Dimensional and Categorical Solutions to Parsing Depression Heterogeneity in a Large Single-Site Sample.

BACKGROUND: Recent studies have reported significant advances in modeling the biological basis of heterogeneity in major depressive disorder, but investigators have also identified important technical challenges, including scanner-related artifacts, a propensity for multivariate models to overfit, and a need for larger samples with more extensive clinical phenotyping. The goals of the current study were to evaluate dimensional and categorical solutions to parsing heterogeneity in depression that are stable and generalizable in a large, single-site sample. METHODS: We used regularized canonical correlation analysis to identify data-driven brain-behavior dimensions that explain individual differences in depression symptom domains in a large, single-site dataset comprising clinical assessments and resting-state functional magnetic resonance imaging data for 328 patients with major depressive disorder and 461 healthy control participants. We examined the stability of clinical loadings and model performance in held-out data. Finally, hierarchical clustering on these dimensions was used to identify categorical depression subtypes. RESULTS: The optimal regularized canonical correlation analysis model yielded 3 robust and generalizable brain-behavior dimensions that explained individual differences in depressed mood and anxiety, anhedonia, and insomnia. Hierarchical clustering identified 4 depression subtypes, each with distinct clinical symptom profiles, abnormal resting-state functional connectivity patterns, and antidepressant responsiveness to repetitive transcranial magnetic stimulation. CONCLUSIONS: Our results define dimensional and categorical solutions to parsing neurobiological heterogeneity in major depressive disorder that are stable, generalizable, and capable of predicting treatment outcomes, each with distinct advantages in different contexts. They also provide additional evidence that regularized canonical correlation analysis and hierarchical clustering are effective tools for investigating associations between functional connectivity and clinical symptoms.

Expansion of a frontostriatal salience network in individuals with depression.

Hundreds of neuroimaging studies spanning two decades have revealed differences in brain structure and functional connectivity in depression, but with modest effect sizes, complicating efforts to derive mechanistic pathophysiologic insights or develop biomarkers. 1 Furthermore, although depression is a fundamentally episodic condition, few neuroimaging studies have taken a longitudinal approach, which is critical for understanding cause and effect and delineating mechanisms that drive mood state transitions over time. The emerging field of precision functional mapping using densely-sampled longitudinal neuroimaging data has revealed unexpected, functionally meaningful individual differences in brain network topology in healthy individuals, 2-5 but these approaches have never been applied to individuals with depression. Here, using precision functional mapping techniques and 11 datasets comprising n=187 repeatedly sampled individuals and >21,000 minutes of fMRI data, we show that the frontostriatal salience network is expanded two-fold in most individuals with depression. This effect was replicable in multiple samples, including large-scale, group-average data (N=1,231 subjects), and caused primarily by network border shifts affecting specific functional systems, with three distinct modes of encroachment occurring in different individuals. Salience network expansion was unexpectedly stable over time, unaffected by changes in mood state, and detectable in children before the subsequent onset of depressive symptoms in adolescence. Longitudinal analyses of individuals scanned up to 62 times over 1.5 years identified connectivity changes in specific frontostriatal circuits that tracked fluctuations in specific symptom domains and predicted future anhedonia symptoms before they emerged. Together, these findings identify a stable trait-like brain network topology that may confer risk for depression and mood-state dependent connectivity changes in frontostriatal circuits that predict the emergence and remission of depressive symptoms over time.

Bidirectional Regulation of Motor Circuits Using Magnetogenetic Gene Therapy.

Regulating the activity of discrete neuronal populations in living mammals after delivery of modified ion channels can be used to map functional circuits and potentially treat neurological diseases. Here we report a novel suite of magnetogenetic tools, based on a single anti-ferritin nanobody-TRPV1 receptor fusion protein, which regulated neuronal activity in motor circuits when exposed to magnetic fields. AAV-mediated delivery of a cre-dependent nanobody-TRPV1 calcium channel into the striatum of adenosine 2a (A2a) receptor-cre driver mice led to restricted expression within D2 neurons, resulting in motor freezing when placed in a 3T MRI or adjacent to a transcranial magnetic stimulation (TMS) device. Functional imaging and fiber photometry both confirmed focal activation of the target region in response to the magnetic fields. Expression of the same construct in the striatum of wild-type mice along with a second injection of an AAVretro expressing cre into the globus pallidus led to similar circuit specificity and motor responses. Finally, a mutation was generated to gate chloride and inhibit neuronal activity. Expression of this variant in subthalamic nucleus (STN) projection neurons in PitX2-cre parkinsonian mice resulted in reduced local c-fos expression and a corresponding improvement in motor rotational behavior during magnetic field exposure. These data demonstrate that AAV delivery of magnetogenetic constructs can bidirectionally regulate activity of specific neuronal circuits non-invasively in vivo using clinically available devices for both preclinical analysis of circuit effects on behavior and potential human clinical translation.

Regulation of social interaction in mice by a frontostriatal circuit modulated by established hierarchical relationships.

Social hierarchies exert a powerful influence on behavior, but the neurobiological mechanisms that detect and regulate hierarchical interactions are not well understood, especially at the level of neural circuits. Here, we use fiber photometry and chemogenetic tools to record and manipulate the activity of nucleus accumbens-projecting cells in the ventromedial prefrontal cortex (vmPFC-NAcSh) during tube test social competitions. We show that vmPFC-NAcSh projections signal learned hierarchical relationships, and are selectively recruited by subordinate mice when they initiate effortful social dominance behavior during encounters with a dominant competitor from an established hierarchy. After repeated bouts of social defeat stress, this circuit is preferentially activated during social interactions initiated by stress resilient individuals, and plays a necessary role in supporting social approach behavior in subordinated mice. These results define a necessary role for vmPFC-NAcSh cells in the adaptive regulation of social interaction behavior based on prior hierarchical interactions.

Molecular and network-level mechanisms explaining individual differences in autism spectrum disorder.

The mechanisms underlying phenotypic heterogeneity in autism spectrum disorder (ASD) are not well understood. Using a large neuroimaging dataset, we identified three latent dimensions of functional brain network connectivity that predicted individual differences in ASD behaviors and were stable in cross-validation. Clustering along these three dimensions revealed four reproducible ASD subgroups with distinct functional connectivity alterations in ASD-related networks and clinical symptom profiles that were reproducible in an independent sample. By integrating neuroimaging data with normative gene expression data from two independent transcriptomic atlases, we found that within each subgroup, ASD-related functional connectivity was explained by regional differences in the expression of distinct ASD-related gene sets. These gene sets were differentially associated with distinct molecular signaling pathways involving immune and synapse function, G-protein-coupled receptor signaling, protein synthesis and other processes. Collectively, our findings delineate atypical connectivity patterns underlying different forms of ASD that implicate distinct molecular signaling mechanisms.

Functional and Optogenetic Approaches to Discovering Stable Subtype-Specific Circuit Mechanisms in Depression.

BACKGROUND: Previously, we identified four depression subtypes defined by distinct functional connectivity alterations in depression-related brain networks, which in turn predicted clinical symptoms and treatment response. Optogenetic functional magnetic resonance imaging offers a promising approach for testing how dysfunction in specific circuits gives rise to subtype-specific, depression-related behaviors. However, this approach assumes that there are robust, reproducible correlations between functional connectivity and depressive symptoms-an assumption that was not extensively tested in previous work. METHODS: First, we comprehensively reevaluated the stability of canonical correlations between functional connectivity and symptoms (N = 220 subjects) using optimized approaches for large-scale statistical hypothesis testing, and we validated methods for improving estimation of latent variables driving brain-behavior correlations. Having confirmed this necessary condition, we reviewed recent advances in optogenetic functional magnetic resonance imaging and illustrated one approach to formulating hypotheses regarding latent subtype-specific circuit mechanisms and testing them in animal models. RESULTS: Correlations between connectivity features and clinical symptoms were robustly significant, and canonical correlation analysis solutions tested repeatedly on held-out data generalized. However, they were sensitive to data quality, preprocessing, and clinical heterogeneity, which can reduce effect sizes. Generalization could be markedly improved by adding L2 regularization, which decreased estimator variance, increased canonical correlations in left-out data, and stabilized feature selection. These improvements were useful for identifying candidate circuits for optogenetic interrogation in animal models. CONCLUSIONS: Multiview, latent-variable approaches such as canonical correlation analysis offer a conceptually useful framework for discovering stable patient subtypes by synthesizing multiple clinical and functional measures. Optogenetic functional magnetic resonance imaging holds promise for testing hypotheses regarding latent, subtype-specific mechanisms driving depressive symptoms and behaviors.

Neuronal Dynamics Regulating Brain and Behavioral State Transitions.

Prolonged behavioral challenges can cause animals to switch from active to passive coping strategies to manage effort-expenditure during stress; such normally adaptive behavioral state transitions can become maladaptive in psychiatric disorders such as depression. The underlying neuronal dynamics and brainwide interactions important for passive coping have remained unclear. Here, we develop a paradigm to study these behavioral state transitions at cellular-resolution across the entire vertebrate brain. Using brainwide imaging in zebrafish, we observed that the transition to passive coping is manifested by progressive activation of neurons in the ventral (lateral) habenula. Activation of these ventral-habenula neurons suppressed downstream neurons in the serotonergic raphe nucleus and caused behavioral passivity, whereas inhibition of these neurons prevented passivity. Data-driven recurrent neural network modeling pointed to altered intra-habenula interactions as a contributory mechanism. These results demonstrate ongoing encoding of experience features in the habenula, which guides recruitment of downstream networks and imposes a passive coping behavioral strategy.

Fast near-whole-brain imaging in adult Drosophila during responses to stimuli and behavior.

Whole-brain recordings give us a global perspective of the brain in action. In this study, we describe a method using light field microscopy to record near-whole brain calcium and voltage activity at high speed in behaving adult flies. We first obtained global activity maps for various stimuli and behaviors. Notably, we found that brain activity increased on a global scale when the fly walked but not when it groomed. This global increase with walking was particularly strong in dopamine neurons. Second, we extracted maps of spatially distinct sources of activity as well as their time series using principal component analysis and independent component analysis. The characteristic shapes in the maps matched the anatomy of subneuropil regions and, in some cases, a specific neuron type. Brain structures that responded to light and odor were consistent with previous reports, confirming the new technique's validity. We also observed previously uncharacterized behavior-related activity as well as patterns of spontaneous voltage activity.

Coordinated Reductions in Excitatory Input to the Nucleus Accumbens Underlie Food Consumption.

Reward-seeking behavior is regulated by a diverse collection of inputs to the nucleus accumbens (NAc). The information encoded in each excitatory afferent to the NAc is unknown, in part because it is unclear when these pathways are active in relation to behavior. Here we compare the activity profiles of amygdala, hippocampal, and thalamic inputs to the NAc shell in mice performing a cued reward-seeking task using GCaMP-based fiber photometry. We find that the rostral and caudal ends of the NAc shell are innervated by distinct but intermingled populations of forebrain neurons that exhibit divergent feeding-related activity. In the rostral NAc shell, a coordinated network-wide reduction in excitatory drive correlates with feeding, and reduced input from individual pathways is sufficient to promote it. Overall, the data suggest that pathway-specific input activity at a population level may vary more across the NAc than between pathways.

Resting-state connectivity biomarkers define neurophysiological subtypes of depression.

Biomarkers have transformed modern medicine but remain largely elusive in psychiatry, partly because there is a weak correspondence between diagnostic labels and their neurobiological substrates. Like other neuropsychiatric disorders, depression is not a unitary disease, but rather a heterogeneous syndrome that encompasses varied, co-occurring symptoms and divergent responses to treatment. By using functional magnetic resonance imaging (fMRI) in a large multisite sample (n = 1,188), we show here that patients with depression can be subdivided into four neurophysiological subtypes ('biotypes') defined by distinct patterns of dysfunctional connectivity in limbic and frontostriatal networks. Clustering patients on this basis enabled the development of diagnostic classifiers (biomarkers) with high (82-93%) sensitivity and specificity for depression subtypes in multisite validation (n = 711) and out-of-sample replication (n = 477) data sets. These biotypes cannot be differentiated solely on the basis of clinical features, but they are associated with differing clinical-symptom profiles. They also predict responsiveness to transcranial magnetic stimulation therapy (n = 154). Our results define novel subtypes of depression that transcend current diagnostic boundaries and may be useful for identifying the individuals who are most likely to benefit from targeted neurostimulation therapies.

Hypothalamic control of male aggression-seeking behavior.

In many vertebrate species, certain individuals will seek out opportunities for aggression, even in the absence of threat-provoking cues. Although several brain areas have been implicated in the generation of attack in response to social threat, little is known about the neural mechanisms that promote self-initiated or 'voluntary' aggression-seeking when no threat is present. To explore this directly, we utilized an aggression-seeking task in which male mice self-initiated aggression trials to gain brief and repeated access to a weaker male that they could attack. In males that exhibited rapid task learning, we found that the ventrolateral part of the ventromedial hypothalamus (VMHvl), an area with a known role in attack, was essential for aggression-seeking. Using both single-unit electrophysiology and population optical recording, we found that VMHvl neurons became active during aggression-seeking and that their activity tracked changes in task learning and extinction. Inactivation of the VMHvl reduced aggression-seeking behavior, whereas optogenetic stimulation of the VMHvl accelerated moment-to-moment aggression-seeking and intensified future attack. These data demonstrate that the VMHvl can mediate both acute attack and flexible seeking actions that precede attack.

Prefrontal cortical regulation of brainwide circuit dynamics and reward-related behavior.

Motivation for reward drives adaptive behaviors, whereas impairment of reward perception and experience (anhedonia) can contribute to psychiatric diseases, including depression and schizophrenia. We sought to test the hypothesis that the medial prefrontal cortex (mPFC) controls interactions among specific subcortical regions that govern hedonic responses. By using optogenetic functional magnetic resonance imaging to locally manipulate but globally visualize neural activity in rats, we found that dopamine neuron stimulation drives striatal activity, whereas locally increased mPFC excitability reduces this striatal response and inhibits the behavioral drive for dopaminergic stimulation. This chronic mPFC overactivity also stably suppresses natural reward-motivated behaviors and induces specific new brainwide functional interactions, which predict the degree of anhedonia in individuals. These findings describe a mechanism by which mPFC modulates expression of reward-seeking behavior, by regulating the dynamical interactions between specific distant subcortical regions.

SPED Light Sheet Microscopy: Fast Mapping of Biological System Structure and Function.

The goal of understanding living nervous systems has driven interest in high-speed and large field-of-view volumetric imaging at cellular resolution. Light sheet microscopy approaches have emerged for cellular-resolution functional brain imaging in small organisms such as larval zebrafish, but remain fundamentally limited in speed. Here, we have developed SPED light sheet microscopy, which combines large volumetric field-of-view via an extended depth of field with the optical sectioning of light sheet microscopy, thereby eliminating the need to physically scan detection objectives for volumetric imaging. SPED enables scanning of thousands of volumes-per-second, limited only by camera acquisition rate, through the harnessing of optical mechanisms that normally result in unwanted spherical aberrations. We demonstrate capabilities of SPED microscopy by performing fast sub-cellular resolution imaging of CLARITY mouse brains and cellular-resolution volumetric Ca(2+) imaging of entire zebrafish nervous systems. Together, SPED light sheet methods enable high-speed cellular-resolution volumetric mapping of biological system structure and function.

Wirelessly powered, fully internal optogenetics for brain, spinal and peripheral circuits in mice.

To enable sophisticated optogenetic manipulation of neural circuits throughout the nervous system with limited disruption of animal behavior, light-delivery systems beyond fiber optic tethering and large, head-mounted wireless receivers are desirable. We report the development of an easy-to-construct, implantable wireless optogenetic device. Our smallest version (20 mg, 10 mm(3)) is two orders of magnitude smaller than previously reported wireless optogenetic systems, allowing the entire device to be implanted subcutaneously. With a radio-frequency (RF) power source and controller, this implant produces sufficient light power for optogenetic stimulation with minimal tissue heating (<1 °C). We show how three adaptations of the implant allow for untethered optogenetic control throughout the nervous system (brain, spinal cord and peripheral nerve endings) of behaving mice. This technology opens the door for optogenetic experiments in which animals are able to behave naturally with optogenetic manipulation of both central and peripheral targets.

Closed-loop and activity-guided optogenetic control.

Advances in optical manipulation and observation of neural activity have set the stage for widespread implementation of closed-loop and activity-guided optical control of neural circuit dynamics. Closing the loop optogenetically (i.e., basing optogenetic stimulation on simultaneously observed dynamics in a principled way) is a powerful strategy for causal investigation of neural circuitry. In particular, observing and feeding back the effects of circuit interventions on physiologically relevant timescales is valuable for directly testing whether inferred models of dynamics, connectivity, and causation are accurate in vivo. Here we highlight technical and theoretical foundations as well as recent advances and opportunities in this area, and we review in detail the known caveats and limitations of optogenetic experimentation in the context of addressing these challenges with closed-loop optogenetic control in behaving animals.

Enhancing the performance of the light field microscope using wavefront coding.

Light field microscopy has been proposed as a new high-speed volumetric computational imaging method that enables reconstruction of 3-D volumes from captured projections of the 4-D light field. Recently, a detailed physical optics model of the light field microscope has been derived, which led to the development of a deconvolution algorithm that reconstructs 3-D volumes with high spatial resolution. However, the spatial resolution of the reconstructions has been shown to be non-uniform across depth, with some z planes showing high resolution and others, particularly at the center of the imaged volume, showing very low resolution. In this paper, we enhance the performance of the light field microscope using wavefront coding techniques. By including phase masks in the optical path of the microscope we are able to address this non-uniform resolution limitation. We have also found that superior control over the performance of the light field microscope can be achieved by using two phase masks rather than one, placed at the objective's back focal plane and at the microscope's native image plane. We present an extended optical model for our wavefront coded light field microscope and develop a performance metric based on Fisher information, which we use to choose adequate phase masks parameters. We validate our approach using both simulated data and experimental resolution measurements of a USAF 1951 resolution target; and demonstrate the utility for biological applications with in vivo volumetric calcium imaging of larval zebrafish brain.

Natural neural projection dynamics underlying social behavior.

Social interaction is a complex behavior essential for many species and is impaired in major neuropsychiatric disorders. Pharmacological studies have implicated certain neurotransmitter systems in social behavior, but circuit-level understanding of endogenous neural activity during social interaction is lacking. We therefore developed and applied a new methodology, termed fiber photometry, to optically record natural neural activity in genetically and connectivity-defined projections to elucidate the real-time role of specified pathways in mammalian behavior. Fiber photometry revealed that activity dynamics of a ventral tegmental area (VTA)-to-nucleus accumbens (NAc) projection could encode and predict key features of social, but not novel object, interaction. Consistent with this observation, optogenetic control of cells specifically contributing to this projection was sufficient to modulate social behavior, which was mediated by type 1 dopamine receptor signaling downstream in the NAc. Direct observation of deep projection-specific activity in this way captures a fundamental and previously inaccessible dimension of mammalian circuit dynamics.