An integrated approach to classifying neuronal phenotypes

A deep-learning strategy to identify cell types across species from high-density extracellular recordings

High-density probes allow electrophysiological recordings from many neurons simultaneously across entire brain circuits but don't reveal cell type. Here, we develop a strategy to identify cell types from extracellular recordings in awake animals, revealing the computational roles of neurons with distinct functional, molecular, and anatomical properties. We combine optogenetic activation and pharmacology using the cerebellum as a testbed to generate a curated ground-truth library of electrophysiological properties for Purkinje cells, molecular layer interneurons, Golgi cells, and mossy fibers. We train a semi-supervised deep-learning classifier that predicts cell types with greater than 95% accuracy based on waveform, discharge statistics, and layer of the recorded neuron. The classifier's predictions agree with expert classification on recordings using different probes, in different laboratories, from functionally distinct cerebellar regions, and across animal species. Our classifier extends the power of modern dynamical systems analyses by revealing the unique contributions of simultaneously-recorded cell types during behavior.

Non-uniform contextual interactions in the visual cortex place fundamental limits on spatial vision

A prevailing assumption in our understanding of how neurons in the primary visual cortex (V1) integrate contextual information is that such processes are spatially uniform. Conversely, perceptual phenomena such as visual crowding, the impaired ability to accurately recognize a target stimulus among distractors, suggest that interactions among stimuli are distinctly non-uniform. Prior studies have shown flankers at specific spatial geometries exert differential effects on target perception. To resolve this discrepancy, we investigated how flanker geometry impacted the representation of a target stimulus in the laminar microcircuits of V1. Our study reveals flanker location differentially impairs stimulus representation in excitatory neurons in the superficial and input layers of V1 by tuned suppression and untuned facilitation of orientation responses. Mechanistically, this effect can be explained by asymmetrical spatial kernels in a normalization model of cortical activity. Strikingly, these non-uniform modulations of neural representation mirror perceptual anisotropies. These results establish the non-uniform spatial integration of information in the earliest stages of cortical processing as a fundamental limitation of spatial vision.

Three Decades of Valproate: A Current Model for Studying Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with increased prevalence and incidence in recent decades. Its etiology remains largely unclear, but it seems to involve a strong genetic component and environmental factors that, in turn, induce epigenetic changes during embryonic and postnatal brain development. In recent decades, clinical studies have shown that inutero exposure to valproic acid (VPA), a commonly prescribed antiepileptic drug, is an environmental factor associated with an increased risk of ASD. Subsequently, prenatal VPA exposure in rodents has been established as a reliable translational model to study the pathophysiology of ASD, which has helped demonstrate neurobiological changes in rodents, non-human primates, and brain organoids from human pluripotent stem cells. This evidence supports the notion that prenatal VPA exposure is a valid and current model to replicate an idiopathic ASD-like disorder in experimental animals. This review summarizes and describes the current features reported with this animal model of autism and the main neurobiological findings and correlates that help elucidate the pathophysiology of ASD. Finally, we discuss the general framework of the VPA model in comparison to other environmental and genetic ASD models.

Laminar compartmentalization of attention modulation in area V4 aligns with the demands of visual processing hierarchy in the cortex

Attention selectively enhances neural responses to low contrast stimuli in visual area V4, a critical hub that sends projections both up and down the visual hierarchy. Veridical encoding of contrast information is a key computation in early visual areas, while later stages encoding higher level features benefit from improved sensitivity to low contrast. How area V4 meets these distinct information processing demands in the attentive state is unknown. We found that attentional modulation in V4 is cortical layer and cell-class specific. Putative excitatory neurons in the superficial layers show enhanced boosting of low contrast information, while those of deep layers exhibit contrast-independent scaling. Computational modeling suggested the extent of spatial integration of inhibitory neurons as the mechanism behind such laminar differences. Considering that superficial neurons are known to project to higher areas and deep layers to early visual areas, our findings suggest that the interactions between attention and contrast in V4 are compartmentalized, in alignment with the demands of the visual processing hierarchy.

Distinctive biophysical features of human cell-types: insights from studies of neurosurgically resected brain tissue

Electrophysiological characterization of live human tissue from epilepsy patients has been performed for many decades. Although initially these studies sought to understand the biophysical and synaptic changes associated with human epilepsy, recently, it has become the mainstay for exploring the distinctive biophysical and synaptic features of human cell-types. Both epochs of these human cellular electrophysiological explorations have faced criticism. Early studies revealed that cortical pyramidal neurons obtained from individuals with epilepsy appeared to function "normally" in comparison to neurons from non-epilepsy controls or neurons from other species and thus there was little to gain from the study of human neurons from epilepsy patients. On the other hand, contemporary studies are often questioned for the "normalcy" of the recorded neurons since they are derived from epilepsy patients. In this review, we discuss our current understanding of the distinct biophysical features of human cortical neurons and glia obtained from tissue removed from patients with epilepsy and tumors. We then explore the concept of within cell-type diversity and its loss (i.e., "neural homogenization"). We introduce neural homogenization to help reconcile the epileptogenicity of seemingly "normal" human cortical cells and circuits. We propose that there should be continued efforts to study cortical tissue from epilepsy patients in the quest to understand what makes human cell-types "human".

Types of Neurons in the Human Colonic Myenteric Plexus Identified by Multilayer Immunohistochemical Coding

BACKGROUND AND AIMS

Gut functions including motility, secretion, and blood flow are largely controlled by the enteric nervous system. Characterizing the different classes of enteric neurons in the human gut is an important step to understand how its circuitry is organized and how it is affected by disease.

METHODS

Using multiplexed immunohistochemistry, 12 discriminating antisera were applied to distinguish different classes of myenteric neurons in the human colon (2596 neurons, 12 patients) according to their chemical coding. All antisera were applied to every neuron, in multiple layers, separated by elutions.

RESULTS

A total of 164 combinations of immunohistochemical markers were present among the 2596 neurons, which could be divided into 20 classes, with statistical validation. Putative functions were ascribed for 4 classes of putative excitatory motor neurons (EMN1-4), 4 inhibitory motor neurons (IMN1-4), 3 ascending interneurons (AIN1-3), 6 descending interneurons (DIN1-6), 2 classes of multiaxonal sensory neurons (SN1-2), and a small, miscellaneous group (1.8% of total). Soma-dendritic morphology was analyzed, revealing 5 common shapes distributed differentially between the 20 classes. Distinctive baskets of axonal varicosities surrounded 45% of myenteric nerve cell bodies and were associated with close appositions, suggesting possible connectivity. Baskets of cholinergic terminals and several other types of baskets selectively targeted ascending interneurons and excitatory motor neurons but were significantly sparser around inhibitory motor neurons.

CONCLUSIONS

Using a simple immunohistochemical method, human myenteric neurons were shown to comprise multiple classes based on chemical coding and morphology and dense clusters of axonal varicosities were selectively associated with some classes.

mRNA isoform balance in neuronal development and disease

Balanced mRNA isoform diversity and abundance are spatially and temporally regulated throughout cellular differentiation. The proportion of expressed isoforms contributes to cell type specification and determines key properties of the differentiated cells. Neurons are unique cell types with intricate developmental programs, characteristic cellular morphologies, and electrophysiological potential. Neuron-specific gene expression programs establish these distinctive cellular characteristics and drive diversity among neuronal subtypes. Genes with neuron-specific alternative processing are enriched in key neuronal functions, including synaptic proteins, adhesion molecules, and scaffold proteins. Despite the similarity of neuronal gene expression programs, each neuronal subclass can be distinguished by unique alternative mRNA processing events. Alternative processing of developmentally important transcripts alters coding and regulatory information, including interaction domains, transcript stability, subcellular localization, and targeting by RNA binding proteins. Fine-tuning of mRNA processing is essential for neuronal activity and maintenance. Thus, the focus of neuronal RNA biology research is to dissect the transcriptomic mechanisms that underlie neuronal homeostasis, and consequently, predispose neuronal subtypes to disease. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

Genetically Defined Subtypes of Somatostatin-Containing Cortical Interneurons

Inhibitory interneurons play a crucial role in proper development and function of the mammalian cerebral cortex. Of the different inhibitory subclasses, dendritic-targeting, somatostatin-containing (SOM) interneurons may be the most diverse. Earlier studies used transgenic mouse lines to identify and characterize subtypes of SOM interneurons by morphological, electrophysiological and neurochemical properties. More recently, large-scale studies classified SOM interneurons into 13 morpho-electro-transcriptomic (MET) types. It remains unclear, however, how these various classification schemes relate to each other, and experimental access to MET types has been limited by the scarcity of type-specific mouse driver lines. To begin to address these issues we crossed Flp and Cre driver mouse lines and a dual-color combinatorial reporter, allowing experimental access to genetically defined SOM subsets. Brains from adult mice of both sexes were retrogradely dye-labeled from the pial surface to identify layer 1-projecting neurons, and immunostained against several marker proteins, allowing correlation of genetic label, axonal target and marker protein expression in the same neurons. Using whole-cell recordings ex-vivo, we compared electrophysiological properties between intersectional and transgenic SOM subsets. We identified two layer 1-targeting intersectional subsets with non-overlapping marker protein expression and electrophysiological properties which, together with a previously characterized layer 4-targeting subtype, account for about half of all layer 5 SOM cells and >40% of all SOM cells, and appear to map onto 5 of the 13 MET types. Genetic access to these subtypes will allow researchers to determine their synaptic inputs and outputs and uncover their roles in cortical computations and animal behavior.

SIGNIFICANCE STATEMENT

Inhibitory neurons are critically important for proper development and function of the cerebral cortex. Although a minority population, they are highly diverse, which poses a major challenge to investigating their contributions to cortical computations and animal and human behavior. As a step towards understanding this diversity we crossed genetically modified mouse lines to allow detailed examination of genetically-defined groups of the most diverse inhibitory subtype, somatostatin-containing interneurons. We identified and characterized three somatostatin subtypes in the deep cortical layers with distinct combinations of anatomical, neurochemical and electrophysiological properties. Future studies could now use these genetic tools to examine how these different subtypes are integrated into the cortical circuit and what roles they play during sensory, cognitive or motor behavior.

Advances in Single-Cell Toxicogenomics in Environmental Toxicology

The toxicity evaluation system of environmental pollutants has undergone numerous changes due to the application of new technologies. Single-cell toxicogenomics is rapidly changing our view on environmental toxicology by increasing the resolution of our analysis to the level of a single cell. Applications of this technology in environmental toxicology have begun to emerge and are rapidly expanding the portfolio of existing technologies and applications. Here, we first summarized different methods involved in single-cell isolation and amplification in single-cell sequencing process, compared the advantages and disadvantages of different methods, and analyzed their development trends. Then, we reviewed the main advances of single-cell toxicogenomics in environmental toxicology, emphatically analyzed the application prospects of this technology in identifying the target cells of pollutants in early embryos, clarifying the heterogeneous response of cell subtypes to pollutants, and finding pathogenic bacteria in unknown microbes, and highlighted the unique characteristics of this approach with high resolution, high throughput, and high specificity by examples. We also offered a prediction of the further application of this technology and the revolution it brings in environmental toxicology. Overall, these advances will provide practical solutions for controlling or mitigating exogenous toxicological effects that threaten human and ecosystem health, contribute to improving our understanding of the physiological processes affected by pollutants, and lead to the emergence of new methods of pollution control.

Activity-dependent modulation of synapse-regulating genes in astrocytes

Astrocytes regulate the formation and function of neuronal synapses via multiple signals; however, what controls regional and temporal expression of these signals during development is unknown. We determined the expression profile of astrocyte synapse-regulating genes in the developing mouse visual cortex, identifying astrocyte signals that show differential temporal and layer-enriched expression. These patterns are not intrinsic to astrocytes, but regulated by visually evoked neuronal activity, as they are absent in mice lacking glutamate release from thalamocortical terminals. Consequently, synapses remain immature. Expression of synapse-regulating genes and synaptic development is also altered when astrocyte signaling is blunted by diminishing calcium release from astrocyte stores. Single-nucleus RNA sequencing identified groups of astrocytic genes regulated by neuronal and astrocyte activity, and a cassette of genes that show layer-specific enrichment. Thus, the development of cortical circuits requires coordinated signaling between astrocytes and neurons, highlighting astrocytes as a target to manipulate in neurodevelopmental disorders.

Distinct neuron phenotypes may serve object feature sensing in the electrosensory lobe of Gymnotus omarorum

Early sensory relay circuits in the vertebrate medulla often adopt a cerebellum-like organization specialized for comparing primary afferent inputs with central expectations. These circuits usually have a dual output, carried by center ON and center OFF neurons responding in opposite ways to the same stimulus at the center of their receptive fields. Here, we show in the electrosensory lateral line lobe of Gymnotiform weakly electric fish that basilar pyramidal neurons, representing 'ON' cells, and non-basilar pyramidal neurons, representing 'OFF' cells, have different intrinsic electrophysiological properties. We used classical anatomical techniques and electrophysiological in vitro recordings to compare these neurons. Basilar neurons are silent at rest, have a high threshold to intracellular stimulation, delayed responses to steady-state depolarization and low pass responsiveness to membrane voltage variations. They respond to low-intensity depolarizing stimuli with large, isolated spikes. As stimulus intensity increases, the spikes are followed by a depolarizing after-potential from which phase-locked spikes often arise. Non-basilar neurons show a pacemaker-like spiking activity, smoothly modulated in frequency by slow variations of stimulus intensity. Spike-frequency adaptation provides a memory of their recent firing, facilitating non-basilar response to stimulus transients. Considering anatomical and functional dimensions, we conclude that basilar and non-basilar pyramidal neurons are clear-cut, different anatomo-functional phenotypes. We propose that, in addition to their role in contrast processing, basilar pyramidal neurons encode sustained global stimuli such as those elicited by large or distant objects while non-basilar pyramidal neurons respond to transient stimuli due to movement of objects with a textured surface.

Postnatal Arx transcriptional activity regulates functional properties of PV interneurons

The transcription factor Aristaless-related X-linked gene (Arx) is a monogenic factor in early onset epileptic encephalopathies (EOEEs) and a fundamental regulator of early stages of brain development. However, Arx expression persists in mature GABAergic neurons with an unknown role. To address this issue, we generated a conditional knockout (CKO) mouse in which postnatal Arx was ablated in parvalbumin interneurons (PVIs). Electroencephalogram (EEG) recordings in CKO mice revealed an increase in theta oscillations and the occurrence of occasional seizures. Behavioral analysis uncovered an increase in anxiety. Genome-wide sequencing of fluorescence activated cell sorted (FACS) PVIs revealed that Arx impinged on network excitability via genes primarily associated with synaptic and extracellular matrix pathways. Whole-cell recordings revealed prominent hypoexcitability of various intrinsic and synaptic properties. These results revealed important roles for postnatal Arx expression in PVIs in the control of neural circuits and that dysfunction in those roles alone can cause EOEE-like network abnormalities.

Estimation of neuron parameters from imperfect observations

The estimation of parameters controlling the electrical properties of biological neurons is essential to determine their complement of ion channels and to understand the function of biological circuits. By synchronizing conductance models to time series observations of the membrane voltage, one may construct models capable of predicting neuronal dynamics. However, identifying the actual set of parameters of biological ion channels remains a formidable theoretical challenge. Here, we present a regularization method that improves convergence towards this optimal solution when data are noisy and the model is unknown. Our method relies on the existence of an offset in parameter space arising from the interplay between model nonlinearity and experimental error. By tuning this offset, we induce saddle-node bifurcations from sub-optimal to optimal solutions. This regularization method increases the probability of finding the optimal set of parameters from 67% to 94.3%. We also reduce parameter correlations by implementing adaptive sampling and stimulation protocols compatible with parameter identifiability requirements. Our results show that the optimal model parameters may be inferred from imperfect observations provided the conditions of observability and identifiability are fulfilled.

Axonal degeneration as substrate of fractional anisotropy abnormalities in multiple sclerosis cortex

Cortical microstructural abnormalities are associated with clinical and cognitive deterioration in multiple sclerosis. Using diffusion tensor MRI, a higher fractional anisotropy has been found in cortical lesions versus normal-appearing cortex in multiple sclerosis. The pathological substrates of this finding have yet to be definitively elucidated. By performing a combined post-mortem diffusion tensor MRI and histopathology study, we aimed to define the histopathological substrates of diffusivity abnormalities in multiple sclerosis cortex. Sixteen subjects with multiple sclerosis and 10 age- and sex-matched non-neurological control donors underwent post-mortem in situ at 3 T MRI, followed by brain dissection. One hundred and ten paraffin-embedded tissue blocks (54 from multiple sclerosis patients, 56 from non-neurological controls) were matched to the diffusion tensor sequence to obtain regional diffusivity measures. Using immunohistochemistry and silver staining, cortical density of myelin, microglia, astrocytes and axons, and density and volume of neurons and glial cells were evaluated. Correlates of diffusivity abnormalities with histological markers were assessed through linear mixed-effects models. Cortical lesions (77% subpial) were found in 27/54 (50%) multiple sclerosis cortical regions. Multiple sclerosis normal-appearing cortex had a significantly lower fractional anisotropy compared to cortex from non-neurological controls (P = 0.047), whereas fractional anisotropy in demyelinated cortex was significantly higher than in multiple sclerosis normal-appearing cortex (P = 0.012) but not different from non-neurological control cortex (P = 0.420). Compared to non-neurological control cortex, both multiple sclerosis normal-appearing and demyelinated cortices showed a lower density of axons perpendicular to the cortical surface (P = 0.012 for both) and of total axons (parallel and perpendicular to cortical surface) (P = 0.028 and 0.012). In multiple sclerosis, demyelinated cortex had a lower density of myelin (P = 0.004), parallel (P = 0.018) and total axons (P = 0.029) versus normal-appearing cortex. Regarding the pathological substrate, in non-neurological controls, cortical fractional anisotropy was positively associated with density of perpendicular, parallel, and total axons (P = 0.031 for all). In multiple sclerosis, normal-appearing cortex fractional anisotropy was positively associated with perpendicular and total axon density (P = 0.031 for both), while associations with myelin, glial and total cells and parallel axons did not survive multiple comparison correction. Demyelinated cortex fractional anisotropy was positively associated with density of neurons, and total cells and negatively with microglia density, without surviving multiple comparison correction. Our results suggest that a reduction of perpendicular axons in normal-appearing cortex and of both perpendicular and parallel axons in demyelinated cortex may underlie the substrate influencing cortical microstructural coherence and being responsible for the different patterns of fractional anisotropy changes occurring in multiple sclerosis cortex.

Degeneracy in the emergence of spike-triggered average of hippocampal pyramidal neurons

Hippocampal pyramidal neurons are endowed with signature excitability characteristics, exhibit theta-frequency selectivity - manifesting as impedance resonance and as a band-pass structure in the spike-triggered average (STA) - and coincidence detection tuned for gamma-frequency inputs. Are there specific constraints on molecular-scale (ion channel) properties in the concomitant emergence of cellular-scale encoding (feature detection and selectivity) and excitability characteristics? Here, we employed a biophysically-constrained unbiased stochastic search strategy involving thousands of conductance-based models, spanning 11 active ion channels, to assess the concomitant emergence of 14 different electrophysiological measurements. Despite the strong biophysical and physiological constraints, we found models that were similar in terms of their spectral selectivity, operating mode along the integrator-coincidence detection continuum and intrinsic excitability characteristics. The parametric combinations that resulted in these functionally similar models were non-unique with weak pair-wise correlations. Employing virtual knockout of individual ion channels in these functionally similar models, we found a many-to-many relationship between channels and physiological characteristics to mediate this degeneracy, and predicted a dominant role for HCN and transient potassium channels in regulating hippocampal neuronal STA. Our analyses reveals the expression of degeneracy, that results from synergistic interactions among disparate channel components, in the concomitant emergence of neuronal excitability and encoding characteristics.

Quantitative firing pattern phenotyping of hippocampal neuron types

Systematically organizing the anatomical, molecular, and physiological properties of cortical neurons is important for understanding their computational functions. Hippocampome.org defines 122 neuron types in the rodent hippocampal formation based on their somatic, axonal, and dendritic locations, putative excitatory/inhibitory outputs, molecular marker expression, and biophysical properties. We augmented the electrophysiological data of this knowledge base by collecting, quantifying, and analyzing the firing responses to depolarizing current injections for every hippocampal neuron type from published experiments. We designed and implemented objective protocols to classify firing patterns based on 5 transients (delay, adapting spiking, rapidly adapting spiking, transient stuttering, and transient slow-wave bursting) and 4 steady states (non-adapting spiking, persistent stuttering, persistent slow-wave bursting, and silence). This automated approach revealed 9 unique (plus one spurious) families of firing pattern phenotypes while distinguishing potential new neuronal subtypes. Novel statistical associations emerged between firing responses and other electrophysiological properties, morphological features, and molecular marker expression. The firing pattern parameters, experimental conditions, spike times, references to the original empirical evidences, and analysis scripts are released open-source through Hippocampome.org for all neuron types, greatly enhancing the existing search and browse capabilities. This information, collated online in human- and machine-accessible form, will help design and interpret both experiments and model simulations.

Degeneracy in hippocampal physiology and plasticity

Degeneracy, defined as the ability of structurally disparate elements to perform analogous function, has largely been assessed from the perspective of maintaining robustness of physiology or plasticity. How does the framework of degeneracy assimilate into an encoding system where the ability to change is an essential ingredient for storing new incoming information? Could degeneracy maintain the balance between the apparently contradictory goals of the need to change for encoding and the need to resist change towards maintaining homeostasis? In this review, we explore these fundamental questions with the mammalian hippocampus as an example encoding system. We systematically catalog lines of evidence, spanning multiple scales of analysis that point to the expression of degeneracy in hippocampal physiology and plasticity. We assess the potential of degeneracy as a framework to achieve the conjoint goals of encoding and homeostasis without cross-interferences. We postulate that biological complexity, involving interactions among the numerous parameters spanning different scales of analysis, could establish disparate routes towards accomplishing these conjoint goals. These disparate routes then provide several degrees of freedom to the encoding-homeostasis system in accomplishing its tasks in an input- and state-dependent manner. Finally, the expression of degeneracy spanning multiple scales offers an ideal reconciliation to several outstanding controversies, through the recognition that the seemingly contradictory disparate observations are merely alternate routes that the system might recruit towards accomplishment of its goals.

Using brain organoids to study human neurodevelopment, evolution and disease

The brain is one of the most complex organs, responsible for the advanced intellectual and cognitive ability of humans. Although primates are to some extent capable of performing cognitive tasks, their abilities are less evolved. One of the reasons for this is the vast differences in the brain of humans compared to other mammals, in terms of shape, size and complexity. Such differences make the study of human brain development fascinating. Interestingly, the cerebral cortex is by far the most complex brain region resulting from its selective evolution within mammals over millions of years. Unraveling the molecular and cellular mechanisms regulating brain development, as well as the evolutionary differences seen across species and the need to understand human brain disorders, are some of the reasons why scientists are interested in improving their current knowledge on human corticogenesis. Toward this end, several animal models including primates have been used, however, these models are limited in their extent to recapitulate human-specific features. Recent technological achievements in the field of stem cell research, which have enabled the generation of human models of corticogenesis, called brain or cerebral organoids, are of great importance. This review focuses on the main cellular and molecular features of human corticogenesis and the use of brain organoids to study it. We will discuss the key differences between cortical development in human and nonhuman mammals, the technological applications of brain organoids and the different aspects of cortical development in normal and pathological conditions, which can be modeled using brain organoids. This article is categorized under: Comparative Development and Evolution > Regulation of Organ Diversity Nervous System Development > Vertebrates: General Principles.

A Brief History of Simulation Neuroscience

Our knowledge of the brain has evolved over millennia in philosophical, experimental and theoretical phases. We suggest that the next phase is simulation neuroscience. The main drivers of simulation neuroscience are big data generated at multiple levels of brain organization and the need to integrate these data to trace the causal chain of interactions within and across all these levels. Simulation neuroscience is currently the only methodology for systematically approaching the multiscale brain. In this review, we attempt to reconstruct the deep historical paths leading to simulation neuroscience, from the first observations of the nerve cell to modern efforts to digitally reconstruct and simulate the brain. Neuroscience began with the identification of the neuron as the fundamental unit of brain structure and function and has evolved towards understanding the role of each cell type in the brain, how brain cells are connected to each other, and how the seemingly infinite networks they form give rise to the vast diversity of brain functions. Neuronal mapping is evolving from subjective descriptions of cell types towards objective classes, subclasses and types. Connectivity mapping is evolving from loose topographic maps between brain regions towards dense anatomical and physiological maps of connections between individual genetically distinct neurons. Functional mapping is evolving from psychological and behavioral stereotypes towards a map of behaviors emerging from structural and functional connectomes. We show how industrialization of neuroscience and the resulting large disconnected datasets are generating demand for integrative neuroscience, how the scale of neuronal and connectivity maps is driving digital atlasing and digital reconstruction to piece together the multiple levels of brain organization, and how the complexity of the interactions between molecules, neurons, microcircuits and brain regions is driving brain simulation to understand the interactions in the multiscale brain.

A simplified morphological classification scheme for pyramidal cells in six layers of primary somatosensory cortex of juvenile rats

The majority of neurons in the neocortex are excitatory pyramidal cells (PCs). Many systematic classification schemes have been proposed based the neuronal morphology, the chemical composition, and the synaptic connectivity, etc. Recently, a cortical column of primary somatosensory cortex (SSC) has been reconstruction and functionally simulated (Markram et al., 2015). Putting forward from this study, here we proposed a simplified classification scheme for PCs in all layers of the SSC by mainly identifying apical dendritic morphology based on a large data set of 3D neuron reconstructions. We used this scheme to classify three types in layer 2, two in layer 3, three in layer 4, four in layer 5, and six types in layer 6. These PC types were visually distinguished and confirmed by quantitative differences in their morphometric properties. The classes yielded using this scheme largely corresponded with PC classes that were defined previously based on other neuronal and synaptic properties such as long-range projects and synaptic innervations, further validating its applicability. Therefore, the morphology information of apical dendrites is sufficient for a simple scheme to classify a spectrum of anatomical types of PCs in the SSC.

Development of lentiviral vectors for efficient glutamatergic-selective gene expression in cultured hippocampal neurons

Targeting gene expression to a particular subset of neurons helps study the cellular function of the nervous system. Although neuron-specific promoters, such as the synapsin I promoter and the α-CaMKII promoter, are known to exhibit selectivity for excitatory glutamatergic neurons in vivo, the cell type-specificity of these promoters has not been thoroughly tested in culture preparations. Here, by using hippocampal culture preparation from the VGAT-Venus transgenic mice, we examined the ability of five putative promoter sequences of glutamatergic-selective markers including synapsin I, α-CaMKII, the vesicular glutamate transporter 1 (VGLUT1), Dock10 and Prox1. Among these, a genomic fragment containing a 2.1 kb segment upstream of the translation start site (TSS) of the VGLUT1 implemented in a lentiviral vector with the Tet-Off inducible system achieved the highest preferential gene expression in glutamatergic neurons. Analysis of various lengths of the VGLUT1 promoter regions identified a segment between −2.1 kb and −1.4 kb from the TSS as a responsible element for the glutamatergic selectivity. Consistently, expression of channelrhodopsin under this promoter sequence allowed for selective light-evoked activation of excitatory neurons. Thus, the lentiviral system carrying the VGLUT1 promoter fragment can be used to effectively target exogenous gene expression to excitatory glutamatergic neurons in cultures.

Parallel Development of Chromatin Patterns, Neuron Morphology, and Connections: Potential for Disruption in Autism

The phenotype of neurons and their connections depend on complex genetic and epigenetic processes that regulate the expression of genes in the nucleus during development and throughout life. Here we examined the distribution of nuclear chromatin patters in relation to the epigenetic landscape, phenotype and connections of neurons with a focus on the primate cerebral cortex. We show that nuclear patterns of chromatin in cortical neurons are related to neuron size and cortical connections. Moreover, we point to evidence that reveals an orderly sequence of events during development, linking chromatin and gene expression patterns, neuron morphology, function, and connections across cortical areas and layers. Based on this synthesis, we posit that systematic studies of changes in chromatin patterns and epigenetic marks across cortical areas will provide novel insights on the development and evolution of cortical networks, and their disruption in connectivity disorders of developmental origin, like autism. Achieving this requires embedding and interpreting genetic, transcriptional, and epigenetic studies within a framework that takes into consideration distinct types of neurons, local circuit interactions, and interareal pathways. These features vary systematically across cortical areas in parallel with laminar structure and are differentially affected in disorders. Finally, based on evidence that autism-associated genetic polymorphisms are especially prominent in excitatory neurons and connectivity disruption affects mostly limbic cortices, we employ this systematic approach to propose novel, targeted studies of projection neurons in limbic areas to elucidate the emergence and time-course of developmental disruptions in autism.

Ih interacts with somato-dendritic structure to determine frequency response to weak alternating electric field stimulation

Transcranial current stimulation (tCS) modulates brain dynamics using weak electric fields. Given the pathological changes in brain network oscillations in neurological and psychiatric illnesses, using alternating electric field waveforms that engage rhythmic activity has been proposed as a targeted, network-level treatment approach. Previous studies have investigated the effects of electric fields at the neuronal level. However, the biophysical basis of the cellular response to electric fields has remained limited. Here, we characterized the frequency-dependent response of different compartments in a layer V pyramidal neuron to exogenous electric fields to dissect the relative contributions of voltage-gated ion channels and neuronal morphology. Hyperpolarization-activated cation current (I_h) in the distal dendrites was the primary ionic mechanism shaping the model's response to electric field stimulation and caused subthreshold resonance in the tuft at 20 ± 4 Hz. In contrast, subthreshold I_h-mediated resonance in response to local sinusoidal current injection was present in all model compartments at 11 ± 2 Hz. The frequencies of both resonance responses were modulated by I_h conductance density. We found that the difference in resonance frequency between the two stimulation types can be explained by the fact that exogenous electric fields simultaneously polarize the membrane potentials at the distal ends of the neuron (relative to field direction) in opposite directions. Our results highlight the role of I_h in shaping the cellular response to electric field stimulation and suggest that the common model of tCS as a weak somatic current injection fails to capture the cellular effects of electric field stimulation. NEW & NOTEWORTHY Modulation of cortical oscillation by brain stimulation serves as a tool to understand the causal role of network oscillations in behavior and is a potential treatment modality that engages impaired network oscillations in disorders of the central nervous system. To develop targeted stimulation paradigms, cellular-level effects must be understood. We demonstrate that hyperpolarization-activated cation current (I_h) and cell morphology cooperatively shape the response to applied alternating electric fields.

Single-cell analysis of diversity in human stem cell-derived neurons

Neural stem and progenitor cells produce one of the most remarkable organs in nature, the human brain. Among neural stem cell progeny, post-mitotic neurons are likewise remarkably diverse. Single-cell transcriptomic approaches are now cataloging a long-sought-after molecular taxonomy of neuronal diversity in the brain. Contemporary single-cell omic classifications of neuronal diversity build from electrophysiological approaches that for decades have measured and cataloged diverse biophysical properties of single neurons. With the widespread application of human pluripotent stem cell-based models of neurogenesis to investigate disease pathology and to develop new drugs, a high-resolution understanding of neuronal diversity in vivo is essential to benchmark the state of in vitro models of human neurological disease.

Implications of Schwann Cells Biomechanics and Mechanosensitivity for Peripheral Nervous System Physiology and Pathophysiology

The presence of bones around the central nervous system (CNS) provides it with highly effective physiologically crucial mechanical protection. The peripheral nervous system (PNS), in contrast, lacks this barrier. Consequently, the long held belief is that the PNS is mechanically vulnerable. On the other hand, the PNS is exposed to a variety of physiological mechanical stresses during regular daily activities. This fact prompts us to question the dogma of PNS mechanical vulnerability. As a matter of fact, impaired mechanics of PNS nerves is associated with neuropathies with the liability to mechanical stresses paralleled by significant impairment of PNS physiological functions. Our recent biomechanical integrity investigations on nerve fibers from wild-type and neuropathic mice lend strong support in favor of natural mechanical protection of the PNS and demonstrate a key role of Schwann cells (SCs) therein. Moreover, recent works point out that SCs can sense mechanical properties of their microenvironment and the evidence is growing that SCs mechanosensitivity is important for PNS development and myelination. Hence, SCs exhibit mechanical strength necessary for PNS mechanoprotection as well as mechanosensitivity necessary for PNS development and myelination. This mini review reflects on the intriguing dual ability of SCs and implications for PNS physiology and pathophysiology.

Neuronal cell-type classification: challenges, opportunities and the path forward

Neurons have diverse molecular, morphological, connectional and functional properties. We believe that the only realistic way to manage this complexity - and thereby pave the way for understanding the structure, function and development of brain circuits - is to group neurons into types, which can then be analysed systematically and reproducibly. However, neuronal classification has been challenging both technically and conceptually. New high-throughput methods have created opportunities to address the technical challenges associated with neuronal classification by collecting comprehensive information about individual cells. Nonetheless, conceptual difficulties persist. Borrowing from the field of species taxonomy, we propose principles to be followed in the cell-type classification effort, including the incorporation of multiple, quantitative features as criteria, the use of discontinuous variation to define types and the creation of a hierarchical system to represent relationships between cells. We review the progress of classifying cell types in the retina and cerebral cortex and propose a staged approach for moving forward with a systematic cell-type classification in the nervous system.

Homeostatic Plasticity of Subcellular Neuronal Structures: From Inputs to Outputs

Neurons in the brain are highly plastic, allowing an organism to learn and adapt to its environment. However, this ongoing plasticity is also inherently unstable, potentially leading to aberrant levels of circuit activity. Homeostatic forms of plasticity are thought to provide a means of controlling neuronal activity by avoiding extremes and allowing network stability. Recent work has shown that many of these homeostatic modifications change the structure of subcellular neuronal compartments, ranging from changes to synaptic inputs at both excitatory and inhibitory compartments to modulation of neuronal output through changes at the axon initial segment (AIS) and presynaptic terminals. Here we review these different forms of structural plasticity in neurons and the effects they may have on network function.

The possible consequences for cognitive functions of external electric fields at power line frequency on hippocampal CA1 pyramidal neurons

The possible effects on cognitive processes of external electric fields, such as those generated by power line pillars and household appliances are of increasing public concern. They are difficult to study experimentally, and the relatively scarce and contradictory evidence make it difficult to clearly assess these effects. In this study, we investigate how, why and to what extent external perturbations of the intrinsic neuronal activity, such as those that can be caused by generation, transmission and use of electrical energy can affect neuronal activity during cognitive processes. For this purpose, we used a morphologically and biophysically realistic three-dimensional model of CA1 pyramidal neurons. The simulation findings suggest that an electric field oscillating at power lines frequency, and environmentally measured strength, can significantly alter both the average firing rate and temporal spike distribution properties of a hippocampal CA1 pyramidal neuron. This effect strongly depends on the specific and instantaneous relative spatial location of the neuron with respect to the field, and on the synaptic input properties. The model makes experimentally testable predictions on the possible functional consequences for normal hippocampal functions such as object recognition and spatial navigation. The results suggest that, although EF effects on cognitive processes may be difficult to occur in everyday life, their functional consequences deserve some consideration, especially when they constitute a systematic presence in living environments.

NBLAST: Rapid, Sensitive Comparison of Neuronal Structure and Construction of Neuron Family Databases

Neural circuit mapping is generating datasets of tens of thousands of labeled neurons. New computational tools are needed to search and organize these data. We present NBLAST, a sensitive and rapid algorithm, for measuring pairwise neuronal similarity. NBLAST considers both position and local geometry, decomposing neurons into short segments; matched segments are scored using a probabilistic scoring matrix defined by statistics of matches and non-matches. We validated NBLAST on a published dataset of 16,129 single Drosophila neurons. NBLAST can distinguish neuronal types down to the finest level (single identified neurons) without a priori information. Cluster analysis of extensively studied neuronal classes identified new types and unreported topographical features. Fully automated clustering organized the validation dataset into 1,052 clusters, many of which map onto previously described neuronal types. NBLAST supports additional query types, including searching neurons against transgene expression patterns. Finally, we show that NBLAST is effective with data from other invertebrates and zebrafish.

Video Abstract

•

NBLAST is a fast and sensitive algorithm to measure pairwise neuronal similarity

•

NBLAST can distinguish neuronal types at the finest level without training

•

Automated clustering of 16,129 Drosophila neurons identifies 1,052 classes

•

Online search tool for databases of single neurons or genetic driver lines

Effects of Morphology Constraint on Electrophysiological Properties of Cortical Neurons

There is growing interest in engineering nerve cells in vitro to control architecture and connectivity of cultured neuronal networks or to build neuronal networks with predictable computational function. Pattern technologies, such as micro-contact printing, have been developed to design ordered neuronal networks. However, electrophysiological characteristics of the single patterned neuron haven't been reported. Here, micro-contact printing, using polyolefine polymer (POP) stamps with high resolution, was employed to grow cortical neurons in a designed structure. The results demonstrated that the morphology of patterned neurons was well constrained, and the number of dendrites was decreased to be about 2. Our electrophysiological results showed that alterations of dendritic morphology affected firing patterns of neurons and neural excitability. When stimulated by current, though both patterned and un-patterned neurons presented regular spiking, the dynamics and strength of the response were different. The un-patterned neurons exhibited a monotonically increasing firing frequency in response to injected current, while the patterned neurons first exhibited frequency increase and then a slow decrease. Our findings indicate that the decrease in dendritic complexity of cortical neurons will influence their electrophysiological characteristics and alter their information processing activity, which could be considered when designing neuronal circuitries.

Spatiotemporal expression and transcriptional perturbations by long noncoding RNAs in the mouse brain

Long noncoding RNAs (lncRNAs) have been implicated in numerous cellular processes including brain development. However, the in vivo expression dynamics and molecular pathways regulated by these loci are not well understood. Here, we leveraged a cohort of 13 lncRNAnull mutant mouse models to investigate the spatiotemporal expression of lncRNAs in the developing and adult brain and the transcriptome alterations resulting from the loss of these lncRNA loci. We show that several lncRNAs are differentially expressed both in time and space, with some presenting highly restricted expression in only selected brain regions. We further demonstrate altered regulation of genes for a large variety of cellular pathways and processes upon deletion of the lncRNA loci. Finally, we found that 4 of the 13 lncRNAs significantly affect the expression of several neighboring proteincoding genes in a cis-like manner. By providing insight into the endogenous expression patterns and the transcriptional perturbations caused by deletion of the lncRNA locus in the developing and postnatal mammalian brain, these data provide a resource to facilitate future examination of the specific functional relevance of these genes in neural development, brain function, and disease.

New neurons in the adult striatum: from rodents to humans

Most neurons are generated during development and are not replaced during adulthood, even if they are lost to injury or disease. However, it is firmly established that new neurons are generated in the dentate gyrus of the hippocampus of almost all adult mammals, including humans. Nevertheless, many questions remain regarding adult neurogenesis in other brain regions and particularly in humans, where standard birth-dating methods are not generally feasible. Exciting recent evidence indicates that calretinin-expressing interneurons are added to the adult human striatum at a substantial rate. The role of new neurons is unknown, but studies in rodents will be able to further elucidate their identity and origin and then we may begin to understand their regulation and function.

Building blocks of the cerebral cortex: from development to the dish

Since Ramon y Cajal's examination of the cellular makeup of the cerebral cortex, it has been appreciated that this tissue exhibits some of the greatest degrees of cellular heterogeneity in the entire nervous system. This intricate structure emerges during a well-choreographed developmental process. Here, we review current classifications of the cellular constituents of the cerebral cortex and examine how these building blocks are forged during development. We also look at how basic developmental features underlying cortex formation in vivo have been applied to protocols aimed at generating cortical tissue in vitro.

Brain-wide analysis of electrophysiological diversity yields novel categorization of mammalian neuron types

For decades, neurophysiologists have characterized the biophysical properties of a rich diversity of neuron types. However, identifying common features and computational roles shared across neuron types is made more difficult by inconsistent conventions for collecting and reporting biophysical data. Here, we leverage NeuroElectro, a literature-based database of electrophysiological properties (www.neuroelectro.org), to better understand neuronal diversity, both within and across neuron types, and the confounding influences of methodological variability. We show that experimental conditions (e.g., electrode types, recording temperatures, or animal age) can explain a substantial degree of the literature-reported biophysical variability observed within a neuron type. Critically, accounting for experimental metadata enables massive cross-study data normalization and reveals that electrophysiological data are far more reproducible across laboratories than previously appreciated. Using this normalized dataset, we find that neuron types throughout the brain cluster by biophysical properties into six to nine superclasses. These classes include intuitive clusters, such as fast-spiking basket cells, as well as previously unrecognized clusters, including a novel class of cortical and olfactory bulb interneurons that exhibit persistent activity at theta-band frequencies.

Specification of excitatory neurons in the developing cerebral cortex: progenitor diversity and environmental influences

The mature cerebral cortex harbors a heterogeneous population of glutamatergic neurons, organized into a highly intricate histological architecture. Classically, this mixed population of neurons was thought to be generated sequentially from a seemingly homogenous group of progenitors under the influence of external cues. This view, however, has been challenged in the last decade by evidences pointing to the existence of fate-restricted neuronal progenitors in the developing neocortex. Here, we review classical studies using cell transplantation, retroviral labeling and cell culture, as well as new data from genetic fate-mapping analysis, to discuss the lineage relationships between neocortical progenitors and subclasses of excitatory neurons. We also propose a temporal model to conciliate the existence of fate-restricted progenitors alongside multipotent progenitors in the neocortex. Finally, we discuss evidences for a critical period of plasticity among post mitotic excitatory cortical neurons when environmental influences could change neuronal cell fate.

Cerebral cortex assembly: generating and reprogramming projection neuron diversity

The mammalian cerebral cortex is responsible for the highest levels of associative, cognitive and motor functions. In the central nervous system (CNS) the cortex stands as a prime example of extreme neuronal diversity, broadly classified into excitatory projection neurons (PNs) and inhibitory interneurons (INs). We review here recent progress made in understanding the strategies and mechanisms that shape PN diversity during embryogenesis, and discuss how PN classes may be maintained, postnatally, for the life of the organism. In addition, we consider the intriguing possibility that PNs may be amenable to directed reprogramming of their class-specific features to allow enhanced cortical plasticity in the adult.

Effects of low frequency electric fields on synaptic integration in hippocampal CA1 pyramidal neurons: implications for power line emissions

The possible cognitive effects of low frequency external electric fields (EFs), such as those generated by power lines, are poorly understood. Their functional consequences for mechanisms at the single neuron level are very difficult to study and identify experimentally, especially in vivo. The major open problem is that experimental investigations on humans have given inconsistent or contradictory results, making it difficult to estimate the possible effects of external low frequency electric fields on cognitive functions. Here we investigate this issue with realistic models of hippocampal CA1 pyramidal neurons. Our findings suggest how and why EFs, with environmentally observed frequencies and intensities far lower than what is required for direct neural activation, can perturb dendritic signal processing and somatic firing of neurons that are crucially involved in cognitive tasks such as learning and memory. These results show that individual neuronal morphology, ion channel dendritic distribution, and alignment with the electric field are major determinants of overall effects, and provide a physiologically plausible explanation of why experimental findings can appear to be small and difficult to reproduce, yet deserve serious consideration.

Effects of increasing CREB-dependent transcription on the storage and recall processes in a hippocampal CA1 microcircuit

The involvement of the hippocampus in learning processes and major brain diseases makes it an ideal candidate to investigate possible ways to devise effective therapies for memory-related pathologies like Alzheimer's Disease (AD). It has been previously reported that augmenting CREB activity increases the synaptic Long-Term Potentiation (LTP) magnitude in CA1 pyramidal neurons and their intrinsic excitability in healthy rodents. It has also been suggested that hippocampal CREB signaling is likely to be down-regulated during AD, possibly degrading memory functions. Therefore, the concept of CREB-based memory enhancers, i.e. drugs that would boost memory by activation of CREB, has emerged. Here, using a model of a CA1 microcircuit, we investigate whether hippocampal CA1 pyramidal neuron properties altered by increasing CREB activity may contribute to improve memory storage and recall. With a set of patterns presented to a network, we find that the pattern recall quality under AD-like conditions is significantly better when boosting CREB function with respect to control. The results are robust and consistent upon increasing the synaptic damage expected by AD progression, supporting the idea that the use of CREB-based therapies could provide a new approach to treat AD.

Gene co-regulation by Fezf2 selects neurotransmitter identity and connectivity of corticospinal neurons

The neocortex contains an unparalleled diversity of neuronal subtypes, each defined by distinct traits that are developmentally acquired under the control of subtype-specific and pan-neuronal genes. The regulatory logic that orchestrates the expression of these unique combinations of genes is unknown for any class of cortical neuron. Here, we report that Fezf2 is a selector gene able to regulate the expression of gene sets that collectively define mouse corticospinal motor neurons (CSMN). We find that Fezf2 directly induces the glutamatergic identity of CSMN via activation of Vglut1 (Slc17a7) and inhibits a GABAergic fate by repressing transcription of Gad1. In addition, we identify the axon guidance receptor EphB1 as a target of Fezf2 necessary to execute the ipsilateral extension of the corticospinal tract. Our data indicate that co-regulated expression of neuron subtype-specific and pan-neuronal gene batteries by a single transcription factor is one component of the regulatory logic responsible for the establishment of CSMN identity.

How big is the myelinating orchestra? Cellular diversity within the oligodendrocyte lineage: facts and hypotheses

Since monumental studies from scientists like His, Ramón y Cajal, Lorente de Nó and many others have put down roots for modern neuroscience, the scientific community has spent a considerable amount of time, and money, investigating any possible aspect of the evolution, development and function of neurons. Today, the complexity and diversity of myriads of neuronal populations, and their progenitors, is still focus of extensive studies in hundreds of laboratories around the world. However, our prevalent neuron-centric perspective has dampened the efforts in understanding glial cells, even though their active participation in the brain physiology and pathophysiology has been increasingly recognized over the years. Among all glial cells of the central nervous system (CNS), oligodendrocytes (OLs) are a particularly specialized type of cells that provide fundamental support to neuronal activity by producing the myelin sheath. Despite their functional relevance, the developmental mechanisms regulating the generation of OLs are still poorly understood. In particular, it is still not known whether these cells share the same degree of heterogeneity of their neuronal companions and whether multiple subtypes exist within the lineage. Here, we will review and discuss current knowledge about OL development and function in the brain and spinal cord. We will try to address some specific questions: do multiple OL subtypes exist in the CNS? What is the evidence for their existence and those against them? What are the functional features that define an oligodendrocyte? We will end our journey by reviewing recent advances in human pluripotent stem cell differentiation towards OLs. This exciting field is still at its earliest days, but it is quickly evolving with improved protocols to generate functional OLs from different spatial origins. As stem cells constitute now an unprecedented source of human OLs, we believe that they will become an increasingly valuable tool for deciphering the complexity of human OL identity.

Optimizing neuronal differentiation from induced pluripotent stem cells to model ASD

Autism spectrum disorder (ASD) is an early-onset neurodevelopmental disorder characterized by deficits in social communication, and restricted and repetitive patterns of behavior. Despite its high prevalence, discovery of pathophysiological mechanisms underlying ASD has lagged due to a lack of appropriate model systems. Recent advances in induced pluripotent stem cell (iPSC) technology and neural differentiation techniques allow for detailed functional analyses of neurons generated from living individuals with ASD. Refinement of cortical neuron differentiation methods from iPSCs will enable mechanistic studies of specific neuronal subpopulations that may be preferentially impaired in ASD. In this review, we summarize recent accomplishments in differentiation of cortical neurons from human pluripotent stems cells and efforts to establish in vitro model systems to study ASD using personalized neurons.

Splicing factor TRA2B is required for neural progenitor survival

Alternative splicing of pre-mRNAs can rapidly regulate the expression of large groups of proteins. The RNA binding protein TRA2B (SFRS10) plays well-established roles in developmentally regulated alternative splicing during Drosophila sexual differentiation. TRA2B is also essential for mammalian embryogenesis and is implicated in numerous human diseases. Precise regulation of alternative splicing is critical to the development and function of the central nervous system; however, the requirements for specific splicing factors in neurogenesis are poorly understood. This study focuses on the role of TRA2B in mammalian brain development. We show that, during murine cortical neurogenesis, TRA2B is expressed in both neural progenitors and cortical projection neurons. Using cortex-specific Tra2b mutant mice, we show that TRA2B depletion results in apoptosis of the neural progenitor cells as well as disorganization of the cortical plate. Thus, TRA2B is essential for proper development of the cerebral cortex.

From the intrinsic properties to the functional role of a neuron phenotype: an example from electric fish during signal trade-off

This review deals with the question: what is the relationship between the properties of a neuron and the role that the neuron plays within a given neural circuit? Answering this kind of question requires collecting evidence from multiple neuron phenotypes and comparing the role of each type in circuits that perform well-defined computational tasks. The focus here is on the spherical neurons in the electrosensory lobe of the electric fish Gymnotus omarorum. They belong to the one-spike-onset phenotype expressed at the early stages of signal processing in various sensory modalities and diverse taxa. First, we refer to the one-spike neuron intrinsic properties, their foundation on a low-threshold K(+) conductance, and the potential roles of this phenotype in different circuits within a comparative framework. Second, we present a brief description of the active electric sense of weakly electric fish and the particularities of spherical one-spike-onset neurons in the electrosensory lobe of G. omarorum. Third, we introduce one of the specific tasks in which these neurons are involved: the trade-off between self- and allo-generated signals. Fourth, we discuss recent evidence indicating a still-undescribed role for the one-spike phenotype. This role deals with the blockage of the pathway after being activated by the self-generated electric organ discharge and how this blockage favors self-generated electrosensory information in the context of allo-generated interference. Based on comparative analysis we conclude that one-spike-onset neurons may play several functional roles in animal sensory behavior. There are specific adaptations of the neuron's 'response function' to the circuit and task. Conversely, the way in which a task is accomplished depends on the intrinsic properties of the neurons involved. In short, the role of a neuron within a circuit depends on the neuron and its functional context.

Molecular logic of neocortical projection neuron specification, development and diversity

The sophisticated circuitry of the neocortex is assembled from a diverse repertoire of neuronal subtypes generated during development under precise molecular regulation. In recent years, several key controls over the specification and differentiation of neocortical projection neurons have been identified. This work provides substantial insight into the 'molecular logic' underlying cortical development and increasingly supports a model in which individual progenitor-stage and postmitotic regulators are embedded within highly interconnected networks that gate sequential developmental decisions. Here, we provide an integrative account of the molecular controls that direct the progressive development and delineation of subtype and area identity of neocortical projection neurons.

NeuroLex.org: an online framework for neuroscience knowledge

The ability to transmit, organize, and query information digitally has brought with it the challenge of how to best use this power to facilitate scientific inquiry. Today, few information systems are able to provide detailed answers to complex questions about neuroscience that account for multiple spatial scales, and which cross the boundaries of diverse parts of the nervous system such as molecules, cellular parts, cells, circuits, systems and tissues. As a result, investigators still primarily seek answers to their questions in an increasingly densely populated collection of articles in the literature, each of which must be digested individually. If it were easier to search a knowledge base that was structured to answer neuroscience questions, such a system would enable questions to be answered in seconds that would otherwise require hours of literature review. In this article, we describe NeuroLex.org, a wiki-based website and knowledge management system. Its goal is to bring neurobiological knowledge into a framework that allows neuroscientists to review the concepts of neuroscience, with an emphasis on multiscale descriptions of the parts of nervous systems, aggregate their understanding with that of other scientists, link them to data sources and descriptions of important concepts in neuroscience, and expose parts that are still controversial or missing. To date, the site is tracking ~25,000 unique neuroanatomical parts and concepts in neurobiology spanning experimental techniques, behavioral paradigms, anatomical nomenclature, genes, proteins and molecules. Here we show how the structuring of information about these anatomical parts in the nervous system can be reused to answer multiple neuroscience questions, such as displaying all known GABAergic neurons aggregated in NeuroLex or displaying all brain regions that are known within NeuroLex to send axons into the cerebellar cortex.

Challenges of understanding brain function by selective modulation of neuronal subpopulations

Neuronal networks confront researchers with an overwhelming complexity of interactions between their elements. A common approach to understanding neuronal processing is to reduce complexity by defining subunits and infer their functional role by selectively modulating them. However, this seemingly straightforward approach may lead to confusing results if the network exhibits parallel pathways leading to recurrent connectivity. We demonstrate limits of the selective modulation approach and argue that, even though highly successful in some instances, the approach fails in networks with complex connectivity. We argue to refine experimental techniques by carefully considering the structural features of the neuronal networks involved. Such methods could dramatically increase the effectiveness of selective modulation and may lead to a mechanistic understanding of principles underlying brain function.

Blood chromatin as a biosensor of the epigenetic milieu: a tool for studies in living psychiatric patients

This article constructs an argument for using blood chromatin (contained in nucleated blood cells) as a protein biosensor to integrate the ambient epigenetic influences in the internal milieu. An analogy is made to blood glycated hemoglobin (HbA1c) in diabetes as an integrated proxy for glucose levels and body-wide protein glycation. Genome-wide chromatin can serve as an organizing principle that bridges the central and peripheral compartments by entraining commensurable gene networks. Chromatin deposition along these networks will be imposed by the totality of epigenetic influences, which incorporates significant contributions from biochemicals that readily traverse the blood-brain barrier. In a clinical trial, these influences would be dominated by pharmaceuticals designed to override pathophysiological signals. In practice, mRNA readouts would be limited to nonsynaptic gene networks whose critical nodes are occupied by a site-specific chromatin modification. Finally, chromatin measurements in peripheral tissue will retain the influences of a patient's lifestyle and unique genomic background.