Biology subjects

Sakata, S.

Publications and source records attributed to Sakata, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Distributed state-dependent neural ensembles across sleep stages

Sleep architecture is organized by neural ensembles operating across multiple timescales, yet the organizing principles remain unclear. By monitoring neural populations across >40 brain regions in mice, we reveal a distributed sleep code spanning multiple temporal scales. On a slow (minutes-to-seconds) timescale, vigilance state reorganized brain-wide firing and was decodable from every region, with REM sleep emerging as a globally activated state. State transitions followed low-dimensional trajectories, with cortical and subcortical ensembles evolving in antiphase at wake-NREM boundaries but in register during transitions into REM sleep. On a fast (seconds-to-milliseconds) timescale, NREM slow/delta oscillations served as a global rhythm while hierarchically nesting spindles, sharp-wave ripples, and pontine (P) waves, whereas REM theta-P-wave coupling coordinated firing across regions. Regional sleep-related activities covaried with neuromodulatory innervation, while infraslow, history-dependent firing dynamics tracked NREM-REM cycles. Together, these findings provide a cell-resolved atlas of distributed neural population dynamics across sleep stages.

neuroscience↗

bioRxiv2025

Multi-fiber array-based photometry system for multi-regional functional mapping in the mouse brain

Mesoscopic functional brain mapping is essential to better understanding of various brain functions and dysfunctions. However, accessing distributed neural circuits in mammalian brain regions remains a significant challenge. While fiber photometry is a versatile optical approach, existing methods often suffer from invasiveness and scalability. Here we present an affordable multi-fiber array (MFA)-based photometry system to monitor neural signals across multiple regions. Our system comprises a custom-designed MFA utilizing 50-{micro}m diameter optical fibers and off-the-shelf optical components. To demonstrate the systems versatility, we monitored GABAergic population activity using jGCaMP8s across multiple brain regions in head-fixed, awake mice. By combining with pupillometry, we identified state-dependent, region-specific GABAergic dynamics. Our MFA-based photometry system opens new avenues for investigating state-dependent neural dynamics at the mesoscopic level. To facilitate wider adoption, all codes and resources are publicly available on GitHub (https://github.com/Sakata-Lab/MFA).

neuroscience↗

bioRxiv2025

A probiotic bacterium modulates antitumor γδ T-cell responses in lung cancer

The link between the intestinal microflora and cancer outcomes has been recognized for over a decade. Several recent studies have demonstrated that the gut microbiome is associated with the efficiency of T-cell checkpoint blockade therapy for cancer raising interest in strategies to harness this effect via consumption of live microorganisms (probiotics). The probiotic Clostridium butyricum strain MIYAIRI 588 (CBM588) enhances both response rates and overall survival in patients receiving immune checkpoint blockade therapy for non-small cell lung cancer and metastatic renal cell carcinoma but the mechanism underpinning this benefit remains unclear. Here, we show that CBM588 spores induce a population of V{gamma}9V{delta}2 T-cells from the peripheral blood of healthy donors and lung cancer patients. A subset of these T-cells responded to, and directly lysed, cancer cell lines via a butyrophilin 3A-dependant mechanism. In patients taking CBM588 alongside checkpoint blockade, peripheral V{delta}2 T-cells expressed the activation marker CD69 more frequently than those receiving checkpoint blockade alone and the frequency of V{delta}2CD69 cells increased following initiation of CBM588 treatment (p = 0.0041). Our findings provide a potential mechanism by which the manipulation of the intestinal microflora might directly contribute to cancer prognosis by activating immune effector cells with intrinsic anticancer properties.

immunology↗

bioRxiv2025

Experience-dependent sharp-wave ripple deficits in an Alzheimer's disease mouse model

Amyloid pathology is a hallmark of Alzheimers disease (AD). Hippocampal sharp-wave ripples (SWRs) play a role in memory consolidation and are impaired in various AD mouse models. However, it remains unclear how experience affects SWRs and how extrinsic signals contribute to SWR generation in AD. Here, by combining behavioral, in vivo electrophysiological and fiber photometry approaches, we show that an experience-dependent increase in hippocampal SWRs is disrupted in male and female 5xFAD mice. In wild-type mice, SWRs during non-rapid eye movement sleep (NREMS) increased after exploring a novel environment and the SWR rate gradually decreased with NREMS episodes and multiple behavioral sessions. However, 5xFAD mice did not show such experience-dependent SWR rate changes. A similar deficit was observed after a novel object recognition test. On the other hand, sleep spindles were intact in 5xFAD mice under all conditions. Since deficits in basal forebrain cholinergic neurons have been implicated in 5xFAD mice and SWRs are regulated by hippocampal cholinergic tone, we examined if hippocampal cholinergic signals could explain experience-dependent SWR deficits. Using fiber photometry and expressing a genetically encoded acetylcholine (ACh) sensor in the hippocampus, we found that ACh dynamics in the hippocampus were intact in 5xFAD mice across sleep-wake cycles, including NREMS, while we also found a negative correlation of infraslow cortical signal power dynamics with hippocampal ACh signals during NREMS regardless of genotypes. These results suggest that experience-dependent SWR deficits stem from non-cholinergic pathological changes.

neuroscience↗

bioRxiv2025

Depth-resolved fiber photometry of amyloid plaque signals in freely behaving Alzheimer's disease mice

Alzheimers disease pathology typically manifests itself across multiple brain regions yet assessment at this scale in mouse models remains a challenge. This hinders the development of novel therapeutic approaches. Here we introduce a novel fiber photometry approach to monitor amyloid pathology in freely behaving mice. We first demonstrated that flat fiber-based photometry can detect amyloid signals across multiple brain regions under anesthesia after injecting a blood-brain barrier permeable tracer, Methoxy-X04. The depth profile of in vivo fluorescent signals was correlated with postmortem histological plaque signals. After confirming its feasibility ex vivo, we chronically implanted a tapered fiber for depth-resolved fiber photometry in freely behaving mice. After injecting Methoxy-X04, fluorescent signals increased in a depth-specific manner in Alzheimers mice, but not in wild-type littermates. While fiber photometry has been widely adopted to monitor neuronal and non-neuronal activity, our approach expands the capabilities to monitor molecular pathologies such as amyloid plaques, even in a freely behaving condition.

neuroscience↗

bioRxiv2023

SaLSa: a combinatory approach of semi-automatic labeling and long short-term memory to classify behavioral syllables

Accurately and quantitatively describing mouse behavior is an important area. Although advances in machine learning have made it possible to track their behaviors accurately, reliable classification of behavioral sequences or syllables remains a challenge. In this study, we present a novel machine learning approach, called SaLSa (a combination of semi-automatic labeling and long short-term memory-based classification), to classify behavioral syllables of mice exploring an open field. This approach consists of two major steps: first, after tracking multiple body parts, spatial and temporal features of their egocentric coordinates are extracted. A fully automated unsupervised process identifies candidates for behavioral syllables, followed by manual labeling of behavioral syllables using a graphical user interface. Second, a long short-term memory (LSTM) classifier is trained with the labeled data. We found that the classification performance was marked over 97%. It provides a performance equivalent to a state-of-the-art model while classifying some of the syllables. We applied this approach to examine how hyperactivity in a mouse model of Alzheimers disease (AD) develops with age. When the proportion of each behavioral syllable was compared between genotypes and sexes, we found that the characteristic hyper-locomotion of female AD mice emerges between 4 and 8 months. In contrast, age-related reduction in rearing is common regardless of genotype and sex. Overall, SaLSa enables detailed characterization of mouse behavior. Significance StatementDescribing complex animal behavior is a challenge. Here, we developed an open-source, combinatory approach to behavioral syllable classification, called SaLSa (a combination of semi- automatic labeling and long short-term memory-based classification). In order to classify behavioral syllables, this approach combines multiple machine learning methods to label video frames semi- automatically and train a deep learning model. To demonstrate SaLSas versatility, we monitored the exploratory behavior of an Alzheimers disease mouse model and delineated their complex behaviors. We found that female Alzheimers mice become hyperactive in the sense that their locomotion behavior, but not other active behaviors, appear more frequently than controls and even male Alzheimers mice as they age. SaLSa offers a toolkit to analyze complex behaviors.

neuroscience↗

bioRxiv2022

Epigenetic silencing by SMYD3 represses tumor intrinsic interferon response in HPV-negative squamous cell carcinoma of the head and neck.

Cancers often display immune escape, but the mechanisms and potential for reversibility are incompletely understood. Epigenetic dysregulation has been implicated in the immune escape of various cancer types. We have identified the epigenetic modifier SET and MYND-domain containing protein 3 (SMYD3) as a mediator of immune escape in human papilloma virus (HPV)- negative head and neck squamous cell carcinoma (HNSCC), an aggressive disease with poor prognosis and low response to immunotherapy with pembrolizumab, a programmed-death-1 (PD-1) targeting antibody. SMYD3 loss increased the sensitivity of HNSCC cancer cells to IFN-{beta}, resulting in upregulation of type I IFN response and antigen presentation machinery genes. We found that SMYD3 regulates the transcription of Ubiquitin-Like PHD And RING Finger Domain- Containing Protein 1 (UHRF1), a key epigenetic reader of trimethylated lysine 9 on histone H3 (H3K9me3), which binds to H3K9me3-enriched promoters of key immune-related genes and silences their expression. SMYD3 further maintains the repression of immune-related genes through the deposition of H4K20me3 within the gene body regions of these genes. In an anti-PD-1 immune checkpoint resistant syngeneic mouse model of HPV-negative HNSCC, Smyd3 depletion induced influx of CD8+ T-cells, upregulated PD-L1 and MHC class I molecules, and increased sensitivity to anti-PD-1 therapy. SMYD3 overexpression was associated with decreased CD8 T-cell infiltration in tumor samples from patients with HPV-negative HNSCC, and was associated with poor response to pembrolizumab. Overall, these data highlight a previously unreported function of SMYD3 as a master epigenetic regulator of anti-tumor immune response in HPV-negative HNSCC and provide a rationale for translational approaches combining SMYD3 depletion strategies with checkpoint blockade to overcome anti-PD-1 resistance in this devastating disease.

cancer biology↗

bioRxiv2022

Sleep state-dependent modulations of hippocampal theta oscillations and sharp wave-ripples by pontine waves

Ponto-geniculo-occipital (PGO) or pontine (P) waves have long been recognized as an electrophysiological signature of rapid eye movement (REM) sleep. However, P-waves can be observed not just during REM sleep, but also during non-REM (NREM) sleep. Recent studies have uncovered that P-waves are functionally coupled with hippocampal sharp wave-ripples (SWRs) during NREM sleep. However, it remains unclear to what extent P-waves during NREM sleep share their characteristics with P-waves during REM sleep and how the functional coupling to P-waves modulates SWRs. Here, we address these issues by performing multiple types of electrophysiological recordings and fiber photometry in both sexes of mice. P-waves during NREM sleep share their waveform shapes and local neural ensemble dynamics at a short ([~]100 ms) timescale with their REM sleep counterparts. However, the dynamics of mesopontine cholinergic neurons are distinct at a longer ([~]10 s) timescale: although P-waves are accompanied by cholinergic transients, the cholinergic tone gradually reduces before P-wave genesis during NREM sleep. While P-waves are coupled to hippocampal theta rhythms during REM sleep, P-waves during NREM sleep are accompanied by a rapid reduction in hippocampal ripple power. SWRs coupled with P-waves are short-lived and hippocampal neural firing is also reduced after P-waves. These results demonstrate that P-waves are part of coordinated sleep-related activity by functionally coupling with hippocampal ensembles in a state-dependent manner.

neuroscience↗

bioRxiv2022

Developmental overproduction of cortical superficial neurons impairs adult auditory cortical processing

While evolutionary cortical expansion is thought to underlie the evolution of human cognitive capabilities, excessive developmental expansion can lead to megalencephaly, often found in neurodevelopmental disorders such as autism spectrum disorder. Still, little is known about how the overproduction of cortical neurons during development affects cortical processing and behavior in later life. Here we show that the developmental overproduction of cortical superficial neurons impairs auditory processing in mice. We took advantage of a WNT/{beta}- catenin signaling inhibitor, XAV939, to overproduce cortical superficial excitatory neurons during development. XAV939-treated adult mice exhibited a longer reaction time and a higher threshold to detect acoustic stimuli behaviorally. This mouse model also demonstrated abnormal auditory cortical processing depending on experimental conditions: in a passive listening condition, we observed lower beta power and lower spontaneous and auditory-evoked activity in putative excitatory cells whereas higher pre-stimulus spontaneous activity in excitatory cells is associated with failing to detect auditory stimuli behaviorally. On the other hand, the auditory thalamus did not show any significant difference in neural firing between XAV939-treated and control groups. Furthermore, functional monosynaptic connections were significantly reduced between cortical putative excitatory cells. Altogether, our results suggest that the atypical auditory detectability of XAV939-treated animals can be explained by abnormal auditory cortical processing. Although the expansion of cortical size is evolutionarily advantageous, an abnormal expansion during development can result in detrimental effects on cortical processing and perceptual behavior in adulthood.

neuroscience↗

bioRxiv2021

Learned deconvolution using physics priors for structured light-sheet microscopy

Deconvolution is a challenging inverse problem, particularly in techniques that employ complex engineered point-spread functions, such as microscopy with propagation-invariant beams. Here, we present a deep learning method for deconvolution that, in lieu of end-to-end training with ground truths, is trained using known physics of the imaging system. Specifically, we train a generative adversarial network with images generated with the known point-spread function of the system, and combine this with unpaired experimental data that preserves perceptual content. Our method rapidly and robustly deconvolves and superresolves microscopy images, demonstrating a two-fold improvement in image contrast to conventional deconvolution methods. In contrast to common end-to-end networks that often require 1,000-10,000s paired images, our method is experimentally unsupervised and can be trained solely on a few hundred regions of interest. We demonstrate its performance on light-sheet microscopy with propagation-invariant Airy beams, including in calibration beads, oocytes, preimplantation embryos, and excised brain tissue, as well as illustrate its utility for Bessel-beam LSM. This method aims to democratise learned methods for deconvolution, as it does not require data acquisition outwith the conventional imaging protocol.

biophysics↗

bioRxiv2020

Region-specific and state-dependent astrocyte Ca2+ dynamics during the sleep-wake cycle in mice

Neural activity is diverse, and varies depending on brain regions and sleep/wakefulness states. However, whether astrocyte activity differs between sleep/wakefulness states, and whether there are differences in astrocyte activity among brain regions remain poorly understood. In this study, we recorded astrocyte intracellular calcium (Ca2+) concentrations of mice during sleep/wakefulness states in the cortex, hippocampus, hypothalamus, cerebellum, and pons using fiber photometry. For this purpose, male transgenic mice in which their astrocytes specifically express the genetically encoded ratiometric Ca2+ sensor YCnano50 were used. We demonstrated that Ca2+ levels in astrocytes significantly decrease during Rapid Eye Movement (REM) sleep and increase after the onset of wakefulness. In contrast, differences in Ca2+ levels during non-Rapid Eye Movement (NREM) sleep were observed among different brain regions, and no significant decrease was observed in the hypothalamus and pons. Further analyses focusing on the transition between sleep/wakefulness states and correlation analysis with episode duration of REM showed that Ca2+ dynamics differed among brain regions, suggesting the existence of several clusters. To quantify region-specific Ca2+ dynamics, principal component analysis was performed to uncover three clusters; i.e., the first comprised the cortex and hippocampus, the second comprised the cerebellum, and the third comprised the hypothalamus and pons. Our study demonstrated that astrocyte Ca2+ levels change substantially according to sleep/wakefulness states. These changes were generally consistent, unlike neural activity. However, we also clarified that Ca2+ dynamics varies depending on the brain region, implying that astrocytes may play various physiological roles in sleep. Significance statementSleep is an instinctive behavior of many organisms. In the previous five decades, the mechanism of the neural circuits controlling sleep/wakefulness states and the neural activities associated with sleep/wakefulness states in various brain regions have been elucidated. However, whether astrocytes, which are a type of glial cell, change their activity during different sleep/wakefulness states is poorly understood. Here, we demonstrated that dynamic changes in intracellular Ca2+ concentrations occur in the cortex, hippocampus, hypothalamus, cerebellum, and pons of genetically modified mice during natural sleep. Further analyses demonstrated that Ca2+ dynamics slightly differ among different brain regions, implying that the physiological roles of astrocytes in sleep/wakefulness might vary depending on the brain region.

neuroscience↗

bioRxiv2020

Effects of optogenetic stimulation of basal forebrain parvalbumin neurons on Alzheimer's disease pathology

Neuronal activity can modify Alzheimers disease pathology. Although overexcitation of neurons can facilitate disease progression, the induction of cortical gamma oscillations can reduce amyloid load and improve cognitive functions in mouse models. These beneficial effects of gamma oscillations can be caused by either optogenetic activation of cortical parvalbumin-positive (PV+) neurons or 40 Hz repetitive sensory stimuli. However, given the fact that cortical gamma oscillations can be induced by multiple mechanisms, it is still unclear whether other approaches to induce gamma oscillations can also be beneficial. Here we show that optogenetic activation of PV+ neurons in the basal forebrain (BF) increases amyloid burden, rather than reducing it. We applied 40 Hz optical stimulation in the BF of 5xFAD mice by expressing channelrhodopsin-2 (ChR2) in PV+ neurons. After one-hour induction of cortical gamma oscillations over three days, we observed the increase in the concentration of amyloid-{beta}42 in the frontal cortical region, but not amyloid-{beta}40. The density of amyloid plaques also increased in the medial prefrontal cortex and the septal nuclei, both of which are targets of BF PV+ neurons. These results suggest that effects of cortical gamma oscillations on Alzheimers disease pathology can be bidirectional depending on their induction mechanisms. Significance StatementAlzheimers disease (AD) is the most common cause of dementia. Although numerous molecular targets have been identified, the development of treatment is still a challenge. Accumulating evidence shows that artificial control of neuronal activity can modify AD pathology. In particular, the induction of cortical gamma (~40 Hz) oscillations can ameliorate AD pathology and improve cognitive functions. Here we show that optogenetic activation of parvalbumin-positive (PV+) neurons in the basal forebrain (BF) has opposite effects. By expressing channelrhodopsin-2 (ChR2) in PV+ neurons of an AD mouse model and optically stimulating BF PV+ neurons, we induced gamma oscillations and found increased amyloid burden. These results imply that AD pathology can be modified bidirectionally depending on induction mechanisms of gamma oscillations.

neuroscience↗

bioRxiv2020

Widefield light sheet microscopy using an Airy beam combined with deep-learning super-resolution

Imaging across length scales and in depth has been an important pursuit of widefield optical imaging. This promises to reveal fine cellular detail within a widefield snapshot of a tissue sample. Current advances often sacrifice resolution through selective sub-sampling to provide a wide field of view in a reasonable time scale. We demonstrate a new avenue for recovering high-resolution images from sub-sampled data in light-sheet microscopy using deep-learning super-resolution. We combine this with the use of a widefield Airy beam to achieve high-resolution imaging over extended fields of view and depths. We characterise our method on fluorescent beads as test targets. We then demonstrate improvements in imaging amyloid plaques in a cleared brain from a mouse model of Alzheimers disease, and in excised healthy and cancerous colon and breast tissues. This development can be widely applied in all forms of light sheet microscopy to provide a two-fold increase in the dynamic range of the imaged length scale. It has the potential to provide further insight into neuroscience, developmental biology and histopathology.

biophysics↗

bioRxiv2019

Simultaneous electrophysiological recording and fiber photometry in freely behaving mice

In vivo electrophysiology is the gold standard technique used to investigate sub-second neural dynamics in freely behaving animals. However, monitoring cell-type-specific population activity is not a trivial task. Over the last decade, fiber photometry based on genetically encoded calcium indicators has been widely adopted as a versatile tool to monitor cell-type-specific population activity in vivo. However, this approach suffers from low temporal resolution. Here, we combine these two approaches to monitor both sub-second field potentials and cell-type-specific population activity in freely behaving mice. By developing an economical custom-made system, and constructing a hybrid implant of an electrode and a fiber optic cannula, we simultaneously monitor artifact-free pontine field potentials and calcium transients in cholinergic neurons across the sleep-wake cycle. We find that pontine cholinergic activity co-occurs with sub-second pontine waves, called P-waves, during rapid eye movement sleep. Given the simplicity of our approach, simultaneous electrophysiological recording and cell-type-specific imaging provides a novel and valuable tool for interrogating state-dependent neural circuit dynamics in vivo.

neuroscience↗

bioRxiv2019

State-dependent pontine ensemble dynamics and interactions with cortex across sleep states

The pontine nuclei play a crucial role in sleep-wake regulation. However, pontine ensemble dynamics underlying sleep regulation remain poorly understood. By monitoring population activity in multiple pontine and adjacent brainstem areas, here we show slow, state-predictive pontine ensemble dynamics and state-dependent interactions between the pons and the cortex in mice. On a timescale of seconds to minutes, pontine populations exhibit diverse firing across vigilance states, with some of these dynamics being attributed to cell type-specific activity. Pontine population activity can predict pupil dilation and vigilance states: pontine neurons exhibit longer predictable power compared with hippocampal neurons. On a timescale of sub-seconds, pontine waves (P-waves) are observed as synchronous firing of pontine neurons primarily during rapid eye movement (REM) sleep, but also during non-REM (NREM) sleep. Crucially, P-waves functionally interact with cortical activity in a state-dependent manner: during NREM sleep, hippocampal sharp wave-ripples (SWRs) precede P-waves. On the other hand, P-waves during REM sleep are phase-locked with ongoing hippocampal theta oscillations and are followed by burst firing in a subset of hippocampal neurons. Thus, the directionality of functional interactions between the hippocampus and pons changes depending on sleep states. This state-dependent global coordination between pontine and cortical regions implicates distinct functional roles of sleep.

neuroscience↗

bioRxiv2019

Pathway-dependent regulation of sleep dynamics in a network model of the sleep-wake cycle

Sleep is a fundamental homeostatic process within the animal kingdom. Although various brain areas and cell types are involved in the regulation of the sleep-wake cycle, it is still unclear how different pathways between neural populations contribute to its regulation. Here we address this issue by investigating the behavior of a simplified network model upon synaptic weight manipulations. Our model consists of three neural populations connected by excitatory and inhibitory synapses. Activity in each population is described by a firing-rate model, which determines the state of the network. Namely wakefulness, rapid eye movement (REM) sleep or non-REM (NREM) sleep. By systematically manipulating the synaptic weight of every pathway, we show that even this simplified model exhibits non-trivial behaviors: for example, the wake-promoting population contributes not just to the induction and maintenance of wakefulness, but also to sleep induction. Although a recurrent excitatory connection of the REM-promoting population is essential for REM sleep genesis, this recurrent connection does not necessarily contribute to the maintenance of REM sleep. The duration of NREM sleep can be shortened or extended by changes in the synaptic strength of the pathways from the NREM-promoting population. In some cases, there is an optimal range of synaptic strengths that affect a particular state, implying that the amount of manipulations, not just direction (i.e., activation or inactivation), needs to be taken into account. These results demonstrate pathway-dependent regulation of sleep dynamics and highlight the importance of systems-level quantitative approaches for sleep-wake regulatory circuits.\n\nAuthor SummarySleep is essential and ubiquitous across animal species. Over the past half-century, various brain areas, cell types, neurotransmitters, and neuropeptides have been identified as part of a sleep-wake regulating circuitry in the brain. However, it is less explored how individual neural pathways contribute to the sleep-wake cycle. In the present study, we investigate the behavior of a computational model by altering the strength of connections between neuronal populations. This computational model is comprised of a simple network where three neuronal populations are connected together, and the activity of each population determines the current state of the model, that is, wakefulness, rapid-eye-movement (REM) sleep or non-REM (NREM) sleep. When we alter the connection strength of each pathway, we observe that the effect of such alterations on the sleep-wake cycle is highly pathway-dependent. Our results provide further insights into the mechanisms of sleep-wake regulation, and our computational approach can complement future biological experiments.

neuroscience↗

bioRxiv2019

Disentangling neuronal inhibition and inhibitory pathways in the lateral habenula

The lateral habenula (LHb) is hyperactive in depression, and thus potentiating inhibition of this structure makes an interesting target for future antidepressant therapies. However, the circuit mechanisms mediating inhibitory signalling within the LHb are not well-known. We addressed this issue by studying LHb neurons expressing either parvalbumin (PV), neuron-derived neurotrophic factor (Ndnf) or somatostatin (SOM), three markers of particular sub-classes of neocortical inhibitory neurons. While we report that Ndnf is not representative of any particular sub-population of LHb neuron, we find that both PV and SOM are expressed by physiologically distinct sub-classes. Furthermore, we describe multiple sources of inhibitory input to the LHb arising from both local PV-positive neurons, and from PV-positive neurons in the medial dorsal thalamic nucleus, and from SOM-positive neurons in the ventral pallidum. These findings hence provide new insight into inhibitory control within the LHb, and highlight that this structure is more neuronally diverse than previously thought. SummaryThe lateral habenula receives inhibitory input from three distinct sources: from local PV-positive neurons, from PV-positive neurons in the medial dorsal thalamic nucleus (MDT); and from SOM-positive neurons in the ventral pallidum (VP). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/633271v2_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@8df117org.highwire.dtl.DTLVardef@cf226aorg.highwire.dtl.DTLVardef@dc94f5org.highwire.dtl.DTLVardef@1b76a7f_HPS_FORMAT_FIGEXP M_FIG C_FIG Significance statementThe circuitry by which inhibitory signalling is processed within the lateral habenula is currently not well understood; yet this is an important topic as inhibition of the lateral habenula has been shown to have antidepressant efficacy. We therefore investigated inhibitory signalling mechanisms within the lateral habenula by studying input neurons expressing markers commonly associated with inhibitory identity. We identity sources of inhibitory input from both local neurons, and arising from neurons in the medial dorsal thalamic nucleus and ventral pallidum. ContributionsJ.F.W. performed the experiments. R.V. contributed to experiments. J.F.W. analysed the data. K.B. and P.W. designed and performed the in situ hybridisation experiments. C.W. designed and supervised the study, and helped J.F.W write the manuscript. R.V. and S.S. contributed to the manuscript and discussions.

neuroscience↗

bioRxiv2018

Subcortical theta oscillations alternate with high amplitude neocortical population within synchronized states

Synchronized states are marked by large-amplitude low-frequency oscillations in the cortex. These states can be seen during quiet waking or slow-wave sleep. Within synchronized states, previous studies have noted a plethora of different types of activity, including delta oscillations (0.5-4 Hz) and slow oscillations (<1 Hz) in the cortex and large- and small-irregular activity in the hippocampus. However, it is not still fully characterized how neural populations contribute to the synchronized state. Here we apply independent component analysis (ICA) to parse which populations are involved in different kinds of cortical activity, and find two populations that alternate throughout synchronized states. One population broadly affects cortical deep layers, and is associated with larger amplitude slower cortical activity. The other population exhibits theta-frequency oscillations that are not easily observed in raw field potential recordings. These theta oscillations apparently come from below the cortex, suggesting hippocampal origin, and are associated with smaller amplitude faster cortical activity. Relative involvement of these two alternating populations may indicate different modes of operation within synchronized states.

neuroscience↗