A technique for designing and optimizing the next generation of smart process controllers has been developed in this dissertation. The literature review indicated that neural networks held the most promise for this application, yet fundamental limitations have prevented their introduction to commercial settings thus far. This fundamental limitation has been overcome through the enhancement of neural network theory. The approach taken in this research was to produce highly intelligent process control systems by accurately modeling the nervous structures of higher biological organisms. The mammalian cerebral cortex was selected as the primary model since it is the only computational element capable of interpreting and complex patterns that develop over time. However the choice of the mammalian cerebral cortex as the model introduced two new levels of network complexity. First, the cerebral cortex is a three dimensional structure with extremely complicated patterns of interconnectivity. Second, the structure of the cerebral cortex can only be realized when thousands or millions of neurons are integrated into a massive scale neural network. The neural networks developed in this research were designed around the Hebbian adaptation, the only training technique proven by the literature review to be applicable to massive scale networks. These design difficulties were resolved by not only modeling the cerebral cortex, but the process by which it develops and evolves in biological systems. To complete this model, an advanced genetic algorithm was produced, and a technique was developed to encode all functional and structural parameters that define the cerebral cortex into the artificial chromosome. The neural networks were designed by a cell growth simulation program that decoded the structural and functional information on the chromosome. The cell growth simulation program is capable of producing patterns of differentiation unique for any slight variations in the genetic parameters. These growth patterns are similar to patterns of cellular differentiation seen in biological systems. While the computational resources needed to implement a massive scale neural network are beyond that available in existing computer systems, the technique has produced output lists which fully define the interconnections and functional characteristic of the neurons, thereby laying the foundation for their future use in process control. / Ph. D.

The subplate layer of the cerebral cortex is comprised of a heterogeneous population of cells and contains some of the earliest-generated neurons. Subplate plays a fundamental role in cortical development. In the embryonic brain, subplate cells contribute to the guidance and areal targeting of corticofugal and thalamic axons. At later stages, these cells are involved in the maturation and plasticity of the cortical circuitry and the establishment of functional modules. In my thesis, I aimed to further characterize the embryonic murine subplate by establishing a gene expression profile of this population at embryonic day 15.5 (E15.5) using laser capture microdissection combined with microarrays. I found over 250 transcripts with presumed higher expression in the subplate at E15.5. Using quantitative RT-PCR, in situ hybridization and immunohistochemistry, I have confirmed specific expression in the E15.5 subplate for 13 selected genes which have not been previously associated with this compartment. In the reeler mutant, the expression pattern of a majority of these genes was shifted in accordance with the altered position of subplate cells. These genes belong to several functional groups and likely contribute to the maturation and electrophysiological properties of subplate cells and to axonal growth and guidance. The roles of two selected genes - cadherin 10 (Cdh10) and Unc5 homologue c (Unc5c) - were explored in more detail. Preliminary results suggest an involvement of Cdh10 in subplate layer organization while Unc5c could mediate the waiting period of subplate corticothalamic axons in the internal capsule. Finally, I compared the expression of a selection of subplate-specific genes (subplate markers) between mouse and rat and found some surprising species differences. Confirmed subplate markers were used to monitor subplate injury in a rat model of preterm hypoxiaischemia and it appeared that deep cortical layers including subplate showed an increased vulnerability over upper layers. Further characterization of subplate-specific genes will allow us to broaden our understanding of molecular mechanisms underlying subplate properties and functions in normal and pathological development.

Le neurone est une cellule polarisée qui se divise en deux compartiments spécialisés : le compartiment somato-dendritique et le compartiment axonal. Généralement, le premier reçoit l'information en provenance d'autres neurones et le second génère un message en sortie lorsque la somme des entrées dépasse une valeur seuil au segment initial de l'axone. Ce signal de nature discrète appelé potentiel d'action (PA) est propagé activement jusqu'à la terminaison synaptique où il déclenche la transmission chimique de l'information. Cependant, la fonction axonale ne se résume pas à la simple transmission des séquences de PA à l'image d'un câble de télégraphe. L'axone est également capable de transmettre des variations continues de signaux électriques infraliminaires dit analogues et les combiner avec l'information digitale véhiculée par le PA. J'ai consacré la majorité de mon travail de thèse à l'étude de ce nouvel aspect de la fonction axonale dans le cadre de la transmission synaptique entre les neurones pyramidaux au sein du réseau excitateur CA3 de l'hippocampe de rat. Les résultats obtenus à partir d'enregistrements de paires de neurones pendant ma thèse mettent en évidence deux sortes de signalisation analogue et digitale qui aboutissent à la facilitation de la transmission synaptique. La facilitation analogue-digitale (FAD) a été observée lors d'une dépolarisation prolongée, mais également à la suite d'une hyperpolarisation transitoire au niveau du corps cellulaire. Ce sont deux versants d'une même plasticité à court-terme qui découle de l'état biophysique des canaux ioniques sensibles au voltage étant à l'origine du PA. / The neuron is a polarised cell divided into two specialized compartments: the somato-dendritic and the axonal compartment. Generally, the first one receives information arriving from other neurones and the second generates an output message, when the sum of inputs exceeds a threshold value at the axon initial segment. This all-or-none signal, called the action potential (AP) is propagated actively to the synaptic terminal where it triggers chemical transmission of information. However, axonal function is not limited to transmission of AP sequences like a telegraph cable. The axon is also capable of transmitting continuously changing sub-threshold electric signals called analogue signals and to combine them with the digital information carried by the AP. I devoted the majority of my thesis work to the study of these novel aspects of axonal function in the framework of synaptic transmission between pyramidal neurons in the CA3 excitatory network of the rat hippocampus. The results obtained through paired recordings brought to light two kinds of analogue and digital signalling that lead to a facilitation of synaptic transmission. Analogue-digital facilitation (ADF) was observed during prolonged presynaptic depolarization and also after a transient hyperpolarization of the neuronal cell body. These are two sides of the same form of short-term synaptic plasticity depending on the biophysical state of voltage gated ion channels responsible for AP generation. The first variant of ADF induced by depolarization (ADFD) is due to AP broadening and involves Kv1 potassium channels.

TBI stands for Traumatic Brain Injury and refers to damage to the brain resulting from an external physical force, such as a blow, jolt, or penetrating injury to the head. Common causes of TBI include falls, motor vehicle accidents, sports injuries, and violence and has been linked to thousands of deaths and injuries in the US and the EU alike. This thesis was aimed to localise certain TBI to a specific part of the brain by exerting similar loading conditions on an Finite Element Method (FEM) of the rat brain as physical experiments conducted on living rats. By comparing the strain in 7 vital parts of the brain to injury diagnosis conducted in the physical experiments, an effort was made to link localised strain to injury diagnosis. The results indicate that strain in the thalamus and hypothalamus are linked with a loss of consciousness while strain in the hypothalamus coupled with the neocortex correlates greatly with activity-based behaviour changes. Lastly, injury associated with emotional changes are believed to stem from large strains in the neocortex. There is a theory suggesting that the structure of myeline, which provides support in motion and movement patterns of biological systems in humans and animals (known as biomechanical kinematics), could have an impact. However, more studies are needed to confirm and determine the exact cause. / TBI, från engelskans Traumatic Brain Injury, står för Traumatisk Hjärn Skada och syftar på en skada i hjärnan till följd av enyttre fysisk kraft, såsom ett slag, stöt eller genomträngande skada i huvudet. Vanliga orsaker till TBI inkluderar fall, motorfordonsolyckor, sportskador och våld och har kopplats till tusentals dödsfall och skadade i både USA och EU. Denna rapport syftar till att försöka lokalisera viss TBI till en specifik del av hjärnan genom att utöva liknandebelastningsförhållanden på en finit elementmetod (FEM) modell av råtthjärnan som fysiska experimentutförs på levande råttor. Genom att jämföra belastningen i 7 vitala delar av hjärnan med skadediagnos som utfördes i de fysiska experimenten gjordes en ansträngning för att koppla lokaliserad belastning till skadediagnos. Resultaten indikerar att skada i thalamus och hypotalamus är kopplade till en förlust av medvetande medan belastning i hypotalamus i kombination med neocortex korrelerar kraftigtmed aktivitetsbaserade beteendeförändringar. Slutligen är skador i samband med känslomässiga förändringartros härröra från skada i neocortex. Det finns teori som tyder på attstruktur av myelin, som ger stöd i rörelse och rörelsemönster av biologiskasystem hos människor och djur (känd som biomekanisk kinematik), kan ha en inverkan.Det behövs dock fler studier för att bekräfta och fastställa den exakta orsaken.

There is a basic rule to mammalian neocortical expansion: as it expands, so does it fold. The degree to which it folds, however, cannot strictly be attributed to its expansion. Across species, cortical volume does not keep pace with cortical surface area, but rather folds appear more rapidly than expected. As a result, larger brains quickly become disproportionately more convoluted than smaller brains. Both the absence (lissencephaly) and presence (gyrencephaly) of cortical folds is observed in all mammalian orders and, while there is likely some phylogenetic signature to the evolutionary appearance of gyri and sulci, there are undoubtedly universal trends to the acquisition of folds in an expanding neocortex. Whether these trends are governed by conical expansion of neocortical germinal zones, the distribution of cortical connectivity, or a combination of growth- and connectivity-driven forces remains an open question. But the importance of cortical folding for evolution of the uniquely mammalian neocortex, as well as for the incidence of neuropathologies in humans, is undisputed. In this hypothesis and theory article, we will summarize the development of cortical folds in the neocortex, consider the relative influence of growth- vs. connectivity-driven forces for the acquisition of cortical folds between and within species, assess the genetic, cell-biological, and mechanistic implications for neocortical expansion, and discuss the significance of these implications for human evolution, development, and disease. We will argue that evolutionary increases in the density of neuron production, achieved via maintenance of a basal proliferative niche in the neocortical germinal zones, drive the conical migration of neurons toward the cortical surface and ultimately lead to the establishment of cortical folds in large-brained mammal species.

Thesis (MScMedSc (Biomedical Sciences. Molecular Biology and Human Genetics. Medical Biochemistry))--University of Stellenbosch, 2009. / The mammalian neocortex contributes to the increasing functional complexity of the mammalian brain, partly because of its striking organisation into distinct neuronal layers. The development of the neocortex has been well studied because disrupted neurodevelopment results in several human diseases. The basic principles of neocortical development have been well established for some time; however the molecular mechanisms have only recently been identified. One major advance in our understanding of these molecular mechanisms was the discovery of Reelin, an extracellular matrix protein that directs the migration of neurons to their final positions in the developing neocortex. Reelin is a large multi-domain protein that exerts its functions by binding to its ligands on the cell surface and initiating a signal transduction cascade that ultimately results in cytoskeletal rearrangements. Several investigations have been undertaken to elucidate the functions of each of these domains to gain a better understanding reelin’s functions. We have previously identified the WR40 repeat protein 47 (WDR47), a protein of unknown function, as a novel putative ligand for the N-terminal reeler domain of reelin. To gain better understanding into the functional significance of this interaction, the present study sought to identify novel WDR47- interacting proteins. In order to achieve this, a cDNA encoding a polypeptide that contains the two N-terminal domains of WDR47, i.e. the Lis homology and the C-terminal Lis homology domain (CTLH) was used as bait in a Y2H screen of a foetal brain cDNA library. Putative WDR47 ligands were subsequently verified using 3D in vivo co-localisation. Results of these analyses showed that SCG10, a microtubule destabilizing protein belonging to the stathmin family of proteins, interacted with the N-terminal of WDR47. The identification of SCG10 as a novel WDR47 interacting protein not only sheds some light on the role and function of WDR47 but also aids in a better understanding of the reelin pathway and cortical lamination. Moreover, the data presented here, may also provide researchers with new avenues of research into molecular mechanisms involved in neuronal migration disorders.

During development of the neocortex, many diverse projection neuron subtypes are generated under regulation of cell-extrinsic and cell-intrinsic controls. One broad projection neuron class, corticofugal projection neurons (CFuPN), is the primary output neuron population of the neocortex. CFuPN axons innervate sub-cortical targets including thalamus, striatum, brainstem, and spinal cord.

This thesis presents an abstract model of the mammalian neocortex. The model was constructed by taking a top-down view on the cortex, where it is assumed that cortex to a first approximation works as a system with attractor dynamics. The model deals with the processing of static inputs from the perspectives of biological mapping, algorithmic, and physical implementation, but it does not consider the temporal aspects of these inputs. The purpose of the model is twofold: Firstly, it is an abstract model of the cortex and as such it can be used to evaluate hypotheses about cortical function and structure. Secondly, it forms the basis of a general information processing system that may be implemented in computers. The characteristics of this model are studied both analytically and by simulation experiments, and we also discuss its parallel implementation on cluster computers as well as in digital hardware. The basic design of the model is based on a thorough literature study of the mammalian cortex’s anatomy and physiology. We review both the layered and columnar structure of cortex and also the long- and short-range connectivity between neurons. Characteristics of cortex that defines its computational complexity such as the time-scales of cellular processes that transport ions in and out of neurons and give rise to electric signals are also investigated. In particular we study the size of cortex in terms of neuron and synapse numbers in five mammals; mouse, rat, cat, macaque, and human. The cortical model is implemented with a connectionist type of network where the functional units correspond to cortical minicolumns and these are in turn grouped into hypercolumn modules. The learning-rules used in the model are local in space and time, which make them biologically plausible and also allows for efficient parallel implementation. We study the implemented model both as a single- and multi-layered network. Instances of the model with sizes up to that of a rat-cortex equivalent are implemented and run on cluster computers in 23% of real time. We demonstrate on tasks involving image-data that the cortical model can be used for meaningful computations such as noise reduction, pattern completion, prototype extraction, hierarchical clustering, classification, and content addressable memory, and we show that also the largest cortex equivalent instances of the model can perform these types of computations. Important characteristics of the model are that it is insensitive to limited errors in the computational hardware and noise in the input data. Furthermore, it can learn from examples and is self-organizing to some extent. The proposed model contributes to the quest of understanding the cortex and it is also a first step towards a brain-inspired computing system that can be implemented in the molecular scale computers of tomorrow. The main contributions of this thesis are: (i) A review of the size, modularization, and computational structure of the mammalian neocortex. (ii) An abstract generic connectionist network model of the mammalian cortex. (iii) A framework for a brain-inspired self-organizing information processing system. (iv) Theoretical work on the properties of the model when used as an autoassociative memory. (v) Theoretical insights on the anatomy and physiology of the cortex. (vi) Efficient implementation techniques and simulations of cortical sized instances. (vii) A fixed-point arithmetic implementation of the model that can be used in digital hardware. / QC 20100903

This thesis proposes a novel set of generic and compact biologically plausible VLSI (Very Large Scale Integration) neural circuits, suitable for implementing a parallel VLSI network that closely resembles the function of a small-scale neocortical network. The proposed circuits include a cortical neuron, two different long-term plastic synapses and four different short-term plastic synapses. These circuits operate in accelerated-time, where the time scale of neural responses is approximately three to four orders of magnitude faster than the biological-time scale of the neuronal activities, providing higher computational throughput in computing neural dynamics. Further, a novel biological-time cortical neuron circuit with similar dynamics as of the accelerated-time neuron is proposed to demonstrate the feasibility of migrating accelerated-time circuits into biological-time circuits. The fabricated accelerated-time VLSI neuron circuit is capable of replicating distinct firing patterns such as regular spiking, fast spiking, chattering and intrinsic bursting, by tuning two external voltages. It reproduces biologically plausible action potentials. This neuron circuit is compact and enables implementation of many neurons in a single silicon chip. The circuit consumes extremely low energy per spike (8pJ). Incorporating this neuron circuit in a neural network facilitates diverse non-linear neuron responses, which is an important aspect in neural processing. Two of the proposed long term plastic synapse circuits include spike-time dependent plasticity (STDP) synapse, and dopamine modulated STDP synapse. The short-term plastic synapses include excitatory depressing, inhibitory facilitating, inhibitory depressing, and excitatory facilitating synapses. Many neural parameters of short- and long- term synapses can be modified independently using externally controlled tuning voltages to obtain distinct synaptic properties. Having diverse synaptic dynamics in a network facilitates richer network behaviours such as learning, memory, stability and dynamic gain control, inherent in a biological neural network. To prove the concept in VLSI, different combinations of these accelerated-time neural circuits are fabricated in three integrated circuits (ICs) using a standard 0.35 µm CMOS technology. Using first two ICs, functions of cortical neuron and STDP synapses have been experimentally verified. The third IC, the Cortical Neural Layer (CNL) Chip is designed and fabricated to facilitate cortical network emulations. This IC implements neural circuits with a similar composition to the cortical layer of the neocortex. The CNL chip comprises 120 cortical neurons and 7 560 synapses. Many of these CNL chips can be combined together to form a six-layered VLSI neocortical network to validate the network dynamics and to perform neural processing of small-scale cortical networks. The proposed neuromorphic systems can be used as a simulation acceleration platform to explore the processing principles of biological brains and also move towards realising low power, real-time intelligent computing devices and control systems.

Gyrencephaly (the folding of the surface of the neocortex) is a mammalian-specific trait present in almost all mammalian orders. Despite the widespread appearance of the trait, little is known about the mechanism of its genesis or its adaptive significance. Still, most of the hypotheses proposed concentrated on the pattern of connectivity of mature neurons as main components of gyri formation. Recent work on embryonic neurogenesis in several species of mammals revealed different progenitor and stem cells and their neurogenic potential as having important roles in the process of gyrification. Studies in the field of comparative neurogenesis revealed that gyrencephaly is an evolutionarily labile trait, and that some species underwent a secondary loss of a convoluted brain surface and thus reverted to a more ancient form, a less folded brain surface (lissencephaly). This phenotypic reversion provides an excellent system for understanding the phenomenon of secondary loss. In this review, we will outline the theory behind secondary loss and, as specific examples, present species that have undergone this transition with respect to neocortical folding. We will also discuss different possible pathways for obtaining (or losing) gyri. Finally, we will explore the potential adaptive consequence of gyrencephaly relative to lissencephaly and vice versa.