Wide-Field Calcium Imaging of Dynamic Cortical Networks during Locomotion

Brain-wide neural recordings in mice navigating physical spaces enabled by robotic neural recording headstages

Technologies that can record neural activity at cellular resolution at multiple spatial and temporal scales are typically much larger than the animals that are being recorded from and are thus limited to recording from head-fixed subjects. Here we have engineered robotic neural recording devices-'cranial exoskeletons'-that assist mice in maneuvering recording headstages that are orders of magnitude larger and heavier than the mice, while they navigate physical behavioral environments. We discovered optimal controller parameters that enable mice to locomote at physiologically realistic velocities while maintaining natural walking gaits. We show that mice learn to work with the robot to make turns and perform decision-making tasks. Robotic imaging and electrophysiology headstages were used to record recordings of Ca2+ activity of thousands of neurons distributed across the dorsal cortex and spiking activity of hundreds of neurons across multiple brain regions and multiple days, respectively.

Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data

BACKGROUND

Wide-field calcium imaging (WFCI) with genetically encoded calcium indicators allows for spatiotemporal recordings of neuronal activity in mice. When applied to the study of sleep, WFCI data are manually scored into the sleep states of wakefulness, non-REM (NREM) and REM by use of adjunct EEG and EMG recordings. However, this process is time-consuming, invasive and often suffers from low inter- and intra-rater reliability. Therefore, an automated sleep state classification method that operates on spatiotemporal WFCI data is desired.

NEW METHOD

A hybrid network architecture consisting of a convolutional neural network (CNN) to extract spatial features of image frames and a bidirectional long short-term memory network (BiLSTM) with attention mechanism to identify temporal dependencies among different time points was proposed to classify WFCI data into states of wakefulness, NREM and REM sleep.

RESULTS

Sleep states were classified with an accuracy of 84 % and Cohen's κ of 0.64. Gradient-weighted class activation maps revealed that the frontal region of the cortex carries more importance when classifying WFCI data into NREM sleep while posterior area contributes most to the identification of wakefulness. The attention scores indicated that the proposed network focuses on short- and long-range temporal dependency in a state-specific manner.

COMPARISON WITH EXISTING METHOD

On a held out, repeated 3-hour WFCI recording, the CNN-BiLSTM achieved a κ of 0.67, comparable to a κ of 0.65 corresponding to the human EEG/EMG-based scoring.

CONCLUSIONS

The CNN-BiLSTM effectively classifies sleep states from spatiotemporal WFCI data and will enable broader application of WFCI in sleep research.

Cortex-wide characterization of decision-making neural dynamics during spatial navigation

Decision-making during freely moving behaviors involves complex interactions among many cortical and subcortical regions. However, the spatiotemporal coordination across regions to generate a decision is less understood. Using a head-mounted widefield microscope, cortex-wide calcium dynamics were recorded in mice expressing GCaMP7f as they navigated an 8-maze using two paradigms. The first was an alternating pattern that required short term memory of the previous trial to make the correct decision and the second after a rule change to a fixed path in which rewards were delivered only on the left side. Identification of cortex-wide activation states revealed differences between the two paradigms. There was a higher probability for a visual/retrosplenial cortical state during the alternating paradigm and higher probability of a secondary motor and posterior parietal state during left-only. Three state sequences (motifs) illustrated both anterior and posterior activity propagations across the cortex. The anterior propagating motifs had the highest probability around the decision and propagating motifs peaked following the decision. The latter, likely reflecting internal feedback to influence future actions, were more common in the left-only paradigm. Therefore, the probabilities and sequences of cortical states differ when working memory is required versus a fixed trajectory reward paradigm.

Network statistics of the whole-brain connectome of Drosophila

Brains comprise complex networks of neurons and connections, similar to the nodes and edges of artificial networks. Network analysis applied to the wiring diagrams of brains can offer insights into how they support computations and regulate the flow of information underlying perception and behaviour. The completion of the first whole-brain connectome of an adult fly, containing over 130,000 neurons and millions of synaptic connections1-3, offers an opportunity to analyse the statistical properties and topological features of a complete brain. Here we computed the prevalence of two- and three-node motifs, examined their strengths, related this information to both neurotransmitter composition and cell type annotations4,5, and compared these metrics with wiring diagrams of other animals. We found that the network of the fly brain displays rich-club organization, with a large population (30% of the connectome) of highly connected neurons. We identified subsets of rich-club neurons that may serve as integrators or broadcasters of signals. Finally, we examined subnetworks based on 78 anatomically defined brain regions or neuropils. These data products are shared within the FlyWire Codex ( https://codex.flywire.ai ) and should serve as a foundation for models and experiments exploring the relationship between neural activity and anatomical structure.

Wide-field calcium imaging of cortical activation and functional connectivity in externally- and internally-driven locomotion

The role of the cerebral cortex in self-initiated versus sensory-driven movements is central to understanding volitional action. Whether the differences in these two movement classes are due to specific cortical areas versus more cortex-wide engagement is debated. Using wide-field Ca2+ imaging, we compared neural dynamics during spontaneous and motorized treadmill locomotion, determining the similarities and differences in cortex-wide activation and functional connectivity (FC). During motorized locomotion, the cortex exhibits greater activation globally prior to and during locomotion starting compared to spontaneous and less during steady-state walking, during stopping, and after termination. Both conditions are characterized by FC increases in anterior secondary motor cortex (M2) nodes and decreases in all other regions. There are also cortex-wide differences; most notably, M2 decreases in FC with all other nodes during motorized stopping and after termination. Therefore, both internally- and externally-generated movements widely engage the cortex, with differences represented in cortex-wide activation and FC patterns.

Pan-cortical cellular imaging in freely behaving mice using a miniaturized micro-camera array microscope (mini-MCAM)

Understanding how circuits in the brain simultaneously coordinate their activity to mediate complex ethnologically relevant behaviors requires recording neural activities from distributed populations of neurons in freely behaving animals. Current miniaturized imaging microscopes are typically limited to imaging a relatively small field of view, precluding the measurement of neural activities across multiple brain regions. Here we present a miniaturized micro-camera array microscope (mini-MCAM) that consists of four fluorescence imaging micro-cameras, each capable of capturing neural activity across a 4.5 mm x 2.55 mm field of view (FOV). Cumulatively, the mini-MCAM images over 30 mm 2 area of sparsely expressed GCaMP6s neurons distributed throughout the dorsal cortex, in regions including the primary and secondary motor, somatosensory, visual, retrosplenial, and association cortices across both hemispheres. We demonstrate cortex-wide cellular resolution in vivo Calcium (Ca 2+ ) imaging using the mini-MCAM in both head-fixed and freely behaving mice.

Wide-field imaging in behaving mice as a tool to study cognitive function

Cognitive functions are mediated through coordinated and dynamic neuronal responses that involve many different areas across the brain. Therefore, it is of high interest to simultaneously record neuronal activity from as many brain areas as possible while the subject performs a cognitive behavioral task. One of the emerging tools to achieve a mesoscopic field of view is wide-field imaging of cortex-wide dynamics in mice. Wide-field imaging is cost-effective, user-friendly, and enables obtaining cortex-wide signals from mice performing complex and demanding cognitive tasks. Importantly, wide-field imaging offers an unbiased cortex-wide observation that sheds light on overlooked cortical regions and highlights parallel processing circuits. Recent wide-field imaging studies have shown that multi-area cortex-wide patterns, rather than just a single area, are involved in encoding cognitive functions. The optical properties of wide-field imaging enable imaging of different brain signals, such as layer-specific, inhibitory subtypes, or neuromodulation signals. Here, I review the main advantages of wide-field imaging in mice, review the recent literature, and discuss future directions of the field. It is expected that wide-field imaging in behaving mice will continue to gain popularity and aid in understanding the mesoscale dynamics underlying cognitive function.

Special Section Guest Editorial: Open-source neurophotonic tools for neuroscience

The editorial completes the Neurophotonics special series on open-source neurophotonic tools for neuroscience.

Decoding state-dependent cortical-cerebellar cellular functional connectivity in the mouse brain

The cortex and cerebellum form multi-synaptic reciprocal connections. We investigate the functional connectivity between single spiking cerebellar neurons and the population activity of the mouse dorsal cortex using mesoscale imaging. Cortical representations of individual cerebellar neurons vary significantly across different brain states but are drawn from a common set of cortical networks. These cortical-cerebellar connectivity features are observed in mossy fibers and Purkinje cells as well as neurons in different cerebellar lobules, albeit with variations across cell types and regions. Complex spikes of Purkinje cells preferably associate with the sensorimotor cortex, whereas simple spikes display more diverse cortical connectivity patterns. The spontaneous functional connectivity patterns align with cerebellar neurons' functional responses to external stimuli in a modality-specific manner. The tuning properties of subsets of cerebellar neurons differ between anesthesia and awake states, mirrored by state-dependent changes in their long-range functional connectivity patterns with mesoscale cortical activity.

Cerebral cortical functional hyperconnectivity in a mouse model of spinocerebellar ataxia type 8 (SCA8)

Spinocerebellar Ataxia Type 8 (SCA8) is an inherited neurodegenerative disease caused by a bidirectionally expressed CTG●CAG expansion mutation in the ATXN-8 and ATXN8-OS genes. While primarily a motor disorder, psychiatric and cognitive symptoms have been reported. It is difficult to elucidate how the disease alters brain function in areas with little or no degeneration producing both motor and cognitive symptoms. Using transparent polymer skulls and CNS-wide GCaMP6f expression, we studied neocortical networks throughout SCA8 progression using wide-field Ca2+ imaging in a transgenic mouse model of SCA8. We observed that neocortical networks in SCA8+ mice were hyperconnected globally which led to network configurations with increased global efficiency and centrality. At the regional level, significant network changes occurred in nearly all cortical regions, however mainly involved sensory and association cortices. Changes in functional connectivity in anterior motor regions worsened later in the disease. Near perfect decoding of animal genotype was obtained using a generalized linear model based on canonical correlation strengths between activity in cortical regions. The major contributors to decoding were concentrated in the somatosensory, higher visual and retrosplenial cortices and occasionally extended into the motor regions, demonstrating that the areas with the largest network changes are predictive of disease state.

Early and widespread engagement of the cerebellum during hippocampal epileptiform activity Format: Brief Communication

Despite research illustrating the cerebellum may be a critical circuit element in the epilepsies, remarkably little is known about cerebellar engagement during seizures. We therefore implemented a novel method for repeated imaging of the cerebellum in awake, chronically epileptic animals. We found widespread changes in cerebellar calcium signals during behavioral seizures and during hippocampal seizures that remained electrographic only, arguing against cerebellar modulation simply reflecting motor components. Moreover, even brief interictal spikes produced widespread alterations in cerebellar activity. Changes were noted in the anterior and posterior cerebellum, along the midline, and both ipsilaterally and contralaterally to the seizure focus. Remarkably, changes in the cerebellum also occurred prior to any noticeable change in the hippocampal electrographic recordings, suggesting a special relationship between the cerebellum and hippocampal epileptiform activity. Together these results underscore the importance of the cerebellum in epilepsy, warranting a more consistent consideration of the cerebellum when evaluating epilepsy patients.

Group ICA of wide-field calcium imaging data reveals the retrosplenial cortex as a major contributor to cortical activity during anesthesia

Large-scale cortical dynamics play a crucial role in many cognitive functions such as goal-directed behaviors, motor learning and sensory processing. It is well established that brain states including wakefulness, sleep, and anesthesia modulate neuronal firing and synchronization both within and across different brain regions. However, how the brain state affects cortical activity at the mesoscale level is less understood. This work aimed to identify the cortical regions engaged in different brain states. To this end, we employed group ICA (Independent Component Analysis) to wide-field imaging recordings of cortical activity in mice during different anesthesia levels and the awake state. Thanks to this approach we identified independent components (ICs) representing elements of the cortical networks that are common across subjects under decreasing levels of anesthesia toward the awake state. We found that ICs related to the retrosplenial cortices exhibited a pronounced dependence on brain state, being most prevalent in deeper anesthesia levels and diminishing during the transition to the awake state. Analyzing the occurrence of the ICs we found that activity in deeper anesthesia states was characterized by a strong correlation between the retrosplenial components and this correlation decreases when transitioning toward wakefulness. Overall these results indicate that during deeper anesthesia states coactivation of the posterior-medial cortices is predominant over other connectivity patterns, whereas a richer repertoire of dynamics is expressed in lighter anesthesia levels and the awake state.

Spatial nonstationarity of image noise in widefield optical imaging and its effects on cluster-based inference for resting-state functional connectivity

BACKGROUND

Resting-state functional connectivity (RSFC) analysis with widefield optical imaging (WOI) is a potentially powerful tool to develop imaging biomarkers in mouse models of disease before translating them to human neuroimaging with functional magnetic resonance imaging (fMRI). The delineation of such biomarkers depends on rigorous statistical analysis. However, statistical understanding of WOI data is limited. In particular, cluster-based analysis of neuroimaging data depends on assumptions of spatial stationarity (i.e., that the distribution of cluster sizes under the null is equal at all brain locations). Whether actual data deviate from this assumption has not previously been examined in WOI.

NEW METHOD

In this manuscript, we characterize the effects of spatial nonstationarity in WOI RSFC data and adapt a "two-pass" technique from fMRI to correct cluster sizes and mitigate spatial bias, both parametrically and nonparametrically. These methods are tested on multi-institutional data.

RESULTS AND COMPARISON WITH EXISTING METHODS

We find that spatial nonstationarity has a substantial effect on inference in WOI RSFC data with false positives much more likely at some brain regions than others. This pattern of bias varies between imaging systems, contrasts, and mouse ages, all of which could affect experimental reproducibility if not accounted for.

CONCLUSIONS

Both parametric and nonparametric corrections for nonstationarity result in significant improvements in spatial bias. The proposed methods are simple to implement and will improve the robustness of inference in optical neuroimaging data.

All-optical interrogation of millimeter-scale networks and application to developing ferret cortex

BACKGROUND

Perception and behavior require coordinated activity of thousands of neurons operating in networks that span millimeters of brain area. In vivo calcium imaging approaches have proven exceptionally powerful for examining the structure of these networks at large scales, and optogenetics can allow for causal manipulations of large populations of neurons. However, realizing the full potential of these techniques requires the ability to simultaneously measure and manipulate distinct circuit elements on the scale of millimeters.

NEW METHOD

We describe an opto-macroscope, an artifact-free, all-optical system capable of delivering patterned optogenetic stimulation with high spatial and temporal resolution across millimeters of brain while simultaneously imaging functional neural activity.

RESULTS

We find that this approach provides direct manipulation of cortical regions ranging from hundreds of microns to several millimeters in area, allowing for the perturbation of individual brain areas or networks of functional domains. Using this system we find that spatially complex endogenous networks in the developing ferret visual cortex can be readily reactivated by precisely designed patterned optogenetic stimuli.

COMPARISON WITH EXISTING METHODS

Our opto-macroscope extends current all-optical optogenetic approaches which operate on a cellular scale with multiphoton stimulation, and are poorly suited to investigate the millimeter-scale of many functional networks. It also builds upon other mesoscopic optogenetic techniques that lack simultaneous optical readouts of neural activity.

CONCLUSIONS

The large-scale all-optical capabilities of our system make it a powerful new tool for investigating the contribution of cortical domains and brain areas to the functional neural networks that underlie perception and behavior.

Network Statistics of the Whole-Brain Connectome of Drosophila

Brains comprise complex networks of neurons and connections. Network analysis applied to the wiring diagrams of brains can offer insights into how brains support computations and regulate information flow. The completion of the first whole-brain connectome of an adult Drosophila, the largest connectome to date, containing 130,000 neurons and millions of connections, offers an unprecedented opportunity to analyze its network properties and topological features. To gain insights into local connectivity, we computed the prevalence of two- and three-node network motifs, examined their strengths and neurotransmitter compositions, and compared these topological metrics with wiring diagrams of other animals. We discovered that the network of the fly brain displays rich club organization, with a large population (30% percent of the connectome) of highly connected neurons. We identified subsets of rich club neurons that may serve as integrators or broadcasters of signals. Finally, we examined subnetworks based on 78 anatomically defined brain regions or neuropils. These data products are shared within the FlyWire Codex and will serve as a foundation for models and experiments exploring the relationship between neural activity and anatomical structure.

Traumatic brain injury disrupts state-dependent functional cortical connectivity in a mouse model

Traumatic brain injury (TBI) is the leading cause of death in young people and can cause cognitive and motor dysfunction and disruptions in functional connectivity between brain regions. In human TBI patients and rodent models of TBI, functional connectivity is decreased after injury. Recovery of connectivity after TBI is associated with improved cognition and memory, suggesting an important link between connectivity and functional outcome. We examined widespread alterations in functional connectivity following TBI using simultaneous widefield mesoscale GCaMP7c calcium imaging and electrocorticography (ECoG) in mice injured using the controlled cortical impact (CCI) model of TBI. Combining CCI with widefield cortical imaging provides us with unprecedented access to characterize network connectivity changes throughout the entire injured cortex over time. Our data demonstrate that CCI profoundly disrupts functional connectivity immediately after injury, followed by partial recovery over 3 weeks. Examining discrete periods of locomotion and stillness reveals that CCI alters functional connectivity and reduces theta power only during periods of behavioral stillness. Together, these findings demonstrate that TBI causes dynamic, behavioral state-dependent changes in functional connectivity and ECoG activity across the cortex.

Non-consummatory behavior signals predict aversion-resistant alcohol drinking in head-fixed mice

A key facet of alcohol use disorder is continuing to drink alcohol despite negative consequences (so called "aversion-resistant drinking"). In this study, we sought to assess the degree to which head-fixed mice exhibit aversion-resistant drinking and to leverage behavioral analysis techniques available in head-fixture to relate non-consummatory behaviors to aversion-resistant drinking. We assessed aversion-resistant drinking in head-fixed female and male C57BL/6 J mice. We adulterated 20% (v/v) alcohol with varying concentrations of the bitter tastant quinine to measure the degree to which mice would continue to drink despite this aversive stimulus. We recorded high-resolution video of the mice during head-fixed drinking, tracked body parts with machine vision tools, and analyzed body movements in relation to consumption. Female and male head-fixed mice exhibited heterogenous levels of aversion-resistant drinking. Additionally, non-consummatory behaviors, such as paw movement and snout movement, were related to the intensity of aversion-resistant drinking. These studies demonstrate that head-fixed mice exhibit aversion-resistant drinking and that non-consummatory behaviors can be used to assess perceived aversiveness in this paradigm. Furthermore, these studies lay the groundwork for future experiments that will utilize advanced electrophysiological techniques to record from large populations of neurons during aversion-resistant drinking to understand the neurocomputational processes that drive this clinically relevant behavior. This article is part of the Special Issue on "PFC circuit function in psychiatric disease and relevant models".

Arousal as a universal embedding for spatiotemporal brain dynamics

Neural activity in awake organisms shows widespread and spatiotemporally diverse correlations with behavioral and physiological measurements. We propose that this covariation reflects in part the dynamics of a unified, arousal-related process that regulates brain-wide physiology on the timescale of seconds. Taken together with theoretical foundations in dynamical systems, this interpretation leads us to a surprising prediction: that a single, scalar measurement of arousal (e.g., pupil diameter) should suffice to reconstruct the continuous evolution of multimodal, spatiotemporal measurements of large-scale brain physiology. To test this hypothesis, we perform multimodal, cortex-wide optical imaging and behavioral monitoring in awake mice. We demonstrate that spatiotemporal measurements of neuronal calcium, metabolism, and blood-oxygen can be accurately and parsimoniously modeled from a low-dimensional state-space reconstructed from the time history of pupil diameter. Extending this framework to behavioral and electrophysiological measurements from the Allen Brain Observatory, we demonstrate the ability to integrate diverse experimental data into a unified generative model via mappings from an intrinsic arousal manifold. Our results support the hypothesis that spontaneous, spatially structured fluctuations in brain-wide physiology-widely interpreted to reflect regionally-specific neural communication-are in large part reflections of an arousal-related process. This enriched view of arousal dynamics has broad implications for interpreting observations of brain, body, and behavior as measured across modalities, contexts, and scales.

Non-Consummatory Behavior Signals Predict Aversion-Resistant Alcohol Drinking in Head-Fixed Mice

A key facet of alcohol use disorder is continuing to drink alcohol despite negative consequences (so called "aversion-resistant drinking"). In this study, we sought to assess the degree to which head-fixed mice exhibit aversion-resistant drinking and to leverage behavioral analysis techniques available in head-fixture to relate non-consummatory behaviors to aversion-resistant drinking. We assessed aversion-resistant drinking in head-fixed female and male C57BL/6J mice. We adulterated 20% (v/v) alcohol with varying concentrations of the bitter tastant quinine to measure the degree to which mice would continue to drink despite this aversive stimulus. We recorded high-resolution video of the mice during head-fixed drinking, tracked body parts with machine vision tools, and analyzed body movements in relation to consumption. Female and male head-fixed mice exhibited heterogenous levels of aversion-resistant drinking. Additionally, non-consummatory behaviors, such as paw movement and snout movement, were related to the intensity of aversion-resistant drinking. These studies demonstrate that head-fixed mice exhibit aversion-resistant drinking and that non-consummatory behaviors can be used to assess perceived aversiveness in this paradigm. Furthermore, these studies lay the groundwork for future experiments that will utilize advanced electrophysiological techniques to record from large populations of neurons during aversion-resistant drinking to understand the neurocomputational processes that drive this clinically relevant behavior.

Why is everyone talking about brain state?

The rapid and coordinated propagation of neural activity across the brain provides the foundation for complex behavior and cognition. Technical advances across neuroscience subfields have advanced understanding of these dynamics, but points of convergence are often obscured by semantic differences, creating silos of subfield-specific findings. In this review we describe how a parsimonious conceptualization of brain state as the fundamental building block of whole-brain activity offers a common framework to relate findings across scales and species. We present examples of the diverse techniques commonly used to study brain states associated with physiology and higher-order cognitive processes, and discuss how integration across them will enable a more comprehensive and mechanistic characterization of the neural dynamics that are crucial to survival but are disrupted in disease.

Strategy dependent recruitment of distributed cortical circuits during spatial navigation

Spatial navigation is a complex cognitive process that involves neural computations in distributed regions of the brain. Little is known about how cortical regions are coordinated when animals navigate novel spatial environments or how that coordination changes as environments become familiar. We recorded mesoscale calcium (Ca2+) dynamics across large swathes of the dorsal cortex in mice solving the Barnes maze, a 2D spatial navigation task where mice used random, serial, and spatial search strategies to navigate to the goal. Cortical dynamics exhibited patterns of repeated calcium activity with rapid and abrupt shifts between cortical activation patterns at sub-second time scales. We used a clustering algorithm to decompose the spatial patterns of cortical calcium activity in a low dimensional state space, identifying 7 states, each corresponding to a distinct spatial pattern of cortical activation, sufficient to describe the cortical dynamics across all the mice. When mice used serial or spatial search strategies to navigate to the goal, the frontal regions of the cortex were reliably activated for prolonged durations of time (> 1s) shortly after trial initiation. These frontal cortex activation events coincided with mice approaching the edge of the maze from the center and were preceded by temporal sequences of cortical activation patterns that were distinct for serial and spatial search strategies. In serial search trials, frontal cortex activation events were preceded by activation of the posterior regions of the cortex followed by lateral activation of one hemisphere. In spatial search trials, frontal cortical events were preceded by activation of posterior regions of the cortex followed by broad activation of the lateral regions of the cortex. Our results delineated cortical components that differentiate goal- and non-goal oriented spatial navigation strategies.

Not everything, not everywhere, not all at once: a study of brain-wide encoding of movement

Activity related to movement is found throughout sensory and motor regions of the brain. However, it remains unclear how movement-related activity is distributed across the brain and whether systematic differences exist between brain areas. Here, we analyzed movement related activity in brain-wide recordings containing more than 50,000 neurons in mice performing a decision-making task. Using multiple techniques, from markers to deep neural networks, we find that movement-related signals were pervasive across the brain, but systematically differed across areas. Movement-related activity was stronger in areas closer to the motor or sensory periphery. Delineating activity in terms of sensory- and motor-related components revealed finer scale structures of their encodings within brain areas. We further identified activity modulation that correlates with decision-making and uninstructed movement. Our work charts out a largescale map of movement encoding and provides a roadmap for dissecting different forms of movement and decision-making related encoding across multi-regional neural circuits.

Virtual reality-based real-time imaging reveals abnormal cortical dynamics during behavioral transitions in a mouse model of autism

Functional connectivity (FC) can provide insight into cortical circuit dysfunction in neuropsychiatric disorders. However, dynamic changes in FC related to locomotion with sensory feedback remain to be elucidated. To investigate FC dynamics in locomoting mice, we develop mesoscopic Ca2+ imaging with a virtual reality (VR) environment. We find rapid reorganization of cortical FC in response to changing behavioral states. By using machine learning classification, behavioral states are accurately decoded. We then use our VR-based imaging system to study cortical FC in a mouse model of autism and find that locomotion states are associated with altered FC dynamics. Furthermore, we identify FC patterns involving the motor area as the most distinguishing features of the autism mice from wild-type mice during behavioral transitions, which might correlate with motor clumsiness in individuals with autism. Our VR-based real-time imaging system provides crucial information to understand FC dynamics linked to behavioral abnormality of neuropsychiatric disorders.

Wide-field calcium imaging of cortical activation and functional connectivity in externally- and internally-driven locomotion

The neural dynamics underlying self-initiated versus sensory driven movements is central to understanding volitional action. Upstream motor cortices are associated with the generation of internally-driven movements over externally-driven. Here we directly compare cortical dynamics during internally- versus externally-driven locomotion using wide-field Ca2+ imaging. We find that secondary motor cortex (M2) plays a larger role in internally-driven spontaneous locomotion transitions, with increased M2 functional connectivity during starting and stopping than in the externally-driven, motorized treadmill locomotion. This is not the case in steady-state walk. In addition, motorized treadmill and spontaneous locomotion are characterized by markedly different patterns of cortical activation and functional connectivity at the different behavior periods. Furthermore, the patterns of fluorescence activation and connectivity are uncorrelated. These experiments reveal widespread and striking differences in the cortical control of internally- and externally-driven locomotion, with M2 playing a major role in the preparation and execution of the self-initiated state.

Distinct mesoscale cortical dynamics encode search strategies during spatial navigation

Spatial navigation is a complex cognitive process that involves neural computations in distributed regions of the brain. Little is known about how cortical regions are coordinated when animals navigate novel spatial environments or how that coordination changes as environments become familiar. We recorded mesoscale calcium (Ca2+) dynamics across large swathes of the dorsal cortex in mice solving the Barnes maze, a 2D spatial navigation task where mice used random, serial, and spatial search strategies to navigate to the goal. Cortical dynamics exhibited patterns of repeated calcium activity with rapid and abrupt shifts between cortical activation patterns at sub-second time scales. We used a clustering algorithm to decompose the spatial patterns of cortical calcium activity in a low dimensional state space, identifying 7 states, each corresponding to a distinct spatial pattern of cortical activation, sufficient to describe the cortical dynamics across all the mice. When mice used serial or spatial search strategies to navigate to the goal, the frontal regions of the cortex were reliably activated for prolonged durations of time (> 1s) shortly after trial initiation. These frontal cortex activation events coincided with mice approaching the edge of the maze from the center and were preceded by temporal sequences of cortical activation patterns that were distinct for serial and spatial search strategies. In serial search trials, frontal cortex activation events were preceded by activation of the posterior regions of the cortex followed by lateral activation of one hemisphere. In spatial search trials, frontal cortical events were preceded by activation of posterior regions of the cortex followed by broad activation of the lateral regions of the cortex. Our results delineated cortical components that differentiate goal- and non-goal oriented spatial navigation strategies.

Sharp cell-type-identity changes differentiate the retrosplenial cortex from the neocortex

The laminae of the neocortex are fundamental processing layers of the mammalian brain. Notably, such laminae are believed to be relatively stereotyped across short spatial scales such that shared laminae between nearby brain regions exhibit similar constituent cells. Here, we consider a potential exception to this rule by studying the retrosplenial cortex (RSC), a brain region known for sharp cytoarchitectonic differences across its granular-dysgranular border. Using a variety of transcriptomics techniques, we identify, spatially map, and interpret the excitatory cell-type landscape of the mouse RSC. In doing so, we uncover that RSC gene expression and cell types change sharply at the granular-dysgranular border. Additionally, supposedly homologous laminae between the RSC and the neocortex are effectively wholly distinct in their cell-type composition. In collection, the RSC exhibits a variety of intrinsic cell-type specializations and embodies an organizational principle wherein cell-type identities can vary sharply within and between brain regions.

Cortical glutamatergic projection neuron types contribute to distinct functional subnetworks

The cellular basis of cerebral cortex functional architecture remains not well understood. A major challenge is to monitor and decipher neural network dynamics across broad cortical areas yet with projection-neuron-type resolution in real time during behavior. Combining genetic targeting and wide-field imaging, we monitored activity dynamics of subcortical-projecting (PTFezf2) and intratelencephalic-projecting (ITPlxnD1) types across dorsal cortex of mice during different brain states and behaviors. ITPlxnD1 and PTFezf2 neurons showed distinct activation patterns during wakeful resting, during spontaneous movements and upon sensory stimulation. Distinct ITPlxnD1 and PTFezf2 subnetworks were dynamically tuned to different sensorimotor components of a naturalistic feeding behavior, and optogenetic inhibition of ITsPlxnD1 and PTsFezf2 in subnetwork nodes disrupted distinct components of this behavior. Lastly, ITPlxnD1 and PTFezf2 projection patterns are consistent with their subnetwork activation patterns. Our results show that, in addition to the concept of columnar organization, dynamic areal and projection-neuron-type specific subnetworks are a key feature of cortical functional architecture linking microcircuit components with global brain networks.

To be and not to be: wide-field Ca2+ imaging reveals neocortical functional segmentation combines stability and flexibility

The stability and flexibility of the functional parcellation of the cerebral cortex is fundamental to how familiar and novel information is both represented and stored. We leveraged new advances in Ca2+ sensors and microscopy to understand the dynamics of functional segmentation in the dorsal cerebral cortex. We performed wide-field Ca2+ imaging in head-fixed mice and used spatial independent component analysis (ICA) to identify independent spatial sources of Ca2+ fluorescence. The imaging data were evaluated over multiple timescales and discrete behaviors including resting, walking, and grooming. When evaluated over the entire dataset, a set of template independent components (ICs) were identified that were common across behaviors. Template ICs were present across a range of timescales, from days to 30 seconds, although with lower occurrence probability at shorter timescales, highlighting the stability of the functional segmentation. Importantly, unique ICs emerged at the shorter duration timescales that could act to transiently refine the cortical network. When data were evaluated by behavior, both common and behavior-specific ICs emerged. Each behavior is composed of unique combinations of common and behavior-specific ICs. These observations suggest that cerebral cortical functional segmentation exhibits considerable spatial stability over time and behaviors while retaining the flexibility for task-dependent reorganization.

Fully desktop fabricated flexible graphene electrocorticography (ECoG) arrays

Objective:Flexible Electrocorticography (ECoG) electrode arrays that conform to the cortical surface and record surface field potentials from multiple brain regions provide unique insights into how computations occurring in distributed brain regions mediate behavior. Specialized microfabrication methods are required to produce flexible ECoG devices with high-density electrode arrays. However, these fabrication methods are challenging for scientists without access to cleanroom fabrication equipment.Results:Here we present a fully desktop fabricated flexible graphene ECoG array. First, we synthesized a stable, conductive ink via liquid exfoliation of Graphene in Cyrene. Next, we established a stencil-printing process for patterning the graphene ink via laser-cut stencils on flexible polyimide substrates. Benchtop tests indicate that the graphene electrodes have good conductivity of ∼1.1 × 103S cm-1, flexibility to maintain their electrical connection under static bending, and electrochemical stability in a 15 d accelerated corrosion test. Chronically implanted graphene ECoG devices remain fully functional for up to 180 d, with averagein vivoimpedances of 24.72 ± 95.23 kΩ at 1 kHz. The ECoG device can measure spontaneous surface field potentials from mice under awake and anesthetized states and sensory stimulus-evoked responses.Significance:The stencil-printing fabrication process can be used to create Graphene ECoG devices with customized electrode layouts within 24 h using commonly available laboratory equipment.

Chronic multiscale resolution of mouse brain networks using combined mesoscale cortical imaging and subcortical fiber photometry

SIGNIFICANCE

Genetically encoded optical probes to image calcium levels in neurons in vivo are used widely as a real-time measure of neuronal activity in the brain. Mesoscale calcium imaging through a cranial window provides a method of studying the interaction of circuit activity between cortical areas but lacks access to subcortical regions.

AIM

We have developed an optical and surgical preparation that preserves wide-field imaging of the cortical surface while also permitting access to specific subcortical networks.

APPROACH

This was achieved using an optical fiber implanted in the striatum, along with a bilateral widefield cranial window, enabling simultaneous mesoscale cortical imaging and subcortical fiber photometry recording of calcium signals in a transgenic animal expressing GCaMP. Subcortical signals were collected from the dorsal regions of the striatum. We combined this approach with multiple sensory-motor tasks, including specific auditory and visual stimulation, and video monitoring of animal movements and pupillometry during head-fixed behaviors.

RESULTS

We found high correlations between cortical and striatal activity in response to sensory stimulation or movement. Furthermore, spontaneous activity recordings revealed that specific motifs of cortical activity are correlated with presynaptic activity recorded in the striatum, enabling us to select for corticostriatal activity motifs.

CONCLUSION

We believe that this method can be utilized to reveal not only global patterns but also cell-specific connectivity that provides insight into corticobasal ganglia circuit organization.

Wide-field calcium imaging reveals widespread changes in cortical functional connectivity following mild traumatic brain injury in the mouse

>2.5 million individuals in the United States suffer mild traumatic brain injuries (mTBI) annually. Mild TBI is characterized by a brief period of altered consciousness, without objective findings of anatomic injury on clinical imaging or physical deficit on examination. Nevertheless, a subset of mTBI patients experience persistent subjective symptoms and repeated mTBI can lead to quantifiable neurological deficits, suggesting that each mTBI alters neurophysiology in a deleterious manner not detected using current clinical methods. To better understand these effects, we performed mesoscopic Ca²⁺ imaging in mice to evaluate how mTBI alters patterns of neuronal interactions across the dorsal cerebral cortex. Spatial Independent Component Analysis (sICA) and Localized semi-Nonnegative Matrix Factorization (LocaNMF) were used to quantify changes in cerebral functional connectivity (FC). Repetitive, mild, controlled cortical impacts induce temporary neuroinflammatory responses, characterized by increased density of microglia exhibiting de-ramified morphology. These temporary neuro-inflammatory changes were not associated with compromised cognitive performance in the Barnes maze or motor function as assessed by rotarod. However, long-term alterations in functional connectivity (FC) were observed. Widespread, bilateral changes in FC occurred immediately following impact and persisted for up to 7 weeks, the duration of the experiment. Network alterations include decreases in global efficiency, clustering coefficient, and nodal strength, thereby disrupting functional interactions and information flow throughout the dorsal cerebral cortex. A subnetwork analysis shows the largest disruptions in FC were concentrated near the impact site. Therefore, mTBI induces a transient neuroinflammation, without alterations in cognitive or motor behavior, and a reorganized cortical network evidenced by the widespread, chronic alterations in cortical FC.

Wide-Field Calcium Imaging of Neuronal Network Dynamics In Vivo

A central tenet of neuroscience is that sensory, motor, and cognitive behaviors are generated by the communications and interactions among neurons, distributed within and across anatomically and functionally distinct brain regions. Therefore, to decipher how the brain plans, learns, and executes behaviors requires characterizing neuronal activity at multiple spatial and temporal scales. This includes simultaneously recording neuronal dynamics at the mesoscale level to understand the interactions among brain regions during different behavioral and brain states. Wide-field Ca2+ imaging, which uses single photon excitation and improved genetically encoded Ca2+ indicators, allows for simultaneous recordings of large brain areas and is proving to be a powerful tool to study neuronal activity at the mesoscopic scale in behaving animals. This review details the techniques used for wide-field Ca2+ imaging and the various approaches employed for the analyses of the rich neuronal-behavioral data sets obtained. Also discussed is how wide-field Ca2+ imaging is providing novel insights into both normal and altered neural processing in disease. Finally, we examine the limitations of the approach and new developments in wide-field Ca2+ imaging that are bringing new capabilities to this important technique for investigating large-scale neuronal dynamics.

Cerebellar Representations of Errors and Internal Models

After decades of study, a comprehensive understanding of cerebellar function remains elusive. Several hypotheses have been put forward over the years, including that the cerebellum functions as a forward internal model. Integrated into the forward model framework is the long-standing view that Purkinje cell complex spike discharge encodes error information. In this brief review, we address both of these concepts based on our recordings of cerebellar Purkinje cells over the last decade as well as newer findings from the literature. During a high-dimensionality tracking task requiring continuous error processing, we find that complex spike discharge provides a rich source of non-error signals to Purkinje cells, indicating that the classical error encoding role ascribed to climbing fiber input needs revision. Instead, the simple spike discharge of Purkinje cells carries robust predictive and feedback signals of performance errors, as well as kinematics. These simple spike signals are consistent with a forward internal model. We also show that the information encoded in the simple spike is dynamically adjusted by the complex spike firing. Synthesis of these observations leads to the hypothesis that complex spikes convey behavioral state changes, possibly acting to select and maintain forward models.

Combining Cortical Voltage Imaging and Hippocampal Electrophysiology for Investigating Global, Multi-Timescale Activity Interactions in the Brain

A new generation of optogenetic tools for analyzing neural activity has been contributing to the elucidation of classical open questions in neuroscience. Specifically, voltage imaging technologies using enhanced genetically encoded voltage indicators have been increasingly used to observe the dynamics of large circuits at the mesoscale. Here, we describe how to combine cortical wide-field voltage imaging with hippocampal electrophysiology in awake, behaving mice. Furthermore, we highlight how this method can be useful for different possible investigations, using the characterization of hippocampal-neocortical interactions as a case study.