NSF workshop report: discovering general principles of nervous system organization by comparing brain maps across species

Comparative Analysis of Human-Chimpanzee Divergence in Brain Connectivity and its Genetic Correlates

Chimpanzees (Pan troglodytes) are humans' closest living relatives, making them the most directly relevant comparison point for understanding human brain evolution. Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occured along the human lineage. However, conducting comparisons of brain connectivity between humans and chimpanzees remains challenging, as cross-species brain atlases established within the same framework are currently lacking. Without the availability of cross-species brain atlases, the region-wise connectivity patterns between humans and chimpanzees cannot be directly compared. To address this gap, we built the first Chimpanzee Brainnetome Atlas (ChimpBNA) by following a well-established connectivity-based parcellation framework. Leveraging this new resource, we found substantial divergence in connectivity patterns across most association cortices, notably in the lateral temporal and dorsolateral prefrontal cortex between the two species. Intriguingly, these patterns significantly deviate from the patterns of cortical expansion observed in humans compared to chimpanzees. Additionally, we identified regions displaying connectional asymmetries that differed between species, likely resulting from evolutionary divergence. Genes associated with these divergent connectivities were found to be enriched in cell types crucial for cortical projection circuits and synapse formation. These genes exhibited more pronounced differences in expression patterns in regions with higher connectivity divergence, suggesting a potential foundation for brain connectivity evolution. Therefore, our study not only provides a fine-scale brain atlas of chimpanzees but also highlights the connectivity divergence between humans and chimpanzees in a more rigorous and comparative manner and suggests potential genetic correlates for the observed divergence in brain connectivity patterns between the two species. This can help us better understand the origins and development of uniquely human cognitive capabilities.

The mouse motor system contains multiple premotor areas and partially follows human organizational principles

While humans are known to have several premotor cortical areas, secondary motor cortex (M2) is often considered to be the only higher-order motor area of the mouse brain and is thought to combine properties of various human premotor cortices. Here, we show that axonal tracer, functional connectivity, myelin mapping, gene expression, and optogenetics data contradict this notion. Our analyses reveal three premotor areas in the mouse, anterior-lateral motor cortex (ALM), anterior-lateral M2 (aM2), and posterior-medial M2 (pM2), with distinct structural, functional, and behavioral properties. By using the same techniques across mice and humans, we show that ALM has strikingly similar functional and microstructural properties to human anterior ventral premotor areas and that aM2 and pM2 amalgamate properties of human pre-SMA and cingulate cortex. These results provide evidence for the existence of multiple premotor areas in the mouse and chart a comparative map between the motor systems of humans and mice.

The effects of early-life and intergenerational stress on the brain

Stress experienced during ontogeny can have profound effects on the adult phenotype. However, stress can also be experienced intergenerationally, where an offspring's phenotype can be moulded by stress experienced by the parents. Although early-life and intergenerational stress can alter anatomy, physiology, and behaviour, nothing is known about how these stress contexts interact to affect the neural phenotype. Here, we examined how early-life and intergenerational stress affect the brain in eastern fence lizards (Sceloporus undulatus). Some lizard populations co-occur with predatory fire ants, and stress from fire ant attacks exerts intergenerational physiological and behavioural changes in lizards. However, it is unclear if intergenerational stress, or the interaction between intergenerational and early-life stress, modulates the brain. To test this, we captured gravid females from fire ant invaded and uninvaded populations, and subjected offspring to three early-life stress treatments: (1) fire ant attack, (2) corticosterone, or (3) a control. Corticosterone and fire ant attack decreased some aspects of the neural phenotype while population of origin and the interaction of early-life stress and population had no effects on the brain. These results suggest that early-life stressors may better predict adult brain variation than intergenerational stress in this species.

Characterisation of geometric variance in the epithelial nerve net of the ctenophore Pleurobrachia pileus

Neuroscience lacks a diverse repertoire of model organisms, resulting in an incomplete understanding into the general principles of neural function. Ctenophores display many neurobiological and experimental features which make them a promising candidate to fill this gap. They possess a nerve net distributed across their body surface, in the epithelial layer. There is a long-held assumption that nerve nets are 'simple' and lack distinct organisational principles. We want to challenge this assumption and determine how stereotyped the structure of this network is. We estimated body surface area in Pleurobrachia pileus using custom Optical Projection Tomography and Light Sheet Morphometry imaging systems. Using an antibody against tyrosinated α-tubulin we visualised the nerve net in situ and quantified the geometric properties using an automated segmentation approach. We characterised organisational rules of the epithelial nerve net in animals of different sizes and at different regions of the body. We found that specific morphological features within the nerve net are largely unchanged during growth. These properties must be essential to the functionality of the nervous system and therefore are maintained during a change in body size. We have also established the principles of organisation of the network and showed that some of the geometric properties are variable across different parts of the body. This suggests that there may be different functions occurring in regions with different structural characteristics. This is the most comprehensive structural description of a ctenophore nerve net to date and demonstrates the amenability of P. pileus for whole organism network analysis. This article is protected by copyright. All rights reserved.

Evolving Views on the Pallium

The pallium is the largest part of the telencephalon in amniotes, and comparison of its subdivisions across species has been extremely difficult and controversial due to its high divergence. Comparative embryonic genoarchitecture studies have greatly contributed to propose models of pallial fundamental divisions, which can be compared across species and be used to extract general organizing principles as well as to ask more focused and insightful research questions. The use of these models is crucial to discern between conservation, convergence or divergence in the neural populations and networks found in the pallium. Here we provide a critical review of the models proposed using this approach, including tetrapartite, hexapartite and double-ring models, and compare them to other models. While recognizing the power of these models for understanding brain architecture, development and evolution, we also highlight limitations and comment on aspects that require attention for improvement. We also discuss on the use of transcriptomic data for understanding pallial evolution and advise for better contextualization of these data by discerning between gene regulatory networks involved in the generation of specific units and cell populations versus genes expressed later, many of which are activity dependent and their expression is more likely subjected to convergent evolution.

The Neuroscience Community Has a Role in Environmental Conservation

We previously argued that the neuroscience community has a role in environmental conservation because protection of biodiversity and the specialized behavioral adaptions of animals is essential to understanding brain structure and function. Preserving biodiversity and the natural world is also linked to human mental health and broadens our insight on the origins of psychiatric disorders like stress, anxiety, and depression. The study of neuroscience has become a global scientific pursuit that involves thousands of researchers and has an economic impact in the billions of dollars. As a group of biomedical research scientists, neuroscientists have the knowledge base and public credibility to convincingly promote sustainable environmental actions and policies. Here, we outline several key areas in which we as a neuroscience academic community can participate to preserve a rich global biodiversity and confront the environmental crises that lie before us.

A tale of two leeches: Toward the understanding of the evolution and development of behavioral neural circuits

In the animal kingdom, behavioral traits encompass a broad spectrum of biological phenotypes that have critical roles in adaptive evolution, but an EvoDevo approach has not been broadly used to study behavior evolution. Here, we propose that, by integrating two leech model systems, each of which has already attained some success in its respective field, it is possible to take on behavioral traits with an EvoDevo approach. We first identify the developmental changes that may theoretically lead to behavioral evolution and explain why an EvoDevo study of behavior is challenging. Next, we discuss the pros and cons of the two leech model species, Hirudo, a classic model for invertebrate neurobiology, and Helobdella, an emerging model for clitellate developmental biology, as models for behavioral EvoDevo research. Given the limitations of each leech system, neither is particularly strong for behavioral EvoDevo. However, the two leech systems are complementary in their technical accessibilities, and they do exhibit some behavioral similarities and differences. By studying them in parallel and together with additional leech species such as Haementeria, it is possible to explore the different levels of behavioral development and evolution.

Longitudinal connections and the organization of the temporal cortex in macaques, great apes, and humans

The temporal association cortex is considered a primate specialization and is involved in complex behaviors, with some, such as language, particularly characteristic of humans. The emergence of these behaviors has been linked to major differences in temporal lobe white matter in humans compared with monkeys. It is unknown, however, how the organization of the temporal lobe differs across several anthropoid primates. Therefore, we systematically compared the organization of the major temporal lobe white matter tracts in the human, gorilla, and chimpanzee great apes and in the macaque monkey. We show that humans and great apes, in particular the chimpanzee, exhibit an expanded and more complex occipital-temporal white matter system; additionally, in humans, the invasion of dorsal tracts into the temporal lobe provides a further specialization. We demonstrate the reorganization of different tracts along the primate evolutionary tree, including distinctive connectivity of human temporal gray matter.

Why behavioral neuroscience still needs diversity?: A curious case of a persistent need

In the past few decades, a substantial portion of neuroscience research has moved from studies conducted across a spectrum of animals to reliance on a few species. While this undoubtedly promotes consistency, in-depth analysis, and a better claim to unraveling molecular mechanisms, investing heavily in a subset of species also restricts the type of questions that can be asked, and impacts the generalizability of findings. A conspicuous body of literature has long advocated the need to expand the diversity of animal systems used in neuroscience research. Part of this need is utilitarian with respect to translation, but the remaining is the knowledge that historically, a diverse set of species were instrumental in obtaining transformative understanding. We argue that diversifying matters also because the current approach limits the scope of what can be discovered. Technological advancements are already bridging several practical gaps separating these two worlds. What remains is a wholehearted embrace by the community that has benefitted from past history. We suggest the time for it is now.

Contrasting neurochemical and behavioral profiles reflects stress coping styles but not stress responsiveness in farmed gilthead seabream (Sparus aurata)

In fish, as well as in other vertebrates, contrasting suites of physiological and behavioral traits, or coping styles, are often shown in response to stressors. However, the magnitude of the response (i.e. stress responsiveness) has been suggested to be independent of stress coping style. One central neurotransmitter that has been associated with both stress responsiveness and differences in stress coping styles is serotonin (5-hydroxytryptamine, 5-HT). In this study, we investigated to what extent stress responsiveness reflects differences in stress coping, and the potential involvement of the 5-HT system in mediating such differences in farmed Gilthead seabream. Initially, fish were classified as proactive or reactive based on their behavioural response to net restraint. Following 1.5 months, fish classified as proactive still showed a higher number of escape attempts and spent longer time escaping than those classified as reactive. These differences were reflected in a generally higher brain stem 5-HT concentration and a lower telencephalic 5-HT activity, i.e. the ratio of 5-hydroxyindoleacetic acid (5-HIAA) to 5-HT, in proactive fish. Independent of stress coping styles, stress responsiveness was reflected in elevated 5-HIAA concentrations and 5-HIAA/5-HT ratios in telencephalon and brain stem together with increased plasma cortisol concentrations at 0.5 and 2 h following the last net restraint. The current results show that 5-HT signaling can reflect different behavioural output to a challenge which are independent of neuroendocrine responses to stress and lend support to the hypothesis that stress coping styles can be independent of stress responsiveness.

Large-scale comparative neuroimaging: Where are we and what do we need?

Neuroimaging has a lot to offer comparative neuroscience. Although invasive "gold standard" techniques have a better spatial resolution, neuroimaging allows fast, whole-brain, repeatable, and multi-modal measurements of structure and function in living animals and post-mortem tissue. In the past years, comparative neuroimaging has increased in popularity. However, we argue that its most significant potential lies in its ability to collect large-scale datasets of many species to investigate principles of variability in brain organisation across whole orders of species-an ambition that is presently unfulfilled but achievable. We briefly review the current state of the field and explore what the current obstacles to such an approach are. We propose some calls to action.

The Future of Gene-Guided Neuroscience Research in Non-Traditional Model Organisms

Natural variations across animals in form, function, and behavior have long been sources of inspiration to scientists. Despite this, experimentalists focusing on the neural bases of behavior have increasingly focused on a select few model species. This consolidation is motivated primarily by the availability of resources and technologies for manipulation in these species. Recent years have witnessed a proliferation of experimental approaches that were developed primarily in traditional model species, but that may in principle be readily applied to any species. High-throughput sequencing, CRISPR gene editing, transgenesis, and other technologies have enabled new insights through their deployment in non-traditional model species. The availability of such approaches changes the calculation of which species to study, particularly when a trait of interest is most readily observed in a non-traditional model organism. If these technologies are widely adopted in many new species, it promises to revolutionize the field of neuroethology.

Variation across Species and Levels: Implications for Model Species Research

The selection of model species tends to involve two typically unstated assumptions, namely: (1) that the similarity between species decreases steadily with phylogenetic distance, and (2) that similarities are greater at lower levels of biological organization. The first assumption holds on average, but species similarities tend to decrease with the square root of divergence time, rather than linearly, and lineages with short generation times (which includes most model species) tend to diverge faster than average, making the decrease in similarity non-monotonic. The second assumption is more difficult to test. Comparative molecular research has traditionally emphasized species similarities over differences, whereas comparative research at higher levels of organization frequently highlights the species differences. However, advances in comparative genomics have brought to light a great variety of species differences, not just in gene regulation but also in protein coding genes. Particularly relevant are cases in which homologous high-level characters are based on non-homologous genes. This phenomenon of non-orthologous gene displacement, or "deep non-homology," indicates that species differences at the molecular level can be surprisingly large. Given these observations, it is not surprising that some findings obtained in model species do not generalize across species as well as researchers had hoped, even if the research is molecular.

Critique of Pure Marmoset

The common marmoset, a New World (platyrrhine) monkey, is currently being fast-tracked as a non-human primate model species, especially for genetic modification but also as a general-purpose model for research on the brain and behavior bearing on the human condition. Compared to the currently dominant primate model, the catarrhine macaque monkey, marmosets are notable for certain evolutionary specializations, including their propensity for twin births, their very small size (a result of phyletic dwarfism), and features related to their small size (rapid development and relatively short lifespan), which result in these animals yielding experimental results more rapidly and at lower cost. Macaques, however, have their own advantages. Importantly, macaques are more closely related to humans (which are also catarrhine primates) than are marmosets, sharing approximately 20 million more years of common descent, and are demonstrably more similar to humans in a variety of genomic, molecular, and neurobiological characteristics. Furthermore, the very specializations of marmosets that make them attractive as experimental subjects, such as their rapid development and short lifespan, are ways in which marmosets differ from humans and in which macaques more closely resemble humans. These facts warrant careful consideration of the trade-offs between convenience and cost, on the one hand, and biological realism, on the other, in choosing between non-human primate models of human biology. Notwithstanding the advantages marmosets offer as models, prudence requires continued commitment to research on macaques and other primate species.

Reductionist thinking and animal models in neuropsychiatric research

Reductionist thinking in neuroscience is manifest in the widespread use of animal models of neuropsychiatric disorders. Broader investigations of diverse behaviors in non-model organisms and longer-term study of the mechanisms of plasticity will yield fundamental insights into the neurobiological, developmental, genetic, and environmental factors contributing to the “massively multifactorial system networks” which go awry in mental disorders.

Social plasticity in the fish brain: Neuroscientific and ethological aspects

Social plasticity, defined as the ability to adaptively change the expression of social behavior according to previous experience and to social context, is a key ecological performance trait that should be viewed as crucial for Darwinian fitness. The neural mechanisms for social plasticity are poorly understood, in part due to skewed reliance on rodent models. Fish model organisms are relevant in the field of social plasticity for at least two reasons: first, the diversity of social organization among fish species is staggering, increasing the breadth of evolutionary relevant questions that can be asked. Second, that diversity also suggests translational relevance, since it is more likely that "core" mechanisms of social plasticity are discovered by analyzing a wider variety of social arrangements than relying on a single species. We analyze examples of social plasticity across fish species with different social organizations, concluding that a "core" mechanism is the initiation of behavioral shifts through the modulation of a conserved "social decision-making network", along with other relevant brain regions, by monoamines, neuropeptides, and steroid hormones. The consolidation of these shifts may be mediated via neurogenomic adjustments and regulation of the expression of plasticity-related molecules (transcription factors, cell cycle regulators, and plasticity products).

Mapping multiple principles of parietal-frontal cortical organization using functional connectivity

Resting state functional connectivity has been promoted as a promising tool for creating cortical maps that show remarkable similarity to those established by invasive histological methods. While this tool has been largely used to identify and map cortical areas, its true potential in the context of studying connectional architecture and in conducting comparative neuroscience has remained unexplored. Here, we employ widely used resting state connectivity and data-driven clustering methods to extend this approach for the study of the organizational principles of the macaque parietal–frontal system. We show multiple, overlapping principles of organization, including a dissociation between dorsomedial and dorsolateral pathways and separate parietal–premotor and parietal–frontal pathways. These results demonstrate the suitability of this approach for understanding the complex organizational principles of the brain and for large-scale comparative neuroscience.

NeuroSystematics and Periodic System of Neurons: Model vs Reference Species at Single-Cell Resolution

There is more than one way to develop neuronal complexity, and animals frequently use different molecular toolkits to achieve similar functional outcomes (=convergent evolution). Neurons are different not only because they have different functions, but also because neurons and circuits have different genealogies, and perhaps independent origins at the broadest scale from ctenophores and cnidarians to cephalopods and primates. By combining modern phylogenomics, single-neuron sequencing (scRNA-seq), machine learning, single-cell proteomics, and metabolomic across Metazoa, it is possible to reconstruct the evolutionary histories of neurons tracing them to ancestral secretory cells. Comparative data suggest that neurons, and perhaps synapses, evolved at least 2-3 times (in ctenophore, cnidarian and bilateral lineages) during ∼600 million years of animal evolution. There were also several independent events of the nervous system centralization either from a common bilateral/cnidarian ancestor without the bona fide neurons or from the urbilaterian with diffuse, nerve-net type nervous system. From the evolutionary standpoint, (i) a neuron should be viewed as a functional rather than a genetic character, and (ii) any given neural system might be chimeric and composed of different cell lineages with distinct origins and evolutionary histories. The identification of distant neural homologies or examples of convergent evolution among 34 phyla will not only allow the reconstruction of neural systems' evolution but together with single-cell "omic" approaches the proposed synthesis would lead to the "Periodic System of Neurons" with predictive power for neuronal phenotypes and plasticity. Such a phylogenetic classification framework of Neuronal Systematics (NeuroSystematics) might be a conceptual analog of the Periodic System of Chemical Elements. scRNA-seq profiling of all neurons in an entire brain or Brain-seq is now fully achievable in many nontraditional reference species across the entire animal kingdom. Arguably, marine animals are the most suitable for the proposed tasks because the world oceans represent the greatest taxonomic and body-plan diversity.

The morphology of antennal lobe projection neurons is controlled by a POU-domain transcription factor Bmacj6 in the silkmoth Bombyx mori

How to wire a neural circuit is crucial for the functioning of the nervous system. Here, we describe the neuroanatomy of the olfactory neurons in the spli mutant strain of silkmoth (Bombyx mori) to investigate the function of a transcription factor involved in neuronal wiring in the central olfactory circuit. The genomic structure of the gene Bmacj6, which encodes a class IV POU domain transcription factor, is disrupted in the spli mutant. We report the neuroanatomical abnormality in the morphology of the antennal lobe projection neurons (PNs) that process the sex pheromone. In addition to the mis-targeting of dendrites and axons, we found axonal bifurcation within the PNs. These results indicate that the morphology of neurons in the pheromone processing pathway is modified by Bmacj6.

Contrasting Coping Styles Meet the Wall: A Dopamine Driven Dichotomy in Behavior and Cognition

Individual variation in the ability to modify previously learned behavior is an important dimension of trait correlations referred to as coping styles, behavioral syndromes or personality. These trait clusters have been shaped by natural selection, and underlying control mechanisms are often conserved throughout vertebrate evolution. In teleost fishes, behavioral flexibility and coping style have been studied in the high (HR) and low-responsive (LR) rainbow trout lines. Generally, proactive LR trout show a behavior guided by previously learned routines, while HR trout show a more flexible behavior relying on environmental cues. In mammals, routine dependent vs. flexible behavior has been connected to variation in limbic dopamine (DA) signaling. Here, we studied the link between limbic DA signaling and individual variation in flexibility in teleost fishes by a reversal learning approach. HR/LR trout were challenged by blocking a learned escape route, previously available during interaction with a large and aggressive conspecific. LR trout performed a higher number of failed escape attempts against the transparent blockage, while HR trout were more able to inhibit the now futile escape impulse. Regionally discrete changes in DA neurochemistry were observed in micro dissected limbic areas of the telencephalon. Most notably, DA utilization in the dorsomedial telencephalon (DM, a suggested amygdala equivalent) remained stable in HR trout in response to reversal learning under acute stress, while increasing from an initially lower level in LR trout. In summary, these results support the view that limbic homologs control individual differences in behavioral flexibility even in non-mammalian vertebrates.

Applying gene regulatory network logic to the evolution of social behavior

Animal behavior is ultimately the product of gene regulatory networks (GRNs) for brain development and neural networks for brain function. The GRN approach has advanced the fields of genomics and development, and we identify organizational similarities between networks of genes that build the brain and networks of neurons that encode brain function. In this perspective, we engage the analogy between developmental networks and neural networks, exploring the advantages of using GRN logic to study behavior. Applying the GRN approach to the brain and behavior provides a quantitative and manipulative framework for discovery. We illustrate features of this framework using the example of social behavior and the neural circuitry of aggression.

Putting the "Biology" Back into "Neurobiology": The Strength of Diversity in Animal Model Systems for Neuroscience Research

Current trends in neuroscience research have moved toward a reliance on rodent animal models to study most aspects of brain function. Such laboratory-reared animals are highly inbred, have been disengaged from their natural environments for generations and appear to be of limited predictive value for successful clinical outcomes. In this Perspective article, we argue that research on a rich diversity of animal model systems is fundamental to new discoveries in evolutionarily conserved core physiological and molecular mechanisms that are the foundation of human brain function. Analysis of neural circuits across phyla will reveal general computational solutions that form the basis for adaptive behavioral responses. Further, we stress that development of ethoexperimental approaches to improve our understanding of behavioral nuance will help to realign our research strategies with therapeutic goals and improve the translational validity of specific animal models. Finally, we suggest that neuroscience has a role in environmental conservation of habitat and fauna that will preserve and protect the ecological settings that drive species-specific behavioral adaptations. A rich biodiversity will enhance our understanding of human brain function and lead in unpredicted directions for development of therapeutic treatments for neurological disorders.

Comparing brains by matching connectivity profiles

The great promise of comparative neuroscience is to understand why brains differ by investigating the relations between variations in the organization of different brains, their evolutionary history, and their current ecological niche. For this approach to be successful, the organization of different brains needs to be quantifiable. Here, we present an approach to formally comparing the connectivity of different cortical areas across different brains. We exploit the fact that cortical regions can be characterized by the unique pattern of connectivity, the so-called connectivity fingerprint. By comparing connectivity fingerprints between cortical areas in the human and non-human primate brain we can identify between-species homologs, but also illustrate that is driving differences between species. We illustrate the approach by comparing the organization of the frontal cortex between humans and macaques, showing general similarities combined with some differences in the lateral frontal pole.

Non-mammalian models in behavioral neuroscience: consequences for biological psychiatry

Current models in biological psychiatry focus on a handful of model species, and the majority of work relies on data generated in rodents. However, in the same sense that a comparative approach to neuroanatomy allows for the identification of patterns of brain organization, the inclusion of other species and an adoption of comparative viewpoints in behavioral neuroscience could also lead to increases in knowledge relevant to biological psychiatry. Specifically, this approach could help to identify conserved features of brain structure and behavior, as well as to understand how variation in gene expression or developmental trajectories relates to variation in brain and behavior pertinent to psychiatric disorders. To achieve this goal, the current focus on mammalian species must be expanded to include other species, including non-mammalian taxa. In this article, we review behavioral neuroscientific experiments in non-mammalian species, including traditional "model organisms" (zebrafish and Drosophila) as well as in other species which can be used as "reference." The application of these domains in biological psychiatry and their translational relevance is considered.

Future advances

Future advances in the auditory systems are difficult to predict, and only educated guesses are possible. It is expected that innovative technologies in the field of neuroscience will be applied to the auditory system. Optogenetics, Brainbow, and CLARITY will improve our knowledge of the working of neural auditory networks and the relationship between sound and language, providing a dynamic picture of the brain in action. CLARITY makes brain tissue transparent and offers a three-dimensional view of neural networks, which, combined with genetically labeling neurons with multiple, distinct colors (Optogenetics), will provide detailed information of the complex brain system. Molecular functional magnetic resonance imaging (MRI) will allow the study of neurotransmitters detectable by MRI and their function in the auditory pathways. The Human Connectome project will study the patterns of distributed brain activity that underlie virtually all aspects of cognition and behavior and determine if abnormalities in the distributed patterns of activity may result in hearing and behavior disorders. Similarly, the programs of Big Brain and ENIGMA will improve our understanding of auditory disorders. New stem-cell therapy and gene therapies therapy may bring about a partial restoration of hearing for impaired patients by inducing regeneration of cochlear hair cells.

The circuit architecture of whole brains at the mesoscopic scale

Vertebrate brains of even moderate size are composed of astronomically large numbers of neurons and show a great degree of individual variability at the microscopic scale. This variation is presumably the result of phenotypic plasticity and individual experience. At a larger scale, however, relatively stable species-typical spatial patterns are observed in neuronal architecture, e.g., the spatial distributions of somata and axonal projection patterns, probably the result of a genetically encoded developmental program. The mesoscopic scale of analysis of brain architecture is the transitional point between a microscopic scale where individual variation is prominent and the macroscopic level where a stable, species-typical neural architecture is observed. The empirical existence of this scale, implicit in neuroanatomical atlases, combined with advances in computational resources, makes studying the circuit architecture of entire brains a practical task. A methodology has previously been proposed that employs a shotgun-like grid-based approach to systematically cover entire brain volumes with injections of neuronal tracers. This methodology is being employed to obtain mesoscale circuit maps in mouse and should be applicable to other vertebrate taxa. The resulting large data sets raise issues of data representation, analysis, and interpretation, which must be resolved. Even for data representation the challenges are nontrivial: the conventional approach using regional connectivity matrices fails to capture the collateral branching patterns of projection neurons. Future success of this promising research enterprise depends on the integration of previous neuroanatomical knowledge, partly through the development of suitable computational tools that encapsulate such expertise.

The big data problem: turning maps into knowledge

In this NeuroView, Engert discusses the challenges for the connectomics field in making insights about brain function from big data.

Mapping circuits beyond the models: integrating connectomics and comparative neuroscience

The brain has been shaped by evolution, and its connectome reflects that history. Comparative neuroscience research, framed by evolutionary relationships, is key to interpreting connectome organization and can address fundamental circuit questions that are not accessible through single-species connectomics efforts.

Recent developments in VSD imaging of small neuronal networks

Voltage-sensitive dye (VSD) imaging is a powerful technique that can provide, in single experiments, a large-scale view of network activity unobtainable with traditional sharp electrode recording methods. Here we review recent work using VSDs to study small networks and highlight several results from this approach. Topics covered include circuit mapping, network multifunctionality, the network basis of decision making, and the presence of variably participating neurons in networks. Analytical tools being developed and applied to large-scale VSD imaging data sets are discussed, and the future prospects for this exciting field are considered.