Understanding brain function requires monitoring and interpreting the activity of large networks of neurons during behavior. Advances in recording technology are greatly increasing the size and complexity of neural data. Analyzing such data will pose a fundamental bottleneck for neuroscience. We present a library of analytical tools called Thunder built on the open-source Apache Spark platform for large-scale distributed computing. The library implements a variety of univariate and multivariate analyses with a modular, extendable structure well-suited to interactive exploration and analysis development. We demonstrate how these analyses find structure in large-scale neural data, including whole-brain light-sheet imaging data from fictively behaving larval zebrafish, and two-photon imaging data from behaving mouse. The analyses relate neuronal responses to sensory input and behavior, run in minutes or less and can be used on a private cluster or in the cloud. Our open-source framework thus holds promise for turning brain activity mapping efforts into biological insights.

Systemic lupus erythematosus (SLE) is an autoimmune disease with a strong genetic component. We recently identified a novel SLE susceptibility locus near RASGRP1, which governs the ERK/MAPK kinase cascade and B-/T-cell differentiation and development. However, precise causal RASGRP1functional variant(s) and their mechanisms of action in SLE pathogenesis remain undefined. Our goal was to fine-map this locus, prioritize genetic variants likely to be functional, experimentally validate their biochemical mechanisms, and determine the contribution of these SNPs to SLE risk. We performed a meta-analysis across six Asian and European cohorts (9,529 cases; 22,462 controls), followed by in silico bioinformatic and epigenetic analyses to prioritize potentially functional SNPs. We experimentally validated the functional significance and mechanism of action of three SNPs in cultured T-cells. Meta-analysis identified 18 genome-wide significant (p < 5 × 10−8) SNPs, mostly concentrated in two haplotype blocks, one intronic and the other intergenic. Epigenetic fine-mapping, allelic, eQTL, and imbalance analyses predicted three transcriptional regulatory regions with four SNPs (rs7170151, rs11631591-rs7173565, and rs9920715) prioritized for functional validation. Luciferase reporter assays indicated significant allele-specific enhancer activity for intronic rs7170151 and rs11631591-rs7173565 in T-lymphoid (Jurkat) cells, but not in HEK293 cells. Following up with EMSA, mass spectrometry, and ChIP-qPCR, we detected allele-dependent interactions between heterogeneous nuclear ribonucleoprotein K (hnRNP-K) and rs11631591. Furthermore, inhibition of hnRNP-K in Jurkat and primary T-cells downregulated RASGRP1 and ERK/MAPK signaling. Comprehensive association, bioinformatics, and epigenetic analyses yielded putative functional variants of RASGRP1, which were experimentally validated. Notably, intronic variant (rs11631591) is located in a cell type-specific enhancer sequence, where its risk allele binds to the hnRNP-K protein and modulates RASGRP1 expression in Jurkat and primary T-cells. As risk allele dosage of rs11631591 correlates with increased RASGRP1 expression and ERK activity, we suggest that this SNP may underlie SLE risk at this locus.

In mammals, subplate neurons (SPNs) are among the first generated cortical neurons. While most SPNs exist only transiently during development, a number of SPNs persist among adult Layer 6b (L6b). During development, SPNs receive thalamic and intra-cortical input, and primarily project to Layer 4 (L4). SPNs are critical for the anatomical and functional development of thalamocortical connections and also pioneer corticothalamic projections. Since SPNs are heterogeneous, SPN subpopulations might serve different roles. Here, we investigate the connectivity of one subpopulation, complexin-3 (Cplx3)-positive SPNs (Cplx3-SPNs), in mouse whisker somatosensory (barrel) cortex (S1). We find that many Cplx3-SPNs survive into adulthood and become a subpopulation of L6b. Cplx3-SPNs axons project to thalamorecipient layers, that is, L4, 5a, and 1. The L4 projections are biased towards the septal regions between barrels in the second postnatal week. Thus, S1 Cplx3-SPN targets co-localize with the eventual projections of the medial posterior thalamic nucleus (POm). In addition to their cortical targets, Cplx3-SPNs also extend long-range axons to several thalamic nuclei, including POm. Thus, Cplx3-SPN/L6b neurons are associated with paralemniscal pathways and can potentially directly link thalamocortical and corticothalamic circuits. This suggests an additional key role for SPNs in the establishment and maintenance of thalamocortical processing.

The mechanisms linking sensation and action during learning are poorly understood. Layer 2/3 neurons in the motor cortex might participate in sensorimotor integration and learning; they receive input from sensory cortex and excite deep layer neurons, which control movement. Here we imaged activity in the same set of layer 2/3 neurons in the motor cortex over weeks, while mice learned to detect objects with their whiskers and report detection with licking. Spatially intermingled neurons represented sensory (touch) and motor behaviours (whisker movements and licking). With learning, the population-level representation of task-related licking strengthened. In trained mice, population-level representations were redundant and stable, despite dynamism of single-neuron representations. The activity of a subpopulation of neurons was consistent with touch driving licking behaviour. Our results suggest that ensembles of motor cortex neurons couple sensory input to multiple, related motor programs during learning.

Information processing by brain circuits depends on Ca-dependent, stochastic release of the excitatory neurotransmitter glutamate. Whilst optical glutamate sensors have enabled detection of synaptic discharges, understanding presynaptic machinery requires simultaneous readout of glutamate release and nanomolar presynaptic Ca in situ. Here, we find that the fluorescence lifetime of the red-shifted Ca indicator Cal-590 is Ca-sensitive in the nanomolar range, and employ it in combination with green glutamate sensors to relate quantal neurotransmission to presynaptic Ca kinetics. Multiplexed imaging of individual and multiple synapses in identified axonal circuits reveals that glutamate release efficacy, but not its short-term plasticity, varies with time-dependent fluctuations in presynaptic resting Ca or spike-evoked Ca entry. Within individual presynaptic boutons, we find no nanoscopic co-localisation of evoked presynaptic Ca entry with the prevalent glutamate release site, suggesting loose coupling between the two. The approach enables a better understanding of release machinery at central synapses.

How neuromodulatory transmitters diffuse into the extracellular space remains an unsolved fundamental biological question, despite wide acceptance of the volume transmission model. Here, we report development of a method combining genetically encoded fluorescent sensors with high-resolution imaging and analysis algorithms which permits the first direct visualization of neuromodulatory transmitter diffusion at various neuronal and non-neuronal cells. Our analysis reveals that acetylcholine and monoamines diffuse at individual release sites with a spread length constant of ∼0.75 μm. These transmitters employ varied numbers of release sites, and when spatially close-packed release sites coactivate they can spillover into larger subcellular areas. Our data indicate spatially restricted (i.e., nonvolume) neuromodulatory transmission to be a prominent intercellular communication mode, reshaping current thinking of control and precision of neuromodulation crucial for understanding behaviors and diseases.

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

Imaging approaches based on single molecule localization break the diffraction barrier of conventional fluorescence microscopy, allowing for bioimaging with nanometer resolution. It remains a challenge, however, to precisely localize photon-limited single molecules in 3D. We have developed a new localization-based imaging technique achieving almost isotropic subdiffraction resolution in 3D. A tilted mirror is used to generate a side view in addition to the front view of activated single emitters, allowing their 3D localization to be precisely determined for superresolution imaging. Because both front and side views are in focus, this method is able to efficiently collect emitted photons. The technique is simple to implement on a commercial fluorescence microscope, and especially suitable for biological samples with photon-limited chromophores such as endogenously expressed photoactivatable fluorescent proteins. Moreover, this method is relatively resistant to optical aberration, as it requires only centroid determination for localization analysis. Here we demonstrate the application of this method to 3D imaging of bacterial protein distribution and neuron dendritic morphology with subdiffraction resolution.

Genetically encoded calcium indicators (GECIs), together with modern microscopy, allow repeated activity measurement, in real time and with cellular resolution, of defined cellular populations. Recent efforts in protein engineering have yielded several high-quality GECIs that facilitate new applications in neuroscience. Here, we summarize recent progress in GECI design, optimization, and characterization, and provide guidelines for selecting the appropriate GECI for a given biological application. We focus on the unique challenges associated with imaging in behaving animals.