A Simple, Lightweight, and Low-Cost Customizable Multielectrode Array for Local Field Potential Recordings.

Local field potential (LFP) recording is a valuable method for assessing brain systems communication. Multiple methods have been developed to collect LFP data to study the rhythmic activity of the brain. These methods range from the use of single or bundled metal electrodes to electrode arrays that can target multiple brain regions. Although these electrodes are efficient in collecting LFP activity, they can be expensive, difficult to build, and less adaptable to different applications, which may include targeting multiple brain regions simultaneously. Here, the building process for a 16-channel customizable multielectrode array (CMEA) that can be used to collect LFP data from different brain regions simultaneously in rats is described. These CMEA electrode arrays are lightweight (<1 g), take little time to build (<1 h), and are affordable ($15 Canadian). The CMEA can also be modified to record single-unit and multiunit activity in addition to LFP activity using both wired and wireless neural data acquisition systems. Moreover, these CMEAs can be used to explore neural activity (LFP and single-unit/multiunit activity) in preliminary studies, before purchasing more expensive electrodes for targeted studies. Together, these characteristics make the described CMEA a competitive alternative to the commercially available multielectrode arrays for its simplicity, low cost, and efficiency in collecting LFP data in freely behaving animals.

Neural oscillations in the ventral striatum reveal differences between the encoding of palatable food and ethanol consumption.

BACKGROUND: Across multiple levels of investigation, there appear to be convergent neuronal processes underlying substance use and other motivated behaviors (i.e., the pursuit and consumption of rewarding substances). The consumption of alcohol and sweet, high-fat food engages many of the same brain regions, especially, the ventral striatum. In the current study, we hypothesized that ventral striatal local field potentials (LFPs) recorded during self-administration sessions could be used to detect when the consumption of 10% ethanol or sweet-fat food (SF) was occurring compared to all other behaviors, including naturalistic controls (i.e., water or house-chow). METHODS: We used an intermittent limited access approach to condition Sprague-Dawley rats to consume either ethanol or SF while we recorded LFPs. We used machine learning and simple logistic regressions to determine whether LFP features could classify when consumption of each substance was occurring, and whether a general model could predict consumption of both substances. We report performance as the average area under the receiver operator characteristic curve (AUROC). RESULTS: Consumption of a single substance was differentiable from all other behaviors, as evidenced by the AUROC (ethanol = 0.84 and SF = 0.83, p < 0.01). Models built from the combined dataset (general) did modestly overall (general → general = 0.68, p < 0.05), and did not detect the consumption of the two substances similarly (general → SF = 0.5 and general → ethanol = 0.63, p > 0.05). CONCLUSIONS: Models successfully classified ethanol and SF consumption versus all other behavior/naturalistic controls. However, the findings highlight differences in how the ventral striatum represents the consumption of ethanol and SF and show that, although there is potential for finding biomarkers related to substance use, it may be difficult to build a model that performs well detecting multiple substances.

Maternal immune activation and adolescent alcohol exposure increase alcohol drinking and disrupt cortical-striatal-hippocampal oscillations in adult offspring.

Maternal immune activation (MIA) is strongly associated with an increased risk of developing mental illness in adulthood, which often co-occurs with alcohol misuse. The current study aimed to begin to determine whether MIA, combined with adolescent alcohol exposure (AE), could be used as a model with which we could study the neurobiological mechanisms behind such co-occurring disorders. Pregnant Sprague-Dawley rats were treated with polyI:C or saline on gestational day 15. Half of the offspring were given continuous access to alcohol during adolescence, leading to four experimental groups: controls, MIA, AE, and Dual (MIA + AE). We then evaluated whether MIA and/or AE alter: (1) alcohol consumption; (2) locomotor behavior; and (3) cortical-striatal-hippocampal local field potentials (LFPs) in adult offspring. Dual rats, particularly females, drank significantly more alcohol in adulthood compared to all other groups. MIA led to reduced locomotor behavior in males only. Using machine learning to build predictive models from LFPs, we were able to differentiate Dual rats from control rats and AE rats in both sexes, and Dual rats from MIA rats in females. These data suggest that Dual "hits" (MIA + AE) increases substance use behavior and disrupts activity in reward-related circuits, and that this may be a valuable heuristic model we can use to study the neurobiological underpinnings of co-occurring disorders. Our future work aims to extend these findings to other addictive substances to enhance the translational relevance of this model, as well as determine whether amelioration of these circuit disruptions can reduce substance use behavior.

Chronic chemogenetic manipulation of ventral pallidum targeted neurons in male rats fed an obesogenic diet.

Current treatments for obesity do not reliably reduce body weight over time. New interventional strategies, including chemogenetics, carry promise based on preclinical animal studies. Here, we focused on the ventral pallidum (VP) due to its clearly established role in eating behavior. Chronic inhibitory or excitatory chemogenetic activation was used to modulate the activity of VP-targeted neurons in rats on an obesogenic diet. Based on studies using acute VP manipulations, we hypothesized that VP inhibition would decrease weight gain, while VP stimulation would increase weight. Instead, both manipulations caused weight gain over time, and in a manner not clearly linked to consumption levels. We theorize that the complex reciprocal feedback between ventral striatal structures and metabolic centers likely underpin our unexpected findings. Regardless, this study suggests that the result of strategies to prevent obesity with chronic neuromodulation could be difficult to predict from prior preclinical studies that have used acute interventions.

The Impact of Adolescent Alcohol Exposure on Nicotine Behavioral Sensitization in the Adult Male Neonatal Ventral Hippocampal Lesion Rat.

Nicotine and alcohol use is highly prevalent among patients with serious mental illness, including those with schizophrenia (SCZ), and this co-occurrence can lead to a worsening of medical and psychiatric morbidity. While the mechanistic drivers of co-occurring SCZ, nicotine use and alcohol use are unknown, emerging evidence suggests that the use of drugs during adolescence may increase the probability of developing psychiatric disorders. The current study used the neonatal ventral hippocampal lesion (NVHL) rat model of SCZ, which has previously been shown to have enhanced nicotine behavioral sensitization and, following adolescent alcohol, increased alcohol consumption. Given how commonly alcohol is used by adolescents that develop SCZ, we used the NVHL rat to determine how exposure to adolescent alcohol impacts the development of nicotine behavioral sensitization in adulthood. Male Sprague-Dawley rats underwent the NVHL surgery or a sham (control) surgery and subsequently, half of each group was allowed to drink alcohol during adolescence. Nicotine behavioral sensitization was assessed in adulthood with rats receiving subcutaneous injections of nicotine (0.5 mg/kg) each day for 3 weeks followed by a nicotine challenge session 2 weeks later. We demonstrate that all groups of rats became sensitized to nicotine and there were no NVHL-specific increases in nicotine behavioral sensitization. We also found that NVHL rats appeared to develop sensitization to the nicotine paired context and that adolescent alcohol exposure blocked this context sensitization. The current findings suggest that exposure to alcohol during adolescence can influence behaviors that manifest in the adult NVHL rat (i.e., context sensitization). Interestingly, nicotine behavioral sensitization levels were not altered in the NVHL groups regardless of adolescent alcohol exposure in contrast to prior reports.

Acquisition of Resting-State Functional Magnetic Resonance Imaging Data in the Rat.

Resting-state functional magnetic resonance imaging (rs-fMRI) has become an increasingly popular method to study brain function in a resting, non-task state. This protocol describes a preclinical survival method for obtaining rs-fMRI data. Combining low dose isoflurane with continuous infusion of the α2 adrenergic receptor agonist dexmedetomidine provides a robust option for stable, high-quality data acquisition while preserving brain network function. Furthermore, this procedure allows for spontaneous breathing and near-normal physiology in the rat. Additional imaging sequences can be combined with resting-state acquisition creating experimental protocols with anesthetic stability of up to 5 h using this method. This protocol describes the setup of equipment, monitoring of rat physiology during four distinct phases of anesthesia, acquisition of resting-state scans, quality assessment of data, recovery of the animal, and a brief discussion of post-processing data analysis. This protocol can be used across a wide variety of preclinical rodent models to help reveal the resulting brain network changes that occur at rest.

Sex differences in the ability of corticostriatal oscillations to predict rodent alcohol consumption.

BACKGROUND: Although male and female rats differ in their patterns of alcohol use, little is known regarding the neural circuit activity that underlies these differences in behavior. The current study used a machine learning approach to characterize sex differences in local field potential (LFP) oscillations that may relate to sex differences in alcohol-drinking behavior. METHODS: LFP oscillations were recorded from the nucleus accumbens shell and the rodent medial prefrontal cortex of adult male and female Sprague-Dawley rats. Recordings occurred before rats were exposed to alcohol (n = 10/sex × 2 recordings/rat) and during sessions of limited access to alcohol (n = 5/sex × 5 recordings/rat). Oscillations were also recorded from each female rat in each phase of estrous prior to alcohol exposure. Using machine learning, we built predictive models with oscillation data to classify rats based on: (1) biological sex, (2) phase of estrous, and (3) alcohol intake levels. We evaluated model performance from real data by comparing it to the performance of models built and tested on permutations of the data. RESULTS: Our data demonstrate that corticostriatal oscillations were able to predict alcohol intake levels in males (p < 0.01), but not in females (p = 0.45). The accuracies of models predicting biological sex and phase of estrous were related to fluctuations observed in alcohol drinking levels; females in diestrus drank more alcohol than males (p = 0.052), and the male vs. diestrus female model had the highest accuracy (71.01%) compared to chance estimates. Conversely, females in estrus drank very similar amounts of alcohol to males (p = 0.702), and the male vs. estrus female model had the lowest accuracy (56.14%) compared to chance estimates. CONCLUSIONS: The current data demonstrate that oscillations recorded from corticostriatal circuits contain significant information regarding alcohol drinking in males, but not alcohol drinking in females. Future work will focus on identifying where to record LFP oscillations in order to predict alcohol drinking in females, which may help elucidate sex-specific neural targets for future therapeutic development.

Corticostriatal Oscillations Predict High vs. Low Drinkers in a Rat Model of Limited Access Alcohol Consumption.

Individuals differ in their vulnerability to develop alcohol dependence, which is determined by innate and environmental factors. The corticostriatal circuit is heavily involved in the development of alcohol dependence and may contain neural information regarding vulnerability to drink excessively. In the current experiment, we hypothesized that we could characterize high and low alcohol-drinking rats (HD and LD, respectively) based on corticostriatal oscillations and that these subgroups would differentially respond to corticostriatal brain stimulation. Male Sprague-Dawley rats (n = 13) were trained to drink 10% alcohol in a limited access paradigm. In separate sessions, local field potentials (LFPs) were recorded from the nucleus accumbens shell (NAcSh) and medial prefrontal cortex (mPFC). Based on training alcohol consumption levels, we classified rats using a median split as HD or LD. Then, using machine-learning, we built predictive models to classify rats as HD or LD by corticostriatal LFPs and compared the model performance from real data to the performance of models built on data permutations. Additionally, we explored the impact of NAcSh or mPFC stimulation on alcohol consumption in HD vs. LD. Corticostriatal LFPs were able to predict HD vs. LD group classification with greater accuracy than expected by chance (>80% accuracy). Moreover, NAcSh stimulation significantly reduced alcohol consumption in HD, but not LD (p < 0.05), while mPFC stimulation did not alter drinking behavior in either HD or LD (p > 0.05). These data collectively show that the corticostriatal circuit is differentially involved in regulating alcohol intake in HD vs. LD rats, and suggests that corticostriatal activity may have the potential to predict a vulnerability to develop alcohol dependence in a clinical population.

Finding the balance between model complexity and performance: Using ventral striatal oscillations to classify feeding behavior in rats.

The ventral striatum (VS) is a central node within a distributed network that controls appetitive behavior, and neuromodulation of the VS has demonstrated therapeutic potential for appetitive disorders. Local field potential (LFP) oscillations recorded from deep brain stimulation (DBS) electrodes within the VS are a pragmatic source of neural systems-level information about appetitive behavior that could be used in responsive neuromodulation systems. Here, we recorded LFPs from the bilateral nucleus accumbens core and shell (subregions of the VS) during limited access to palatable food across varying conditions of hunger and food palatability in male rats. We used standard statistical methods (logistic regression) as well as the machine learning algorithm lasso to predict aspects of feeding behavior using VS LFPs. We were able to predict the amount of food eaten, the increase in consumption following food deprivation, and the type of food eaten. Further, we were able to predict whether the initiation of feeding was imminent up to 42.5 seconds before feeding began and classify current behavior as either feeding or not-feeding. In classifying feeding behavior, we found an optimal balance between model complexity and performance with models using 3 LFP features primarily from the alpha and high gamma frequencies. As shown here, unbiased methods can identify systems-level neural activity linked to domains of mental illness with potential application to the development and personalization of novel treatments.

Machine Learning Based Classification of Deep Brain Stimulation Outcomes in a Rat Model of Binge Eating Using Ventral Striatal Oscillations.

Neuromodulation-based interventions continue to be evaluated across an array of appetitive disorders but broader implementation of these approaches remains limited due to variable treatment outcomes. We hypothesize that individual variation in treatment outcomes may be linked to differences in the networks underlying these disorders. Here, Sprague-Dawley rats received deep brain stimulation separately within each nucleus accumbens (NAc) sub-region (core and shell) using a within-animal crossover design in a rat model of binge eating. Significant reductions in binge size were observed with stimulation of either target but with significant variation in effectiveness across individuals. When features of local field potentials (LFPs) recorded from the NAc were used to classify the pre-defined stimulation outcomes (response or non-response) from each rat using a machine-learning approach (lasso), stimulation outcomes could be classified with greater accuracy than expected by chance (effect sizes: core = 1.13, shell = 1.05). Further, these LFP features could be used to identify the best stimulation target for each animal (core vs. shell) with an effect size = 0.96. These data suggest that individual differences in underlying network activity may relate to the variable outcomes of circuit based interventions, and measures of network activity could have the potential to individually guide the selection of an optimal stimulation target to improve overall treatment response rates.

The link between schizophrenia and substance use disorder: A unifying hypothesis.

Substance use disorders occur commonly in patients with schizophrenia and dramatically worsen their overall clinical course. While the exact mechanisms contributing to substance use in schizophrenia are not known, a number of theories have been put forward to explain the basis of the co-occurrence of these disorders. We propose here a unifying hypothesis that combines recent evidence from epidemiological and genetic association studies with brain imaging and pre-clinical studies to provide an updated formulation regarding the basis of substance use in patients with schizophrenia. We suggest that the genetic determinants of risk for schizophrenia (especially within neural systems that contribute to the risk for both psychosis and addiction) make patients vulnerable to substance use. Since this vulnerability may arise prior to the appearance of psychotic symptoms, an increased use of substances in adolescence may both enhance the risk for developing a later substance use disorder, and also serve as an additional risk factor for the appearance of psychotic symptoms. Future studies that assess brain circuitry in a prospective longitudinal manner during adolescence prior to the appearance of psychotic symptoms could shed further light on the mechanistic underpinnings of these co-occurring disorders while identifying potential points of intervention for these difficult-to-treat co-occurring disorders.

Behavioral Status Influences the Dependence of Odorant-Induced Change in Firing on Prestimulus Firing Rate.

The firing rate of the mitral/tufted cells in the olfactory bulb is known to undergo significant trial-to-trial variability and is affected by anesthesia. Here we ask whether odorant-elicited changes in firing rate depend on the rate before application of the stimulus in the awake and anesthetized mouse. We find that prestimulus firing rate varies widely on a trial-to-trial basis and that the stimulus-induced change in firing rate decreases with increasing prestimulus firing rate. Interestingly, this prestimulus firing rate dependence was different when the behavioral task did not involve detecting the valence of the stimulus. Finally, when the animal was learning to associate the odor with reward, the prestimulus firing rate was smaller for false alarms compared with correct rejections, suggesting that intrinsic activity reflects the anticipatory status of the animal. Thus, in this sensory modality, changes in behavioral status alter the intrinsic prestimulus activity, leading to a change in the responsiveness of the second-order neurons. We speculate that this trial-to-trial variability in odorant responses reflects sampling of the massive parallel input by subsets of mitral cells.SIGNIFICANCE STATEMENT The olfactory bulb must deal with processing massive parallel input from ∼1200 distinct olfactory receptors. In contrast, the visual system receives input from a small number of photoreceptors and achieves recognition of complex stimuli by allocating processing for distinct spatial locations to different brain areas. Here we find that the change in firing rate elicited by the odorant in second-order mitral cells depends on the intrinsic activity leading to a change of magnitude in the responsiveness of these neurons relative to this prestimulus activity. Further, we find that prestimulus firing rate is influenced by behavioral status. This suggests that there is top-down modulation allowing downstream brain processing areas to perform dynamic readout of olfactory information.