Temporal Progression of Excitotoxic Calcium Following Distal Middle Cerebral Artery Occlusion in Freely Moving Mice.

Ischemic stroke is recognized as one of the leading causes of adult disability, morbidity, and death worldwide. Following stroke, acute neuronal excitotoxicity can lead to many deleterious consequences, one of which is the dysregulation of intracellular calcium ultimately culminating in cell death. However, to develop neuroprotective treatments that target neuronal excitotoxicity, it is essential to know the therapeutic time window for intervention following an ischemic event. To address this question, the current study aimed to characterize the magnitude and temporal progression of neuronal intracellular calcium observed following distal middle cerebral artery occlusion (dMCAO) in mice. Using the calcium fluorescence indicator, GCaMP, we tracked neuronal population response in freely moving animals immediately following dMCAO in both the core infarct and peri-infarct regions. Our results demonstrate that calcium excitotoxicity following artery occlusion can be generally characterized by two phases: a transient increase in activity that lasts tens of minutes, followed by a long, slow sustained increase in fluorescence signal. The first phase is primarily thought to represent neuronal hyperexcitability, defining our therapeutic window, while the second may represent gradual cell death. Importantly, we show that the level of intracellular calcium following artery occlusion correlated with the infarct size at 24 h demonstrating a direct connection between excitotoxicity and cell death in our stroke model. In addition, we show that administration of the NMDA antagonist MK-801 resulted in both a decrease in calcium signal and a subsequent reduction in the infarct size. Altogether, this study represents the first demonstration in freely moving animals characterizing the temporal progression of toxic calcium signaling following artery occlusion. In addition, these results define a critical time window for neuroprotective therapeutic intervention in mice.

In Vivo Modulation of Hippocampal Excitability by M4 Muscarinic Acetylcholine Receptor Activator: Implications for Treatment of Alzheimer's Disease and Schizophrenic Patients.

Abnormal hippocampal activity has been linked to impaired cognitive performance in Alzheimer's disease and schizophrenia, leading to a hypothesis that normalization of this activity may be therapeutically beneficial. Our work suggests that one approach for hippocampal normalization may be through activation of the M4 muscarinic acetylcholine receptor. We used a brain penetrant M4 muscarinic acetylcholine receptor selective activator, PT-3763, to show dose-dependent attenuation of field potentials in Schaffer collateral (CA3-CA1) and recurrent associational connections (CA3-CA3) ex vivo in hippocampal slices. In vivo, systemic administration of PT-3763 led to attenuation of glutamate release in CA3 as measured by amperometry and to a dose-dependent decrease in population CA1 pyramidal activity as measured by fiber photometry. This decrease in population activity was also evident with a localized administration of the compound to the recorded site. Finally, PT-3763 reversed scopolamine-induced deficit in Morris water maze. Our results suggest that M4 muscarinic acetylcholine receptor activation may be a suitable therapeutic treatment in diseases associated with hyperactive hippocampal activity.

A rapidly acting glutamatergic ARC→PVH satiety circuit postsynaptically regulated by α-MSH.

Arcuate nucleus (ARC) neurons sense the fed or fasted state and regulate hunger. Agouti-related protein (AgRP) neurons in the ARC (ARCAgRP neurons) are stimulated by fasting and, once activated, they rapidly (within minutes) drive hunger. Pro-opiomelanocortin (ARCPOMC) neurons are viewed as the counterpoint to ARCAgRP neurons. They are regulated in an opposite fashion and decrease hunger. However, unlike ARCAgRP neurons, ARCPOMC neurons are extremely slow in affecting hunger (many hours). Thus, a temporally analogous, rapid ARC satiety pathway does not exist or is presently unidentified. Here we show that glutamate-releasing ARC neurons expressing oxytocin receptor, unlike ARCPOMC neurons, rapidly cause satiety when chemo- or optogenetically manipulated. These glutamatergic ARC projections synaptically converge with GABAergic ARCAgRP projections on melanocortin-4 receptor (MC4R)-expressing satiety neurons in the paraventricular hypothalamus (PVHMC4R neurons). Transmission across the ARCGlutamatergic→PVHMC4R synapse is potentiated by the ARCPOMC neuron-derived MC4R agonist, α-melanocyte stimulating hormone (α-MSH). This excitatory ARC→PVH satiety circuit, and its modulation by α-MSH, provides insight into regulation of hunger and satiety.

Bidirectional Anticipation of Future Osmotic Challenges by Vasopressin Neurons.

Ingestion of water and food are major hypo- and hyperosmotic challenges. To protect the body from osmotic stress, posterior pituitary-projecting, vasopressin-secreting neurons (VPpp neurons) counter osmotic perturbations by altering their release of vasopressin, which controls renal water excretion. Vasopressin levels begin to fall within minutes of water consumption, even prior to changes in blood osmolality. To ascertain the precise temporal dynamics by which water or food ingestion affect VPpp neuron activity, we directly recorded the spiking and calcium activity of genetically defined VPpp neurons. In states of elevated osmolality, water availability rapidly decreased VPpp neuron activity within seconds, beginning prior to water ingestion, upon presentation of water-predicting cues. In contrast, food availability following food restriction rapidly increased VPpp neuron activity within seconds, but only following feeding onset. These rapid and distinct changes in activity during drinking and feeding suggest diverse neural mechanisms underlying anticipatory regulation of VPpp neurons.

Interacting Neural Processes of Feeding, Hyperactivity, Stress, Reward, and the Utility of the Activity-Based Anorexia Model of Anorexia Nervosa.

Anorexia nervosa (AN) is a psychiatric illness with minimal effective treatments and a very high rate of mortality. Understanding the neurobiological underpinnings of the disease is imperative for improving outcomes and can be aided by the study of animal models. The activity-based anorexia rodent model (ABA) is the current best parallel for the study of AN. This review describes the basic neurobiology of feeding and hyperactivity seen in both ABA and AN, and compiles the research on the role that stress-response and reward pathways play in modulating the homeostatic drive to eat and to expend energy, which become dysfunctional in ABA and AN.

Preemptive Stimulation of AgRP Neurons in Fed Mice Enables Conditioned Food Seeking under Threat.

The decision to engage in food-seeking behavior depends not only on homeostatic signals related to energy balance [1] but also on the presence of competing motivational drives [2] and learned cues signaling food availability [3]. Agouti-related peptide (AgRP) neurons in the arcuate nucleus of the hypothalamus are critical for homeostatic feeding behavior. Selective ablation or silencing of AgRP neurons causes anorexia [4, 5], whereas selective stimulation in fed mice promotes feeding and learned instrumental actions to obtain food reward [5-8]. However, it remains unknown whether AgRP neuron stimulation is sufficient to drive food-seeking behavior in the continued presence of a competing motivational drive, such as threat avoidance, or whether it can drive discrimination between learned sensory cues associated with food reward and other outcomes. Here we trained mice to perform a sensory discrimination task involving appetitive and aversive visual cues. Food-restricted mice exhibited selective operant responding to food-predicting cues but largely failed to avoid cued shocks by moving onto a safety platform. The opposite was true following re-feeding. Strikingly, AgRP neuron photostimulation did not restore operant responding in fed mice when initiated within the threat-containing arena, but did when initiated in the home cage, prior to arena entry. These data suggest that the choice to pursue certain behaviors and not others (e.g., food seeking versus shock avoidance) can depend on the temporal primacy of one motivational drive relative to the onset of a competing drive.

Arcuate hypothalamic AgRP and putative POMC neurons show opposite changes in spiking across multiple timescales.

Agouti-related-peptide (AgRP) neurons-interoceptive neurons in the arcuate nucleus of the hypothalamus (ARC)-are both necessary and sufficient for driving feeding behavior. To better understand the functional roles of AgRP neurons, we performed optetrode electrophysiological recordings from AgRP neurons in awake, behaving AgRP-IRES-Cre mice. In free-feeding mice, we observed a fivefold increase in AgRP neuron firing with mounting caloric deficit in afternoon vs morning recordings. In food-restricted mice, as food became available, AgRP neuron firing dropped, yet remained elevated as compared to firing in sated mice. The rapid drop in spiking activity of AgRP neurons at meal onset may reflect a termination of the drive to find food, while residual, persistent spiking may reflect a sustained drive to consume food. Moreover, nearby neurons inhibited by AgRP neuron photostimulation, likely including satiety-promoting pro-opiomelanocortin (POMC) neurons, demonstrated opposite changes in spiking. Finally, firing of ARC neurons was also rapidly modulated within seconds of individual licks for liquid food. These findings suggest novel roles for antagonistic AgRP and POMC neurons in the regulation of feeding behaviors across multiple timescales.

A role for descending auditory cortical projections in songbird vocal learning.

Many learned motor behaviors are acquired by comparing ongoing behavior with an internal representation of correct performance, rather than using an explicit external reward. For example, juvenile songbirds learn to sing by comparing their song with the memory of a tutor song. At present, the brain regions subserving song evaluation are not known. In this study, we report several findings suggesting that song evaluation involves an avian 'cortical' area previously shown to project to the dopaminergic midbrain and other downstream targets. We find that this ventral portion of the intermediate arcopallium (AIV) receives inputs from auditory cortical areas, and that lesions of AIV result in significant deficits in vocal learning. Additionally, AIV neurons exhibit fast responses to disruptive auditory feedback presented during singing, but not during nonsinging periods. Our findings suggest that auditory cortical areas may guide learning by transmitting song evaluation signals to the dopaminergic midbrain and/or other subcortical targets.

An automated procedure for evaluating song imitation.

Songbirds have emerged as an excellent model system to understand the neural basis of vocal and motor learning. Like humans, songbirds learn to imitate the vocalizations of their parents or other conspecific "tutors." Young songbirds learn by comparing their own vocalizations to the memory of their tutor song, slowly improving until over the course of several weeks they can achieve an excellent imitation of the tutor. Because of the slow progression of vocal learning, and the large amounts of singing generated, automated algorithms for quantifying vocal imitation have become increasingly important for studying the mechanisms underlying this process. However, methodologies for quantifying song imitation are complicated by the highly variable songs of either juvenile birds or those that learn poorly because of experimental manipulations. Here we present a method for the evaluation of song imitation that incorporates two innovations: First, an automated procedure for selecting pupil song segments, and, second, a new algorithm, implemented in Matlab, for computing both song acoustic and sequence similarity. We tested our procedure using zebra finch song and determined a set of acoustic features for which the algorithm optimally differentiates between similar and non-similar songs.

Expressions of multiple neuronal dynamics during sensorimotor learning in the motor cortex of behaving monkeys.

Previous studies support the notion that sensorimotor learning involves multiple processes. We investigated the neuronal basis of these processes by recording single-unit activity in motor cortex of non-human primates (Macaca fascicularis), during adaptation to force-field perturbations. Perturbed trials (reaching to one direction) were practiced along with unperturbed trials (to other directions). The number of perturbed trials relative to the unperturbed ones was either low or high, in two separate practice schedules. Unsurprisingly, practice under high-rate resulted in faster learning with more pronounced generalization, as compared to the low-rate practice. However, generalization and retention of behavioral and neuronal effects following practice in high-rate were less stable; namely, the faster learning was forgotten faster. We examined two subgroups of cells and showed that, during learning, the changes in firing-rate in one subgroup depended on the number of practiced trials, but not on time. In contrast, changes in the second subgroup depended on time and practice; the changes in firing-rate, following the same number of perturbed trials, were larger under high-rate than low-rate learning. After learning, the neuronal changes gradually decayed. In the first subgroup, the decay pace did not depend on the practice rate, whereas in the second subgroup, the decay pace was greater following high-rate practice. This group shows neuronal representation that mirrors the behavioral performance, evolving faster but also decaying faster at learning under high-rate, as compared to low-rate. The results suggest that the stability of a new learned skill and its neuronal representation are affected by the acquisition schedule.

The neuronal basis of long-term sensorimotor learning.

The brain has a remarkable ability to learn and adjust behavior. For instance, the brain can adjust muscle activation to cope with changes in the environment. However, the neuronal mechanisms behind this adaptation are not clear. To address this fundamental question, this study examines the neuronal basis of long-term sensorimotor learning by recording neuronal activity in the primary motor cortex of monkeys during a long-term adaptation to a force-field perturbation. For 5 consecutive days, the same perturbation was applied to the monkey's hand when reaching to a single target, whereas movements to all other targets were not perturbed. The gradual improvement in performance over these 5 days was correlated to the evolvement in the population neuronal signal, with two timescales of changes in single-cell activity. Specifically, one subgroup of cells showed a relatively fast increase in activity, whereas the other showed a gradual, slower decrease. These adapted patterns of neuronal activity did not involve changes in directional tuning of single cells, suggesting that adaptation was the result of adjustments of the required motor plan by a population of neurons rather than changes in single-cell properties. Furthermore, generalization was mostly expressed in the direction of the required compensatory force during adaptation. Altogether, the neuronal activity and its generalization accord with the adapted motor plan.

Neuronal correlates of memory formation in motor cortex after adaptation to force field.

Activity of single neurons in the motor cortex has been shown to change during acquisition of motor skills. We previously reported that the combined activity of cell ensembles in the motor cortex of monkeys (Macaca fascicularis) evolves during adaptation to a novel force field perturbation to encode the direction of compensatory force when reaching to visual targets. We also showed that the population directional signal was altered by the available sensory feedback. Here, we examined whether traces of such activity would linger on to later constitute motor memories of the newly acquired skill and whether memory traces would differ depending on feedback. We found that motor-cortical cell ensembles retained features of their adaptive activity pattern in the absence of perturbation when reaching to both learned and unlearned targets. Moreover, the preferred directions of these cells rotated in the direction of force field while the entire population of cells produced no net rotation of preferred direction when returning to null-field reaches. Whereas the activity pattern and preferred direction rotations were comparable with and without visual feedback, changes in tuning amplitudes differed across feedback conditions. Last, savings in behavioral performance and neuronal activity during later reexposure to force field were apparent. Overall, the findings reflect a novel representation of motor memory by cell ensembles and indicate a putative role of the motor cortex in early acquisition of motor memory.

Combined adaptiveness of specific motor cortical ensembles underlies learning.

Learning motor skills entails adaptation of neural computations that can generate or modify associations between sensations and actions. Indeed, humans can use different strategies when adapting to dynamic loads depending on available sensory feedback. Here, we examined how neural activity in motor cortex was modified when monkeys made arm reaches to a visual target and locally adapted to curl force field with or without visual trajectory feedback. We found that firing rates of a large subpopulation of cells were consistently modulated depending on the distance of their preferred direction from the learned movement direction. The newly acquired activity followed a cosine-like function, with maximal increase in directions that opposed the perturbing force and decrease in opposite directions. As a result, the combined neuronal activity generated an adapted population vector. The results suggest that this could be achieved without changing the tuning properties of the cells. This population directional signal was however altered in the absence of visual feedback; while the cosine pattern of modulation was maintained, the population distributions of modulated cells differed across feedback consistent with the different trajectory shapes. Finally, we predicted generalization patterns of force-field learning based on the cosine-like modulation. These conformed to reported features of generalization in humans, suggesting that the generalization function was related to the observed rate modulations in the motor cortex. Overall, the findings suggest that the new combined activation of neuronal ensembles could underlie the change in the internal model of movement dynamics in a way that depends on available sensory feedback and chosen strategy.

Trial-to-trial variability of single cells in motor cortices is dynamically modified during visuomotor adaptation.

Neurons in all brain areas exhibit variability in their spiking activity. Although part of this variability can be considered as noise that is detrimental to information processing, recent findings indicate that variability can also be beneficial. In particular, it was suggested that variability in the motor system allows for exploration of possible motor states and therefore can facilitate learning and adaptation to new environments. Here, we provide evidence to support this idea by analyzing the variability of neurons in the primary motor cortex (M1) and in the supplementary motor area (SMA-proper) of monkeys adapting to new rotational visuomotor tasks. We found that trial-to-trial variability increased during learning and exhibited four main characteristics: (1) modulation occurred preferentially during a delay period when the target of movement was already known, but before movement onset; (2) variability returned to its initial levels toward the end of learning; (3) the increase in variability was more apparent in cells with preferred movement directions close to those experienced during learning; and (4) the increase in variability emerged at early phases of learning in the SMA, whereas in M1 behavior reached plateau levels of performance. These results are highly consistent with previous findings that showed similar trends in variability across a population of neurons. Together, the results strengthen the idea that single-cell variability can be much more than mere noise and may be an integral part of the underlying mechanism of sensorimotor learning.