Neuromodulation of neurons and synapses

Diabetic peripheral neuropathy and neuromodulation techniques: a systematic review of progress and prospects

Neuromodulation for diabetic peripheral neuropathy represents a significant area of interest in the management of chronic pain associated with this condition. Diabetic peripheral neuropathy, a common complication of diabetes, is characterized by nerve damage due to high blood sugar levels that lead to symptoms, such as pain, tingling, and numbness, primarily in the hands and feet. The aim of this systematic review was to evaluate the efficacy of neuromodulatory techniques as potential therapeutic interventions for patients with diabetic peripheral neuropathy, while also examining recent developments in this domain. The investigation encompassed an array of neuromodulation methods, including frequency rhythmic electrical modulated systems, dorsal root ganglion stimulation, and spinal cord stimulation. This systematic review suggests that neuromodulatory techniques may be useful in the treatment of diabetic peripheral neuropathy. Understanding the advantages of these treatments will enable physicians and other healthcare providers to offer additional options for patients with symptoms refractory to standard pharmacologic treatments. Through these efforts, we may improve quality of life and increase functional capacity in patients suffering from complications related to diabetic neuropathy.

The unique role of anosognosia in the clinical progression of Alzheimer's disease: a disorder-network perspective

Alzheimer's disease (AD) encompasses a long continuum from a preclinical phase, characterized by neuropathological alterations albeit normal cognition, to a symptomatic phase, marked by its clinical manifestations. Yet, the neural mechanisms responsible for cognitive decline in AD patients remain poorly understood. Here, we posit that anosognosia, emerging from an error-monitoring failure due to early amyloid-β deposits in the posterior cingulate cortex, plays a causal role in the clinical progression of AD by preventing patients from being aware of their deficits and implementing strategies to cope with their difficulties, thus fostering a vicious circle of cognitive decline.

Neuromodulators in Acute and Chronic Cough in Children: An Update from the Literature

Cough is one of the most common reasons leading to pediatric consultations, negatively impacting the quality of life of patients and caregivers. It is defined as a sudden and forceful expulsion of air from the lungs through the mouth, typically triggered by irritation or the stimulation of sensory nerves in the respiratory tract. This reflex is controlled by a neural pathway that includes sensory receptors, afferent nerves, the brainstem's cough center, efferent nerves, and the muscles involved in coughing. Based on its duration, cough in children may be classified as acute, lasting less than four weeks, and chronic, persisting for more than four weeks. Neuromodulators have shown promise in reducing the frequency and severity of cough by modulating the neural pathways involved in the cough reflex, although they require careful monitoring and patient selection to optimize the outcomes. This review aims to examine the rationale for using neuromodulators in the management of cough in children.

Involvement of muscarinic acetylcholine receptor-mediated cholinergic neurotransmission in TMS-EEG responses

The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a valuable tool for investigating brain functions in health and disease. However, the detailed neural mechanisms underlying TMS-EEG responses, including TMS-evoked EEG potentials (TEPs) and TMS-induced EEG oscillations (TIOs), remain largely unknown. Combining TMS-EEG with pharmacological interventions provides a unique opportunity to elucidate the roles of specific receptor-mediated neurotransmissions in these responses. Here, we investigated the involvement of muscarinic acetylcholine receptor (mAChR)-mediated cholinergic neurotransmission in TMS-EEG responses by evaluating the effects of mAChR antagonists on TEPs and TIOs in twenty-four healthy participants using a randomized, placebo-controlled crossover design. TEPs and TIOs were measured before and after administering a single oral dose of scopolamine (a non-selective mAChR antagonist), biperiden (an M1 mAChR antagonist), or placebo, with TMS targeting the left medial prefrontal cortex (mPFC), angular gyrus (AG), and supplementary motor area (SMA). The results indicated that mAChR-mediated cholinergic neurotransmission played a role in TEPs, but not TIOs, in a target-specific manner. Specifically, scopolamine significantly increased the amplitude of a local TEP component between approximately 40 and 63 ms post-stimulus when TMS was applied to the SMA, but not the mPFC or AG. Biperiden produced a similar but less pronounced effect. Importantly, the effects of these mAChR antagonists on TEPs were independent of those on sensory-evoked EEG potentials caused by TMS-associated sensory stimulation. These findings expand our understanding of TMS-EEG physiology, providing insights for its application in physiological and clinical research.

Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanisms

Neuronal systems maintain stable functions despite large variability in their physiological components. Ion channel expression, in particular, is highly variable in neurons exhibiting similar electrophysiological phenotypes, which raises questions regarding how specific ion channel subsets reliably shape intrinsic properties of neurons. Here, we use detailed conductance-based modeling to explore how stable neuronal function is achieved despite variability in channel composition among neurons. Using dimensionality reduction, we uncover two principal dimensions in the channel conductance space that capture most of the variance of the observed variability. These two dimensions correspond to two sources of variability that originate from distinct physiologically relevant mechanisms underlying the regulation of neuronal activity, providing quantitative insights into how channel composition is linked to the electrophysiological activity of neurons. These insights allow us to understand and design a model-independent, reliable neuromodulation rule for variable neuronal populations.

Neuropeptide signaling network of Caenorhabditis elegans: from structure to behavior

Neuropeptides are abundant signaling molecules that control neuronal activity and behavior in all animals. Owing in part to its well-defined and compact nervous system, Caenorhabditis elegans has been one of the primary model organisms used to investigate how neuropeptide signaling networks are organized and how these neurochemicals regulate behavior. We here review recent work that has expanded our understanding of the neuropeptidergic signaling network in C. elegans by mapping the evolutionary conservation, the molecular expression, the receptor-ligand interactions, and the system-wide organization of neuropeptide pathways in the C. elegans nervous system. We also describe general insights into neuropeptidergic circuit motifs and the spatiotemporal range of peptidergic transmission that have emerged from in vivo studies on neuropeptide signaling. With efforts ongoing to chart peptide signaling networks in other organisms, the C. elegans neuropeptidergic connectome can serve as a prototype to further understand the organization and the signaling dynamics of these networks at organismal level.

Neuromodulator and neuropeptide sensors and probes for precise circuit interrogation in vivo

To determine how neuronal circuits encode and drive behavior, it is often necessary to measure and manipulate different aspects of neurochemical signaling in awake animals. Optogenetics and calcium sensors have paved the way for these types of studies, allowing for the perturbation and readout of spiking activity within genetically defined cell types. However, these methods lack the ability to further disentangle the roles of individual neuromodulator and neuropeptides on circuits and behavior. We review recent advances in chemical biology tools that enable precise spatiotemporal monitoring and control over individual neuroeffectors and their receptors in vivo. We also highlight discoveries enabled by such tools, revealing how these molecules signal across different timescales to drive learning, orchestrate behavioral changes, and modulate circuit activity.

Tremendous Fidelity of Vitamin D3 in Age-related Neurological Disorders

Vitamin D3 (VD) is a secosteroid hormone and shows a pleiotropic effect in brain-related disorders where it regulates redox imbalance, inflammation, apoptosis, energy production, and growth factor synthesis. Vitamin D3's active metabolic form, 1,25-dihydroxy Vitamin D3 (1,25(OH)2D3 or calcitriol), is a known regulator of several genes involved in neuroplasticity, neuroprotection, neurotropism, and neuroinflammation. Multiple studies suggest that VD deficiency can be proposed as a risk factor for the development of several age-related neurological disorders. The evidence for low serum levels of 25-hydroxy Vitamin D3 (25(OH)D3 or calcidiol), the major circulating form of VD, is associated with an increased risk of Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), dementia, and cognitive impairment. Despite decades of evidence on low VD association with neurological disorders, the precise molecular mechanism behind its beneficial effect remains controversial. Here, we will be delving into the neurobiological importance of VD and discuss its benefits in different neuropsychiatric disorders. The focus will be on AD, PD, and HD as they share some common clinical, pathological, and epidemiological features. The central focus will be on the different attributes of VD in the aspect of its anti-oxidative, anti-inflammatory, anti-apoptotic, anti-cholinesterase activity, and psychotropic effect in different neurodegenerative diseases.

Fiber-based in vivo imaging: unveiling avenues for exploring mechanisms of synaptic plasticity and neuronal adaptations underlying behavior

In recent decades, various subfields within neuroscience, spanning molecular, cellular, and systemic dimensions, have significantly advanced our understanding of the elaborate molecular and cellular mechanisms that underpin learning, memory, and adaptive behaviors. There have been notable advancements in imaging techniques, particularly in reaching superficial brain structures. This progress has led to their widespread adoption in numerous laboratories. However, essential physiological and cognitive processes, including sensory integration, emotional modulation of motivated behavior, motor regulation, learning, and memory consolidation, are intricately encoded within deeper brain structures. Hence, visualization techniques such as calcium imaging using miniscopes have gained popularity for studying brain activity in unrestrained animals. Despite its utility, miniscope technology is associated with substantial brain tissue damage caused by gradient refractive index lens implantation. Furthermore, its imaging capabilities are primarily confined to the neuronal somata level, thus constraining a comprehensive exploration of subcellular processes underlying adaptive behaviors. Consequently, the trajectory of neuroscience's future hinges on the development of minimally invasive optical fiber-based endo-microscopes optimized for cellular, subcellular, and molecular imaging within the intricate depths of the brain. In pursuit of this goal, select research groups have invested significant efforts in advancing this technology. In this review, we present a perspective on the potential impact of this innovation on various aspects of neuroscience, enabling the functional exploration of in vivo cellular and subcellular processes that underlie synaptic plasticity and the neuronal adaptations that govern behavior.

Convergent Comodulation Reduces Interindividual Variability of Circuit Output

Ionic current levels of identified neurons vary substantially across individual animals. Yet, under similar conditions, neural circuit output can be remarkably similar, as evidenced in many motor systems. All neural circuits are influenced by multiple neuromodulators, which provide flexibility to their output. These neuromodulators often overlap in their actions by modulating the same channel type or synapse, yet have neuron-specific actions resulting from distinct receptor expression. Because of this different receptor expression pattern, in the presence of multiple convergent neuromodulators, a common downstream target would be activated more uniformly in circuit neurons across individuals. We therefore propose that a baseline tonic (non-saturating) level of comodulation by convergent neuromodulators can reduce interindividual variability of circuit output. We tested this hypothesis in the pyloric circuit of the crab, Cancer borealis Multiple excitatory neuropeptides converge to activate the same voltage-gated current in this circuit, but different subsets of pyloric neurons have receptors for each peptide. We quantified the interindividual variability of the unmodulated pyloric circuit output by measuring the activity phases, cycle frequency, and intraburst spike number and frequency. We then examined the variability in the presence of different combinations and concentrations of three neuropeptides. We found that at mid-level concentration (30 nM) but not at near-threshold (1 nM) or saturating (1 µM) concentrations, comodulation by multiple neuropeptides reduced the circuit output variability. Notably, the interindividual variability of response properties of an isolated neuron was not reduced by comodulation, suggesting that the reduction of output variability may emerge as a network effect.

Hydrogel-Based Artificial Synapses for Sustainable Neuromorphic Electronics

Hydrogels find widespread applications in biomedicine because of their outstanding biocompatibility, biodegradability, and tunable material properties. Hydrogels can be chemically functionalized or reinforced to respond to physical or chemical stimulation, which opens up new possibilities in the emerging field of intelligent bioelectronics. Here, the state-of-the-art in functional hydrogel-based transistors and memristors is reviewed as potential artificial synapses. Within these systems, hydrogels can serve as semisolid dielectric electrolytes in transistors and as switching layers in memristors. These synaptic devices with volatile and non-volatile resistive switching show good adaptability to external stimuli for short-term and long-term synaptic memory effects, some of which are integrated into synaptic arrays as artificial neurons; although, there are discrepancies in switching performance and efficacy. By comparing different hydrogels and their respective properties, an outlook is provided on a new range of biocompatible, environment-friendly, and sustainable neuromorphic hardware. How potential energy-efficient information storage and processing can be achieved using artificial neural networks with brain-inspired architecture for neuromorphic computing is described. The development of hydrogel-based artificial synapses can significantly impact the fields of neuromorphic bionics, biometrics, and biosensing.

Biomimetic Neuromorphic Sensory System via Electrolyte Gated Transistors

Biomimetic neuromorphic sensing systems, inspired by the structure and function of biological neural networks, represent a major advancement in the field of sensing technology and artificial intelligence. This review paper focuses on the development and application of electrolyte gated transistors (EGTs) as the core components (synapses and neuros) of these neuromorphic systems. EGTs offer unique advantages, including low operating voltage, high transconductance, and biocompatibility, making them ideal for integrating with sensors, interfacing with biological tissues, and mimicking neural processes. Major advances in the use of EGTs for neuromorphic sensory applications such as tactile sensors, visual neuromorphic systems, chemical neuromorphic systems, and multimode neuromorphic systems are carefully discussed. Furthermore, the challenges and future directions of the field are explored, highlighting the potential of EGT-based biomimetic systems to revolutionize neuromorphic prosthetics, robotics, and human-machine interfaces. Through a comprehensive analysis of the latest research, this review is intended to provide a detailed understanding of the current status and future prospects of biomimetic neuromorphic sensory systems via EGT sensing and integrated technologies.

Emotional vocalizations alter behaviors and neurochemical release into the amygdala

The basolateral amygdala (BLA), a brain center of emotional expression, contributes to acoustic communication by first interpreting the meaning of social sounds in the context of the listener's internal state, then organizing the appropriate behavioral responses. We propose that modulatory neurochemicals such as acetylcholine (ACh) and dopamine (DA) provide internal-state signals to the BLA while an animal listens to social vocalizations. We tested this in a vocal playback experiment utilizing highly affective vocal sequences associated with either mating or restraint, then sampled and analyzed fluids within the BLA for a broad range of neurochemicals and observed behavioral responses of adult male and female mice. In male mice, playback of restraint vocalizations increased ACh release and usually decreased DA release, while playback of mating sequences evoked the opposite neurochemical release patterns. In non-estrus female mice, patterns of ACh and DA release with mating playback were similar to males. Estrus females, however, showed increased ACh, associated with vigilance, as well as increased DA, associated with reward-seeking. Experimental groups that showed increased ACh release also showed the largest increases in an aversive behavior. These neurochemical release patterns and several behavioral responses depended on a single prior experience with the mating and restraint behaviors. Our results support a model in which ACh and DA provide contextual information to sound analyzing BLA neurons that modulate their output to downstream brain regions controlling behavioral responses to social vocalizations.

Neuropeptide modulation of bidirectional internetwork synapses

Oscillatory networks underlying rhythmic motor behaviors, and sensory and complex neural processing, are flexible, even in their neuronal composition. Neuromodulatory inputs enable neurons to switch participation between networks or participate in multiple networks simultaneously. Neuromodulation of internetwork synapses can both recruit and coordinate a switching neuron in a second network. We previously identified an example in which a neuron is recruited into dual-network activity via peptidergic modulation of intrinsic properties. We now ask whether the same neuropeptide also modulates internetwork synapses for internetwork coordination. The crab (Cancer borealis) stomatogastric nervous system contains two well-defined feeding-related networks (pyloric, food filtering, ∼1 Hz; gastric mill, food chewing, ∼0.1 Hz). The projection neuron MCN5 uses the neuropeptide Gly1-SIFamide to recruit the pyloric-only lateral posterior gastric (LPG) neuron into dual pyloric- plus gastric mill-timed bursting via modulation of LPG's intrinsic properties. Descending input is not required for a coordinated rhythm, thus intranetwork synapses between LPG and its second network must underlie coordination among these neurons. However, synapses between LPG and gastric mill neurons have not been documented. Using two-electrode voltage-clamp recordings, we found that graded synaptic currents between LPG and gastric mill neurons (lateral gastric, inferior cardiac, and dorsal gastric) were primarily negligible in saline, but were enhanced by Gly1-SIFamide. Furthermore, LPG and gastric mill neurons entrain each other during Gly1-SIFamide application, indicating bidirectional, functional connectivity. Thus, a neuropeptide mediates neuronal switching through parallel actions, modulating intrinsic properties for recruitment into a second network and as shown here, also modulating bidirectional internetwork synapses for coordination.NEW & NOTEWORTHY Neuromodulation can enable neurons to simultaneously coordinate with separate networks. Both recruitment into, and coordination with, a second network can occur via modulation of internetwork synapses. Alternatively, recruitment can occur via modulation of intrinsic ionic currents. We find that the same neuropeptide previously determined to modulate intrinsic currents also modulates bidirectional internetwork synapses that are typically ineffective. Thus, complementary modulatory peptide actions enable recruitment and coordination of a neuron into a second network.

Topological Quantum Switching Enabled Neuroelectronic Synaptic Modulators for Brain Computer Interface

Aging and genetic-related disorders in the human brain lead to impairment of daily cognitive functions. Due to their neural synaptic complexity and the current limits of knowledge, reversing these disorders remains a substantial challenge for brain-computer interfaces (BCI). In this work, a solution is provided to potentially override aging and neurological disorder-related cognitive function loss in the human brain through the application of the authors' quantum synaptic device. To illustrate this point, a quantum topological insulator (QTI) Bi2Se2Te-based synaptic neuroelectronic device, where the electric field-induced tunable topological surface edge states and quantum switching properties make them a premier option for establishing artificial synaptic neuromodulation approaches, is designed and developed. Leveraging these unique quantum synaptic properties, the developed synaptic device provides the capability to neuromodulate distorted neural signals, leading to the reversal of age-related disorders via BCI. With the synaptic neuroelectronic characteristics of this device, excellent efficacy in treating cognitive neural dysfunctions through modulated neuromorphic stimuli is demonstrated. As a proof of concept, real-time neuromodulation of electroencephalogram (EEG) deduced distorted event-related potentials (ERP) is demonstrated by modulation of the synaptic device array.

Neuroimmune modulation by tryptophan derivatives in neurological and inflammatory disorders

The nervous and immune systems are highly developed, and each performs specialized physiological functions. However, they work together, and their dysfunction is associated with various diseases. Specialized molecules, such as neurotransmitters, cytokines, and more general metabolites, are essential for the appropriate regulation of both systems. Tryptophan, an essential amino acid, is converted into functional molecules such as serotonin and kynurenine, both of which play important roles in the nervous and immune systems. The role of kynurenine metabolites in neurodegenerative and psychiatric diseases has recently received particular attention. Recently, we found that hyperactivity of the kynurenine pathway is a critical risk factor for septic shock. In this review, we first outline neuroimmune interactions and tryptophan derivatives and then summarized the changes in tryptophan metabolism in neurological disorders. Finally, we discuss the potential of tryptophan derivatives as therapeutic targets for neuroimmune disorders.

Common synaptic inputs and persistent inward currents of vastus lateralis motor units are reduced in older male adults

Although muscle atrophy may partially account for age-related strength decline, it is further influenced by alterations of neural input to muscle. Persistent inward currents (PIC) and the level of common synaptic inputs to motoneurons influence neuromuscular function. However, these have not yet been described in the aged human quadriceps. High-density surface electromyography (HDsEMG) signals were collected from the vastus lateralis of 15 young (mean ± SD, 23 ± 5 y) and 15 older (67 ± 9 y) men during submaximal sustained and 20-s ramped contractions. HDsEMG signals were decomposed to identify individual motor unit discharges, from which PIC amplitude and intramuscular coherence were estimated. Older participants produced significantly lower knee extensor torque (p < 0.001) and poorer force tracking ability (p < 0.001) than young. Older participants also had lower PIC amplitude (p = 0.001) and coherence estimates in the alpha frequency band (p < 0.001) during ramp contractions when compared to young. Persistent inward currents and common synaptic inputs are lower in the vastus lateralis of older males when compared to young. These data highlight altered neural input to the clinically and functionally important quadriceps, further underpinning age-related loss of function which may occur independently of the loss of muscle mass.

Unified control of temporal and spatial scales of sensorimotor behavior through neuromodulation of short-term synaptic plasticity

Neuromodulators have been shown to alter the temporal profile of short-term synaptic plasticity (STP); however, the computational function of this neuromodulation remains unexplored. Here, we propose that the neuromodulation of STP provides a general mechanism to scale neural dynamics and motor outputs in time and space. We trained recurrent neural networks that incorporated STP to produce complex motor trajectories-handwritten digits-with different temporal (speed) and spatial (size) scales. Neuromodulation of STP produced temporal and spatial scaling of the learned dynamics and enhanced temporal or spatial generalization compared to standard training of the synaptic weights in the absence of STP. The model also accounted for the results of two experimental studies involving flexible sensorimotor timing. Neuromodulation of STP provides a unified and biologically plausible mechanism to control the temporal and spatial scales of neural dynamics and sensorimotor behaviors.

CKR-1 orchestrates two motor states from a single motoneuron in C. elegans

Neuromodulation is pivotal in modifying neuronal properties and motor states. CKR-1, a homolog of the cholecystokinin receptor, modulates robust escape steering and undulation body bending in C. elegans. Nevertheless, the mechanisms through which CKR-1 governs these motor states remain elusive. We elucidate the head motoneuron SMD as the orchestrator of both motor states. This regulation involves two neuropeptides: NLP-12 from DVA enhances undulation body curvature, while NLP-18 from ASI amplifies Ω-turn head curvature. Moreover, synthetic NLP-12 and NLP-18 peptides elicit CKR-1-dependent currents in Xenopus oocytes and Ca2+ transients in SMD neurons. Notably, CKR-1 shows higher sensitivity to NLP-18 compared to NLP-12. In situ patch-clamp recordings reveal CKR-1, NLP-12, and NLP-18 are not essential for neurotransmission at C. elegans neuromuscular junction, suggesting that SMD independently regulates head and body bending. Our studies illustrate that a single motoneuron SMD utilizes a cholecystokinin receptor CKR-1 to integrate two motor states.

Neuromodulator regulation and emotions: insights from the crosstalk of cell signaling

The unraveling of the regulatory mechanisms that govern neuronal excitability is a major challenge for neuroscientists worldwide. Neurotransmitters play a critical role in maintaining the balance between excitatory and inhibitory activity in the brain. The balance controls cognitive functions and emotional responses. Glutamate and γ-aminobutyric acid (GABA) are the primary excitatory and inhibitory neurotransmitters of the brain, respectively. Disruptions in the balance between excitatory and inhibitory transmission are implicated in several psychiatric disorders, including anxiety disorders, depression, and schizophrenia. Neuromodulators such as dopamine and acetylcholine control cognition and emotion by regulating the excitatory/inhibitory balance initiated by glutamate and GABA. Dopamine is closely associated with reward-related behaviors, while acetylcholine plays a role in aversive and attentional behaviors. Although the physiological roles of neuromodulators have been extensively studied neuroanatomically and electrophysiologically, few researchers have explored the interplay between neuronal excitability and cell signaling and the resulting impact on emotion regulation. This review provides an in-depth understanding of "cell signaling crosstalk" in the context of neuronal excitability and emotion regulation. It also anticipates that the next generation of neurochemical analyses, facilitated by integrated phosphorylation studies, will shed more light on this topic.

Bioelectronic Medicine: a multidisciplinary roadmap from biophysics to precision therapies

Bioelectronic Medicine stands as an emerging field that rapidly evolves and offers distinctive clinical benefits, alongside unique challenges. It consists of the modulation of the nervous system by precise delivery of electrical current for the treatment of clinical conditions, such as post-stroke movement recovery or drug-resistant disorders. The unquestionable clinical impact of Bioelectronic Medicine is underscored by the successful translation to humans in the last decades, and the long list of preclinical studies. Given the emergency of accelerating the progress in new neuromodulation treatments (i.e., drug-resistant hypertension, autoimmune and degenerative diseases), collaboration between multiple fields is imperative. This work intends to foster multidisciplinary work and bring together different fields to provide the fundamental basis underlying Bioelectronic Medicine. In this review we will go from the biophysics of the cell membrane, which we consider the inner core of neuromodulation, to patient care. We will discuss the recently discovered mechanism of neurotransmission switching and how it will impact neuromodulation design, and we will provide an update on neuronal and glial basis in health and disease. The advances in biomedical technology have facilitated the collection of large amounts of data, thereby introducing new challenges in data analysis. We will discuss the current approaches and challenges in high throughput data analysis, encompassing big data, networks, artificial intelligence, and internet of things. Emphasis will be placed on understanding the electrochemical properties of neural interfaces, along with the integration of biocompatible and reliable materials and compliance with biomedical regulations for translational applications. Preclinical validation is foundational to the translational process, and we will discuss the critical aspects of such animal studies. Finally, we will focus on the patient point-of-care and challenges in neuromodulation as the ultimate goal of bioelectronic medicine. This review is a call to scientists from different fields to work together with a common endeavor: accelerate the decoding and modulation of the nervous system in a new era of therapeutic possibilities.

Switching neuron contributions to second network activity

Network flexibility is important for adaptable behaviors. This includes neuronal switching, where neurons alter their network participation, including changing from single- to dual-network activity. Understanding the implications of neuronal switching requires determining how a switching neuron interacts with each of its networks. Here, we tested 1) whether "home" and second networks, operating via divergent rhythm generation mechanisms, regulate a switching neuron and 2) if a switching neuron, recruited via modulation of intrinsic properties, contributes to rhythm or pattern generation in a new network. Small, well-characterized feeding-related networks (pyloric, ∼1 Hz; gastric mill, ∼0.1 Hz) and identified modulatory inputs make the isolated crab (Cancer borealis) stomatogastric nervous system (STNS) a useful model to study neuronal switching. In particular, the neuropeptide Gly1-SIFamide switches the lateral posterior gastric (LPG) neuron (2 copies) from pyloric-only to dual-frequency pyloric/gastric mill (fast/slow) activity via modulation of LPG-intrinsic properties. Using current injections to manipulate neuronal activity, we found that gastric mill, but not pyloric, network neurons regulated the intrinsically generated LPG slow bursting. Conversely, selective elimination of LPG from both networks using photoinactivation revealed that LPG regulated gastric mill neuron-firing frequencies but was not necessary for gastric mill rhythm generation or coordination. However, LPG alone was sufficient to produce a distinct pattern of network coordination. Thus, modulated intrinsic properties underlying dual-network participation may constrain which networks can regulate switching neuron activity. Furthermore, recruitment via intrinsic properties may occur in modulatory states where it is important for the switching neuron to actively contribute to network output.NEW & NOTEWORTHY We used small, well-characterized networks to investigate interactions between rhythmic networks and neurons that switch their network participation. For a neuron switching into dual-network activity, only the second network regulated its activity in that network. In addition, the switching neuron was sufficient but not necessary to coordinate second network neurons and regulated their activity levels. Thus, regulation of switching neurons may be selective, and a switching neuron is not necessarily simply a follower in additional networks.

Applications of information geometry to spiking neural network activity

The space of possible behaviors that complex biological systems may exhibit is unimaginably vast, and these systems often appear to be stochastic, whether due to variable noisy environmental inputs or intrinsically generated chaos. The brain is a prominent example of a biological system with complex behaviors. The number of possible patterns of spikes emitted by a local brain circuit is combinatorially large, although the brain may not make use of all of them. Understanding which of these possible patterns are actually used by the brain, and how those sets of patterns change as properties of neural circuitry change is a major goal in neuroscience. Recently, tools from information geometry have been used to study embeddings of probabilistic models onto a hierarchy of model manifolds that encode how model outputs change as a function of their parameters, giving a quantitative notion of "distances" between outputs. We apply this method to a network model of excitatory and inhibitory neural populations to understand how the competition between membrane and synaptic response timescales shapes the network's information geometry. The hyperbolic embedding allows us to identify the statistical parameters to which the model behavior is most sensitive, and demonstrate how the ranking of these coordinates changes with the balance of excitation and inhibition in the network.

Spatiotemporal Mapping and Molecular Basis of Whole-brain Circuit Maturation

Brain development is highly dynamic and asynchronous, marked by the sequential maturation of functional circuits across the brain. The timing and mechanisms driving circuit maturation remain elusive due to an inability to identify and map maturing neuronal populations. Here we create DevATLAS (Developmental Activation Timing-based Longitudinal Acquisition System) to overcome this obstacle. We develop whole-brain mapping methods to construct the first longitudinal, spatiotemporal map of circuit maturation in early postnatal mouse brains. Moreover, we uncover dramatic impairments within the deep cortical layers in a neurodevelopmental disorders (NDDs) model, demonstrating the utility of this resource to pinpoint when and where circuit maturation is disrupted. Using DevATLAS, we reveal that early experiences accelerate the development of hippocampus-dependent learning by increasing the synaptically mature granule cell population in the dentate gyrus. Finally, DevATLAS enables the discovery of molecular mechanisms driving activity-dependent circuit maturation.

Modulation by Neuropeptides with Overlapping Targets Results in Functional Overlap in Oscillatory Circuit Activation

Neuromodulation lends flexibility to neural circuit operation but the general notion that different neuromodulators sculpt neural circuit activity into distinct and characteristic patterns is complicated by interindividual variability. In addition, some neuromodulators converge onto the same signaling pathways, with similar effects on neurons and synapses. We compared the effects of three neuropeptides on the rhythmic pyloric circuit in the stomatogastric ganglion of male crabs, Cancer borealis Proctolin (PROC), crustacean cardioactive peptide (CCAP), and red pigment concentrating hormone (RPCH) activate the same modulatory inward current, I MI, and have convergent actions on synapses. However, while PROC targets all four neuron types in the core pyloric circuit, CCAP and RPCH target the same subset of only two neurons. After removal of spontaneous neuromodulator release, none of the neuropeptides restored the control cycle frequency, but all restored the relative timing between neuron types. Consequently, differences between neuropeptide effects were mainly found in the spiking activity of different neuron types. We performed statistical comparisons using the Euclidean distance in the multidimensional space of normalized output attributes to obtain a single measure of difference between modulatory states. Across preparations, the circuit output in PROC was distinguishable from CCAP and RPCH, but CCAP and RPCH were not distinguishable from each other. However, we argue that even between PROC and the other two neuropeptides, population data overlapped enough to prevent reliable identification of individual output patterns as characteristic for a specific neuropeptide. We confirmed this notion by showing that blind classifications by machine learning algorithms were only moderately successful.Significance Statement It is commonly assumed that distinct behaviors or circuit activities can be elicited by different neuromodulators. Yet it is unknown to what extent these characteristic actions remain distinct across individuals. We use a well-studied circuit model of neuromodulation to examine the effects of three neuropeptides, each known to produce a distinct activity pattern in controlled studies. We find that, when compared across individuals, the three peptides elicit activity patterns that are either statistically indistinguishable or show too much overlap to be labeled characteristic. We ascribe this to interindividual variability and overlapping subcellular actions of the modulators. Because both factors are common in all neural circuits, these findings have broad significance for understanding chemical neuromodulatory actions while considering interindividual variability.

Astrocytes in Pain Perception: A Systems Neuroscience Approach

Astrocytes play an active role in the function of the brain integrating neuronal activity and regulating back neuronal dynamic. They have recently emerged as active contributors of brain's emergent properties such as perceptions. Here, we analyzed the role of astrocytes in pain perception from the lens of systems neuroscience, and we do this by analyzing how astrocytes encode nociceptive information within brain processing areas and how they are key regulators of the internal state that determines pain perception. Specifically, we discuss the dynamic interactions between astrocytes and neuromodulators, such as noradrenaline, highlighting their role in shaping the level of activation of the neuronal ensemble, thereby influencing the experience of pain. Also, we will discuss the possible implications of an "Astro-NeuroMatrix" in the integration of pain across sensory, affective, and cognitive dimensions of pain perception.

An energy costly architecture of neuromodulators for human brain evolution and cognition

In comparison to other species, the human brain exhibits one of the highest energy demands relative to body metabolism. It remains unclear whether this heightened energy demand uniformly supports an enlarged brain or if specific signaling mechanisms necessitate greater energy. We hypothesized that the regional distribution of energy demands will reveal signaling strategies that have contributed to human cognitive development. We measured the energy distribution within the brain functional connectome using multimodal brain imaging and found that signaling pathways in evolutionarily expanded regions have up to 67% higher energetic costs than those in sensory-motor regions. Additionally, histology, transcriptomic data, and molecular imaging independently reveal an up-regulation of signaling at G-protein-coupled receptors in energy-demanding regions. Our findings indicate that neuromodulator activity is predominantly involved in cognitive functions, such as reading or memory processing. This study suggests that an up-regulation of neuromodulator activity, alongside increased brain size, is a crucial aspect of human brain evolution.

Cell type specificity for circuit output in the midbrain dopaminergic system

Midbrain dopaminergic neurons are a relatively small group of neurons in the mammalian brain controlling a wide range of behaviors. In recent years, increasingly sophisticated tracing, imaging, transcriptomic, and machine learning approaches have provided substantial insights into the anatomical, molecular, and functional heterogeneity of dopaminergic neurons. Despite this wealth of new knowledge, it remains unclear whether and how the diverse features defining dopaminergic subclasses converge to delineate functional ensembles within the dopaminergic system. Here, we review recent studies investigating various aspects of dopaminergic heterogeneity and discuss how development, behavior, and disease influence subtype characteristics. We then outline what further approaches could be pursued to gain a more inclusive picture of dopaminergic diversity, which could be crucial to understanding the functional architecture of this system.

A dietary polyphenol metabolite alters CA1 excitability ex vivo and mildly affects cortico-hippocampal field potential generators in anesthetized animals

Dietary polyphenols have beneficial effects in situations of impaired cognition in acute models of neurodegeneration. The possibility that they may have a direct effect on the electrical activity of neuronal populations has not been tested. We explored the electrophysiological action of protocatechuic acid (PCA) on CA1 pyramidal cells ex vivo and network activity in anesthetized female rats using pathway-specific field potential (FP) generators obtained from laminar FPs in cortex and hippocampus. Whole-cell recordings from CA1 pyramidal cells revealed increased synaptic potentials, particularly in response to basal dendritic excitation, while the associated evoked firing was significantly reduced. This counterintuitive result was attributed to a marked increase of the rheobase and voltage threshold, indicating a decreased ability to generate spikes in response to depolarizing current. Systemic administration of PCA only slightly altered the ongoing activity of some FP generators, although it produced a striking disengagement of infraslow activities between the cortex and hippocampus on a scale of minutes. To our knowledge, this is the first report showing the direct action of a dietary polyphenol on electrical activity, performing neuromodulatory roles at both the cellular and network levels.

Comodulation reduces interindividual variability of circuit output

Ionic current levels of identified neurons vary substantially across individual animals. Yet, under similar conditions, neural circuit output can be remarkably similar, as evidenced in many motor systems. All neural circuits are influenced by multiple neuromodulators which provide flexibility to their output. These neuromodulators often overlap in their actions by modulating the same channel type or synapse, yet have neuron-specific actions resulting from distinct receptor expression. Because of this different receptor expression pattern, in the presence of multiple convergent neuromodulators, a common downstream target would be activated more uniformly in circuit neurons across individuals. We therefore propose that a baseline tonic (non-saturating) level of comodulation by convergent neuromodulators can reduce interindividual variability of circuit output. We tested this hypothesis in the pyloric circuit of the crab, Cancer borealis. Multiple excitatory neuropeptides converge to activate the same voltage-gated current in this circuit, but different subsets of pyloric neurons have receptors for each peptide. We quantified the interindividual variability of the unmodulated pyloric circuit output by measuring the activity phases, cycle frequency and intraburst spike number and frequency. We then examined the variability in the presence of different combinations and concentrations of three neuropeptides. We found that at mid-level concentration (30 nM) but not at near-threshold (1 nM) or saturating (1 μM) concentrations, comodulation by multiple neuropeptides reduced the circuit output variability. Notably, the interindividual variability of response properties of an isolated neuron was not reduced by comodulation, suggesting that the reduction of output variability may emerge as a network effect.

From Enzymatic Dopamine Biosensors to OECT Biosensors of Dopamine

Neurotransmitters are an important category of substances used inside the nervous system, whose detection with biosensors has been seriously addressed in the last decades. Dopamine, a neurotransmitter from the catecholamine family, was recently discovered to have implications for cardiac arrest or muscle contractions. In addition to having many other neuro-psychiatric implications, dopamine can be detected in blood, urine, and sweat. This review highlights the importance of biosensors as influential tools for dopamine recognition. The first part of this article is related to an introduction to biosensors for neurotransmitters, with a focus on dopamine. The regular methods in their detection are expensive and require high expertise personnel. A major direction of evolution of these biosensors has expanded with the integration of active biological materials suitable for molecular recognition near electronic devices. Secondly, for dopamine in particular, the miniaturized biosensors offer excellent sensitivity and specificity and offer cheaper detection than conventional spectrometry, while their linear detection ranges from the last years fall exactly on the clinical intervals. Thirdly, the applications of novel nanomaterials and biomaterials to these biosensors are discussed. Older generations, metabolism-based or enzymatic biosensors, could not detect concentrations below the micro-molar range. But new generations of biosensors combine aptamer receptors and organic electrochemical transistors, OECTs, as transducers. They have pushed the detection limit to the pico-molar and even femto-molar ranges, which fully correspond to the usual ranges of clinical detection of human dopamine in body humors that cover 0.1 ÷ 10 nM. In addition, if ten years ago the use of natural dopamine receptors on cell membranes seemed impossible for biosensors, the actual technology allows co-integrate transistors and vesicles with natural receptors of dopamine, like G protein-coupled receptors. The technology is still complicated, but the uni-molecular detection selectivity is promising.

Past, present, and future of tools for dopamine detection

Dopamine (DA) is a critical neuromodulator involved in various brain functions. To understand how DA regulates neural circuits and behaviors in the physiological and pathological conditions, it is essential to have tools that enable the direct detection of DA dynamics in vivo. Recently, genetically encoded DA sensors based on G protein-coupled receptors revolutionized this field, as it allows us to track in vivo DA dynamic with unprecedented spatial-temporal resolution, high molecular specificity, and sub-second kinetics. In this review, we first summarize traditional DA detection methods. Then we focus on the development of genetically encoded DA sensors and feature its significance to understanding dopaminergic neuromodulation across diverse behaviors and species. Finally, we present our perspectives about the future direction of the next-generation DA sensors and extend their potential applications. Overall, this review offers a comprehensive perspective on the past, present, and future of DA detection tools, with important implications for the study of DA functions in health and disease.

Robust Resting-State Dynamics in a Large-Scale Spiking Neural Network Model of Area CA3 in the Mouse Hippocampus

Hippocampal area CA3 performs the critical auto-associative function underlying pattern completion in episodic memory. Without external inputs, the electrical activity of this neural circuit reflects the spontaneous spiking interplay among glutamatergic pyramidal neurons and GABAergic interneurons. However, the network mechanisms underlying these resting-state firing patterns are poorly understood. Leveraging the Hippocampome.org knowledge base, we developed a data-driven, large-scale spiking neural network (SNN) model of mouse CA3 with 8 neuron types, 90,000 neurons, 51 neuron-type specific connections, and 250,000,000 synapses. We instantiated the SNN in the CARLsim4 multi-GPU simulation environment using the Izhikevich and Tsodyks-Markram formalisms for neuronal and synaptic dynamics, respectively. We analyzed the resultant population activity upon transient activation. The SNN settled into stable oscillations with a biologically plausible grand-average firing frequency, which was robust relative to a wide range of transient activation. The diverse firing patterns of individual neuron types were consistent with existing knowledge of cell type-specific activity in vivo. Altered network structures that lacked neuron- or connection-type specificity were neither stable nor robust, highlighting the importance of neuron type circuitry. Additionally, external inputs reflecting dentate mossy fibers shifted the observed rhythms to the gamma band. We freely released the CARLsim4-Hippocampome framework on GitHub to test hippocampal hypotheses. Our SNN may be useful to investigate the circuit mechanisms underlying the computational functions of CA3. Moreover, our approach can be scaled to the whole hippocampal formation, which may contribute to elucidating how the unique neuronal architecture of this system subserves its crucial cognitive roles.

Modulation by neuropeptides with overlapping targets results in functional overlap in oscillatory circuit activation

Neuromodulation lends flexibility to neural circuit operation but the general notion that different neuromodulators sculpt neural circuit activity into distinct and characteristic patterns is complicated by interindividual variability. In addition, some neuromodulators converge onto the same signaling pathways, with similar effects on neurons and synapses. We compared the effects of three neuropeptides on the rhythmic pyloric circuit in the crab Cancer borealis stomatogastric nervous system. Proctolin (PROC), crustacean cardioactive peptide (CCAP), and red pigment concentrating hormone (RPCH) all activate the same modulatory inward current, IMI, and have convergent actions on synapses. However, while PROC targets all four neuron types in the core pyloric circuit, CCAP and RPCH target the same subset of only two neurons. After removal of spontaneous neuromodulator release, none of the neuropeptides restored the control cycle frequency, but all restored the relative timing between neuron types. Consequently, differences between neuropeptide effects were mainly found in the spiking activity of different neuron types. We performed statistical comparisons using the Euclidean distance in the multidimensional space of normalized output attributes to obtain a single measure of difference between modulatory states. Across preparations, circuit output in PROC was distinguishable from CCAP and RPCH, but CCAP and RPCH were not distinguishable from each other. However, we argue that even between PROC and the other two neuropeptides, population data overlapped enough to prevent reliable identification of individual output patterns as characteristic for a specific neuropeptide. We confirmed this notion by showing that blind classifications by machine learning algorithms were only moderately successful.

Distinctive properties of biological neural networks and recent advances in bottom-up approaches toward a better biologically plausible neural network

Although it may appear infeasible and impractical, building artificial intelligence (AI) using a bottom-up approach based on the understanding of neuroscience is straightforward. The lack of a generalized governing principle for biological neural networks (BNNs) forces us to address this problem by converting piecemeal information on the diverse features of neurons, synapses, and neural circuits into AI. In this review, we described recent attempts to build a biologically plausible neural network by following neuroscientifically similar strategies of neural network optimization or by implanting the outcome of the optimization, such as the properties of single computational units and the characteristics of the network architecture. In addition, we proposed a formalism of the relationship between the set of objectives that neural networks attempt to achieve, and neural network classes categorized by how closely their architectural features resemble those of BNN. This formalism is expected to define the potential roles of top-down and bottom-up approaches for building a biologically plausible neural network and offer a map helping the navigation of the gap between neuroscience and AI engineering.

Comparison of fluorescence biosensors and whole-cell patch clamp recording in detecting ACh, NE, and 5-HT

The communication between neurons and, in some cases, between neurons and non-neuronal cells, through neurotransmission plays a crucial role in various physiological and pathological processes. Despite its importance, the neuromodulatory transmission in most tissues and organs remains poorly understood due to the limitations of current tools for direct measurement of neuromodulatory transmitters. In order to study the functional roles of neuromodulatory transmitters in animal behaviors and brain disorders, new fluorescent sensors based on bacterial periplasmic binding proteins (PBPs) and G-protein coupled receptors have been developed, but their results have not been compared to or multiplexed with traditional methods such as electrophysiological recordings. In this study, a multiplexed method was developed to measure acetylcholine (ACh), norepinephrine (NE), and serotonin (5-HT) in cultured rat hippocampal slices using simultaneous whole-cell patch clamp recordings and genetically encoded fluorescence sensor imaging. The strengths and weaknesses of each technique were compared, and the results showed that both techniques did not interfere with each other. In general, genetically encoded sensors GRAB_NE and GRAB_5HT1.₀ showed better stability compared to electrophysiological recordings in detecting NE and 5-HT, while electrophysiological recordings had faster temporal kinetics in reporting ACh. Moreover, genetically encoded sensors mainly report the presynaptic neurotransmitter release while electrophysiological recordings provide more information of the activation of downstream receptors. In sum, this study demonstrates the use of combined techniques to measure neurotransmitter dynamics and highlights the potential for future multianalyte monitoring.

The endogenous cannabinoid system modulates male sexual behavior expression

The endocannabinoid system (ECS) plays a key neuromodulatory role in the brain. Main features of endocannabinoids (eCBs) are that they are produced on demand, in response to enhanced neuronal activity, act as retrograde messengers, and participate in the induction of brain plasticity processes. Sexual activity is a motivated behavior and therefore, the mesolimbic dopaminergic system (MSL) plays a central role in the control of its appetitive component (drive to engage in copulation). In turn, copulation activates mesolimbic dopamine neurons and repeated copulation produces the continuous activation of the MSL system. Sustained sexual activity leads to the achievement of sexual satiety, which main outcome is the transient transformation of sexually active male rats into sexually inhibited animals. Thus, 24 h after copulation to satiety, the sexually satiated males exhibit a decreased sexual motivation and do not respond to the presence of a sexually receptive female with sexual activity. Interestingly, blockade of cannabinoid receptor 1 (CB1R) during the copulation to satiety process, interferes with both the appearance of the long-lasting sexual inhibition and the decrease in sexual motivation in the sexually satiated males. This effect is reproduced when blocking CB1R at the ventral tegmental area evidencing the involvement of MSL eCBs in the induction of this sexual inhibitory state. Here we review the available evidence regarding the effects of cannabinoids, including exogenously administered eCBs, on male rodent sexual behavior of both sexually competent animals and rat sub populations spontaneously showing copulatory deficits, considered useful to model some human male sexual dysfunctions. We also include the effects of cannabis preparations on human male sexual activity. Finally, we review the role played by the ECS in the control of male sexual behavior expression with the aid of the sexual satiety phenomenon. Sexual satiety appears as a suitable model for the study of the relationship between eCB signaling, MSL synaptic plasticity and the modulation of male sexual motivation under physiological conditions that might be useful for the understanding of MSL functioning, eCB-mediated plasticity and their relationship with motivational processes.

Application of Original Therapy for Stimulation of Oral Areas Innervated by the Trigeminal Nerve in a Child with Beckwith-Wiedemann Syndrome

About 90% of children diagnosed with classic BWS have macroglossia, and 40% of them are submitted to surgical tongue reduction. The purpose of our article is to present a case study of a 5-month-old child with BWS who was treated with an original therapy for stimulation of oral areas innervated by the trigeminal nerve. The therapy included stimulation of the upper and lower lip and muscles of the floor of the mouth. The treatment was provided by a therapist once a week. In addition, the child was stimulated every day at home by his mother. After 3 months, a significant improvement in oral alignment and function was achieved. Preliminary observations of therapy application for stimulation regions innervated by the trigeminal nerve in children with Beckwith-Wiedemann syndrome seem promising. The original therapy for stimulation of oral areas innervated by the trigeminal nerve is a good alternative to existing methods of surgical tongue reduction in children with BWS and macroglossia.

A CPG-Based Versatile Control Framework for Metameric Earthworm-Like Robotic Locomotion

Annelids such as earthworms are considered to have central pattern generators (CPGs) that generate rhythms in neural circuits to coordinate the deformation of body segments for effective locomotion. At present, the states of earthworm-like robot segments are often assigned holistically and artificially by mimicking the earthworms' retrograde peristalsis wave, which is unable to adapt their gaits for variable environments and tasks. This motivates the authors to extend the bioinspired research from morphology to neurobiology by mimicking the CPG to build a versatile framework for spontaneous motion control. Here, the spatiotemporal dynamics is exploited from the coupled Hopf oscillators to not only unify the two existing gait generators for restoring temporal-symmetric phase-coordinated gaits and discrete gaits but also generate novel temporal-asymmetric phase-coordinated gaits. Theoretical and experimental tests consistently confirm that the introduction of temporal asymmetry improves the robot's locomotion performance. The CPG-based controller also enables seamless online switching of locomotion gaits to avoid abrupt changes, sharp stops, and starts, thus improving the robot's adaptability in variable working scenarios.

Electrical stimulation methods and protocols for the treatment of traumatic brain injury: a critical review of preclinical research

BACKGROUND

Traumatic brain injury (TBI) is a leading cause of disabilities resulting from cognitive and neurological deficits, as well as psychological disorders. Only recently, preclinical research on electrical stimulation methods as a potential treatment of TBI sequelae has gained more traction. However, the underlying mechanisms of the anticipated improvements induced by these methods are still not fully understood. It remains unclear in which stage after TBI they are best applied to optimize the therapeutic outcome, preferably with persisting effects. Studies with animal models address these questions and investigate beneficial long- and short-term changes mediated by these novel modalities.

METHODS

In this review, we present the state-of-the-art in preclinical research on electrical stimulation methods used to treat TBI sequelae. We analyze publications on the most commonly used electrical stimulation methods, namely transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), deep brain stimulation (DBS) and vagus nerve stimulation (VNS), that aim to treat disabilities caused by TBI. We discuss applied stimulation parameters, such as the amplitude, frequency, and length of stimulation, as well as stimulation time frames, specifically the onset of stimulation, how often stimulation sessions were repeated and the total length of the treatment. These parameters are then analyzed in the context of injury severity, the disability under investigation and the stimulated location, and the resulting therapeutic effects are compared. We provide a comprehensive and critical review and discuss directions for future research. RESULTS AND CONCLUSION: We find that the parameters used in studies on each of these stimulation methods vary widely, making it difficult to draw direct comparisons between stimulation protocols and therapeutic outcome. Persisting beneficial effects and adverse consequences of electrical simulation are rarely investigated, leaving many questions about their suitability for clinical applications. Nevertheless, we conclude that the stimulation methods discussed here show promising results that could be further supported by additional research in this field.

Mathematical models of learning and what can be learned from them

Learning is a multi-faceted phenomenon of critical importance and hence attracted a great deal of research, both experimental and theoretical. In this review, we will consider some of the paradigmatic examples of learning and discuss the common themes in theoretical learning research, such as levels of modeling and their corresponding relation to experimental observations and mathematical ideas common to different types of learning.

GABABR silencing of nerve terminals

Control of neurotransmission efficacy is central to theories of how the brain computes and stores information. Presynaptic G-protein coupled receptors (GPCRs) are critical in this problem as they locally influence synaptic strength and can operate on a wide range of time scales. Among the mechanisms by which GPCRs impact neurotransmission is by inhibiting voltage-gated calcium (Ca2+) influx in the active zone. Here, using quantitative analysis of both single bouton Ca2+ influx and exocytosis, we uncovered an unexpected non-linear relationship between the magnitude of action potential driven Ca2+ influx and the concentration of external Ca2+ ([Ca2+]e). We find that this unexpected relationship is leveraged by GPCR signaling when operating at the nominal physiological set point for [Ca2+]e, 1.2 mM, to achieve complete silencing of nerve terminals. These data imply that the information throughput in neural circuits can be readily modulated in an all-or-none fashion at the single synapse level when operating at the physiological set point.

Neural circuit regulation by identified modulatory projection neurons

Rhythmic behaviors (e.g., walking, breathing, and chewing) are produced by central pattern generator (CPG) circuits. These circuits are highly dynamic due to a multitude of input they receive from hormones, sensory neurons, and modulatory projection neurons. Such inputs not only turn CPG circuits on and off, but they adjust their synaptic and cellular properties to select behaviorally relevant outputs that last from seconds to hours. Similar to the contributions of fully identified connectomes to establishing general principles of circuit function and flexibility, identified modulatory neurons have enabled key insights into neural circuit modulation. For instance, while bath-applying neuromodulators continues to be an important approach to studying neural circuit modulation, this approach does not always mimic the neural circuit response to neuronal release of the same modulator. There is additional complexity in the actions of neuronally-released modulators due to: (1) the prevalence of co-transmitters, (2) local- and long-distance feedback regulating the timing of (co-)release, and (3) differential regulation of co-transmitter release. Identifying the physiological stimuli (e.g., identified sensory neurons) that activate modulatory projection neurons has demonstrated multiple “modulatory codes” for selecting particular circuit outputs. In some cases, population coding occurs, and in others circuit output is determined by the firing pattern and rate of the modulatory projection neurons. The ability to perform electrophysiological recordings and manipulations of small populations of identified neurons at multiple levels of rhythmic motor systems remains an important approach for determining the cellular and synaptic mechanisms underlying the rapid adaptability of rhythmic neural circuits.

Neural learning rules for generating flexible predictions and computing the successor representation

The predictive nature of the hippocampus is thought to be useful for memory-guided cognitive behaviors. Inspired by the reinforcement learning literature, this notion has been formalized as a predictive map called the successor representation (SR). The SR captures a number of observations about hippocampal activity. However, the algorithm does not provide a neural mechanism for how such representations arise. Here, we show the dynamics of a recurrent neural network naturally calculate the SR when the synaptic weights match the transition probability matrix. Interestingly, the predictive horizon can be flexibly modulated simply by changing the network gain. We derive simple, biologically plausible learning rules to learn the SR in a recurrent network. We test our model with realistic inputs and match hippocampal data recorded during random foraging. Taken together, our results suggest that the SR is more accessible in neural circuits than previously thought and can support a broad range of cognitive functions.

From circuits to behavior: Amygdala dysfunction in fragile X syndrome

Fragile X syndrome (FXS) is a neurodevelopmental disorder caused by a repeat expansion mutation in the promotor region of the FMR1 gene resulting in transcriptional silencing and loss of function of fragile X messenger ribonucleoprotein 1 protein (FMRP). FMRP has a well-defined role in the early development of the brain. Thus, loss of the FMRP has well-known consequences for normal cellular and synaptic development leading to a variety of neuropsychiatric disorders including an increased prevalence of amygdala-based disorders. Despite our detailed understanding of the pathophysiology of FXS, the precise cellular and circuit-level underpinnings of amygdala-based disorders is incompletely understood. In this review, we discuss the development of the amygdala, the role of neuromodulation in the critical period plasticity, and recent advances in our understanding of how synaptic and circuit-level changes in the basolateral amygdala contribute to the behavioral manifestations seen in FXS.

Cocaine regulates sensory filtering in cortical pyramidal neurons

Exposure to cocaine leads to robust changes in the structure and function of neurons within the mesocorticolimbic pathway. However, little is known about how cocaine influences the processing of information within the sensory cortex. We address this by using patch-clamp and juxtacellular voltage recordings and two-photon Ca2+ imaging in vivo to investigate the influence of acute cocaine exposure on layer 2/3 (L2/3) pyramidal neurons within the primary somatosensory cortex (S1). Here, cocaine dampens membrane potential state transitions and decreases spontaneous somatic action potentials and Ca2+ transients. In contrast to the uniform decrease in background spontaneous activity, cocaine has a heterogeneous influence on sensory encoding, increasing tactile-evoked responses in dendrites that do not typically encode sensory information and decreasing responses in those dendrites that are more reliable sensory encoders. Combined, these findings suggest that cocaine acts as a filter that suppresses background noise to selectively modulate incoming sensory information.

Convergent Energy State-Dependent Antagonistic Signaling by Cocaine- and Amphetamine-Regulated Transcript (CART) and Neuropeptide Y (NPY) Modulates the Plasticity of Forebrain Neurons to Regulate Feeding in Zebrafish

Dynamic reconfiguration of circuit function subserves the flexibility of innate behaviors tuned to physiological states. Internal energy stores adaptively regulate feeding-associated behaviors and integrate opposing hunger and satiety signals at the level of neural circuits. Across vertebrate lineages, the neuropeptides cocaine- and amphetamine-regulated transcript (CART) and neuropeptide Y (NPY) have potent anorexic and orexic functions, respectively, and show energy-state-dependent expression in interoceptive neurons. However, how the antagonistic activities of these peptides modulate circuit plasticity remains unclear. Using behavioral, neuroanatomical, and activity analysis in adult zebrafish of both sexes, along with pharmacological interventions, we show that CART and NPY activities converge on a population of neurons in the dorsomedial telencephalon (Dm). Although CART facilitates glutamatergic neurotransmission at the Dm, NPY dampens the response to glutamate. In energy-rich states, CART enhances NMDA receptor (NMDAR) function by protein kinase A/protein kinase C (PKA/PKC)-mediated phosphorylation of the NR1 subunit of the NMDAR complex. Conversely, starvation triggers NPY-mediated reduction in phosphorylated NR1 via calcineurin activation and inhibition of cAMP production leading to reduced responsiveness to glutamate. Our data identify convergent integration of CART and NPY inputs by the Dm neurons to generate nutritional state-dependent circuit plasticity that is correlated with the behavioral switch induced by the opposing actions of satiety and hunger signals.SIGNIFICANCE STATEMENT Internal energy needs reconfigure neuronal circuits to adaptively regulate feeding behavior. Energy-state-dependent neuropeptide release can signal energy status to feeding-associated circuits and modulate circuit function. CART and NPY are major anorexic and orexic factors, respectively, but the intracellular signaling pathways used by these peptides to alter circuit function remain uncharacterized. We show that CART and NPY-expressing neurons from energy-state interoceptive areas project to a novel telencephalic region, Dm, in adult zebrafish. CART increases the excitability of Dm neurons, whereas NPY opposes CART activity. Antagonistic signaling by CART and NPY converge onto NMDA-receptor function to modulate glutamatergic neurotransmission. Thus, opposing activities of anorexic CART and orexic NPY reconfigure circuit function to generate flexibility in feeding behavior.

Genetically encoded fluorescent sensors for imaging neuronal dynamics in vivo

The brain relies on many forms of dynamic activities in individual neurons, from synaptic transmission to electrical activity and intracellular signaling events. Monitoring these neuronal activities with high spatiotemporal resolution in the context of animal behavior is a necessary step to achieve a mechanistic understanding of brain function. With the rapid development and dissemination of highly optimized genetically encoded fluorescent sensors, a growing number of brain activities can now be visualized in vivo. To date, cellular calcium imaging, which has been largely used as a proxy for electrical activity, has become a mainstay in systems neuroscience. While challenges remain, voltage imaging of neural populations is now possible. In addition, it is becoming increasingly practical to image over half a dozen neurotransmitters, as well as certain intracellular signaling and metabolic activities. These new capabilities enable neuroscientists to test previously unattainable hypotheses and questions. This review summarizes recent progress in the development and delivery of genetically encoded fluorescent sensors, and highlights example applications in the context of in vivo imaging.

Circadian time- and sleep-dependent modulation of cortical parvalbumin-positive inhibitory neurons

Parvalbumin-positive neurons (PVs) are the main class of inhibitory neurons in the mammalian central nervous system. By examining diurnal changes in synaptic and neuronal activity of PVs in the supragranular layer of the mouse primary visual cortex (V1), we found that both PV input and output are modulated in a time- and sleep-dependent manner throughout the 24-h day. We first show that PV-evoked inhibition is stronger by the end of the light cycle (ZT12) relative to the end of the dark cycle (ZT0), which is in line with the lower inhibitory input of PV neurons at ZT12 than at ZT0. Interestingly, PV inhibitory and excitatory synaptic transmission slowly oscillate in opposite directions during the light/dark cycle. Although excitatory synapses are predominantly regulated by experience, inhibitory synapses are regulated by sleep, via acetylcholine activating M1 receptors. Consistent with synaptic regulation of PVs, we further show in vivo that spontaneous PV activity displays daily rhythm mainly determined by visual experience, which negatively correlates with the activity cycle of surrounding pyramidal neurons and the dorsal lateral geniculate nucleus-evoked responses in V1. These findings underscore the physiological significance of PV's daily modulation.