Cooperation of the basal ganglia, cerebellum, sensory cerebrum and hippocampus: possible implications for cognition, consciousness, intelligence and creativity.

It is suggested that the anatomical structures which mediate consciousness evolved as decisive embellishments to a (non-conscious) design strategy present even in the simplest unicellular organisms. Consciousness is thus not the pinnacle of a hierarchy whose base is the primitive reflex, because reflexes require a nervous system, which the single-celled creature does not possess. By postulating that consciousness is intimately connected to self-paced probing of the environment, also prominent in prokaryotic behavior, one can make mammalian neuroanatomy amenable to dramatically straightforward rationalization. Muscular contraction is the nervous system's only externally directed product, and the signaling routes which pass through the various brain components must ultimately converge on the motor areas. The function of several components is still debatable, so it might seem premature to analyze the global operation of the circuit these routes constitute. But such analysis produces a remarkably simple picture, and it sheds new light on the roles of the individual components. The underlying principle is conditionally permitted movement, some components being able to veto muscular contraction by denying the motor areas sufficient activation. This is true of the basal ganglia (BG) and the cerebellum (Cb), which act in tandem with the sensory cerebrum, and which can prevent the latter's signals to the motor areas from exceeding the threshold for overt movement. It is also true of the anterior cingulate, which appears to play a major role in directing attention. In mammals, the result can be mere thought, provided that a second lower threshold is exceeded. The veto functions of the BG and the Cb stem from inhibition, but the countermanding disinhibition develops at markedly different rates in those two key components. It develops rapidly in the BG, control being exercised by the amygdala, which itself is governed by various other brain regions. It develops over time in the Cb, thereby permitting previously executed movements that have proved advantageous. If cognition is linked to overt or covert movement, intelligence becomes the ability to consolidate individual motor elements into more complex patterns, and creativity is the outcome of a race-to-threshold process which centers on the motor areas. Amongst the ramifications of these ideas are aspects of cortical oscillations, phantom limb sensations, amyotrophic lateral sclerosis (ALS) the difficulty of self-tickling and mirror neurons.

Protein structures from distance inequalities.

A computer method for folding protein backbones from distance inequalities is presented. It involves an algorithm that uses a novel approach for handling inequalities through the minimization of a continuous energy function. Tests of the folding algorithm have been carried out on a small protein, the 6PTI (bovine pancreatic trypsin inhibitor) with 56 amino acid residues, and on a medium-size protein, the 1TRM (rat trypsin) with 223 amino acid residues. Reconstructions based on a real-valued distance matrix led to folded three-dimensional structures with root-mean-square values of 0.04 A when compared with the crystallographic data. The obtained root-mean-square measures were of the order of 1 A, when distance inequalities were used for the reconstruction. Subsequently, the folding approach has been applied to distance inequalities predicted by neural network techniques that use the amino acid sequence as the only input. The inaccuracy in the inequalities predicted by the neural network was the reason for the root-mean-square value of 5.2 A. An error analysis of the method for reconstruction was performed and showed that no more than 3% inaccurate distance inequalities could be corrected for. Finally, a simple technique for root-mean-square comparisons of different protein structures is discussed.

A model for cortical 40 Hz oscillations invokes inter-area interactions.

Computer simulation of the dynamics of neuronal assemblies within minicolumns, and of the interactions between minicolumns in different cortical areas, has produced a quantitative explanation of the 35-60 Hz oscillations recently observed in adult cat striate cortices. The observed behavior suggests an association mechanism that exploits the NMDA receptor's properties. Detectable oscillations are predicted in cortical areas not directly stimulated, provided these are associatively linked with areas receiving sensory input.

Analysis of the secondary structure of the human immunodeficiency virus (HIV) proteins p17, gp120, and gp41 by computer modeling based on neural network methods.

A neural network computer program, trained to predict secondary structure of proteins by exposing it to matching sets of primary and secondary structures from a database, was used to analyze the human immunodeficiency virus (HIV) proteins p17, gp120, and gp41 from their amino acid sequences. The results are compared to those obtained by the Chou-Fasman analysis. Two alpha-helical sequences corresponding to the putative fusigenic domain and to the transmembrane domain of gp41 could be predicted, as well as a possible binding site between p17 and gp41. On the basis of the secondary structure predictions, a three-dimensional model of p17 was constructed. This model was found to represent a stable conformation by an analysis using an energy-minimization program. The model predicts that p17 is attached to the membrane only by the acylated N-terminus, in analogy with the N-terminus of the gag protein of other retroviruses and also with the src oncogene protein p60src. The intracellular C-terminal part of gp41 may act as a receptor by electrostatic interaction with p17.

A novel approach to prediction of the 3-dimensional structures of protein backbones by neural networks.

Three-dimensional structures of protein backbones have been predicted using neural networks. A feed forward neural network was trained on a class of functionally, but not structurally, homologous proteins, using backpropagation learning. The network generated tertiary structure information in the form of binary distance constraints for the C(alpha) atoms in the protein backbone. The binary distance between two C(alpha) atoms was 0 if the distance between them was less than a certain threshold distance, and 1 otherwise. The distance constraints predicted by the trained neural network were utilized to generate a folded conformation of the protein backbone, using a steepest descent minimization approach.

Protein secondary structure and homology by neural networks. The alpha-helices in rhodopsin.

Neural networks provide a basis for semiempirical studies of pattern matching between the primary and secondary structures of proteins. Networks of the perceptron class have been trained to classify the amino-acid residues into two categories for each of three types of secondary feature: alpha-helix or not, beta-sheet or not, and random coil or not. The explicit prediction for the helices in rhodopsin is compared with both electron microscopy results and those of the Chou-Fasman method. A new measure of homology between proteins is provided by the network approach, which thereby leads to quantification of the differences between the primary structures of proteins.