Biology subjects

Miller, R.

Publications and source records attributed to Miller, R..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Social influences on delayed gratification in New Caledonian crows and Eurasian jays

Self-control underlies goal-directed behaviour in humans and other animals. Delayed gratification - a measure of self-control - requires the ability to tolerate a delay and/or invest more effort to obtain a reward of higher value over one of lower value, such as food or mates. Social context, in particular, the presence of competitors, may influence delayed gratification. We adapted the rotating-tray paradigm, where subjects need to forgo an immediate, lower-quality (i.e. less preferred) reward for a delayed, higher-quality (i.e. more preferred) one, to test social influences on delayed gratification in two corvid species: New Caledonian crows and Eurasian jays. We compared choices for immediate vs. delayed rewards while alone, in the presence of a competitive conspecific and in the presence of a non-competitive conspecific. We found that species differed: jays were more likely to select the immediate, less preferred reward than the crows. We also found that jays were more likely to select the immediate, less preferred reward when a competitor or non-competitor was present than when alone, or when a competitor was present compared to a non- competitor, while the crows selected the delayed, highly preferred reward irrespective of social presence. We discuss our findings in relation to species differences in socio-ecological factors (adult sociality and food caching) and wider implications of social influences on self-control.

animal behavior and cognition↗

bioRxiv2023

Intra-Articular Sprouting Of Nociceptors Accompanies Progressive Osteoarthritis: Comparative Evidence In Four Murine Models

ObjectiveKnee joints are densely innervated by nociceptors. Sprouting of nociceptors has been reported in late-stage osteoarthritis (OA), both in human knees and in rodent models. Here, we sought to describe progressive nociceptor remodeling in four mouse models of knee OA, capturing early and late-stage disease. MethodsSham surgery, destabilization of the medial meniscus (DMM), partial meniscectomy (PMX), or non-invasive anterior cruciate ligament rupture (ACLR) was performed in the right knee of 10-12-week old male C57BL/6 NaV1.8-tdTomato mice. Mice were euthanized (1) 4, 8 or 16 weeks after DMM or sham surgery; (2) 4 or 12 weeks after PMX or sham; (3) 1 or 4 weeks after ACLR injury or sham. Additionally, a cohort of naive male wildtype mice was evaluated at 6 and 24 months. Twenty-m thick mid-joint cryosections were assessed qualitatively and quantitatively for NaV1.8+ and PGP9.5+ innervation. Cartilage damage (using a modified OARSI score), synovitis, and osteophytes were assessed blindly. ResultsProgressive OA developed in the medial compartment after DMM, PMX, and ACLR. Synovitis and associated neo-innervation by nociceptors peaked in early-stage OA. In the subchondral bone, channels containing sprouting nociceptors appeared early, and progressed with worsening joint damage. Two-year old mice developed primary OA in both the medial and the lateral compartment, accompanied with neuroplasticity in the synovium and the subchondral bone. All 4 models had an increased nerve signal in osteophytes. ConclusionAnatomical neuroplasticity of nociceptors was observed in association with joint damage in 4 distinct mouse models, suggesting that it is intrinsic to OA pathology.

neuroscience↗

bioRxiv2023

Extended Nucleic Acid (exNA): A Novel, Biologically Compatible Backbone that Significantly Enhances Oligonucleotide Efficacy in vivo

Metabolic stabilization of therapeutic oligonucleotides requires both sugar and backbone modifications, where phosphorothioate (PS) is the only backbone chemistry used in the clinic. Here, we describe the discovery, synthesis, and characterization of a novel biologically compatible backbone, extended nucleic acid (exNA). Upon exNA precursor scale up, exNA incorporation is fully compatible with common nucleic acid synthetic protocols. The novel backbone is orthogonal to PS and shows profound stabilization against 3- and 5-exonucleases. Using small interfering RNAs (siRNAs) as an example, we show exNA is tolerated at most nucleotide positions and profoundly improves in vivo efficacy. A combined exNA-PS backbone enhances siRNA resistance to serum 3-exonuclease by [~]32-fold over PS backbone and >1000-fold over the natural phosphodiester backbone, thereby enhancing tissue exposure ([~]6-fold), tissues accumulation (4- to 20-fold), and potency both systemically and in brain. The improved potency and durability imparted by exNA opens more tissues and indications to oligonucleotide-driven therapeutic interventions.

biochemistry↗

bioRxiv2023

A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis

Machine learning methods have frequently been applied to electroencephalography (EEG) data. However, while supervised EEG classification is well-developed, relatively few studies have clustered EEG, which is problematic given the potential for clustering EEG to identify novel subtypes or patterns of dynamics that could improve our understanding of neuropsychiatric disorders. There are established methods for clustering EEG using manually extracted features that reduce the richness of the feature space for clustering, but only a couple studies have sought to use deep learning-based approaches with automated feature learning to cluster EEG. Those studies involve separately training an autoencoder and then performing clustering on the extracted features, and the separation of those steps can lead to poor quality clustering. In this study, we propose an explainable convolutional autoencoder-based approach that combines model training with clustering to yield high quality clusters. We apply the approach within the context of schizophrenia (SZ), identifying 8 EEG states characterized by varying levels of {delta} activity. We also find that individuals who spend more time outside of the dominant state tend to have increased negative symptom severity. Our approach represents a significant step forward for clustering resting-state EEG data and has the potential to lead to novel findings across a variety of neurological and neuropsychological disorders in future years.

neuroscience↗

bioRxiv2022

Motion Impact Score for Detecting Spurious Brain-Behavior Associations

Between-participant differences in head motion introduce systematic bias to resting state fMRI brain-wide association studies (BWAS) that is not completely removed by denoising algorithms. Researchers who study traits, or phenotypes associated with in-scanner head motion (e.g. psychiatric disorders) need to know if trait-functional connectivity (FC) effects are biased by residual motion artifact in order to avoid reporting false positive results. We devised an adaptable method, Split Half Analysis of Motion Associated Networks (SHAMAN), to assign a motion impact score to specific trait-FC effects. The SHAMAN approach distinguishes between motion artifact causing overestimation or underestimation of trait-FC effects. SHAMAN was > 95% specific at sample sizes of n = 100 and above. SHAMAN was powered to detect motion overestimation scores 80% of the time at sample sizes of n = 5,000 but could detect motion underestimation scores only 50% of the time at n = 5000, making it most useful for researchers seeking to avoid overestimating trait-FC effects in large BWAS. We computed motion impact scores for trait-FC effect with 45 demographic, biophysical, cognitive, and personality traits from n = 7,270 participants in the Adolescent Brain Cognitive Development (ABCD) Study. After standard denoising with ABCD-BIDS and without motion censoring, 42% (19/45) of traits had significant (p < 0.05) motion overestimation scores and 38% (17/45) of traits had significant motion underestimation scores. Censoring at framewise displacement (FD) < 0.2 mm reduced the proportion of traits with significant motion overestimation scores from 42% to 2% (1/45) but did not decrease the number of traits with significant motion underestimation scores.

neuroscience↗

bioRxiv2022

Sexual dimorphism of the synovial transcriptome underpins greater PTOA disease severity in male mice following joint injury

ObjectiveTo elucidate sex differences in synovitis, mechanical sensitization, structural damage, bone remodeling, and the synovial transcriptome in the anterior cruciate ligament rupture (ACLR) mouse model of post-traumatic osteoarthritis (PTOA). MethodsMale and female 12-week-old C57Bl/6 mice were randomized to noninvasive ACLR or sham (n=9/sex/group/timepoint). Knee hyperalgesia, mechanical allodynia, and intra-articular MMP activity (via intravital imaging) were measured longitudinally. Trabecular and subchondral bone remodeling and osteophyte formation were assessed by CT. Histological scoring of PTOA and synovitis and anti-MMP13 immunostaining was performed. NaV1.8-Cre;tdTomato mice were used to document localization and sprouting of nociceptors. Bulk RNAseq of synovium in sham, 7d, and 28d post-ACLR, and contralateral joints (n=6) assessed injury-induced and sex-dependent synovial gene expression. ResultsMale mice exhibited worse joint damage at 7d and 28d and worse synovitis at 28d, accompanied by greater MMP activity, knee hyperalgesia, and mechanical allodynia. Females had catabolic responses in trabecular and subchondral bone after injury, whereas males exhibited greater osteophyte formation and sclerotic remodeling of trabecular and subchondral bone. NaV1.8+ nociceptor sprouting in subchondral bone and medial synovium was induced by injury and comparable between sexes. RNAseq of synovium demonstrated that both sexes had similar injury-induced gene expression at 7d, but only female mice exhibited synovial inflammatory resolution by 28d, whereas males had persistent pro-inflammatory, pro-fibrotic, pro-neurogenic, and pro-angiogenic gene expression. ConclusionWorse overall joint pathology and pain behavior in male mice was associated with persistent activation of synovial inflammatory, fibrotic, and neuroangiogenic processes, implicating persistent synovitis in driving sex differences in murine PTOA.

physiology↗

bioRxiv2022

From Pigs to Silkworms: Cognition and Welfare across 10 Farmed Taxa

Billions of animals across many taxa are extensively farmed, with critical impacts on animal welfare. Societal efforts to reduce animal suffering lack rigorous and systematic approaches that facilitate maximising welfare improvements, such as informed funding allocation decisions. We present a multi-measure, cross-taxa framework for modelling differences in pain, suffering, and related cognition to assess whether certain animals have larger welfare ranges (how well or badly animals can fare). Measures include behavioural flexibility, cognitive sophistication, and general learning. We evaluated 90 empirically detectable proxies for cognition and welfare range (henceforth proxies) in pigs, chickens, carp, salmon, octopus, shrimp, crabs, crayfish, bees, and silkworms. We grouped a subset of proxies into: A) 10 ideal proxies and B) 10 less ideal proxies but with sufficient data for interspecies comparisons. We graded the strength of evidence per proxy across taxa, and constructed a cognition and welfare range profile, with overall judgement scores (ranging from likely no/low confidence to yes/very high confidence). We discuss the implications of comparisons and highlight key avenues for future research. This work is timely, given recent indications of significant political will towards reducing animal suffering, such as the inclusion of cephalopods and decapods in the Animal Welfare (Sentience) Bill following a UK government-commissioned research review. Given the novelty and robustness of our review, we believe it sets a new standard for investigating interspecies comparisons of cognition and welfare ranges and helps inform future research. This should help streamline funding allocations and improve the welfare of millions of farmed animals. Graphical/ Visual Abstract and Caption O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY Cognition and welfare in farmed animals - from pigs to silkworms (Free stock images: http://www.pixabay.com) C_FIG_DISPLAY

animal behavior and cognition↗

bioRxiv2022

AssemblyTron: Flexible automation of DNA assembly with Opentrons OT-2 lab robots

As one of the newest fields of engineering, synthetic biology relies upon a trial-and-error Design-Build-Test-Learn approach to simultaneously learn how function is encoded in biology and attempt to engineer it. Many software and hardware platforms have been developed to automate, optimize, and algorithmically perform each step of the Design-Build-Test-Learn cycle. However, there are many fewer options for automating the Build step. Build typically involves DNA assembly, which remains manual, low throughput, and unreliable in most cases, limiting our ability to advance the science and engineering of biology. Here, we present AssemblyTron: an open-source python package to integrate j5 DNA assembly design software outputs with build implementation in Opentrons liquid handling robotics with minimal human intervention. We demonstrate the versatility of AssemblyTron through several scarless, multipart DNA assemblies beginning from fragment amplification. We show that AssemblyTron can perform PCRs across a range of fragment lengths and annealing temperatures by using an optimal annealing temperature gradient calculation algorithm. We then demonstrate that AssemblyTron can perform Golden Gate and homology-dependent in vivo assemblies with comparable fidelity to manual assemblies by simultaneously building four four-fragment assemblies of chromoprotein reporter expression plasmids. Finally, we used AssemblyTron to perform site-directed mutagenesis reactions via homology-dependent in vivo assembly also achieving comparable fidelity to manual assemblies as assessed by sequencing. AssemblyTron can reduce the time, training, costs, and wastes associated with synthetic biology, which along with open-source and affordable automation, will further foster the accessibility of synthetic biology and accelerate biological research and engineering.

synthetic biology↗

bioRxiv2022

Inline SAXS-coupled chromatography under extreme hydrostatic pressure

As continuing discoveries highlight the surprising abundance and resilience of deep ocean and subsurface microbial life, the effects of extreme hydrostatic pressure on biological structure and function have attracted renewed interest. Biological small angle X-ray scattering (BioSAXS) is a widely used method of obtaining structural information from biomolecules in solution under a wide range of solution conditions. Due to its ability to reduce radiation damage, remove aggregates, and separate monodisperse components from complex mixtures, size-exclusion chromatography coupled SAXS (SEC-SAXS) is now the dominant form of BioSAXS at many synchrotron beamlines. While BioSAXS can currently be performed with some difficulty under pressure with non-flowing samples, it has not been clear how, or even if, continuously flowing SEC-SAXS, with its fragile media-packed columns, might work in an extreme high-pressure environment. Here we show, for the first time, that reproducible chromatographic separations coupled directly to high-pressure BioSAXS can be achieved at pressures up to at least 100 MPa and that pressure-induced changes in folding and oligomeric state and other properties can be observed. The apparatus described here functions at a range of temperatures (0{degrees} C - 50{degrees} C), expanding opportunities for understanding biomolecular rules of life in deep ocean and subsurface environments.

biophysics↗

bioRxiv2022

Chemical engineering of therapeutic siRNAs for allele-specific gene silencing in vivo in CNS

Small interfering RNAs (siRNAs) are a new class of drugs, exhibiting sequence-driven, potent, and sustained silencing of gene expression in vivo. We recently demonstrated that siRNA chemical architectures can be optimized to provide efficient delivery to the CNS. Many genetically-defined neurodegenerative disorders are autosomal dominant favoring selective silencing of the mutant allele. In some cases, successful targeting of the mutant allele requires targeting of a single nucleotide polymorphism (SNP) heterozygosity. Using Huntingtons disease as a model, we demonstrate allele-specific RNAi-based silencing of gene expression in vivo and in neurons differentiated from HD patient-derived iPSCs. A series of in vitro screens, with chemical and thermodynamic optimization, identified compounds with >50-fold selectivity for the mutant HD-causing allele, based on a single nucleotide difference. The optimized compound exhibits selective silencing of mutant huntingtin (HTT) protein in patient derived cells and throughout the HD mouse brain, providing a demonstration of SNP-based allele-specific RNAi silencing of gene expression in vivo in the CNS. The ability to target a disease-causing allele using RNAi-based therapies could be applied to a wide range of dominant CNS disorders, where maintenance of wild-type expression is essential.

neuroscience↗

bioRxiv2022

Activity of Tricyclic Pyrrolopyrimidine Gyrase B Inhibitor against Mycobacterium abscessus

Tricyclic pyrrolopyrimidines (TPPs) are a new class of antibacterials inhibiting the ATPase of DNA gyrase. TPP8, a representative of this class, is active against Mycobacterium abscessus in vitro. Spontaneous TPP8 resistance mutations mapped to the ATPase domain of M. abscessus DNA gyrase and the compound inhibited DNA supercoiling activity of recombinant M. abscessus enzyme. Further profiling of TPP8 in macrophage and mouse infection studies demonstrated proof-of-concept activity against M. abscessus ex vivo and in vivo.

microbiology↗

bioRxiv2022

iSparse kmeans: a two-step clustering approach for big dynamic functional network connectivity data

BackgroundDynamic functional network connectivity (dFNC) estimated from resting-state functional magnetic imaging (rs-fMRI) studies the temporally varying of functional integration between brain networks. In a typical dFNC pipeline, a clustering stage to summarize the connectivity patterns that are transiently but reliably realized over the course of a scanning session. However, identifying the right number of clusters through a conventional clustering criterion computed by running the algorithm repeatedly, over a large range of cluster numbers is time-consuming and requires substantial computational power even for typical dFNC datasets, and the computational demands become prohibitive as datasets become larger and scans longer. Here we developed a new dFNC pipeline, called iterative sparse kmeans or iSparse kmeans, to analyze large dFNC data without having access to huge computational power. MethodIn iSparse kmeans, we implement two-step clustering. In the first step, we randomly use a sub-sample dFNC data and identify several sets of states at different model orders. In the second step, we aggregate all dFNC states estimated from all iterations in the first step and use this to identify the optimum number of clusters using the elbow criteria. Additionally, we use this new reduced dataset and estimate a final set of states by performing a second kmeans clustering on the aggregated dFNC states from the first k-means clustering. To validate the reproducibility of iSparse kmeans, we analyzed four dFNC datasets from the human connectome project (HCP). ResultsWe found that both conventional kmeans and iSparse kmeans generate similar brain dFNC states while iSparse kmeans is 27 times faster than the traditional method in finding the optimum number of clusters. We show that the results are replicated across four different datasets from HCP. ConclusionWe developed a new analytic pipeline which facilitates analysis of large dFNC datasets without having access to a huge computational power source. We validated the reproducibility of the result across multiple datasets.

bioinformatics↗

bioRxiv2022

A Pan-Pneumovirus vaccine based on immunodominant epitopes of the fusion protein

Respiratory syncytial virus (RSV) and human metapneumovirus (hMPV) are two leading causes of severe respiratory infections in children, the elderly, and immunocompromised patients. The fusion (F) protein is the major target of neutralizing antibodies. Recent developments in stabilizing the pre-fusion conformation of the F proteins, and identifying immunodominant epitopes that elicit potent neutralizing antibodies have led to testing of numerous pre-fusion RSV F-based vaccines in clinical trials. We designed and tested the immunogenicity and protective efficacy of a chimeric fusion protein that contains immunodominant epitopes of RSV F and hMPV F (RHMS-1). RHMS-1 has several advantages over vaccination with pre-fusion RSV F or hMPV F, including a focus on recalling B cells to the most important protective epitopes and the ability to induce protection against two viruses with a single antigen. RHMS-1 was generated as a trimeric recombinant protein, and negative-stain EM analysis demonstrated the protein resembles the pre-fusion conformation. Probing of RHMS-1 antigenicity using a panel of RSV and hMPV F-specific monoclonal antibodies (mAbs) revealed the protein retains features of both viruses, including the pre-fusion site O epitope of RSV F. BALB/c mice immunized with RHMS-1 had serum binding and neutralizing antibodies to both viruses. RHMS-1 vaccinated mice challenged with RSV or hMPV had undetectable virus in lung homogenates for both viruses, in contrast to RSV F or hMPV F vaccinated mice, which had detectable virus for hMPV and RSV, respectively. Overall, this study demonstrates protection against two viruses with a single antigen and supports further testing of RHMS-1 in additional pre-clinical animal models. SignificanceRespiratory syncytial virus (RSV) and human metapneumovirus (hMPV) are two Pneumoviruses that cause substantial respiratory tract infections in young children, the elderly, and immunocompromised adults. Yet vaccines against either of them are still unavailable. Multiple promising vaccine designs based on the fusion proteins of RSV and hMPV have been tested, but none of them can induce cross-protective antibody responses despite their similar structures and closely related amino acid sequence identity. Here, we report a vaccine candidate, RHMS-1, which combines the immunodominant epitopes of the RSV and hMPV fusion proteins into a single antigen. RHMS-1 maintains the immunological features of both RSV F and hMPV F, which can be recognized by epitope-specific mAbs and human B cells pre-exposed to RSV or hMPV. Furthermore, this is the first immunogen that induced potent cross-neutralizing antibodies and protected mice from RSV and hMPV challenge. Our results suggest RHMS-1 is a promising Pan-Pneumovirus vaccine.

immunology↗

bioRxiv2021

Neophobia and innovation in critically endangered Bali myna, Leucopsar rothschildi

Cognition underlies animal behaviour, which is key to successful conservation strategies, yet largely under-utilised in conservation, though there are recent calls for closer integration. Conservation-relevant cognitive abilities can impact on adaptability and survival, such as neophobia, e.g., responses to novelty, and innovation e.g., problem-solving, particularly in todays changing world. Bali myna are a critically endangered endemic species, which are a focus of active conservation efforts, including reintroductions. Therefore, gathering cognitive data can aid in improving and developing conservation strategies, like pre-release training and individual selection for release. In 22 captive Bali myna, we tested neophobia (novel object, novel food, control conditions), innovation (bark, cup, lid conditions) and individual repeatability. We found effects of condition and social environment, including longer latencies to touch familiar food in presence than absence of novel items, and between problem-solving tasks, as well as in the presence of conspecifics, compared with being alone, or with conspecifics and competing heterospecifics. Individuals were repeatable in latency responses: 1) temporally in both experiments; 2) contextually in innovation experiment and between both experiments (and approach order), suggesting a stable behaviour trait. These findings are an important starting point for improving conservation strategies in Bali myna and other similarly threatened species.

animal behavior and cognition↗

bioRxiv2021

Individual repeatability, species differences, and the influence of socio-ecological factors on neophobia in 10 corvid species

Behavioural responses to novelty, including fear and subsequent avoidance of novel stimuli, behaviours referred to as neophobia, determine how animals interact with their environment. Neophobia aids in navigating risk and impacts on adaptability and survival. There is variation within and between individuals and species, however, lack of large-scale, comparative studies critically limits investigation of the socio-ecological drivers of neophobia. In this study, we tested responses to novel objects and food (alongside familiar food) versus a baseline (familiar food alone) in 10 corvid species (241 subjects) across 10 labs worldwide. There were species differences in the latency to touch familiar food in the novel object and food conditions relative to the baseline. Three of seven socio-ecological factors influenced object neophobia: 1) use of urban habitat (vs not), 2) territorial pair vs family group sociality and 3) large vs small flock size (whereas range, caching, hunting live animals, and genus did not); while only flock size influenced food neophobia. We found that, overall, individuals were temporally and contextually repeatable (i.e. consistent) in their novelty responses in all conditions, indicating neophobia is a stable behavioural trait. With this study, we have established a network of corvid researchers, demonstrating potential for further collaboration to explore the evolution of cognition in corvids and other bird species. These novel findings enable us, for the first time in corvids, to identify the socio-ecological correlates of neophobia and grant insight into specific elements that drive higher neophobic responses in this avian family group.

animal behavior and cognition↗

bioRxiv2021

Human Fronto-Striatal Connectivity is Organized into Discrete Functional Subnetworks

The striatum is interconnected with the cerebral cortex via multiple recurrent loops that play a major role in many neuropsychiatric conditions. Primate cortico-striatal connections can be precisely mapped using invasive tract-tracing. However, noninvasive human research has not mapped these connections with anatomical precision, limited by the practice of averaging neuroimaging data across individuals. Here we utilized highly-sampled resting-state functional connectivity MRI for individually-specific precision functional mapping of cortico-striatal connections. We identified ten discrete, individual-specific subnetworks linking cortex--predominately frontal cortex--to striatum. These subnetworks included previously unknown striatal connections to the human language network. The discrete subnetworks formed a stepped rostral-caudal gradient progressing from nucleus accumbens to posterior putamen; this organization was strongest for projections from medial frontal cortex. The stepped gradient organization fit patterns of fronto-striatal connections better than a smooth, continuous gradient. Thus, precision subnetworks identify detailed, individual-specific stepped gradients of cortico-striatal connectivity that include human-specific language networks.

neuroscience↗

bioRxiv2021

Precision Diffusion Imaging

Diffusion tensor imaging (DTI) aims to non-invasively characterize the anatomy and integrity of the brains white matter fibers. To establish individual-specific precision approaches for DTI, we defined its reliability and accuracy as a function of data quantity and analysis method, using both simulations and highly sampled individual-specific data (927-1442 diffusion weighted images [DWIs] per individual). DTI methods that allow for crossing fibers (BedpostX [BPX], Q-Ball Imaging [QBI]) estimated excess fibers when insufficient data was present and when the data did not match the model priors. To reduce such overfitting, we developed a novel crossing-fiber diffusion imaging method, Bayesian Multi-tensor Model-selection (BaMM), that is designed for high-quality repeated sampling data sets. BaMM was robust to overfitting, showing high reliability and the relatively best crossing-fiber accuracy with increasing amounts of diffusion data. Thus, the choice of diffusion imaging analysis method is important for the success of individual-specific diffusion imaging. Importantly, for potential clinical applications of individual-specific precision DTI, such as deep brain stimulation (DBS), other forms of neuromodulation or neurosurgical planning, the data quantities required to achieve DTI reliability are lower than for functional MRI measures.

neuroscience↗

bioRxiv2020

Inactivation of posterior but not anterior dorsomedial caudate-putamen impedes learning with self-administered nicotine stimulus

The rodent caudate-putamen is a large heterogeneous neural structure with distinct anatomical connections that differ in their control of learning processes. Previous research suggests that the anterior and posterior dorsomedial caudate-putamen (a- and p-dmCPu) differentially regulate associative learning with a non-contingent nicotine stimulus. The current study used bilateral NMDA-induced excitotoxic lesions to the a-dmCPu and p-dmCPu to determine the functional involvement of a-dmCPu and p-dmCPu in appetitive learning with contingent nicotine stimulus. Rats with a-dmCPu, p-dmCPu, or sham lesions were trained to lever-press for intravenous nicotine (0.03 mg/kg/inf) followed by access to sucrose 30 s later. After 1, 3, 9, and 20 nicotine-sucrose training sessions, appetitive learning in the form of a goal-tracking response was assessed using a non-contingent nicotine-alone test. All rats acquired nicotine self-administration and learned to retrieve sucrose from a receptacle at equal rates. However, rats with lesions to p-dmCPu demonstrated blunted learning of the nicotine-sucrose association. Our primary findings show that rats with lesions to p-dmCPu had a blunted goal-tracking response to a non-contingent nicotine administration after 20 consecutive days of nicotine-sucrose pairing. Our findings extend previous reports to a contingent model of nicotine self-administration and show that p-dmCPu is involved in associative learning with nicotine stimulus using a paradigm where rats voluntarily self-administer nicotine infusions that are paired with access to sucrose--a paradigm that closely resembles learning processes observed in humans.

animal behavior and cognition↗