Parallel distributed processing and neuropsychology: A neural network model of Wisconsin card sorting and verbal fluency

Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.     

Connectionist models of conditioning: A tutorial

Models containing networks of neuron-like units have become increasingly prominent in the study of both cognitive psychology and artificial intelligence. This article describes the basic features of connectionist models and provides an illustrative application to compound-stimulus effects in respondent conditioning. Connectionist models designed specifically for operant conditioning are not yet widely available, but some current learning algorithms for machine learning indicate that such models are feasible. Conversely, designers for machine learning appear to have recognized the value of behavioral principles in producing adaptive behavior in their creations.     

Character-Principlism and the Particularity Objection

This paper is a response to particularist critics of the normative force of moral principles. The particularist critique, as I understand it, is a rejection not only of principle-based accounts of moral deliberation and justification, but also of accounts of character in which principles play a central role. I focus on the latter challenge and counter it with a view I call character-principlism .
I begin by discussing in a general way what motivates the particularity objection to principles and then contrast two views – both of which insist on the importance of attentiveness to particularity – about the relative normative status of principles and particular cases. I present some reasons for believing that we need a more normatively robust conception of the role of moral principles than the particularists provide. In the main portion of the paper, I discuss how character-principlism sees principles functioning in our lives and the lives we lead with others. I contrast this with some other accounts of desirable character that particularists can embrace, and argue that these are seriously flawed because, unlike character-principlism, they cannot satisfactorily explain how a person could possess the constancy of character that moral integrity requires.     

An Ecologically Differentiated, Multifactor Model of Adolescent Network Orientation

The paper presents a test of an ecologically differentiated model of social network orientation for adolescents that distinguished between different social network reference groups (family, peers, and nonfamily adults). The model was tested in two consecutive studies. Study 1 describes initial model development (N = 120). Study 2 presents a confirmatory factor analysis with a second sample (N = 430) to replicate the factor structure developed in Study 1. Results supported a three-factor model of network orientation that differentiated between network reference groups. Analyses of concurrent and predictive validity indicated that orientation to network reference groups was differentially related to the perceived quality and frequency of support from members of respective social network groups. Group differences (gender, race) regarding network orientation to different network reference groups were consistent with studies of other social network processes. Implications for the study of the network orientation and the study of social networks more generally are discussed.     

Single-Stage Prediction Models Do Not Explain the Magnitude of Syntactic Disambiguation Difficulty

The disambiguation of a syntactically ambiguous sentence in favor of a less preferred parse can lead to slower reading at the disambiguation point. This phenomenon, referred to as a garden-path effect, has motivated models in which readers initially maintain only a subset of the possible parses of the sentence, and subsequently require time-consuming reanalysis to reconstruct a discarded parse. A more recent proposal argues that the garden-path effect can be reduced to surprisal arising in a fully parallel parser: words consistent with the initially dispreferred but ultimately correct parse are simply less predictable than those consistent with the incorrect parse. Since predictability has pervasive effects in reading far beyond garden-path sentences, this account, which dispenses with reanalysis mechanisms, is more parsimonious. Crucially, it predicts a linear effect of surprisal: the garden-path effect is expected to be proportional to the difference in word surprisal between the ultimately correct and ultimately incorrect interpretations. To test this prediction, we used recurrent neural network language models to estimate word-by-word surprisal for three temporarily ambiguous constructions. We then estimated the slowdown attributed to each bit of surprisal from human self-paced reading times, and used that quantity to predict syntactic disambiguation difficulty. Surprisal successfully predicted the existence of garden-path effects, but drastically underpredicted their magnitude, and failed to predict their relative severity across constructions. We conclude that a full explanation of syntactic disambiguation difficulty may require recovery mechanisms beyond predictability.     

The Role of Emotional Content and Perceptual Saliency During the Programming of Saccades Toward Faces

Previous studies have shown that the human visual system can detect a face and elicit a saccadic eye movement toward it very efficiently compared to other categories of visual stimuli. In the first experiment, we tested the influence of facial expressions on fast face detection using a saccadic choice task. Face-vehicle pairs were simultaneously presented and participants were asked to saccade toward the target (the face or the vehicle). We observed that saccades toward faces were initiated faster, and more often in the correct direction, than saccades toward vehicles, regardless of the facial expressions (happy, fearful, or neutral). We also observed that saccade endpoints on face images were lower when the face was happy and higher when it was neutral. In the second experiment, we explicitly tested the detection of facial expressions. We used a saccadic choice task with emotional-neutral pairs of faces and participants were asked to saccade toward the emotional (happy or fearful) or the neutral face. Participants were faster when they were asked to saccade toward the emotional face. They also made fewer errors, especially when the emotional face was happy. Using computational modeling, we showed that this happy face advantage can, at least partly, be explained by perceptual factors. Also, saccade endpoints were lower when the target was happy than when it was fearful. Overall, we suggest that there is no automatic prioritization of emotional faces, at least for saccades with short latencies, but that salient local face features can automatically attract attention.     

Refuting the unfolding-argument on the irrelevance of causal structure to consciousness

The unfolding argument (UA) was advanced as a refutation of prominent theories, which posit that phenomenal experience is determined by patterns of neural activation in a recurrent (neural) network (RN) structure. The argument is based on the statement that any input–output function of an RN can be approximated by an “equivalent” feedforward-network (FFN). According to UA, if consciousness depends on causal structure, its presence is unfalsifiable (thus non-scientific), as an equivalent FFN structure is behaviorally indistinguishable with regards to any behavioral test. Here I refute UA by appealing to computational theory and cognitive-neuroscience. I argue that a robust functional equivalence between FFN and RN is not supported by the mathematical work on the Universal Approximator theorem, and is also unlikely to hold, as a conjecture, given data in cognitive neuroscience; I argue that an equivalence of RN and FFN can only apply to static functions between input/output layers and not to the temporal patterns or to the network’s reactions to structural perturbations. Finally, I review data indicating that consciousness has functional characteristics, such as a flexible control of behavior, and that cognitive/brain dynamics reveal interacting top-down and bottom-up processes, which are necessary for the mediation of such control processes.     

Cognitive computing models for estimation of reference evapotranspiration: A review

Irrigation practices can be advanced by the aid of cognitive computing models. Repeated droughts, population expansion and the impact of global warming collectively impose rigorous restrictions over irrigation practices. Reference evapotranspiration (ET₀) is a vital factor to predict the crop water requirements based on climate data. There are many techniques available for the prediction of ET₀. An efficient ET₀ prediction model plays an important role in irrigation system to increase water productivity. In the present study, a review has been carried out over cognitive computing models used for the estimation of ET₀. Review exhibits that artificial neural network (ANN) approach outperforms support vector machine (SVM) and genetic programming (GP). Second order neural network (SONN) is the most promising approach among ANN models.     

Assessing Representations of Close Relationships Among Chinese and Japanese Adolescents and Young Adults: Commonalities and Differences in the Two Confucian Cultures

This article proposed an affective relationships model with its assessment instrument and examined how Chinese and Japanese adolescents and young adults construct mental representations of their close relationships, and the influence of Confucian cultural beliefs on these representations. The participants were 1,565 students aged 14 to 24 years living in China or Japan. The students were asked about their relationships with four figures: mother, father, closest friend, and romantic partner. We found that: (a) adolescents and young adults in both cultures constructed constellations of relationships containing multiple figures, and they articulated reasons for each figure's significance; and (b) there were between-group differences in the relationships with the father and the romantic partner for Chinese versus Japanese adolescents and young adults. These differences were partly explained by the influence of Confucianism on the Chinese participants’ cultural beliefs that retained the patriarchal values.