Large-scale animal model study uncovers altered brain pH and lactate levels as a transdiagnostic endophenotype of neuropsychiatric disorders involving cognitive impairment.

Increased levels of lactate, an end-product of glycolysis, have been proposed as a potential surrogate marker for metabolic changes during neuronal excitation. These changes in lactate levels can result in decreased brain pH, which has been implicated in patients with various neuropsychiatric disorders. We previously demonstrated that such alterations are commonly observed in five mouse models of schizophrenia, bipolar disorder, and autism, suggesting a shared endophenotype among these disorders rather than mere artifacts due to medications or agonal state. However, there is still limited research on this phenomenon in animal models, leaving its generality across other disease animal models uncertain. Moreover, the association between changes in brain lactate levels and specific behavioral abnormalities remains unclear. To address these gaps, the International Brain pH Project Consortium investigated brain pH and lactate levels in 109 strains/conditions of 2294 animals with genetic and other experimental manipulations relevant to neuropsychiatric disorders. Systematic analysis revealed that decreased brain pH and increased lactate levels were common features observed in multiple models of depression, epilepsy, Alzheimer's disease, and some additional schizophrenia models. While certain autism models also exhibited decreased pH and increased lactate levels, others showed the opposite pattern, potentially reflecting subpopulations within the autism spectrum. Furthermore, utilizing large-scale behavioral test battery, a multivariate cross-validated prediction analysis demonstrated that poor working memory performance was predominantly associated with increased brain lactate levels. Importantly, this association was confirmed in an independent cohort of animal models. Collectively, these findings suggest that altered brain pH and lactate levels, which could be attributed to dysregulated excitation/inhibition balance, may serve as transdiagnostic endophenotypes of debilitating neuropsychiatric disorders characterized by cognitive impairment, irrespective of their beneficial or detrimental nature.

Unraveling the mysteries of dendritic spine dynamics: Five key principles shaping memory and cognition.

Recent research extends our understanding of brain processes beyond just action potentials and chemical transmissions within neural circuits, emphasizing the mechanical forces generated by excitatory synapses on dendritic spines to modulate presynaptic function. From in vivo and in vitro studies, we outline five central principles of synaptic mechanics in brain function: P1: Stability - Underpinning the integral relationship between the structure and function of the spine synapses. P2: Extrinsic dynamics - Highlighting synapse-selective structural plasticity which plays a crucial role in Hebbian associative learning, distinct from pathway-selective long-term potentiation (LTP) and depression (LTD). P3: Neuromodulation - Analyzing the role of G-protein-coupled receptors, particularly dopamine receptors, in time-sensitive modulation of associative learning frameworks such as Pavlovian classical conditioning and Thorndike's reinforcement learning (RL). P4: Instability - Addressing the intrinsic dynamics crucial to memory management during continual learning, spotlighting their role in "spine dysgenesis" associated with mental disorders. P5: Mechanics - Exploring how synaptic mechanics influence both sides of synapses to establish structural traces of short- and long-term memory, thereby aiding the integration of mental functions. We also delve into the historical background and foresee impending challenges.

Mechanical transmission at spine synapses: Short-term potentiation and working memory.

Do dendritic spines, which comprise the postsynaptic component of most excitatory synapses, exist only for their structural dynamics, receptor trafficking, and chemical and electrical compartmentation? The answer is no. Simultaneous investigation of both spine and presynaptic terminals has recently revealed a novel feature of spine synapses. Spine enlargement pushes the presynaptic terminals with muscle-like force and augments the evoked glutamate release for up to 20 min. We now summarize the evidence that such mechanical transmission shares critical features in common with short-term potentiation (STP) and may represent the cellular basis of short-term and working memory. Thus, spine synapses produce the force of learning to leave structural traces for both short and long-term memories.

Tri-view two-photon microscopic image registration and deblurring with convolutional neural networks.

Two-photon fluorescence microscopy has enabled the three-dimensional (3D) neural imaging of deep cortical regions. While it can capture the detailed neural structures in the x-y image space, the image quality along the depth direction is lower because of lens blur, which often makes it difficult to identify the neural connectivity. To address this problem, we propose a novel approach for restoring the isotropic image volume by estimating and fusing the intersection regions of the images captured from three orthogonal viewpoints using convolutional neural networks (CNNs). Because convolution on 3D images is computationally complex, the proposed method takes the form of cascaded CNN models consisting of rigid transformation, dense registration, and deblurring networks for more efficient processing. In addition, to enable self-supervised learning, we trained the CNN models with simulated synthetic images by considering the distortions of the microscopic imaging process. Through extensive experiments, the proposed method achieved substantial image quality improvements.

A behavioural correlate of the synaptic eligibility trace in the nucleus accumbens.

Reward reinforces the association between a preceding sensorimotor event and its outcome. Reinforcement learning (RL) theory and recent brain slice studies explain the delayed reward action such that synaptic activities triggered by sensorimotor events leave a synaptic eligibility trace for 1 s. The trace produces a sensitive period for reward-related dopamine to induce synaptic plasticity in the nucleus accumbens (NAc). However, the contribution of the synaptic eligibility trace to behaviour remains unclear. Here we examined a reward-sensitive period to brief pure tones with an accurate measurement of an effective timing of water reward in head-fixed Pavlovian conditioning, which depended on the plasticity-related signaling in the NAc. We found that the reward-sensitive period was within 1 s after the pure tone presentation and optogenetically-induced presynaptic activities at the NAc, showing that the short reward-sensitive period was in conformity with the synaptic eligibility trace in the NAc. These findings support the application of the synaptic eligibility trace to construct biologically plausible RL models.

Mechanical actions of dendritic-spine enlargement on presynaptic exocytosis.

Synaptic transmission involves cell-to-cell communication at the synaptic junction between two neurons, and chemical and electrical forms of this process have been extensively studied. In the brain, excitatory glutamatergic synapses are often made on dendritic spines that enlarge during learning1-5. As dendritic spines and the presynaptic terminals are tightly connected with the synaptic cleft6, the enlargement may have mechanical effects on presynaptic functions7. Here we show that fine and transient pushing of the presynaptic boutons with a glass pipette markedly promotes both the evoked release of glutamate and the assembly of SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins8-12-as measured by Förster resonance transfer (FRET) and fluorescence lifetime imaging-in rat slice culture preparations13. Both of these effects persisted for more than 20 minutes. The increased presynaptic FRET was independent of cytosolic calcium (Ca2+), but dependent on the assembly of SNARE proteins and actin polymerization in the boutons. Notably, a low hypertonic solution of sucrose (20 mM) had facilitatory effects on both the FRET and the evoked release without inducing spontaneous release, in striking contrast with a high hypertonic sucrose solution (300 mM), which induced exocytosis by itself14. Finally, spine enlargement induced by two-photon glutamate uncaging enhanced the evoked release and the FRET only when the spines pushed the boutons by their elongation. Thus, we have identified a mechanosensory and transduction mechanism15 in the presynaptic boutons, in which the evoked release of glutamate is enhanced for more than 20 min.

The critical balance between dopamine D2 receptor and RGS for the sensitive detection of a transient decay in dopamine signal.

In behavioral learning, reward-related events are encoded into phasic dopamine (DA) signals in the brain. In particular, unexpected reward omission leads to a phasic decrease in DA (DA dip) in the striatum, which triggers long-term potentiation (LTP) in DA D2 receptor (D2R)-expressing spiny-projection neurons (D2 SPNs). While this LTP is required for reward discrimination, it is unclear how such a short DA-dip signal (0.5-2 s) is transferred through intracellular signaling to the coincidence detector, adenylate cyclase (AC). In the present study, we built a computational model of D2 signaling to determine conditions for the DA-dip detection. The DA dip can be detected only if the basal DA signal sufficiently inhibits AC, and the DA-dip signal sufficiently disinhibits AC. We found that those two requirements were simultaneously satisfied only if two key molecules, D2R and regulators of G protein signaling (RGS) were balanced within a certain range; this balance has indeed been observed in experimental studies. We also found that high level of RGS was required for the detection of a 0.5-s short DA dip, and the analytical solutions for these requirements confirmed their universality. The imbalance between D2R and RGS is associated with schizophrenia and DYT1 dystonia, both of which are accompanied by abnormal striatal LTP. Our simulations suggest that D2 SPNs in patients with schizophrenia and DYT1 dystonia cannot detect short DA dips. We finally discussed that such psychiatric and movement disorders can be understood in terms of the imbalance between D2R and RGS.

Computational roles of intrinsic synaptic dynamics.

Conventional theories assume that long-term information storage in the brain is implemented by modifying synaptic efficacy. Recent experimental findings challenge this view by demonstrating that dendritic spine sizes, or their corresponding synaptic weights, are highly volatile even in the absence of neural activity. Here, we review previous computational works on the roles of these intrinsic synaptic dynamics. We first present the possibility for neuronal networks to sustain stable performance in their presence, and we then hypothesize that intrinsic dynamics could be more than mere noise to withstand, but they may improve information processing in the brain.

Spine dynamics in the brain, mental disorders and artificial neural networks.

In the brain, most synapses are formed on minute protrusions known as dendritic spines. Unlike their artificial intelligence counterparts, spines are not merely tuneable memory elements: they also embody algorithms that implement the brain's ability to learn from experience and cope with new challenges. Importantly, they exhibit structural dynamics that depend on activity, excitatory input and inhibitory input (synaptic plasticity or 'extrinsic' dynamics) and dynamics independent of activity ('intrinsic' dynamics), both of which are subject to neuromodulatory influences and reinforcers such as dopamine. Here we succinctly review extrinsic and intrinsic dynamics, compare these with parallels in machine learning where they exist, describe the importance of intrinsic dynamics for memory management and adaptation, and speculate on how disruption of extrinsic and intrinsic dynamics may give rise to mental disorders. Throughout, we also highlight algorithmic features of spine dynamics that may be relevant to future artificial intelligence developments.

Melanophilin Accelerates Insulin Granule Fusion without Predocking to the Plasma Membrane.

Direct observation of fluorescence-labeled secretory granule exocytosis in living pancreatic ß-cells has revealed heterogeneous prefusion behaviors: some granules dwell beneath the plasma membrane before fusion, while others fuse immediately once they are recruited to the plasma membrane. Although the former mode seems to follow sequential docking-priming-fusion steps as found in synaptic vesicle exocytosis, the latter mode, which is unique to secretory granule exocytosis, has not been explored well. Here, we show that melanophilin, one of the effectors of the monomeric guanosine-5'-triphosphatase Rab27 on the granule membrane, is involved in such an accelerated mode of exocytosis. Melanophilin-mutated leaden mouse and melanophilin-downregulated human pancreatic ß-cells both exhibit impaired glucose-stimulated insulin secretion, with a specific reduction in fusion events that bypass stable docking to the plasma membrane. Upon stimulus-induced [Ca2+]i rise, melanophilin mediates this type of fusion by dissociating granules from myosin-Va and actin in the actin cortex and by associating them with a fusion-competent, open form of syntaxin-4 on the plasma membrane. These findings provide the hitherto unknown mechanism to support sustainable exocytosis by which granules are recruited from the cell interior and fuse promptly without stable predocking to the plasma membrane.

Computational Characteristics of the Striatal Dopamine System Described by Reinforcement Learning With Fast Generalization.

Generalization is the ability to apply past experience to similar but non-identical situations. It not only affects stimulus-outcome relationships, as observed in conditioning experiments, but may also be essential for adaptive behaviors, which involve the interaction between individuals and their environment. Computational modeling could potentially clarify the effect of generalization on adaptive behaviors and how this effect emerges from the underlying computation. Recent neurobiological observation indicated that the striatal dopamine system achieves generalization and subsequent discrimination by updating the corticostriatal synaptic connections in differential response to reward and punishment. In this study, we analyzed how computational characteristics in this neurobiological system affects adaptive behaviors. We proposed a novel reinforcement learning model with multilayer neural networks in which the synaptic weights of only the last layer are updated according to the prediction error. We set fixed connections between the input and hidden layers to maintain the similarity of inputs in the hidden-layer representation. This network enabled fast generalization of reward and punishment learning, and thereby facilitated safe and efficient exploration of spatial navigation tasks. Notably, it demonstrated a quick reward approach and efficient punishment aversion in the early learning phase, compared to algorithms that do not show generalization. However, disturbance of the network that causes noisy generalization and impaired discrimination induced maladaptive valuation. These results suggested the advantage and potential drawback of computation by the striatal dopamine system with regard to adaptive behaviors.

Signaling models for dopamine-dependent temporal contiguity in striatal synaptic plasticity.

Animals remember temporal links between their actions and subsequent rewards. We previously discovered a synaptic mechanism underlying such reward learning in D1 receptor (D1R)-expressing spiny projection neurons (D1 SPN) of the striatum. Dopamine (DA) bursts promote dendritic spine enlargement in a time window of only a few seconds after paired pre- and post-synaptic spiking (pre-post pairing), which is termed as reinforcement plasticity (RP). The previous study has also identified underlying signaling pathways; however, it still remains unclear how the signaling dynamics results in RP. In the present study, we first developed a computational model of signaling dynamics of D1 SPNs. The D1 RP model successfully reproduced experimentally observed protein kinase A (PKA) activity, including its critical time window. In this model, adenylate cyclase type 1 (AC1) in the spines/thin dendrites played a pivotal role as a coincidence detector against pre-post pairing and DA burst. In particular, pre-post pairing (Ca2+ signal) stimulated AC1 with a delay, and the Ca2+-stimulated AC1 was activated by the DA burst for the asymmetric time window. Moreover, the smallness of the spines/thin dendrites is crucial to the short time window for the PKA activity. We then developed a RP model for D2 SPNs, which also predicted the critical time window for RP that depended on the timing of pre-post pairing and phasic DA dip. AC1 worked for the coincidence detector in the D2 RP model as well. We further simulated the signaling pathway leading to Ca2+/calmodulin-dependent protein kinase II (CaMKII) activation and clarified the role of the downstream molecules of AC1 as the integrators that turn transient input signals into persistent spine enlargement. Finally, we discuss how such timing windows guide animals' reward learning.

Dopamine D2 receptors in discrimination learning and spine enlargement.

Dopamine D2 receptors (D2Rs) are densely expressed in the striatum and have been linked to neuropsychiatric disorders such as schizophrenia1,2. High-affinity binding of dopamine suggests that D2Rs detect transient reductions in dopamine concentration (the dopamine dip) during punishment learning3-5. However, the nature and cellular basis of D2R-dependent behaviour are unclear. Here we show that tone reward conditioning induces marked stimulus generalization in a manner that depends on dopamine D1 receptors (D1Rs) in the nucleus accumbens (NAc) of mice, and that discrimination learning refines the conditioning using a dopamine dip. In NAc slices, a narrow dopamine dip (as short as 0.4 s) was detected by D2Rs to disinhibit adenosine A2A receptor (A2AR)-mediated enlargement of dendritic spines in D2R-expressing spiny projection neurons (D2-SPNs). Plasticity-related signalling by Ca2+/calmodulin-dependent protein kinase II and A2ARs in the NAc was required for discrimination learning. By contrast, extinction learning did not involve dopamine dips or D2-SPNs. Treatment with methamphetamine, which dysregulates dopamine signalling, impaired discrimination learning and spine enlargement, and these impairments were reversed by a D2R antagonist. Our data show that D2Rs refine the generalized reward learning mediated by D1Rs.

Generative and discriminative model-based approaches to microscopic image restoration and segmentation.

Image processing is one of the most important applications of recent machine learning (ML) technologies. Convolutional neural networks (CNNs), a popular deep learning-based ML architecture, have been developed for image processing applications. However, the application of ML to microscopic images is limited as microscopic images are often 3D/4D, that is, the image sizes can be very large, and the images may suffer from serious noise generated due to optics. In this review, three types of feature reconstruction applications to microscopic images are discussed, which fully utilize the recent advancements in ML technologies. First, multi-frame super-resolution is introduced, based on the formulation of statistical generative model-based techniques such as Bayesian inference. Second, data-driven image restoration is introduced, based on supervised discriminative model-based ML technique. In this application, CNNs are demonstrated to exhibit preferable restoration performance. Third, image segmentation based on data-driven CNNs is introduced. Image segmentation has become immensely popular in object segmentation based on electron microscopy (EM); therefore, we focus on EM image processing.

Mu-net: Multi-scale U-net for two-photon microscopy image denoising and restoration.

Advances in two two-photon microscopy (2PM) have made three-dimensional (3D) neural imaging of deep cortical regions possible. However, 2PM often suffers from poor image quality because of various noise factors, including blur, white noise, and photo bleaching. In addition, the effectiveness of the existing image processing methods is limited because of the special features of 2PM images such as deeper tissue penetration but higher image noises owing to rapid laser scanning. To address the denoising problems in 2PM 3D images, we present a new algorithm based on deep convolutional neural networks (CNNs). The proposed model consists of multiple U-nets in which an individual U-net removes noises at different scales and then yields a performance improvement based on a coarse-to-fine strategy. Moreover, the constituent CNNs employ fully 3D convolution operations. Such an architecture enables the proposed model to facilitate end-to-end learning without any pre/post processing. Based on the experiments on 2PM image denoising, we observed that our new algorithm demonstrates substantial performance improvements over other baseline methods.

Dual-Component Structural Plasticity Mediated by αCaMKII Autophosphorylation on Basal Dendrites of Cortical Layer 2/3 Neurones.

Sensory cortex exhibits receptive field plasticity throughout life in response to changes in sensory experience and offers the experimental possibility of aligning functional changes in receptive field properties with underpinning structural changes in synapses. We looked at the effects on structural plasticity of two different patterns of whisker deprivation in male and female mice: chessboard deprivation, which causes functional plasticity; and all deprived, which does not. Using 2-photon microscopy and chronic imaging through a cranial window over the barrel cortex, we found that layer 2/3 neurones exhibit robust structural plasticity, but only in response to whisker deprivation patterns that cause functional plasticity. Chessboard pattern deprivation caused dual-component plasticity in layer 2/3 by (1) increasing production of new spines that subsequently persisted for weeks and (2) enlarging spine head sizes in the preexisting stable spine population. Structural plasticity occurred on basal dendrites, but not apical dendrites. Both components of plasticity were absent in αCaMKII-T286A mutants that lack LTP and experience-dependent potentiation in barrel cortex, implying that αCaMKII autophosphorylation is not only important for stabilization and enlargement of spines, but also for new spine production. These studies therefore reveal the relationship between spared whisker potentiation in layer 2/3 neurones and the form and mechanisms of structural plasticity processes that underlie them.SIGNIFICANCE STATEMENT This study provides a missing link in a chain of reasoning that connects LTP to experience-dependent functional plasticity in vivo We found that increases in dendritic spine formation and spine enlargement (both of which are characteristic of LTP) only occurred in barrel cortex during sensory deprivation that produced potentiation of sensory responses. Furthermore, the dendritic spine plasticity did not occur during sensory deprivation in mice lacking LTP and experience-dependent potentiation (αCaMKII autophosphorylation mutants). We also found that the dual-component dendritic spine plasticity only occurred on basal dendrites and not on apical dendrites, thereby resolving a paradox in the literature suggesting that layer 2/3 neurones lack structural plasticity in response to sensory deprivation.

Bidirectional in vivo structural dendritic spine plasticity revealed by two-photon glutamate uncaging in the mouse neocortex.

Most excitatory synapses in the brain form on dendritic spines. Two-photon uncaging of glutamate is widely utilized to characterize the structural plasticity of dendritic spines in brain slice preparations in vitro. In the present study, glutamate uncaging was used to investigate spine plasticity, for the first time, in vivo. A caged glutamate compound was applied to the surface of the mouse visual cortex in vivo, revealing the successful induction of spine enlargement by repetitive two-photon uncaging in a magnesium free solution. Notably, this induction occurred in a smaller fraction of spines in the neocortex in vivo (22%) than in hippocampal slices (95%). Once induced, the time course and mean long-term enlargement amplitudes were similar to those found in hippocampal slices. However, low-frequency (1-2 Hz) glutamate uncaging in the presence of magnesium caused spine shrinkage in a similar fraction (35%) of spines as in hippocampal slices, though spread to neighboring spines occurred less frequently than it did in hippocampal slices. Thus, the structural plasticity may occur similarly in the neocortex in vivo as in hippocampal slices, although it happened less frequently in our experimental conditions.

Intrinsic Spine Dynamics Are Critical for Recurrent Network Learning in Models With and Without Autism Spectrum Disorder.

It is often assumed that Hebbian synaptic plasticity forms a cell assembly, a mutually interacting group of neurons that encodes memory. However, in recurrently connected networks with pure Hebbian plasticity, cell assemblies typically diverge or fade under ongoing changes of synaptic strength. Previously assumed mechanisms that stabilize cell assemblies do not robustly reproduce the experimentally reported unimodal and long-tailed distribution of synaptic strengths. Here, we show that augmenting Hebbian plasticity with experimentally observed intrinsic spine dynamics can stabilize cell assemblies and reproduce the distribution of synaptic strengths. Moreover, we posit that strong intrinsic spine dynamics impair learning performance. Our theory explains how excessively strong spine dynamics, experimentally observed in several animal models of autism spectrum disorder, impair learning associations in the brain.

Nanoscale imaging reveals miRNA-mediated control of functional states of dendritic spines.

Dendritic spines are major loci of excitatory inputs and undergo activity-dependent structural changes that contribute to synaptic plasticity and memory formation. Despite the existence of various classification types of spines, how they arise and which molecular components trigger their structural plasticity remain elusive. microRNAs (miRNAs) have emerged as critical regulators of synapse development and plasticity via their control of gene expression. Brain-specific miR-134s likely regulate the morphological maturation of spines, but their subcellular distributions and functional impacts have rarely been assessed. Here, we exploited atomic force microscopy to visualize in situ miR-134s, which indicated that they are mainly distributed at nearby dendritic shafts and necks of spines. The abundance of miR-134s varied between morphologically and functionally distinct spine types, and their amounts were inversely correlated with their postulated maturation stages. Moreover, spines exhibited reduced contents of miR-134s when selectively stimulated with beads containing brain-derived neurotropic factor (BDNF). Taken together, in situ visualizations of miRNAs provided unprecedented insights into the "inverse synaptic-tagging" roles of miR-134s that are selective to inactive/irrelevant synapses and potentially a molecular means for modifying synaptic connectivity via structural alteration.

Strong stimulation triggers full fusion exocytosis and very slow endocytosis of the small dense core granules in carotid glomus cells.

Chemosensory glomus cells of the carotid bodies release transmitters, including ATP and dopamine mainly via the exocytosis of small dense core granules (SDCGs, vesicular diameter of ∼100 nm). Using carbon-fiber amperometry, we showed previously that with a modest uniform elevation in cytosolic Ca2+ concentration ([Ca2+]i of ∼0.5 µM), SDCGs of rat glomus cells predominantly underwent a "kiss-and-run" mode of exocytosis. Here, we examined whether a larger [Ca2+]i rise influenced the mode of exocytosis. Activation of voltage-gated Ca2+ channels by a train of voltage-clamped depolarizations which elevated [Ca2+]i to ∼1.6 µM increased the cell membrane capacitance by ∼2.5%. At 30 s after such a stimulus, only 5% of the added membrane was retrieved. Flash photolysis of caged-Ca2+ (which elevated [Ca2+]i to ∼16 µM) increased cell membrane capacitance by ∼13%, and only ∼30% of the added membrane was retrieved at 30 s after the UV flash. When exocytosis and endocytosis were monitored using the two-photon excitation and extracellular polar tracer (TEP) imaging of FM1-43 fluorescence in conjunction with photolysis of caged Ca2+, almost uniform exocytosis was detected over the cell's entire surface and it was followed by slow endocytosis. Immunocytochemistry showed that the cytoplasmic densities of dynamin I, II and clathrin (key proteins that mediate endocytosis) in glomus cells were less than half of those in adrenal chromaffin cells, suggesting that a lower expression of endocytotic machinery may underlie the slow endocytosis in glomus cells. An analysis of the relative change in the signals from two fluorescent dyes that simultaneously monitored the addition of vesicular volume and plasma membrane surface area, suggested that with an intense stimulus, SDCGs of glomus cells underwent full fusion without any significant "compound" exocytosis. Therefore, during a severe hypoxic challenge, glomus granules undergo full fusion for a more complete release of transmitters.