In the past two decades or so, a number of researchers from various fields within linguistics have turned their attention to interpersonal phenomena, such as the linguistic expression of speaker opinion or evaluation , or the encoding of subjectivity in language and its diachronic development . Many linguists have offered categorizations of evaluative meaning, based on authentic discourse data, but no connection has been made with cognitive approaches to appraisal processes. This paper offers a first meta-theoretical exploration of such issues. (...) It compares dimensions of evaluation that have been identified in linguistic and cognitive studies, and also examines how psychological research into basic emotions can be related to linguistic research on affect. On the basis of these comparisons a proposal for a new classification of evaluative meanings is made. The focus of this paper is on only one aspect of the highly complex phenomenon of evaluation, namely potential evaluative dimensions, although other relevant issues will also be touched upon, including the pragmatics of evaluation. (shrink)

There is some complementarity of models for the origin of the electroencephalogram (EEG) and neural network models for information storage in brainlike systems. From the EEG models of Freeman, of Nunez, and of the authors' group we argue that the wavelike processes revealed in the EEG exhibit linear and near-equilibrium dynamics at macroscopic scale, despite extremely nonlinear – probably chaotic – dynamics at microscopic scale. Simulations of cortical neuronal interactions at global and microscopic scales are then presented. The simulations depend (...) on anatomical and physiological estimates of synaptic densities, coupling symmetries, synaptic gain, dendritic time constants, and axonal delays. It is shown that the frequency content, wave velocities, frequency/wavenumber spectra and response to cortical activation of the electrocorticogram (ECoG) can be reproduced by a “lumped” simulation treating small cortical areas as single-function units. The corresponding cellular neural network simulation has properties that include those of attractor neural networks proposed by Amit and by Parisi. Within the simulations at both scales, sharp transitions occur between low and high cell firing rates. These transitions may form a basis for neural interactions across scale. To maintain overall cortical dynamics in the normal low firing-rate range, interactions between the cortex and the subcortical systems are required to prevent runaway global excitation. Thus, the interaction of cortex and subcortex via corticostriatal and related pathways may partly regulate global dynamics by a principle analogous to adiabatic control of artificial neural networks. (shrink)

According to the dominant computational approach in cognitive science, cognitive agents are digital computers; according to the alternative approach, they are dynamical systems. This target article attempts to articulate and support the dynamical hypothesis. The dynamical hypothesis has two major components: the nature hypothesis (cognitive agents are dynamical systems) and the knowledge hypothesis (cognitive agents can be understood dynamically). A wide range of objections to this hypothesis can be rebutted. The conclusion is that cognitive systems may well be dynamical systems, (...) and only sustained empirical research in cognitive science will determine the extent to which that is true. (shrink)

Long neglected as a focus of linguistic research, evaluation in its various guises is now being recognized as a crucial aspect of any study of discourse. In this book, writers coming from different standpoints are brought together, providing a unique profile of the topic from several perspectives. These perspectives include: Systemic Linguistics, Narrative, Corpus Linguistics, and Discourse Analysis.