Neuronal Dynamics Regulating Brain and Behavioral State Transitions

Complex dynamic behavioral transitions in auditory neurons induced by chaotic activity

Chaotic sequences are widely used in secure communication due to their high randomness. Chaotic resonance (CR) refers to the resonant response of a system to weak signals induced by chaotic activity, but its practical application remains limited. This study designs a simplified FitzHugh-Nagumo (FHN) auditory neuron model by simulating the physiological activities of auditory neurons and considering the combined stimulation of chaotic activity and sound signals. It is found that the neuron dynamics depend on both external sound stimuli and chaotic current intensity. Chaotic currents induce spikes in the neuron output sequence through CR, and the spikes become more frequent with increasing current intensity, eventually leading to a chaotic state regardless of the initial state. However, the sensitivity of the initial value of this chaotic sequence shifts to the chaotic current excitation system. The injection of chaotic currents can reduce the system's average Hamiltonian energy under certain conditions. By measuring the complexity of the generated sequences, we find that the addition of chaotic currents can enhance the complexity of the original sequences, and the enhancement ability increases with the intensity. This provides a new approach to enhance the complexity of original chaotic sequences. Moreover, different chaotic currents can induce different chaotic sequences with varying abilities to enhance the complexity of the original sequences. We hope our work can contribute to secure communication.

A line attractor encoding a persistent internal state requires neuropeptide signaling

Internal states drive survival behaviors, but their neural implementation is poorly understood. Recently, we identified a line attractor in the ventromedial hypothalamus (VMH) that represents a state of aggressiveness. Line attractors can be implemented by recurrent connectivity or neuromodulatory signaling, but evidence for the latter is scant. Here, we demonstrate that neuropeptidergic signaling is necessary for line attractor dynamics in this system by using cell-type-specific CRISPR-Cas9-based gene editing combined with single-cell calcium imaging. Co-disruption of receptors for oxytocin and vasopressin in adult VMH Esr1+ neurons that control aggression diminished attack, reduced persistent neural activity, and eliminated line attractor dynamics while only slightly reducing overall neural activity and sex- or behavior-specific tuning. These data identify a requisite role for neuropeptidergic signaling in implementing a behaviorally relevant line attractor in mammals. Our approach should facilitate mechanistic studies in neuroscience that bridge different levels of biological function and abstraction.

Two-photon all-optical neurophysiology for the dissection of larval zebrafish brain functional and effective connectivity

One of the most audacious goals of modern neuroscience is unraveling the complex web of causal relations underlying the activity of neuronal populations on a whole-brain scale. This endeavor, which was prohibitive only a couple of decades ago, has recently become within reach owing to the advancements in optical methods and the advent of genetically encoded indicators/actuators. These techniques, applied to the translucent larval zebrafish have enabled recording and manipulation of the activity of extensive neuronal populations spanning the entire vertebrate brain. Here, we present a custom two-photon optical system that couples light-sheet imaging and 3D excitation with acousto-optic deflectors for simultaneous high-speed volumetric recording and optogenetic stimulation. By employing a zebrafish line with pan-neuronal expression of both the calcium reporter GCaMP6s and the red-shifted opsin ReaChR, we implemented a crosstalk-free, noninvasive all-optical approach and applied it to reconstruct the functional and effective connectivity of the left habenula.

A small population of stress-responsive neurons in the hypothalamus-habenula circuit mediates development of depression-like behavior in mice

Accumulating evidence has shown that various brain functions are associated with experience-activated neuronal ensembles. However, whether such neuronal ensembles are engaged in the pathogenesis of stress-induced depression remains elusive. Utilizing activity-dependent viral strategies in mice, we identified a small population of stress-responsive neurons, primarily located in the middle part of the lateral hypothalamus (mLH) and the medial part of the lateral habenula (LHbM). These neurons serve as "starter cells" to transmit stress-related information and mediate the development of depression-like behaviors during chronic stress. Starter cells in the mLH and LHbM form dominant connections, which are selectively potentiated by chronic stress. Silencing these connections during chronic stress prevents the development of depression-like behaviors, whereas activating these connections directly elicits depression-like behaviors without stress experience. Collectively, our findings dissect a core functional unit within the LH-LHb circuit that mediates the development of depression-like behaviors in mice.

Emotional contagion builds resilience

Mice that witness cage mates in distress withstand future negative emotions better.

Brain-wide circuitry underlying altered auditory habituation in zebrafish models of autism

Auditory processing is widely understood to occur differently in autism, though the patterns of brain activity underlying these differences are not well understood. The diversity of autism also means brain-wide networks may change in various ways to produce similar behavioral outputs. We used larval zebrafish to investigate auditory habituation in four genetic lines relevant to autism: fmr1, mecp2, scn1lab and cntnap2. In free-swimming behavioral tests, we found each line had a unique profile of auditory hypersensitivity and/or delayed habituation. Combining the optical transparency of larval zebrafish with genetically encoded calcium indicators and light-sheet microscopy, we then observed brain-wide activity at cellular resolution during auditory habituation. As with behavior, each line showed unique alterations in brain-wide spontaneous activity, auditory processing, and adaptation in response to repetitive acoustic stimuli. We also observed commonalities in activity across our genetic lines that indicate shared circuit changes underlying certain aspects of their behavioral phenotypes. These were predominantly in regions involved in sensory integration and sensorimotor gating rather than primary auditory areas. Overlapping phenotypes include differences in the activity and functional connectivity of the telencephalon, thalamus, dopaminergic regions, and the locus coeruleus, and excitatory/inhibitory imbalance in the cerebellum. Unique phenotypes include loss of activity in the habenula in scn1lab, increased activity in auditory regions in fmr1, and differences in network activity over time in mecp2 and cntnap2. Comparing these distinct but overlapping brain-wide auditory networks furthers our understanding of how diverse genetic factors can produce similar behavioral effects through a range of circuit- and network-scale mechanisms.

The lateral habenula integrates age and experience to promote social transitions in developing rats

Early caregiving adversity (ECA) is associated with social behavior deficits and later development of psychopathology. However, the infant neural substrates of ECA are poorly understood. The lateral habenula (LHb), a highly conserved brain region with consistent links to adult psychopathology, is understudied in development, when the brain is most vulnerable to environmental impacts. Here, we describe the structural and functional ontogeny of the LHb and its behavioral role in infant and juvenile rat pups. We show that the LHb promotes a developmental transition in social approach behavior under threat as typically reared infants mature. By contrast, we show that ECA disrupts habenular ontogeny, including volume, protein expression, firing properties, and corticohabenular connectivity. Furthermore, inhibiting a specific corticohabenular projection rescues infant social approach deficits following ECA. Together, these results identify immediate biomarkers of ECA in the LHb and highlight this region as a site of early social processing and behavior control.

The behavioral relevance of a modular organization in the lateral habenula

Behavioral strategies for survival rely on the updates the brain continuously makes based on the surrounding environment. External stimuli-neutral, positive, and negative-relay core information to the brain, where a complex anatomical network rapidly organizes actions, including approach or escape, and regulates emotions. Human neuroimaging and physiology in nonhuman primates, rodents, and teleosts suggest a pivotal role of the lateral habenula in translating external information into survival behaviors. Here, we review the literature describing how discrete habenular modules-reflecting the molecular signatures, anatomical connectivity, and functional components-are recruited by environmental stimuli and cooperate to prompt specific behavioral outcomes. We argue that integration of these findings in the context of valence processing for reinforcing or discouraging behaviors is necessary, offering a compelling model to guide future work.

Brain region-specific action of ketamine as a rapid antidepressant

Ketamine has been found to have rapid and potent antidepressant activity. However, despite the ubiquitous brain expression of its molecular target, the N-methyl-d-aspartate receptor (NMDAR), it was not clear whether there is a selective, primary site for ketamine's antidepressant action. We found that ketamine injection in depressive-like mice specifically blocks NMDARs in lateral habenular (LHb) neurons, but not in hippocampal pyramidal neurons. This regional specificity depended on the use-dependent nature of ketamine as a channel blocker, local neural activity, and the extrasynaptic reservoir pool size of NMDARs. Activating hippocampal or inactivating LHb neurons swapped their ketamine sensitivity. Conditional knockout of NMDARs in the LHb occluded ketamine's antidepressant effects and blocked the systemic ketamine-induced elevation of serotonin and brain-derived neurotrophic factor in the hippocampus. This distinction of the primary versus secondary brain target(s) of ketamine should help with the design of more precise and efficient antidepressant treatments.

A REM-active basal ganglia circuit that regulates anxiety

Rapid eye movement (REM) sleep has been hypothesized to promote emotional resilience, but any neuronal circuits mediating this have not been identified. We find that in mice, somatostatin (Som) neurons in the entopeduncular nucleus (EPSom)/internal globus pallidus are predominantly active during REM sleep. This unique REM activity is both necessary and sufficient for maintaining normal REM sleep. Inhibiting or exciting EPSom neurons reduced or increased REM sleep duration, respectively. Activation of the sole downstream target of EPSom neurons, Vglut2 cells in the lateral habenula (LHb), increased sleep via the ventral tegmental area (VTA). A simple chemogenetic scheme to periodically inhibit the LHb over 4 days selectively removed a significant amount of cumulative REM sleep. Chronic, but not acute, REM reduction correlated with mice becoming anxious and more sensitive to aversive stimuli. Therefore, we suggest that cumulative REM sleep, in part generated by the EP → LHb → VTA circuit identified here, could contribute to stabilizing reactions to habitual aversive stimuli.

Anxiety control by astrocytes in the lateral habenula

The potential role of astrocytes in lateral habenula (LHb) in modulating anxiety was explored in this study. The habenula are a pair of small nuclei located above the thalamus, known for their involvement in punishment avoidance and anxiety. Herein, we observed an increase in theta-band oscillations of local field potentials (LFPs) in the LHb when mice were exposed to anxiety-inducing environments. Electrical stimulation of LHb at theta-band frequency promoted anxiety-like behavior. Calcium (Ca2+) levels and pH in the cytosol of astrocytes and local brain blood volume changes were studied in mice expressing either a Ca2+ or a pH sensor protein specifically in astrocytes and mScarlet fluorescent protein in the blood plasma using fiber photometry. An acidification response to anxiety was observed. Photoactivation of archaerhopsin-T (ArchT), an optogenetic tool that acts as an outward proton pump, results in intracellular alkalinization. Photostimulation of LHb in astrocyte-specific ArchT-expressing mice resulted in dissipation of theta-band LFP oscillation in an anxiogenic environment and suppression of anxiety-like behavior. These findings provide evidence that LHb astrocytes modulate anxiety and may offer a new target for treatment of anxiety disorders.

The N-methyl-d-aspartate receptor hypothesis of ketamine's antidepressant action: evidence and controversies

Substantial clinical evidence has unravelled the superior antidepressant efficacy of ketamine: in comparison to traditional antidepressants targeting the monoamine systems, ketamine, as an N-methyl-d-aspartate receptor (NMDAR) antagonist, acts much faster and more potently. Surrounding the antidepressant mechanisms of ketamine, there is ample evidence supporting an NMDAR-antagonism-based hypothesis. However, alternative arguments also exist, mostly derived from the controversial clinical results of other NMDAR inhibitors. In this article, we first summarize the historical development of the NMDAR-centred hypothesis of rapid antidepressants. We then classify different NMDAR inhibitors based on their mechanisms of inhibition and evaluate preclinical as well as clinical evidence of their antidepressant effects. Finally, we critically analyse controversies and arguments surrounding ketamine's NMDAR-dependent and NMDAR-independent antidepressant action. A better understanding of ketamine's molecular targets and antidepressant mechanisms should shed light on the future development of better treatment for depression. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

A multi-region recurrent circuit for evidence accumulation in rats

Decision-making based on noisy evidence requires accumulating evidence and categorizing it to form a choice. Here we evaluate a proposed feedforward and modular mapping of this process in rats: evidence accumulated in anterodorsal striatum (ADS) is categorized in prefrontal cortex (frontal orienting fields, FOF). Contrary to this, we show that both regions appear to be indistinguishable in their encoding/decoding of accumulator value and communicate this information bidirectionally. Consistent with a role for FOF in accumulation, silencing FOF to ADS projections impacted behavior throughout the accumulation period, even while nonselective FOF silencing did not. We synthesize these findings into a multi-region recurrent neural network trained with a novel approach. In-silico experiments reveal that multiple scales of recurrence in the cortico-striatal circuit rescue computation upon nonselective FOF perturbations. These results suggest that ADS and FOF accumulate evidence in a recurrent and distributed manner, yielding redundant representations and robustness to certain perturbations.

HCN channels in the lateral habenula regulate pain and comorbid depressive-like behaviors in mice

AIMS

Comorbid anxiodepressive-like symptoms (CADS) in chronic pain are closely related to the overactivation of the lateral habenula (LHb). Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels have been implicated to play a key role in regulating neuronal excitability. However, the role of HCN channels in the LHb during CADS has not yet been characterized. This study aimed to investigate the effect of HCN channels in the LHb on CADS during chronic pain.

METHODS

After chronic neuropathic pain induction by spared nerve injury (SNI), mice underwent a sucrose preference test, forced swimming test, tail suspension test, open-field test, and elevated plus maze test to evaluate their anxiodepressive-like behaviors. Electrophysiological recordings, immunohistochemistry, Western blotting, pharmacological experiments, and virus knockdown strategies were used to investigate the underlying mechanisms.

RESULTS

Evident anxiodepressive-like behaviors were observed 6w after the SNI surgery, accompanied by increased neuronal excitability, enhanced HCN channel function, and increased expression of HCN2 isoforms in the LHb. Either pharmacological inhibition or virus knockdown of HCN2 channels significantly reduced LHb neuronal excitability and ameliorated both pain and depressive-like behaviors.

CONCLUSION

Our results indicated that the LHb neurons were hyperactive under CADS in chronic pain, and this hyperactivation possibly resulted from the enhanced function of HCN channels and up-regulation of HCN2 isoforms.

Glutamatergic supramammillary nucleus neurons respond to threatening stressors and promote active coping

Threat-response neural circuits are conserved across species and play roles in normal behavior and psychiatric diseases. Maladaptive changes in these neural circuits contribute to stress, mood, and anxiety disorders. Active coping in response to stressors is a psychosocial factor associated with resilience against stress-induced mood and anxiety disorders. The neural circuitry underlying active coping is poorly understood, but the functioning of these circuits could be key for overcoming anxiety and related disorders. The supramammillary nucleus (SuM) has been suggested to be engaged by threat. SuM has many projections and a poorly understood diversity of neural populations. In studies using mice, we identified a unique population of glutamatergic SuM neurons (SuMVGLUT2+::POA) based on projection to the preoptic area of the hypothalamus (POA) and found SuMVGLUT2+::POA neurons have extensive arborizations. SuMVGLUT2+::POA neurons project to brain areas that mediate features of the stress and threat responses including the paraventricular nucleus thalamus (PVT), periaqueductal gray (PAG), and habenula (Hb). Thus, SuMVGLUT2+::POA neurons are positioned as a hub, connecting to areas implicated in regulating stress responses. Here we report SuMVGLUT2+::POA neurons are recruited by diverse threatening stressors, and recruitment correlated with active coping behaviors. We found that selective photoactivation of the SuMVGLUT2+::POA population drove aversion but not anxiety like behaviors. Activation of SuMVGLUT2+::POA neurons in the absence of acute stressors evoked active coping like behaviors and drove instrumental behavior. Also, activation of SuMVGLUT2+::POA neurons was sufficient to convert passive coping strategies to active behaviors during acute stress. In contrast, we found activation of GABAergic (VGAT+) SuM neurons (SuMVGAT+) neurons did not alter drive aversion or active coping, but termination of photostimulation was followed by increased mobility in the forced swim test. These findings establish a new node in stress response circuitry that has projections to many brain areas and evokes flexible active coping behaviors.

The lateral habenula: A hub for value-guided behavior

The habenula is an evolutionarily highly conserved diencephalic brain region divided into two major parts, medial and lateral. Over the past two decades, studies of the lateral habenula (LHb), in particular, have identified key functions in value-guided behavior in health and disease. In this review, we focus on recent insights into LHb connectivity and its functional relevance for different types of aversive and appetitive value-guided behavior. First, we give an overview of the anatomical organization of the LHb and its main cellular composition. Next, we elaborate on how distinct LHb neuronal subpopulations encode aversive and appetitive stimuli and on their involvement in more complex decision-making processes. Finally, we scrutinize the afferent and efferent connections of the LHb and discuss their functional implications for LHb-dependent behavior. A deepened understanding of distinct LHb circuit components will substantially contribute to our knowledge of value-guided behavior.

Whole-brain connections of glutamatergic neurons in the mouse lateral habenula in both sexes

BACKGROUND

The lateral habenula (LHb) is an epithalamus nucleus that is evolutionarily conserved and involved in various physiological functions, such as encoding value signals, integrating emotional information, and regulating related behaviors. The cells in the LHb are predominantly glutamatergic and have heterogeneous functions in response to different stimuli. The circuitry connections of the LHb glutamatergic neurons play a crucial role in integrating a wide range of events. However, the circuitry connections of LHb glutamatergic neurons in both sexes have not been thoroughly investigated.

METHODS

In this study, we injected Cre-dependent retrograde trace virus and anterograde synaptophysin-labeling virus into the LHb of adult male and female Vglut2-ires-Cre mice, respectively. We then quantitatively analyzed the input and output of the LHb glutamatergic connections in both the ipsilateral and contralateral whole brain.

RESULTS

Our findings showed that the inputs to LHbvGlut2 neurons come from more than 30 brain subregions, including the cortex, striatum, pallidum, thalamus, hypothalamus, midbrain, pons, medulla, and cerebellum with no significant differences between males and females. The outputs of LHbvGlut2 neurons targeted eight large brain regions, primarily focusing on the midbrain and pons nuclei, with distinct features in presynaptic bouton across different brain subregions. While correlation and cluster analysis revealed differences in input and collateral projection features, the input-output connection pattern of LHbvGlut2 neurons in both sexes was highly similar.

CONCLUSIONS

This study provides a systematic and comprehensive analysis of the input and output connections of LHbvGlut2 neurons in male and female mice, shedding light on the anatomical architecture of these specific cell types in the mouse LHb. This structural understanding can help guide further investigations into the complex functions of the LHb.

Input-output specific orchestration of aversive valence in lateral habenula during stress dynamics

Stress has been considered as a major risk factor for depressive disorders, triggering depression onset via inducing persistent dysfunctions in specialized brain regions and neural circuits. Among various regions across the brain, the lateral habenula (LHb) serves as a critical hub for processing aversive information during the dynamic process of stress accumulation, thus having been implicated in the pathogenesis of depression. LHb neurons integrate aversive valence conveyed by distinct upstream inputs, many of which selectively innervate the medial part (LHbM) or lateral part (LHbL) of LHb. LHb subregions also separately assign aversive valence via dissociable projections to the downstream targets in the midbrain which provides feedback loops. Despite these strides, the spatiotemporal dynamics of LHb-centric neural circuits remain elusive during the progression of depression-like state under stress. In this review, we attempt to describe a framework in which LHb orchestrates aversive valence via the input-output specific neuronal architecture. Notably, a physiological form of Hebbian plasticity in LHb under multiple stressors has been unveiled to incubate neuronal hyperactivity in an input-specific manner, which causally encodes chronic stress experience and drives depression onset. Collectively, the recent progress and future efforts in elucidating LHb circuits shed light on early interventions and circuit-specific antidepressant therapies.

High-resolution tracking of unconfined zebrafish behavior reveals stimulatory and anxiolytic effects of psilocybin

Serotonergic psychedelics are emerging therapeutics for psychiatric disorders, yet their underlying mechanisms of action in the brain remain largely elusive. Here, we developed a wide-field behavioral tracking system for larval zebrafish and investigated the effects of psilocybin, a psychedelic serotonin receptor agonist. Machine learning analyses of precise body kinematics identified latent behavioral states reflecting spontaneous exploration, visually-driven rapid swimming, and irregular swim patterns following stress exposure. Using this method, we found that acute psilocybin treatment has two behavioral effects: [i] facilitation of spontaneous exploration ("stimulatory") and [ii] prevention of irregular swim patterns following stress exposure ("anxiolytic"). These effects differed from the effect of acute SSRI treatment and were rather similar to the effect of ketamine treatment. Neural activity imaging in the dorsal raphe nucleus suggested that psilocybin inhibits serotonergic neurons by activating local GABAergic neurons, consistent with psychedelic-induced suppression of serotonergic neurons in mammals. These findings pave the way for using larval zebrafish to elucidate neural mechanisms underlying the behavioral effects of serotonergic psychedelics.

Label-free, whole-brain in vivo mapping in an adult vertebrate with third harmonic generation microscopy

Comprehensive understanding of interconnected networks within the brain requires access to high resolution information within large field of views and over time. Currently, methods that enable mapping structural changes of the entire brain in vivo are extremely limited. Third harmonic generation (THG) can resolve myelinated structures, blood vessels, and cell bodies throughout the brain without the need for any exogenous labeling. Together with deep penetration of long wavelengths, this enables in vivo brain-mapping of large fractions of the brain in small animals and over time. Here, we demonstrate that THG microscopy allows non-invasive label-free mapping of the entire brain of an adult vertebrate, Danionella dracula, which is a miniature species of cyprinid fish. We show this capability in multiple brain regions and in particular the identification of major commissural fiber bundles in the midbrain and the hindbrain. These features provide readily discernable landmarks for navigation and identification of regional-specific neuronal groups and even single neurons during in vivo experiments. We further show how this label-free technique can easily be coupled with fluorescence microscopy and used as a comparative tool for studies of other species with similar body features to Danionella, such as zebrafish (Danio rerio) and tetras (Trochilocharax ornatus). This new evidence, building on previous studies, demonstrates how small size and relative transparency, combined with the unique capabilities of THG microscopy, can enable label-free access to the entire adult vertebrate brain.

Serotonergic modulation of vigilance states in zebrafish and mice

Vigilance refers to being alertly watchful or paying sustained attention to avoid potential threats. Animals in vigilance states reduce locomotion and have an enhanced sensitivity to aversive stimuli so as to react quickly to dangers. Here we report that an unconventional 5-HT driven mechanism operating at neural circuit level which shapes the internal state underlying vigilance behavior in zebrafish and male mice. The neural signature of internal vigilance state was characterized by persistent low-frequency high-amplitude neuronal synchrony in zebrafish dorsal pallium and mice prefrontal cortex. The neuronal synchronization underlying vigilance was dependent on intense release of 5-HT induced by persistent activation of either DRN 5-HT neuron or local 5-HT axon terminals in related brain regions via activation of 5-HTR7. Thus, we identify a mechanism of vigilance behavior across species that illustrates the interplay between neuromodulators and neural circuits necessary to shape behavior states.

Neuronal ensembles: Building blocks of neural circuits

Neuronal ensembles, defined as groups of neurons displaying recurring patterns of coordinated activity, represent an intermediate functional level between individual neurons and brain areas. Novel methods to measure and optically manipulate the activity of neuronal populations have provided evidence of ensembles in the neocortex and hippocampus. Ensembles can be activated intrinsically or in response to sensory stimuli and play a causal role in perception and behavior. Here we review ensemble phenomenology, developmental origin, biophysical and synaptic mechanisms, and potential functional roles across different brain areas and species, including humans. As modular units of neural circuits, ensembles could provide a mechanistic underpinning of fundamental brain processes, including neural coding, motor planning, decision-making, learning, and adaptability.

Improving depression-like behaviors caused by diabetes is likely to offer a new perspective for the treatment of non-healing chronic wounds

Background

Three phases are often involved in the intricate process of wound healing: inflammatory exudation, cell proliferation, and tissue remodeling. It is challenging for wounds to heal if conditions like ischemia, persistent pressure, infection, repetitive trauma, or systemic or localized illnesses arise during the healing process. Chronic wounds are persistent injuries that do not follow the normal healing process and fail to progress through the stages of healing within a reasonable timeframe, like diabetic ulcers, vascular ulcers, pressure sores, and infectious wounds. Various factors affect chronic wound healing. A large body of research has illuminated that psychological distress may often be related to wound healing in clinical settings. Our observations have indicated that the pace of wound healing in diabetic mice is generally slower than that of healthy mice, and mice induced by streptozotocin (STZ) and fed a high-fat diet generally exhibit depression-like behavior. Our experiment delves into whether there is an inherent correlation and provides new ideas for clinical treatment to promote wound healing.

Methods

In order to explore the relationship between diabetes, depression, and wound healing, we observed wound healing through HE staining, Masson's trichrome staining, and IHC staining for CD31 and detected the depressive condition through behavioral tests. Then, RT-PCR was used to detect the mRNA expression levels of α-SMA, Col1, CD31, and VEGF in wound tissue. Finally, the related brain areas were regulated through chemical genetic methods and the process of wound healing was observed.

Conclusion

It has been observed that the lateral habenula (LHb) areas are associated with depression-like behavior induced by diabetes. Inhibiting LHb neuronal activity mitigates these depressive symptoms and enhances wound healing. Refractory wounds can be improved by considering patients' emotional issues from a broad standpoint, which provides fresh concepts for potential clinical treatments in the future.

Habenular functional connections are associated with depression state and modulated by ketamine

BACKGROUND

Depression is a widespread mental health disorder with complex neurobiological underpinnings. The habenula, known as the 'anti-reward center', is thought to play a pivotal role in the pathophysiology of depression. This study aims to elucidate the association between the functional connections of the habenula and depression severity and to explore the modulation of these connections by ketamine.

METHODS

We studied 177 participants from a 7-T resting-state functional magnetic resonance imaging subset of the Human Connectome Project dataset to determine the associations between the functional connections of the habenula and depression. Additionally, we analyzed 60 depressed patients from our ketamine database to conduct a preliminary study on alterations in the functional connections of the habenula after ketamine infusions. We also investigated whether the baseline functional connectivity of the habenula is linked to subsequent improvement in depression.

RESULTS

We found that functional connections between the habenula and the substantia nigra, as well as the ventral tegmental area were negatively correlated with depression scores and elevated after ketamine infusions. Furthermore, the connection between the right habenula and the right substantia nigra was negatively associated with the improvement of depression.

LIMITATIONS

The Human Connectome Project dataset primarily consists of data from healthy participants, with varying levels of depression scores.

CONCLUSION

These results suggest that the habenula may facilitate depression by suppressing dopamine reward centers, and ketamine may relieve depression by disinhibiting these dopaminergic regions. This study may enhance our understanding of the neural underpinnings of depression and ketamine's antidepressant effects.

The lateral habenula integrates age and experience to promote social transitions in developing rats

Social behavior deficits are an early-emerging marker of psychopathology and are linked with early caregiving quality. However, the infant neural substrates linking early care to social development are poorly understood. Here, we focused on the infant lateral habenula (LHb), a highly-conserved brain region at the nexus between forebrain and monoaminergic circuits. Despite its consistent links to adult psychopathology, this brain region has been understudied in development when the brain is most vulnerable to environmental impacts. In a task combining social and threat cues, suppressing LHb principal neurons had opposing effects in infants versus juveniles, suggesting the LHb promotes a developmental switch in social approach behavior under threat. We observed that early caregiving adversity (ECA) disrupts typical growth curves of LHb baseline structure and function, including volume, firing patterns, neuromodulatory receptor expression, and functional connectivity with cortical regions. Further, we observed that suppressing cortical projections to the LHb rescued social approach deficits following ECA, identifying this microcircuit as a substrate for disrupted social behavior. Together, these results identify immediate biomarkers of ECA in the LHb and highlight this region as a site of early social processing and behavior control.

Functional hierarchies in brain dynamics characterized by signal reversibility in ferret cortex

Brain signal irreversibility has been shown to be a promising approach to study neural dynamics. Nevertheless, the relation with cortical hierarchy and the influence of different electrophysiological features is not completely understood. In this study, we recorded local field potentials (LFPs) during spontaneous behavior, including awake and sleep periods, using custom micro-electrocorticographic (μECoG) arrays implanted in ferrets. In contrast to humans, ferrets remain less time in each state across the sleep-wake cycle. We deployed a diverse set of metrics in order to measure the levels of complexity of the different behavioral states. In particular, brain irreversibility, which is a signature of non-equilibrium dynamics, captured by the arrow of time of the signal, revealed the hierarchical organization of the ferret's cortex. We found different signatures of irreversibility and functional hierarchy of large-scale dynamics in three different brain states (active awake, quiet awake, and deep sleep), showing a lower level of irreversibility in the deep sleep stage, compared to the other. Irreversibility also allowed us to disentangle the influence of different cortical areas and frequency bands in this process, showing a predominance of the parietal cortex and the theta band. Furthermore, when inspecting the embedded dynamic through a Hidden Markov Model, the deep sleep stage was revealed to have a lower switching rate and lower entropy production. These results suggest functional hierarchies in organization that can be revealed through thermodynamic features and information theory metrics.

Neurotoxicity of the Cu(OH)2 Nanopesticide through Perturbing Multiple Neurotransmitter Pathways in Developing Zebrafish

The copper hydroxide [Cu(OH)2] nanopesticide is an emerging agricultural chemical that can negatively impact aquatic organisms. This study evaluated the behavioral changes of zebrafish larvae exposed to the Cu(OH)2 nanopesticide and assessed its potential to induce neurotoxicity. Metabolomic and transcriptomic profiling was also conducted to uncover the molecular mechanisms related to potential neurotoxicity. The Cu(OH)2 nanopesticide at 100 μg/L induced zebrafish hypoactivity, dark avoidance, and response to the light stimulus, suggestive of neurotoxic effects. Altered neurotransmitter-related pathways (serotoninergic, dopaminergic, glutamatergic, GABAergic) and reduction of serotonin (5-HT), dopamine (DA), glutamate (GLU), γ-aminobutyric acid (GABA), and several of their precursors and metabolites were noted following metabolomic and transcriptomic analyses. Differentially expressed genes (DEGs) were associated with the synthesis, transport, receptor binding, and metabolism of 5-HT, DA, GLU, and GABA. Transcripts (or protein levels) related to neurotransmitter receptors for 5-HT, DA, GLU, and GABA and enzymes for the synthesis of GLU and GABA were downregulated. Effects on both the glutamatergic and GABAergic pathways in zebrafish were specific to the nanopesticide and differed from those in fish exposed to copper ions. Taken together, the Cu(OH)2 nanopesticide induced developmental neurotoxicity in zebrafish by inhibiting several neurotransmitter-related pathways. This study presented a model for Cu(OH)2 nanopesticide-induced neurotoxicity in developing zebrafish that can inform ecological risk assessments.

Neuropeptide Signaling is Required to Implement a Line Attractor Encoding a Persistent Internal Behavioral State

Internal states drive survival behaviors, but their neural implementation is not well understood. Recently we identified a line attractor in the ventromedial hypothalamus (VMH) that represents an internal state of aggressiveness. Line attractors can be implemented by recurrent connectivity and/or neuromodulatory signaling, but evidence for the latter is scant. Here we show that neuropeptidergic signaling is necessary for line attractor dynamics in this system, using a novel approach that integrates cell type-specific, anatomically restricted CRISPR/Cas9-based gene editing with microendoscopic calcium imaging. Co-disruption of receptors for oxytocin and vasopressin in adult VMH Esr1 + neurons that control aggression suppressed attack, reduced persistent neural activity and eliminated line attractor dynamics, while only modestly impacting neural activity and sex- or behavior-tuning. These data identify a requisite role for neuropeptidergic signaling in implementing a behaviorally relevant line attractor. Our approach should facilitate mechanistic studies in neuroscience that bridge different levels of biological function and abstraction.

Zebrafish brain atlases: a collective effort for a tiny vertebrate brain

In the past two decades, digital brain atlases have emerged as essential tools for sharing and integrating complex neuroscience datasets. Concurrently, the larval zebrafish has become a prominent vertebrate model offering a strategic compromise for brain size, complexity, transparency, optogenetic access, and behavior. We provide a brief overview of digital atlases recently developed for the larval zebrafish brain, intersecting neuroanatomical information, gene expression patterns, and connectivity. These atlases are becoming pivotal by centralizing large datasets while supporting the generation of circuit hypotheses as functional measurements can be registered into an atlas' standard coordinate system to interrogate its structural database. As challenges persist in mapping neural circuits and incorporating functional measurements into zebrafish atlases, we emphasize the importance of collaborative efforts and standardized protocols to expand these resources to crack the complex codes of neuronal activity guiding behavior in this tiny vertebrate brain.

Sustained antidepressant effect of ketamine through NMDAR trapping in the LHb

Ketamine, an N-methyl-D-aspartate receptor (NMDAR) antagonist1, has revolutionized the treatment of depression because of its potent, rapid and sustained antidepressant effects2-4. Although the elimination half-life of ketamine is only 13 min in mice5, its antidepressant activities can last for at least 24 h6-9. This large discrepancy poses an interesting basic biological question and has strong clinical implications. Here we demonstrate that after a single systemic injection, ketamine continues to suppress burst firing and block NMDARs in the lateral habenula (LHb) for up to 24 h. This long inhibition of NMDARs is not due to endocytosis but depends on the use-dependent trapping of ketamine in NMDARs. The rate of untrapping is regulated by neural activity. Harnessing the dynamic equilibrium of ketamine-NMDAR interactions by activating the LHb and opening local NMDARs at different plasma ketamine concentrations, we were able to either shorten or prolong the antidepressant effects of ketamine in vivo. These results provide new insights into the causal mechanisms of the sustained antidepressant effects of ketamine. The ability to modulate the duration of ketamine action based on the biophysical properties of ketamine-NMDAR interactions opens up new opportunities for the therapeutic use of ketamine.

Teleosts as behaviour test models for social stress

Stress is an important aspect of our everyday life and exposure to it is an unavoidable occurrence. In humans, this can come in the form of social stress or physical stress from an injury. Studies in animal models have helped researchers to understand the body's adaptive response to stress in human. Notably, the use of behavioural tests in animal models plays a pivotal role in understanding the neural, endocrine and behavioural changes induced by social stress. Under socially stressed conditions, behavioural parameters are often measured physiological and molecular parameters as changes in behaviour are direct responses to stress and are easily assessed by behavioural tests. Throughout the past few decades, the rodent model has been used as a well-established animal model for stress and behavioural changes. Recently, more attention has been drawn towards using fish as an animal model. Common fish models such as zebrafish, medaka, and African cichlids have the advantage of a higher rate of reproduction, easier handling techniques, sociability and most importantly, share evolutionary conserved genetic make-up, neural circuitry, neuropeptide molecular structure and function with mammalian species. In fact, some fish species exhibit a clear diurnal or seasonal rhythmicity in their stress response, similar to humans, as opposed to rodents. Various social stress models have been established in fish including but not limited to chronic social defeat stress, social stress avoidance, and social stress-related decision-making. The huge variety of behavioural patterns in teleost also aids in the study of more behavioural phenotypes than the mammalian species. In this review, we focus on the use of fish models as alternative models to study the effects of stress on different types of behaviours. Finally, fish behavioural tests against the typical mammalian model-based behavioural test are compared and discussed for their viability.

Network models to enhance the translational impact of cross-species studies

Neuroscience studies are often carried out in animal models for the purpose of understanding specific aspects of the human condition. However, the translation of findings across species remains a substantial challenge. Network science approaches can enhance the translational impact of cross-species studies by providing a means of mapping small-scale cellular processes identified in animal model studies to larger-scale inter-regional circuits observed in humans. In this Review, we highlight the contributions of network science approaches to the development of cross-species translational research in neuroscience. We lay the foundation for our discussion by exploring the objectives of cross-species translational models. We then discuss how the development of new tools that enable the acquisition of whole-brain data in animal models with cellular resolution provides unprecedented opportunity for cross-species applications of network science approaches for understanding large-scale brain networks. We describe how these tools may support the translation of findings across species and imaging modalities and highlight future opportunities. Our overarching goal is to illustrate how the application of network science tools across human and animal model studies could deepen insight into the neurobiology that underlies phenomena observed with non-invasive neuroimaging methods and could simultaneously further our ability to translate findings across species.

From single-neuron dynamics to higher-order circuit motifs in control and pathological brain networks

The convergence of advanced single-cell in vivo functional imaging techniques, computational modelling tools and graph-based network analytics has heralded new opportunities to study single-cell dynamics across large-scale networks, providing novel insights into principles of brain communication and pointing towards potential new strategies for treating neurological disorders. A major recent finding has been the identification of unusually richly connected hub cells that have capacity to synchronize networks and may also be critical in network dysfunction. While hub neurons are traditionally defined by measures that consider solely the number and strength of connections, novel higher-order graph analytics now enables the mining of massive networks for repeating subgraph patterns called motifs. As an illustration of the power offered by higher-order analysis of neuronal networks, we highlight how recent methodological advances uncovered a new functional cell type, the superhub, that is predicted to play a major role in regulating network dynamics. Finally, we discuss open questions that will be critical for assessing the importance of higher-order cellular-scale network analytics in understanding brain function in health and disease.

A scalable implementation of the recursive least-squares algorithm for training spiking neural networks

Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a popular way to study computations performed by the nervous system. As the size and complexity of neural recordings increase, there is a need for efficient algorithms that can train models in a short period of time using minimal resources. We present optimized CPU and GPU implementations of the recursive least-squares algorithm in spiking neural networks. The GPU implementation can train networks of one million neurons, with 100 million plastic synapses and a billion static synapses, about 1,000 times faster than an unoptimized reference CPU implementation. We demonstrate the code's utility by training a network, in less than an hour, to reproduce the activity of > 66, 000 recorded neurons of a mouse performing a decision-making task. The fast implementation enables a more interactive in-silico study of the dynamics and connectivity underlying multi-area computations. It also admits the possibility to train models as in-vivo experiments are being conducted, thus closing the loop between modeling and experiments.

Larval zebrafish as a model for studying individual variability in translational neuroscience research

The larval zebrafish is a popular model for translational research into neurological and psychiatric disorders due to its conserved vertebrate brain structures, ease of genetic and experimental manipulation and small size and scalability to large numbers. The possibility of obtaining in vivo whole-brain cellular resolution neural data is contributing important advances into our understanding of neural circuit function and their relation to behavior. Here we argue that the larval zebrafish is ideally poised to push our understanding of how neural circuit function relates to behavior to the next level by including considerations of individual differences. Understanding variability across individuals is particularly relevant for tackling the variable presentations that neuropsychiatric conditions frequently show, and it is equally elemental if we are to achieve personalized medicine in the future. We provide a blueprint for investigating variability by covering examples from humans and other model organisms as well as existing examples from larval zebrafish. We highlight recent studies where variability may be hiding in plain sight and suggest how future studies can take advantage of existing paradigms for further exploring individual variability. We conclude with an outlook on how the field can harness the unique strengths of the zebrafish model to advance this important impending translational question.

Imaging Approaches to Investigate Pathophysiological Mechanisms of Brain Disease in Zebrafish

Zebrafish has become an essential model organism in modern biomedical research. Owing to its distinctive features and high grade of genomic homology with humans, it is increasingly employed to model diverse neurological disorders, both through genetic and pharmacological intervention. The use of this vertebrate model has recently enhanced research efforts, both in the optical technology and in the bioengineering fields, aiming at developing novel tools for high spatiotemporal resolution imaging. Indeed, the ever-increasing use of imaging methods, often combined with fluorescent reporters or tags, enable a unique chance for translational neuroscience research at different levels, ranging from behavior (whole-organism) to functional aspects (whole-brain) and down to structural features (cellular and subcellular). In this work, we present a review of the imaging approaches employed to investigate pathophysiological mechanisms underlying functional, structural, and behavioral alterations of human neurological diseases modeled in zebrafish.

Multisite regulation integrates multimodal context in sensory circuits to control persistent behavioral states in C. elegans

Maintaining or shifting between behavioral states according to context is essential for animals to implement fitness-promoting strategies. How the integration of internal state, past experience and sensory inputs orchestrates persistent multidimensional behavioral changes remains poorly understood. Here, we show that C. elegans integrates environmental temperature and food availability over different timescales to engage in persistent dwelling, scanning, global or glocal search strategies matching thermoregulatory and feeding needs. Transition between states, in each case, involves regulating multiple processes including AFD or FLP tonic sensory neurons activity, neuropeptide expression and downstream circuit responsiveness. State-specific FLP-6 or FLP-5 neuropeptide signaling acts on a distributed set of inhibitory GPCR(s) to promote scanning or glocal search, respectively, bypassing dopamine and glutamate-dependent behavioral state control. Integration of multimodal context via multisite regulation in sensory circuits might represent a conserved regulatory logic for a flexible prioritization on the valence of multiple inputs when operating persistent behavioral state transitions.

Distributing task-related neural activity across a cortical network through task-independent connections

Task-related neural activity is widespread across populations of neurons during goal-directed behaviors. However, little is known about the synaptic reorganization and circuit mechanisms that lead to broad activity changes. Here we trained a subset of neurons in a spiking network with strong synaptic interactions to reproduce the activity of neurons in the motor cortex during a decision-making task. Task-related activity, resembling the neural data, emerged across the network, even in the untrained neurons. Analysis of trained networks showed that strong untrained synapses, which were independent of the task and determined the dynamical state of the network, mediated the spread of task-related activity. Optogenetic perturbations suggest that the motor cortex is strongly-coupled, supporting the applicability of the mechanism to cortical networks. Our results reveal a cortical mechanism that facilitates distributed representations of task-variables by spreading the activity from a subset of plastic neurons to the entire network through task-independent strong synapses.

Whole-brain imaging of freely-moving zebrafish

One of the holy grails of neuroscience is to record the activity of every neuron in the brain while an animal moves freely and performs complex behavioral tasks. While important steps forward have been taken recently in large-scale neural recording in rodent models, single neuron resolution across the entire mammalian brain remains elusive. In contrast the larval zebrafish offers great promise in this regard. Zebrafish are a vertebrate model with substantial homology to the mammalian brain, but their transparency allows whole-brain recordings of genetically-encoded fluorescent indicators at single-neuron resolution using optical microscopy techniques. Furthermore zebrafish begin to show a complex repertoire of natural behavior from an early age, including hunting small, fast-moving prey using visual cues. Until recently work to address the neural bases of these behaviors mostly relied on assays where the fish was immobilized under the microscope objective, and stimuli such as prey were presented virtually. However significant progress has recently been made in developing brain imaging techniques for zebrafish which are not immobilized. Here we discuss recent advances, focusing particularly on techniques based on light-field microscopy. We also draw attention to several important outstanding issues which remain to be addressed to increase the ecological validity of the results obtained.

Subcortical serotonin 5HT2c receptor-containing neurons sex-specifically regulate binge-like alcohol consumption, social, and arousal behaviors in mice

Binge alcohol consumption induces discrete social and arousal disturbances in human populations that promote increased drinking and accelerate the progression of Alcohol Use Disorder. Here, we show in a mouse model that binge alcohol consumption disrupts social recognition in females and potentiates sensorimotor arousal in males. These negative behavioral outcomes were associated with sex-specific adaptations in serotonergic signaling systems within the lateral habenula (LHb) and the bed nucleus of the stria terminalis (BNST), particularly those related to the receptor 5HT2c. While both BNST and LHb neurons expressing this receptor display potentiated activation following binge alcohol consumption, the primary causal mechanism underlying the effects of alcohol on social and arousal behaviors appears to be excessive activation of LHb5HT2c neurons. These findings may have valuable implications for the development of sex-specific treatments for mood and alcohol use disorders targeting the brain's serotonin system.

Expressive architectures enhance interpretability of dynamics-based neural population models

Artificial neural networks that can recover latent dynamics from recorded neural activity may provide a powerful avenue for identifying and interpreting the dynamical motifs underlying biological computation. Given that neural variance alone does not uniquely determine a latent dynamical system, interpretable architectures should prioritize accurate and low-dimensional latent dynamics. In this work, we evaluated the performance of sequential autoencoders (SAEs) in recovering latent chaotic attractors from simulated neural datasets. We found that SAEs with widely-used recurrent neural network (RNN)-based dynamics were unable to infer accurate firing rates at the true latent state dimensionality, and that larger RNNs relied upon dynamical features not present in the data. On the other hand, SAEs with neural ordinary differential equation (NODE)-based dynamics inferred accurate rates at the true latent state dimensionality, while also recovering latent trajectories and fixed point structure. Ablations reveal that this is mainly because NODEs (1) allow use of higher-capacity multi-layer perceptrons (MLPs) to model the vector field and (2) predict the derivative rather than the next state. Decoupling the capacity of the dynamics model from its latent dimensionality enables NODEs to learn the requisite low-D dynamics where RNN cells fail. Additionally, the fact that the NODE predicts derivatives imposes a useful autoregressive prior on the latent states. The suboptimal interpretability of widely-used RNN-based dynamics may motivate substitution for alternative architectures, such as NODE, that enable learning of accurate dynamics in low-dimensional latent spaces.

Alteration of Lateral Habenula Function Prevents the Proper Exploration of a Novel Environment

The lateral habenula (LHb) is an epithalamic brain region viewed as a converging hub, integrating information from a large connectome and then projecting to few critical midbrain monoaminergic systems. Numerous studies have explored the roles of the LHb, notably in aversion and avoidance. An important recurring finding when manipulating the LHb is the induction of anxiety-related behaviours. However, its exact role in such behaviours remains poorly understood. In the present study, we used two pharmacological approaches altering LHb activity, intra-LHb infusion of either the GABA-A receptor agonist, Muscimol, or the glutamatergic AMPA receptor antagonist, 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX) and exposed rats to three consecutive open field (OF) sessions. We found that both pharmacological treatments prevented rats to explore the centre of the OF, considered as the most anxiogenic part of the apparatus, across the three OF sessions. In addition, during the first, but not the two consecutive sessions, both treatments prevented a thorough exploration of the OF. Altogether, these results confirm the crucial role played by the LHb in anxiety-related behaviours and further suggest its implication in the exploration of new anxiogenic environments.

NMDA receptors as therapeutic targets for depression treatment: Evidence from clinical to basic research

Ketamine, functioning as a channel blocker of the excitatory glutamate-gated N-methyl-d-aspartate (NMDA) receptors, displays compelling fast-acting and sustained antidepressant effects for treatment-resistant depression. Over the past decades, clinical and preclinical studies have implied that the pathology of depression is associated with dysfunction of glutamatergic transmission. In particular, the discovery of antidepressant agents modulating NMDA receptor function has prompted breakthroughs for depression treatment compared with conventional antidepressants targeting the monoaminergic system. In this review, we first summarized the signalling pathway of the ketamine-mediated antidepressant effects, based on the glutamate hypothesis of depression. Second, we reviewed the hypotheses of the synaptic mechanism and network of ketamine antidepressant effects within different brain areas and distinct subcellular localizations, including NMDA receptor antagonism on GABAergic interneurons, extrasynaptic and synaptic NMDA receptor-mediated antagonism, and ketamine blocking bursting activities in the lateral habenula. Third, we reviewed the different roles of NMDA receptor subunits in ketamine-mediated cognitive and psychiatric behaviours in genetically-manipulated rodent models. Finally, we summarized the structural basis of NMDA receptor channel blockers and discussed NMDA receptor modulators that have been reported to exert potential antidepressant effects in animal models or in clinical trials. Integrating the cutting-edge technologies of cryo-EM and artificial intelligence-based drug design (AIDD), we expect that the next generation of first-in-class rapid antidepressants targeting NMDA receptors would be an emerging direction for depression therapeutics. This article is part of the Special Issue on 'Ketamine and its Metabolites'.

Neural mechanism underlying depressive-like state associated with social status loss

Downward social mobility is a well-known mental risk factor for depression, but its neural mechanism remains elusive. Here, by forcing mice to lose against their subordinates in a non-violent social contest, we lower their social ranks stably and induce depressive-like behaviors. These rank-decline-associated depressive-like behaviors can be reversed by regaining social status. In vivo fiber photometry and single-unit electrophysiological recording show that forced loss, but not natural loss, generates negative reward prediction error (RPE). Through the lateral hypothalamus, the RPE strongly activates the brain's anti-reward center, the lateral habenula (LHb). LHb activation inhibits the medial prefrontal cortex (mPFC) that controls social competitiveness and reinforces retreats in contests. These results reveal the core neural mechanisms mutually promoting social status loss and depressive behaviors. The intertwined neuronal signaling controlling mPFC and LHb activities provides a mechanistic foundation for the crosstalk between social mobility and psychological disorder, unveiling a promising target for intervention.

tension: A Python package for FORCE learning

First-Order, Reduced and Controlled Error (FORCE) learning and its variants are widely used to train chaotic recurrent neural networks (RNNs), and outperform gradient methods on certain tasks. However, there is currently no standard software framework for FORCE learning. We present tension, an object-oriented, open-source Python package that implements a TensorFlow / Keras API for FORCE. We show how rate networks, spiking networks, and networks constrained by biological data can all be trained using a shared, easily extensible high-level API. With the same resources, our implementation outperforms a conventional RNN in loss and published FORCE implementations in runtime. Our work here makes FORCE training chaotic RNNs accessible and simple to iterate, and facilitates modeling of how behaviors of interest emerge from neural dynamics.

Controllability of Functional Brain Networks and Its Clinical Significance in First-Episode Schizophrenia

BACKGROUND AND HYPOTHESIS

Disrupted control of brain state transitions may contribute to the diverse dysfunctions of cognition, emotion, and behavior that are fundamental to schizophrenia. Control theory provides the rationale for evaluating brain state transitions from a controllability perspective, which may help reveal the brain mechanism for clinical features such as cognitive control deficits associated with schizophrenia. We hypothesized that brain controllability would be altered in patients with schizophrenia, and that controllability of brain networks would be related to clinical symptomatology.

STUDY DESIGN

Controllability measurements of functional brain networks, including average controllability and modal controllability, were calculated and compared between 125 first-episode never-treated patients with schizophrenia and 133 healthy controls (HCs). Associations between controllability metrics and clinical symptoms were evaluated using sparse canonical correlation analysis.

STUDY RESULTS

Compared to HCs, patients showed significantly increased average controllability (PFDR = .023) and decreased modal controllability (PFDR = .023) in dorsal anterior cingulate cortex (dACC). General psychopathology symptoms and positive symptoms were positively correlated with average controllability in regions of default mode network and negatively associated with average controllability in regions of sensorimotor, dorsal attention, and frontoparietal networks.

CONCLUSIONS

Our findings suggest that altered controllability of functional activity in dACC may play a critical role in the pathophysiology of schizophrenia, consistent with the importance of this region in cognitive and brain state control operations. The demonstration of associations of functional controllability with psychosis symptoms suggests that the identified alterations in average controllability of brain function may contribute to the severity of acute psychotic illness in schizophrenia.

The diverse role of the raphe 5-HTergic systems in epilepsy

The raphe nuclei comprise nearly all of 5-hydroxytryptaminergic (5-HTergic) neurons in the brain and are widely acknowledged to participate in the modulation of neural excitability. "Excitability-inhibition imbalance" results in a variety of brain disorders, including epilepsy. Epilepsy is a common neurological disorder characterized by hypersynchronous epileptic seizures accompanied by many psychological, social, cognitive consequences. Current antiepileptic drugs and other therapeutics are not ideal to control epilepsy and its comorbidities. Cumulative evidence suggests that the raphe nuclei and 5-HTergic system play an important role in epilepsy and epilepsy-associated comorbidities. Seizure activities propagate to the raphe nuclei and induce various alterations in different subregions of the raphe nuclei at the cellular and molecular levels. Intervention of the activity of raphe nuclei and raphe 5-HTergic system with pharmacological or genetic approaches, deep brain stimulation or optogenetics produces indeed diverse and even contradictory effects on seizure and epilepsy-associated comorbidities in different epilepsy models. Nevertheless, there are still many open questions left, especially regarding to the relationship between 5-HTergic neural circuit and epilepsy. Understanding of 5-HTergic network in a circuit- and molecule-specific way may not only be therapeutically relevant for increasing the drug specificity and precise treatment in epilepsy, but also provide critical hints for other brain disorders with abnormal neural excitability. In this review we focus on the roles of the raphe 5-HTergic system in epilepsy and epilepsy-associated comorbidities. Besides, further perspectives about the complexity and diversity of the raphe nuclei in epilepsy are also addressed.

Activity in a prefrontal-periaqueductal gray circuit overcomes behavioral and endocrine features of the passive coping stress response

The question of how the brain links behavioral and biological features of defensive responses has remained elusive. The importance of this problem is underscored by the observation that behavioral passivity in stress coping is associated with elevations in glucocorticoid hormones, and each may carry risks for susceptibility to a host of stress-related diseases. Past work implicates the medial prefrontal cortex (mPFC) in the top-down regulation of stress-related behaviors; however, it is unknown whether such changes have the capacity to buffer against the longer-lasting biological consequences associated with aversive experiences. Using the shock probe defensive burying test in rats to naturalistically measure behavioral and endocrine features of coping, we observed that the active behavioral component of stress coping is associated with increases in activity along a circuit involving the caudal mPFC and midbrain dorsolateral periaqueductal gray (PAG). Optogenetic manipulations of the caudal mPFC-to-dorsolateral PAG pathway bidirectionally modulated active (escape and defensive burying) behaviors, distinct from a rostral mPFC-ventrolateral PAG circuit that instead limited passive (immobility) behavior. Strikingly, under conditions that biased rats toward a passive coping response set, including exaggerated stress hormonal output and increased immobility, excitation of the caudal mPFC-dorsolateral PAG projection significantly attenuated each of these features. These results lend insight into how the brain coordinates response features to overcome passive coping and may be of importance for understanding how activated neural systems promote stress resilience.

Multiregion neuronal activity: the forest and the trees

The past decade has witnessed remarkable advances in the simultaneous measurement of neuronal activity across many brain regions, enabling fundamentally new explorations of the brain-spanning cellular dynamics that underlie sensation, cognition and action. These recently developed multiregion recording techniques have provided many experimental opportunities, but thoughtful consideration of methodological trade-offs is necessary, especially regarding field of view, temporal acquisition rate and ability to guarantee cellular resolution. When applied in concert with modern optogenetic and computational tools, multiregion recording has already made possible fundamental biological discoveries - in part via the unprecedented ability to perform unbiased neural activity screens for principles of brain function, spanning dozens of brain areas and from local to global scales.

Tonic activity in lateral habenula neurons acts as a neutral valence brake on reward-seeking behavior

Survival requires both the ability to persistently pursue goals and the ability to determine when it is time to stop, an adaptive balance of perseverance and disengagement. Neural activity in the lateral habenula (LHb) has been linked to negative valence, but its role in regulating the balance between engaged reward seeking and disengaged behavioral states remains unclear. Here, we show that LHb neural activity is tonically elevated during minutes-long periods of disengagement from reward-seeking behavior, both when due to repeated reward omission (negative valence) and when sufficient reward has been consumed (positive valence). Furthermore, we show that LHb inhibition extends ongoing reward-seeking behavioral states but does not prompt task re-engagement. We find no evidence for similar tonic activity changes in ventral tegmental area dopamine neurons. Our findings support a framework in which tonic activity in LHb neurons suppresses engagement in reward-seeking behavior in response to both negatively and positively valenced factors.