Positive reinforcement and conditioned taste aversion induced by self-administered drugs : are they related?

The prevalence of alcohol, nicotine and caffeine place these substances among the most widely consumed in the world. Over the years studies have documented a strong positive relationship in the use of these drugs. Increasing attention within both the human and animal literature has been devoted to the study of the potential interactive effects between these recreational substances. The goal of this thesis was to examine the relationship between the positive reinforcing and conditioned taste aversion (CTA)-inducing properties of alcohol, caffeine and nicotine, and in so doing, to further elucidate the nature of the relationship between the phenomena of positive reinforcement and conditioned taste aversion. Experiments 1a-c and 2a-c showed that acetaldehyde, the putative reinforcing metabolite of ethanol may share common stimulus properties with nicotine and may also mediate the previously observed interaction between nicotine and ethanol in the preexposure CTA paradigm. Experiment 3 demonstrated that caffeine and nicotine shared common stimulus properties in the preexposure CTA procedure. Experiment 4 showed that mecamylamine, the nicotinic acetylcholine receptor antagonist, reversed the nicotine-induced attenuation of caffeine CTA and also blocked the formation of a caffeine-induced CTA. Experiments 5a and 5b demonstrated that caffeine facilitated the acquisition and maintenance of ethanol drinking in free feeding ethanol naïve animals. Experiments 5c and 5d revealed that the caffeine-induced elevation in ethanol drinking while unrelated to alteration in blood ethanol, might have been related to an increase in corticosterone. Experiments 6a-c showed that caffeine's facilitation of ethanol drinking might have resulted in an increase in the reinforcing efficacy of ethanol as reflected in CTA. Experiments 7a-c indicated that while locomotion responses to an inescapable novel environment appeared to be differentially related to the development of CTAs to amphetamine and morphine in rats it was unrelated to the expression of a LiCl induced CTA. Finally, the results of experiment 8 demonstrated a positive relationship between the amount of saccharin consumed orally and the expression of c-Fos -like immunoreactivity (FLI) in the Nucleus of the Solitary Tract suggesting that FLI may be more reactive to positive rather than aversive conditioning effects. Taken together, the studies reported here further shed light on the nature of the relationship between commonly co-used recreational substances and also support the hypothesis that the positively reinforcing and CTA inducing properties of self-administered drugs are indeed related and possibly governed by a shared neurobiological substrate

The interaction of psychomotor stimulants and sedative hypnotics in the conditioned taste aversion paradigm

Specific pairs of drugs such as cocaine and ethanol and nicotine and ethanol are widely used by humans. A variety of existing studies have reported behavioral and pharmacological interactive effects between these pairs of drugs. The present thesis was designed to further examine the potential interactive effects between these pairs of drugs as reflected in two variants of the Conditioned Taste Aversion (CTA) paradigm. Experiment 1 examined the potential for cocaine and ethanol to interact pharmacologically in the pretreatment CTA procedure. These results revealed that while cocaine and ethanol may interact pharmacologically, their interaction was asymmetrical and therefore not cocaethylene mediated. Experiment 2 examined the potential for nicotine and ethanol to interact pharmacologically in the pretreatment CTA procedure. These results demonstrated that nicotine and ethanol interacted pharmacologically in an asymmetrical fashion. Together, these pretreatment effects indicated a pharmacological specificity between pairs of drugs as reflected in their interaction. Experiments 3 and 4 were conducted in order to assess whether cocaine and ethanol as well as nicotine and ethanol were functionally related and endowed with overlapping stimulus properties as reflected in the pre-exposure CTA paradigm. These results demonstrated that both pairs of drugs were functionally related and endowed with overlapping but non-identical stimulus properties. That is, cocaine less effectively disrupted CTA to ethanol while ethanol more effectively disrupted CTA to cocaine. Similarly, nicotine effectively disrupted CTA to ethanol while ethanol less effectively disrupted CTA to nicotine. Taken together, these asymmetrical pre-exposure effects were thought to be related to the self-administration potential of these drugs

Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks

In this work, we reveal a strong implicit bias of stochastic gradient descent (SGD) that drives overly expressive networks to much simpler subnetworks, thereby dramatically reducing the number of independent parameters, and improving generalization. To reveal this bias, we identify invariant sets, or subsets of parameter space that remain unmodified by SGD. We focus on two classes of invariant sets that correspond to simpler (sparse or low-rank) subnetworks and commonly appear in modern architectures. Our analysis uncovers that SGD exhibits a property of stochastic attractivity towards these simpler invariant sets. We establish a sufficient condition for stochastic attractivity based on a competition between the loss landscape's curvature around the invariant set and the noise introduced by stochastic gradients. Remarkably, we find that an increased level of noise strengthens attractivity, leading to the emergence of attractive invariant sets associated with saddle-points or local maxima of the train loss. We observe empirically the existence of attractive invariant sets in trained deep neural networks, implying that SGD dynamics often collapses to simple subnetworks with either vanishing or redundant neurons. We further demonstrate how this simplifying process of stochastic collapse benefits generalization in a linear teacher-student framework. Finally, through this analysis, we mechanistically explain why early training with large learning rates for extended periods benefits subsequent generalization.Comment: 37 pages, 12 figures, NeurIPS 202

The Asymmetric Maximum Margin Bias of Quasi-Homogeneous Neural Networks

In this work, we explore the maximum-margin bias of quasi-homogeneous neural networks trained with gradient flow on an exponential loss and past a point of separability. We introduce the class of quasi-homogeneous models, which is expressive enough to describe nearly all neural networks with homogeneous activations, even those with biases, residual connections, and normalization layers, while structured enough to enable geometric analysis of its gradient dynamics. Using this analysis, we generalize the existing results of maximum-margin bias for homogeneous networks to this richer class of models. We find that gradient flow implicitly favors a subset of the parameters, unlike in the case of a homogeneous model where all parameters are treated equally. We demonstrate through simple examples how this strong favoritism toward minimizing an asymmetric norm can degrade the robustness of quasi-homogeneous models. On the other hand, we conjecture that this norm-minimization discards, when possible, unnecessary higher-order parameters, reducing the model to a sparser parameterization. Lastly, by applying our theorem to sufficiently expressive neural networks with normalization layers, we reveal a universal mechanism behind the empirical phenomenon of Neural Collapse.Comment: 33 pages, 5 figure

Photodissociation dynamics of the iodide-uracil (I-U) complex

Photofragment action spectroscopy and femtosecond time-resolved photoelectron imaging are utilized to probe the dissociation channels in iodide-uracil (I− ⋅ U) binary clusters upon photoexcitation. The photofragment action spectra show strong I− and weak [U- H]− ion signal upon photoexcitation. The action spectra show two bands for I− and [U- H]− production peaking around 4.0 and 4.8 eV. Time-resolved experiments measured the rate of I− production resulting from excitation of the two bands. At 4.03 eV and 4.72 eV, the photoelectron signal from I− exhibits rise times of 86 ± 7 ps and 36 ± 3 ps, respectively. Electronic structure calculations indicate that the lower energy band, which encompasses the vertical detachment energy (4.11 eV) of I−U, corresponds to excitation of a dipole-bound state of the complex, while the higher energy band is primarily a π-π∗ excitation on the uracil moiety. Although the nature of the two excited states is very different, the long lifetimes for I− production suggest that this channel results from internal conversion to the I− ⋅ U ground state followed by evaporation of I−. This hypothesis was tested by comparing the dissociation rates to Rice-Ramsperger-Kassel-Marcus calculations

A method for the objective selection of landscape-scale study regions and sites at the national level

1. Ecological processes operating on large spatio-temporal scales are difficult to disentangle with traditional empirical approaches. Alternatively, researchers can take advantage of ‘natural’ experiments, where experimental control is exercised by careful site selection. Recent advances in developing protocols for designing these ‘pseudo-experiments’ commonly do not consider the selection of the focal region and predictor variables are usually restricted to two. Here, we advance this type of site selection protocol to study the impact of multiple landscape scale factors on pollinator abundance and diversity across multiple regions. 2. Using datasets of geographic and ecological variables with national coverage, we applied a novel hierarchical computation approach to select study sites that contrast as much as possible in four key variables, while attempting to maintain regional comparability and national representativeness. There were three main steps to the protocol: (i) selection of six 100 9 100 km2 regions that collectively provided land cover representative of the national land average, (ii) mapping of potential sites into a multivariate space with axes representing four key factors potentially influencing insect pollinator abundance, and (iii) applying a selection algorithm which maximized differences between the four key variables, while controlling for a set of external constraints. 3. Validation data for the site selection metrics were recorded alongside the collection of data on pollinator populations during two field campaigns. While the accuracy of the metric estimates varied, the site selection succeeded in objectively identifying field sites that differed significantly in values for each of the four key variables. Between-variable correlations were also reduced or eliminated, thus facilitating analysis of their separate effects. 4. This study has shown that national datasets can be used to select randomized and replicated field sites objectively within multiple regions and along multiple interacting gradients. Similar protocols could be used for studying a range of alternative research questions related to land use or other spatially explicit environmental variables, and to identify networks of field sites for other countries, regions, drivers and response taxa in a wide range of scenarios