Exploring internal state-coding across the rodent brain

Whole-brain neural substrates of behavioral variability in the larval zebrafish

Animals engaged in naturalistic behavior can exhibit a large degree of behavioral variability even under sensory invariant conditions. Such behavioral variability can include not only variations of the same behavior, but also variability across qualitatively different behaviors driven by divergent cognitive states, such as fight-or-flight decisions. However, the neural circuit mechanisms that generate such divergent behaviors across trials are not well understood. To investigate this question, here we studied the visual-evoked responses of larval zebrafish to moving objects of various sizes, which we found exhibited highly variable and divergent responses across repetitions of the same stimulus. Given that the neuronal circuits underlying such behaviors span sensory, motor, and other brain areas, we built a novel Fourier light field microscope which enables high-resolution, whole-brain imaging of larval zebrafish during behavior. This enabled us to screen for neural loci which exhibited activity patterns correlated with behavioral variability. We found that despite the highly variable activity of single neurons, visual stimuli were robustly encoded at the population level, and the visual-encoding dimensions of neural activity did not explain behavioral variability. This robustness despite apparent single neuron variability was due to the multi-dimensional geometry of the neuronal population dynamics: almost all neural dimensions that were variable across individual trials, i.e. the "noise" modes, were nearly orthogonal to those encoding for sensory information. Investigating this neuronal variability further, we identified two sparsely-distributed, brain-wide neuronal populations whose pre-motor activity predicted whether the larva would respond to a stimulus and, if so, which direction it would turn on a single-trial level. These populations predicted single-trial behavior seconds before stimulus onset, indicating they encoded time-varying internal modulating behavior, perhaps organizing behavior over longer timescales or enabling flexible behavior routines dependent on the animal's internal state. Our results provide the first whole-brain confirmation that sensory, motor, and internal variables are encoded in a highly mixed fashion throughout the brain and demonstrate that de-mixing each of these components at the neuronal population level is critical to understanding the mechanisms underlying the brain's remarkable flexibility and robustness.

Compensatory enhancement of input maintains aversive dopaminergic reinforcement in hungry Drosophila

Hungry animals need compensatory mechanisms to maintain flexible brain function, while modulation reconfigures circuits to prioritize resource seeking. In Drosophila, hunger inhibits aversively reinforcing dopaminergic neurons (DANs) to permit the expression of food-seeking memories. Multitasking the reinforcement system for motivation potentially undermines aversive learning. We find that chronic hunger mildly enhances aversive learning and that satiated-baseline and hunger-enhanced learning require endocrine adipokinetic hormone (AKH) signaling. Circulating AKH influences aversive learning via its receptor in four neurons in the ventral brain, two of which are octopaminergic. Connectomics revealed AKH receptor-expressing neurons to be upstream of several classes of ascending neurons, many of which are presynaptic to aversively reinforcing DANs. Octopaminergic modulation of and output from at least one of these ascending pathways is required for shock- and bitter-taste-reinforced aversive learning. We propose that coordinated enhancement of input compensates for hunger-directed inhibition of aversive DANs to preserve reinforcement when required.

The attenuation of activity-based anorexia by obese adipose tissue transplant is AgRP neuron-dependent

Anorexia nervosa (AN) is an eating disorder observed primarily in girls and women, and is characterized by a low body mass index, hypophagia, and hyperactivity. The activity-based anorexia (ABA) paradigm models aspects of AN, and refers to the progressive weight loss, hypophagia, and hyperactivity developed by rodents exposed to time-restricted feeding and running wheel access. Recent studies identified white adipose tissue (WAT) as a primary location of the 'metabolic memory' of prior obesity, and implicated WAT-derived signals as drivers of recidivism to obesity following weight loss. Here, we tested whether an obese WAT transplant could attenuate ABA-induced weight loss in normal female mice. Recipient mice received a WAT transplant harvested from normal chow-fed, or HFD-fed obese mice; obese fat recipient (OFR) and control fat recipient (CFR) mice were then tested for ABA. During ABA, OFR mice survived longer than CFR mice, defined as maintaining 75% of their initial body weight. Next, we tested whether agouti-related peptide (AgRP) neurons, which regulate feeding behavior and metabolic sensing, mediate this effect of obese WAT transplant. CFR and OFR mice received either control or neonatal AgRP ablation, and were assessed for ABA. OFR intact mice maintained higher body weights longer than CFR intact mice, and this effect was abolished by neonatal AgRP ablation; further, ablation reduced survival in OFR, but not CFR mice. In summary, obese WAT transplant communicates with AgRP neurons to increase body weight maintenance during ABA. These findings encourage the examination of obese WAT-derived factors as potential treatments for AN.

Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number

The brain's remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.

A Goldilocks theory of cognitive control: Balancing precision and efficiency with low-dimensional control states

Cognitive control orchestrates interactions between brain regions, guiding the transformation of information to support contextually appropriate and goal-directed behaviors. In this review, we propose a hierarchical model of cognitive control where low-dimensional control states direct the flow of high-dimensional representations between regions. This allows cognitive control to flexibly adapt to new environments and maintain the representational capacity to capture the richness of the world.

Cell-type-specific population dynamics of diverse reward computations

Computational analysis of cellular activity has developed largely independently of modern transcriptomic cell typology, but integrating these approaches may be essential for full insight into cellular-level mechanisms underlying brain function and dysfunction. Applying this approach to the habenula (a structure with diverse, intermingled molecular, anatomical, and computational features), we identified encoding of reward-predictive cues and reward outcomes in distinct genetically defined neural populations, including TH+ cells and Tac1+ cells. Data from genetically targeted recordings were used to train an optimized nonlinear dynamical systems model and revealed activity dynamics consistent with a line attractor. High-density, cell-type-specific electrophysiological recordings and optogenetic perturbation provided supporting evidence for this model. Reverse-engineering predicted how Tac1+ cells might integrate reward history, which was complemented by in vivo experimentation. This integrated approach describes a process by which data-driven computational models of population activity can generate and frame actionable hypotheses for cell-type-specific investigation in biological systems.

A serotonergic circuit regulates aversive associative learning under mitochondrial stress in C. elegans

Physiological stress triggers avoidance behavior, allowing the animals to stay away from potential threats and optimize their chance of survival. Mitochondrial disruption, a common physiological stress in diverse species, induces the nematode Caenorhabditis elegans to avoid non-pathogenic bacteria through a serotonergic neuronal circuit. We find that distinct neurons, communicated through serotonin and a specific serotonin receptor, are required for the formation and retrieval of this learned aversive behavior. This learned avoidance behavior is associated with increased serotonin synthesis, altered neuronal response property, and reprogramming of locomotion patterns. The circuit and neuromodulatory mechanisms described here offer important insights for stress-induced avoidance behavior.

A role for dopamine in C. elegans avoidance behavior induced by mitochondrial stress

Physiological stress triggers aversive learning that profoundly alters animal behavior. Systemic mitochondrial disruption induces avoidance of C. elegans to non-pathogenic food bacteria. Mutations in cat-2 and dat-1, which control dopamine synthesis and reuptake, respectively, impair this learned bacterial avoidance, suggesting that dopaminergic modulation is essential. Cell-specific rescue experiments indicate that dopamine likely acts from the CEP and ADE neurons to regulate learned bacterial avoidance. We find that mutations in multiple dopamine receptor genes, including dop-1, dop-2 and dop-3, reduced learned bacterial avoidance. Our work reveals a role for dopamine signaling in C. elegans learned avoidance behavior induced by mitochondrial stress.

AgRP neurons: Regulators of feeding, energy expenditure, and behavior

Neurons in the hypothalamic arcuate nucleus (ARC) that express agouti-related peptide (AgRP) govern a critical aspect of survival: the drive to eat. Equally important to survival is the timing at which food is consumed-seeking or eating food to alleviate hunger in the face of a more pressing threat, like the risk of predation, is clearly maladaptive. To ensure optimal prioritization of behaviors within a given environment, therefore, AgRP neurons must integrate signals of internal need states with contextual environmental cues. In this state-of-the-art review, we highlight recent advances that extend our understanding of AgRP neurons, including the neural circuits they engage to regulate feeding, energy expenditure, and behavior. We also discuss key findings that illustrate how both classical feedback and anticipatory feedforward signals regulate this neuronal population and how the integration of these signals may be disrupted in states of energy excess. Finally, we examine both technical and conceptual challenges facing the field moving forward.

Expressions of emotions across species

What are emotions and how should we study them? These questions give rise to ongoing controversy amongst scientists in the fields of neuroscience, psychology and philosophy, and have resulted in different views on emotions [1-6]. In this review, we define emotions as functional states that bear essential roles in promoting survival and thus have emerged through evolution. Emotions trigger behavioral, somatic, hormonal, and neurochemical reactions, referred to as expressions of emotion. We discuss recent studies on emotion expression across species and highlight emerging common principles. We argue that detailed and multidimensional analyses of emotion expressions are key to develop biology-based definitions of emotions and to reveal their neuronal underpinnings.

Spontaneous neural synchrony links intrinsic spinal sensory and motor networks during unconsciousness

Non-random functional connectivity during unconsciousness is a defining feature of supraspinal networks. However, its generalizability to intrinsic spinal networks remains incompletely understood. Previously, Barry et al., 2014 used fMRI to reveal bilateral resting state functional connectivity within sensory-dominant and, separately, motor-dominant regions of the spinal cord. Here, we record spike trains from large populations of spinal interneurons in vivo in rats and demonstrate that spontaneous functional connectivity also links sensory- and motor-dominant regions during unconsciousness. The spatiotemporal patterns of connectivity could not be explained by latent afferent activity or by populations of interconnected neurons spiking randomly. We also document connection latencies compatible with mono- and disynaptic interactions and putative excitatory and inhibitory connections. The observed activity is consistent with the hypothesis that salient, experience-dependent patterns of neural transmission introduced during behavior or by injury/disease are reactivated during unconsciousness. Such a spinal replay mechanism could shape circuit-level connectivity and ultimately behavior.

Transcriptome Analysis of NPFR Neurons Reveals a Connection Between Proteome Diversity and Social Behavior

Social behaviors are mediated by the activity of highly complex neuronal networks, the function of which is shaped by their transcriptomic and proteomic content. Contemporary advances in neurogenetics, genomics, and tools for automated behavior analysis make it possible to functionally connect the transcriptome profile of candidate neurons to their role in regulating behavior. In this study we used Drosophila melanogaster to explore the molecular signature of neurons expressing receptor for neuropeptide F (NPF), the fly homolog of neuropeptide Y (NPY). By comparing the transcription profile of NPFR neurons to those of nine other populations of neurons, we discovered that NPFR neurons exhibit a unique transcriptome, enriched with receptors for various neuropeptides and neuromodulators, as well as with genes known to regulate behavioral processes, such as learning and memory. By manipulating RNA editing and protein ubiquitination programs specifically in NPFR neurons, we demonstrate that the proper expression of their unique transcriptome and proteome is required to suppress male courtship and certain features of social group interaction. Our results highlight the importance of transcriptome and proteome diversity in the regulation of complex behaviors and pave the path for future dissection of the spatiotemporal regulation of genes within highly complex tissues, such as the brain.

Beyond somatosensation: Mrgprs in mucosal tissues

Mas-related G coupled receptors (Mrgprs) are a superfamily of receptors expressed in sensory neurons that are known to transmit somatic sensations from the skin to the central nervous system. Interestingly, Mrgprs have recently been implicated in sensory and motor functions of mucosal-associated neuronal circuits. The gastrointestinal and pulmonary tracts are constantly exposed to noxious stimuli. Therefore, it is likely that neuronal Mrgpr signaling pathways in mucosal tissues, akin to their family members expressed in the skin, might relay messages that alert the host when mucosal tissues are affected by damaging signals. Further, Mrgprs have been proposed to mediate the cross-talk between sensory neurons and immune cells that promotes host-protective functions at barrier sites. Although the mechanisms by which Mrgprs are activated in mucosal tissues are not completely understood, these exciting studies implicate Mrgprs as potential therapeutic targets for conditions affecting the intestinal and airway mucosa. This review will highlight the central role of Mrgpr signaling pathways in the regulation of homeostasis at mucosal tissues.