Linking brain activity across scales with simultaneous opto- and electrophysiology

The brain enables adaptive behavior via the dynamic coordination of diverse neuronal signals across spatial and temporal scales: from fast action potential patterns in microcircuits to slower patterns of distributed activity in brain-wide networks. Understanding principles of multiscale dynamics requires simultaneous monitoring of signals in multiple, distributed network nodes. Combining optical and electrical recordings of brain activity is promising for collecting data across multiple scales and can reveal aspects of coordinated dynamics invisible to standard, single-modality approaches. We review recent progress in combining opto- and electrophysiology, focusing on mouse studies that shed new light on the function of single neurons by embedding their activity in the context of brain-wide activity patterns. Optical and electrical readouts can be tailored to desired scales to tackle specific questions. For example, fast dynamics in single cells or local populations recorded with multi-electrode arrays can be related to simultaneously acquired optical signals that report activity in specified subpopulations of neurons, in non-neuronal cells, or in neuromodulatory pathways. Conversely, two-photon imaging can be used to densely monitor activity in local circuits while sampling electrical activity in distant brain areas at the same time. The refinement of combined approaches will continue to reveal previously inaccessible and under-appreciated aspects of coordinated brain activity

Influence of Focal Activity on Macroscale Brain Dynamics in Health and Disease

Macroscopic recordings of brain activity (e.g. fMRI, EEG) are a sensitive biomarker of the neural networks supporting neurocognitive function. However, it remains largely unclear what mechanisms mediate changes in macroscale networks after focal brain injuries like stroke, seizure, and TBI. Recently, optical neuroimaging in animal models has emerged as a powerful tool to begin addressing these questions. Using widefield imaging of cortical calcium dynamics in mice, this dissertation investigates the mechanisms by which focal disruptions in activity alter brain-wide functional dynamics. In two chapters, I demonstrate 1) that focal sensory stimulation elicits state-dependent, global slow waves propagating from primary somatosensory cortex (S1). Using a focal ischemic stroke model, I show that bilateral activation of somatosensory cortices is required for initiating global SWs, while spontaneous SWs are generated independent of S1. 2) That regional disruption of cortical excitability induces widespread changes across cortical networks, using chemogenetic manipulation of parvalbumin interneurons to model focal epileptiform activity in S1. We further show that local imbalances in excitability propagate differentially through intra- and interhemispheric connections, and can induce plasticity in large-scale networks. These studies begin to define the mechanisms of macro-scale network disruption after focal injuries, adding to our understanding of how local cortical circuits modulate global brain networks

Relationships between correlated spikes, oxygen and LFP in the resting-state primate

Resting-state functional MRI (rsfMRI) provides a view of human brain organization based on correlation patterns of blood oxygen level dependent (BOLD) signals recorded across the whole brain. The neural basis of resting-state BOLD fluctuations and their correlation remains poorly understood. We simultaneously recorded oxygen level, spikes, and local field potential (LFP) at multiple sites in awake, resting monkeys. Following a spike, the average local oxygen and LFP voltage responses each resemble a task-driven BOLD response, with LFP preceding oxygen by 0.5 s. Between sites, features of the long-range correlation patterns of oxygen, LFP, and spikes are similar to features seen in rsfMRI. Most of the variance shared between sites lies in the infraslow frequency band (0.01-0.1 Hz) and in the infraslow envelope of higher-frequency bands (e.g. gamma LFP). While gamma LFP and infraslow LFP are both strong correlates of local oxygen, infraslow LFP explains significantly more of the variance shared between correlated oxygen signals than any other electrophysiological signal. Together these findings are consistent with a causal relationship between infraslow LFP and long-range oxygen correlations in the resting state

The (un)conscious mouse as a model for human brain functions: key principles of anesthesia and their impact on translational neuroimaging

In recent years, technical and procedural advances have brought functional magnetic resonance imaging (fMRI) to the field of murine neuroscience. Due to its unique capacity to measure functional activity non-invasively, across the entire brain, fMRI allows for the direct comparison of large-scale murine and human brain functions. This opens an avenue for bidirectional translational strategies to address fundamental questions ranging from neurological disorders to the nature of consciousness. The key challenges of murine fMRI are: (1) to generate and maintain functional brain states that approximate those of calm and relaxed human volunteers, while (2) preserving neurovascular coupling and physiological baseline conditions. Low-dose anesthetic protocols are commonly applied in murine functional brain studies to prevent stress and facilitate a calm and relaxed condition among animals. Yet, current mono-anesthesia has been shown to impair neural transmission and hemodynamic integrity. By linking the current state of murine electrophysiology, Ca(2+) imaging and fMRI of anesthetic effects to findings from human studies, this systematic review proposes general principles to design, apply and monitor anesthetic protocols in a more sophisticated way. The further development of balanced multimodal anesthesia, combining two or more drugs with complementary modes of action helps to shape and maintain specific brain states and relevant aspects of murine physiology. Functional connectivity and its dynamic repertoire as assessed by fMRI can be used to make inferences about cortical states and provide additional information about whole-brain functional dynamics. Based on this, a simple and comprehensive functional neurosignature pattern can be determined for use in defining brain states and anesthetic depth in rest and in response to stimuli. Such a signature can be evaluated and shared between labs to indicate the brain state of a mouse during experiments, an important step toward translating findings across species

Spatio-temporal Principles of Infra-slow Brain Activity

In the study of systems where basic laws have eluded us, as is largely the case in neuroscience, the simplest approach to progress might be to ask: what are the biggest, most noticeable things the system does when left alone? Without any perturbations or fine dissections, can regularities be found in the basic operations of the system as a whole? In the case of the brain, it turns out that there is an amazing amount of activity even in the absence of explicit environmental inputs or outputs. We call this spontaneous, or resting state, brain activity. Prior work has shown that spontaneous brain activity is dominated by very low frequencies: the biggest changes in brain activity happen relatively slowly, over 10’s-100’s of seconds. Moreover, this very slow activity of the brain is quite metabolically expensive. The brain accounts for 2% of body mass in an adult, but requires 20% of basal metabolic expenditure. Remarkably, the energy required to sustain brain function is nearly constant whether one is engaged in a demanding mental task or simply out to lunch. Furthermore, work over the past three decades has established that the spontaneous activities of the brain are not random, but instead organized into specific patterns, most often characterized by correlations within large brain systems. Yet, how do these correlations arise, and does spontaneous activity support slow signaling within and between neural systems? In this thesis, we approach these questions by providing a comprehensive analysis of the temporal structure of very low frequency spontaneous activity. Specifically, we focus on the direction of travel in low frequency activity, measured using resting state fMRI in humans, but also using electrophysiological techniques in humans and mice, and optical calcium imaging in mice. Our temporal analyses reveal heretofore unknown regularities in the way slow signals move through the brain. We further find that very low frequency activity behaves differently than faster frequencies, that it travels through distinct layers of the cortex, and that its travel patterns give rise to correlations within networks. We also demonstrate that the travel patterns of very low frequency activity are highly dependent on the state of the brain, especially the difference between wake and sleep states. Taken together, the findings in this thesis offer a glimpse into the principles that govern brain activity

High-Field Functional MRI from the Perspective of Single Vessels in Rats and Humans

Functional MRI (fMRI) has been employed to map brain activity and connectivity based on the neurovascular coupled hemodynamic signal. However, in most cases of fMRI studies, the cerebral vascular hemodynamic signal has been imaged in a spatially smoothed manner due to the limit of spatial resolution. There is a need to improve the spatiotemporal resolution of fMRI to map dynamic signal from individual venule or individual arteriole directly. Here, the thesis aims to provide a vascular-specific view of hemodynamic response during active state or resting state. To better characterize the temporal features of task-related fMRI signal from different vascular compartments, we implemented a line-scanning method to acquire vessel-specific blood-oxygen-level-dependent (BOLD) / cerebral-blood-volume (CBV) fMRI signal at 100-ms temporal resolution with sensory or optogenetic stimulation. Furthermore, we extended the line-scanning method with multi-echo scheme to provide vessel-specific fMRI with the higher contrast-to-noise ratio (CNR), which allowed us to directly map the distinct evoked hemodynamic signal from arterioles and venules at different echo time (TE) from 3 ms to 30 ms. The line-scanning fMRI methods acquire single k-space line per TR under a reshuffled k space acquisition scheme which has the limitation of sampling the fMRI signal in real-time for resting-state fMRI studies. To overcome this, we implemented a balanced Steady-state free precession (SSFP) to map task-related and resting-state fMRI (rsfMRI) with high spatial resolution in anesthetized rats. We reveal venule-dominated functional connectivity for BOLD fMRI and arteriole-dominated functional connectivity for CBV fMRI. The BOLD signal from individual venules and CBV signal from individual arterioles show correlations at an ultra-slow frequency (< 0.1 Hz), which are correlated with the intracellular calcium signal measured in neighboring neurons. In complementary data from awake human subjects, the BOLD signal is spatially correlated among sulcus veins and specified intracortical veins of the visual cortex at similar ultra-slow rhythms. This work provides a high-resolution fMRI approach to resolve brain activation and functional connectivity at the level of single vessels, which opened a new avenue to investigate brian functional connectivity at the scale of vessels

On Arousal and the Internal Regulation of Brain Function: Theory and Evidence across Modalities and Species

The brain is an organ. It is subject to the same physiological regulatory processes that engage the rest of the body’s organs, sculpted over hundreds of millions of years to sustain life so effectively. The central message of this thesis is that the holistic functioning of the brain, rather than operating at some level above or independent from these systemic regulatory processes, is deeply related to them. In short, as our limited attention spans might suggest: brain function is internally regulated. I propose that this internal regulation is a primary function of intrinsic brain activity. Chapter 2 provides a theoretical treatment of this issue, recasting intrinsic activity as an internal regulatory process operating on the brain’s temporal “states” and spatial “networks”. After establishing this framework, Chapters 3 and 4 provide tests of specific predictions. Thus, Chapter 3 confirms, in humans and macaque monkeys, the presence of topographically organized traveling waves occurring in synchrony with ongoing arousal fluctuations, with propagation occurring in parallel within the neocortex, striatum, thalamus, and cerebellum. This process is argued to provide a heretofore lacking physiological account of “resting-state functional connectivity” and related phenomenology. Chapter 4 extends this observation by demonstrating a continuous and tightly coordinated temporal evolution of brain, body, and behavioral states along a latent arousal cycle. Across multiple recording techniques and species, this cyclic trajectory is shown to be coupled to the traveling wave process described in Chapter 3, thus providing a parsimonious and integrative account of intrinsic brain activity and its spatiotemporal dynamics. Taken together, this thesis argues for the existence of an intrinsic regulatory process for global brain function

Metabolic and Blood Flow Properties of Functional Brain Networks Using Human Multimodal Neuroimaging

The brain has a high energetic cost to support neuronal activity, requiring both oxygen and glucose supply from the cerebral vascular system. Additionally, the brain functions through complex patterns of interconnectivity between neuronal assemblies giving rise to functional network architectures that can be investigated across multiple spatial scales. Different brain regions have different roles and importance within these network architectures, with some regions exhibiting more global importance by being involved in cross-network communication while other being predominantly involved in local connections. There are indications that regions exhibiting a more global role in inter networks connectivity are characterized by a higher and more efficient metabolic profile, leading to differences in metabolic properties when compared to more locally connected regions. Understanding the link between oxygen/glucose metabolism and functional features of brain network architectures, across different spatial scales, is of primary importance. This thesis consists of three original studies combining human brain resting-state multimodal neuroimaging and transcriptional data to investigate the glucose/oxygen metabolic costs of brain functional connectivity. We quantified glucose metabolism from positron emission tomography, and oxygen metabolism and functional connectivity from magnetic resonance imaging. In the first study, we highlight how the oxygen/glucose metabolism of brain regions can non-linearly relate to their functional hubness, within the resting-state networks of the brain across a nested hierarchy. We found that an increase in oxygen/glucose metabolism is associated with a non-linear increase in functional hubness where increase rates are both network- and scale-dependent. In the second study, we show specific transcriptional signatures that characterize the oxygen/glucose metabolic costs of regions involved in network global versus local centrality. This study highlights the different metabolic profiles of local and global regions, with gene expression related to oxidative metabolism and synaptic pathways being enriched in association with spatial patterns in common with resting blood flow and metabolism (oxygen and glucose) and globally-connected regions. In the third study, we demonstrate that there are oxygen/glucose metabolic costs to the functional integration and segregation of resting-state networks. We highlight that the metabolic costs of functional integration could reflect the hierarchical organization of the brain from unimodal to transmodal regions

DETECTING BRAIN-WIDE INTRINSIC CONNECTIVITY NETWORKS USING fMRI IN MICE

Functional neuroimaging methods in mice are essential for unraveling complex neuronal networks that underlie maladaptive behavior in neurological disorder models. By using fMRI to detect intrinsic connectivity networks in mice, we can examine large scale alteration in brain activity and functional connectivity to establish causal associations in brain network changes. The work presented in this dissertation is organized into five chapters. Chapter 1 provides the necessary background required to understand how functional neuroimaging tools such as fMRI detect signal changes attributed to spontaneous neuronal activity of intrinsic connectivity networks in mice. Chapter 2 describes the development of our isotropic fMRI acquisition sequence in mice and semi-automated pipeline for mouse fMRI data. Naïve mouse fMRI scans were used to validated the pipeline by reliably and reproducibly extracting intrinsic connectivity networks. Chapter 3 establishes the development and validation of a novel superparamagenetic iron-oxide nanoparticle to enhance fMRI signal sensitivity. Chapter 4 studies the effects norepinephrine released by locus coeruleus neurons on the default mode network in mice. Norepinephrine release selectively enhanced neuronal activity and connectivity in the Frontal module of the default mode network by suppressing information flow from the Retrosplenial-Hippocampal to the Association modules. Chapter 5 addresses the implications of our findings and addresses the limitations and future studies that can be conducted to expand on this research.Doctor of Philosoph