4,202 research outputs found

    Computational techniques to interpret the neural code underlying complex cognitive processes

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    Advances in large-scale neural recording technology have significantly improved the capacity to further elucidate the neural code underlying complex cognitive processes. This thesis aimed to investigate two research questions in rodent models. First, what is the role of the hippocampus in memory and specifically what is the underlying neural code that contributes to spatial memory and navigational decision-making. Second, how is social cognition represented in the medial prefrontal cortex at the level of individual neurons. To start, the thesis begins by investigating memory and social cognition in the context of healthy and diseased states that use non-invasive methods (i.e. fMRI and animal behavioural studies). The main body of the thesis then shifts to developing our fundamental understanding of the neural mechanisms underpinning these cognitive processes by applying computational techniques to ana lyse stable large-scale neural recordings. To achieve this, tailored calcium imaging and behaviour preprocessing computational pipelines were developed and optimised for use in social interaction and spatial navigation experimental analysis. In parallel, a review was conducted on methods for multivariate/neural population analysis. A comparison of multiple neural manifold learning (NML) algorithms identified that non linear algorithms such as UMAP are more adaptable across datasets of varying noise and behavioural complexity. Furthermore, the review visualises how NML can be applied to disease states in the brain and introduces the secondary analyses that can be used to enhance or characterise a neural manifold. Lastly, the preprocessing and analytical pipelines were combined to investigate the neural mechanisms in volved in social cognition and spatial memory. The social cognition study explored how neural firing in the medial Prefrontal cortex changed as a function of the social dominance paradigm, the "Tube Test". The univariate analysis identified an ensemble of behavioural-tuned neurons that fire preferentially during specific behaviours such as "pushing" or "retreating" for the animal’s own behaviour and/or the competitor’s behaviour. Furthermore, in dominant animals, the neural population exhibited greater average firing than that of subordinate animals. Next, to investigate spatial memory, a spatial recency task was used, where rats learnt to navigate towards one of three reward locations and then recall the rewarded location of the session. During the task, over 1000 neurons were recorded from the hippocampal CA1 region for five rats over multiple sessions. Multivariate analysis revealed that the sequence of neurons encoding an animal’s spatial position leading up to a rewarded location was also active in the decision period before the animal navigates to the rewarded location. The result posits that prospective replay of neural sequences in the hippocampal CA1 region could provide a mechanism by which decision-making is supported

    Linking language and emotion: how emotion is understood in language comprehension, production and prediction using psycholinguistic methods

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    Emotions are an integral part of why and how we use language in everyday life. We communicate our concerns, express our woes, and share our joy through the use of non-verbal and verbal language. Yet there is a limited understanding of when and how emotional language is processed differently to neutral language, or of how emotional information facilitates or inhibits language processing. Indeed, various efforts have been made to bring back emotions into the discipline of psycholinguistics in the last decade. This can be seen in many interdisciplinary models focusing on the role played by emotion in each aspect of linguistic experience. In this thesis, I answer this call and pursue questions that remain unanswered in psycholinguistics regarding its interaction with emotion. The general trend that I am using to bring emotion into psycholinguistic research is straightforward. Where applicable and relevant, I use well-established tasks or paradigms to investigate the effects of emotional content in language processing. Hence, I focused on three main areas of language processing: comprehension, production and prediction. The first experimental chapter includes a series of experiments utilising the Modality Switching Paradigm to investigate whether sentences describing emotional states are processed differently from sentences describing cognitive states. No switching effects were found consistently in my 3 experiments. My results suggest that these distinct classes of interoceptive concepts, such as ‘thinking’ or ‘being happy’, are not processed differently from each other, suggesting that people do not switch attention between different interoceptive systems when comprehending emotional or cognitive sentences. I discuss the implications for grounded cognition theory in the embodiment literature. In my second experimental chapter, I used the Cumulative Semantic Interference Paradigm to investigate these two questions: (1) whether emotion concepts interfere with one another when repeatedly retrieved (emotion label objects), and (2) whether similar interference occurs for concrete objects that share similar valence association (emotion-laden objects). This could indicate that people use information such as valence and arousal to group objects in semantic memory. I found that interference occurs when people retrieve direct emotion labels repeatedly (e.g., “happy” and “sad”) but not when they retrieve the names of concrete objects that have similar emotion connotations (e.g., “puppy” and “rainbow”). I discuss my findings in terms of the different types of information that support representation of abstract vs. concrete concepts. In my final experimental chapter, I used the Visual World Paradigm to investigate whether the emotional state of an agent is used to inform predictions during sentence processing. I found that people do use the description of emotional state of an agent (e.g., “The boy is happy”) to predict the cause of that affective state during sentence processing (e.g., “because he was given an ice-cream”). A key result here is that people were more likely to fixate on the emotionally congruent objects (e.g., ice-cream) compared to incongruent objects (e.g., broccoli). This suggests that people rapidly and automatically inform predictions about upcoming sentence information based on the emotional state of the agent. I discuss our findings as a novel contribution to the Visual World literature. I conducted a diverse set of experiments using a range of established psycholinguistic methods to investigate the roles of emotional information in language processing. I found clear results in the eye-tracking study but inconsistent effects in both switching and interference studies. I interpret these mixed findings in the following way: emotional content does not always have effects in language processing and that effect are most likely in tasks that explicitly require participants to simulate emotion states in some way. Regardless, not only was I successful in finding some novel results by extending previous tasks, but I was also able to show that this is an avenue that can be explored more to advance the affective psycholinguistic field

    Non-Market Food Practices Do Things Markets Cannot: Why Vermonters Produce and Distribute Food That\u27s Not For Sale

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    Researchers tend to portray food self-provisioning in high-income societies as a coping mechanism for the poor or a hobby for the well-off. They describe food charity as a regrettable band-aid. Vegetable gardens and neighborly sharing are considered remnants of precapitalist tradition. These are non-market food practices: producing food that is not for sale and distributing food in ways other than selling it. Recent scholarship challenges those standard understandings by showing (i) that non-market food practices remain prevalent in high-income countries, (ii) that people in diverse social groups engage in these practices, and (iii) that they articulate diverse reasons for doing so. In this dissertation, I investigate the persistent pervasiveness of non-market food practices in Vermont. To go beyond explanations that rely on individual motivation, I examine the roles these practices play in society. First, I investigate the prevalence of non-market food practices. Several surveys with large, representative samples reveal that more than half of Vermont households grow, hunt, fish, or gather some of their own food. Respondents estimate that they acquire 14% of the food they consume through non-market means, on average. For reference, commercial local food makes up about the same portion of total consumption. Then, drawing on the words of 94 non-market food practitioners I interviewed, I demonstrate that these practices serve functions that markets cannot. Interviewees attested that non-market distribution is special because it feeds the hungry, strengthens relationships, builds resilience, puts edible-but-unsellable food to use, and aligns with a desired future in which food is not for sale. Hunters, fishers, foragers, scavengers, and homesteaders said that these activities contribute to their long-run food security as a skills-based safety net. Self-provisioning allows them to eat from the landscape despite disruptions to their ability to access market food such as job loss, supply chain problems, or a global pandemic. Additional evidence from vegetable growers suggests that non-market settings liberate production from financial discipline, making space for work that is meaningful, playful, educational, and therapeutic. Non-market food practices mend holes in the social fabric torn by the commodification of everyday life. Finally, I synthesize scholarly critiques of markets as institutions for organizing the production and distribution of food. Markets send food toward money rather than hunger. Producing for market compels farmers to prioritize financial viability over other values such as stewardship. Historically, people rarely if ever sell each other food until external authorities coerce them to do so through taxation, indebtedness, cutting off access to the means of subsistence, or extinguishing non-market institutions. Today, more humans than ever suffer from chronic undernourishment even as the scale of commercial agriculture pushes environmental pressures past critical thresholds of planetary sustainability. This research substantiates that alternatives to markets exist and have the potential to address their shortcomings

    An embodied approach to informational interventions: using conceptual metaphors to promote sustainable healthy diets

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    Poor diet quality and environmental degradation are two major challenges of our times. Unhealthy and unsustainable dietary practices, such as the overconsumption of meat and consumer food waste behaviour, contribute greatly to both issues. Across seventeen online and field experiments, in two different cultures (US and China), this thesis investigates if the embodied cognition approach, and more specifically, research on conceptual metaphors, can be used to develop interventions to promote sustainable healthy diets. Interventions relying on conceptual metaphors have been shown to stimulate attitudinal and behavioural changes in other fields (e.g., marketing and political communications), but are rarely adopted to encourage sustainable healthy diets. To fill in this gap in the literature, I conducted five sets of experimental studies examining the effects of different metaphors on specific sustainable healthy dietary practices, each of which forms an independent empirical paper (Chapters 2-6 of the thesis). After introducing the current perspectives on embodied cognition and conceptual metaphors in the context of this research (Chapter 1), Chapter 2 looks into the conceptual metaphor “Healthy is Up”, demonstrating that US people implicitly associate healthiness with verticality, and offering recommendations for healthy eating guidelines. Chapter 3 extends this research to Chinese samples and partially replicates the results. Chapter 4 shows that the anthropomorphic metaphor “Animals are Friends” discourages meat consumption by inducing anticipatory guilt among US omnivores, whereas Chapter 5 reveals that Chinese omnivores are more responsive to another anthropomorphic metaphor, namely, “Animals are Family”. Bringing lab insights 6 to the real world, Chapter 6 demonstrates with a longitudinal field experiment that anthropomorphic metaphors together with environmental feedback result in a higher reduction in food waste as compared to other feedback interventions. The strengths, limitations and implications of those empirical papers are discussed in the conclusive part of the thesis

    Meta-critical thinking, paradox, and probabilities

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    There is as much lack of clarity concerning what “critical thinking” involves, even among those charged with teaching it, as there is consensus that we need more emphasis on it in both academia and society. There is an apparent need to think critically about critical thinking, an exercise that might be called meta-critical thinking. It involves emphasizing a practice in terms of which “critical thinking” is helpfully carried out and clarifying one or more of the concepts in terms of which “critical thinking” is usually defined. The practice is distinction making and the concept that of evidence. Science advances by constructing models that explain real-world processes. Once multiple potential models have been distinguished, there remains the task of identifying which models match the real-world process better than others. Since statistical inference has in large part to do with showing how data provide support, i.e., furnish evidence, that the model/hypothesis is more or less likely while still uncertain, we turn to it to help make the concept more precise and thereby useful. In fact, two of the leading methodological paradigms—Bayesian and likelihood—can be taken to provide answers to the questions of the extent to which as well as how data provide evidence for conclusions. Examining these answers in some detail is a highly promising way to make progress. We do so by way of the analysis of three well-known statistical paradoxes—the Lottery, the Old Evidence, and Humphreys’—and the identification of distinctions on the basis of which their plausible resolutions depend. These distinctions, among others between belief and evidence and different concepts of probability, in turn have more general applications. They are applied here to two highly contested public policy issues—the efficacy of COVID vaccinations and the fossil fuel cause of climate change. Our aim is to provide some tools, they might be called “healthy habits of mind,” with which to assess statistical arguments, in particular with respect to the nature and extent of the evidence they furnish, and to illustrate their use in well-defined ways

    Climate Change and Critical Agrarian Studies

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    Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    A Practical Introduction to Regression Discontinuity Designs: Extensions

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    This monograph, together with its accompanying first part Cattaneo, Idrobo and Titiunik (2020), collects and expands the instructional materials we prepared for more than 4040 short courses and workshops on Regression Discontinuity (RD) methodology that we taught between 2014 and 2022. In this second monograph, we discuss several topics in RD methodology that build on and extend the analysis of RD designs introduced in Cattaneo, Idrobo and Titiunik (2020). Our first goal is to present an alternative RD conceptual framework based on local randomization ideas. This methodological approach can be useful in RD designs with discretely-valued scores, and can also be used more broadly as a complement to the continuity-based approach in other settings. Then, employing both continuity-based and local randomization approaches, we extend the canonical Sharp RD design in multiple directions: fuzzy RD designs, RD designs with discrete scores, and multi-dimensional RD designs. The goal of our two-part monograph is purposely practical and hence we focus on the empirical analysis of RD designs

    Reducing Communication for Split Learning by Randomized Top-k Sparsification

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    Split learning is a simple solution for Vertical Federated Learning (VFL), which has drawn substantial attention in both research and application due to its simplicity and efficiency. However, communication efficiency is still a crucial issue for split learning. In this paper, we investigate multiple communication reduction methods for split learning, including cut layer size reduction, top-k sparsification, quantization, and L1 regularization. Through analysis of the cut layer size reduction and top-k sparsification, we further propose randomized top-k sparsification, to make the model generalize and converge better. This is done by selecting top-k elements with a large probability while also having a small probability to select non-top-k elements. Empirical results show that compared with other communication-reduction methods, our proposed randomized top-k sparsification achieves a better model performance under the same compression level.Comment: Accepted by IJCAI 202

    Balanced Allocations in Batches: The Tower of Two Choices

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    In balanced allocations, the goal is to place mm balls into nn bins, so as to minimize the gap (difference of max to average load). The One-Choice process places each ball to a bin sampled independently and uniformly at random. The Two-Choice process places balls in the least loaded of two sampled bins. Finally, the (1+β)(1+\beta)-process mixes these processes, meaning each ball is allocated using Two-Choice with probability β∈(0,1)\beta\in(0,1), and using One-Choice otherwise. Despite Two-Choice being optimal in the sequential setting, it has been observed in practice that it does not perform well in a parallel environment, where load information may be outdated. Following [BCEFN12], we study such a parallel setting where balls are allocated in batches of size bb, and balls within the same batch are allocated with the same strategy and based on the same load information. For small batch sizes b∈[n,nlog⁡n]b\in[n,n\log n], it was shown in [LS22a] that Two-Choice achieves an asymptotically optimal gap among all processes with a constant number of samples. In this work, we focus on larger batch sizes b∈[nlog⁡n,n3]b\in[n\log n,n^3]. It was proved in [LS22c] that Two-Choice leads to a gap of Θ(b/n)\Theta(b/n). As our main result, we prove that the gap reduces to O((b/n)⋅log⁡n)O(\sqrt{(b/n)\cdot\log n}), if one runs the (1+β)(1+\beta)-process with an appropriately chosen β\beta (in fact this result holds for a larger class of processes). This not only proves the phenomenon that Two-Choice is not the best (leading to the formation of "towers" over previously light bins), but also that mixing two processes (One-Choice and Two-Choice) leads to a process which achieves a gap that is asymptotically smaller than both. We also derive a matching lower bound of Ω((b/n)⋅log⁡n)\Omega(\sqrt{(b/n)\cdot\log n}) for any allocation process, which demonstrates that the above (1+β)(1+\beta)-process is asymptotically optimal.Comment: 36 pages;6 figures; 2 tables. arXiv admin note: text overlap with arXiv:2203.1390
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