The computer analogy of the mind has been as widely adopted in contemporary cognitive neuroscience as was the analogy of the brain as a collection of organs in phrenology. Just as the phrenologist ...would insist that each organ must have its particular function, so contemporary cognitive neuroscience is committed to the notion that each brain region must have its fundamental computation. InAfter Phrenology, Michael Anderson argues that to achieve a fully post-phrenological science of the brain, we need to reassess this commitment and devise an alternate, neuroscientifically grounded taxonomy of mental function. Anderson contends that the cognitive roles played by each region of the brain are highly various, reflecting different neural partnerships established under different circumstances. He proposes quantifying the functional properties of neural assemblies in terms of their dispositional tendencies rather than their computational or information-processing operations. Exploring larger-scale issues, and drawing on evidence from embodied cognition, Anderson develops a picture of thinking rooted in the exploitation and extension of our early-evolving capacity for iterated interaction with the world. He argues that the multidimensional approach to the brain he describes offers a much better fit for these findings, and a more promising road toward a unified science of minded organisms.
This book offers a provocative account of interdisciplinary research across the neurosciences, social sciences and humanities. Setting itself against standard accounts of interdisciplinary ...'integration,' and rooting itself in the authors' own experiences, the book establishes a radical agenda for collaboration across these disciplines. Rethinking Interdisciplinarity does not merely advocate interdisciplinary research, but attends to the hitherto tacit pragmatics, affects, power dynamics, and spatial logics in which that research is enfolded. Understanding the complex relationships between brains, minds, and environments requires a delicate, playful and genuinely experimental interdisciplinarity, and this book shows us how it can be done.
It is a crucial cognitive skill to select the relevant ones and exclude the irrelevant ones from all the stimuli we are exposed to in our constantly changing visual environment. While the ...long-standing early-late selection debates on the efficient attentional selection are still relevant, a hybrid theory was proposed by Lavie and Tsal (1994). Perceptual load theory is similar to the early selection approach in that it emphasizes limited capacity, while it is similar to late selection approaches in that it emphasizes automatic processing. In line with the theory, distractor processing depends on the task-relevant perceptual load. As perceptual load increases, unrelated stimuli can easily be excluded from the attention filter; because the capacity is full. The distractor interference effect is inevitable if the perceptual load is not high enough to fill the restricted capacity. According to the theory, the perceptual load is a key factor of the locus of selection. Although many support studies have been carried out after the theory was supposed, the number of studies inconsistent with the theory's assumptions, especially in recent years, cannot be ignored. Diverse studies have shown the importance of other factors in selective attention, such as salience, proximity, similarity, and dilution effect. In conclusion, despite being an important factor, the perceptual load is not the primary determinant in efficient attentional selection.
This book articulates an original scheme for the conceptualization of action. Beginning with a new approach to the individuation of acts, it delineates the relationships between basic and non-basic ...acts and uses these relationships in the definition of ability and intentional action. The author exhibits the central role of wants and beliefs in the causation of acts and in the analysis of the concept of action.
Professor Goldman suggests answers to fundamental questions about acts, and develops a set of ideas and principles that can be used in the philosophy of mind, the philosophy of language, ethics, and other fields, including the behavioral sciences.
Originally published in 1977.
ThePrinceton Legacy Libraryuses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These paperback editions preserve the original texts of these important books while presenting them in durable paperback editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.
There has been a recent resurgence in the area of explainable artificial intelligence as researchers and practitioners seek to provide more transparency to their algorithms. Much of this research is ...focused on explicitly explaining decisions or actions to a human observer, and it should not be controversial to say that looking at how humans explain to each other can serve as a useful starting point for explanation in artificial intelligence. However, it is fair to say that most work in explainable artificial intelligence uses only the researchers' intuition of what constitutes a ‘good’ explanation. There exist vast and valuable bodies of research in philosophy, psychology, and cognitive science of how people define, generate, select, evaluate, and present explanations, which argues that people employ certain cognitive biases and social expectations to the explanation process. This paper argues that the field of explainable artificial intelligence can build on this existing research, and reviews relevant papers from philosophy, cognitive psychology/science, and social psychology, which study these topics. It draws out some important findings, and discusses ways that these can be infused with work on explainable artificial intelligence.
The feeling that an imagined event will or will not occur in the future – referred to as
belief in future occurrence
– plays a key role in guiding our decisions and actions. Recent research suggests ...that this belief may increase with repeated simulation of future events, but the boundary conditions for this effect remain unclear. Considering the key role of autobiographical knowledge in shaping belief in occurrence, we suggest that the effect of repeated simulation only occurs when prior autobiographical knowledge does not clearly support or contradict the occurrence of the imagined event. To test this hypothesis, we investigated the repetition effect for events that were either plausible or implausible due to their coherence or incoherence with autobiographical knowledge (Experiment
1
), and for events that initially appeared uncertain because they were not clearly supported or contradicted by autobiographical knowledge (Experiment
2
). We found that all types of events became more detailed and took less time to construct after repeated simulation, but belief in their future occurrence increased only for uncertain events; repetition did not influence belief for events already believed or considered implausible. These findings show that the effect of repeated simulation on belief in future occurrence depends on the consistency of imagined events with autobiographical knowledge.
NeuroKit2 is an open-source, community-driven, and user-centered Python package for neurophysiological signal processing. It provides a comprehensive suite of processing routines for a variety of ...bodily signals (e.g., ECG, PPG, EDA, EMG, RSP). These processing routines include high-level functions that enable data processing in a few lines of code using validated pipelines, which we illustrate in two examples covering the most typical scenarios, such as an event-related paradigm and an interval-related analysis. The package also includes tools for specific processing steps such as rate extraction and filtering methods, offering a trade-off between high-level convenience and fine-tuned control. Its goal is to improve transparency and reproducibility in neurophysiological research, as well as foster exploration and innovation. Its design philosophy is centred on user-experience and accessibility to both novice and advanced users.
Race plays an important role in how people think, develop, and behave. In the current article, we queried more than 26,000 empirical articles published between 1974 and 2018 in top-tier cognitive, ...developmental, and social psychology journals to document how often psychological research acknowledges this reality and to examine whether people who edit, write, and participate in the research are systematically connected. We note several findings. First, across the past five decades, psychological publications that highlight race have been rare, and although they have increased in developmental and social psychology, they have remained virtually nonexistent in cognitive psychology. Second, most publications have been edited by White editors, under which there have been significantly fewer publications that highlight race. Third, many of the publications that highlight race have been written by White authors who employed significantly fewer participants of color. In many cases, we document variation as a function of area and decade. We argue that systemic inequality exists within psychological research and that systemic changes are needed to ensure that psychological research benefits from diversity in editing, writing, and participation. To this end, and in the spirit of the field’s recent emphasis on metascience, we offer recommendations for journals and authors.
Compression, the ability to recode information in a denser format, is a core property of working memory (WM). Previous studies have shown that the ability to compress information largely benefits WM ...performance. Importantly, recent evidence also suggests compression as freeing up WM resources, thus enhancing recall performance for other, less compressible information. Contrary to the traditional view positing that between-item similarity decreases WM performance, this study shows that between-item similarity can be used to free up WM resources through compression. Across a series of four experiments, we show that between-item similarity not only enhances recall performance for similar items themselves, but also for other, less compressible items within the same list, and this in the semantic (Experiment 1), phonological (Experiment 2), visuospatial (Experiment 3), and visual (Experiment 4) domains. Across these different domains, a consistent pattern of results emerged: between-item similarity proactively-but not retroactively-enhanced WM performance for other items, and this as compared with a condition in which between-item similarity at the whole-list level was minimized. We propose that between-item similarity in any domain may impact WM using the same underlying machinery: via a compression mechanism, which allows an efficient reallocation of WM resources.
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