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.

Communication in Neural Circuits: Tools, Opportunities, and Challenges.

Communication, the effective delivery of information, is fundamental to life across all scales and species. Nervous systems (by necessity) may be most specifically adapted among biological tissues for high rate and complexity of information transmitted, and thus, the properties of neural tissue and principles of its organization into circuits may illuminate capabilities and limitations of biological communication. Here, we consider recent developments in tools for studying neural circuits with particular attention to defining neuronal cell types by input and output information streams--i.e., by how they communicate. Complementing approaches that define cell types by virtue of genetic promoter/enhancer properties, this communication-based approach to defining cell types operationally by input/output (I/O) relationships links structure and function, resolves difficulties associated with single-genetic-feature definitions, leverages technology for observing and testing significance of precisely these I/O relationships in intact brains, and maps onto processes through which behavior may be adapted during development, experience, and evolution.

Intact-Brain Analyses Reveal Distinct Information Carried by SNc Dopamine Subcircuits.

Recent progress in understanding the diversity of midbrain dopamine neurons has highlighted the importance--and the challenges--of defining mammalian neuronal cell types. Although neurons may be best categorized using inclusive criteria spanning biophysical properties, wiring of inputs, wiring of outputs, and activity during behavior, linking all of these measurements to cell types within the intact brains of living mammals has been difficult. Here, using an array of intact-brain circuit interrogation tools, including CLARITY, COLM, optogenetics, viral tracing, and fiber photometry, we explore the diversity of dopamine neurons within the substantia nigra pars compacta (SNc). We identify two parallel nigrostriatal dopamine neuron subpopulations differing in biophysical properties, input wiring, output wiring to dorsomedial striatum (DMS) versus dorsolateral striatum (DLS), and natural activity patterns during free behavior. Our results reveal independently operating nigrostriatal information streams, with implications for understanding the logic of dopaminergic feedback circuits and the diversity of mammalian neuronal cell types.

Nucleus accumbens D2R cells signal prior outcomes and control risky decision-making.

A marked bias towards risk aversion has been observed in nearly every species tested. A minority of individuals, however, instead seem to prefer risk (repeatedly choosing uncertain large rewards over certain but smaller rewards), and even risk-averse individuals sometimes opt for riskier alternatives. It is not known how neural activity underlies such important shifts in decision-making--either as a stable trait across individuals or at the level of variability within individuals. Here we describe a model of risk-preference in rats, in which stable individual differences, trial-by-trial choices, and responses to pharmacological agents all parallel human behaviour. By combining new genetic targeting strategies with optical recording of neural activity during behaviour in this model, we identify relevant temporally specific signals from a genetically and anatomically defined population of neurons. This activity occurred within dopamine receptor type-2 (D2R)-expressing cells in the nucleus accumbens (NAc), signalled unfavourable outcomes from the recent past at a time appropriate for influencing subsequent decisions, and also predicted subsequent choices made. Having uncovered this naturally occurring neural correlate of risk selection, we then mimicked the temporally specific signal with optogenetic control during decision-making and demonstrated its causal effect in driving risk-preference. Specifically, risk-preferring rats could be instantaneously converted to risk-averse rats with precisely timed phasic stimulation of NAc D2R cells. These findings suggest that individual differences in risk-preference, as well as real-time risky decision-making, can be largely explained by the encoding in D2R-expressing NAc cells of prior unfavourable outcomes during decision-making.

Parvalbumin+ and Npas1+ Pallidal Neurons Have Distinct Circuit Topology and Function.

The external globus pallidus (GPe) is a critical node within the basal ganglia circuit. Phasic changes in the activity of GPe neurons during movement and their alterations in Parkinson's disease (PD) argue that the GPe is important in motor control. Parvalbumin-positive (PV+) neurons and Npas1+ neurons are the two principal neuron classes in the GPe. The distinct electrophysiological properties and axonal projection patterns argue that these two neuron classes serve different roles in regulating motor output. However, the causal relationship between GPe neuron classes and movement remains to be established. Here, by using optogenetic approaches in mice (both males and females), we showed that PV+ neurons and Npas1+ neurons promoted and suppressed locomotion, respectively. Moreover, PV+ neurons and Npas1+ neurons are under different synaptic influences from the subthalamic nucleus (STN). Additionally, we found a selective weakening of STN inputs to PV+ neurons in the chronic 6-hydroxydopamine lesion model of PD. This finding reinforces the idea that the reciprocally connected GPe-STN network plays a key role in disease symptomatology and thus provides the basis for future circuit-based therapies.SIGNIFICANCE STATEMENT The external pallidum is a key, yet an understudied component of the basal ganglia. Neural activity in the pallidum goes awry in neurologic diseases, such as Parkinson's disease. While this strongly argues that the pallidum plays a critical role in motor control, it has been difficult to establish the causal relationship between pallidal activity and motor function/dysfunction. This was in part because of the cellular complexity of the pallidum. Here, we showed that the two principal neuron types in the pallidum have opposing roles in motor control. In addition, we described the differences in their synaptic influence. Importantly, our research provides new insights into the cellular and circuit mechanisms that explain the hypokinetic features of Parkinson's disease.

Basomedial amygdala mediates top-down control of anxiety and fear.

Anxiety-related conditions are among the most difficult neuropsychiatric diseases to treat pharmacologically, but respond to cognitive therapies. There has therefore been interest in identifying relevant top-down pathways from cognitive control regions in medial prefrontal cortex (mPFC). Identification of such pathways could contribute to our understanding of the cognitive regulation of affect, and provide pathways for intervention. Previous studies have suggested that dorsal and ventral mPFC subregions exert opposing effects on fear, as do subregions of other structures. However, precise causal targets for top-down connections among these diverse possibilities have not been established. Here we show that the basomedial amygdala (BMA) represents the major target of ventral mPFC in amygdala in mice. Moreover, BMA neurons differentiate safe and aversive environments, and BMA activation decreases fear-related freezing and high-anxiety states. Lastly, we show that the ventral mPFC-BMA projection implements top-down control of anxiety state and learned freezing, both at baseline and in stress-induced anxiety, defining a broadly relevant new top-down behavioural regulation pathway.

Interfacing behavioral and neural circuit models for habit formation.

Habits are an important mechanism by which organisms can automate the control of behavior to alleviate cognitive demand. However, transitions to habitual control are risky because they lead to inflexible responding in the face of change. The question of how the brain controls transitions into habit is thus an intriguing one. How do we regulate when our repeated actions become automated? When is it advantageous or disadvantageous to release actions from cognitive control? Decades of research have identified a variety of methods for eliciting habitual responding in animal models. Progress has also been made to understand which brain areas and neural circuits control transitions into habit. Here, I discuss existing research on behavioral and neural circuit models for habit formation (with an emphasis on striatal circuits), and discuss strategies for combining information from different paradigms and levels of analysis to prompt further progress in the field.

Simultaneous fast measurement of circuit dynamics at multiple sites across the mammalian brain.

Real-time activity measurements from multiple specific cell populations and projections are likely to be important for understanding the brain as a dynamical system. Here we developed frame-projected independent-fiber photometry (FIP), which we used to record fluorescence activity signals from many brain regions simultaneously in freely behaving mice. We explored the versatility of the FIP microscope by quantifying real-time activity relationships among many brain regions during social behavior, simultaneously recording activity along multiple axonal pathways during sensory experience, performing simultaneous two-color activity recording, and applying optical perturbation tuned to elicit dynamics that match naturally occurring patterns observed during behavior.

Frequency-dependent, cell type-divergent signaling in the hippocamposeptal projection.

Hippocampal oscillations are critical for information processing, and are strongly influenced by inputs from the medial septum. Hippocamposeptal neurons provide direct inhibitory feedback from the hippocampus onto septal cells, and are therefore likely to also play an important role in the circuit; these neurons fire at either low or high frequency, reflecting hippocampal network activity during theta oscillations or ripple events, respectively. Here, we optogenetically target the long-range GABAergic projection from the hippocampus to the medial septum in rats, and thereby simulate hippocampal input onto downstream septal cells in an acute slice preparation. In response to optogenetic activation of hippocamposeptal fibers at theta and ripple frequencies, we elicit postsynaptic GABAergic responses in a subset (24%) of septal cells, most predominantly in fast-spiking cells. In addition, in another subset of septal cells (19%) corresponding primarily to cholinergic cells, we observe a slow hyperpolarization of the resting membrane potential and a decrease in input resistance, particularly in response to prolonged high-frequency (ripple range) stimulation. This slow response is partially sensitive to GIRK channel and D2 dopamine receptor block. Our results suggest that two independent populations of septal cells distinctly encode hippocampal feedback, enabling the septum to monitor ongoing patterns of activity in the hippocampus.

Hidden variables in stress neurobiology research.

Among the central goals of stress neurobiology research is to understand the mechanisms by which stressors change neural circuit function to precipitate or exacerbate psychiatric symptoms. Yet despite decades of effort, psychiatric medications that target the biological substrates of the stress response are largely lacking. We propose that the clinical advancement of stress response-based therapeutics for psychiatric disorders may be hindered by 'hidden variables' in stress research, including considerations of behavioral study design (stressors and outcome measures), individual variability, sex differences, and the interaction of the body's stress hormone system with endogenous circadian and ultradian rhythms. We highlight key issues and suggest ways forward in stress neurobiology research that may improve the ability to assess stress mechanisms and translate preclinical findings.

Dopamine across timescales and cell types: Relevance for phenotypes in Parkinson's disease progression.

Dopamine neurons in the substantia nigra pars compacta (SNc) synthesize and release dopamine, a critical neurotransmitter for movement and learning. SNc dopamine neurons degenerate in Parkinson's Disease (PD), causing a host of motor and non-motor symptoms. Here, we review recent conceptual advances in our basic understanding of the dopamine system - including our rapidly advancing knowledge of dopamine neuron heterogeneity - with special attention to their importance for understanding PD. In PD patients, dopamine neuron degeneration progresses from lateral SNc to medial SNc, suggesting clinically relevant heterogeneity in dopamine neurons. With technical advances in dopamine system interrogation, we can understand the relevance of this heterogeneity for PD progression and harness it to develop new treatments.

Chronically dysregulated corticosterone impairs dopaminergic transmission in the dorsomedial striatum by sex-divergent mechanisms.

Major depressive disorder (MDD) is a leading cause of disability worldwide. Individuals with MDD exhibit decreased motivation and deficits in reward processing. In a subset of MDD patients, chronic dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis occurs, resulting in increased levels of the 'stress hormone' cortisol during the normal rest period (i.e., evening and night). However, the mechanistic relationship between chronically elevated resting cortisol and behavioral deficits in motivation and reward processing remains unclear. Given that women are diagnosed with MDD at twice the rate of men, it is important to understand whether the mechanisms linking cortisol to the symptoms of MDD differ by sex. In this study, we used subcutaneous implants to chronically elevate free plasma corticosterone (the rodent homolog of cortisol; 'CORT') during the rest period in male and female mice and examined changes in behavior and dopamine system function. We found that chronic CORT treatment impaired motivated reward-seeking in both sexes. In female but not male mice, CORT treatment reduced dopamine content in the dorsomedial striatum (DMS). In male but not female mice, CORT treatment impaired the function of the dopamine transporter (DAT) in DMS. From these studies, we conclude that chronic CORT dysregulation impairs motivation by impairing dopaminergic transmission in the DMS, but via different mechanisms in male and female mice. A better understanding of these sex-specific mechanisms could lead to new directions in MDD diagnosis and treatment.

Striatonigrostriatal circuit architecture for disinhibition of dopamine signaling.

The basal ganglia operate largely in closed parallel loops, including an associative circuit for goal-directed behavior originating from the dorsomedial striatum (DMS) and a somatosensory circuit important for habit formation originating from the dorsolateral striatum (DLS). An exception to this parallel circuit organization has been proposed to explain how information might be transferred between striatal subregions, for example, from the DMS to the DLS during habit formation. The "ascending spiral hypothesis" proposes that the DMS disinhibits dopamine signaling in the DLS through a tri-synaptic, open-loop striatonigrostriatal circuit. Here, we use transsynaptic and intersectional genetic tools to investigate both closed- and open-loop striatonigrostriatal circuits. We find strong evidence for closed loops, which would allow striatal subregions to regulate their own dopamine release. We also find evidence for functional synapses in open loops. However, these synapses are unable to modulate tonic dopamine neuron firing, questioning the prominence of their role in mediating crosstalk between striatal subregions.

Dopamine signaling in the dorsomedial striatum promotes compulsive behavior.

Compulsive behavior is a defining feature of disorders such as substance use disorders. Current evidence suggests that corticostriatal circuits control the expression of established compulsions, but little is known about the mechanisms regulating the development of compulsions. We hypothesized that dopamine, a critical modulator of striatal synaptic plasticity, could control alterations in corticostriatal circuits leading to the development of compulsions (defined here as continued reward seeking in the face of punishment). We used dual-site fiber photometry to measure dopamine axon activity in the dorsomedial striatum (DMS) and the dorsolateral striatum (DLS) as compulsions emerged. Individual variability in the speed with which compulsions emerged was predicted by DMS dopamine axon activity. Amplifying this dopamine signal accelerated animals' transitions to compulsion, whereas inhibition delayed it. In contrast, amplifying DLS dopamine signaling had no effect on the emergence of compulsions. These results establish DMS dopamine signaling as a key controller of the development of compulsive reward seeking.

Intersectional mapping of multi-transmitter neurons and other cell types in the brain.

Recent developments in intersectional strategies have greatly advanced our ability to precisely target brain cell types based on unique co-expression patterns. To accelerate the application of intersectional genetics, we perform a brain-wide characterization of 13 Flp and tTA mouse driver lines and selected seven for further analysis based on expression of vesicular neurotransmitter transporters. Using selective Cre driver lines, we created more than 10 Cre/tTA combinational lines for cell type targeting and circuit analysis. We then used VGLUT-Cre/VGAT-Flp combinational lines to identify and map 30 brain regions containing neurons that co-express vesicular glutamate and gamma-aminobutyric acid (GABA) transporters, followed by tracing their projections with intersectional viral vectors. Focusing on the lateral habenula (LHb) as a target, we identified glutamatergic, GABAergic, or co-glutamatergic/GABAergic innervations from ∼40 brain regions. These data provide an important resource for the future application of intersectional strategies and expand our understanding of the neuronal subtypes in the brain.

Endocannabinoid signaling mediates psychomotor activation by adenosine A2A antagonists.

Adenosine A(2A) receptor antagonists are psychomotor stimulants that also hold therapeutic promise for movement disorders. However, the molecular mechanisms underlying their stimulant properties are not well understood. Here, we show that the robust increase in locomotor activity induced by an A(2A) antagonist in vivo is greatly attenuated by antagonizing cannabinoid CB(1) receptor signaling or by administration to CB(1)(-/-) mice. To determine the locus of increased endocannabinoid signaling, we measured the amount of anandamide [AEA (N-arachidonoylethanolamine)] and 2-arachidonoylglycerol (2-AG) in brain tissue from striatum and cortex. We find that 2-AG is selectively increased in striatum after acute blockade of A(2A) receptors, which are highly expressed by striatal indirect-pathway medium spiny neurons (MSNs). Using targeted whole-cell recordings from direct- and indirect-pathway MSNs, we demonstrate that A(2A) receptor antagonists potentiate 2-AG release and induction of long-term depression at indirect-pathway MSNs, but not direct-pathway MSNs. Together, these data outline a molecular mechanism by which A(2A) antagonists reduce excitatory synaptic drive on the indirect pathway through CB(1) receptor signaling, thus leading to increased psychomotor activation.

Dopamine, Updated: Reward Prediction Error and Beyond.

Dopamine neurons have been intensely studied for their roles in reinforcement learning. A dominant theory of how these neurons contribute to learning is through the encoding of a reward prediction error (RPE) signal. Recent advances in dopamine research have added nuance to RPE theory by incorporating the ideas of sensory prediction error, distributional encoding, and belief states. Further nuance is likely to be added shortly by convergent lines of research on dopamine neuron diversity. Finally, a major challenge is to reconcile RPE theory with other current theories of dopamine function to account for dopamine's role in movement, motivation, and goal-directed planning.

GuPPy, a Python toolbox for the analysis of fiber photometry data.

Fiber photometry (FP) is an adaptable method for recording in vivo neural activity in freely behaving animals. It has become a popular tool in neuroscience due to its ease of use, low cost, the ability to combine FP with freely moving behavior, among other advantages. However, analysis of FP data can be challenging for new users, especially those with a limited programming background. Here, we present Guided Photometry Analysis in Python (GuPPy), a free and open-source FP analysis tool. GuPPy is designed to operate across computing platforms and can accept data from a variety of FP data acquisition systems. The program presents users with a set of graphic user interfaces (GUIs) to load data and provide input parameters. Graphs are produced that can be easily exported for integration into scientific figures. As an open-source tool, GuPPy can be modified by users with knowledge of Python to fit their specific needs.