Neuroimaging and neuromodulation of preclinical models of substance use disorders

National Institute On Drug Abuse

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Abstract

1. Compulsive drug-taking is associated with habenula-frontal cortex connectivity As a critical node connecting forebrain with midbrain, the lateral habenula (LHb) processes negative feedback in response to aversive events and plays an essential role in value-based decision-making. Compulsive drug use, a hallmark of substance use disorder, is attributed to maladaptive decision-making regarding aversive drug-use-related events and has been associated with dysregulation of various frontal-midbrain circuits. To understand the contributions of frontal-habenula-midbrain circuits in the development of drug dependence, we employed a rat model of methamphetamine self-administration (SA) in the presence of concomitant footshock, which has been proposed to model compulsive drug-taking in humans. In this longitudinal study, functional MRI data were collected at pretraining baseline, after 20 days of long-access SA phase, and after 5 days of concomitant footshock coupled with SA (punishment phase). Individual differences in response to punishment were quantified by a compulsivity index (CI), defined as drug infusions at the end of punishment phase, normalized by those at the end of SA phase. Functional connectivity of LHb with frontal cortices and substantia nigra (SN) after the punishment phase was positively correlated with the CI in rats that maintained drug SA despite receiving increasing intensity footshock. In contrast, functional connectivity of the same circuits was negatively correlated with CI in rats that significantly reduced methamphetamine SA. These findings suggest that individual differences in compulsive drug-taking are reflected by alterations within frontal-LHb-SN circuits after experiencing the negative consequences from SA, suggesting these circuits may serve as novel biomarkers and potential therapeutic targets for individualized treatment of addiction. (Duan et al., PNAS, 2022) 2. Recognition memory is associated with different patterns of regional gray matter volumes in young and aged monkeys Cognitive aging varies tremendously across individuals and is often accompanied by regionally specific reductions in gray matter (GM) volume, even in the absence of disease. Rhesus monkeys provide a primate model unconfounded by advanced neurodegenerative disease, and the current study used a recognition memory test (delayed non-matching to sample; DNMS) in conjunction with structural imaging and voxel-based morphometry (VBM) to characterize age-related differences in GM volume and brain-behavior relationships. Consistent with expectations from a long history of neuropsychological research, DNMS performance in young animals prominently correlated with the volume of multiple structures in the medial temporal lobe memory system. Less anticipated correlations were also observed in the cingulate and cerebellum. In aged monkeys, significant volumetric correlations with DNMS performance were largely restricted to the prefrontal cortex and striatum. Importantly, interaction effects in an omnibus analysis directly confirmed that the associations between volume and task performance in the MTL and prefrontal cortex are age-dependent. These results demonstrate that the regional distribution of GM volumes coupled with DNMS performance changes across the lifespan, consistent with the perspective that the aged primate brain retains a substantial capacity for structural reorganization. (Cooper et al., Cerebral Cortex, 2022) 3. Longitudinal track of whole brain developmental changes in the adolescent brain of rats Approximately half of all mental health disorders are manifest during adolescence, a critical period for the development of long-term cognitive and affective processes and mental health. Adolescent development is a non-linear transition between the juvenile and adult brain, characterized by profound changes in brain structure and connectivity. However, such dynamic developmental changes are difficult to study longitudinally in humans and are typically studied cross-sectionally. Animal models in contrast offer the unique opportunity to longitudinally track whole brain developmental changes in the adolescent brain. Functional magnetic resonance imaging (fMRI) allows for interrogation of systems-levels functional connectvivity and is a unique translational tool given that the blood-oxygen level-dependent (BOLD) signal is based upon the same biophysical principles measured across species. Here, we acquired whole-brain resting state functional connectivity (rsFC) at four time points separated by two weeks in both adolescent (beginning at post-natal day 33) and adult (beginning at PND 68) male Sprague-Dawley rats and identified large-scale networks that changed as a function of starting age (adolescent vs adult) and scanning session. Using the Network Based Statistic (NBS) analytical method in combination with data-driven, k-means clustering, we characterized these circuits as those that strengthened as compared to those that weakened in connectivity strength across development. Using a Rich Club network classification, hub-hub connections (in contrast with peripheral (non-hub to non-hub) or feeder (hub to non-hub connections)) were disproportionately represented among those circuits that strengthened over adolescence, including notably the hippocampus and frontal cortex. In contrast, insular peripheral and feeder circuits weakened throughout this developmental epoch. Together, these data offer a framework for understanding adolescent brain development in a preclinical model and help inform analyses of ongoing longitudinal studies (e.g. the Adolescent Brain and Cognitive Development (ABCD) study) in adolescent humans as well as provide a platform to interrogate how and which of these networks are susceptible to developmental insults, such as adolescent drug use and early life stress. (Manuscript in preparation) 4. High inductance magnetic-core coils have enhanced efficiency in inducing suprathreshold motor response in rats Transcranial magnetic stimulation (TMS) coil design involves a delicate tradeoff among multiple parameters, including magnetic field strength (H) per unit electric current, inductance (L), focality, penetration depth, and coil heating, etc. Magnetic core has been suggested to enhance coil efficiency, although coils with magnetic cores generally have relatively higher inductance values than their air-core counterparts. Our lab reported a rodent-specific TMS coil that employed silicon-steel magnetic core, achieving a focality of about 2 mm. We have recently constructed several rodent TMS coils with inductance ranging from 35.1 to 74.5 H. The coil with an inductance of 74.5 H generated the highest magnetic field per unit current. Somewhat to our surprise, it was also most efficient in inducing suprathreshold motor response in rats. The aim of this study is to better understand this phenomenon. Both linear and non-linear analyses were performed. With the introduction of magnetic core, the induced E field is the summation of the primary field E_p generated by coil windings and the secondary field E_s by the magnetic core. The high relative permeability (r) of silicon steel substantially changed the E field dynamics during a TMS pulse. Both linear and non-linear analyses revealed that coils with higher inductance also had stronger peak E fields and longer E field waveform w(t). On a macroscopic scale, the effects of these two factors on neuronal membrane potential (and thus neuronal firing) could be conceptually explained through convolution of w(t) with neuronal membrane impulse response function h(t). In conclusion, both theoretical analyses and experimental data reveal that the coil inductance can be much higher than previously anticipated if the magnetic materials have a high saturation threshold. (Manuscript under review)