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1. Cavefish brain atlases reveal functional and anatomical convergence across independently evolved populations

   https://doi.org/10.1126/sciadv.aba3126  

   Jaggard, James B.; Lloyd, Evan; Yuiska, Anders; Patch, Adam; Fily, Yaouen; Kowalko, Johanna E.; Appelbaum, Lior; Duboue, Erik R.; Keene, Alex C. (September 2020, Science Advances)

   null (Ed.)

   Environmental perturbation can drive behavioral evolution and associated changes in brain structure and function. The Mexican fish species, Astyanax mexicanus , includes eyed river-dwelling surface populations and multiple independently evolved populations of blind cavefish. We used whole-brain imaging and neuronal mapping of 684 larval fish to generate neuroanatomical atlases of surface fish and three different cave populations. Analyses of brain region volume and neural circuits associated with cavefish behavior identified evolutionary convergence in hindbrain and hypothalamic expansion, and changes in neurotransmitter systems, including increased numbers of catecholamine and hypocretin/orexin neurons. To define evolutionary changes in brain function, we performed whole-brain activity mapping associated with behavior. Hunting behavior evoked activity in sensory processing centers, while sleep-associated activity differed in the rostral zone of the hypothalamus and tegmentum. These atlases represent a comparative brain-wide study of intraspecies variation in vertebrates and provide a resource for studying the neural basis of behavioral evolution. 

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2. Thirst-associated preoptic neurons encode an aversive motivational drive

   Allen W, DeNardo LA (September 2017, Science)

   Water deprivation produces a drive to seek and consume water. How neural activity creates this motivation remains poorly understood.We used activity-dependent genetic labeling to characterize neurons activated by water deprivation in the hypothalamic median preoptic nucleus (MnPO). Single-cell transcriptional profiling revealed that dehydration-activated MnPO neurons consist of a single excitatory cell type. After optogenetic activation of these neurons, mice drank water and performed an operant lever-pressing task for water reward with rates that scaled with stimulation frequency.This stimulation was aversive, and instrumentally pausing stimulation could reinforce lever-pressing. Activity of these neurons gradually decreased over the course of an operant session.Thus, the activity of dehydration-activated MnPO neurons establishes a scalable, persistent, and aversive internal state that dynamically controls thirst-motivated behavior. 

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3. Nutrigenomic regulation of sensory plasticity

   https://doi.org/10.7554/eLife.83979  

   Sung, Hayeon; Vaziri, Anoumid; Wilinski, Daniel; Woerner, Riley KR; Freddolino, Peter L; Dus, Monica (March 2023, eLife)

   Diet profoundly influences brain physiology, but how metabolic information is transmuted into neural activity and behavior changes remains elusive. Here, we show that the metabolic enzyme O-GlcNAc Transferase (OGT) moonlights on the chromatin of the D. melanogaster gustatory neurons to instruct changes in chromatin accessibility and transcription that underlie sensory adaptations to a high-sugar diet. OGT works synergistically with the Mitogen Activated Kinase/Extracellular signal Regulated Kinase (MAPK/ERK) rolled and its effector stripe (also known as EGR2 or Krox20) to integrate activity information. OGT also cooperates with the epigenetic silencer Polycomb Repressive Complex 2.1 (PRC2.1) to decrease chromatin accessibility and repress transcription in the high-sugar diet. This integration of nutritional and activity information changes the taste neurons’ responses to sugar and the flies’ ability to sense sweetness. Our findings reveal how nutrigenomic signaling generates neural activity and behavior in response to dietary changes in the sensory neurons. 

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4. Scale-free behavioral dynamics directly linked with scale-free cortical dynamics

   https://doi.org/10.7554/eLife.79950  

   Jones, Sabrina A; Barfield, Jacob H; Norman, V Kindler; Shew, Woodrow L (January 2023, eLife)

   Naturally occurring body movements and collective neural activity both exhibit complex dynamics, often with scale-free, fractal spatiotemporal structure. Scale-free dynamics of both brain and behavior are important because each is associated with functional benefits to the organism. Despite their similarities, scale-free brain activity and scale-free behavior have been studied separately, without a unified explanation. Here, we show that scale-free dynamics of mouse behavior and neurons in the visual cortex are strongly related. Surprisingly, the scale-free neural activity is limited to specific subsets of neurons, and these scale-free subsets exhibit stochastic winner-take-all competition with other neural subsets. This observation is inconsistent with prevailing theories of scale-free dynamics in neural systems, which stem from the criticality hypothesis. We develop a computational model which incorporates known cell-type-specific circuit structure, explaining our findings with a new type of critical dynamics. Our results establish neural underpinnings of scale-free behavior and clear behavioral relevance of scale-free neural activity. 

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5. Functional Implications of Dale's Law in Balanced Neuronal Network Dynamics and Decision Making

   https://doi.org/10.3389/fnins.2022.801847  

   Barranca, Victor J.; Bhuiyan, Asha; Sundgren, Max; Xing, Fangzhou (February 2022, Frontiers in Neuroscience)

   The notion that a neuron transmits the same set of neurotransmitters at all of its post-synaptic connections, typically known as Dale's law, is well supported throughout the majority of the brain and is assumed in almost all theoretical studies investigating the mechanisms for computation in neuronal networks. Dale's law has numerous functional implications in fundamental sensory processing and decision-making tasks, and it plays a key role in the current understanding of the structure-function relationship in the brain. However, since exceptions to Dale's law have been discovered for certain neurons and because other biological systems with complex network structure incorporate individual units that send both positive and negative feedback signals, we investigate the functional implications of network model dynamics that violate Dale's law by allowing each neuron to send out both excitatory and inhibitory signals to its neighbors. We show how balanced network dynamics, in which large excitatory and inhibitory inputs are dynamically adjusted such that input fluctuations produce irregular firing events, are theoretically preserved for a single population of neurons violating Dale's law. We further leverage this single-population network model in the context of two competing pools of neurons to demonstrate that effective decision-making dynamics are also produced, agreeing with experimental observations from honeybee dynamics in selecting a food source and artificial neural networks trained in optimal selection. Through direct comparison with the classical two-population balanced neuronal network, we argue that the one-population network demonstrates more robust balanced activity for systems with less computational units, such as honeybee colonies, whereas the two-population network exhibits a more rapid response to temporal variations in network inputs, as required by the brain. We expect this study will shed light on the role of neurons violating Dale's law found in experiment as well as shared design principles across biological systems that perform complex computations. 

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