Neuronal Populations Research Articles

Neuronal cell populations in circumoral nerve ring of sea cucumber Apostichopus japonicus: Ultrastructure and transcriptional profile

The echinoderm nervous system has been studied as a model for understanding the evolution of the chordate nervous system. Neuronal cells are essential groups that release a ‘cocktail’ of messenger molecules providing a spectrum of biological actions in the nervous system. Among echinoderms, most evidence on neuronal cell types has been obtained from starfish and sea urchin. In sea cucumbers, most research has focused on the location of neuronal cells, whereas their transcriptional features have rarely been investigated. Here, we observed the ultrastructure of neuronal cells in the sea cucumber, Apostichopus japonicus. The transcriptional profile of neuronal cells from the circumoral nerve ring (CNR) was investigated using single-cell RNA sequencing (scRNA-seq), and a total of six neuronal cell types were identified. 26 neuropeptide precursor genes (NPPs) and 28 G-protein-coupled receptors (GPCR) were expressed in the six neuronal cell types, comprising five NPP/NP-GPCR pairs. Unsupervised pseudotime analysis of neuronal cells showed their different differentiation status. We also located the neuronal cells in the CNR by immunofluorescence (IF) and identified the potential hub genes of key cell populations. This broad resource serves as a valuable support in the development of cell-specific markers for accurate cell-type identification in sea cucumbers. It also contributes to facilitating comparison across species, providing a deeper understanding of the evolutionary processes of neuronal cells.

Dopamine neurons drive spatiotemporally heterogeneous striatal dopamine signals during learning

Environmental cues, through Pavlovian learning, become conditioned stimuli that invigorate and guide animals toward rewards. Dopamine (DA) neurons in the ventral tegmental area (VTA) and substantia nigra (SNc) are crucial for this process, via engagement of a reciprocally connected network with their striatal targets. Critically, it remains unknown how dopamine neuron activity itself engages dopamine signals throughout the striatum, across learning. Here, we investigated how optogenetic Pavlovian cue conditioning of VTA or SNc dopamine neurons directs cue-evoked behavior and shapes subregion-specific striatal dopamine dynamics. We used a fluorescent biosensor to monitor dopamine in the nucleus accumbens (NAc) core and shell, dorsomedial striatum (DMS), and dorsolateral striatum (DLS). We demonstrate spatially heterogeneous, learning-dependent dopamine changes across striatal regions. Although VTA stimulation-evoked robust dopamine release in NAc core, shell, and DMS, predictive cues preferentially recruited dopamine release in NAc core, starting early in training, and DMS, late in training. Negative prediction error signals, reflecting a violation in the expectation of dopamine neuron activation, only emerged in the NAc core and DMS. Despite the development of vigorous movement late in training, conditioned dopamine signals did not emerge in the DLS, even during Pavlovian conditioning with SNc dopamine neuron activation, which elicited robust DLS dopamine release. Together, our studies show a broad dissociation in the fundamental prediction and reward-related information generated by VTA and SNc dopamine neuron populations and signaled by dopamine across the striatum. Further, they offer new insight into how larger-scale adaptations across the striatal network emerge during learning to coordinate behavior.

Nutritional Approach to Ameliorate Demyelinating Changes Expressed in Spinal Olig2 Immunoreactivity in a Konzo Disease Rat Model

A nutritional approach to ameliorate demyelinating changes expressed in spinal Olig2 immunoreactivity in a Konzo disease rat model was investigated. 30 adult female Wistar rats weighing 200-250g were assigned to 4 groups. Group 1 (Control, n=5) was fed on animal pellets, whereas Group 2 (Protein control, n=5) was provided protein food. Bitter cassava flour was provided to Group 3 (Konzo induced, n=15). Protein and bitter cassava flour were supplied to Group 4 (protein treatment group, n=5). Body weight was taken weekly. The C3-C5 spinal regions were harvested through transcardiac perfusion for histological and immunohistochemical staining. Image J was used to quantify the cells in the spinal cord. Body weight showed a significant reduction in body weight in, Cassava at p<0.01, and Cassava + Protein group at p<0.05 when compared to the control and protein control groups. Examination of the neurons with cresyl violet showed a significant increase in the percentage of unhealthy neuron population in the Konzo-induced group [p<0.001] compared to the control and protein control groups. The rats induced with Konzo showed a significant decrease in Olig2 immunoreactive cells compared to control, protein control, and Cassava + protein groups, at p<0.05. Similarly, Olig2 immunoreactive was substantially increased in the Cassava + Protein group compared to the Cassava group [p<0.05]. This shows that an adequate diet, along with a protein supplement, can counteract the demyelinating and neurodegenerative effects of cyanogenic cassava consumption implicated in Konzo disease.

Neuronal Vulnerability to Degeneration in Parkinson's Disease and Therapeutic Approaches.

Parkinson's disease is the second most common neurodegenerative disease affecting millions of people worldwide. Despite the crucial threat it poses, currently, no specific therapy exists that can completely reverse or halt the progression of the disease. Parkinson's disease pathology is driven by neurodegeneration caused by the intraneuronal accumulation of alpha-synuclein (α-syn) aggregates in Lewy bodies in the substantia nigra region of the brain. Parkinson's disease is a multiorgan disease affecting the central nervous system (CNS) as well as the autonomic nervous system. A bidirectional route of spreading α-syn from the gut to CNS through the vagus nerve and vice versa has also been reported. Despite our understanding of the molecular and pathophysiological aspects of Parkinson's disease, many questions remain unanswered regarding the selective vulnerability of neuronal populations, the neuromodulatory role of the locus coeruleus, and alpha-synuclein aggregation. This review article aims to describe the probable factors that contribute to selective neuronal vulnerability in Parkinson's disease, such as genetic predisposition, bioenergetics, and the physiology of neurons, as well as the interplay of environmental and exogenous modulators. This review also highlights various therapeutic strategies with cell transplants, through viral gene delivery, by targeting α-synuclein and aquaporin protein or epidermal growth factor receptors for the treatment of Parkinson's disease. The application of regenerative medicine and patient-specific personalized approaches have also been explored as promising strategies in the treatment of Parkinson's disease.

Decision-related activity and movement selection in primate visual cortex.

Fluctuations in the activity of sensory neurons often predict perceptual decisions. This connection can be quantified with a metric called choice probability (CP), and there is a longstanding debate about whether CP reflects a causal influence on decisions or an echo of decision-making activity elsewhere in the brain. Here, we show that CP can reflect a third variable, namely, the movement used to indicate the decision. In a standard visual motion discrimination task, neurons in the middle temporal (MT) area of primate cortex responded more strongly during trials that involved a saccade toward their receptive fields. This variability accounted for much of the CP observed across the neuronal population, and it arose through training. Moreover, pharmacological inactivation of MT biased behavioral responses away from the corresponding visual field locations. These results demonstrate that training on a task with fixed sensorimotor contingencies introduces movement-related activity in sensory brain regions and that this plasticity can shape the neural circuitry of perceptual decision-making.

BOLD Contrast Response Characteristics of Aberrant Voxels with Bilateral Visual Population Receptive Fields in Human Albinism.

Albinism is an inherited disorder characterized by disrupted melanin production in the eye, and often in the skin and hair. This retinal hypopigmentation is accompanied by pathological decussation of many temporal retinal afferents at the optic chiasm during development, ultimately resulting in partially superimposed representations of opposite visual hemifields in each cortical hemisphere. Within these aberrant regions of hemifield overlap, individual voxels have been shown to have bilateral, dual population receptive fields (pRFs) responding to roughly mirror-image locations across the vertical meridian. Nonetheless, how these two conflicting inputs combine to determine a voxel's response to image contrast is still unknown. To address this, we stimulated the right and left hemifields with separately controlled sinusoidal gratings, each having a variety of contrasts (0, 8, 20, 45, 100%), and extracted voxel-wise BOLD response amplitudes to each contrast combination in visual areas V1-V3. We then compared voxels' responses to each hemifield stimulated individually with conditions when both hemifields were stimulated simultaneously. We hypothesized that simultaneous stimulation of the two pRF components will result in either a suppressive or facilitative interaction. However, we found that BOLD responses to simultaneous stimulation appeared to reflect simple summation of the neural activity from the individual hemifield conditions. This suggests that the superimposed opposite hemifield representations do not interact. Thus, dual pRFs in albinism likely reflect two co-localized, but functionally independent populations of neurons each of which respond to a single hemifield. This finding is commensurate with psychophysical studies which have shown no clear perceptual interaction between opposite visual hemifields in human albinism.

Enhanced electrophysiological activity and neurotoxicity screening of environmental chemicals using 3D neurons from human neural precursor cells purified with PSA-NCAM

The assessment of neurotoxicity for environmental chemicals is of utmost importance in ensuring public health and environmental safety. Multielectrode array (MEA) technology has emerged as a powerful tool for assessing disturbances in the electrophysiological activity. Although human embryonic stem cell (hESC)-derived neurons have been used in MEA for neurotoxicity screening, obtaining a substantial and sufficiently active population of neurons from hESCs remains challenging. In this study, we successfully differentiated neurons from a large population of human neuronal precursor cells (hNPC) purified using a polysialylated neural cell adhesion molecule (PSA-NCAM), referred to as hNPCPSA-NCAM+. The functional characterization demonstrated that hNPCPSA-NCAM+-derived neurons improve functionality by enhancing electrophysiological activity compared to total hNPC-derived neurons. Furthermore, three-dimensional (3D) neurons derived from hNPCPSA-NCAM+ exhibited reduced maturation time and enhanced electrophysiological activity on MEA. We employed subdivided population analysis of active mean firing rate (MFR) based on electrophysiological intensity to characterize the electrophysiological properties of hNPCPSA-NCAM+-3D neurons. Based on electrophysiological activity including MFR and burst parameters, we evaluated the sensitivity of hNPCPSA-NCAM+-3D neurons on MEA to screen both inhibitory and excitatory neuroactive environmental chemicals. Intriguingly, electrophysiologically active hNPCPSA-NCAM+-3D neurons demonstrated good sensitivity to evaluate neuroactive chemicals, particularly in discriminating excitatory chemicals. Our findings highlight the effectiveness of MEA approaches using hNPCPSA-NCAM+-3D neurons in the assessment of neurotoxicity associated with environmental chemicals. Furthermore, we emphasize the importance of selecting appropriate signal intensity thresholds to enhance neurotoxicity prediction and screening of environmental chemicals.

How well do models of visual cortex generalize to out of distribution samples?

Unit activity in particular deep neural networks (DNNs) are remarkably similar to the neuronal population responses to static images along the primate ventral visual cortex. Linear combinations of DNN unit activities are widely used to build predictive models of neuronal activity in the visual cortex. Nevertheless, prediction performance in these models is often investigated on stimulus sets consisting of everyday objects under naturalistic settings. Recent work has revealed a generalization gap in how predicting neuronal responses to synthetically generated out-of-distribution (OOD) stimuli. Here, we investigated how the recent progress in improving DNNs' object recognition generalization, as well as various DNN design choices such as architecture, learning algorithm, and datasets have impacted the generalization gap in neural predictivity. We came to a surprising conclusion that the performance on none of the common computer vision OOD object recognition benchmarks is predictive of OOD neural predictivity performance. Furthermore, we found that adversarially robust models often yield substantially higher generalization in neural predictivity, although the degree of robustness itself was not predictive of neural predictivity score. These results suggest that improving object recognition behavior on current benchmarks alone may not lead to more general models of neurons in the primate ventral visual cortex.

Neuronal tuning and population representations of shape and category in human visual cortex

Object recognition and categorization are essential cognitive processes which engage considerable neural resources in the human ventral visual stream. However, the tuning properties of human ventral stream neurons for object shape and category are virtually unknown. We performed large-scale recordings of spiking activity in human Lateral Occipital Complex in response to stimuli in which the shape dimension was dissociated from the category dimension. Consistent with studies in nonhuman primates, the neuronal representations were primarily shape-based, although we also observed category-like encoding for images of animals. Surprisingly, linear decoders could reliably classify stimulus category even in data sets that were entirely shape-based. In addition, many recording sites showed an interaction between shape and category tuning. These results represent a detailed study on shape and category coding at the neuronal level in the human ventral visual stream, furnishing essential evidence that reconciles human imaging and macaque single-cell studies.

Alzheimer Disease

Alzheimer's disease (AD) is typified by memory deficiencies that worsen with time, along with cognitive and behavioral abnormalities that eventually result in dementia. AD is one of the most difficult diseases to treat because of its prevalence, high cost of care, effects on patients and caregivers, and lack of mechanism-based therapies. The malfunction and loss of neurons in particular circuits and locations, especially in the populations of nerve cells supporting memory and cognition, causes the AD condition.The neuropathology of AD is characterized by intracellular and extracellular protein aggregation accumulations. In the neuronal perikarya and dystrophic neurites, abnormally phosphorylated tau forms paired helical filaments (PHFs) that combine to form neurofibrillary tangles (NFTs). The extracellular deposition of β-pleated assemblies of Aβ peptide, which result in widespread and neuritic senile plaques, is the second pathogenic hallmark.

Temporal dynamics of short-term neural adaptation across human visual cortex.

Neural responses in visual cortex adapt to prolonged and repeated stimuli. While adaptation occurs across the visual cortex, it is unclear how adaptation patterns and computational mechanisms differ across the visual hierarchy. Here we characterize two signatures of short-term neural adaptation in time-varying intracranial electroencephalography (iEEG) data collected while participants viewed naturalistic image categories varying in duration and repetition interval. Ventral- and lateral-occipitotemporal cortex exhibit slower and prolonged adaptation to single stimuli and slower recovery from adaptation to repeated stimuli compared to V1-V3. For category-selective electrodes, recovery from adaptation is slower for preferred than non-preferred stimuli. To model neural adaptation we augment our delayed divisive normalization (DN) model by scaling the input strength as a function of stimulus category, enabling the model to accurately predict neural responses across multiple image categories. The model fits suggest that differences in adaptation patterns arise from slower normalization dynamics in higher visual areas interacting with differences in input strength resulting from category selectivity. Our results reveal systematic differences in temporal adaptation of neural population responses between lower and higher visual brain areas and show that a single computational model of history-dependent normalization dynamics, fit with area-specific parameters, accounts for these differences.

Populations of hindbrain glucagon-like peptide 1 (GLP1) neurons that innervate the hypothalamic PVH, thalamic PVT, or limbic forebrain BST have axon collaterals that reach all central regions innervated by GLP1 neurons.

Neurons in the caudal nucleus of the solitary tract (cNTS) and intermediate reticular nucleus (IRt) that express the glucagon gene (Gcg) give rise to GLP1-immunopositive axons in the spinal cord and many subcortical brain regions. Central GLP1 receptor signaling contributes to motivated behavior and stress responses in rats and mice, in which hindbrain GLP1 neurons are activated to express cFos in a metabolic state-dependent manner. The present study examined whether GLP1 inputs to distinct brain regions arise from distinct subsets of Gcg-expressing neurons, and mapped the collective distribution of axon collaterals arising from projection-defined GLP1 neural populations. Using our Gcg-Cre knock-in rat model, Cre-dependent adeno-associated virus (AAV1) tracing was conducted in adult male and female rats to compare axonal projections of IRt vs. cNTS GLP1 neurons. Overlapping axonal projections were observed in all brain regions that receive GLP1 input, with the caveat that cNTS injections produced Cre-dependent labeling of some IRt neurons, and vice-versa. In additional experiments, specific diencephalic or limbic forebrain nuclei were microinjected with Cre-dependent retrograde AAVs (AAVrg) expressing reporters that fully labeled the axon collaterals of transduced GLP1 neural populations. AAVrg injected into each forebrain site labeled Gcg-expressing neurons in both the cNTS and IRt. The collective axon collaterals of these labeled neurons entered the spinal cord and every brain region previously reported to contain GLP1-positive axons. These results indicate that axons arising from populations of GLP1 neurons that innervate the thalamic PVT, hypothalamic PVH, and/or limbic forebrain BST collectively innervate all central regions that receive GLP1 axonal input.Significance statement Our novel anatomical findings indicate that target-defined populations of forebrain-projecting GLP1 neurons collectively project to downstream target regions in a widespread sprinkler-type manner, although collateralized axons arising from individual GLP1 projection neurons remain to be defined. Considered together with results from studies investigating the role of central GLP1 receptor signaling pathways in physiology and behavior, these findings support our emerging view that hindbrain Gcg-expressing neurons are positioned to simultaneously modulate synaptic transmission in widespread spinal cord, brainstem, hypothalamic, and limbic forebrain circuits in a metabolic state-dependent manner.

Pan-cortical 2-photon mesoscopic imaging and neurobehavioral alignment in awake, behaving mice.

The flow of neural activity across the neocortex during active sensory discrimination is constrained by task-specific cognitive demands, movements, and internal states. During behavior, the brain appears to sample from a broad repertoire of activation motifs. Understanding how these patterns of local and global activity are selected in relation to both spontaneous and task-dependent behavior requires in-depth study of densely sampled activity at single neuron resolution across large regions of cortex. In a significant advance toward this goal, we developed procedures to record mesoscale 2-photon Ca2+ imaging data from two novel in vivo preparations that, between them, allow for simultaneous access to nearly all 0f the mouse dorsal and lateral neocortex. As a proof of principle, we aligned neural activity with both behavioral primitives and high-level motifs to reveal the existence of large populations of neurons that coordinated their activity across cortical areas with spontaneous changes in movement and/or arousal. The methods we detail here facilitate the identification and exploration of widespread, spatially heterogeneous neural ensembles whose activity is related to diverse aspects of behavior.

Pan-cortical 2-photon mesoscopic imaging and neurobehavioral alignment in awake, behaving mice

The flow of neural activity across the neocortex during active sensory discrimination is constrained by task-specific cognitive demands, movements, and internal states. During behavior, the brain appears to sample from a broad repertoire of activation motifs. Understanding how these patterns of local and global activity are selected in relation to both spontaneous and task-dependent behavior requires in-depth study of densely sampled activity at single neuron resolution across large regions of cortex. In a significant advance toward this goal, we developed procedures to record mesoscale 2-photon Ca2+ imaging data from two novel in vivo preparations that, between them, allow for simultaneous access to nearly all 0f the mouse dorsal and lateral neocortex. As a proof of principle, we aligned neural activity with both behavioral primitives and high-level motifs to reveal the existence of large populations of neurons that coordinated their activity across cortical areas with spontaneous changes in movement and/or arousal. The methods we detail here facilitate the identification and exploration of widespread, spatially heterogeneous neural ensembles whose activity is related to diverse aspects of behavior.

Phase-dependent word perception emerges from region-specific sensitivity to the statistics of language

Neural oscillations reflect fluctuations in excitability, which biases the percept of ambiguous sensory input. Why this bias occurs is still not fully understood. We hypothesized that neural populations representing likely events are more sensitive, and thereby become active on earlier oscillatory phases, when the ensemble itself is less excitable. Perception of ambiguous input presented during less-excitable phases should therefore be biased toward frequent or predictable stimuli that have lower activation thresholds. Here, we show such a frequency bias in spoken word recognition using psychophysics, magnetoencephalography (MEG), and computational modelling. With MEG, we found a double dissociation, where the phase of oscillations in the superior temporal gyrus and medial temporal gyrus biased word-identification behavior based on phoneme and lexical frequencies, respectively. This finding was reproduced in a computational model. These results demonstrate that oscillations provide a temporal ordering of neural activity based on the sensitivity of separable neural populations.

Adaptive modeling and inference of higher-order coordination in neuronal assemblies: A dynamic greedy estimation approach.

Central in the study of population codes, coordinated ensemble spiking activity is widely observable in neural recordings with hypothesized roles in robust stimulus representation, interareal communication, and learning and memory formation. Model-free measures of synchrony characterize coherent pairwise activity but not higher-order interactions, a limitation transcended by statistical models of ensemble spiking activity. However, existing model-based analyses often impose assumptions about the relevance of higher-order interactions and require repeated trials to characterize dynamics in the correlational structure of ensemble activity. To address these shortcomings, we propose an adaptive greedy filtering algorithm based on a discretized mark point-process model of ensemble spiking and a corresponding statistical inference framework to identify significant higher-order coordination. In the course of developing a precise statistical test, we show that confidence intervals can be constructed for greedily estimated parameters. We demonstrate the utility of our proposed methods on simulated neuronal assemblies. Applied to multi-electrode recordings from human and rat cortical assemblies, our proposed methods provide new insights into the dynamics underlying localized population activity during transitions between brain states.

Glioblastoma disrupts cortical network activity at multiple spatial and temporal scales.

The emergence of glioblastoma in cortical tissue initiates early and persistent neural hyperexcitability with signs ranging from mild cognitive impairment to convulsive seizures. The influence of peritumoral synaptic density, expansion dynamics, and spatial contours of excess glutamate upon higher order neuronal network modularity is unknown. We combined cellular and widefield imaging of calcium and glutamate fluorescent reporters in two glioblastoma mouse models with distinct synaptic microenvironments and infiltration profiles. Functional metrics of neural ensembles are dysregulated during tumor invasion depending on the stage of malignant progression and tumor cell proximity. Neural activity is differentially modulated during periods of accelerated and inhibited tumor expansion. Abnormal glutamate accumulation precedes and outpaces the spatial extent of baseline neuronal calcium signaling, indicating these processes are uncoupled in tumor cortex. Distinctive excitability homeostasis patterns and functional connectivity of local and remote neuronal populations support the promise of precision genetic diagnosis and management of this devastating brain disease.

Exploring the Architectural Biases of the Canonical Cortical Microcircuit.

The cortex plays a crucial role in various perceptual and cognitive functions, driven by its basic unit, the canonical cortical microcircuit. Yet, we remain short of a framework that definitively explains the structure-function relationships of this fundamental neuroanatomical motif. To better understand how physical substrates of cortical circuitry facilitate their neuronal dynamics, we employ a computational approach using recurrent neural networks and representational analyses. We examine the differences manifested by the inclusion and exclusion of biologically-motivated inter-areal laminar connections on the computational roles of different neuronal populations in the microcircuit of two hierarchically-related areas, throughout learning. Our findings show that the presence of feedback connections correlates with the functional modularization of cortical populations in different layers, and provides the microcircuit with a natural inductive bias to differentiate expected and unexpected inputs at initialization. Furthermore, when testing the effects of training the microcircuit and its variants with a predictive-coding inspired strategy, we find that doing so helps better encode noisy stimuli in areas of the cortex that receive feedback, all of which combine to suggest evidence for a predictive-coding mechanism serving as an intrinsic operative logic in the cortex.

Hyperactivity of indirect pathway-projecting spiny projection neurons promotes compulsive behavior

Compulsive behaviors are a hallmark symptom of obsessive compulsive disorder (OCD). Striatal hyperactivity has been linked to compulsive behavior generation in correlative studies in humans and causal studies in rodents. However, the contribution of the two distinct striatal output populations to the generation and treatment of compulsive behavior is unknown. These populations of direct and indirect pathway-projecting spiny projection neurons (SPNs) have classically been thought to promote or suppress actions, respectively, leading to a long-held hypothesis that increased output of direct relative to indirect pathway promotes compulsive behavior. Contrary to this hypothesis, here we find that indirect pathway hyperactivity is associated with compulsive grooming in the Sapap3-knockout mouse model of OCD-relevant behavior. Furthermore, we show that suppression of indirect pathway activity using optogenetics or treatment with the first-line OCD pharmacotherapy fluoxetine is associated with reduced grooming in Sapap3-knockouts. Together, these findings highlight the striatal indirect pathway as a potential treatment target for compulsive behavior.

Translational Relevance of Secondary Intracellular Signaling Cascades Following Traumatic Spinal Cord Injury.

Traumatic spinal cord injury (SCI) is a life-threatening and life-altering condition that results in debilitating sensorimotor and autonomic impairments. Despite significant advances in the clinical management of traumatic SCI, many patients continue to suffer due to a lack of effective therapies. The initial mechanical injury to the spinal cord results in a series of secondary molecular processes and intracellular signaling cascades in immune, vascular, glial, and neuronal cell populations, which further damage the injured spinal cord. These intracellular cascades present promising translationally relevant targets for therapeutic intervention due to their high ubiquity and conservation across eukaryotic evolution. To date, many therapeutics have shown either direct or indirect involvement of these pathways in improving recovery after SCI. However, the complex, multifaceted, and heterogeneous nature of traumatic SCI requires better elucidation of the underlying secondary intracellular signaling cascades to minimize off-target effects and maximize effectiveness. Recent advances in transcriptional and molecular neuroscience provide a closer characterization of these pathways in the injured spinal cord. This narrative review article aims to survey the MAPK, PI3K-AKT-mTOR, Rho-ROCK, NF-κB, and JAK-STAT signaling cascades, in addition to providing a comprehensive overview of the involvement and therapeutic potential of these secondary intracellular pathways following traumatic SCI.