Cortical layer-specific critical dynamics triggering perception

Metaplasticity and continual learning: mechanisms subserving brain computer interface proficiency

Objective.Brain computer interfaces (BCIs) require substantial cognitive flexibility to optimize control performance. Remarkably, learning this control is rapid, suggesting it might be mediated by neuroplasticity mechanisms operating on very short time scales. Here, we propose a meta plasticity model of BCI learning and skill consolidation at the single cell and population levels comprised of three elements: (a) behavioral time scale synaptic plasticity (BTSP), (b) intrinsic plasticity (IP) and (c) synaptic scaling (SS) operating at time scales from seconds to minutes to hours and days. Notably, the model is able to explainrepresentational drift-a frequent and widespread phenomenon that adversely affects BCI control and continued use.Approach.We developed an all-optical approach to characterize IP, BTSP and SS with single cell resolution in awake mice using fluorescent two photon (2P) GCaMP7s imaging and optogenetic stimulation of the soma targeted ChRmineKv2.1. We further trained mice on a one-dimensional BCI control task and systematically characterized within session (seconds to minutes) learning as well as across sessions (days and weeks) with different neural ensembles.Main results.On the time scale of seconds, substantial BTSP could be induced and was followed by significant IP over minutes. Over the time scale of days and weeks, these changes could predict BCI control proficiency, suggesting that BTSP and IP might be complemented by SS to stabilize and consolidate BCI control.Significance.Our results provide early experimental support for a meta plasticity model of continual BCI learning and skill consolidation. The model predictions may be used to design and calibrate neural decoders with complete autonomy while considering the temporal and spatial scales of plasticity mechanisms. With the power of modern-day machine learning and artificial Intelligence, fully autonomous neural decoding and adaptation in BCIs might be achieved with minimal to no human intervention.

Dual-color optical activation and suppression of neurons with high temporal precision

A well-known phenomenon in the optogenetic toolbox is that all light-gated ion channels, including red-shifted channelrhodopsins (ChRs), are activated by blue light, whereas blue-shifted ChRs are minimally responsive to longer wavelengths. Here, we took advantage of this feature to create a system which allows high-frequency activation of neurons with pulses of red light, while permitting the suppression of action potentials (APs) with millisecond precision by blue light. We achieved this by pairing an ultrafast red-shifted ChR with a blue light-sensitive anion channel of appropriately matching kinetics. This required screening several anion-selective ChRs, followed by a model-based mutagenesis strategy to optimize their kinetics and light spectra. Slice electrophysiology in the hippocampus as well as behavioral inspection of vibrissa movement demonstrate a minimal excitation from blue light. Of significant potential value, in contrast to existing tools, the system we introduce here allows high-frequency optogenetic excitation of neurons with red light, while blue light suppression of APs is confined within the duration of the light pulse.

Network influence determines the impact of cortical ensembles on stimulus detection

Causally connecting neural activity patterns to behavioral decisions is essential to understand the neural code but requires direct perturbation of the pattern of interest with high specificity. We combined two-photon imaging and cellular-resolution holographic optogenetic photostimulation to causally test how neural activity in the mouse visual cortex is read out to detect visual stimuli. Contrary to expectations, targeted activation of visually sensitive neural ensembles did not preferentially modify behavior compared with targeting randomly selected ensembles. Instead, an activated ensemble's effect on local network activity was the main predictor of its impact on perception. This suggests that downstream regions summate visual cortex activity without preferentially weighting more informative neurons, a notion confirmed by analyzing the impact of photostimulation on decoding models of neural activity. This work challenges conventional notions for how sensory representations mediate perception and demonstrates that perturbing activity is essential to determine which features of neural activity drive behavior.

Association of Bidirectional Network Cores in the Brain with Perceptual Awareness and Cognition

The brain comprises a complex network of interacting regions. To understand the roles and mechanisms of this intricate network, it is crucial to elucidate its structural features related to cognitive functions. Recent empirical evidence suggests that both feedforward and feedback signals are necessary for conscious perception, emphasizing the importance of subnetworks with bidirectional interactions. However, the link between such subnetworks and conscious perception remains unclear due to the complexity of brain networks. In this study, we propose a framework for extracting subnetworks with strong bidirectional interactions-termed the "cores" of a network-from brain activity. We applied this framework to resting-state and task-based human fMRI data from participants of both sexes to identify regions forming strongly bidirectional cores. We then explored the association of these cores with conscious perception and cognitive functions. We found that the extracted central cores predominantly included cerebral cortical regions rather than subcortical regions. Additionally, regarding their relation to conscious perception, we demonstrated that the cores tend to include regions previously reported to be affected by electrical stimulation that altered conscious perception, although the results are not statistically robust due to the small sample size. Furthermore, in relation to cognitive functions, based on a meta-analysis and comparison of the core structure with a cortical functional connectivity gradient, we found that the central cores were related to unimodal sensorimotor functions. The proposed framework provides novel insights into the roles of network cores with strong bidirectional interactions in conscious perception and unimodal sensorimotor functions.

Mapping global brain reconfigurations following local targeted manipulations

Understanding how localized brain interventions influence whole-brain dynamics is essential for deciphering neural function and designing therapeutic strategies. Using longitudinal functional MRI datasets collected from mice, we investigated the effects of focal interventions, such as thalamic lesions and chemogenetic silencing of cortical hubs. We found that these local manipulations disrupted the brain's ability to sustain network-wide activity, leading to global functional connectivity (FC) reconfigurations. Personalized mouse brain simulations based on experimental data revealed that alterations in local excitability modulate firing rates and frequency content across distributed brain regions, driving these FC changes. Notably, the topography of the affected brain regions depended on the intervention site, serving as distinctive signatures of localized perturbations. These findings suggest that focal interventions produce consistent yet region-specific patterns of global FC reorganization, providing an explanation for the seemingly paradoxical observations of hypo- and hyperconnectivity reported in the literature. This framework offers mechanistic insights into the systemic effects of localized neural modulation and holds potential for refining clinical diagnostics in focal brain disorders and advancing personalized neuromodulation strategies.

A neural mechanism for learning from delayed postingestive feedback

Animals learn the value of foods on the basis of their postingestive effects and thereby develop aversions to foods that are toxic1-10 and preferences to those that are nutritious11-13. However, it remains unclear how the brain is able to assign credit to flavours experienced during a meal with postingestive feedback signals that can arise after a substantial delay. Here we reveal an unexpected role for the postingestive reactivation of neural flavour representations in this temporal credit-assignment process. To begin, we leverage the fact that mice learn to associate novel14,15, but not familiar, flavours with delayed gastrointestinal malaise signals to investigate how the brain represents flavours that support aversive postingestive learning. Analyses of brain-wide activation patterns reveal that a network of amygdala regions is unique in being preferentially activated by novel flavours across every stage of learning (consumption, delayed malaise and memory retrieval). By combining high-density recordings in the amygdala with optogenetic stimulation of malaise-coding hindbrain neurons, we show that delayed malaise signals selectively reactivate flavour representations in the amygdala from a recent meal. The degree of malaise-driven reactivation of individual neurons predicts the strengthening of flavour responses upon memory retrieval, which in turn leads to stabilization of the population-level representation of the recently consumed flavour. By contrast, flavour representations in the amygdala degrade in the absence of unexpected postingestive consequences. Thus, we demonstrate that postingestive reactivation and plasticity of neural flavour representations may support learning from delayed feedback.

Foundation model of neural activity predicts response to new stimulus types

The complexity of neural circuits makes it challenging to decipher the brain's algorithms of intelligence. Recent breakthroughs in deep learning have produced models that accurately simulate brain activity, enhancing our understanding of the brain's computational objectives and neural coding. However, it is difficult for such models to generalize beyond their training distribution, limiting their utility. The emergence of foundation models1 trained on vast datasets has introduced a new artificial intelligence paradigm with remarkable generalization capabilities. Here we collected large amounts of neural activity from visual cortices of multiple mice and trained a foundation model to accurately predict neuronal responses to arbitrary natural videos. This model generalized to new mice with minimal training and successfully predicted responses across various new stimulus domains, such as coherent motion and noise patterns. Beyond neural response prediction, the model also accurately predicted anatomical cell types, dendritic features and neuronal connectivity within the MICrONS functional connectomics dataset2. Our work is a crucial step towards building foundation models of the brain. As neuroscience accumulates larger, multimodal datasets, foundation models will reveal statistical regularities, enable rapid adaptation to new tasks and accelerate research.

Optogenetic engineering for ion channel modulation

Optogenetics, which integrates photonics and genetic engineering to control protein activity and cellular processes, has transformed biomedical research. Its precise spatiotemporal control, minimal invasiveness, and tunable reversibility have spurred its widespread adoption in both basic and clinical research. Optogenetic techniques have been applied to partially restore vision in blind patients and are being actively explored as innovative treatments for neurological, psychiatric, cardiac, and immunological disorders. Microbial channelrhodopsins (ChRs) allow precise manipulation of neuronal and cardiac activities, while vertebrate rhodopsins offer unique opportunities for ion channel modulation through G-protein-coupled receptor (GPCR) pathways. Plant-derived photoswitchable domains can also be engineered into ion channels to confer photosensitivity. This review summarizes the latest progress in engineering genetically encoded light-sensitive ion channel actuators and modulators (GELICAMs) with diverse ion selectivity and spectral sensitivity. We further discuss the potential applications and challenges of these tools in advancing biomedical research and therapeutic interventions.

A spherical code of retinal orientation selectivity enables decoding in ensembled and retinotopic operation

Selectivity to orientations of edges is seen at the earliest stages of visual processing in retinal orientation-selective ganglion cells (OSGCs), which are thought to prefer vertical or horizontal orientation. However, because stationary edges are projected on the hemispherical retina as lines of longitude or latitude, how edge orientation is encoded and decoded by the brain is unknown. Here, by mapping the orientation selectivity (OS) of thousands of OSGCs at known retinal locations in mice, we identify three OSGC types whose preferences match two longitudinal fields and a fourth type matching two latitudinal fields, with the members of each field pair being non-orthogonal. A geometric decoder reveals that two OS sensors yield optimal orientation decoding when approaching the deviation from orthogonality we observe for OSGC field pairs. Retinotopically organized decoding generates type-specific variation in decoding efficiency across the visual field. OS tuning is greater in the dorsal retina, possibly reflecting an evolutionary adaptation to an environmental gradient of edges.

Theoretical analysis of low-power deep synergistic sono-optogenetic excitation of neurons by co-expressing light-sensitive and mechano-sensitive ion-channels

The present challenge in neuroscience is to non-invasively exercise low-power and high-fidelity control of neurons situated deep inside the brain. Although, two-photon optogenetic excitation can activate neurons to millimeter depth with sub-cellular specificity and millisecond temporal resolution, it can also cause heating of the targeted tissue. On the other hand, sonogenetics can non-invasively modulate the cellular activity of neurons expressed with mechano-sensitive proteins in deeper areas of the brain with less spatial selectivity. We present a theoretical analysis of a synergistic sono-optogenetic method to overcome these limitations by co-expressing a mechano-sensitive (MscL-I92L) ion-channel with a light-sensitive (CoChR/ChroME2s/ChRmine) ion-channel in hippocampal neurons. It is shown that in the presence of low-amplitude subthreshold ultrasound pulses, the two-photon excitation threshold for neural spiking reduces drastically by 73% with MscL-I92L-CoChR (0.021 mW/µm2), 66% with MscL-I92L-ChroME2s (0.029 mW/µm2), and 64% with MscL-I92L-ChRmine (0.013 mW/µm2) at 5 Hz. It allows deeper excitation of up to 1.2 cm with MscL-I92L-ChRmine combination. The method is useful to design new experiments for low-power deep excitation of neurons and multimodal neuroprosthetic devices and circuits.

GABAergic neuron-to-glioma synapses in diffuse midline gliomas

High-grade gliomas (HGGs) are the leading cause of brain cancer-related death. HGGs include clinically, anatomically and molecularly distinct subtypes that stratify into diffuse midline gliomas (DMGs), such as H3K27M-altered diffuse intrinsic pontine glioma, and hemispheric HGGs, such as IDH wild-type glioblastoma. Neuronal activity drives glioma progression through paracrine signalling1,2 and neuron-to-glioma synapses3-6. Glutamatergic AMPA receptor-dependent synapses between neurons and glioma cells have been demonstrated in paediatric3 and adult4 high-grade gliomas, and early work has suggested heterogeneous glioma GABAergic responses7. However, neuron-to-glioma synapses mediated by neurotransmitters other than glutamate remain understudied. Using whole-cell patch-clamp electrophysiology, in vivo optogenetics and patient-derived orthotopic xenograft models, we identified functional, tumour-promoting GABAergic neuron-to-glioma synapses mediated by GABAA receptors in DMGs. GABAergic input has a depolarizing effect on DMG cells due to NKCC1 chloride transporter function and consequently elevated intracellular chloride concentration in DMG malignant cells. As membrane depolarization increases glioma proliferation3,6, we found that the activity of GABAergic interneurons promotes DMG proliferation in vivo. The benzodiazepine lorazepam enhances GABA-mediated signalling, increases glioma proliferation and growth, and shortens survival in DMG patient-derived orthotopic xenograft models. By contrast, only minimal depolarizing GABAergic currents were found in hemispheric HGGs and lorazepam did not influence the growth rate of hemispheric glioblastoma xenografts. Together, these findings uncover growth-promoting GABAergic synaptic communication between GABAergic neurons and H3K27M-altered DMG cells, underscoring a tumour subtype-specific mechanism of brain cancer neurophysiology.

A large field of view 2- and 3-photon microscope

A new multiphoton fluorescence microscope has been developed, offering cellular resolution across a large field of view deep within biological tissues. This opens new possibilities across a range of biological sciences, particularly within neuroscience where optical approaches can reveal signaling in real time throughout an extended network of cells distributed through the brain of an awake, behaving mouse.

Predictive filtering of sensory response via orbitofrontal top-down input

Habituation is a crucial sensory filtering mechanism whose dysregulation can lead to a continuously intense world in disorders with sensory overload. While habituation is considered to require top-down predictive signaling to suppress irrelevant inputs, the exact brain loci storing the internal predictive model and the circuit mechanisms of sensory filtering remain unclear. We found that daily neural habituation in the primary auditory cortex (A1) was reversed by inactivation of the orbitofrontal cortex (OFC). Top-down projections from the ventrolateral OFC, but not other frontal areas, carried predictive signals that grew with daily sound experience and suppressed A1 via somatostatin-expressing inhibitory neurons. Thus, prediction signals from the OFC cancel out behaviorally irrelevant anticipated stimuli by generating their "negative images" in sensory cortices.

Optogenetics and chemogenetics: key tools for modulating neural circuits in rodent models of depression

Optogenetics and chemogenetics are emerging neuromodulation techniques that have attracted significant attention in recent years. These techniques enable the precise control of specific neuronal types and neural circuits, allowing researchers to investigate the cellular mechanisms underlying depression. The advancement in these techniques has significantly contributed to the understanding of the neural circuits involved in depression; when combined with other emerging technologies, they provide novel therapeutic targets and diagnostic tools for the clinical treatment of depression. Additionally, these techniques have provided theoretical support for the development of novel antidepressants. This review primarily focuses on the application of optogenetics and chemogenetics in several brain regions closely associated with depressive-like behaviors in rodent models, such as the ventral tegmental area, nucleus accumbens, prefrontal cortex, hippocampus, dorsal raphe nucleus, and lateral habenula and discusses the potential and challenges of optogenetics and chemogenetics in future research. Furthermore, this review discusses the potential and challenges these techniques pose for future research and describes the current state of research on sonogenetics and odourgenetics developed based on optogenetics and chemogenetics. Specifically, this study aimed to provide reliable insights and directions for future research on the role of optogenetics and chemogenetics in the neural circuits of depressive rodent models.

Neuropixels Opto: Combining high-resolution electrophysiology and optogenetics

High-resolution extracellular electrophysiology is the gold standard for recording spikes from distributed neural populations, and is especially powerful when combined with optogenetics for manipulation of specific cell types with high temporal resolution. We integrated these approaches into prototype Neuropixels Opto probes, which combine electronic and photonic circuits. These devices pack 960 electrical recording sites and two sets of 14 light emitters onto a 1 cm shank, allowing spatially addressable optogenetic stimulation with blue and red light. In mouse cortex, Neuropixels Opto probes delivered high-quality recordings together with spatially addressable optogenetics, differentially activating or silencing neurons at distinct cortical depths. In mouse striatum and other deep structures, Neuropixels Opto probes delivered efficient optotagging, facilitating the identification of two cell types in parallel. Neuropixels Opto probes represent an unprecedented tool for recording, identifying, and manipulating neuronal populations.

Evolution of Light-Sensitive Proteins in Optogenetic Approaches for Vision Restoration: A Comprehensive Review

Retinal degenerations, such as age-related macular degeneration and retinitis pigmentosa, present significant challenges due to genetic heterogeneity, limited therapeutic options, and the progressive loss of photoreceptors in advanced stages. These challenges are compounded by difficulties in precisely targeting residual retinal neurons and ensuring the sustained efficacy of interventions. Optogenetics offers a novel approach to vision restoration by inducing light sensitivity in residual retinal neurons through gene delivery of light-sensitive opsins. This review traces the evolution of opsins in optogenetic therapies, highlighting advancements from early research on channelrhodopsin-2 (ChR2) to engineered variants addressing key limitations. Red-shifted opsins, including ReaChR and ChrimsonR, reduced phototoxicity by enabling activation under longer wavelengths, while Chronos introduced superior temporal kinetics for dynamic visual tracking. Further innovations, such as Multi-Characteristic Opsin 1 (MCO1), optimized opsin performance under ambient light, bridging the gap to real-world applications. Key milestones include the first partial vision restoration in a human patient using ChrimsonR with light-amplifying goggles and ongoing clinical trials exploring the efficacy of opsin-based therapies for advanced retinal degeneration. While significant progress has been made, challenges remain in achieving sufficient light sensitivity for functional vision under normal ambient lighting conditions in a manner that is both effective and safe, eliminating the need for external light-enhancing devices. As research progresses, optogenetic therapies are positioned to redefine the management of retinal degenerative diseases, offering new hope for millions affected by vision loss.

Optical Precise Ablation of Targeted Individual Neurons In Vivo

Targeted cell ablation is a powerful strategy for investigating the function of individual neurons within neuronal networks. Multiphoton ablation technology by a tightly focused femtosecond laser, with its significant advantages of noninvasiveness, high efficiency, and single-cell resolution, has been widely used in the study of neuroscience. However, the firing activity of the ablated neuron and its impact on the surrounding neurons and entire neuronal ensembles are still unclear. In this study, we describe the depolarization process of targeted neuron ablation by a femtosecond laser based on a standard two-photon microscope in vitro and in vivo. The photoporation damages the cell membrane, depolarizes the membrane potential, and thus disables the neuron's ability to fire action potentials. The dysfunctional neuron after laser ablation affects both the responses of surrounding neighbors and the functions of ensemble neurons in vivo. Although abnormal Ca2+ responses in spatially surrounding neurons are observed, the damage effect is confined to the focal volume. The function of the neuronal ensembles that associate with a specific visual stimulation is not influenced by the ablation of an individual member of the ensemble, indicating the redundancy of the ensemble organization. This study thus provides an insight into the targeted neuron ablation as well as the role of an individual neuron in an ensemble.

The neuroimmune connectome in health and disease

The nervous and immune systems have complementary roles in the adaptation of organisms to environmental changes. However, the mechanisms that mediate cross-talk between the nervous and immune systems, called neuroimmune interactions, are poorly understood. In this Review, we summarize advances in the understanding of neuroimmune communication, with a principal focus on the central nervous system (CNS): its response to immune signals and the immunological consequences of CNS activity. We highlight these themes primarily as they relate to neurological diseases, the control of immunity, and the regulation of complex behaviours. We also consider the importance and challenges linked to the study of the neuroimmune connectome, which is defined as the totality of neuroimmune interactions in the body, because this provides a conceptual framework to identify mechanisms of disease pathogenesis and therapeutic approaches. Finally, we discuss how the latest techniques can advance our understanding of the neuroimmune connectome, and highlight the outstanding questions in the field.

Exact linear theory of perturbation response in a space- and feature-dependent cortical circuit model

What are the principles that govern the responses of cortical networks to their inputs and the emergence of these responses from recurrent connectivity? Recent experiments have probed these questions by measuring cortical responses to two-photon optogenetic perturbations of single cells in the mouse primary visual cortex. A robust theoretical framework is needed to determine the implications of these responses for cortical recurrence. Here we propose a novel analytical approach: a formulation of the dependence of cell-type-specific connectivity on spatial distance that yields an exact solution for the linear perturbation response of a model with multiple cell types and space- and feature-dependent connectivity. Importantly and unlike previous approaches, the solution is valid in regimes of strong as well as weak intra-cortical coupling. Analysis reveals the structure of connectivity implied by various features of single-cell perturbation responses, such as the surprisingly narrow spatial radius of nearby excitation beyond which inhibition dominates, the number of transitions between mean excitation and inhibition thereafter, and the dependence of these responses on feature preferences. Comparison of these results to existing optogenetic perturbation data yields constraints on cell-type-specific connection strengths and their tuning dependence. Finally, we provide experimental predictions regarding the response of inhibitory neurons to single-cell perturbations and the modulation of perturbation response by neuronal gain; the latter can explain observed differences in the feature-tuning of perturbation responses in the presence vs. absence of visual stimuli.

PinkyCaMP a mScarlet-based calcium sensor with exceptional brightness, photostability, and multiplexing capabilities

Genetically encoded calcium (Ca2+) indicators (GECIs) are widely used for imaging neuronal activity, yet current limitations of existing red fluorescent GECIs have constrained their applicability. The inherently dim fluorescence and low signal-to-noise ratio of red-shifted GECIs have posed significant challenges. More critically, several red-fluorescent GECIs exhibit photoswitching when exposed to blue light, thereby limiting their applicability in all-optical experimental approaches. Here, we present the development of PinkyCaMP, the first mScarlet-based Ca2+ sensor that outperforms current red fluorescent sensors in brightness, photostability, signal-to-noise ratio, and compatibility with optogenetics and neurotransmitter imaging. PinkyCaMP is well-tolerated by neurons, showing no toxicity or aggregation, both in vitro and in vivo. All imaging approaches, including single-photon excitation methods such as fiber photometry, widefield imaging, miniscope imaging, as well as two-photon imaging in awake mice, are fully compatible with PinkyCaMP.

A spatial code for temporal information is necessary for efficient sensory learning

The temporal structure of sensory inputs contains essential information for their interpretation. Sensory cortex represents these temporal cues through two codes: the temporal sequences of neuronal activity and the spatial patterns of neuronal firing rate. However, it is unknown which of these coexisting codes causally drives sensory decisions. To separate their contributions, we generated in the mouse auditory cortex optogenetically driven activity patterns differing exclusively along their temporal or spatial dimensions. Mice could rapidly learn to behaviorally discriminate spatial but not temporal patterns. Moreover, large-scale neuronal recordings across the auditory system revealed that the auditory cortex is the first region in which spatial patterns efficiently represent temporal cues on the timescale of several hundred milliseconds. This feature is shared by the deep layers of neural networks categorizing time-varying sounds. Therefore, the emergence of a spatial code for temporal sensory cues is a necessary condition to efficiently associate temporally structured stimuli with decisions.

Association of bidirectional network cores in the brain with perceptual awareness and cognition

The brain comprises a complex network of interacting regions. To understand the roles and mechanisms of this intricate network, it is crucial to elucidate its structural features related to cognitive functions. Recent empirical evidence suggests that both feedforward and feedback signals are necessary for conscious perception, emphasizing the importance of subnetworks with bidirectional interactions. However, the link between such subnetworks and conscious perception remains unclear due to the complexity of brain networks. In this study, we propose a framework for extracting subnetworks with strong bidirectional interactions-termed the "cores" of a network-from brain activity. We applied this framework to resting-state and task-based human fMRI data from participants of both sexes to identify regions forming strongly bidirectional cores. We then explored the association of these cores with conscious perception and cognitive functions. We found that the extracted central cores predominantly included cerebral cortical regions rather than subcortical regions. Additionally, regarding their relation to conscious perception, we demonstrated that the cores tend to include regions previously reported to be affected by electrical stimulation that altered conscious perception, although the results are not statistically robust due to the small sample size. Furthermore, in relation to cognitive functions, based on a meta-analysis and comparison of the core structure with a cortical functional connectivity gradient, we found that the central cores were related to unimodal sensorimotor functions. The proposed framework provides novel insights into the roles of network cores with strong bidirectional interactions in conscious perception and unimodal sensorimotor functions.

Stress disrupts engram ensembles in lateral amygdala to generalize threat memory in mice

Stress induces aversive memory overgeneralization, a hallmark of many psychiatric disorders. Memories are encoded by a sparse ensemble of neurons active during an event (an engram ensemble). We examined the molecular and circuit processes mediating stress-induced threat memory overgeneralization in mice. Stress, acting via corticosterone, increased the density of engram ensembles supporting a threat memory in lateral amygdala, and this engram ensemble was reactivated by both specific and non-specific retrieval cues (generalized threat memory). Furthermore, we identified a critical role for endocannabinoids, acting retrogradely on parvalbumin-positive (PV+) lateral amygdala interneurons in the formation of a less-sparse engram and memory generalization induced by stress. Glucocorticoid receptor antagonists, endocannabinoid synthesis inhibitors, increasing PV+ neuronal activity, and knocking down cannabinoid receptors in lateral amygdala PV+ neurons restored threat memory specificity and a sparse engram in stressed mice. These findings offer insights into stress-induced memory alterations, providing potential therapeutic avenues for stress-related disorders.

Principles of visual cortex excitatory microcircuit organization

Synapse-specific connectivity and dynamics determine microcircuit function but are challenging to explore with classic paired recordings due to their low throughput. We therefore implemented optomapping, a ∼100-fold faster two-photon optogenetic method. In mouse primary visual cortex (V1), we optomapped 30,454 candidate inputs to reveal 1,790 excitatory inputs to pyramidal, basket, and Martinotti cells. Across these cell types, log-normal distribution of synaptic efficacies emerged as a principle. For pyramidal cells, optomapping reproduced the canonical circuit but unexpectedly uncovered that the excitation of basket cells concentrated to layer 5 and that of Martinotti cells dominated in layer 2/3. The excitation of basket cells was stronger and reached farther than the excitation of pyramidal cells, which may promote stability. Short-term plasticity surprisingly depended on cortical layer in addition to target cell. Finally, optomapping revealed an overrepresentation of shared inputs for interconnected layer-6 pyramidal cells. Thus, by resolving the throughput problem, optomapping uncovered hitherto unappreciated principles of V1 structure.

Discretized representations in V1 predict suboptimal orientation discrimination

Neuronal population activity in sensory cortices is the substrate for perceptual decisions. Yet, we still do not understand how neuronal information content in sensory cortices relates to behavioral reports. To reconcile neurometric and psychometric performance, we recorded the activity of V1 neurons in mice performing a Go/NoGo orientation discrimination task. We found that, around the discrimination threshold, V1 does not represent the orientation of the stimuli as canonically expected. Instead, it forms categorical representations characterized by a relocation of activity at task-relevant domains of the orientation representational space. The relative neuronal activity at those discrete domains accurately predicted the probabilities of the animals' decisions. Our results thus suggest that the categorical integration of discretized feature representations from sensory cortices explains perceptual decisions.

A combinatorial neural code for long-term motor memory

Motor skill repertoire can be stably retained over long periods, but the neural mechanism that underlies stable memory storage remains poorly understood1-8. Moreover, it is unknown how existing motor memories are maintained as new motor skills are continuously acquired. Here we tracked neural representation of learned actions throughout a significant portion of the lifespan of a mouse and show that learned actions are stably retained in combination with context, which protects existing memories from erasure during new motor learning. We established a continual learning paradigm in which mice learned to perform directional licking in different task contexts while we tracked motor cortex activity for up to six months using two-photon imaging. Within the same task context, activity driving directional licking was stable over time with little representational drift. When learning new task contexts, new preparatory activity emerged to drive the same licking actions. Learning created parallel new motor memories instead of modifying existing representations. Re-learning to make the same actions in the previous task context re-activated the previous preparatory activity, even months later. Continual learning of new task contexts kept creating new preparatory activity patterns. Context-specific memories, as we observed in the motor system, may provide a solution for stable memory storage throughout continual learning.

Magnetoelectric nanodiscs enable wireless transgene-free neuromodulation

Deep brain stimulation with implanted electrodes has transformed neuroscience studies and treatment of neurological and psychiatric conditions. Discovering less invasive alternatives to deep brain stimulation could expand its clinical and research applications. Nanomaterial-mediated transduction of magnetic fields into electric potentials has been explored as a means for remote neuromodulation. Here we synthesize magnetoelectric nanodiscs (MENDs) with a core-double-shell Fe3O4-CoFe2O4-BaTiO3 architecture (250 nm diameter and 50 nm thickness) with efficient magnetoelectric coupling. We find robust responses to magnetic field stimulation in neurons decorated with MENDs at a density of 1 µg mm-2 despite individual-particle potentials below the neuronal excitation threshold. We propose a model for repetitive subthreshold depolarization that, combined with cable theory, supports our observations in vitro and informs magnetoelectric stimulation in vivo. Injected into the ventral tegmental area or the subthalamic nucleus of genetically intact mice at concentrations of 1 mg ml-1, MENDs enable remote control of reward or motor behaviours, respectively. These findings set the stage for mechanistic optimization of magnetoelectric neuromodulation towards applications in neuroscience research.

Monitoring and modulating cardiac bioelectricity: from Einthoven to end-user

In 2024, we celebrate the 100th anniversary of Willem Einthoven receiving the Nobel Prize for his discovery of the mechanism of the electrocardiogram (ECG). Building on Einthoven's legacy, electrocardiography allows the monitoring of cardiac bioelectricity through solutions to the so-called forward and inverse problems. These solutions link local cardiac electrical signals with the morphology of the ECG, offering a reversible connection between the heart's electrical activity and its representation on the body surface. Inspired by Einthoven's work, researchers have explored the transition from monitoring to modulation of bioelectrical activity in the heart for the development of new anti-arrhythmic strategies, e.g. via optogenetics. In this review, we demonstrate the lasting influence that Einthoven has on our understanding of cardiac electrophysiology in general, and the diagnosis and treatment of cardiac arrhythmias in particular.

Implantable silicon neural probes with nanophotonic phased arrays for single-lobe beam steering

In brain activity mapping with optogenetics, patterned illumination is crucial for targeted neural stimulation. However, due to optical scattering in brain tissue, light-emitting implants are needed to bring patterned illumination to deep brain regions. A promising solution is silicon neural probes with integrated nanophotonic circuits that form tailored beam patterns without lenses. Here we propose neural probes with grating-based light emitters that generate a single steerable beam. The light emitters, optimized for blue or amber light, combine end-fire optical phased arrays with slab gratings to suppress higher-order sidelobes. In vivo experiments in mice demonstrated that the optical phased array provided sufficient power for optogenetic stimulation. While beam steering performance in tissue reveals challenges, including beam broadening from scattering and the need for a wider steering range, this proof-of-concept demonstration illustrates the design principles for realizing compact optical phased arrays capable of continuous single-beam scanning, laying the groundwork for advancing optical phased arrays toward targeted optogenetic stimulation.

HulaCCR1, a pump-like cation channelrhodopsin discovered in a lake microbiome

Channelrhodopsins are light-gated ion channels consisting of seven transmembrane helices and a retinal chromophore, which are used as popular optogenetic tools for modulating neuronal activity. Cation channelrhodopsins (CCRs), first recognized as the photoreceptors in the chlorophyte Chlamydomonas reinhardtii, have since been identified in diverse species of green algae, as well in other unicellular eukaryotes. The CCRs from non-chlorophyte species are commonly referred to as bacteriorhodopsin-like cation channelrhodopsins, or BCCRs, as most of them feature the three characteristic amino acid residues of the "DTD motif" in the third transmembrane helix (TM3 or helix C) matching the canonical DTD motif of the well-studied archaeal light-driven proton pump bacteriorhodopsin. Here, we report characterization of HulaCCR1, a novel BCCR identified through metatranscriptomic analysis of a unicellular eukaryotic community in Lake Hula, Israel. Interestingly, HulaCCR1 has an ETD motif in which the first residue of the canonical motif is substituted for glutamate. Electrophysiological measurements of the wild-type and a mutant with a DTD motif of HulaCCR1 suggest the critical role of the first glutamate in spectral tuning and channel gating. Additionally, HulaCCR1 exhibits long extensions at the N- and C-termini. Photocurrents recorded from a truncated variant without the signal peptide predicted at the N-terminus were diminished, and membrane localization of the truncated variant significantly decreased, indicating that the signal peptide is important for membrane trafficking of HulaCCR1. These characteristics of HulaCCR1 would be related to a new biological significance in the original unidentified species, distinct from those known for other BCCRs.

Brain state and cortical layer-specific mechanisms underlying perception at threshold

Identical stimuli can be perceived or go unnoticed across successive presentations, producing divergent behavioral outcomes despite similarities in sensory input. We sought to understand how fluctuations in behavioral state and cortical layer and cell class-specific neural activity underlie this perceptual variability. We analyzed physiological measurements of state and laminar electrophysiological activity in visual area V4 while monkeys were rewarded for correctly reporting a stimulus change at perceptual threshold. Hit trials were characterized by a behavioral state with heightened arousal, greater eye position stability, and enhanced decoding performance of stimulus identity from neural activity. Target stimuli evoked stronger responses in V4 in hit trials, and excitatory neurons in the superficial layers, the primary feed-forward output of the cortical column, exhibited lower variability. Feed-forward interlaminar population correlations were stronger on hits. Hit trials were further characterized by greater synchrony between the output layers of the cortex during spontaneous activity, while the stimulus-evoked period showed elevated synchrony in the feed-forward pathway. Taken together, these results suggest that a state of elevated arousal and stable retinal images allow enhanced processing of sensory stimuli, which contributes to hits at perceptual threshold.

Pre-existing visual responses in a projection-defined dopamine population explain individual learning trajectories

A key challenge of learning a new task is that the environment is high dimensional-there are many different sensory features and possible actions, with typically only a small reward-relevant subset. Although animals can learn to perform complex tasks that involve arbitrary associations between stimuli, actions, and rewards,1,2,3,4,5,6 a consistent and striking result across varied experimental paradigms is that in initially acquiring such tasks, large differences between individuals are apparent in the learning process.7,8,9,10,11,12 What neural mechanisms contribute to initial task acquisition, and why do some individuals learn a new task much more quickly than others? To address these questions, we recorded longitudinally from dopaminergic (DA) axon terminals in mice learning a visual decision-making task.7 Across striatum, DA responses tracked idiosyncratic and side-specific learning trajectories, consistent with widespread reward prediction error coding across DA terminals. However, even before any rewards were delivered, contralateral-side-specific visual responses were present in DA terminals, primarily in the dorsomedial striatum (DMS). These pre-existing responses predicted the extent of learning for contralateral stimuli. Moreover, activation of these terminals improved contralateral performance. Thus, the initial conditions of a projection-specific and feature-specific DA signal help explain individual learning trajectories. More broadly, this work suggests that functional heterogeneity across DA projections may serve to bias target regions toward learning about different subsets of task features, providing a potential mechanism to address the dimensionality of the initial task learning problem.

Monosynaptic Inputs to Ventral Tegmental Area Glutamate and GABA Co-transmitting Neurons

A unique population of ventral tegmental area (VTA) neurons co-transmits glutamate and GABA. However, the circuit inputs to VTA VGluT2+VGaT+ neurons are unknown, limiting our understanding of their functional capabilities. By coupling monosynaptic rabies tracing with intersectional genetic targeting in male and female mice, we found that VTA VGluT2+VGaT+ neurons received diverse brainwide inputs. The largest numbers of monosynaptic inputs to VTA VGluT2+VGaT+ neurons were from superior colliculus (SC), lateral hypothalamus (LH), midbrain reticular nucleus, and periaqueductal gray, whereas the densest inputs relative to brain region volume were from the dorsal raphe nucleus, lateral habenula, and VTA. Based on these and prior data, we hypothesized that LH and SC inputs were from glutamatergic neurons. Optical activation of glutamatergic LH neurons activated VTA VGluT2+VGaT+ neurons regardless of stimulation frequency and resulted in flee-like ambulatory behavior. In contrast, optical activation of glutamatergic SC neurons activated VTA VGluT2+VGaT+ neurons for a brief period of time at high frequency and resulted in head rotation and arrested ambulatory behavior (freezing). Stimulation of glutamatergic LH neurons, but not glutamatergic SC neurons, was associated with VTA VGluT2+VGaT+ footshock-induced activity and inhibition of LH glutamatergic neurons disrupted VTA VGluT2+VGaT+ tailshock-induced activity. We interpret these results such that inputs to VTA VGluT2+VGaT+ neurons may integrate diverse signals related to the detection and processing of motivationally salient outcomes.

Hunger modulates exploration through suppression of dopamine signaling in the tail of striatum

Caloric depletion leads to behavioral changes that help an animal find food and restore its homeostatic balance. Hunger increases exploration and risk-taking behavior, allowing an animal to forage for food despite risks; however, the neural circuitry underlying this change is unknown. Here, we characterize how hunger restructures an animal's spontaneous behavior as well as its directed exploration of a novel object. We show that hunger-induced changes in exploration are accompanied by and result from modulation of dopamine signaling in the tail of the striatum (TOS). Dopamine signaling in the TOS is modulated by internal hunger state through the activity of agouti-related peptide (AgRP) neurons, putative "hunger neurons" in the arcuate nucleus of the hypothalamus. These AgRP neurons are poly-synaptically connected to TOS-projecting dopaminergic neurons through the lateral hypothalamus, the central amygdala, and the periaqueductal grey. We thus delineate a hypothalamic-midbrain circuit that coordinates changes in exploration behavior in the hungry state.

Integrated Bioelectronic and Optogenetic Methods to Study Brain-Body Circuits

The peripheral nervous system, consisting of somatic sensory circuits and autonomic effector circuits, enables communication between the body's organs and the brain. Dysregulation in these circuits is implicated in an array of disorders and represents a potential target for neuromodulation therapies. In this Perspective, we discuss recent advances in the neurobiological understanding of these brain-body pathways and the expansion of neurotechnologies beyond the brain to the viscera. We focus primarily on the development of integrated technologies that leverage bioelectronic devices with optogenetic tools. We highlight the discovery and application of ultrapotent and red-shifted channelrhodopsins for minimally invasive optogenetics and as tools to study brain-body circuits. These innovations enable studies of freely behaving animals and have enhanced our understanding of the role physiological signals play in brain states and behavior.

Cellular-resolution optogenetics reveals attenuation-by-suppression in visual cortical neurons

The relationship between neurons' input and spiking output is central to brain computation. Studies in vitro and in anesthetized animals suggest that nonlinearities emerge in cells' input-output (IO; activation) functions as network activity increases, yet how neurons transform inputs in vivo has been unclear. Here, we characterize cortical principal neurons' activation functions in awake mice using two-photon optogenetics. We deliver fixed inputs at the soma while neurons' activity varies with sensory stimuli. We find that responses to fixed optogenetic input are nearly unchanged as neurons are excited, reflecting a linear response regime above neurons' resting point. In contrast, responses are dramatically attenuated by suppression. This attenuation is a powerful means to filter inputs arriving to suppressed cells, privileging other inputs arriving to excited neurons. These results have two major implications. First, somatic neural activation functions in vivo accord with the activation functions used in recent machine learning systems. Second, neurons' IO functions can filter sensory inputs-not only do sensory stimuli change neurons' spiking outputs, but these changes also affect responses to input, attenuating responses to some inputs while leaving others unchanged.

Strength of activation and temporal dynamics of bioluminescent-optogenetics in response to systemic injections of the luciferin

BioLuminescent OptoGenetics ("BL-OG") is a chemogenetic method that can evoke optogenetic reactions in the brain non-invasively. In BL-OG, an enzyme that catalyzes a light producing reaction (i.e., a luciferase) is tethered to an optogenetic element that is activated in response to bioluminescent light. Bioluminescence is generated by injecting a chemical substrate (luciferin, e.g., h-Coelenterazine; h-CTZ) that is catalyzed by the luciferase. By directly injecting the luciferin into the brain, we show that bioluminescent light is proportional to spiking activity, and this relationship scales as a function of luciferin dosage. Here, we build on these previous observations by characterizing the temporal dynamics and dose response curves of bioluminescence generated by luminopsins (LMOs), a proxy of BL-OG effects, to intravenous (IV) injections of the luciferin. We imaged bioluminescence through a thinned skull of mice running on a wheel, while delivering h-CTZ via the tail vein with different dosage concentrations and injection rates. The data reveal a systematic relationship between strength of bioluminescence and h-CTZ dosage, with higher concentration generating stronger bioluminescence. We also found that bioluminescent activity occurs rapidly (< 60 s after IV injection) regardless of concentration dosage. However, as expected, the onset time of bioluminescence is delayed as the injection rate decreases. Notably, the strength and time decay of bioluminescence is invariant to the injection rate of h-CTZ. Taken together, these data show that BL-OG effects are highly consistent across injection parameters of h-CTZ, highlighting the reliability of BL-OG as a minimally invasive neuromodulation method.

Unique hydrogen-bonding network in a viral channelrhodopsin

Channelrhodopsins (CRs) are used as key tools in optogenetics, and novel CRs, either found from nature or engineered by mutation, have greatly contributed to the development of optogenetics. Recently CRs were discovered from viruses, and crystal structure of a viral CR, OLPVR1, reported a very similar water-containing hydrogen-bonding network near the retinal Schiff base to that of a light-driven proton-pump bacteriorhodopsin (BR). In both OLPVR1 and BR, nearly planar pentagonal cluster structures are comprised of five oxygen atoms, three oxygens from water molecules and two oxygens from the Schiff base counterions. The planar pentagonal cluster stabilizes a quadrupole, two positive charges at the Schiff base and an arginine, and two negative charges at the counterions, and thus plays important roles in light-gated channel function of OLPVR1 and light-driven proton pump function of BR. Despite similar pentagonal cluster structures, present FTIR analysis revealed different hydrogen-bonding networks between OLPVR1 and BR. The hydrogen bond between the protonated Schiff base and a water is stronger in OLPVR1 than in BR, and internal water molecules donate hydrogen bonds much weaker in OLPVR1 than in BR. In OLPVR1, the bridged water molecule between the Schiff base and counterions forms hydrogen bonds to D76 and D200 equally, while the hydrogen-bonding interaction is much stronger to D85 than to D212 in BR. The present interpretation is supported by the mutation results, where D76 and D200 equally work as the Schiff base counterions in OLPVR1, but D85 is the primary counterion in BR. This work reports highly sensitive hydrogen-bonding network in the Schiff base region, which would be closely related to each function through light-induced alterations of the network.

Comparative Validation of Scintillator Materials for X-Ray-Mediated Neuronal Control in the Deep Brain

When exposed to X-rays, scintillators emit visible luminescence. X-ray-mediated optogenetics employs scintillators for remotely activating light-sensitive proteins in biological tissue through X-ray irradiation. This approach offers advantages over traditional optogenetics, allowing for deeper tissue penetration and wireless control. Here, we assessed the short-term safety and efficacy of candidate scintillator materials for neuronal control. Our analyses revealed that lead-free halide scintillators, such as Cs3Cu2I5, exhibited significant cytotoxicity within 24 h and induced neuroinflammatory effects when injected into the mouse brain. In contrast, cerium-doped gadolinium aluminum gallium garnet (Ce:GAGG) nanoparticles showed no detectable cytotoxicity within the same period, and injection into the mouse brain did not lead to observable neuroinflammation over four weeks. Electrophysiological recordings in the cerebral cortex of awake mice showed that X-ray-induced radioluminescence from Ce:GAGG nanoparticles reliably activated 45% of the neuronal population surrounding the implanted particles, a significantly higher activation rate than europium-doped GAGG (Eu:GAGG) microparticles, which activated only 10% of neurons. Furthermore, we established the cell-type specificity of this technique by using Ce:GAGG nanoparticles to selectively stimulate midbrain dopamine neurons. This technique was applied to freely behaving mice, allowing for wireless modulation of place preference behavior mediated by midbrain dopamine neurons. These findings highlight the unique suitability of Ce:GAGG nanoparticles for X-ray-mediated optogenetics. The deep tissue penetration, short-term safety, wireless neuronal control, and cell-type specificity of this system offer exciting possibilities for diverse neuroscience applications and therapeutic interventions.

Opto2P-FCM: A MEMS based miniature two-photon microscope with two-photon patterned optogenetic stimulation

Multiphoton microscopy combined with optogenetic photostimulation is a powerful technique in neuroscience enabling precise control of cellular activity to determine the neural basis of behavior in a live animal. Two-photon patterned photostimulation has taken this further by allowing interrogation at the individual neuron level. However, it remains a challenge to implement imaging of neural activity with spatially patterned two-photon photostimulation in a freely moving animal. We developed a miniature microscope for high resolution two-photon fluorescence imaging with patterned two-photon optogenetic stimulation. The design incorporates a MEMS scanner for two-photon imaging and a second beam path for patterned two-photon excitation in a compact and lightweight design that can be head-attached to a freely moving animal. We demonstrate cell-specific optogenetics and high resolution MEMS based two-photon imaging in a freely moving mouse. The new capabilities of this miniature microscope design can enable cell-specific studies of behavior that can only be done in freely moving animals.

Heterogeneous Nuclear Ribonucleoprotein A1 Knockdown Alters Constituents of Nucleocytoplasmic Transport

BACKGROUND/OBJECTIVES

Changes in nuclear morphology, alterations to the nuclear pore complex (NPC), including loss, aggregation, and dysfunction of nucleoporins (Nups), and nucleocytoplasmic transport (NCT) abnormalities have become hallmarks of neurodegenerative diseases. Previous RNA sequencing data utilizing knockdown of heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) identified enrichment for pathways and changes in RNAs related to nuclear morphology and showed differential expression of key nuclear targets. This suggests that dysfunction of hnRNP A1, which is observed in neurodegenerative diseases, may contribute to abnormalities in nuclear morphology, NPC, and NCT.

METHODS

We performed knockdown of hnRNP A1 in Neuro-2A cells, a neuronal cell line, to examine nuclear morphology, NPC, and NCT.

RESULTS

First, we examined nuclear morphology using Lamin B, wherein we observed increased nuclear envelope abnormalities in cells with hnRNP A1 knockdown as compared to control. To quantify changes in Lamin B, we designed and validated an automated computer-based model, which quantitatively confirmed our observations. Next, we investigated the impact of hnRNP A1 knockdown on components of the NPC and NCT. In line with the previous literature, we found changes in Nups, including altered distribution and reduced protein expression, as well as disrupted NCT. Finally, we validated our findings in multiple sclerosis (MS) brains, a disease with a significant neurodegenerative component caused by hnRNP A1 dysfunction, where neuronal nuclear envelope alterations were significantly increased as compared to controls.

CONCLUSIONS

Together, these data implicate hnRNP A1 as an important contributor to nuclear morphology, Nup expression and distribution, and NCT and suggest that hnRNP A1 dysfunction may lead to defects in these processes in neurodegenerative diseases.

Causal evidence of a line attractor encoding an affective state

Continuous attractors are an emergent property of neural population dynamics that have been hypothesized to encode continuous variables such as head direction and eye position1-4. In mammals, direct evidence of neural implementation of a continuous attractor has been hindered by the challenge of targeting perturbations to specific neurons within contributing ensembles2,3. Dynamical systems modelling has revealed that neurons in the hypothalamus exhibit approximate line-attractor dynamics in male mice during aggressive encounters5. We have previously hypothesized that these dynamics may encode the variable intensity and persistence of an aggressive internal state. Here we report that these neurons also showed line-attractor dynamics in head-fixed mice observing aggression6. This allowed us to identify and manipulate line-attractor-contributing neurons using two-photon calcium imaging and holographic optogenetic perturbations. On-manifold perturbations yielded integration of optogenetic stimulation pulses and persistent activity that drove the system along the line attractor, while transient off-manifold perturbations were followed by rapid relaxation back into the attractor. Furthermore, single-cell stimulation and imaging revealed selective functional connectivity among attractor-contributing neurons. Notably, individual differences among mice in line-attractor stability were correlated with the degree of functional connectivity among attractor-contributing neurons. Mechanistic recurrent neural network modelling indicated that dense subnetwork connectivity and slow neurotransmission7 best recapitulate our empirical findings. Our work bridges circuit and manifold levels3, providing causal evidence of continuous attractor dynamics encoding an affective internal state in the mammalian hypothalamus.

The high-light-sensitivity mechanism and optogenetic properties of the bacteriorhodopsin-like channelrhodopsin GtCCR4

Channelrhodopsins are microbial light-gated ion channels that can control the firing of neurons in response to light. Among several cation channelrhodopsins identified in Guillardia theta (GtCCRs), GtCCR4 has higher light sensitivity than typical channelrhodopsins. Furthermore, GtCCR4 shows superior properties as an optogenetic tool, such as minimal desensitization. Our structural analyses of GtCCR2 and GtCCR4 revealed that GtCCR4 has an outwardly bent transmembrane helix, resembling the conformation of activated G-protein-coupled receptors. Spectroscopic and electrophysiological comparisons suggested that this helix bend in GtCCR4 omits channel recovery time and contributes to high light sensitivity. An electrophysiological comparison of GtCCR4 and the well-characterized optogenetic tool ChRmine demonstrated that GtCCR4 has superior current continuity and action-potential spike generation with less invasiveness in neurons. We also identified highly active mutants of GtCCR4. These results shed light on the diverse structures and dynamics of microbial rhodopsins and demonstrate the strong optogenetic potential of GtCCR4.

Recent advances in light patterned optogenetic photostimulation in freely moving mice

Optogenetics opened the door to a new era of neuroscience. New optical developments are under way to enable high-resolution neuronal activity imaging and selective photostimulation of neuronal ensembles in freely moving animals. These advancements could allow researchers to interrogate, with cellular precision, functionally relevant neuronal circuits in the framework of naturalistic brain activity. We provide an overview of the current state-of-the-art of imaging and photostimulation in freely moving rodents and present a road map for future optical and engineering developments toward miniaturized microscopes that could reach beyond the currently existing systems.

Foundation model of neural activity predicts response to new stimulus types and anatomy

The complexity of neural circuits makes it challenging to decipher the brain's algorithms of intelligence. Recent breakthroughs in deep learning have produced models that accurately simulate brain activity, enhancing our understanding of the brain's computational objectives and neural coding. However, these models struggle to generalize beyond their training distribution, limiting their utility. The emergence of foundation models, trained on vast datasets, has introduced a new AI paradigm with remarkable generalization capabilities. We collected large amounts of neural activity from visual cortices of multiple mice and trained a foundation model to accurately predict neuronal responses to arbitrary natural videos. This model generalized to new mice with minimal training and successfully predicted responses across various new stimulus domains, such as coherent motion and noise patterns. It could also be adapted to new tasks beyond neural prediction, accurately predicting anatomical cell types, dendritic features, and neuronal connectivity within the MICrONS functional connectomics dataset. Our work is a crucial step toward building foundation brain models. As neuroscience accumulates larger, multi-modal datasets, foundation models will uncover statistical regularities, enabling rapid adaptation to new tasks and accelerating research.

Dynamic control of sequential retrieval speed in networks with heterogeneous learning rules

Temporal rescaling of sequential neural activity has been observed in multiple brain areas during behaviors involving time estimation and motor execution at variable speeds. Temporally asymmetric Hebbian rules have been used in network models to learn and retrieve sequential activity, with characteristics that are qualitatively consistent with experimental observations. However, in these models sequential activity is retrieved at a fixed speed. Here, we investigate the effects of a heterogeneity of plasticity rules on network dynamics. In a model in which neurons differ by the degree of temporal symmetry of their plasticity rule, we find that retrieval speed can be controlled by varying external inputs to the network. Neurons with temporally symmetric plasticity rules act as brakes and tend to slow down the dynamics, while neurons with temporally asymmetric rules act as accelerators of the dynamics. We also find that such networks can naturally generate separate 'preparatory' and 'execution' activity patterns with appropriate external inputs.

Cortical Layer-Dependent Signaling in Cognition: Three Computational Modes of the Canonical Circuit

The cerebral cortex performs computations via numerous six-layer modules. The operational dynamics of these modules were studied primarily in early sensory cortices using bottom-up computation for response selectivity as a model, which has been recently revolutionized by genetic approaches in mice. However, cognitive processes such as recall and imagery require top-down generative computation. The question of whether the layered module operates similarly in top-down generative processing as in bottom-up sensory processing has become testable by advances in the layer identification of recorded neurons in behaving monkeys. This review examines recent advances in laminar signaling in these two computations, using predictive coding computation as a common reference, and shows that each of these computations recruits distinct laminar circuits, particularly in layer 5, depending on the cognitive demands. These findings highlight many open questions, including how different interareal feedback pathways, originating from and terminating at different layers, convey distinct functional signals.

Tetherless Optical Neuromodulation: Wavelength from Orange-red to Mid-infrared

Optogenetics, a technique that employs light for neuromodulation, has revolutionized the study of neural mechanisms and the treatment of neurological disorders due to its high spatiotemporal resolution and cell-type specificity. However, visible light, particularly blue and green light, commonly used in conventional optogenetics, has limited penetration in biological tissue. This limitation necessitates the implantation of optical fibers for light delivery, especially in deep brain regions, leading to tissue damage and experimental constraints. To overcome these challenges, the use of orange-red and infrared light with greater tissue penetration has emerged as a promising approach for tetherless optical neuromodulation. In this review, we provide an overview of the development and applications of tetherless optical neuromodulation methods with long wavelengths. We first discuss the exploration of orange-red wavelength-responsive rhodopsins and their performance in tetherless optical neuromodulation. Then, we summarize two novel tetherless neuromodulation methods using near-infrared light: upconversion nanoparticle-mediated optogenetics and photothermal neuromodulation. In addition, we discuss recent advances in mid-infrared optical neuromodulation.

Neural ensembles: role of intrinsic excitability and its plasticity

Synaptic connectivity defines groups of neurons that engage in correlated activity during specific functional tasks. These co-active groups of neurons form ensembles, the operational units involved in, for example, sensory perception, motor coordination and memory (then called an engram). Traditionally, ensemble formation has been thought to occur via strengthening of synaptic connections via long-term potentiation (LTP) as a plasticity mechanism. This synaptic theory of memory arises from the learning rules formulated by Hebb and is consistent with many experimental observations. Here, we propose, as an alternative, that the intrinsic excitability of neurons and its plasticity constitute a second, non-synaptic mechanism that could be important for the initial formation of ensembles. Indeed, enhanced neural excitability is widely observed in multiple brain areas subsequent to behavioral learning. In cortical structures and the amygdala, excitability changes are often reported as transient, even though they can last tens of minutes to a few days. Perhaps it is for this reason that they have been traditionally considered as modulatory, merely supporting ensemble formation by facilitating LTP induction, without further involvement in memory function (memory allocation hypothesis). We here suggest-based on two lines of evidence-that beyond modulating LTP allocation, enhanced excitability plays a more fundamental role in learning. First, enhanced excitability constitutes a signature of active ensembles and, due to it, subthreshold synaptic connections become suprathreshold in the absence of synaptic plasticity (iceberg model). Second, enhanced excitability promotes the propagation of dendritic potentials toward the soma and allows for enhanced coupling of EPSP amplitude (LTP) to the spike output (and thus ensemble participation). This permissive gate model describes a need for permanently increased excitability, which seems at odds with its traditional consideration as a short-lived mechanism. We propose that longer modifications in excitability are made possible by a low threshold for intrinsic plasticity induction, suggesting that excitability might be on/off-modulated at short intervals. Consistent with this, in cerebellar Purkinje cells, excitability lasts days to weeks, which shows that in some circuits the duration of the phenomenon is not a limiting factor in the first place. In our model, synaptic plasticity defines the information content received by neurons through the connectivity network that they are embedded in. However, the plasticity of cell-autonomous excitability could dynamically regulate the ensemble participation of individual neurons as well as the overall activity state of an ensemble.

Calcium Binding Mechanism in TAT Rhodopsin

TAT rhodopsin binds Ca2+ near the Schiff base region, which accompanies deprotonation of the Schiff base. This paper reports the Ca2+-free and Ca2+-bound structures of TAT rhodopsin by molecular dynamics (MD) simulation launched from AlphaFold structures. In the Ca2+-bound TAT rhodopsin, Ca2+ is directly coordinated by eight oxygen atoms, four oxygens of the side chains of E54 and D227, and four oxygens of water molecules. E54 is not involved in the hydrogen-bonding network of the Ca2+-free TAT rhodopsin, while flipping motion of E54 allows Ca2+ binding to TAT rhodopsin with deformation of helices observed by FTIR spectroscopy. The hydrogen-bonding network plays a crucial role in maintaining the Ca2+ binding, as mutations of E54, Y55, R79, Y200, E220, and D227 abolished the binding. Only T82V exhibited the Ca2+ binding like the wild type among the mutants in this study. The molecular mechanism of Ca2+ binding is discussed based on the present computational and experimental analysis.