Large Populations Of Neurons Research Articles

Functional network topography of the medial entorhinal cortex

The medial entorhinal cortex (MEC) creates a map of local space, based on the firing patterns of grid, head-direction (HD), border, and object-vector (OV) cells. How these cell types are organized anatomically is debated. In-depth analysis of this question requires collection of precise anatomical and activity data across large populations of neurons during unrestrained behavior, which neither electrophysiological nor previous imaging methods fully afford. Here, we examined the topographic arrangement of spatially modulated neurons in the superficial layers of MEC and adjacent parasubiculum using miniaturized, portable two-photon microscopes, which allow mice to roam freely in open fields. Grid cells exhibited low levels of co-occurrence with OV cells and clustered anatomically, while border, HD, and OV cells tended to intermingle. These data suggest that grid cell networks might be largely distinct from those of border, HD, and OV cells and that grid cells exhibit strong coupling among themselves but weaker links to other cell types.

A Flp-dependent G-CaMP9a transgenic mouse for neuronal imaging in vivo

SummaryGenetically encoded calcium indicators (GECIs) are widely used to measure calcium transients in neuronal somata and processes, and their use enables the determination of action potential temporal series in a large population of neurons. Here, we generate a transgenic mouse line expressing a highly sensitive green GECI, G-CaMP9a, in a Flp-dependent manner in excitatory and inhibitory neuronal subpopulations downstream of a strong CAG promoter. Combining this reporter mouse with viral or mouse genetic Flp delivery methods produces a robust and stable G-CaMP9a expression in defined neuronal populations without detectable detrimental effects. In vivo two-photon imaging reveals spontaneous and sensory-evoked calcium transients in excitatory and inhibitory ensembles with cellular resolution. Our results show that this reporter line allows long-term, cell-type-specific investigation of neuronal activity with enhanced resolution in defined populations and facilitates dissecting complex dynamics of neural networks in vivo.

Voltage imaging identifies spinal circuits that modulate locomotor adaptation in zebrafish

Motor systems must continuously adapt their output to maintain a desired trajectory. While the spinal circuits underlying rhythmic locomotion are well described, little is known about how the network modulates its output strength. A major challenge has been the difficulty of recording from spinal neurons during behavior. Here, we use voltage imaging to map the membrane potential of large populations of glutamatergic neurons throughout the spinal cord of the larval zebrafish during fictive swimming in a virtual environment. We characterized a previously undescribed subpopulation of tonic-spiking ventral V3 neurons whose spike rate correlated with swimming strength and bout length. Optogenetic activation of V3 neurons led to stronger swimming and longer bouts but did not affect tail beat frequency. Genetic ablation of V3 neurons led to reduced locomotor adaptation. The power of voltage imaging allowed us to identify V3 neurons as a critical driver of locomotor adaptation in zebrafish.

Rhythmicity in the Enteric Nervous System of Mice.

The enteric nervous system (ENS) is required for many cyclical patterns of motor activity along different regions of the gastrointestinal (GI) tract. What has remained mysterious is precisely how many thousands of neurons within the ENS are temporally activated to generate cyclical neurogenic contractions of GI-smooth muscle layers. This has been an especially puzzling conundrum, since the ENS consists of an extensive network of small ganglia, with each ganglion consisting of a heterogeneous population of neurons, with diverse cell soma morphologies, neurochemical and biophysical characteristics, and neural connectivity. Neuronal imaging studies of the mouse large intestine have provided major new insights into how the different classes of myenteric neurons are activated during cyclical neurogenic motor patterns, such as the colonic motor complex (CMC). It has been revealed that during CMCs (in the isolated mouse whole colon), large populations of myenteric neurons, across large spatial fields, coordinate their firing, via bursts of fast synaptic inputs at ~2 Hz. This coordinated firing of many thousands of myenteric neurons synchronously over many rows of interconnected ganglia occurs irrespective of the functional class of neuron. Aborally directed propulsion of content along the mouse colon is due, in large part, to polarity of the enteric circuits including the projections of the intrinsic excitatory and inhibitory motor neurons but still involves the fundamental ~2 Hz rhythmic activity of specific classes of enteric neurons. What remains to be determined are the mechanisms that initiate and terminate the patterned firing of large ensembles of enteric neurons during cyclic activity. This remains an exciting challenge for future studies.

Measuring Stimulus-Evoked Neurophysiological Differentiation in Distinct Populations of Neurons in Mouse Visual Cortex.

Despite significant progress in understanding neural coding, it remains unclear how the coordinated activity of large populations of neurons relates to what an observer actually perceives. Since neurophysiological differences must underlie differences among percepts, differentiation analysis—quantifying distinct patterns of neurophysiological activity—has been proposed as an “inside-out” approach that addresses this question. This methodology contrasts with “outside-in” approaches such as feature tuning and decoding analyses, which are defined in terms of extrinsic experimental variables. Here, we used two-photon calcium imaging in mice of both sexes to systematically survey stimulus-evoked neurophysiological differentiation (ND) in excitatory neuronal populations in layers (L)2/3, L4, and L5 across five visual cortical areas (primary, lateromedial, anterolateral, posteromedial, and anteromedial) in response to naturalistic and phase-scrambled movie stimuli. We find that unscrambled stimuli evoke greater ND than scrambled stimuli specifically in L2/3 of the anterolateral and anteromedial areas, and that this effect is modulated by arousal state and locomotion. By contrast, decoding performance was far above chance and did not vary substantially across areas and layers. Differentiation also differed within the unscrambled stimulus set, suggesting that differentiation analysis may be used to probe the ethological relevance of individual stimuli.

Leptin coordinates efferent sympathetic outflow to the white adipose tissue through the midbrain centrally-projecting Edinger-Westphal nucleus in male rats

The centrally-projecting Edinger-Westphal nucleus (EWcp) hosts a large population of neurons expressing urocortin 1 (Ucn1) and about half of these neurons also express the leptin receptor (LepRb). Previously, we have shown that the peripheral adiposity hormone leptin signaling energy surfeit modulates EWcp neurons' activity. Here, we hypothesized that Ucn1/LepRb neurons in the EWcp would act as a crucial neuronal node in the brain-white adipose tissue (WAT) axis modulating efferent sympathetic outflow to the WAT. We showed that leptin bound to neurons of the EWcp stimulated STAT3 phosphorylation, and increased Ucn1-production in a time-dependent manner. Besides, retrograde transneuronal tract-tracing using pseudorabies virus (PRV) identified EWcp Ucn1 neurons connected to WAT. Interestingly, reducing EWcp Ucn1 contents by ablating EWcp LepRb-positive neurons with leptin-saporin, did not affect food intake and body weight gain, but substantially (+26%) increased WAT weight accompanied by a higher plasma leptin level and changed plasma lipid profile. We also found that ablation of EWcp Ucn1/LepRb neurons resulted in lower respiratory quotient and oxygen consumption one week after surgery, but was comparable to sham values after 3 and 5 weeks of surgery. Taken together, we report that EWcp/LepRb/Ucn1 neurons not only respond to leptin signaling but also control WAT size and fat metabolism without altering food intake. These data suggest the existence of a EWcp-WAT circuitry allowing an organism to recruit fuels without being able to eat in situations such as the fight-or-flight response.

Functionalized Nanocellulose Drives Neural Stem Cells toward Neuronal Differentiation.

Transplantation of differentiated and fully functional neurons may be a better therapeutic option for the cure of neurodegenerative disorders and brain injuries than direct grafting of neural stem cells (NSCs) that are potentially tumorigenic. However, the differentiation of NSCs into a large population of neurons has been a challenge. Nanomaterials have been widely used as substrates to manipulate cell behavior due to their nano-size, excellent physicochemical properties, ease of synthesis, and versatility in surface functionalization. Nanomaterial-based scaffolds and synthetic polymers have been fabricated with topology resembling the micro-environment of the extracellular matrix. Nanocellulose materials are gaining attention because of their availability, biocompatibility, biodegradability and bioactivity, and affordable cost. We evaluated the role of nanocellulose with different linkage and surface features in promoting neuronal differentiation. Nanocellulose coupled with lysine molecules (CNC–Lys) provided positive charges that helped the cells to attach. Embryonic rat NSCs were differentiated on the CNC–Lys surface for up to three weeks. By the end of the three weeks of in vitro culture, 87% of the cells had attached to the CNC–Lys surface and more than half of the NSCs had differentiated into functional neurons, expressing endogenous glutamate, generating electrical activity and action potentials recorded by the multi-electrode array.

Unsupervised Channel Compression Methods in Motor Prostheses Design.

The development of high performance brain machine interfaces (BMIs) requires scaling recording channel count to enable simultaneous recording from large populations of neurons. Unfortunately, proposed implantable neural interfaces have power requirements that scale linearly with channel count. To facilitate the design of interfaces with reduced power requirements, we propose and evaluate an unsupervised-learning-based compressed sensing strategy. This strategy suggests novel neural interface architectures which compress neural data by methodically combining channels of spiking activity. We develop an entropy-based compression strategy that models the population of neurons as being generated from a lower dimensional set of latent variables and aims to minimize the loss of information in the latent variables due to compression. We evaluate compressed features by inferring the latent variables from these features and measuring the accuracy with which the activity of held out neurons and arm movements can be estimated. We apply these methods to different cortical regions (PMd and M1) and compare the proposed compression methods to a random projections strategy often employed for compressed sensing and to a supervised regression based channel dropping strategy traditionally applied in BMI applications.

Discovering Geometry in Data Arrays.

Modern technologies produce a deluge of complicated data. In neuroscience, for example, minimally invasive experimental methods can take recordings of large populations of neurons at high resolution under a multitude of conditions. Such data arrays possess non-trivial interdependencies along each of their axes. Insights into these data arrays may lay the foundations of advanced treatments for nervous system disorders. The potential impacts of such data, however, will not be fully realized unless the techniques for analyzing them keep pace. Specifically, there is an urgent, growing need for methods for estimating the low-dimensional structure and geometry in big and noisy data arrays. This article reviews a framework for identifying complicated underlying patterns in such data and also recounts the key role that the Department of Energy Computational Sciences Graduate Fellowship played in setting the stage for this work to be done by the author.

Neural tuning and representational geometry.

A central goal of neuroscience is to understand the representations formed by brain activity patterns and their connection to behaviour. The classic approach is to investigate how individual neurons encode stimuli and how their tuning determines the fidelity of the neural representation. Tuning analyses often use the Fisher information to characterize the sensitivity of neural responses to small changes of the stimulus. In recent decades, measurements of large populations of neurons have motivated a complementary approach, which focuses on the information available to linear decoders. The decodable information is captured by the geometry of the representational patterns in the multivariate response space. Here we review neural tuning and representational geometry with the goal of clarifying the relationship between them. The tuning induces the geometry, but different sets of tuned neurons can induce the same geometry. The geometry determines the Fisher information, the mutual information and the behavioural performance of an ideal observer in a range of psychophysical tasks. We argue that future studies can benefit from considering both tuning and geometry to understand neural codes and reveal the connections between stimuli, brain activity and behaviour.

Establishment of an Electrophysiological Platform for Modeling ALS with Regionally-Specific Human Pluripotent Stem Cell-Derived Astrocytes and Neurons

Human pluripotent stem cell-derived astrocytes (hiPSC-A) and neurons (hiPSC-N) provide a powerful tool for modeling Amyotrophic Lateral Sclerosis (ALS) pathophysiology in vitro. Multi-electrode array (MEA) recordings are a means to record electrical field potentials from large populations of neurons and analyze network activity over time. It was previously demonstrated that the presence of hiPSC-A that are differentiated using techniques to promote a spinal cord astrocyte phenotype improved maturation and electrophysiological activity of regionally specific spinal cord hiPSC-motor neurons (MN) when compared to those cultured without hiPSC-A or in the presence of rodent astrocytes. Described here is a method to co-culture spinal cord hiPSC-A with hiPSC-MN and record electrophysiological activity using MEA recordings. While the differentiation protocols described here are particular to astrocytes and neurons that are regionally specific to the spinal cord, the co-culturing platform can be applied to astrocytes and neurons differentiated with techniques specific to other fates, including cortical hiPSC-A and hiPSC-N. These protocols aim to provide an electrophysiological assay to inform about glia-neuron interactions and provide a platform for testing drugs with therapeutic potential in ALS.

In vitro ictogenesis is stochastic at the single neuron level.

Seizure initiation is the least understood and most disabling element of epilepsy. Studies of ictogenesis require high speed recordings at cellular resolution in the area of seizure onset. However, in vivo seizure onset areas cannot be determined at the level of resolution necessary to enable such studies. To circumvent these challenges, we used novel GCaMP7-based calcium imaging in the organotypic hippocampal slice culture model of post-traumatic epilepsy in mice. Organotypic hippocampal slice cultures generate spontaneous, recurrent seizures in a preparation in which it is feasible to image the activity of the entire network (with no unseen inputs existing). Chronic calcium imaging of the entire hippocampal network, with paired electrophysiology, revealed three patterns of seizure onset: (i) low amplitude fast activity; (ii) sentinel spike; and (iii) spike burst and low amplitude fast activity onset. These patterns recapitulate common features of human seizure onset, including low voltage fast activity and spike discharges. Weeks-long imaging of seizure activity showed a characteristic evolution in onset type and a refinement of the seizure onset zone. Longitudinal tracking of individual neurons revealed that seizure onset is stochastic at the single neuron level, suggesting that seizure initiation activates neurons in non-stereotyped sequences seizure to seizure. This study demonstrates for the first time that transitions to seizure are not initiated by a small number of neuronal 'bad actors' (such as overly connected hub cells), but rather by network changes which enable the onset of pathology among large populations of neurons.

Divergence in Population Coding for Space between Dorsal and Ventral CA1.

Molecular, anatomic, and behavioral studies show that the hippocampus is structurally and functionally heterogeneous, with dorsal hippocampus implicated in mnemonic processes and spatial navigation and ventral hippocampus involved in affective processes. By performing electrophysiological recordings of large neuronal populations in dorsal and ventral CA1 in head-fixed mice navigating a virtual environment, we found that this diversity resulted in different strategies for population coding of space. Populations of neurons in dorsal CA1 showed more complex patterns of activity, which resulted in a higher dimensionality of neural representations that translated to more information being encoded, as compared ensembles in vCA1. Furthermore, a pairwise maximum entropy model was better at predicting the structure of these global patterns of activity in ventral CA1 as compared with dorsal CA1. Taken together, the different coding strategies we uncovered likely emerge from anatomic and physiological differences along the longitudinal axis of hippocampus and that may, in turn, underpin the divergent ethological roles of dorsal and ventral CA1.

NeuroRetriever: Automatic Neuron Segmentation for Connectome Assembly.

Segmenting individual neurons from a large number of noisy raw images is the first step in building a comprehensive map of neuron-to-neuron connections for predicting information flow in the brain. Thousands of fluorescence-labeled brain neurons have been imaged. However, mapping a complete connectome remains challenging because imaged neurons are often entangled and manual segmentation of a large population of single neurons is laborious and prone to bias. In this study, we report an automatic algorithm, NeuroRetriever, for unbiased large-scale segmentation of confocal fluorescence images of single neurons in the adult Drosophila brain. NeuroRetriever uses a high-dynamic-range thresholding method to segment three-dimensional morphology of single neurons based on branch-specific structural features. Applying NeuroRetriever to automatically segment single neurons in 22,037 raw brain images, we successfully retrieved 28,125 individual neurons validated by human segmentation. Thus, automated NeuroRetriever will greatly accelerate 3D reconstruction of the single neurons for constructing the complete connectomes.

Reconciling functional differences in populations of neurons recorded with two-photon imaging and electrophysiology.

Extracellular electrophysiology and two-photon calcium imaging are widely used methods for measuring physiological activity with single-cell resolution across large populations of cortical neurons. While each of these two modalities has distinct advantages and disadvantages, neither provides complete, unbiased information about the underlying neural population. Here, we compare evoked responses in visual cortex recorded in awake mice under highly standardized conditions using either imaging of genetically expressed GCaMP6f or electrophysiology with silicon probes. Across all stimulus conditions tested, we observe a larger fraction of responsive neurons in electrophysiology and higher stimulus selectivity in calcium imaging, which was partially reconciled by applying a spikes-to-calcium forward model to the electrophysiology data. However, the forward model could only reconcile differences in responsiveness when restricted to neurons with low contamination and an event rate above a minimum threshold. This work established how the biases of these two modalities impact functional metrics that are fundamental for characterizing sensory-evoked responses.

Recording Strategies for High Channel Count, Densely Spaced Microelectrode Arrays.

Neuroscience research into how complex brain functions are implemented at an extra-cellular level requires in vivo neural recording interfaces, including microelectrodes and read-out circuitry, with increased observability and spatial resolution. The trend in neural recording interfaces toward employing high-channel-count probes or 2D microelectrodes arrays with densely spaced recording sites for recording large neuronal populations makes it harder to save on resources. The low-noise, low-power requirement specifications of the analog front-end usually requires large silicon occupation, making the problem even more challenging. One common approach to alleviating this consumption area burden relies on time-division multiplexing techniques in which read-out electronics are shared, either partially or totally, between channels while preserving the spatial and temporal resolution of the recordings. In this approach, shared elements have to operate over a shorter time slot per channel and active area is thus traded off against larger operating frequencies and signal bandwidths. As a result, power consumption is only mildly affected, although other performance metrics such as in-band noise or crosstalk may be degraded, particularly if the whole read-out circuit is multiplexed at the analog front-end input. In this article, we review the different implementation alternatives reported for time-division multiplexing neural recording systems, analyze their advantages and drawbacks, and suggest strategies for improving performance.

Population Coding of Capsaicin Concentration by Sensory Neurons Revealed Using Ca2+ Imaging of Dorsal Root Ganglia Explants from Adult pirt-GCaMP3 Mouse.

Nociceptors detect noxious capsaicin (CAPS) via the transient receptor potential vanilloid 1 (TRPV1) ion channel, but coding mechanisms for relaying CAPS concentration [CAPS] remain obscure. Prolonged (up to 1h.) exposure to CAPS is used clinically to desensitise sensory fibres for treatment of neuropathic pain, but its signalling has typically been studied in cultures of dissociated sensory neurons employing low cell numbers and very short exposure times. Thus, it was pertinent to examine responses to longer CAPS exposures in large populations of adult neurons. Confocal fluorescence microscopy was used to monitor the simultaneous excitation by CAPS of neuronal populations in intact L3/4 dorsal root ganglia (DRG) explants from adult pirt-GCaMP3 mice that express a cytoplasmic, genetically-encoded Ca2+ sensor in almost all primary sensory neurons. Peak analysis was performed using GraphPad Prism 9 to deconstruct the heterogenous and complex fluorescence signals observed into informative, readily-comparable measurements: number of signals, their lag time, maximum intensity relative to baseline (Max.) and duration. Exposure for 5 min. to CAPS activated plasmalemmal TRPV1 and led to increased fluorescence due to Ca2+ entry into DRG neurons (DRGNs), as it was prevented by capsazepine or removal of extracellular Ca2+. Increasing [CAPS] (0.3, 1 and 10 μM, respectively) evoked signals from more neurons (123, 275 and 390 from 5 DRG) with shorter average lag (6.4 ± 0.4, 3.3 ± 0.2 and 1.9 ± 0.1 min.) and longer duration (1.4 ± 0.2, 2.9 ± 0.2 and 4.8 ± 0.3 min.). Whilst raising [CAPS] produced a modest augmentation of Max. for individual neurons, those with large increases were selectively expedited; this contributed to a faster onset and higher peak of cumulative fluorescence for an enlarged responding neuronal population. CAPS caused many cells to fluctuate between high and low levels of fluorescence, with consecutive pulses increasing Max. and duration especially when exposure was extended from 5 to 20 min. Such signal facilitation counteracted tachyphylaxis, observed upon repeated exposure to 1 μM CAPS, preserving the cumulative fluorescence over time (signal density) in the population. Individual neurons within DRG differed extensively in the dynamics of response to CAPS, but systematic changes elicited by elevating [CAPS] increased signal density in a graded manner, unveiling a possible mechanism for population coding of responses to noxious chemicals. Signal density is sustained during prolonged and repeated exposure to CAPS, despite profound tachyphylaxis in some neurons, by signal facilitation in others. This may explain the burning sensation that persists for several hours when CAPS is used clinically.

Modularity and robustness of frontal cortical networks

Neural activity underlying short-term memory is maintained by interconnected networks of brain regions. It remains unknown how brain regions interact to maintain persistent activity while exhibiting robustness to corrupt information in parts of the network. We simultaneously measured activity in large neuronal populations across mouse frontal hemispheres to probe interactions between brain regions. Activity across hemispheres was coordinated to maintain coherent short-term memory. Across mice, we uncovered individual variability in the organization of frontal cortical networks. A modular organization was required for the robustness of persistent activity to perturbations: each hemisphere retained persistent activity during perturbations of the other hemisphere, thus preventing local perturbations from spreading. A dynamic gating mechanism allowed hemispheres to coordinate coherent information while gating out corrupt information. Our results show that robust short-term memory is mediated by redundant modular representations across brain regions. Redundant modular representations naturally emerge in neural network models that learned robust dynamics.

Corticotropin-Releasing Hormone from the Pontine Micturition Center Plays an Inhibitory Role in Micturition.

Lower urinary tract or voiding disorders are prevalent across all ages and affect >40% of adults over 40 years old, leading to decreased quality of life and high health care costs. The pontine micturition center (PMC; i.e., Barrington's nucleus) contains a large population of neurons that localize the stress-related neuropeptide, corticotropin-releasing hormone (CRH) and project to neurons in the spinal cord to regulate micturition. How the PMC and CRH-expressing neurons in the PMC control volitional micturition is of critical importance for human voiding disorders. To investigate the specific role of CRH in the PMC, neurons in the PMC-expressing CRH were optogenetically activated during in vivo cystometry in unanesthetized mice of either sex. Optogenetic activation of CRH-PMC neurons led to increased intermicturition interval and voided volume, similar to the altered voiding phenotype produced by social stress. Female mice showed a significantly more pronounced phenotype change compared with male mice. These effects were eliminated by CRH-receptor 1 antagonist pretreatment. Optogenetic inhibition of CRH-PMC neurons led to an altered voiding phenotype characterized by more frequent voids and smaller voided volumes. Last, in a cyclophosphamide cystitis model of bladder overactivity, optogenetic activation of CRH-PMC neurons returned the voiding pattern to normal. Collectively, our findings demonstrate that CRH from PMC spinal-projecting neurons has an inhibitory function on micturition and is a potential therapeutic target for human disease states, such as voiding postponement, urinary retention, and underactive or overactive bladder.SIGNIFICANCE STATEMENT The pontine micturition center (PMC), which is a major regulator of volitional micturition, is neurochemically heterogeneous, and excitatory neurotransmission derived from PMC neurons is thought to mediate the micturition reflex. In the present study, using optogenetic manipulation of CRH-containing neurons in double-transgenic mice, we demonstrate that CRH, which is prominent in PMC-spinal projections, has an inhibitory function on volitional micturition. Moreover, engaging this inhibitory function of CRH can ameliorate bladder hyperexcitability induced by cyclophosphamide in a model of cystitis. The data underscore CRH as a novel target for the treatment of voiding dysfunctions, which are highly prevalent disease processes in children and adults.

Direct extraction of signal and noise correlations from two-photon calcium imaging of ensemble neuronal activity.

Neuronal activity correlations are key to understanding how populations of neurons collectively encode information. While two-photon calcium imaging has created a unique opportunity to record the activity of large populations of neurons, existing methods for inferring correlations from these data face several challenges. First, the observations of spiking activity produced by two-photon imaging are temporally blurred and noisy. Secondly, even if the spiking data were perfectly recovered via deconvolution, inferring network-level features from binary spiking data is a challenging task due to the non-linear relation of neuronal spiking to endogenous and exogenous inputs. In this work, we propose a methodology to explicitly model and directly estimate signal and noise correlations from two-photon fluorescence observations, without requiring intermediate spike deconvolution. We provide theoretical guarantees on the performance of the proposed estimator and demonstrate its utility through applications to simulated and experimentally recorded data from the mouse auditory cortex.