Ronald J. MacGregor

Computer simulation of diffusely-connected neuronal populations

This paper describes computer simulations of diffusely-connected neuronal populations. Main findings are that diffuse monosynaptic linkages between populations are selectively sensitive to synchronized clusters of action potentials in the pre-synaptic population; that diffusely-connected excitatory recurrent collaterals tend to produce rhythmic series of synchronized clusters; and that diffusely-connected inhibition (both recurrent and afferent) tend to reduce the number of cells participating in a given synchronized cluster and thereby the overall transfer rate. However, recurrent inhibition tends to increase the rate at which synchronized clusters are produced by recurrent excitation. These results suggest the speculation that diffusely connected neuronal populations are particularly prone to deal with synchronized clusters of action potentials.

Sensory gating in a computer model of the CA3 neural network of the hippocampus

We have developed a unique computer model of the CA3 region of the hippocampus that simulates the P50 auditory evoked potential response to repeated stimuli in order to study the neuronal circuits involved in a sensory processing deficit associated with schizophrenia. Our computer model of the CA3 hippocampal network includes recurrent activation from within the CA3 region as well as input from the entorhinal cortex and the medial septal nucleus. We used the model to help us determine if the cortical and septal inputs to the CA3 hippocampus alone are responsible for the gating of auditory evoked activity, or if the strong recurrent activity within the CA3 region contributes to this phenomenon. The model suggests that the medial septal input is critical for normal gating; however, to a large extent the activity of the medial septal input can be replaced by simulated stimulation of the hippocampal neurons by a nicotinic agonist. The model is thus consistent with experimental data that show that nicotine restores gating of the N40 evoked potential in fimbria-fornix lesioned rats and of the P50 evoked potential in schizophrenic patients.

CONSCIOUSNESS AND THE STRUCTURE OF MATTER

This commentary article extends Vimals [J Integr Neurosci 7:49-73, 2008] concept of protoexperience by outlining a two-factor approach to the localization of consciousness within the physical matter of the brain consistent with contemporary theoretical physics, molecular and system biology, and neuroscience. Specific hypotheses based on this approach predict on clearly stated grounds the occurrence or non-occurrence, and degrees of intensity of consciousness within the human brain and possibly in related species based on the combination of protoconsciousness with energetic activating agents. In this it comprises a mechanics of consciousness.

Sequential configuration model for firing patterns in local neural networks

This paper presents a sequential configuration model to represent the coordinated firing patterns of memory traces in groups of neurons in local networks. Computer simulations are used to study the dynamic properties of memory traces selectively retrieved from networks in which multiple memory traces have been embedded according to the sequential configuration model. Distinct memory traces which utilize the same neurons, but differ only in temporal sequencing are selectively retrievable. Firing patterns of constituent neurons of retrieved memory traces exhibit the main properties of neurons observed in multi microelectrode recordings. The paper shows how to adjust relative synaptic weightings so as to control the disruptive influences of cross-talk in multipy-embedded networks. The theoretical distinction between (primarily anatomical) beds and (primarily physiological) realizations underlines the fundamentally stochastic nature of network firing patterns, and allows the definition of 4 degrees of clarity of retrieved memory traces.

QUANTUM MECHANICS AND BRAIN UNCERTAINTY

This paper argues that molecular governing structures (such as receptors, gating molecules, or ionic channels) which operate pervasively in the brain, often with small number particle systems (as, for example, at the surfaces of membranes, synaptic clefts, or macromolecules), may plausibly be vehicles for the transmutation of quantum mechanical fluctuations to normal-level neural signaling.

Characterization, scaling, and partial representation of neural junctions and coordinated firing patterns by dynamic similarity

This paper presents a dynamic-similarity-based system for mathematically characterizing the functional connectivity and information flow of neural junctions. This approach allows for quantitative comparison of operations of neural junctions across systems, and an interpretation of their connectivity parameters in terms of the flow of multiunit firing patterns. The paper further uses this characterization to show how to rationally construct reduced operational models of neural junctions. Both uniformly proportional scaling and partial fragmentary representations are developed. The uniformly scaled models are better adapted to overall capacities and broader theoretical conceptualizations; the partial representations are better adapted to direct comparison with microelectrode experimentation. The characterization of information flow is based on coordinated multiunit patterns such as synfire chains or sequential configurations. The system can be applied to component parts of large composite networks including junctions with topographical patchiness and other irregularities. The characterization should be of use to anatomists, physiologists, modelers, and theorists. The theory predicts that the necessity for cooperative confluence of synaptic potentials in sending and receiving sequential configurations across topographically constrained projection fields requires the existence of functional ‘pattern modules’ within the topographical synaptology of the junction.

Composite cortical networks as systems of multimodal oscillators

This paper uses a theory of coordinated firing patterns in local cortical networks to extend the modular view of cortical organization into a theory of the structure of neuroelectric signaling in composite regions of cortex that are the size of association or primary receiving areas. The theory assumes that individual cortical modules signal informational states according to particular modes of locally sustained recurrent reverberations, and that the resultant equilibrium configurations across entire composite cortical regions are determined by excitatory and inhibitory lateral interactions among large numbers of such modules. Rough computer simulation of the theory indicates the influences of the local, regional, and global interconnections and the general character of the composite network patterns. The work builds a tentative theoretical bridge across the structure of neuroelectric signals in single neurons, in local networks, and in composite networks, and indicates possible relationships to neuropsychological representations in composite networks.

A FUNCTIONAL VIEW OF CONSCIOUSNESS AND ITS RELATIONS IN BRAIN

Consciousness is seen as evolving jointly with plasticity, self-direction, and autonomy. Its main function is interpreted as the partially autonomous direction of behavioral living in accordance with a vast system of plastic patterns of inner construction, and the development of these--all in the service of a central concern with widely-perceived global well-being. Its central constituents are: conscious awareness itself; sensations and images of sensory bombardment; active development and utilization of inner constructions; and active direction of attention, actions, and behavior. Consciousness operates by the partially autonomous feedback redirection of activation-energization in response to a global distribution of neurobiological flags and states. Central qualities of conscious experience are addressed from this view. Consciousness may act towards an overall principle of minimization. Contrasting its existentially observable manifestations and its neurobiological correspondences provides foundations for five basic views of the fundamental nature of consciousness and its relation to brain.

AN INTEGRATIVE THEORY OF BRAIN AND MIND: THE INNER SENSIBILITIES

This work advances the theory of the integrated functional organic unity of the combined brain and mind, with explicit inclusion of conscious awareness and associated partial autonomy, and outlines its main foundations and qualities. This view: a--indicates new perspectives regarding the foundations of the mind-body question; b--brings the mentoexperiential realm and its qualities into cooperative communication with neurobiological realms; c--offers fresh ground for considering the mentoexperiential in broader biological frameworks such as evolutionary theory; and d--provides a Neuroscientific framework for a full range of specific mentoexperiential qualities.

Characterization, scaling, and partial representation of diffuse and discrete input junctions to CA3 hippocampus

This paper applies a general mathematical system for characterizing and scaling functional connectivity and information flow across the diffuse (EC) and discrete (DG) input junctions to the CA3 hippocampus. Both gross connectivity and coordinated multiunit informational firing patterns are quantitatively characterized in terms of 32 defining parameters interrelated by 17 equations, and then scaled down according to rules for uniformly proportional scaling and for partial representation. The diffuse EC-CA3 junction is shown to be uniformly scalable with realistic representation of both essential spatiotemporal cooperativity and coordinated firing patterns down to populations of a few hundred neurons. Scaling of the discrete DG-CA3 junction can be effected with a two-step process, which necessarily deviates from uniform proportionality but nonetheless produces a valuable and readily interpretable reduced model, also utilizing a few hundred neurons in the receiving population. Partial representation produces a reduced model of only a portion of the full network where each model neuron corresponds directly to a biological neuron. The mathematical analysis illustrated here shows that although omissions and distortions are inescapable in such an application, satisfactorily complete and accurate models the size of pattern modules are possible. Finally, the mathematical characterization of these junctions generates a theory which sees the DG as a definer of the fine structure of embedded traces in the hippocampus and entire coordinated patterns of sequences of 14-cell links in CA3 as triggered by the firing of sequences of individual neurons in DG.