Embodied (4EA) cognitive computational neuroscience.

I argue that ideas and models about the mechanisms of neural computation and representation - including computational architecture, representational format, encoding schemes, learning methods, computation-representation coordination, and substrate-dependent aspects - must be tested by studying embodied neural systems. Thus, cognitive computational neuroscience - the study of neural computations over neural representations - must be an embodied research program.

Situated Neural Representations: Solving the Problems of Content.

Situated approaches to cognition maintain that cognition is embodied, embedded, enactive, and affective (and extended, but that is not relevant here). Situated approaches are often pitched as alternatives to computational and representational approaches, according to which cognition is computation over representations. I argue that, far from being opposites, situatedness and neural representation are more deeply intertwined than anyone suspected.

Quantum-like behavior without quantum physics III : Logic and memory.

We employ some of the machinery developed in previous work to investigate the inferential and memory functions of quantum-like neural networks. We set up a logical apparatus to implement this in the form of a Gentzen sequent calculus which codifies some of the combinatory rules for the state spaces of the neuronal networks introduced earlier. We discuss memory storage in this context and along the way find formal proof that synchronicity promotes binding and storage.

Quantum-like behavior without quantum physics II. A quantum-like model of neural network dynamics.

In earlier work, we laid out the foundation for explaining the quantum-like behavior of neural systems in the basic kinematic case of clusters of neuron-like units. Here we extend this approach to networks and begin developing a dynamical theory for them. Our approach provides a novel mathematical foundation for neural dynamics and computation which abstracts away from lower-level biophysical details in favor of information-processing features of neural activity.

Quantum-like behavior without quantum physics I : Kinematics of neural-like systems.

Recently there has been much interest in the possible quantum-like behavior of the human brain in such functions as cognition, the mental lexicon, memory, etc., producing a vast literature. These studies are both empirical and theoretical, the tenets of the theory in question being mainly, and apparently inevitably, those of quantum physics itself, for lack of other arenas in which quantum-like properties are presumed to obtain.

Foundations of computational neuroscience.

Most computational neuroscientists assume that nervous systems compute and process information. We discuss foundational issues such as what we mean by 'computation' and 'information processing' in nervous systems; whether computation and information processing are matters of objective fact or of conventional, observer-dependent description; and how computational descriptions and explanations are related to other levels of analysis and organization.

Neural computation and the computational theory of cognition.

We begin by distinguishing computationalism from a number of other theses that are sometimes conflated with it. We also distinguish between several important kinds of computation: computation in a generic sense, digital computation, and analog computation. Then, we defend a weak version of computationalism-neural processes are computations in the generic sense.

Information processing, computation, and cognition.

Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both - although others disagree vehemently.

Are prototypes and exemplars used in distinct cognitive processes?

We argue that Machery provides no convincing evidence that prototypes and exemplars are typically used in distinct cognitive processes. This partially undermines the fourth tenet of the Heterogeneity Hypothesis and thus casts doubts on Machery's way of splitting concepts into different kinds. Although Machery may be right that concepts split into different kinds, such kinds may be different from those countenanced by the Heterogeneity Hypothesis.

Some neural networks compute, others don't.

I address whether neural networks perform computations in the sense of computability theory and computer science. I explicate and defend the following theses. (1) Many neural networks compute--they perform computations.