Noradrenergic 'tone' determines dichotomous control of cortical spike-timing-dependent plasticity

Noradrenergic regulation of cue-guided decision making and impulsivity is doubly dissociable across frontal brain regions

RATIONALE

Win-paired stimuli can promote risk taking in experimental gambling paradigms in both rats and humans. We previously demonstrated that atomoxetine, a noradrenaline reuptake inhibitor, and guanfacine, a selective α2A adrenergic receptor agonist, reduced risk taking on the cued rat gambling task (crGT), a rodent assay of risky choice in which wins are accompanied by salient cues. Both compounds also decreased impulsive premature responding.

OBJECTIVE

The key neural loci mediating these effects were unknown. The lateral orbitofrontal cortex (lOFC) and the medial prefrontal cortex (mPFC), which are highly implicated in risk assessment, action selection, and impulse control, receive dense noradrenergic innervation. We therefore infused atomoxetine and guanfacine directly into either the lOFC or prelimbic (PrL) mPFC prior to task performance.

RESULTS

When infused into the lOFC, atomoxetine improved decision making score and adaptive lose-shift behaviour in males, but not in females, without altering motor impulsivity. Conversely, intra-PrL atomoxetine improved impulse control in risk preferring animals of both sexes, but did not alter decision making. Guanfacine administered into the PrL, but not lOFC, also altered motor impulsivity in all subjects, though in the opposite direction to atomoxetine.

CONCLUSIONS

These data highlight a double dissociation between the behavioural effects of noradrenergic signaling across frontal regions with respect to risky choice and impulsive action. Given that the influence of noradrenergic manipulations on motor impulsivity could depend on baseline risk preference, these data also suggest that the noradrenaline system may function differently in subjects that are susceptible to the risk-promoting lure of win-associated cues.

How to fail with paired VNS therapy

Vagus nerve stimulation (VNS) has gained enormous traction as a promising bioelectronic therapy. In particular, the delivery of VNS paired with training to promote neural changes has demonstrated clinical success for stroke recovery and found far-reaching application in other domains, from autism to psychiatric disorders to normal learning. The success of paired VNS has been extensively documented. Here, we consider a more unusual question: why does VNS have such broad utility, and perhaps more importantly, when does VNS not work? We present a discussion of the concepts that underlie VNS therapy and an anthology of studies that describe conditions in which these concepts are violated and VNS fails. We focus specifically on the mechanisms engaged by implanted VNS, and how the parameters of stimulation, stimulation method, pharmacological manipulations, accompanying comorbidities, and specifics of concurrent training interact with these mechanisms to impact the efficacy of VNS therapy. As paired VNS therapy is increasing translated to clinical implementation, a clear understanding of the conditions in which it does, and critically, does not work is fundamental to the success of this approach.

Meta-SpikePropamine: learning to learn with synaptic plasticity in spiking neural networks

We propose that in order to harness our understanding of neuroscience toward machine learning, we must first have powerful tools for training brain-like models of learning. Although substantial progress has been made toward understanding the dynamics of learning in the brain, neuroscience-derived models of learning have yet to demonstrate the same performance capabilities as methods in deep learning such as gradient descent. Inspired by the successes of machine learning using gradient descent, we introduce a bi-level optimization framework that seeks to both solve online learning tasks and improve the ability to learn online using models of plasticity from neuroscience. We demonstrate that models of three-factor learning with synaptic plasticity taken from the neuroscience literature can be trained in Spiking Neural Networks (SNNs) with gradient descent via a framework of learning-to-learn to address challenging online learning problems. This framework opens a new path toward developing neuroscience inspired online learning algorithms.

Neural Field Continuum Limits and the Structure–Function Partitioning of Cognitive–Emotional Brain Networks

In The cognitive-emotional brain, Pessoa overlooks continuum effects on nonlinear brain network connectivity by eschewing neural field theories and physiologically derived constructs representative of neuronal plasticity. The absence of this content, which is so very important for understanding the dynamic structure-function embedding and partitioning of brains, diminishes the rich competitive and cooperative nature of neural networks and trivializes Pessoa’s arguments, and similar arguments by other authors, on the phylogenetic and operational significance of an optimally integrated brain filled with variable-strength neural connections. Riemannian neuromanifolds, containing limit-imposing metaplastic Hebbian- and antiHebbian-type control variables, simulate scalable network behavior that is difficult to capture from the simpler graph-theoretic analysis preferred by Pessoa and other neuroscientists. Field theories suggest the partitioning and performance benefits of embedded cognitive-emotional networks that optimally evolve between exotic classical and quantum computational phases, where matrix singularities and condensations produce degenerate structure-function homogeneities unrealistic of healthy brains. Some network partitioning, as opposed to unconstrained embeddedness, is thus required for effective execution of cognitive-emotional network functions and, in our new era of neuroscience, should be considered a critical aspect of proper brain organization and operation.

Adaptive control of synaptic plasticity integrates micro- and macroscopic network function

Synaptic plasticity configures interactions between neurons and is therefore likely to be a primary driver of behavioral learning and development. How this microscopic-macroscopic interaction occurs is poorly understood, as researchers frequently examine models within particular ranges of abstraction and scale. Computational neuroscience and machine learning models offer theoretically powerful analyses of plasticity in neural networks, but results are often siloed and only coarsely linked to biology. In this review, we examine connections between these areas, asking how network computations change as a function of diverse features of plasticity and vice versa. We review how plasticity can be controlled at synapses by calcium dynamics and neuromodulatory signals, the manifestation of these changes in networks, and their impacts in specialized circuits. We conclude that metaplasticity-defined broadly as the adaptive control of plasticity-forges connections across scales by governing what groups of synapses can and can't learn about, when, and to what ends. The metaplasticity we discuss acts by co-opting Hebbian mechanisms, shifting network properties, and routing activity within and across brain systems. Asking how these operations can go awry should also be useful for understanding pathology, which we address in the context of autism, schizophrenia and Parkinson's disease.

Tag and capture: how salient experiences target and rescue nearby events in memory

The long-term fate of a memory is not exclusively determined by the events occurring at the moment of encoding. Research at the cellular, circuit, and behavioral levels is beginning to reveal how neurochemical activations in the moments surrounding an event can retroactively and proactively rescue weak memory for seemingly mundane experiences. We review emerging evidence showing enhancement of weakly formed memories encoded minutes to hours before or after a related motivationally relevant experience. We discuss proposed neurobiological mechanisms for strengthening weak memories formed in temporal proximity to a strong event, and how this knowledge could be leveraged to improve memory for information that is prone to forgetting.

Response Time Distributions and the Accumulation of Visual Evidence in Freely Moving Mice

Response time (RT) distributions are histograms of the observed RTs for discriminative choices, comprising a rich source of empirical information to study perceptual processes. The drift-diffusion model (DDM), a mathematical formulation predicting decision tasks, reproduces the RT distributions, contributing to our understanding of these processes from a theoretical perspective. Notably, although the mouse is a popular model system for studying brain function and behavior, little is known about mouse perceptual RT distributions, and their description from an information-accumulation perspective. We combined an automated visual discrimination task with pharmacological micro-infusions of targeted brain regions to acquire thousands of responses from freely-moving adult mice. Both choices and escape latencies showed a strong dependency on stimulus discriminability. By applying a DDM fit to our experimental data, we found that the rate of incoming evidence (drift rate) increased with stimulus contrast but was reversibly impaired when inactivating the primary visual cortex (V1). Other brain regions involved in the decision-making process, the posterior parietal cortex (PPC) and the frontal orienting fields (FOF), also influenced relevant parameters from the DDM. The large number of empirical observations that we collected for this study allowed us to achieve accurate convergence for the model fit. Therefore, changes in the experimental conditions were mirrored by changes in model parameters, suggesting the participation of relevant brain areas in the decision-making process. This approach could help interpret future studies involving attention, discrimination, and learning in adult mice.

Neural circuit for social authentication in song learning

Social interactions are essential when learning to communicate. In human speech and bird song, infants must acquire accurate vocalization patterns and learn to associate them with live tutors and not mimetic sources. However, the neural mechanism of social reality during vocal learning remains unknown. Here, we characterize a neural circuit for social authentication in support of accurate song learning in the zebra finch. We recorded neural activity in the attention/arousal state control center, the locus coeruleus (LC), of juvenile birds during song learning from a live adult tutor. LC activity increased with real, not artificial, social information during learning that enhanced the precision and robustness of the learned song. During live social song learning, LC activity regulated long-term song-selective neural responsiveness in an auditory memory region, the caudomedial nidopallium (NCM). In accord, optogenetic inhibition of LC presynaptic signaling in the NCM reduced NCM neuronal responsiveness to live tutor singing and impaired song learning. These results demonstrate that the LC-NCM neural circuit integrates sensory evidence of real social interactions, distinct from song acoustic features, to authenticate song learning. The findings suggest a general mechanism for validating social information in brain development.

Human and bird infants acquire vocal patterns from live, not mimetic, tutors. Here, the authors identified the neuronal circuits to authenticate social information in zebra finch song learning, suggesting a brain developmental mechanism via social interactions.

Canonical neural networks perform active inference

This work considers a class of canonical neural networks comprising rate coding models, wherein neural activity and plasticity minimise a common cost function-and plasticity is modulated with a certain delay. We show that such neural networks implicitly perform active inference and learning to minimise the risk associated with future outcomes. Mathematical analyses demonstrate that this biological optimisation can be cast as maximisation of model evidence, or equivalently minimisation of variational free energy, under the well-known form of a partially observed Markov decision process model. This equivalence indicates that the delayed modulation of Hebbian plasticity-accompanied with adaptation of firing thresholds-is a sufficient neuronal substrate to attain Bayes optimal inference and control. We corroborated this proposition using numerical analyses of maze tasks. This theory offers a universal characterisation of canonical neural networks in terms of Bayesian belief updating and provides insight into the neuronal mechanisms underlying planning and adaptive behavioural control.

Vagus Nerve Stimulation as a Treatment for Fear and Anxiety in Individuals with Autism Spectrum Disorder

Anxiety disorders affect a large percentage of individuals who have an autism spectrum disorder (ASD). In children with ASD, excessive anxiety is also linked to gastrointestinal problems, self-injurious behaviors, and depressive symptoms. Exposure-based cognitive behavioral therapies are effective treatments for anxiety disorders in children with ASD, but high relapse rates indicate the need for additional treatment strategies. This perspective discusses evidence from preclinical research, which indicates that vagus nerve stimulation (VNS) paired with exposure to fear-provoking stimuli and situations could offer benefits as an adjuvant treatment for anxiety disorders that coexist with ASD. Vagus nerve stimulation is approved for use in the treatment of epilepsy, depression, and more recently as an adjuvant in rehabilitative training following stroke. In preclinical models, VNS shows promise in simultaneously enhancing consolidation of extinction memories and reducing anxiety. In this review, we will present potential mechanisms by which VNS could treat fear and anxiety in ASD. We also discuss potential uses of VNS to treat depression and epilepsy in the context of ASD, and noninvasive methods to stimulate the vagus nerve.

Active inference leads to Bayesian neurophysiology

The neuronal substrates that implement the free-energy principle and ensuing active inference at the neuron and synapse level have not been fully elucidated. This Review considers possible neuronal substrates underlying the principle. First, the foundations of the free-energy principle are introduced, and then its ability to empirically explain various brain functions and psychological and biological phenomena in terms of Bayesian inference is described. Mathematically, the dynamics of neural activity and plasticity that minimise a cost function can be cast as performing Bayesian inference that minimises variational free energy. This equivalence licenses the adoption of the free-energy principle as a universal characterisation of neural networks. Further, the neural network structure itself represents a generative model under which an agent operates. A virtue of this perspective is that it enables the formal association of neural network properties with prior beliefs that regulate inference and learning. The possible neuronal substrates that implement prior beliefs and how to empirically examine the theory are discussed. This perspective renders brain activity explainable, leading to a deeper understanding of the neuronal mechanisms underlying basic psychology and psychiatric disorders in terms of an implicit generative model.

Noradrenergic terminal short-term potentiation enables modality-selective integration of sensory input and vigilance state

Recent years have seen compelling demonstrations of the importance of behavioral state on sensory processing and attention. Arousal plays a dominant role in controlling brain-wide neural activity patterns, particularly through modulation by norepinephrine. Noradrenergic brainstem nuclei, including locus coeruleus, can be activated by stimuli of multiple sensory modalities and broadcast modulatory signals via axonal projections throughout the brain. This organization might suggest proportional brain-wide norepinephrine release during states of heightened vigilance. Here, however, we have found that low-intensity, nonarousing visual stimuli enhanced vigilance-dependent noradrenergic signaling locally in visual cortex, revealed using dual-site fiber photometry to monitor noradrenergic Ca²⁺ responses of astroglia simultaneously in cerebellum and visual cortex and two-photon microscopy to monitor noradrenergic axonal terminal Ca²⁺ dynamics. Nitric oxide, following N-methyl-d-aspartate receptor activation in neuronal nitric oxide synthase-positive interneurons, mediated transient acceleration of norepinephrine-dependent astroglia Ca²⁺ activation. These findings reveal a candidate cortical microcircuit for sensory modality-selective modulation of attention.

Local activation of α2 adrenergic receptors is required for vagus nerve stimulation induced motor cortical plasticity

Vagus nerve stimulation (VNS) paired with rehabilitation training is emerging as a potential treatment for improving recovery of motor function following stroke. In rats, VNS paired with skilled forelimb training results in significant reorganization of the somatotopic cortical motor map; however, the mechanisms underlying this form of VNS-dependent plasticity remain unclear. Recent studies have shown that VNS-driven cortical plasticity is dependent on noradrenergic innervation of the neocortex. In the central nervous system, noradrenergic α2 receptors (α2-ARs) are widely expressed in the motor cortex and have been critically implicated in synaptic communication and plasticity. In current study, we examined whether activation of cortical α2-ARs is necessary for VNS-driven motor cortical reorganization to occur. Consistent with previous studies, we found that VNS paired with motor training enlarges the map representation of task-relevant musculature in the motor cortex. Infusion of α2-AR antagonists into M1 blocked VNS-driven motor map reorganization from occurring. Our results suggest that local α2-AR activation is required for VNS-induced cortical reorganization to occur, providing insight into the mechanisms that may underlie the neuroplastic effects of VNS therapy.

Noradrenaline in the aging brain: Promoting cognitive reserve or accelerating Alzheimer's disease?

Many believe that engaging in novel and mentally challenging activities promotes brain health and prevents Alzheimer's disease in later life. However, mental stimulation may also have risks as well as benefits. As neurons release neurotransmitters, they often also release amyloid peptides and tau proteins into the extracellular space. These by-products of neural activity can aggregate into the tau tangle and amyloid plaque signatures of Alzheimer's disease. Over time, more active brain regions accumulate more pathology. Thus, increasing brain activity can have a cost. But the neuromodulator noradrenaline, released during novel and mentally stimulating events, may have some protective effects-as well as some negative effects. Via its inhibitory and excitatory effects on neurons and microglia, noradrenaline sometimes prevents and sometimes accelerates the production and accumulation of amyloid-β and tau in various brain regions. Both α2A- and β-adrenergic receptors influence amyloid-β production and tau hyperphosphorylation. Adrenergic activity also influences clearance of amyloid-β and tau. Furthermore, some findings suggest that Alzheimer's disease increases noradrenergic activity, at least in its early phases. Because older brains clear the by-products of synaptic activity less effectively, increased synaptic activity in the older brain risks accelerating the accumulation of Alzheimer's pathology more than it does in the younger brain.

High intensity VNS disrupts VNS-mediated plasticity in motor cortex

Vagus nerve stimulation (VNS) paired with motor rehabilitation enhances recovery of function after neurological injury in rats and humans. This effect is ascribed to VNS-dependent facilitation of plasticity in motor networks. Previous studies document an inverted-U relationship between VNS intensity and cortical plasticity, such that moderate intensities increase plasticity, while low or high intensity VNS does not. We tested the interaction of moderate and high intensity VNS trains to probe the mechanisms that may underlie VNS-dependent plasticity. Rats performed a behavioral task where VNS was paired with jaw movement during chewing. For five days, subjects received 100 pairings of moderate intensity VNS (Standard VNS), 100 pairings alternating between moderate and high intensity VNS (Interleaved VNS), or 50 pairings of moderate intensity VNS (Short VNS) approximately every 8 s. After the final behavioral session, intracortical microstimulation (ICMS) was used to evaluate movement representations in motor cortex. 100 pairings of moderate intensity VNS enhanced motor cortex plasticity. Replacing half of moderate intensity stimulation with high intensity VNS blocked this enhancement of plasticity. Removing high intensity stimulation, leaving only 50 pairings of moderate intensity VNS, reinstated plasticity. These results demonstrate that there is a period for at least 8 s after high intensity stimulation in which moderate intensity VNS is not able to engage mechanisms required for synaptic reorganization. More importantly, this study demonstrates that changes in stimulation parameters are a critical determinant of the magnitude of plasticity and likely the efficacy of VNS-enhanced recovery.

Targeting the Autonomic Nervous System for Risk Stratification, Outcome Prediction and Neuromodulation in Ischemic Stroke

Ischemic stroke is a worldwide major cause of mortality and disability and has high costs in terms of health-related quality of life and expectancy as well as of social healthcare resources. In recent years, starting from the bidirectional relationship between autonomic nervous system (ANS) dysfunction and acute ischemic stroke (AIS), researchers have identified prognostic factors for risk stratification, prognosis of mid-term outcomes and response to recanalization therapy. In particular, the evaluation of the ANS function through the analysis of heart rate variability (HRV) appears to be a promising non-invasive and reliable tool for the management of patients with AIS. Furthermore, preclinical molecular studies on the pathophysiological mechanisms underlying the onset and progression of stroke damage have shown an extensive overlap with the activity of the vagus nerve. Evidence from the application of vagus nerve stimulation (VNS) on animal models of AIS and on patients with chronic ischemic stroke has highlighted the surprising therapeutic possibilities of neuromodulation. Preclinical molecular studies highlighted that the neuroprotective action of VNS results from anti-inflammatory, antioxidant and antiapoptotic mechanisms mediated by α7 nicotinic acetylcholine receptor. Given the proven safety of non-invasive VNS in the subacute phase, the ease of its use and its possible beneficial effect in hemorrhagic stroke as well, human studies with transcutaneous VNS should be less challenging than protocols that involve invasive VNS and could be the proof of concept that neuromodulation represents the very first therapeutic approach in the ultra-early management of stroke.

Ocular dominance plasticity: Molecular mechanisms revisited

Ocular dominance plasticity (ODP) is a type of cortical plasticity operating in visual cortex of mammals that are endowed with binocular vision based on the competition-driven disparity. Earlier, a molecular mechanism was proposed that catecholamines play an important role in the maintenance of ODP in kittens. Having survived the initial test, the hypothesis was further advanced to identify noradrenaline (NA) as a key factor that regulates ODP in the immature cortex. Later, the ODP-promoting effect of NA is extended to the adult with age-related limitations. Following the enhanced NA availability, the chain events downstream lead to the β-adrenoreceptor-induced cAMP accumulation, which in turn activates the protein kinase A. Eventually, the protein kinase translocates to the cell nucleus to activate cAMP responsive element binding protein (CREB). CREB is a cellular transcription factor that controls the transcription of various genes, underpinning neuronal plasticity and long-term memory. In the advent of molecular genetics in that various types of new tools have become available with relative ease, ODP research has lightly adopted in the rodent model the original concepts and methodologies. Here, after briefly tracing the strategic maturation of our quest, the review moves to the later development of the field, with the emphasis placed around the following issues: (a) Are we testing ODP per se? (b) What does monocular deprivation deprive of the immature cortex? (c) The critical importance of binocular competition, (d) What is the adult plasticity? (e) Excitation-Inhibition balance in local circuits, and (f) Species differences in the animal models.

Citalopram reduces glutamatergic synaptic transmission in the auditory cortex via activation of 5-HT1A receptors

Serotonin modulates cognitive processes and is related to various psychiatric disorders, including major depression. Administration of citalopram reduces the amplitude of auditory evoked potentials in depressed people and animal models, suggesting that 5-HT has an inhibitory role. Here, we characterize the modulation of excitatory post-synaptic currents by application of either 5-HT or agonists of 5-HT1A and 5-HT2 receptors, or by endogenous 5-HT evoked by citalopram on pyramidal neurons from layer II/III of rat auditory cortex. We found that application of 5-HT concentration-dependently reduces excitatory post-synaptic currents amplitude without changing the paired-pulse ratio, suggesting a post-synaptic modulation. We observed that selective agonists of 5-HT1A and 5-HT2 receptors [8-OH-DPAT (10 µM) and DOI (10 µM), respectively] mimic the effect of 5-HT on the excitatory post-synaptic currents. Effect of 5-HT was entirely blocked by co-application of the antagonists NAN-190 (1 µM) and ritanserin (200 nM). Similarly, citalopram application (1 μM) reduced the amplitude of the evoked excitatory post-synaptic currents. Reduction in the magnitude of the excitatory post-synaptic currents by endogenous 5-HT was interpolated in the dose-response curve elicited by exogenous 5-HT, yielding that citalopram raised the extracellular 5-HT concentration to 823 nM. Effect of citalopram was blocked by the previous application of NAN-190 but not ritanserin, indicating that citalopram reduces glutamatergic synaptic transmission via 5-HT1A receptors in layer II/III of the auditory cortex. These results suggest that the local activity of 5-HT contributes to decrease in the basal excitability of the auditory cortex for enhancing the detection of external relevant acoustic signals.

Optimizing Dosing of Vagus Nerve Stimulation for Stroke Recovery

Vagus nerve stimulation (VNS) paired with rehabilitative training enhances recovery of function in models of stroke and is currently under investigation for use in chronic stroke patients. Dosing is critical in translation of pharmacological therapies, but electrical stimulation therapies often fail to comprehensively explore dosing parameters in preclinical studies. Varying VNS parameters has non-monotonic effects on plasticity in the central nervous system, which may directly impact efficacy for stroke. We sought to optimize stimulation intensity to maximize recovery of motor function in a model of ischemic stroke. The study design was preregistered prior to beginning data collection (DOI: https://doi.org/10.17605/OSF.IO/BMJEK ). After training on an automated assessment of forelimb function and receiving an ischemic lesion in motor cortex, rats were separated into groups that received rehabilitative training paired with VNS at distinct stimulation intensities (sham, 0.4 mA, 0.8 mA, or 1.6 mA). Moderate-intensity VNS at 0.8 mA enhanced recovery of function compared with all other groups. Neither 0.4 mA nor 1.6 mA VNS was sufficient to improve functional recovery compared with equivalent rehabilitation without VNS. These results demonstrate that moderate-intensity VNS delivered during rehabilitation improves recovery and defines an optimized intensity paradigm for clinical implementation of VNS therapy.

A limited range of vagus nerve stimulation intensities produce motor cortex reorganization when delivered during training

Pairing vagus nerve stimulation (VNS) with rehabilitation has emerged as a potential strategy to improve recovery after neurological injury, an effect ascribed to VNS-dependent enhancement of synaptic plasticity. Previous studies demonstrate that pairing VNS with forelimb training increases forelimb movement representations in motor cortex. However, it is not known whether VNS-dependent enhancement of plasticity is restricted to forelimb training or whether VNS paired with other movements could induce plasticity of other motor representations. We tested the hypothesis that VNS paired with orofacial movements associated with chewing during an unskilled task would drive a specific increase in jaw representation in motor cortex compared to equivalent behavioral experience without VNS. Rats performed a behavioral task in which VNS at a specified intensity between 0 and 1.2 mA was paired with chewing 200 times per day for five days. Intracortical microstimulation (ICMS) was then used to document movement representations in motor cortex. VNS paired with chewing at 0.8 mA significantly increased motor cortex jaw representation compared to equivalent behavioral training without stimulation (Bonferroni-corrected unpaired t-test, p < 0.01). Higher and lower intensities failed to alter cortical plasticity. No changes in other movement representations or total motor cortex area were observed between groups. These results demonstrate that 0.8 mA VNS paired with training drives robust plasticity specific to the paired movement, is not restricted to forelimb representations, and occurs with training on an unskilled task. This suggests that moderate intensity VNS may be a useful adjuvant to enhance plasticity and support benefits of rehabilitative therapies targeting functions beyond upper limb movement.

Efficient parameters of vagus nerve stimulation to enhance extinction learning in an extinction-resistant rat model of PTSD

Vagus nerve stimulation (VNS) has shown promise as an adjuvant treatment for posttraumatic stress disorder (PTSD), as it enhances fear extinction and reduces anxiety symptoms in multiple rat models of this condition. Yet, identification of the optimal stimulation paradigm is needed to facilitate clinical translation of this potential therapy. Using an extinction-resistant rat model of PTSD, we tested whether varying VNS intensity and duration could maximize extinction learning while minimizing the total amount of stimulation. We confirmed that sham rats failed to extinguish after a week of extinction training. Delivery of the standard LONG VNS trains (30 s) at 0.4 mA enhanced extinction and reduced anxiety but did not prevent fear return. Increasing the intensity of LONG VNS trains to 0.8 mA prevented fear return and attenuated anxiety symptoms. Interestingly, delivering 1, 4 or 16 SHORT VNS bursts (0.5 s) at 0.8 mA during each cue presentation in extinction training also enhanced extinction. LONG VNS trains or multiple SHORT VNS bursts at 0.8 mA attenuated fear renewal and reinstatement, promoted extinction generalization and reduced generalized anxiety. Delivering 16 SHORT VNS bursts also facilitated extinction in fewer trials. This study provides the first evidence that brief bursts of VNS can enhance extinction training, reduce relapse and support symptom remission using much less VNS than previous protocols. These findings suggest that VNS parameters can be adjusted in order to minimize total charge delivery and maximize therapeutic effectiveness.

Bayesian Filtering with Multiple Internal Models: Toward a Theory of Social Intelligence

To exhibit social intelligence, animals have to recognize whom they are communicating with. One way to make this inference is to select among internal generative models of each conspecific who may be encountered. However, these models also have to be learned via some form of Bayesian belief updating. This induces an interesting problem: When receiving sensory input generated by a particular conspecific, how does an animal know which internal model to update? We consider a theoretical and neurobiologically plausible solution that enables inference and learning of the processes that generate sensory inputs (e.g., listening and understanding) and reproduction of those inputs (e.g., talking or singing), under multiple generative models. This is based on recent advances in theoretical neurobiology-namely, active inference and post hoc (online) Bayesian model selection. In brief, this scheme fits sensory inputs under each generative model. Model parameters are then updated in proportion to the probability that each model could have generated the input (i.e., model evidence). The proposed scheme is demonstrated using a series of (real zebra finch) birdsongs, where each song is generated by several different birds. The scheme is implemented using physiologically plausible models of birdsong production. We show that generalized Bayesian filtering, combined with model selection, leads to successful learning across generative models, each possessing different parameters. These results highlight the utility of having multiple internal models when making inferences in social environments with multiple sources of sensory information.

Rewards interact with repetition-dependent learning to enhance long-term retention of motor memories

The combination of behavioral experiences that enhance long-term retention remains largely unknown. Informed by neurophysiological lines of work, this study tested the hypothesis that performance-contingent monetary rewards potentiate repetition-dependent forms of learning, as induced by extensive practice at asymptote, to enhance long-term retention of motor memories. To this end, six groups of 14 participants (n = 84) acquired novel motor behaviors by adapting to a gradual visuomotor rotation while these factors were manipulated. Retention was assessed 24 h later. While all groups similarly acquired the novel motor behaviors, results from the retention session revealed an interaction indicating that rewards enhanced long-term retention, but only when practice was extended to asymptote. Specifically, the interaction indicated that this effect selectively occurred when rewards were intermittently available (i.e., 50%), but not when they were absent (i.e., 0%) or continuously available (i.e., 100%) during acquisition. This suggests that the influence of rewards on extensive practice and long-term retention is nonlinear, as continuous rewards did not further enhance retention as compared with intermittent rewards. One possibility is that rewards' intermittent availability allows to maintain their subjective value during acquisition, which may be key to potentiate long-term retention.

Norepinephrine and serotonin are required for vagus nerve stimulation directed cortical plasticity

Vagus nerve stimulation (VNS) paired with forelimb training drives robust, specific reorganization of movement representations in the motor cortex. This effect is hypothesized to be mediated by VNS-dependent engagement of neuromodulatory networks. VNS influences activity in the locus coeruleus (LC) and dorsal raphe nucleus (DRN), but the involvement of these neuromodulatory networks in VNS-directed plasticity is unknown. We tested the hypothesis that cortical norepinephrine and serotonin are required for VNS-dependent enhancement of motor cortex plasticity. Rats were trained on a lever pressing task emphasizing proximal forelimb use. Once proficient, all rats received a surgically implanted vagus nerve cuff and cortical injections of either immunotoxins to deplete serotonin or norepinephrine, or vehicle control. Following surgical recovery, rats received half second bursts of 0.8 mA or sham VNS after successful trials. After five days of pairing intracortical microstimulation (ICMS) was performed in the motor cortex contralateral to the trained limb. VNS paired with training more than doubled cortical representations of proximal forelimb movements. Depletion of either cortical norepinephrine or serotonin prevented this effect. The requirement of multiple neuromodulators is consistent with earlier studies showing that these neuromodulators regulate synaptic plasticity in a complimentary fashion.

Multi-context blind source separation by error-gated Hebbian rule

Animals need to adjust their inferences according to the context they are in. This is required for the multi-context blind source separation (BSS) task, where an agent needs to infer hidden sources from their context-dependent mixtures. The agent is expected to invert this mixing process for all contexts. Here, we show that a neural network that implements the error-gated Hebbian rule (EGHR) with sufficiently redundant sensory inputs can successfully learn this task. After training, the network can perform the multi-context BSS without further updating synapses, by retaining memories of all experienced contexts. This demonstrates an attractive use of the EGHR for dimensionality reduction by extracting low-dimensional sources across contexts. Finally, if there is a common feature shared across contexts, the EGHR can extract it and generalize the task to even inexperienced contexts. The results highlight the utility of the EGHR as a model for perceptual adaptation in animals.

Adrenergic Modulation of Visually-Guided Behavior

Iontophoretic application of norepinephrine (NE) into the primary visual cortex (V1) in vivo reduces spontaneous and evoked activity, without changing the functional selectivity of cortical units. One possible consequence of this phenomenon is that adrenergic receptors (ARs) regulate the signal-to-noise ratio (SNR) of neural responses in this circuit. However, despite such strong inhibitory action of NE on neuronal firing patterns in V1, its specific action on visual behavior has not been studied. Furthermore, the majority of observations regarding cortical NE from in vivo recordings have been performed in anesthetized animals and have not been tested behaviorally. Here, we describe how micro-infusion of AR agonists/antagonists into mouse V1 influences visually-guided behavior at different contrasts and spatial frequencies. We found that cortical activation of α₁- and β-AR produced a substantial reduction in visual discrimination performance at high contrasts and low spatial frequencies, consistent with a divisive effect. This reduction was reversible and was accompanied by a rise in escape latencies as well as an increase in the group averaged choice variance as a function of stimulus contrast. We conclude that pharmacological activation of cortical AR regulates visual perception and adaptive behavior through a divisive gain control of visual responses.

Targeted Vagus Nerve Stimulation for Rehabilitation After Stroke

Stroke is a leading cause of disability worldwide, and in approximately 60% of individuals, upper limb deficits persist 6 months after stroke. These deficits adversely affect the functional use of the upper limb and restrict participation in day to day activities. An important goal of stroke rehabilitation is to improve the quality of life by enhancing functional independence and participation in activities. Since upper limb deficits are one of the best predictors of quality of life after stroke, effective interventions targeting these deficits may represent a means to improve quality of life. An increased understanding of the neurobiological processes underlying stroke recovery has led to the development of targeted approaches to improve motor deficits. One such targeted strategy uses brief bursts of Vagus Nerve Stimulation (VNS) paired with rehabilitation to enhance plasticity and support recovery of upper limb function after chronic stroke. Stimulation of the vagus nerve triggers release of plasticity promoting neuromodulators, such as acetylcholine and norepinephrine, throughout the cortex. Timed engagement of neuromodulators concurrent with motor training drives task-specific plasticity in the motor cortex to improve function and provides the basis for paired VNS therapy. A number of studies in preclinical models of ischemic stroke demonstrated that VNS paired with rehabilitative training significantly improved the recovery of forelimb motor function compared to rehabilitative training without VNS. The improvements were associated with synaptic reorganization of cortical motor networks and recruitment of residual motor neurons controlling the impaired forelimb, demonstrating the putative neurobiological mechanisms underlying recovery of motor function. These preclinical studies provided the basis for conducting two multi-site, randomized controlled pilot trials in individuals with moderate to severe upper limb weakness after chronic ischemic stroke. In both studies, VNS paired with rehabilitation improved motor deficits compared to rehabilitation alone. The trials provided support for a 120-patient pivotal study designed to evaluate the efficacy of paired VNS therapy in individuals with chronic ischemic stroke. This manuscript will discuss the neurobiological rationale for VNS therapy, provide an in-depth discussion of both animal and human studies of VNS therapy for stroke, and outline the challenges and opportunities for the future use of VNS therapy.

Vagus Nerve Stimulation Rate and Duration Determine whether Sensory Pairing Produces Neural Plasticity

Repeatedly pairing a brief train of vagus nerve stimulation (VNS) with an auditory stimulus drives reorganization of primary auditory cortex (A1), and the magnitude of this VNS-dependent plasticity is dependent on the stimulation parameters, including intensity and pulse rate. However, there is currently little data to guide the selection of VNS train durations, an easily adjusted parameter that could influence the effect of VNS-based therapies. Here, we tested the effect of varying the duration of the VNS train on the extent of VNS-dependent cortical plasticity. Rats were exposed to a 9 kHz tone 300 times per day for 20 days. Coincident with tone presentation, groups received trains of 4, 16, or 64 pulses of VNS delivered at 30 Hz, corresponding to train durations of 0.125 s, 0.5 s, and 2.0 s, respectively. High-density microelectrode mapping of A1 revealed that 0.5 s duration VNS trains significantly increased the number of neurons in A1 that responded to tones near the paired tone frequency. Trains lasting 0.125 or 2.0 s failed to alter A1 responses, indicating that both shorter and longer stimulation durations are less effective at enhancing plasticity. A second set of experiments evaluating the effect of delivering 4 or 64 pulses in a fixed 0.5 s VNS train duration paired with tone presentation reveal that both slower and faster stimulation rates are less effective at enhancing plasticity. We incorporated these results with previous findings describing the effect of stimulation parameters on VNS-dependent plasticity and activation of neuromodulatory networks to generate a model of synaptic activation by VNS.

Emotional arousal amplifies competitions across goal-relevant representation: A neurocomputational framework

Emotional arousal often facilitates memory for some aspects of an event while impairing memory for other aspects of the same event. Across three experiments, we found that emotional arousal amplifies competition among goal-relevant representations, such that arousal impairs memory for multiple goal-relevant representations while enhancing memory for solo goal-relevant information. We also present a computational model to explain the mechanisms by which emotional arousal can modulate memory in opposite ways via the local/synaptic-level noradrenergic system. The model is based on neurophysiological observations that norepinephrine (NE) released under emotional arousal is locally controlled by glutamate levels, resulting in different NE effects across regions, gating either long-term potentiation or long-term depression by activating different adrenergic receptors depending on NE concentration levels. This model successfully replicated behavioral findings from the three experiments. These findings suggest that the NE's local effects are key in determining the effects of emotion on memory.

From membrane receptors to protein synthesis and actin cytoskeleton: Mechanisms underlying long lasting forms of synaptic plasticity

Synaptic plasticity, the activity dependent change in synaptic strength, forms the molecular foundation of learning and memory. Synaptic plasticity includes structural changes, with spines changing their size to accomodate insertion and removal of postynaptic receptors, which are correlated with functional changes. Of particular relevance for memory storage are the long lasting forms of synaptic plasticity which are protein synthesis dependent. Due to the importance of spine structural plasticity and protein synthesis, this review focuses on the signaling pathways that connect synaptic stimulation with regulation of protein synthesis and remodeling of the actin cytoskeleton. We also review computational models that implement novel aspects of molecular signaling in synaptic plasticity, such as the role of neuromodulators and spatial microdomains, as well as highlight the need for computational models that connect activation of memory kinases with spine actin dynamics.

Locus Coeruleus Phasic, But Not Tonic, Activation Initiates Global Remapping in a Familiar Environment

Locus coeruleus (LC) neurons, the source of hippocampal norepinephrine (NE), are activated by novelty and changes in environmental contingencies. Based on the role of monoamines in reconfiguring invertebrate networks, and data from mammalian systems, a network reset hypothesis for the effects of LC activation has been proposed. We used the cellular compartmental analysis of temporal FISH technique based on the cellular distribution of immediate early genes to examine the effect of LC activation and inactivation, on regional hippocampal maps in male rats, when LC activity was manipulated just before placement in a second familiar (A/A) and/or novel environment (A/B). We found that bilateral phasic, but not tonic, activation of LC reset hippocampal maps in the A/A condition, whereas silencing the LC with clonidine before placement in the A/B condition blocked map reset and a familiar map emerged in the dentate gyrus, proximal and distal CA1, and CA3c. However, CA3a and CA3b encoded the novel environment. These results support a role for phasic LC responses in generating novel hippocampal sequences during memory encoding and, potentially, memory updating. The silencing experiments suggest that novel environments may not be recognized as different by dentate gyrus and CA1 without LC input. The functional distinction between phasic and tonic LC activity argues that these parameters are critical for determining network changes. These data are consistent with the hippocampus activating internal network representations to encode novel experiential episodes and suggest LC input is critical for this role.SIGNIFICANCE STATEMENT Burst activation of the broadly projecting novelty signaling system of the locus coeruleus initiates new network representations throughout the hippocampus despite unchanged external environments. Tonic activation does not alter network representations in the same condition. This suggests differences in the temporal parameters of neuromodulator network activation are critical for neuromodulator function. Silencing this novelty signaling system prevented the appearance of new network representations in a novel environment. Instead, familiar representations were expressed in a subset of hippocampal areas, with another subset encoding the novel environment. This "being in two places at once" argues for independent functional regions within the hippocampus. These experiments strengthen the view that internal states are major determinants of the brain's construction of environmental representations.

Vagus nerve stimulation intensity influences motor cortex plasticity

BACKGROUND

Vagus nerve stimulation (VNS) paired with forelimb motor training enhances reorganization of movement representations in the motor cortex. Previous studies have shown an inverted-U relationship between VNS intensity and plasticity in other brain areas, such that moderate intensity VNS yields greater cortical plasticity than low or high intensity VNS. However, the relationship between VNS intensity and plasticity in the motor cortex is unknown.

OBJECTIVE

In this study we sought to test the hypothesis that VNS intensity exhibits an inverted-U relationship with the degree of motor cortex plasticity in rats.

METHODS

Rats were taught to perform a lever pressing task emphasizing use of the proximal forelimb musculature. Once proficient, rats underwent five additional days of behavioral training in which low intensity VNS (0.4 mA), moderate intensity VNS (0.8 mA), high intensity VNS (1.6 mA), or sham stimulation was paired with forelimb movement. 24 h after the completion of behavioral training, intracortical microstimulation (ICMS) was used to document movement representations in the motor cortex.

RESULTS

VNS delivered at 0.8 mA caused a significant increase in motor cortex proximal forelimb representation compared to training alone. VNS delivered at 0.4 mA and 1.6 mA failed to cause a significant expansion of proximal forelimb representation.

CONCLUSION

Moderate intensity 0.8 mA VNS optimally enhances motor cortex plasticity while low intensity 0.4 mA and high intensity 1.6 mA VNS fail to enhance plasticity. Plasticity in the motor cortex exhibits an inverted-U function of VNS intensity similar to previous findings in auditory cortex.

Modulation of Spike-Timing Dependent Plasticity: Towards the Inclusion of a Third Factor in Computational Models

In spike-timing dependent plasticity (STDP) change in synaptic strength depends on the timing of pre- vs. postsynaptic spiking activity. Since STDP is in compliance with Hebb's postulate, it is considered one of the major mechanisms of memory storage and recall. STDP comprises a system of two coincidence detectors with N-methyl-D-aspartate receptor (NMDAR) activation often posited as one of the main components. Numerous studies have unveiled a third component of this coincidence detection system, namely neuromodulation and glia activity shaping STDP. Even though dopaminergic control of STDP has most often been reported, acetylcholine, noradrenaline, nitric oxide (NO), brain-derived neurotrophic factor (BDNF) or gamma-aminobutyric acid (GABA) also has been shown to effectively modulate STDP. Furthermore, it has been demonstrated that astrocytes, via the release or uptake of glutamate, gate STDP expression. At the most fundamental level, the timing properties of STDP are expected to depend on the spatiotemporal dynamics of the underlying signaling pathways. However in most cases, due to technical limitations experiments grant only indirect access to these pathways. Computational models carefully constrained by experiments, allow for a better qualitative understanding of the molecular basis of STDP and its regulation by neuromodulators. Recently, computational models of calcium dynamics and signaling pathway molecules have started to explore STDP emergence in ex and in vivo-like conditions. These models are expected to reproduce better at least part of the complex modulation of STDP as an emergent property of the underlying molecular pathways. Elucidation of the mechanisms underlying STDP modulation and its consequences on network dynamics is of critical importance and will allow better understanding of the major mechanisms of memory storage and recall both in health and disease.

Arousal increases neural gain via the locus coeruleus-norepinephrine system in younger adults but not in older adults

In younger adults, arousal amplifies attentional focus to the most salient or goal-relevant information while suppressing other information. A computational model of how the locus coeruleus-norepinephrine (LC-NE) system can implement this increased selectivity under arousal and an fMRI study comparing how arousal affects younger and older adults' processing indicate that the amplification of salient stimuli and the suppression of non-salient stimuli are separate processes, with aging affecting suppression without impacting amplification under arousal. In the fMRI study, arousal increased processing of salient stimuli and decreased processing of non-salient stimuli for younger adults. In contrast, for older adults, arousal increased processing of both low and high salience stimuli, generally increasing excitatory responses to visual stimuli. Older adults also showed decline in LC functional connectivity with frontoparietal networks that coordinate attentional selectivity. Thus, among older adults, arousal increases the potential for distraction from non-salient stimuli.

Error-Gated Hebbian Rule: A Local Learning Rule for Principal and Independent Component Analysis

We developed a biologically plausible unsupervised learning algorithm, error-gated Hebbian rule (EGHR)-β, that performs principal component analysis (PCA) and independent component analysis (ICA) in a single-layer feedforward neural network. If parameter β = 1, it can extract the subspace that major principal components span similarly to Oja’s subspace rule for PCA. If β = 0, it can separate independent sources similarly to Bell-Sejnowski’s ICA rule but without requiring the same number of input and output neurons. Unlike these engineering rules, the EGHR-β can be easily implemented in a biological or neuromorphic circuit because it only uses local information available at each synapse. We analytically and numerically demonstrate the reliability of the EGHR-β in extracting and separating major sources given high-dimensional input. By adjusting β, the EGHR-β can extract sources that are missed by the conventional engineering approach that first applies PCA and then ICA. Namely, the proposed rule can successfully extract hidden natural images even in the presence of dominant or non-Gaussian noise components. The results highlight the reliability and utility of the EGHR-β for large-scale parallel computation of PCA and ICA and its future implementation in a neuromorphic hardware.

Monoaminergic Modulation of Motor Cortex Function

Elaboration of appropriate responses to behavioral situations rests on the ability of selecting appropriate motor outcomes in accordance to specific environmental inputs. To this end, the primary motor cortex (M1) is a key structure for the control of voluntary movements and motor skills learning. Subcortical loops regulate the activity of the motor cortex and thus contribute to the selection of appropriate motor plans. Monoamines are key mediators of arousal, attention and motivation. Their firing pattern enables a direct encoding of different states thus promoting or repressing the selection of actions adapted to the behavioral context. Monoaminergic modulation of motor systems has been extensively studied in subcortical circuits. Despite evidence of converging projections of multiple neurotransmitters systems in the motor cortex pointing to a direct modulation of local circuits, their contribution to the execution and learning of motor skills is still poorly understood. Monoaminergic dysregulation leads to impaired plasticity and motor function in several neurological and psychiatric conditions, thus it is critical to better understand how monoamines modulate neural activity in the motor cortex. This review aims to provide an update of our current understanding on the monoaminergic modulation of the motor cortex with an emphasis on motor skill learning and execution under physiological conditions.

Learning with three factors: modulating Hebbian plasticity with errors

Synaptic plasticity is a central theme in neuroscience. A framework of three-factor learning rules provides a powerful abstraction, helping to navigate through the abundance of models of synaptic plasticity. It is well-known that the dopamine modulation of learning is related to reward, but theoretical models predict other functional roles of the modulatory third factor; it may encode errors for supervised learning, summary statistics of the population activity for unsupervised learning or attentional feedback. Specialized structures may be needed in order to generate and propagate third factors in the neural network.

CREB decreases astrocytic excitability by modifying subcellular calcium fluxes via the sigma-1 receptor

Astrocytic excitability relies on cytosolic calcium increases as a key mechanism, whereby astrocytes contribute to synaptic transmission and hence learning and memory. While it is a cornerstone of neurosciences that experiences are remembered, because transmitters activate gene expression in neurons, long-term adaptive astrocyte plasticity has not been described. Here, we investigated whether the transcription factor CREB mediates adaptive plasticity-like phenomena in astrocytes. We found that activation of CREB-dependent transcription reduced the calcium responses induced by ATP, noradrenaline, or endothelin-1. As to the mechanism, expression of VP16-CREB, a constitutively active CREB mutant, had no effect on basal cytosolic calcium levels, extracellular calcium entry, or calcium mobilization from lysosomal-related acidic stores. Rather, VP16-CREB upregulated sigma-1 receptor expression thereby increasing the release of calcium from the endoplasmic reticulum and its uptake by mitochondria. Sigma-1 receptor was also upregulated in vivo upon VP16-CREB expression in astrocytes. We conclude that CREB decreases astrocyte responsiveness by increasing calcium signalling at the endoplasmic reticulum-mitochondria interface, which might be an astrocyte-based form of long-term depression.

Noradrenergic mechanisms of arousal's bidirectional effects on episodic memory

Arousal's selective effects on cognition go beyond the simple enhancement of emotional stimuli, sometimes enhancing and other times impairing processing of proximal neutral information. Past work shows that arousal impairs encoding of subsequent neutral stimuli regardless of their top-down priority via the engagement of β-adrenoreceptors. In contrast, retrograde amnesia induced by emotional arousal can flip to enhancement when preceding neutral items are prioritized in top-down attention. Whether β-adrenoreceptors also contribute to this retrograde memory enhancement of goal-relevant neutral stimuli is unclear. In this pharmacological study, we administered 40mg of propranolol or 40mg of placebo to healthy young adults to examine whether emotional arousal's bidirectional effects on declarative memory relies on β-adrenoreceptor activation. Following pill intake, participants completed an emotional oddball task in which they were asked to prioritize a neutral object appearing just before an emotional or neutral oddball image within a sequence of 7 neutral objects. Under placebo, emotional oddballs impaired memory for lower priority oddball+1 objects but had no effect on memory for high priority oddball-1 objects. Propranolol blocked this anterograde amnesic effect of arousal. Emotional oddballs also enhanced selective memory trade-offs significantly more in the placebo than drug condition, such that high priority oddball-1 objects were more likely to be remembered at the cost of their corresponding lower priority oddball+1 objects under arousal. Lastly, those who recalled more high priority oddball-1 objects preceding an emotional versus neutral oddball image showed greater increases in salivary alpha-amylase, a biomarker of noradrenergic system activation, across the task. Together these findings suggest that different noradrenergic mechanisms contribute to the anterograde and retrograde mnemonic effects of arousal on proximal neutral memoranda.

The effects of arousal on apical amplification and conscious state

Neocortical pyramidal cells can integrate two classes of input separately and use one to modulate response to the other. Their tuft dendrites are electrotonically separated from basal dendrites and soma by the apical dendrite, and apical hyperpolarization-activated currents (Ih) further isolate subthreshold integration of tuft inputs. When apical depolarization exceeds a threshold, however, it can enhance response to the basal inputs that specify the cell's selective sensitivity. This process is referred to as apical amplification (AA). We review evidence suggesting that, by regulating Ih in the apical compartments, adrenergic arousal controls the coupling between apical and somatic integration zones thus modifying cognitive capabilities closely associated with consciousness. Evidence relating AA to schizophrenia, sleep, and anesthesia is reviewed, and we assess theories that emphasize the relevance of AA to consciousness. Implications for theories of neocortical computation that emphasize context-sensitive modulation are summarized. We conclude that the findings concerning AA and its regulation by arousal offer a new perspective on states of consciousness, the function and evolution of neocortex, and psychopathology. Many issues worthy of closer examination arise.

Locus Ceruleus Norepinephrine Release: A Central Regulator of CNS Spatio-Temporal Activation?

Norepinephrine (NE) is synthesized in the Locus Coeruleus (LC) of the brainstem, from where it is released by axonal varicosities throughout the brain via volume transmission. A wealth of data from clinics and from animal models indicates that this catecholamine coordinates the activity of the central nervous system (CNS) and of the whole organism by modulating cell function in a vast number of brain areas in a coordinated manner. The ubiquity of NE receptors, the daunting number of cerebral areas regulated by the catecholamine, as well as the variety of cellular effects and of their timescales have contributed so far to defeat the attempts to integrate central adrenergic function into a unitary and coherent framework. Since three main families of NE receptors are represented-in order of decreasing affinity for the catecholamine-by: α2 adrenoceptors (α2Rs, high affinity), α1 adrenoceptors (α1Rs, intermediate affinity), and β adrenoceptors (βRs, low affinity), on a pharmacological basis, and on the ground of recent studies on cellular and systemic central noradrenergic effects, we propose that an increase in LC tonic activity promotes the emergence of four global states covering the whole spectrum of brain activation: (1) sleep: virtual absence of NE, (2) quiet wake: activation of α2Rs, (3) active wake/physiological stress: activation of α2- and α1-Rs, (4) distress: activation of α2-, α1-, and β-Rs. We postulate that excess intensity and/or duration of states (3) and (4) may lead to maladaptive plasticity, causing-in turn-a variety of neuropsychiatric illnesses including depression, schizophrenic psychoses, anxiety disorders, and attention deficit. The interplay between tonic and phasic LC activity identified in the LC in relationship with behavioral response is of critical importance in defining the short- and long-term biological mechanisms associated with the basic states postulated for the CNS. While the model has the potential to explain a large number of experimental and clinical findings, a major challenge will be to adapt this hypothesis to integrate the role of other neurotransmitters released during stress in a centralized fashion, like serotonin, acetylcholine, and histamine, as well as those released in a non-centralized fashion, like purines and cytokines.

Linking Neuromodulated Spike-Timing Dependent Plasticity with the Free-Energy Principle

The free-energy principle is a candidate unified theory for learning and memory in the brain that predicts that neurons, synapses, and neuromodulators work in a manner that minimizes free energy. However, electrophysiological data elucidating the neural and synaptic bases for this theory are lacking. Here, we propose a novel theory bridging the information-theoretical principle with the biological phenomenon of spike-timing dependent plasticity (STDP) regulated by neuromodulators, which we term mSTDP. We propose that by integrating an mSTDP equation, we can obtain a form of Friston's free energy (an information-theoretical function). Then we analytically and numerically show that dopamine (DA) and noradrenaline (NA) influence the accuracy of a principal component analysis (PCA) performed using the mSTDP algorithm. From the perspective of free-energy minimization, these neuromodulatory changes alter the relative weighting or precision of accuracy and prior terms, which induces a switch from pattern completion to separation. These results are consistent with electrophysiological findings and validate the free-energy principle and mSTDP. Moreover, our scheme can potentially be applied in computational psychiatry to build models of the faulty neural networks that underlie the positive symptoms of schizophrenia, which involve abnormal DA levels, as well as models of the NA contribution to memory triage and posttraumatic stress disorder.

A Local Learning Rule for Independent Component Analysis

Humans can separately recognize independent sources when they sense their superposition. This decomposition is mathematically formulated as independent component analysis (ICA). While a few biologically plausible learning rules, so-called local learning rules, have been proposed to achieve ICA, their performance varies depending on the parameters characterizing the mixed signals. Here, we propose a new learning rule that is both easy to implement and reliable. Both mathematical and numerical analyses confirm that the proposed rule outperforms other local learning rules over a wide range of parameters. Notably, unlike other rules, the proposed rule can separate independent sources without any preprocessing, even if the number of sources is unknown. The successful performance of the proposed rule is then demonstrated using natural images and movies. We discuss the implications of this finding for our understanding of neuronal information processing and its promising applications to neuromorphic engineering.

Inhibition Controls Asynchronous States of Neuronal Networks

Computations in cortical circuits require action potentials from excitatory and inhibitory neurons. In this mini-review, I first provide a quick overview of findings that indicate that GABAergic neurons play a fundamental role in coordinating spikes and generating synchronized network activity. Next, I argue that these observations helped popularize the notion that network oscillations require a high degree of spike correlations among interneurons which, in turn, produce synchronous inhibition of the local microcircuit. The aim of this text is to discuss some recent experimental and computational findings that support a complementary view: one in which interneurons participate actively in producing asynchronous states in cortical networks. This requires a proper mixture of shared excitation and inhibition leading to asynchronous activity between neighboring cells. Such contribution from interneurons would be extremely important because it would tend to reduce the spike correlation between neighboring pyramidal cells, a drop in redundancy that could enhance the information-processing capacity of neural networks.

Convergent evidence from alcohol-dependent humans and rats for a hyperdopaminergic state in protracted abstinence

A major hypothesis in addiction research is that alcohol induces neuroadaptations in the mesolimbic dopamine (DA) system and that these neuroadaptations represent a key neurochemical event in compulsive drug use and relapse. Whether these neuroadaptations lead to a hypo- or hyperdopaminergic state during abstinence is a long-standing, unresolved debate among addiction researchers. The answer is of critical importance for understanding the neurobiological mechanism of addictive behavior. Here we set out to study systematically the neuroadaptive changes in the DA system during the addiction cycle in alcohol-dependent patients and rats. In postmortem brain samples from human alcoholics we found a strong down-regulation of the D1 receptor- and DA transporter (DAT)-binding sites, but D2-like receptor binding was unaffected. To gain insight into the time course of these neuroadaptations, we compared the human data with that from alcohol-dependent rats at several time points during abstinence. We found a dynamic regulation of D1 and DAT during 3 wk of abstinence. After the third week the rat data mirrored our human data. This time point was characterized by elevated extracellular DA levels, lack of synaptic response to D1 stimulation, and augmented motor activity. Further functional evidence is given by a genetic rat model for hyperdopaminergia that resembles a phenocopy of alcohol-dependent rats during protracted abstinence. In summary, we provide a new dynamic model of abstinence-related changes in the striatal DA system; in this model a hyperdopaminergic state during protracted abstinence is associated with vulnerability for relapse.

Layer- and area-specific actions of norepinephrine on cortical synaptic transmission

The cerebral cortex is a critical target of the central noradrenergic system. The importance of norepinephrine (NE) in the regulation of cortical activity is underscored by clinical findings that involve this catecholamine and its receptor subtypes in the regulation of a large number of emotional and cognitive functions and illnesses. In this review, we highlight diverse effects of the LC/NE system in the mammalian cortex. Indeed, electrophysiological, pharmacological, and behavioral studies in the last few decades reveal that NE elicits a mixed repertoire of excitatory, inhibitory, and biphasic effects on the firing activity and transmitter release of cortical neurons. At the intrinsic cellular level, NE can produce a series of effects similar to those elicited by other monoamines or acetylcholine, associated with systemic arousal. At the synaptic level, NE induces numerous acute changes in synaptic function, and ׳gates' the induction of long-term plasticity of glutamatergic synapses, consisting in an enhancement of engaged and relevant cortical synapses and/or depression of unengaged synapses. Equally important in shaping cortical function, in many cortical areas NE promotes a characteristic, most often reversible, increase in the gain of local inhibitory synapses, whose extent and temporal properties vary between different areas and sometimes even between cortical layers of the same area. While we are still a long way from a comprehensive theory of the function of the LC/NE system, its cellular, synaptic, and plastic effects are consistent with the hypothesis that noradrenergic modulation is critical in coordinating the activity of cortical and subcortical circuits for the integration of sensory activity and working memory. This article is part of a Special Issue entitled SI: Noradrenergic System.