This chapter focuses on evidence from functional magnetic resonance imaging data, and discusses the application of neuroimaging techniques to various fields, including cognitive sciences. It considers the role of neuroimaging data in providing informative evidence regarding hypotheses in cognitive science, and explains differences in data, high-level null hypotheses, and ways to accommodate null hypotheses. Finally, the chapter looks into the scope of neuroimaging data in the cognitive sciences.

The party registration of tenure‐track faculty at 11 California universities, ranging from small, private, religiously affiliated institutions to large, public, elite schools, shows that the “one‐party campus” conjecture does not extend to all institutions or all departments. At one end of the scale, U.C. Berkeley has an adjusted Democrat:Republican ratio of almost 9:1, while Pepperdine University has a ratio of nearly 1:1. Academic field also makes a tremendous difference, with the humanities averaging a 10:1 D:R ratio and business schools averaging (...) 1.3:1, and with departments ranging from sociology (44:1) to management (1.5:1). Across all departments and institutions, the D:R ratio is 5:1, while in the “soft” liberal‐arts fields, the ratio is higher than 8:1. These findings are generally in line with comparable previous studies. (shrink)

We demonstrate that an unlexicalized PCFG can parse much more accurately than previously shown, by making use of simple, linguistically motivated state splits, which break down false independence assumptions latent in a vanilla treebank grammar. Indeed, its performance of 86.36% (LP/LR F1) is better than that of early lexicalized PCFG models, and surprisingly close to the current state-of-theart. This result has potential uses beyond establishing a strong lower bound on the maximum possible accuracy of unlexicalized models: an unlexicalized PCFG is (...) much more compact, easier to replicate, and easier to interpret than more complex lexical models, and the parsing algorithms are simpler, more widely understood, of lower asymptotic complexity, and easier to optimize. (shrink)

Culturally different connotations of basic concepts challenge the comparative study of religion. Do persons in Germany or in the United States refer to the same concepts when talking about ‘spirituality’ and ‘religion’? Does it make a difference how they identify themselves? The Bielefeld-Chattanooga Cross-Cultural Study on ‘Spirituality’ includes a semantic differential approach for the comparison of self-identified “neither religious nor spiritual”, “religious”, and “spiritual” persons regarding semantic attributes attached to the concepts ‘religion’ and ‘spirituality’ in each research context. Results show (...) that ‘spirituality’ is used as a broader concept than ‘religion’. Regarding religion, semantics attributed by self-identified religious persons differ significantly from those of the spiritual persons. The ‘spiritual’ and the ‘religious’ groups agree on semantics attributed to spirituality but differ from the ‘neither spiritual nor religious’ group. Qualifications of differences and agreements become visible from the comparison between the United States and Germany. It is argued for the semantically sensitive study of culturally situated ‘spiritualities’. (shrink)

We present a novel generative model for natural language tree structures in which semantic (lexical dependency) and syntactic (PCFG) structures are scored with separate models. This factorization provides conceptual simplicity, straightforward opportunities for separately improving the component models, and a level of performance comparable to similar, non-factored models. Most importantly, unlike other modern parsing models, the factored model admits an extremely effective A* parsing algorithm, which enables efficient, exact inference.

This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according to generative PCFG models. In contrast, we employ a simpler probabilistic model over trees based directly on constituent identity and linear context, and use an EM-like iterative procedure to induce structure. This method produces much higher quality analyses, giving the best published results on the ATIS dataset.

We present a generative distributional model for the unsupervised induction of natural language syntax which explicitly models constituent yields and contexts. Parameter search with EM produces higher quality analyses than previously exhibited by unsupervised systems, giving the best published unsupervised parsing results on the ATIS corpus. Experiments on Penn treebank sentences of comparable length show an even higher F1 of 71% on nontrivial brackets. We compare distributionally induced and actual part-of-speech tags as input data, and examine extensions to the basic (...) model. We discuss errors made by the system, compare the system to previous models, and discuss upper bounds, lower bounds, and stability for this task. (shrink)

We agree that external validity of social psychological experiments is a concern, we disagree these models are useless. Experiments, reconsidered from a situated cognition perspective and non-linearly combined with other methods allow grasping decision dynamics beyond bias outcomes. Dynamic insights regarding these processes are key to understand missing forces and bias in real-world social groups.

Name der Zeitschrift: Zeitschrift für Religionswissenschaft Jahrgang: 24 Heft: 1 Seiten: 47-82.

This paper presents empirical studies and closely corresponding theoretical models of the performance of a chart parser exhaustively parsing the Penn Treebank with the Treebank’s own CFG grammar. We show how performance is dramatically affected by rule representation and tree transformations, but little by top-down vs. bottom-up strategies. We discuss grammatical saturation, including analysis of the strongly connected components of the phrasal nonterminals in the Treebank, and model how, as sentence length increases, the effective grammar rule size increases as regions (...) of the grammar are unlocked, yielding super-cubic observed time behavior in some configurations. (shrink)

This paper separates conditional parameter estima- tion, which consistently raises test set accuracy on statistical NLP tasks, from conditional model struc- tures, such as the conditional Markov model used for maximum-entropy tagging, which tend to lower accuracy. Error analysis on part-of-speech tagging shows that the actual tagging errors made by the conditionally structured model derive not only from label bias, but also from other ways in which the independence assumptions of the conditional model structure are unsuited to linguistic sequences. The (...) paper presents new word-sense disambiguation and POS tagging experiments, and integrates apparently conflicting reports from other recent work. (shrink)

Name der Zeitschrift: Zeitschrift für Religionswissenschaft Jahrgang: 23 Heft: 1 Seiten: 3-34.

Das Wiskott-Aldrich-Syndrom (WAS), ein genetisch bedingter Immundefekt mit klinischer Manifestation im Kleinkindalter, wird voraussichtlich in näherer Zukunft erstmals versuchsweise durch eine somatische Gentherapie behandelt werden. Im vor- liegenden Beitrag werden die wichtigsten medizinisch-naturwissenschaftlichen Fakten dieses Krankheitsbildes sowie die bisherigen Erfahrungen mit somatischen Gentherapien bei anderen Immunmangelsyndromen ausführlich dargestellt. Sodann erfolgt eine ethische Analyse eines möglichen gentherapeutischen Eingriffs bei WAS-Patienten, bei der die spezifischen Aspekte des Wiskott-Aldrich-Syndroms – insbesondere die fast ausschließliche Betroffenheit von Kindern sowie die unterschiedlich aussichtsreiche Alter- nativoption einer (...) allogenen Knochenmarktransplantation–wesentliche Aspekte der Beurteilung sind. Im Ergebnis zeigt sich, dass ein gentherapeutischer Eingriff im vorliegenden Fall nicht im Rahmen einer Forschungsstudie, d.h. als Humanexperiment, gerechtfertigt werden kann, sondern allein als individueller Heilversuch. Gleichwohl las- sen die besonderen Risiken und die Innovativität eines solchen Eingriffs es notwendig erscheinen, diesen Heilversuch – anders als andere Heilbehandlungen mit bislang unerprobten Mitteln – in streng kontrollierter Form durchzuführen. Der neuartige Gedanke eines kontrollierten individuellen Heilversuchs zeichnet sich daher für den vorliegenden Fall, und womöglich auch für vergleichbare risikoreiche Behandlungsansätze namentlich im Bereich der Gentherapie, als geeignetes Instrument der Konzeption und Beurteilung ab. (shrink)

While Ç ´Ò¿ µ methods for parsing probabilistic context-free grammars (PCFGs) are well known, a tabular parsing framework for arbitrary PCFGs which allows for botton-up, topdown, and other parsing strategies, has not yet been provided. This paper presents such an algorithm, and shows its correctness and advantages over prior work. The paper finishes by bringing out the connections between the algorithm and work on hypergraphs, which permits us to extend the presented Viterbi (best parse) algorithm to an inside (total probability) (...) algorithm. (shrink)

A* PCFG parsing can dramatically reduce the time required to find the exact Viterbi parse by conservatively estimating outside Viterbi probabilities. We discuss various estimates and give efficient algorithms for computing them. On Penn treebank sentences, our most detailed estimate reduces the total number of edges processed to less than 3% of that required by exhaustive parsing, and even a simpler estimate which can be pre-computed in under a minute still reduces the work by a factor of 5. The algorithm (...) extends the classic A* graph search procedure to a certain hypergraph associated with parsing. Unlike bestfirst and finite-beam methods for achieving this kind of speed-up, the A* parser is guaranteed to return the most likely parse, not just an approximation. The algorithm is also correct for a wide range of parser control strategies and maintains a worst-case cubic time bound. (shrink)

This paper discusses ensembles of simple but heterogeneous classifiers for word-sense disambiguation, examining the Stanford-CS224N system entered in the SENSEVAL-2 English lexical sample task. First-order classifiers are combined by a second-order classifier, which variously uses majority voting, weighted voting, or a maximum entropy model. While individual first-order classifiers perform comparably to middle-scoring teams’ systems, the combination achieves high performance. We discuss trade-offs and empirical performance. Finally, we present an analysis of the combination, examining how ensemble performance depends on error independence (...) and task difficulty. (shrink)

Unsupervised grammar induction systems commonly judge potential constituents on the basis of their effects on the likelihood of the data. Linguistic justifications of constituency, on the other hand, rely on notions such as substitutability and varying external contexts. We describe two systems for distributional grammar induction which operate on such principles, using part-of-speech tags as the contextual features. The advantages and disadvantages of these systems are examined, including precision/recall trade-offs, error analysis, and extensibility.

We present an improved method for clustering in the presence of very limited supervisory information, given as pairwise instance constraints. By allowing instance-level constraints to have spacelevel inductive implications, we are able to successfully incorporate constraints for a wide range of data set types. Our method greatly improves on the previously studied constrained -means algorithm, generally requiring less than half as many constraints to achieve a given accuracy on a range of real-world data, while also being more robust when over-constrained. (...) We additionally discuss an active learning algorithm which increases the value of constraints even further. (shrink)

erative clustering. First, we show formally that the common heuristic agglomerative clustering algorithms – Ward’s method, single-link, complete-link, and a variant of group-average – are each equivalent to a hierarchical model-based method. This interpretation gives a theoretical explanation of the empirical behavior of these algorithms, as well as a principled approach to resolving practical issues, such as number of clusters or the choice of method. Second, we show how a model-based viewpoint can suggest variations on these basic agglomerative algorithms. We (...) introduce adjusted complete-link, Mahalanobis-link, and line-link as variants, and demonstrate their utility. (shrink)

While symbolic parsers can be viewed as deduction systems, this view is less natural for probabilistic parsers. We present a view of parsing as directed hypergraph analysis which naturally covers both symbolic and probabilistic parsing. We illustrate the approach by showing how a dynamic extension of Dijkstra’s algorithm can be used to construct a probabilistic chart parser with an Ç´Ò¿µ time bound for arbitrary PCFGs, while preserving as much of the flexibility of symbolic chart parsers as allowed by the inherent (...) ordering of probabilistic dependencies. (shrink)

Name der Zeitschrift: Zeitschrift für Religionswissenschaft Jahrgang: 23 Heft: 1 Seiten: 1-2.

Recently, an associative learning account of cognitive control has been suggested (Verguts & Notebaert, 2009). In this so-called adaptation by binding theory, Hebbian learning of stimulus–stimulus and stimulus–response associations is assumed to drive the adaptation of human behavior. In this study, we evaluated the validity of the adaptation-by-binding account for the case of implicit learning of regularities within a stimulus set (i.e., the frequency of specific unit digit combinations in a two-digit number magnitude comparison task) and their association with a (...) particular response. Our data indicated that participants indeed learned these regularities and adapted their behavior accordingly. In particular, influences of cognitive control were even able to override the numerical distance effect—one of the most robust effects in numerical cognition research. Thus, the general cognitive processes involved in two-digit number magnitude comparison seem much more complex than previously assumed. Multi-digit number magnitude comparison may not be automatic and inflexible but influenced by processes of cognitive control being highly adaptive to stimulus set properties and task demands on multiple levels. (shrink)

Name der Zeitschrift: Zeitschrift für Religionswissenschaft Jahrgang: 25 Heft: 2 Seiten: 181-195.

Culturally different connotations of basic concepts challenge the comparative study of religion. Do persons in Germany or in the United States refer to the same concepts when talking about ‘spirituality’ and ‘religion’? Does it make a difference how they identify themselves? The Bielefeld-Chattanooga Cross-Cultural Study on ‘Spirituality’ includes a semantic differential approach for the comparison of self-identified “neither religious nor spiritual”, “religious”, and “spiritual” persons regarding semantic attributes attached to the concepts ‘religion’ and ‘spirituality’ in each research context. Results show (...) that ‘spirituality’ is used as a broader concept than ‘religion’. Regarding religion, semantics attributed by self-identified religious persons differ significantly from those of the spiritual persons. The ‘spiritual’ and the ‘religious’ groups agree on semantics attributed to spirituality but differ from the ‘neither spiritual nor religious’ group. Qualifications of differences and agreements become visible from the comparison between the United States and Germany. It is argued for the semantically sensitive study of culturally situated ‘spiritualities’. (shrink)

Ben Taskar Dan Klein Michael Collins Computer Science Dept. Computer Science Dept. CS and AI Lab Stanford University Stanford University.