CaMPARI2 enables stimulus-locked whole-brain activity mapping at cellular resolution in unrestrained larval zebrafish

Visualizing active neurons and circuits in vivo is critical for investigating the neural activity that underlies behavior. While several established methodologies are available to achieve this end in larval zebrafish, they are limited by the scale of tissue visualization, temporal resolution, need to restrain larvae, and/or accessibility of necessary instruments. Here, we establish a pipeline for the visualization and quantification of spatiotemporally precise whole-brain neural activity in larval zebrafish using CaMPARI2, a genetically encoded calcium indicator. Using temporally specific photoconverting UV light exposures, we capture whole-brain “snapshots” of neural activity time-locked to stimuli during unrestrained larval behavior. We optimize experimental conditions for establishing sub-second neuronal activity changes across acoustically-evoked behavioral paradigms spanning minutes to hours. We then leverage this system to pinpoint brain-wide neural activity changes during nonassociative habituation learning, observing distinct activity signatures in the subpallium, preoptic area, and habenulae that are altered through pharmacological disruption of habituation learning. This approach effectively complements the temporal precision achievable through post hoc activity detection methods and expands the accessibility of large-scale behavioral circuit dissection beyond highly specialized real-time volumetric imaging equipment.

In vivo optical imaging can reveal the dynamics of large-scale cortical activity, but methods for chronic recording are limited. Here we present a technique for long-term investigation of cortical map dynamics using wide-field ratiometric fluorescence imaging of the genetically encoded calcium indicator (GECI) Yellow Cameleon 3.60. We find that wide-field GECI signals report sensory-evoked activity in anaesthetized mouse somatosensory cortex with high sensitivity and spatiotemporal precision, and furthermore, can be measured repeatedly in separate imaging sessions over multiple weeks. This method opens new possibilities for the longitudinal study of stability and plasticity of cortical sensory representations.

Preparatory activity, characterized by gradual, longer timescale changes in neural activity, is present in a number of different brain areas before the onset of simple movements and is believed to be important for movement initiation. However, relatively little is known about such activity before initiation of naturally learned movement sequences. The song of an adult male zebra finch is a well studied example of a naturally learned movement sequence and previous studies have shown robust premotor activity immediately before song. Here, I characterize longer timescale changes in neural activity in adult male zebra finch premotor nucleus HVC before onset of song bouts. I show that interneurons and a subset of basal-ganglia-projecting neurons change their activity several hundred milliseconds before song bout onset. Interneurons increased their activity, whereas basal-ganglia-projecting neurons either increased or decreased their activity. Such changes in neural activity were larger, started earlier, and were more common specifically before song bouts that began with the short, repetitive, introductory notes (INs) characteristic of zebra finch song bouts. Further, stronger and earlier changes were also correlated with successful song sequence initiation. Finally, a small fraction of basal-ganglia-projecting neurons that increased their activity before song bout onset did not have song or IN-related activity, suggesting a specialized preparatory role for such neurons. Overall, these data suggest that pre-bout activity in HVC represents preparatory activity important for initiation of a naturally learned movement sequence.SIGNIFICANCE STATEMENT Changes in neuronal activity well before the onset of simple movements are thought to be important for movement initiation. However, a number of animal movements consist of sequences of simple movements and relatively little is known about neuronal activity before such movement sequences. Using adult zebra finch song, a well studied example of a movement sequence, I show here that neurons in premotor nucleus HVC change their activity hundreds of milliseconds before song bout onset. In most neurons, the presence of such changes correlated with successful song sequence initiation. My results show the presence of preparatory neural activity in HVC and suggest a role for HVC in sequence initiation in addition to its established role in song sequence timing.

Recent advance in the design of genetically encoded calcium indicators (GECIs) has further increased their potential for direct measurements of activity in intact neural circuits. However, a quantitative analysis of their fluorescence changes (DeltaF) in vivo and the relationship to the underlying neural activity and changes in intracellular calcium concentration (Delta[Ca(2+)](i)) has not been given. We used two-photon microscopy, microinjection of synthetic Ca(2+) dyes and in vivo calibration of Oregon-Green-BAPTA-1 (OGB-1) to estimate [Ca(2+)](i) at rest and Delta[Ca(2+)](i) at different action potential frequencies in presynaptic motoneuron boutons of transgenic Drosophila larvae. We calibrated DeltaF of eight different GECIs in vivo to neural activity, Delta[Ca(2+)](i), and DeltaF of purified GECI protein at similar Delta[Ca(2+)] in vitro. Yellow Cameleon 3.60 (YC3.60), YC2.60, D3cpv, and TN-XL exhibited twofold higher maximum DeltaF compared with YC3.3 and TN-L15 in vivo. Maximum DeltaF of GCaMP2 and GCaMP1.6 were almost identical. Small Delta[Ca(2+)](i) were reported best by YC3.60, D3cpv, and YC2.60. The kinetics of Delta[Ca(2+)](i) was massively distorted by all GECIs, with YC2.60 showing the slowest kinetics, whereas TN-XL exhibited the fastest decay. Single spikes were only reported by OGB-1; all GECIs were blind for Delta[Ca(2+)](i) associated with single action potentials. YC3.60 and D3cpv tentatively reported spike doublets. In vivo, the K(D) (dissociation constant) of all GECIs was shifted toward lower values, the Hill coefficient was changed, and the maximum DeltaF was reduced. The latter could be attributed to resting [Ca(2+)](i) and the optical filters of the equipment. These results suggest increased sensitivity of new GECIs but still slow on rates for calcium binding.

Almost 60 years have passed since the initial discovery by Hubel and Wiesel that changes in neuronal activity can elicit developmental rewiring of the central nervous system (CNS). Over this period, we have gained a more comprehensive picture of how both spontaneous neural activity and sensory experience-induced changes in neuronal activity guide CNS circuit development. Here we review activity-dependent synaptic pruning in the mammalian CNS, which we define as the removal of a subset of synapses, while others are maintained, in response to changes in neural activity in the developing nervous system. We discuss the mounting evidence that immune and cell-death molecules are important mechanistic links by which changes in neural activity guide the pruning of specific synapses, emphasizing the role of glial cells in this process. Finally, we discuss how these developmental pruning programmes may go awry in neurodevelopmental disorders of the human CNS, focusing on autism spectrum disorder and schizophrenia. Together, our aim is to give an overview of how the field of activity-dependent pruning research has evolved, led to exciting new questions and guided the identification of new, therapeutically relevant mechanisms that result in aberrant circuit development in neurodevelopmental disorders.

The study of vision is probably the most advanced in systems neuroscience. Significant progress has been made over the last 30 years in understanding the anatomical, physiological, and computational organization of the visual system in the primate brain (1). Since the seminal work of David Marr (2), a major goal in vision research has been to characterize vision as a complex computational task and the visual system as an informationprocessing device. From this systems perspective, it is becoming more evident that the elementary processing components within the visual system are not isolated neurons, but neuronal assemblies within cortical or subcortical areas. The visual system (and brain systems in general) has been characterized as a distributed multilevel hierarchy of visual areas in which both serial and parallel processing occur simultaneously. Single neuron recordings in awakebehaving monkeys has been a powerful way to correlate neuronal activity and visual behavior. The above considerations suggest, however, that a more complete understanding of visual processing requires the analysis of neuronal activity from a wider spatial window. This analysis is now being provided by several techniques, such as 2-deoxyglucose autoradiography and optical imaging in primates and neuroimaging [PET and functional magnetic resonance imaging (fMRI)] methods in humans. The basic rationale for using PET to study human visual neurophysiology is that the performance of any task places specific information processing demands on the brain. These demands are met through changes in neural activity in various functional areas of the brain. Changes in neuronal activity produce changes in local blood flow (3, 4), and these variations in blood flow can be measured with PET. It is currently believed that changes in blood flow correspond to changes in neuronal activity at the level of one or a few adjacent cortical or subcortical functional areas. The spatial localization of the method-i.e., the accuracy of localizing a single source-is -2-5 mm (see, e.g., ref. 5), in the order of magnitude of most brain areas. The temporal resolution of a PET activation study, when using a short-lived tracer such as 150labeled water (half-life 2 min), is about 40 sec. A major drawback of the poor temporal resolution is the inability to discern the temporal relationships among multiple regions of activation. Furthermore, only processes that are repeated many times over the 40 sec can be imaged through appropriate experimental designs. It is possible that partial resolution of some of these issues will be provided by coupling PET recording with faster methods (magnetoencephalography, evoked response potentials, electrocorticography). In summary, PET allows monitoring of brain neural activity that has been averaged over time at the level of individual functional areas. PET spatio-temporal performance characteristics better suit experimental designs that look at the activation of distributed networks in the brain rather than at the fine mapping (e.g., retinotopical organization) of cortical areas in space or time.

While substantial task-related neural activity has been observed during motor tasks in rodent primary motor cortex and premotor cortex, the long-term stability of these responses in healthy rats is uncertain, limiting the interpretability of longitudinal changes in the specific patterns of neural activity associated with learning or motor recovery following injury. This study examined the stability of task-related neural activity associated with execution of two distinct reaching tasks in healthy rodents. A novel automated rodent behavioral apparatus was constructed and rats were trained to perform a reaching task combining a ‘gross’ lever press and a ‘fine’ pellet retrieval. In each animal, two chronic microelectrode arrays were implanted in motor cortex spanning the caudal forelimb area (rodent primary motor cortex) and the rostral forelimb area (rodent premotor cortex). We recorded multiunit spiking and local field potential activity from 10 days to 7–10 weeks post-implantation to characterize the patterns of neural activity observed during each task component and analyzed the consistency of channel-specific task-related neural activity. Task-related changes in neural activity were observed on the majority of channels. While the task-related changes in multi-unit spiking and local field potential spectral power were consistent over several weeks, spectral power changes were more stable, despite the trade-off of decreased spatial and temporal resolution. These results show that neural activity in rodent primary and premotor cortex is associated with specific phases of reaching movements with stable patterns of task-related activity across time, establishing the relevance of the rodent for future studies designed to examine changes in task-related neural activity during recovery from focal cortical lesions.

Evidence from human and animal studies indicates that mechanical loads to breathing are stressful stimuli and evoke compensatory behaviours. Conditioning of stressful stimuli is known to cause changes in basal stress levels and behaviour. Individuals with respiratory obstructive diseases repeatedly experience bouts of airway obstruction, which may act as a form of conditioning, and often have affective disorders, such as anxiety and depression. It is unknown whether the development of affective disorders in these individuals results from the unexpected recurring respiratory perturbations. To investigate this possibility, we developed a model to elicit tracheal occlusion (TO) in conscious rats and exposed them to 10 days of TO conditioning. We hypothesized that healthy, conscious animals exposed to TO conditioning would develop stress and anxiety and would have modulated neural activity in respiratory, stress, discriminative and affective neural regions. Following TO conditioning, rats had increased basal corticosterone levels, greater adrenal weights and elevated anxiety levels compared with animals not receiving TO. Significant increases in cytochrome oxidase staining were found in brainstem respiratory nuclei, periaqueductal grey, dorsal raphe, thalamus and insular cortex. These results suggest that healthy animals develop stress and anxiety responses to respiratory load conditioning via inescapable tracheal occlusions, which may be mediated through state changes in specific brain nuclei.

Neural activity is closely coupled with energy metabolism but details of the association remain to be identified. One basic area involves the relationships between neural activity and the main supportive substrates of glucose and lactate. This is of fundamental significance for the interpretation of non-invasive neural imaging. Here, we use microelectrodes with high spatial and temporal resolution to determine simultaneous co-localized changes in glucose, lactate, and neural activity during visual activation of the cerebral cortex in the cat. Tissue glucose and lactate concentration levels are measured with electrochemical microelectrodes while neural spiking activity and local field potentials are sampled by a microelectrode. These measurements are performed simultaneously while neurons are activated by visual stimuli of different contrast levels, orientations, and sizes. We find immediate decreases in tissue glucose concentration and simultaneous increases in lactate during neural activation. Both glucose and lactate signals return to their baseline levels instantly as neurons cease firing. No sustained changes or initial dips in glucose or lactate signals are elicited by visual stimulation. However, co-localized measurements of cerebral blood flow and neural activity demonstrate a clear delay in the cerebral blood flow signal such that it does not correlate temporally with the neural response. These results provide direct real-time evidence regarding the coupling between co-localized energy metabolism and neural activity during physiological stimulation. They are also relevant to a current question regarding the role of lactate in energy metabolism in the brain during neural activation. Dynamic changes in energy metabolites can be measured directly with high spatial and temporal resolution by use of enzyme-based microelectrodes. Here, to examine neuro-metabolic coupling during brain activation, we use combined microelectrodes to simultaneously measure extracellular glucose, lactate, and neural responses in the primary visual cortex to visual stimulation. We demonstrate rapid decreases in glucose and increases in lactate during neural activation. Changes in glucose and lactate signals are transient and closely coupled with neuronal firing.

Nervous systems extract and process information from the environment to alter animal behavior and physiology. Despite progress in understanding how different stimuli are represented by changes in neuronal activity, less is known about how they affect broader neural network properties. We developed a framework for using graph-theoretic features of neural network activity to predict ecologically relevant stimulus properties, in particular stimulus identity. We used the transparent nematode, Caenorhabditis elegans, with its small nervous system to define neural network features associated with various chemosensory stimuli. We first immobilized animals using a microfluidic device and exposed their noses to chemical stimuli while monitoring changes in neural activity of more than 50 neurons in the head region. We found that graph-theoretic features, which capture patterns of interactions between neurons, are modulated by stimulus identity. Further, we show that a simple machine learning classifier trained using graph-theoretic features alone, or in combination with neural activity features, can accurately predict salt stimulus. Moreover, by focusing on putative causal interactions between neurons, the graph-theoretic features were almost twice as predictive as the neural activity features. These results reveal that stimulus identity modulates the broad, network-level organization of the nervous system, and that graph theory can be used to characterize these changes.

Human midbrain organoids (hMOs) show promise as a patient-derived model for the study of Parkinson's disease (PD). Yet, much remains unknown about how accurately hMOs recapitulate key features of PD in the human brain. In both PD patients and animal models, disease progression leads to characteristic changes in neural activity throughout the basal ganglia. Here we demonstrate that patient-derived induced pluripotent stem cell (iPSC) hMOs harboring a triplication in the SNCA gene, encoding α-synuclein, a key protein in PD pathogenesis, can recapitulate PD-associated changes in neural activity. Namely, we observe hyperactive network activity in SNCA triplication hMOs, but not in isogenic, CRISPR-corrected iPSC hMOs. These changes are characterized by an increase in the number of bursts and network-wide bursts. Moreover, SNCA triplication hMOs exhibit an increase in network synchrony and burst/network burst strength similar to observations in animal and human PD brains. Subsequently, we show that the observed changes in neuronal activity are attributed to dopamine D2 receptor hypoactivity due to dopamine depletion, which could be reversed by the D2 receptor agonist quinpirole. Thus, hMOs faithfully model network wide electrophysiological changes associated with PD progression and serve as a promising tool for PD research and personalized medicine.

Advances in neuroimaging technology, like functional near-infrared spectroscopy (fNIRS), support the evaluation of task-dependent brain activity during functional tasks, like balance, in healthy and clinical populations. To date, there have been no studies examining how interventions, like yoga, impact task-dependent brain activity in adults with chronic acquired brain injury (ABI). This pilot study compared eight weeks of group yoga (active) to group exercise (control) on balance and task-dependent neural activity outcomes. Twenty-three participants were randomized to yoga (n = 13) or exercise groups (n = 10). Neuroimaging and balance performance data were collected simultaneously using a force plate and mobile fNIRS device before and after interventions. Linear mixed-effects models were used to evaluate the effect of time, time x group interactions, and simple (i.e., within-group) effects. Regardless of group, all participants had significant balance improvements after the interventions. Additionally, regardless of group, there were significant changes in task-dependent neural activity, as well as distinct changes in neural activity within each group. In summary, using advances in sensor technology, we were able to demonstrate preliminary evidence of intervention-induced changes in balance and neural activity in adults with ABI. These preliminary results may provide an important foundation for future neurorehabilitation studies that leverage neuroimaging methods, like fNIRS.

Deep brain stimulation (DBS) has been used in the clinic to treat Parkinson's disease (PD) and other neuropsychiatric disorders. Our previous work has shown that DBS in the subthalamic nucleus (STN) can improve major motor deficits, and induce a variety of neural responses in rats with unilateral dopamine (DA) lesions. In the present study, we examined the effect of STN DBS on reaction time (RT) performance and parallel changes in neural activity in the cortico-basal ganglia regions of partially bilateral DA- lesioned rats. We recorded neural activity with a multiple-channel single-unit electrode system in the primary motor cortex (MI), the STN, and the substantia nigra pars reticulata (SNr) during RT test. RT performance was severely impaired following bilateral injection of 6-OHDA into the dorsolateral part of the striatum. In parallel with such behavioral impairments, the number of responsive neurons to different behavioral events was remarkably decreased after DA lesion. Bilateral STN DBS improved RT performance in 6-OHDA lesioned rats, and restored operational behavior-related neural responses in cortico-basal ganglia regions. These behavioral and electrophysiological effects of DBS lasted nearly an hour after DBS termination. These results demonstrate that a partial DA lesion-induced impairment of RT performance is associated with changes in neural activity in the cortico-basal ganglia circuit. Furthermore, STN DBS can reverse changes in behavior and neural activity caused by partial DA depletion. The observed long-lasting beneficial effect of STN DBS suggests the involvement of the mechanism of neural plasticity in modulating cortico-basal ganglia circuits.

Pilot study of a mobile application-based intervention to induce changes in neural activity in the frontal region and behaviors in children with attention deficit hyperactivity disorder and/or intellectual disability

Genetically Encoded Calcium Indicators (GECIs) are fundamental tools in neuroscience for monitoring real-time neural activity through calcium imaging. These sophisticated indicators, such as GCaMP and RCaMP, allow for non-invasive, precise measurement of intracellular calcium dynamics with high spatial and temporal resolution. Leveraging fluorescence intensity data, researchers can uncover the intricate correlations among neurons, elucidating the complex communication underlying brain function. Moreover, advancements in multicolor fluorescence imaging enable simultaneous monitoring of multiple neural processes, improving our understanding of the interplay between diverse cellular systems. This approach integrates various indicators that fluoresce in different colors, such as GCaMP (green) and RCaMP (red), which enhances visualization capabilities and minimizes spectral overlap. While these technologies have transformed biological research, significant challenges remain, including signal noise, photobleaching, and spectral interference. Addressing these challenges requires robust data processing techniques, such as advanced filters, standardization methods, and computational tools, to extract reliable insights from fluorescence imaging data. Additionally, the development of far-red and near-infrared GECIs continues to expand imaging depth and reduce interference in complex biological systems. This research highlights the ongoing advancements in GCaMP data processing methods, multicolor fluorescence imaging, and computational techniques, underscoring their potential to revolutionize our understanding of neural activity and dynamic cellular processes. Future work aims to overcome these technical challenges to enhance precision and broaden the applications of GECIs in neuroscience and beyond.