of converging evidence, human neuroscience studies in neuroeconomics currently rely far too heavily on methods that test association, most notably functional MRI.

Brain atlases are designed to provide a standard reference coordinate system of the brain for neuroscience research. Existing human brain atlases are widely used to provide anatomical references and information regarding structural characteristics of the brain. The majority of them, however, are derived from one paticipant or small samples of the Western population. This poses a limitation for scientific studies on Eastern subjects. In this study, 10 new Chinese brain atlases for different ages and genders were constructed using MR anatomical images based on HAMMER (Hierarchical Attribute Matching Mechanism for Elastic Registration). A total of 1,000 Chinese volunteers ranging from 18 to 70 years old participated in this study. These population-specific brain atlases represent the basic structural characteristics of the Chinese population. They may be utilized for basic neuroscience studies and clinical diagnosis, including evaluation of neurological and neuropsychiatric disorders, in Chinese patients and those from other Eastern countries.

The characterization of topological architecture of complex brain networks is one of the most challenging issues in neuroscience. Slow (<0.1 Hz), spontaneous fluctuations of the blood oxygen level dependent (BOLD) signal in functional magnetic resonance imaging are thought to be potentially important for the reflection of spontaneous neuronal activity. Many studies have shown that these fluctuations are highly coherent within anatomically or functionally linked areas of the brain. However, the underlying topological mechanisms responsible for these coherent intrinsic or spontaneous fluctuations are still poorly understood. Here, we apply modern network analysis techniques to investigate how spontaneous neuronal activities in the human brain derived from the resting-state BOLD signals are topologically organized at both the temporal and spatial scales. We first show that the spontaneous brain functional networks have an intrinsically cohesive modular structure in which the connections between regions are much denser within modules than between them. These identified modules are found to be closely associated with several well known functionally interconnected subsystems such as the somatosensory/motor, auditory, attention, visual, subcortical, and the “default” system. Specifically, we demonstrate that the module-specific topological features can not be captured by means of computing the corresponding global network parameters, suggesting a unique organization within each module. Finally, we identify several pivotal network connectors and paths (predominantly associated with the association and limbic/paralimbic cortex regions) that are vital for the global coordination of information flow over the whole network, and we find that their lesions (deletions) critically affect the stability and robustness of the brain functional system. Together, our results demonstrate the highly organized modular architecture and associated topological properties in the temporal and spatial brain functional networks of the human brain that underlie spontaneous neuronal dynamics, which provides important implications for our understanding of how intrinsically coherent spontaneous brain activity has evolved into an optimal neuronal architecture to support global computation and information integration in the absence of specific stimuli or behaviors.

One of the fundamental insights emerging from contemporary neuroscience is that mental illnesses are brain disorders. In contrast to classic neurological illnesses that involve discrete brain lesions, mental disorders need to be addressed as disorders of distributed brain systems with symptoms forged by developmental and social experiences. While genomics will be important for revealing risk, and cellular neuroscience should provide targets for novel treatments for these disorders, it is most likely that the tools of systems neuroscience will yield the biomarkers needed to revolutionize psychiatric diagnosis and treatment. This essay considers the discoveries that will be necessary over the next two decades to translate the promise of modern neuroscience into strategies for prevention and cures of mental disorders. To deliver on this spectacular new potential, clinical neuroscience must be integrated into the discipline of psychiatry, thereby transforming current psychiatric training, tools, and practices.