Hegel: Death of God and Recognition of the Self

Abstract

This paper covers the theme of the death of God considered from a Hegelian standpoint. For Aristotle, the image of God as ‘thought thinking itself’ was an image of the knowledge aspired to in philosophy. With the notion of God becoming man and his insistence on the icon of the Cross, Hegel challenged the Aristotelian goal of philosophy as immutable knowledge of an ‘ultimate’ reality. Hegel viewed the crisis of normativity (the death of the Cartesian divine guarantor) as strictly linked to the conception of the self. It is Nietzsche who is best known for alluding to the full significance of this image for modern life, but Hegel’s thought on the complex relations of philosophy and religion in the modern world can be regarded as an attempt to think through this same historical phenomenon. In this paper, I focus on the philosophical relevance of Hegel’s notion of the death of God. I argue that unpacking the significance of the ‘truths’ presented symbolically in modern Christianity is crucial in understanding the requirements that an idealistic philosophy must meet.     

Change Detection Without Awareness: Do Explicit Reports Underestimate the Representation of Change in the Visual System?

Evidence from many different paradigms (e.g. change blindness, inattentional blindness, transsaccadic integration) indicate that observers are often very poor at reporting changes to their visual environment. Such evidence has been used to suggest that the spatio-temporal coherence needed to represent change can only occur in the presence of focused attention. In four experiments we use modified change blindness tasks to demonstrate (a) that sensitivity to change does occur in the absence of awareness, and (b) this sensitivity does not rely on the redeployment of attention. We discuss these results in relation to theories of scene perception, and propose a reinterpretation of the role of attention in representing change.     

The effect of multiple indicators on the power to detect inter‐individual differences in change

Hertzog et al. evaluated the statistical power of linear latent growth curve models (LGCMs) to detect individual differences in change, i.e., variances of latent slopes, as a function of sample size, number of longitudinal measurement occasions, and growth curve reliability. We extend this work by investigating the effect of the number of indicators per measurement occasion on power. We analytically demonstrate that the positive effect of multiple indicators on statistical power is inversely related to the relative magnitude of occasion‐specific latent residual variance and is independent of the specific model that constitutes the observed variables, in particular of other parameters in the LGCM. When designing a study, researchers have to consider trade‐offs of costs and benefits of different design features. We demonstrate how knowledge about power equivalent transformations between indicator measurement designs allows researchers to identify the most cost‐efficient research design for detecting parameters of interest. Finally, we integrate different formal results to exhibit the trade‐off between the number of measurement occasions and number of indicators per occasion for constant power in LGCMs.     

Critical issues in psychological autopsy studies

This paper reviews research based on the psychological autopsy (PA) method applied to the study of suicide. It evidences the presence of a number of methodological problems. Shortcomings concern sampling biases in the selection of control subjects, confounding influences of extraneous variables, and reliability of the assessment instruments. The absence of homogeneity among studies in the procedure employed, as well as the lack of defined guidelines for performing this type of inquiry are emphasized. Questions needing empirical investigation in the future are pointed out. It is concluded that the validity and reliability of findings emerging from the use of this method of investigation would benefit from a standardization of its application.     

Anxiety selectively disrupts visuospatial working memory

On the basis of a review of the extant literature describing emotion-cognition interactions, the authors propose 4 methodological desiderata for studying how task-irrelevant affect modulates cognition and present data from an experiment satisfying them. Consistent with accounts of the hemispheric asymmetries characterizing withdrawal-related negative affect and visuospatial working memory (WM) in prefrontal and parietal cortices, threat-induced anxiety selectively disrupted accuracy of spatial but not verbal WM performance. Furthermore, individual differences in physiological measures of anxiety statistically mediated the degree of disruption. A second experiment revealed that individuals characterized by high levels of behavioral inhibition exhibited more intense anxiety and relatively worse spatial WM performance in the absence of threat, solidifying the authors' inference that anxiety causally mediates disruption. These observations suggest a revision of extant models of how anxiety sculpts cognition and underscore the utility of the desiderata.     

From models to rules: mechanization of reasoning as a way to cope with cognitive overloading in combinatorial problems

It is hypothesized that the transition from unfamiliar problems to familiar, well-learned problems coincides with the transition from a model-based style of reasoning to a rule-based style of reasoning; model-based style of reasoning helps understanding the problem structure, but can overload working memory when the number of models required increases; rule-based style of reasoning avoids cognitive overloading, at the cost of making individuals liable to mechanization errors. In Experiment 1, the number of models required to respond to a verification task affected response latencies with unfamiliar problems, but not with familiar problems, supporting the initial hypothesis. In Experiment 2, participants were prone to mechanization errors when confronted with slightly modified problems in the late stages of the experiment, supporting the hypothesis that they had developed a reasoning rule in the early stages and were blindly applying it. The findings suggest that model-based reasoning and rule-based reasoning serve different purposes and have different costs and benefits, are both available to human reasoners, and familiarization with a problem may induce the transition from the former to the latter. The findings also suggest that mechanization of reasoning may be the first step along a gradient of decreasing cognitive load, whose end-point is automatization, as discussed in theories of automatization of information processing.     

Coordinate high-frequency pattern of stimulation and calcium levels control the induction of LTP in striatal cholinergic interneurons

Current evidence appoints a central role to cholinergic interneurons in modulating striatal function. Recently, a long-term potentiation (LTP) of synaptic transmission has been reported to occur in these neurons. The relationship between the pattern of cortico/thalamostriatal fibers stimulation, the consequent changes in the intracellular calcium concentration ([Ca2+]i), and the induction of synaptic plasticity was investigated in striatal cholinergic interneurons from a rat corticostriatal slice preparation by means of combined electrophysiological intracellular recordings and microfluorometric techniques. Different protocols of stimulation were considered, varying both the frequency and the duration of the train of stimuli. High-frequency stimulation (HFS) (three trains at 100 Hz for 3 sec, 20-sec interval) induced a rise in [Ca2+]i, exceeding by fivefold the resting level, and caused a LTP of synaptic transmission. Tetanic stimulation delivered at lower frequencies (5-30 Hz) failed to induce long-term changes of synaptic efficacy. The observed elevation in [Ca2+]i during HFS was primarily mediated by L-type high-voltage activated (HVA)-Ca2+ channels, as it was fully prevented by nifedipine. Conversely, blockade of NMDA and AMPA glutamate receptor did not affect either LTP or the magnitude of the [Ca2+]i rise. Interestingly, the pharmacological analysis of the post-tetanic depolarizing postsynaptic potential (DPSP) revealed that LTP was attributable, to a large extent, to the potentiation of the GABA(A)-mediated component. In conclusion, the expression of LTP in striatal cholinergic interneurons is a selective response to a precise stimulation pattern of induction requiring a critical rise in [Ca2+]i.     

Selective attention, inhibition for repeated events and hemispheric specialization

When two visual events appear consecutively in the same spatial location, our response to the second event is slower than to the first. This inhibition for repeated events may reflect a bias toward sampling novel locations, a bias useful for exploring visual space. It has been shown that the left hemisphere is more specialized in selective attentional processes than the right one. The aim of the present experiment was to test if this hemispheric specialization for selective attention may also affect the inhibition for repeated events. For this purpose, we asked 11 normal subjects to perform an identity-based discrimination task in which the target to be detected could appear alone or surrounded by flanking letters, in the left or in the right visual field. Results show that inhibition for repeated events is present only when selective attention is required and when the task is performed in the right specialized visual field.     

Learning first-pass structural attachment preferences with dynamic grammars and recursive neural networks

One of the central problems in the study of human language processing is ambiguity resolution: how do people resolve the extremely pervasive ambiguity of the language they encounter? One possible answer to this question is suggested by experience-based models, which claim that people typically resolve ambiguities in a way which has been successful in the past. In order to determine the course of action that has been "successful in the past" when faced with some ambiguity, it is necessary to generalize over past experience. In this paper, we will present a computational experience-based model, which learns to generalize over linguistic experience from exposure to syntactic structures in a corpus. The model is a hybrid system, which uses symbolic grammars to build and represent syntactic structures, and neural networks to rank these structures on the basis of its experience. We use a dynamic grammar, which provides a very tight correspondence between grammatical derivations and incremental processing, and recursive neural networks, which are able to deal with the complex hierarchical structures produced by the grammar. We demonstrate that the model reproduces a number of the structural preferences found in the experimental psycholinguistics literature, and also performs well on unrestricted text.     

Proof-Theoretic Modal PA-Completeness I: A System-Sequent Metric

This paper is the first of a series of three articles that present the syntactic proof of the PA-completeness of the modal system G, by introducing suitable proof-theoretic objects, which also have an independent interest. We start from the syntactic PA-completeness of modal system GL-LIN, previously obtained in [7], [8], and so we assume to be working on modal sequents S which are GL-LIN-theorems. If S is not a G-theorem we define here a notion of syntactic metric d(S, G): we calculate a canonical characteristic fomula H of S (char(S)) so that _G H (S) and _GL-LIN H, and the complexity of H gives the distance d(S, G) of S from G. Then, in order to produce the whole completeness proof as an induction on this d(S, G), we introduce the tree-interpretation of a modal sequent Q into PA, that sends the letters of Q into PA-formulas describing the properties of a GL-LIN-proof P of Q: It is also a d(*, G)-metric linked interpretation, since it will be applied to a proof-tree T of H with H = char(S) and ( H) = d(S, G).