BRAIN Initiative: Cutting-Edge Tools and Resources for the Community

A Modular 512-Channel Neural Signal Acquisition ASIC for High-Density 4096 Channel Electrophysiology

The complexity of information processing in the brain requires the development of technologies that can provide spatial and temporal resolution by means of dense electrode arrays paired with high-channel-count signal acquisition electronics. In this work, we present an ultra-low noise modular 512-channel neural recording circuit that is scalable to up to 4096 simultaneously recording channels. The neural readout application-specific integrated circuit (ASIC) uses a dense 8.2 mm × 6.8 mm 2D layout to enable high-channel count, creating an ultra-light 350 mg flexible module. The module can be deployed on headstages for small animals like rodents and songbirds, and it can be integrated with a variety of electrode arrays. The chip was fabricated in a TSMC 0.18 µm 1.8 V CMOS technology and dissipates a total of 125 mW. Each DC-coupled channel features a gain and bandwidth programmable analog front-end along with 14 b analog-to-digital conversion at speeds up to 30 kS/s. Additionally, each front-end includes programmable electrode plating and electrode impedance measurement capability. We present both standalone and in vivo measurements results, demonstrating the readout of spikes and field potentials that are modulated by a sensory input.

Unsupervised classification of brain-wide axons reveals the presubiculum neuronal projection blueprint

We present a quantitative strategy to identify all projection neuron types from a given region with statistically different patterns of anatomical targeting. We first validate the technique with mouse primary motor cortex layer 6 data, yielding two clusters consistent with cortico-thalamic and intra-telencephalic neurons. We next analyze the presubiculum, a less-explored region, identifying five classes of projecting neurons with unique patterns of divergence, convergence, and specificity. We report several findings: individual classes target multiple subregions along defined functions; all hypothalamic regions are exclusively targeted by the same class also invading midbrain and agranular retrosplenial cortex; Cornu Ammonis receives input from a single class of presubicular axons also projecting to granular retrosplenial cortex; path distances from the presubiculum to the same targets differ significantly between classes, as do the path distances to distinct targets within most classes; the identified classes have highly non-uniform abundances; and presubicular somata are topographically segregated among classes. This study thus demonstrates that statistically distinct projections shed light on the functional organization of their circuit.

Oligodendrocyte calcium signaling promotes actin-dependent myelin sheath extension

Myelin is essential for rapid nerve signaling and is increasingly found to play important roles in learning and in diverse diseases of the CNS. Morphological parameters of myelin such as sheath length are thought to precisely tune conduction velocity, but the mechanisms controlling sheath morphology are poorly understood. Local calcium signaling has been observed in nascent myelin sheaths and can be modulated by neuronal activity. However, the role of calcium signaling in sheath formation remains incompletely understood. Here, we use genetic tools to attenuate oligodendrocyte calcium signaling during myelination in the developing mouse CNS. Surprisingly, genetic calcium attenuation does not grossly affect the number of myelinated axons or myelin thickness. Instead, calcium attenuation causes myelination defects resulting in shorter, dysmorphic sheaths. Mechanistically, calcium attenuation reduces actin filaments in oligodendrocytes, and an intact actin cytoskeleton is necessary and sufficient to achieve accurate myelin morphology. Together, our work reveals a cellular mechanism required for accurate CNS myelin formation and may provide mechanistic insight into how oligodendrocytes respond to neuronal activity to sculpt and refine myelin sheaths.

Anatomically distributed neural representations of instincts in the hypothalamus

Artificial activation of anatomically localized, genetically defined hypothalamic neuron populations is known to trigger distinct innate behaviors, suggesting a hypothalamic nucleus-centered organization of behavior control. To assess whether the encoding of behavior is similarly anatomically confined, we performed simultaneous neuron recordings across twenty hypothalamic regions in freely moving animals. Here we show that distinct but anatomically distributed neuron ensembles encode the social and fear behavior classes, primarily through mixed selectivity. While behavior class-encoding ensembles were spatially distributed, individual ensembles exhibited strong localization bias. Encoding models identified that behavior actions, but not motion-related variables, explained a large fraction of hypothalamic neuron activity variance. These results identify unexpected complexity in the hypothalamic encoding of instincts and provide a foundation for understanding the role of distributed neural representations in the expression of behaviors driven by hardwired circuits.

Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possible, and to turn the model into a useful framework for making predictions based on the principles governing the nature of neural cells. In such a context, the access to existing neural models and data outstandingly facilitates the work of computational neuroscientists and fosters its novelty, as the scientific community grows wider and neural models progressively increase in type, size, and number. Nonetheless, even when accessibility is guaranteed, data and models are rarely reused since it is difficult to retrieve, extract and/or understand relevant information and scientists are often required to download and modify individual files, perform neural data analysis, optimize model parameters, and run simulations, on their own and with their own resources. While focusing on the construction of biophysically and morphologically accurate models of hippocampal cells, we have created an online resource, the Build section of the Hippocampus Hub -a scientific portal for research on the hippocampus- that gathers data and models from different online open repositories and allows their collection as the first step of a single cell model building workflow. Interoperability of tools and data is the key feature of the work we are presenting. Through a simple click-and-collect procedure, like filling the shopping cart of an online store, researchers can intuitively select the files of interest (i.e., electrophysiological recordings, neural morphology, and model components), and get started with the construction of a data-driven hippocampal neuron model. Such a workflow importantly includes a model optimization process, which leverages high performance computing resources transparently granted to the users, and a framework for running simulations of the optimized model, both available through the EBRAINS Hodgkin-Huxley Neuron Builder online tool.

Unsupervised classification of brain-wide axons reveals neuronal projection blueprint

Long-range axonal projections are quintessential determinants of network connectivity, linking cellular organization and circuit architecture. Here we introduce a quantitative strategy to identify, from a given source region, all "projection neuron types" with statistically different patterns of anatomical targeting. We first validate the proposed technique with well-characterized data from layer 6 of the mouse primary motor cortex. The results yield two clusters, consistent with previously discovered cortico-thalamic and intra-telencephalic neuron classes. We next analyze neurons from the presubiculum, a less-explored region. Extending sparse knowledge from earlier retrograde tracing studies, we identify five classes of presubicular projecting neurons, revealing unique patterns of divergence, convergence, and specificity. We thus report several findings: (1) individual classes target multiple subregions along defined functions, such as spatial representation vs. sensory integration and visual vs. auditory input; (2) all hypothalamic regions are exclusively targeted by the same class also invading midbrain, a sharp subset of thalamic nuclei, and agranular retrosplenial cortex; (3) Cornu Ammonis, in contrast, receives input from the same presubicular axons projecting to granular retrosplenial cortex, also the purview of a single class; (4) path distances from the presubiculum to the same targets differ significantly between classes, as do the path distances to distinct targets within most classes, suggesting fine temporal coordination in activating distant areas; (5) the identified classes have highly non-uniform abundances, with substantially more neurons projecting to midbrain and hypothalamus than to medial and lateral entorhinal cortex; (6) lastly, presubicular soma locations are segregated among classes, indicating topographic organization of projections. This study thus demonstrates that classifying neurons based on statistically distinct axonal projection patterns sheds light on the functional organizational of their circuit.

High fidelity sensory-evoked responses in neocortex after intravenous injection of genetically encoded calcium sensors

Two-photon imaging of genetically-encoded calcium indicators (GECIs) has traditionally relied on intracranial injections of adeno-associated virus (AAV) or transgenic animals to achieve expression. Intracranial injections require an invasive surgery and result in a relatively small volume of tissue labeling. Transgenic animals, although they can have brain-wide GECI expression, often express GECIs in only a small subset of neurons, may have abnormal behavioral phenotypes, and are currently limited to older generations of GECIs. Inspired by recent developments in the synthesis of AAVs that readily cross the blood brain barrier, we tested whether an alternative strategy of intravenously injecting AAV-PHP.eB is suitable for two-photon calcium imaging of neurons over many months after injection. We injected C57BL/6 J mice with AAV-PHP.eB-Synapsin-jGCaMP7s via the retro-orbital sinus. After allowing 5 to 34 weeks for expression, we performed conventional and widefield two-photon imaging of layers 2/3, 4 and 5 of the primary visual cortex. We found reproducible trial-by-trial neural responses and tuning properties consistent with known feature selectivity in the visual cortex. Thus, intravenous injection of AAV-PHP.eB does not interfere with the normal processing in neural circuits. In vivo and histological images show no nuclear expression of jGCaMP7s for at least 34 weeks post-injection.

Oligodendrocyte calcium signaling sculpts myelin sheath morphology

Myelin is essential for rapid nerve signaling and is increasingly found to play important roles in learning and in diverse diseases of the CNS. Morphological parameters of myelin such as sheath length and thickness are regulated by neuronal activity and can precisely tune conduction velocity, but the mechanisms controlling sheath morphology are poorly understood. Local calcium signaling has been observed in nascent myelin sheaths and can be modulated by neuronal activity. However, the role of calcium signaling in sheath formation and remodeling is unknown. Here, we used genetic tools to attenuate oligodendrocyte calcium signaling during active myelination in the developing mouse CNS. Surprisingly, we found that genetic calcium attenuation did not grossly affect the number of myelinated axons or myelin thickness. Instead, calcium attenuation caused striking myelination defects resulting in shorter, dysmorphic sheaths. Mechanistically, calcium attenuation reduced actin filaments in oligodendrocytes, and an intact actin cytoskeleton was necessary and sufficient to achieve accurate myelin morphology. Together, our work reveals a novel cellular mechanism required for accurate CNS myelin formation and provides mechanistic insight into how oligodendrocytes may respond to neuronal activity to sculpt myelin sheaths throughout the nervous system.

Violation of the ultrastructural size principle in the dorsolateral prefrontal cortex underlies working memory impairment in the aged common marmoset (Callithrix jacchus)

Morphology and function of the dorsolateral prefrontal cortex (dlPFC), and corresponding working memory performance, are affected early in the aging process, but nearly half of aged individuals are spared of working memory deficits. Translationally relevant model systems are critical for determining the neurobiological drivers of this variability. The common marmoset (Callithrix jacchus) is advantageous as a model for these investigations because, as a non-human primate, marmosets have a clearly defined dlPFC that enables measurement of prefrontal-dependent cognitive functions, and their short (∼10 year) lifespan facilitates longitudinal studies of aging. Previously, we characterized working memory capacity in a cohort of marmosets that collectively covered the lifespan, and found age-related working memory impairment. We also found a remarkable degree of heterogeneity in performance, similar to that found in humans. Here, we tested the hypothesis that changes to synaptic ultrastructure that affect synaptic efficacy stratify marmosets that age with cognitive impairment from those that age without cognitive impairment. We utilized electron microscopy to visualize synapses in the marmoset dlPFC and measured the sizes of boutons, presynaptic mitochondria, and synapses. We found that coordinated scaling of the sizes of synapses and mitochondria with their associated boutons is essential for intact working memory performance in aged marmosets. Further, lack of synaptic scaling, due to a remarkable failure of synaptic mitochondria to scale with presynaptic boutons, selectively underlies age-related working memory impairment. We posit that this decoupling results in mismatched energy supply and demand, leading to impaired synaptic transmission. We also found that aged marmosets have fewer synapses in dlPFC than young, though the severity of synapse loss did not predict whether aging occurred with or without cognitive impairment. This work identifies a novel mechanism of synapse dysfunction that stratifies marmosets that age with cognitive impairment from those that age without cognitive impairment. The process by which synaptic scaling is regulated is yet unknown and warrants future investigation.

The influence of autoregressive relation strength and search strategy on directionality recovery in group iterative multiple model estimation

Unified structural equation modeling (uSEM) implemented in the group iterative multiple model estimation (GIMME) framework has recently been widely used for characterizing within-person network dynamics of behavioral and functional neuroimaging variables. Previous studies have established that GIMME accurately recovers the presence of relations between variables. However, recovery of relation directionality is less consistent, which is concerning given the importance of directionality estimates for many research questions. There is evidence that strong autoregressive relations may aid directionality recovery and indirect evidence that a novel version of GIMME allowing for multiple solutions could improve recovery when such relations are weak, but it remains unclear how these strategies perform under a range of study conditions. Using comprehensive simulations that varied the strength of autoregressive relations among other factors, this study evaluated the directionality recovery of two GIMME search strategies: (a) estimating autoregressive relations by default in the null model (GIMME-AR) and (b) generating multiple solution paths (GIMME-MS). Both strategies recovered directionality best-and were roughly equivalent in performance-when autoregressive relations were strong (e.g., β = .60). When they were weak (β ≤ .10), GIMME-MS displayed an advantage, although overall directionality recovery was modest. Analyses of empirical data in which autoregressive relations were characteristically strong (resting state functional MRI) versus weak (daily diary) mirrored simulation results and confirmed that these strategies can disagree on directionality when autoregressive relations are weak. Findings have important implications for psychological and neuroimaging applications of uSEM/GIMME and suggest specific scenarios in which researchers might or might not be confident in directionality results. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

High fidelity sensory-evoked responses in neocortex after intravenous injection of genetically encoded calcium sensors

Two-photon imaging of genetically-encoded calcium indicators (GECIs) has traditionally relied on intracranial injections of adeno-associated virus (AAV) or transgenic animals to achieve expression. Intracranial injections require an invasive surgery and result in a relatively small volume of tissue labeling. Transgenic animals, although they can have brain-wide GECI expression, often express GECIs in only a small subset of neurons, may have abnormal behavioral phenotypes, and are currently limited to older generations of GECIs. Inspired by recent developments in the synthesis of AAVs that readily cross the blood brain barrier, we tested whether an alternative strategy of intravenously injecting AAV-PhP.eB is suitable for two-photon calcium imaging of neurons over many months after injection. We injected young (postnatal day 23 to 31) C57BL/6J mice with AAV-PhP.eB-Synapsin-jGCaMP7s via the retro-orbital sinus. After allowing 5 to 34 weeks for expression, we performed conventional and widefield two-photon imaging of layers 2/3, 4 and 5 of the primary visual cortex. We found reproducible trial-by-trial neural responses and tuning properties consistent with known feature selectivity in the visual cortex. Thus, intravenous injection of AAV-PhP.eB does not interfere with the normal processing in neural circuits. In vivo and histological images show no nuclear expression of jGCaMP7s for at least 34 weeks post-injection.

Data management strategy for a collaborative research center

The importance of effective research data management (RDM) strategies to support the generation of Findable, Accessible, Interoperable, and Reusable (FAIR) neuroscience data grows with each advance in data acquisition techniques and research methods. To maximize the impact of diverse research strategies, multidisciplinary, large-scale neuroscience research consortia face a number of unsolved challenges in RDM. While open science principles are largely accepted, it is practically difficult for researchers to prioritize RDM over other pressing demands. The implementation of a coherent, executable RDM plan for consortia spanning animal, human, and clinical studies is becoming increasingly challenging. Here, we present an RDM strategy implemented for the Heidelberg Collaborative Research Consortium. Our consortium combines basic and clinical research in diverse populations (animals and humans) and produces highly heterogeneous and multimodal research data (e.g., neurophysiology, neuroimaging, genetics, behavior). We present a concrete strategy for initiating early-stage RDM and FAIR data generation for large-scale collaborative research consortia, with a focus on sustainable solutions that incentivize incremental RDM while respecting research-specific requirements.

Resting state functional connectivity subtypes predict discrete patterns of cognitive-affective functioning across levels of analysis among patients with treatment-resistant depression

Resting state functional connectivity (RSFC) in ventral affective (VAN), default mode (DMN) and cognitive control (CCN) networks may partially underlie heterogeneity in depression. The current study used data-driven parsing of RSFC to identify subgroups of patients with treatment-resistant depression (TRD; n = 70) and determine if subgroups generalized to transdiagnostic measures of cognitive-affective functioning relevant to depression (indexed across self-report, behavioral, and molecular levels of analysis). RSFC paths within key networks were characterized using Subgroup-Group Iterative Multiple Model Estimation. Three connectivity-based subgroups emerged: Subgroup A, the largest subset and containing the fewest pathways; Subgroup B, containing unique bidirectional VAN/DMN negative feedback; and Subgroup C, containing the most pathways. Compared to other subgroups, subgroup B was characterized by lower self-reported positive affect and subgroup C by higher self-reported positive affect, greater variability in induced positive affect, worse response inhibition, and reduced striatal tissue iron concentration. RSFC-based categorization revealed three TRD subtypes associated with discrete aberrations in transdiagnostic cognitive-affective functioning that were largely unified across levels of analysis and were maintained after accounting for the variability captured by a disorder-specific measure of depressive symptoms. Findings advance understanding of transdiagnostic brain-behavior heterogeneity in TRD and may inform novel treatment targets for this population.

Super-Selective Reconstruction of Causal and Direct Connectivity With Application to in vitro iPSC Neuronal Networks

Despite advancements in the development of cell-based in-vitro neuronal network models, the lack of appropriate computational tools limits their analyses. Methods aimed at deciphering the effective connections between neurons from extracellular spike recordings would increase utility of in vitro local neural circuits, especially for studies of human neural development and disease based on induced pluripotent stem cells (hiPSC). Current techniques allow statistical inference of functional couplings in the network but are fundamentally unable to correctly identify indirect and apparent connections between neurons, generating redundant maps with limited ability to model the causal dynamics of the network. In this paper, we describe a novel mathematically rigorous, model-free method to map effective-direct and causal-connectivity of neuronal networks from multi-electrode array data. The inference algorithm uses a combination of statistical and deterministic indicators which, first, enables identification of all existing functional links in the network and then reconstructs the directed and causal connection diagram via a super-selective rule enabling highly accurate classification of direct, indirect, and apparent links. Our method can be generally applied to the functional characterization of any in vitro neuronal networks. Here, we show that, given its accuracy, it can offer important insights into the functional development of in vitro hiPSC-derived neuronal cultures.

The promise of the BRAIN initiative: NIH strategies for understanding neural circuit function

New neurotechnologies fueled by the BRAIN Initiative now allow investigators to map, monitor and modulate complex neural circuits, enabling the pursuit of research questions previously considered unapproachable. Yet it is the convergence of molecular neuroscience with the new systems neuroscience that promises the greatest future advances. This is particularly true for our understanding of nervous system disorders, some of which have known molecular drivers or pathology but result in unknown perturbations in circuit function. NIH-supported research on "BRAIN Circuits" programs integrate experimental, analytic, and theoretical capabilities for analysis of specific neural circuits and their contributions to perceptions, motivations, and actions. In this review, we describe the BRAIN priority areas, review our strategy for balancing early feasibility with mature projects, and the balance of individual with team science for this 'BRAIN Circuits' program. We also highlight the diverse portfolio of techniques, species, and neural systems represented in these projects.