Different Effects of Peer Sex on Operant Responding for Social Interaction and Striatal Dopamine Activity.

When rats are given discrete choices between social interactions with a peer and opioid or psychostimulant drugs, they choose social interaction, even after extensive drug self-administration experience. Studies show that like drug and nondrug food reinforcers, social interaction is an operant reinforcer and induces dopamine release. However, these studies were conducted with same-sex peers. We examined if peer sex influences operant social interaction and the role of estrous cycle and striatal dopamine in same- versus opposite-sex social interaction. We trained male and female rats (n = 13 responders/12 peers) to lever-press (fixed-ratio 1 [FR1] schedule) for 15 s access to a same- or opposite-sex peer for 16 d (8 d/sex) while tracking females' estrous cycle. Next, we transfected GRAB-DA2m and implanted optic fibers into nucleus accumbens (NAc) core and dorsomedial striatum (DMS). We then retrained the rats for 15 s social interaction (FR1 schedule) for 16 d (8 d/sex) and recorded striatal dopamine during operant responding for a peer for 8 d (4 d/sex). Finally, we assessed economic demand by manipulating FR requirements for a peer (10 d/sex). In male, but not female rats, operant responding was higher for the opposite-sex peer. Female's estrous cycle fluctuations had no effect on operant social interaction. Striatal dopamine signals for operant social interaction were dependent on the peer's sex and striatal region (NAc core vs DMS). Results indicate that estrous cycle fluctuations did not influence operant social interaction and that NAc core and DMS dopamine activity reflect sex-dependent features of volitional social interaction.

Listening to the Data: Computational Approaches to Addiction and Learning.

Computational approaches hold great promise for identifying novel treatment targets and creating translational therapeutics for substance use disorders. From circuitries underlying decision-making to computationally derived neural markers of drug-cue reactivity, this review is a summary of the approaches to data presented at our 2023 Society for Neuroscience Mini-Symposium. Here, we highlight data- and hypothesis-driven computational approaches that recently afforded advancements in addiction and learning neuroscience. First, we discuss the value of hypothesis-driven algorithmic modeling approaches, which integrate behavioral, neural, and cognitive outputs to refine hypothesis testing. Then, we review the advantages of data-driven dimensionality reduction and machine learning methods for uncovering novel predictor variables and elucidating relationships in high-dimensional data. Overall, this review highlights recent breakthroughs in cognitive mapping, model-based analysis of behavior/risky decision-making, patterns of drug taking, relapse, and neuromarker discovery, and showcases the benefits of novel modeling techniques, across both preclinical and clinical data.

Multi-scale detection of rate changes in spike trains with weak dependencies.

The statistical analysis of neuronal spike trains by models of point processes often relies on the assumption of constant process parameters. However, it is a well-known problem that the parameters of empirical spike trains can be highly variable, such as for example the firing rate. In order to test the null hypothesis of a constant rate and to estimate the change points, a Multiple Filter Test (MFT) and a corresponding algorithm (MFA) have been proposed that can be applied under the assumption of independent inter spike intervals (ISIs). As empirical spike trains often show weak dependencies in the correlation structure of ISIs, we extend the MFT here to point processes associated with short range dependencies. By specifically estimating serial dependencies in the test statistic, we show that the new MFT can be applied to a variety of empirical firing patterns, including positive and negative serial correlations as well as tonic and bursty firing. The new MFT is applied to a data set of empirical spike trains with serial correlations, and simulations show improved performance against methods that assume independence. In case of positive correlations, our new MFT is necessary to reduce the number of false positives, which can be highly enhanced when falsely assuming independence. For the frequent case of negative correlations, the new MFT shows an improved detection probability of change points and thus, also a higher potential of signal extraction from noisy spike trains.

Short-term sustained hypoxia induces changes in the coupling of sympathetic and respiratory activities in rats.

Individuals experiencing sustained hypoxia (SH) exhibit adjustments in the respiratory and autonomic functions by neural mechanisms not yet elucidated. In the present study we evaluated the central mechanisms underpinning the SH-induced changes in the respiratory pattern and their impact on the sympathetic outflow. Using a decerebrated arterially perfused in situ preparation, we verified that juvenile rats exposed to SH (10% O2) for 24 h presented an active expiratory pattern, with increased abdominal, hypoglossal and vagal activities during late-expiration (late-E). SH also enhanced the activity of augmenting-expiratory neurones and depressed the activity of post-inspiratory neurones of the Bötzinger complex (BötC) by mechanisms not related to changes in their intrinsic electrophysiological properties. SH rats exhibited high thoracic sympathetic activity and arterial pressure levels associated with an augmented firing frequency of pre-sympathetic neurones of the rostral ventrolateral medulla (RVLM) during the late-E phase. The antagonism of ionotropic glutamatergic receptors in the BötC/RVLM abolished the late-E bursts in expiratory and sympathetic outputs of SH rats, indicating that glutamatergic inputs to the BötC/RVLM are essential for the changes in the expiratory and sympathetic coupling observed in SH rats. We also observed that the usually silent late-E neurones of the retrotrapezoid nucleus/parafacial respiratory group became active in SH rats, suggesting that this neuronal population may provide the excitatory drive essential to the emergence of active expiration and sympathetic overactivity. We conclude that short-term SH induces the activation of medullary expiratory neurones, which affects the pattern of expiratory motor activity and its coupling with sympathetic activity.

Generalized cue reactivity in dopamine neurons after opioids.

Cue reactivity is the maladaptive neurobiological and behavioral response upon exposure to drug cues and is a major driver of relapse. The leading hypothesis is that dopamine release by addictive drugs represents a persistently positive reward prediction error that causes runaway enhancement of dopamine responses to drug cues, leading to their pathological overvaluation compared to non-drug reward alternatives. However, this hypothesis has not been directly tested. Here we developed Pavlovian and operant procedures to measure firing responses, within the same dopamine neurons, to drug versus natural reward cues, which we found to be similarly enhanced compared to cues predicting natural rewards in drug-naïve controls. This enhancement was associated with increased behavioral reactivity to the drug cue, suggesting that dopamine release is still critical to cue reactivity, albeit not as previously hypothesized. These results challenge the prevailing hypothesis of cue reactivity, warranting new models of dopaminergic function in drug addiction, and provide critical insights into the neurobiology of cue reactivity with potential implications for relapse prevention.

The epilepsies: complex challenges needing complex solutions.

It is widely accepted that epilepsies are complex syndromes due to their multi-factorial origins and manifestations. Different mathematical and computational descriptions use appropriate methods to address nonlinear relationships, chaotic behaviors and emergent properties. These theoretical approaches can be divided into two major categories: descriptive, such as flowcharts, graphs and other statistical analyses, and explicative, which include both realistic and abstract models. Although these modeling tools have brought great advances, a common framework to guide their design, implementation and evaluation, with the goal of future integration, is still needed. In the current review, we discuss two examples of complexity analysis that can be performed with epilepsy data: behavioral sequences of temporal lobe seizures and alterations in an experimental cellular model. We also highlight the importance of the creation of model repositories for the epileptology field and encourage the development of mathematical descriptions of complex systems, together with more accurate simulation techniques.

A Digital Filter-Based Method for Diagnosing Speech Comprehension Deficits.

OBJECTIVE: To improve the diagnostic efficiency of current tests for auditory processing disorders (APDs) by creating new test signals using digital filtering methods. METHODS: We conducted a prospective study from August 1, 2014, to August 31, 2019, using 3 low speech redundancy tests with novel test signals that we created with specially designed digital filters: the binaural resynthesis test and the low pass and high pass filtered speech tests. We validated and optimized these new tests, then applied them to healthy individuals across different age groups to examine how age affected performance and to children with APD before and after acoustically controlled auditory training (ACAT) to assess clinical improvement after treatment. RESULTS: We found a progressive increase in performance accuracy with less restrictive filters (P<.001) and with increasing age for all tests (P<.001). Our results suggest that binaural resynthesis and auditory closure mature at similar rates. We also demonstrate that the new tests can be used for the diagnosis of APD and for the monitoring of ACAT effects. Interestingly, we found that patients having the most severe deficits also benefited the most from ACAT (P<.001). CONCLUSION: We introduce a method that substantially improves current diagnostic tools for APD. In addition, we provide information on auditory processing maturation in normal development and validate that our method can detect APD-related deficits and ACAT-induced improvements in auditory processing.

Voice disorder in systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a chronic disease characterized by progressive tissue damage. In recent decades, novel treatments have greatly extended the life span of SLE patients. This creates a high demand for identifying the overarching symptoms associated with SLE and developing therapies that improve their life quality under chronic care. We hypothesized that SLE patients would present dysphonic symptoms. Given that voice disorders can reduce life quality, identifying a potential SLE-related dysphonia could be relevant for the appraisal and management of this disease. We measured objective vocal parameters and perceived vocal quality with the GRBAS (Grade, Roughness, Breathiness, Asthenia, Strain) scale in SLE patients and compared them to matched healthy controls. SLE patients also filled a questionnaire reporting perceived vocal deficits. SLE patients had significantly lower vocal intensity and harmonics to noise ratio, as well as increased jitter and shimmer. All subjective parameters of the GRBAS scale were significantly abnormal in SLE patients. Additionally, the vast majority of SLE patients (29/36) reported at least one perceived vocal deficit, with the most prevalent deficits being vocal fatigue (19/36) and hoarseness (17/36). Self-reported voice deficits were highly correlated with altered GRBAS scores. Additionally, tissue damage scores in different organ systems correlated with dysphonic symptoms, suggesting that some features of SLE-related dysphonia are due to tissue damage. Our results show that a large fraction of SLE patients suffers from perceivable dysphonia and may benefit from voice therapy in order to improve quality of life.

Evolution and physiology of neural oxygen sensing.

Major evolutionary trends in animal physiology have been heavily influenced by atmospheric O2 levels. Amongst other important factors, the increase in atmospheric O2 which occurred in the Pre-Cambrian and the development of aerobic respiration beckoned the evolution of animal organ systems that were dedicated to the absorption and transportation of O2, e.g., the respiratory and cardiovascular systems of vertebrates. Global variations of O2 levels in post-Cambrian periods have also been correlated with evolutionary changes in animal physiology, especially cardiorespiratory function. Oxygen transportation systems are, in our view, ultimately controlled by the brain related mechanisms, which senses changes in O2 availability and regulates autonomic and respiratory responses that ensure the survival of the organism in the face of hypoxic challenges. In vertebrates, the major sensorial system for oxygen sensing and responding to hypoxia is the peripheral chemoreflex neuronal pathways, which includes the oxygen chemosensitive glomus cells and several brainstem regions involved in the autonomic regulation of the cardiovascular system and respiratory control. In this review we discuss the concept that regulating O2 homeostasis was one of the primordial roles of the nervous system. We also review the physiology of the peripheral chemoreflex, focusing on the integrative repercussions of chemoreflex activation and the evolutionary importance of this system, which is essential for the survival of complex organisms such as vertebrates. The contribution of hypoxia and peripheral chemoreflex for the development of diseases associated to the cardiovascular and respiratory systems is also discussed in an evolutionary context.

Acute inhibition of glial cells in the NTS does not affect respiratory and sympathetic activities in rats exposed to chronic intermittent hypoxia.

Recent studies suggest that neuron-glia interactions are involved in multiple aspects of neuronal activity regulation. In the nucleus tractus solitarius (NTS) neuron-glia interactions are thought to participate in the integration of autonomic responses to physiological challenges. However, it remains to be shown whether NTS glial cells might influence breathing and cardiovascular control, and also if they could be integral to the autonomic and respiratory responses to hypoxic challenges. Here, we investigated whether NTS glia play a tonic role in the modulation of central respiratory and sympathetic activities as well as in the changes in respiratory-sympathetic coupling induced by exposure to chronic intermittent hypoxia (CIH), a model of central autonomic and respiratory plasticity. We show that bilateral microinjections of fluorocitrate (FCt), a glial cell inhibitor, into the caudal and intermediate subnuclei of the NTS did not alter baseline respiratory and sympathetic parameters in in situ preparations of juvenile rats. Similar results were observed in rats previously exposed to CIH. Likewise, CIH-induced changes in respiratory-sympathetic coupling were unaffected by FCt-mediated inhibition. However, microinjection of FCt into the ventral medulla produced changes in respiratory frequency. Our results show that acute glial inhibition in the NTS does not affect baseline respiratory and sympathetic control. Additionally, we conclude that NTS glial cells may not be necessary for the continuous manifestation of sympathetic and respiratory adaptations to CIH. Our work provides evidence that neuron-glia interactions in the NTS do not participate in baseline respiratory and sympathetic control.