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Ohki, K.

Publications and source records attributed to Ohki, K..

14 recordsLinked to original sources

Ultrastructurally planar growth cones during neocortical axon navigation

Neurons extend axons toward spatially defined but often distant targets to establish brain circuits. Callosal projection neurons exemplify this organization, linking corresponding cortical territories between the two hemispheres. Growing axons rely on growth cones to regulate direction and speed through densely packed tissues. Although growth cone morphology and dynamics have been extensively characterized in cultured neurons and invertebrate models, how growth cones navigate the three-dimensional environment of the developing mammalian brain remains poorly explored. Here, we combined a genetically encoded electron microscopy (EM)-labeling strategy and zero-shot deep-learning-based tracing with high-resolution volume EM to reconstruct growth cones of identified callosal projection neurons in the developing mouse brain. Mediolaterally extending growth cones exhibited a planar, fan-shaped morphology, preferentially expanded along the dorsoventral axis. Filopodia extended from the edges of this plane and aligned predominantly with the same axis but showed no directional bias toward the growing direction. Longitudinal in vivo imaging revealed that increased growth cone complexity associated with filopodial extension coincided with lower instantaneous velocity but preceded accelerated extension. Together, these findings reveal a dorsoventrally oriented planar growth cone architecture in which filopodial extension precedes accelerated axon growth, suggesting a structural constraint that may restrict axon navigation to the callosal plane.

neuroscience↗

Blockade of associative spine enlargement impairs awake cortical function

Awake cognition is usually attributed to arousal systems and ongoing electrical activity, yet these do not explain how cortical processing is coupled to prior context and memory formation. Associative synaptic plasticity provides a cellular mechanism for such coupling, but is viewed as memory-related rather than an online requirement for cognition. Here we developed SynC, an A/C-activated chemogenetic perturbation that selectively and reversibly blocks associative spine enlargement while sparing non-associative spine dynamics, excitability, synaptic transmission and NMDA receptor-mediated responses. In mice with broad frontoparietal SynC expression, acute A/C reversibly impaired open-field centre exploration, abolished laser-dot chasing, and delayed feeding initiation. During quiet-wake immobile epochs, cortical firing rates and {gamma}-band power were preserved, but pairwise spike correlations were reduced. Mice also intermittently showed sudden behavioural arrest with reduced {gamma} activity but without the robust {delta} elevation of slow-wave sleep. Critically, in vivo two-photon glutamate uncaging induced seconds-scale associative spine enlargement in [~]24% of neocortical spines, acutely blocked by SynC-A/C. These A/C-induced behavioural, circuit and spine-enlargement effects recovered within 1 h. Thus, wake-like firing and {gamma} activity are not sufficient to sustain awake cognitive function. Rapid associative spine enlargement is required to maintain functional cortical coupling and stable wakefulness.

neuroscience↗

Synaptic input architecture of visual cortical neurons revealed by large-scale synapse imaging without backpropagating action potentials

How neurons integrate thousands of synaptic inputs to compute sharply tuned outputs is a critical question in sensory information processing. To answer this question, it is essential to record the location and activity of synaptic inputs in vivo. However, back-propagating action potential (BAP) calcium signals invade dendrites and spines, making accurate recording of spine responses difficult. In this study, we first developed a new method to record spine calcium responses without BAP signals. Using this method, we performed large-scale imaging of visually evoked spine activity from layer 2/3 pyramidal neurons and revealed three patterns of dendritic functional architectures of synaptic inputs: dendrites with clusters of spines of similar responses, dendrites with spines of diverse responses, and dendrites with spines where the majority of them show no visual response. Our model suggests that only a small fraction of spines on dendrites of clustered architectures are sufficient to generate sharply tuned output.

neuroscience↗

Omission-responsive neurons encode negative prediction error and probability in the auditory cortex

Predictive coding posits the brain predicts incoming sensory information and signals prediction errors when actual input differs from expectations. Positive prediction errors occur when input exceeds predictions, while negative prediction errors arise when input falls short. Specific neurons are theorized to encode negative prediction errors, linked to responses to omitted expected inputs. However, the information encoded in omission responses remains unclear. We recorded single-unit activity in rat auditory cortex during an omission paradigm with varying tone probabilities. We identified neurons selectively responding to omissions, with responses increasing with evidence accumulation and correlating with tone predictability--key characteristics of negative prediction-error neurons. Interestingly, these neurons showed selective omission responses but broad tone responses, revealing an asymmetry in error signaling. We propose a circuit model with laterally interconnected prediction-error neurons reproducing this asymmetry. Our model demonstrates that lateral connections enhance precision and efficiency of prediction encoding, supported by the free energy principle.

neuroscience↗

Orthogonalization of spontaneous and stimulus-driven activity by hierarchical neocortical areal network in primates

Understanding how biological neural networks perform reliable information processing in the presence of intensive spontaneous activity (1-3) is an essential question in biological computation. Stimulus-evoked and spontaneous activities show orthogonal (dissimilar) patterns in the primary visual cortex (V1) of mice (4-6), which is likely to be beneficial for separating sensory signals from internally generated noise (5, 7-12); however, those in V1 of carnivores and primates show highly similar patterns (3, 13-17). Consequently, the mechanism of segregation of stimulus information and internally generated noise in carnivores and primates remain unclear. To address this question, we used primate-optimized functional imaging (18) to precisely compare spontaneous and stimulus-evoked activities in multiple areas of the marmoset visual cortical pathway (19). In marmoset V1, but not in mouse V1, spontaneous and stimulus-evoked activity shared similar activity patterns, suggesting a function of spontaneous activity specific to mammals with functional columns. However, in the higher-order visual areas of marmosets, spontaneous and stimulus-evoked activities exhibited dissimilar patterns. Analysis of neural activity geometry further revealed progressive orthogonalization of the two types of activities along the cortical hierarchy in marmosets, which reached a level comparable to that of mouse V1. Thus, orthogonalization of spontaneous and stimulus-evoked activity is a general principle of cortical computation, which, in primates, is implemented by the hierarchical areal network.

neuroscience↗

ARViS: A bleed-free multi-site automated injection robot for accurate, fast, and dense delivery of virus to mouse and marmoset brains

Genetically encoded fluorescent sensors continue to be developed and improved. If they could be expressed across multiple cortical areas in non-human primates, it would be possible to measure a variety of spatiotemporal dynamics of primate-specific cortical activity. Here, we develop an Automated Robotic Virus injection System (ARViS) for broad expression of a biosensor. ARViS consists of two technologies: image recognition of vasculature structures on the cortical surface to determine multiple injection sites without hitting them, and robotic control of micropipette insertion perpendicular to the cortical surface with 50-m precision. In mouse cortex, ARViS sequentially injected virus solution into 100 sites over a duration of 100-minutes with a bleeding probability of only 0.1% per site. Furthermore, ARViS successfully achieved 266-site injections over the frontoparietal cortex of a common marmoset. We demonstrate one-photon and two-photon calcium imaging in the marmoset frontoparietal cortex, illustrating the effective expression of biosensors delivered by ARViS.

neuroscience↗

Dynamics of motor direction representation in the primate premotor and primary motor cortices during sensorimotor learning

Sensorimotor learning requires reorganization of neuronal activity in the premotor cortex (PM) and primary motor cortex (M1). However, how PM- and M1-specific reorganization occurs in primates remains unclear. We conducted calcium imaging of these areas in common marmosets while they learned a two-target reaching (pull/push) task. Throughout learning, the dorsorostral PM (PMdr) showed peak activity earlier than the dorsocaudal PM (PMdc) and M1. PMdr showed decreased representation of newly introduced (push) movement, whereas PMdc and M1 maintained high representation. Many task-related neurons in PMdc and M1 exhibited a strong preference to either movement direction. PMdc neurons dynamically switched their preferred direction, whereas M1 neurons stably retained their preferred direction. Differences in preferred direction between adjacent neurons in PMdc increased during learning. These results suggest that in primate sensorimotor learning, dynamic motor representation in PMdc converts the cognitive sensorimotor signals of PMdr to stable and specific motor representation of M1.

neuroscience↗

Dynamic behavior of nuclear shape induced by visual stimulation in excitatory neurons of visual cortex

Neurons decline in their functionality over time, and age-related neuronal alterations are associated with phenotypes of neurodegenerative diseases. In non-neural tissues, an infolded nuclear shape has been proposed as a hallmark of aged cells and neurons with infolded nuclei have also been reported to be associated with neuronal activity. Here, we perform time-lapse imaging in the visual cortex of Nex-Cre;SUN1-GFP mice. Nuclear infolding was observed within 15 minutes of stimulation in young nuclei, while the aged nuclei were already infolded pre-stimulation and showed reduced dynamics of the morphology. In young nuclei, the depletion of the stimuli restored the nucleus to a spherical shape and reduced the dynamic behavior, suggesting that nuclear infolding is a reversible process. We also found the aged nucleus to be stiffer than the young one, further relating to the age-associated loss of nuclear shape dynamics. We reveal temporal changes in the nuclear shape upon external stimulation and observe that these morphological dynamics decrease with age.

cell biology↗

Developmental stage-specific patterned activity contributes to callosal axon projections

The developing neocortex exhibits spontaneous network activity with various synchrony levels, which has been implicated in the formation of cortical circuits. We previously reported that the development of callosal axon projections, one of the major long-range axonal projections in the brain, is activity dependent. However, what sort of and when activity is indispensable are not known. Here, using a genetic method to manipulate network activity in a stage-specific manner, we demonstrated that network activity contributes to callosal axon projections in the mouse visual cortex during a "critical period": restoring neuronal activity during that period resumed the projections, whereas restoration after the period failed. Furthermore, in vivo Ca2+ imaging revealed that the projections could be established even without fully restoring highly synchronous activity. Overall, our findings suggest that the spontaneous network activity is selectively required during a critical developmental time window for the formation of long-range axonal projections in the cortex. (150)

neuroscience↗

Long-range interhemispheric projection neurons show biased response properties and fine-scale local subnetworks in mouse visual cortex

Integration of information processed separately in distributed brain regions is essential for brain functions. This integration is enabled by long-range projection neurons, and further, concerted interactions between long-range projections and local microcircuits are crucial. It is not well known, however, how this interaction is implemented in cortical circuits. Here, to decipher this logic, using callosal projection neurons (CPNs) as a model of long-range projections, we found that CPNs exhibited distinct response properties and fine-scale local connectivity patterns. In vivo 2-photon calcium imaging revealed that CPNs showed a higher ipsilateral eye (with respect to their somata) preference, and that CPN pairs showed stronger signal/noise correlation than random pairs. Slice recordings showed CPNs were preferentially connected to CPNs, demonstrating the existence of projection target-dependent fine-scale subnetworks. Collectively, our results suggest that long-range projection target predicts response properties and local connectivity of cortical projection neurons.

neuroscience↗

Astrocytes in the mouse visual cortex reliably respond to visual stimulation

Astrocytes are known to contact with a great number of synapses and may integrate sensory inputs. In the ferret primary visual cortex, astrocytes respond to a visual stimulus with a delay of several seconds with respect to the surrounding neurons. However, in the mouse visual cortex, it remains unclear whether astrocytes respond to visual stimulations. In this study, using dual-color simultaneous in vivo two-photon Ca2+ imaging of neurons and astrocytes in the awake mouse visual cortex, we examined the visual responsiveness of astrocytes and their precise response timing relative to the surrounding neurons. Neurons reliably responded to visual stimulations, whereas astrocytes often showed neuromodulator-mediated global activities, which largely masked small periodic activities. Administration of the selective 1-adrenergic receptor antagonist prazosin substantially reduced such global astrocytic activities without affecting the neuronal visual responses. In the presence of prazosin, astrocytes showed weak but consistent visual responses mostly at their somata. Cross-correlation analysis estimated that the astrocytic visual responses were delayed by approximately 5 s relative to the surrounding neuronal responses. In conclusion, our research demonstrated that astrocytes in the primary visual cortex of awake mice responded to visual stimuli with a delay of several seconds relative to the surrounding neurons, which may indicate the existence of a common mechanism of neuron-astrocyte communication across species.\n\nHighlightsO_LIWe performed dual-color in vivo two-photon Ca2+ imaging of neurons and astrocytes.\nC_LIO_LI1-adrenoblocker prazosin substantially reduced global astrocytic activities.\nC_LIO_LIAstrocytes showed weak but reliable visual responses in the awake mouse visual cortex.\nC_LIO_LIAstrocytic visual responses were delayed by 5 s relative to the neuronal ones.\nC_LI

neuroscience↗

Characterization of nonlinear receptive fields of visual neurons by convolutional neural network

A comprehensive understanding of the stimulus-response properties of individual neurons is necessary to crack the neural code of sensory cortices. However, a barrier to achieving this goal is the difficulty of analyzing the nonlinearity of neuronal responses. In computer vision, artificial neural networks, especially convolutional neural networks (CNNs), have demonstrated state-of-the-art performance in image recognition by capturing the higher-order statistics of natural images. Here, we incorporated CNN for encoding models of neurons in the visual cortex to develop a new method of nonlinear response characterization, especially nonlinear estimation of receptive fields (RFs), without assumptions regarding the type of nonlinearity. Briefly, after training CNN to predict the visual responses of neurons to natural images, we synthesized the RF image such that the image would predictively evoke a maximum response (\"maximization-of-activation\" method). We first demonstrated the proof-of-principle using a dataset of simulated cells with various types of nonlinearity, revealing that CNN could be used to estimate the nonlinear RF of simulated cells. In particular, we could visualize various types of nonlinearity underlying the responses, such as shift-invariant RFs or rotation-invariant RFs. These results suggest that the method may be applicable to neurons with complex nonlinearities, such as rotation-invariant neurons in higher visual areas. Next, we applied the method to a dataset of neurons in the mouse primary visual cortex (V1) whose responses to natural images were recorded via two-photon Ca2+ imaging. We could visualize shift-invariant RFs with Gabor-like shapes for some V1 neurons. By quantifying the degree of shift-invariance, each V1 neuron was classified as either a shift-variant (simple) cell or shift-invariant (complex-like) cell, and these two types of neurons were not clustered in cortical space. These results suggest that the novel CNN encoding model is useful in nonlinear response analyses of visual neurons and potentially of any sensory neurons.

neuroscience↗

Representation of natural image contents by sparsely active neurons in visual cortex

Natural scenes sparsely activate neurons in the primary visual cortex (V1). However, how sparsely active neurons robustly represent natural images and how the information is optimally decoded from the representation have not been revealed. We reconstructed natural images from V1 activity in anaesthetized and awake mice. A single natural image was linearly decodable from a surprisingly small number of highly responsive neurons, and an additional use of remaining neurons even degraded the decoding. This representation was achieved by diverse receptive fields (RFs) of the small number of highly responsive neurons. Furthermore, these neurons reliably represented the image across trials, regardless of trial-to-trial response variability. The reliable representation was supported by multiple neurons with overlapping RFs. Based on our results, the diverse, partially overlapping RFs ensure sparse and reliable representation. We propose a new representation scheme in which information is reliably represented while the representing neuronal patterns change across trials and that collecting only the activity of highly responsive neurons is an optimal decoding strategy for the downstream neurons

neuroscience↗

Neuronal origin of the temporal dynamics of spontaneous BOLD activity correlation

Resting-state functional connectivity (FC) has become a major fMRI method to study network organization of human brains. There has been recent interest in the temporal fluctuations of FC calculated using short time windows (\"dynamic FC\") because this method could provide information inaccessible with conventional \"static\" FC, which is typically calculated using the entire scan lasting several tens of minutes. Although multiple studies have revealed considerable temporal fluctuations in FC, it is still unclear whether the fluctuations of FC measured in hemodynamics reflect the dynamics of underlying neural activity. We addressed this question using simultaneous imaging of neuronal calcium and hemodynamic signals in mice and found coordinated temporal dynamics of calcium FC and hemodynamic FC measured in the same short time windows. Moreover, we found that variation in transient neuronal coactivation patterns (CAPs) was significantly related to temporal fluctuations of sliding window FC in hemodynamics. Finally, we show that the observed dynamics of FC cannot be fully accounted for by simulated data assuming stationary FC. These results provide evidence for the neuronal origin of dynamic FC and further suggest that information relevant to FC is condensed in temporally sparse events that can be extracted using a small number of time points.

neuroscience↗