Jamie Wright

According to a venerable tradition in philosophy and linguistics, expressions have meaning through being subject to conventions or rules. This claim has become a central topic of contemporary philosophy of language and mind in the wake of Wittgenstein and Kripke, largely because the normativity of meaning is regarded as a serious challenge to naturalism. One reaction to this challenge is to deny that the normativity of meaning is genuine. While there are ‘semantic principles’ specifying conditions for the correct application of expressions, these are either not genuinely normative or they are not in fact constitutive of meaning. But this dilemma can be defused if one distinguishes different dimensions of semantic normativity and pays attention to different types of mistakes that can afflict linguistic behavior. In particular, one needs to keep apart norms of truth and norms of meaning, regulative, and constitutive rules, and to appreciate the normative dimensions of the notion of correctness. The final section discusses the role of communally shared rules or conventions for language, in particular the age-old problem of circularity: how could such conventions be essential to language, given that the latter appears prerequisite for establishing and communicating conventions in the first place.

We outline fresh findings that show that our macroscopic electrocorticographic (ECoG) simulations can account for synchronous multiunit pulse oscillations at separate, simultaneously activated cortical sites and the associated gamma-band ECoG activity. We clarify our views on the approximations of dynamic class applicable to neural events at macroscopic and microscopic scales, and the analogies drawn to classes of ANN behaviour. We accept the need to introduce memory processes and detailed anatomical and physiological information into any future developments of our simulations. On the issue of intrinsic cortical stability and the role of extrinsic fibre systems in maintaining stability, we argue that this position is not in extreme contradiction to those of our commentators, and that the mechanisms implicit in our simulations' properties imply rich computational possibilities. We discuss some of the reasons for and against the existence of significant global resonances in the brain and explain why such behaviour appears absent in our simulations. Last, we discuss other phenomena, such as rhythmic driving of the cortex, which have not yet been introduced into our models, and indicate lines for future development of the simulations.

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.

Freeman's pioneering work -- and neurodynamics in general -- has largely ignored specification of an anatomical framework within which features of coherent objects are represented, associated, deleted, and manipulated in computations. Recent theoretical work suggests such a framework can emerge during embryogenesis by selection of neuron ensembles and synaptic connections that maximize the magnitude of synchrony while approaching ultra-small-world connectivity. The emergent structures correspond to those of both columnar and non-columnar cortex. With initial connections thus organized, spatio-temporal information in sensory inputs can generate systematic and specific patterns of synchronous oscillation, with consequent synaptic storage. The theoretical assemblies of connections resemble experimentally observed 'lego sets', while facilitation and interference among synchronous patterns, particularly when executed by fast synapses under metabolic entanglement, imply powerful parallel computation.