Using modular neural networks to model self-consciousness and self-representation for artificial entities

Self-consciousness implies not only self or group recognition, but also real knowledge of one’s own identity. Self-consciousness is only possible if an individual is intelligent enough to formulate an abstract self-representation. Moreover, it necessarily entails the capability of referencing and using this elf-representation in connection with other cognitive features, such as inference, and the anticipation of the consequences of both one’s own and other individuals’ acts. In this paper, a cognitive architecture for self-consciousness is proposed. This cognitive architecture includes several modules: abstraction, self-representation, other individuals'representation, decision and action modules. It includes a learning process of self-representation by direct (self-experience based) and observational learning (based on the observation of other individuals). For model implementation a new approach is taken using Modular Artificial Neural Networks (MANN). For model testing, a virtual environment has been implemented. This virtual environment can be described as a holonic system or holarchy, meaning that it is composed of autonomous entities that behave both as a whole and as part of a greater whole. The system is composed of a certain number of holons interacting. These holons are equipped with cognitive features, such as sensory perception, and a simplified model of personality and self-representation. We explain holons’ cognitive architecture that enables dynamic self-representation. We analyse the effect of holon interaction, focusing on the evolution of the holon’s abstract self-representation. Finally, the results are explained and analysed and conclusions drawn.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

Prion crystalization model and its application to recognition pattern

This paper introduces APA (?Artificial Prion Assembly?): a pattern recognition system based on artificial prion crystalization. Specifically, the system exhibits the capability to classify patterns according to the resulting prion self- assembly simulated with cellular automata. Our approach is inspired in the biological process of proteins aggregation, known as prions, which are assembled as amyloid fibers related with neurodegenerative disorders.

Striking sequence similarity in inter- and intra-specific comparisons of class I SLG alleles from Brassica oleracea and Brassica campestris: Implications for the evolution and recognition mechanism

Self-incompatibility in Brassica is controlled by a single multi-allelic locus (S locus), which contains at least two highly polymorphic genes expressed in the stigma: an S glycoprotein gene (SLG) and an S receptor kinase gene (SRK). The putative ligand-binding domain of SRK exhibits high homology to the secretory protein SLG, and it is believed that SLG and SRK form an active receptor kinase complex with a self-pollen ligand, which leads to the rejection of self-pollen. Here, we report 31 novel SLG sequences of Brassica oleracea and Brassica campestris. Sequence comparisons of a large number of SLG alleles and SLG-related genes revealed the following points. (i) The striking sequence similarity observed in an inter-specific comparison (95.6% identity between SLG14 of B. oleracea and SLG25 of B. campestris in deduced amino acid sequence) suggests that SLG diversification predates speciation. (ii) A perfect match of the sequences in hypervariable regions, which are thought to determine S specificity in an intra-specific comparison (SLG8 and SLG46 of B. campestris) and the observation that the hypervariable regions of SLG and SRK of the same S haplotype were not necessarily highly similar suggests that SLG and SRK bind different sites of the pollen ligand and that they together determine S specificity. (iii) Comparison of the hypervariable regions of SLG alleles suggests that intragenic recombination, together with point mutations, has contributed to the generation of the high level of sequence variation in SLG alleles. Models for the evolution of SLG/SRK are presented.

Molecular basis for the recognition of two structurally different major histocompatibility complex/peptide complexes by a single T-cell receptor

2C is a typical alloreactive cytotoxic T lymphocyte clone that recognizes two different ligands. These ligands are adducts of the allo-major histocompatibility complex (MHC) molecule H-2Ld and an endogenous octapeptide, and of the self-MHC molecule H-2Kb and another peptide. MHC-binding and T-cell assays with synthetic peptides in combination with molecular modeling studies were employed to analyze the structural basis for this crossreactivity. The molecular surfaces of the two complexes differ greatly in densities and distributions of positive and negative charges. However, modifications of the peptides that increase similarity decrease the capacities of the resulting MHC peptide complexes to induce T-cell responses. Moreover, the roles of the peptides in ligand recognition are different for self- and allo-MHC-restricted T-cell responses. The self-MHC-restricted T-cell responses were finely tuned to recognition of the peptide. The allo-MHC-restricted responses, on the other hand, largely ignore modifications of the peptide. The results strongly suggest that adaptation of the T-cell receptor to the different ligand structures, rather than molecular mimicry by the ligands, is the basis for the crossreactivity of 2C. This conclusion has important implications for T-cell immunology and for the understanding of immunological disorders.

Detection of competing DNA structures by thermal gradient gel electrophoresis: from self-association to triple helix formation by (G,A)-containing oligonucleotides

Sequence-specific recognition of DNA can be achieved by triple helix-forming oligonucleotides that bind to the major groove of double-helical DNA. These oligonucleotides have been used as sequence-specific DNA ligands for various purposes, including sequence-specific gene regulation in the so-called ‘antigene strategy’. In particular, (G,A)-containing oligonucleotides can form stable triple helices under physiological conditions. However, triplex formation may be in competition with self-association of these oligonucleotides. For biological applications it would be interesting to identify the conditions under which one structure is favoured as compared to the other(s). Here we have directly studied competition between formation of a parallel (G,A) homoduplex and that of a triple helix by a 13 nt (G,A)-containing oligonucleotide. Temperature gradient gel electrophoresis allows simultaneous detection of competition between the two structures, because of their different temperature dependencies and gel electrophoretic mobilities, and characterisation of this competition.

Synaptic pattern formation during cellular recognition

Cell–cell recognition often requires the formation of a highly organized pattern of receptor proteins (a synapse) in the intercellular junction. Recent experiments [e.g., Monks, C. R. F., Freiberg, B. A., Kupfer, H., Sciaky, N. & Kupfer, A. (1998) Nature (London) 395, 82–86; Grakoui, A., Bromley, S. K., Sumen, C., Davis, M. M., Shaw, A. S., Allen, P. M. & Dustin, M. L. (1999) Science 285, 221–227; and Davis, D. M., Chiu, I., Fassett, M., Cohen, G. B., Mandelboim, O. & Strominger, J. L. (1999) Proc. Natl. Acad. Sci. USA 96, 15062–15067] vividly demonstrate a complex evolution of cell shape and spatial receptor–ligand patterns (several microns in size) in the intercellular junction during immunological synapse formation. The current view is that this dynamic rearrangement of proteins into organized supramolecular activation clusters is driven primarily by active cytoskeletal processes [e.g., Dustin, M. L. & Cooper, J. A. (2000) Nat. Immunol. 1, 23–29; and Wulfing, C. & Davis, M. M. (1998) Science 282, 2266–2269]. Here, aided by a quantitative analysis of the relevant physico-chemical processes, we demonstrate that the essential characteristics of synaptic patterns observed in living cells can result from spontaneous self-assembly processes. Active cellular interventions are superimposed on these self-organizing tendencies and may also serve to regulate the spontaneous processes. We find that the protein binding/dissociation characteristics, protein mobilities, and membrane constraints measured in the cellular environment are delicately balanced such that the length and time scales of spontaneously evolving patterns are in near-quantitative agreement with observations for synapse formation between T cells and supported membranes [Grakoui, A., Bromley, S. K., Sumen, C., Davis, M. M., Shaw, A. S., Allen, P. M. & Dustin, M. L. (1999) Science 285, 221–227]. The model we present provides a common way of analyzing immunological synapse formation in disparate systems (e.g., T cell/antigen-presenting cell junctions with different MHC-peptides, natural killer cells, etc.).

Structural Analysis and Molecular Model of a Self-Incompatibility RNase from Wild Tomato1

Self-incompatibility RNases (S-RNases) are an allelic series of style glycoproteins associated with rejection of self-pollen in solanaceous plants. The nucleotide sequences of S-RNase alleles from several genera have been determined, but the structure of the gene products has only been described for those from Nicotiana alata. We report on the N-glycan structures and the disulfide bonding of the S3-RNase from wild tomato (Lycopersicon peruvianum) and use this and other information to construct a model of this molecule. The S3-RNase has a single N-glycosylation site (Asn-28) to which one of three N-glycans is attached. S3-RNase has seven Cys residues; six are involved in disulfide linkages (Cys-16-Cys-21, Cys-46-Cys-91, and Cys-166-Cys-177), and one has a free thiol group (Cys-150). The disulfide-bonding pattern is consistent with that observed in RNase Rh, a related RNase for which radiographic-crystallographic information is available. A molecular model of the S3-RNase shows that four of the most variable regions of the S-RNases are clustered on one surface of the molecule. This is discussed in the context of recent experiments that set out to determine the regions of the S-RNase important for recognition during the self-incompatibility response.

Expression of a second receptor rescues self-specific T cells from thymic deletion and allows activation of autoreactive effector function.

Allelic exclusion at the T-cell receptor alpha chain locus is incomplete resulting in the generation of T cells that express two T-cell receptors. The potential involvement of such T cells in autoimmunity has been suggested [Padovan, E., Casorati, G., Dellabona, P., Meyer, S., Brockhaus, M. & Lanzavecchia, A. (1993) Science 262, 422-424; Heath, W. R. & Miller, J. F. A. P. (1993) J. Exp. Med. 178, 1807-1811]. Here we show that expression of a second T-cell receptor can rescue T cells with autospecific receptors from thymic deletion and allow their exit into the periphery. Dual receptor T cells, created by constitutive expression of two transgenic T-cell receptors on a Rag1-/- background, are tolerant to self by maintaining low levels of autospecific receptor, but selfreactive effector function (killing) can be induced through activation via the second receptor. This opens the possibility that T cells carrying two receptors in the periphery of normal individuals contain putatively autoreactive cells that could engage in autoimmune effector functions after recognition of an unrelated environmental antigen.

Self-organized phase transitions in neural networks as a neural mechanism of information processing.

Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of phase transition. A key event for the neural process of information processing in a population coding scheme is transition between the activity patterns encoding usual entities. We propose that the infinitesimal and short-term synaptic changes based on the Hebbian learning rule are the driving force for the transition. The phase transition between the following two dynamical stable states is studied in detail, the state where the firing pattern is changed temporally so as to itinerate among several patterns and the state where the firing pattern is fixed to one of several patterns. The phase transition from the pattern itinerant state to a pattern fixed state may be induced by the Hebbian learning process under a weak input relevant to the fixed pattern. The reverse transition may be induced by the Hebbian unlearning process without input. The former transition is considered as recognition of the input stimulus, while the latter is considered as clearing of the used input data to get ready for new input. To ensure that information processing based on the phase transition can be made by the infinitesimal and short-term synaptic changes, it is absolutely necessary that the network always stays near the critical state corresponding to the phase transition point.

The BALB/c mouse B-cell response to pigeon cytochrome c initiates as a heteroclitic response specific for the self antigen mouse cytochrome c.

Direct evidence is presented in support of the longstanding but unproven hypothesis that B lymphocytes specific for self antigens (Ags) can be used in the immune response to foreign Ags. We show that the B cells in BALB/c mic responding early to pigeon cytochrome c (CYT) produce antibodies that recognize and bind the major antigenic site on mouse CYT with greater affinity than they bind pigeon CYT i.e., they are heteroclitic for the self Ag. Furthermore, these B cells express the same combination of immunoglobulin variable region (V) genes that are known to be used in B-cell recognition of mouse CYT. Over time, the response to pigeon CYT becomes more specific for the foreign Ag through the recruitment of B cells expressing different combinations of V genes and, possibly, somatic mutation of the mouse CYT specific B cells from early in the response. Cross-recognition of pigeon CYT by mouse CYT-specific B cells results from the sharing of critical amino acid residues by the two Ags. Although B-cell recognition of the self Ag, mouse CYT, is very specific, which limits the extent to which foreign Ags can cross-activate the autoreactive B cells, it is possible that polyreactive B cells to other self Ags may be used more frequently in response to foreign Ags.

Antagonism of WT1 activity by protein self-association.

Germline loss-of-function mutations at the Wilms tumor (WT) suppressor locus WT1 are associated with a predisposition to WTs and mild genital system anomalies. In contrast, germ-line missense mutations within the WT1 gene encoding the DNA-binding domain often yield a more severe phenotype consisting of WT, sexual ambiguity, and renal nephropathy. In this report, we demonstrate that the products of mutant alleles that impair DNA recognition can antagonize WT1-mediated transcriptional repression. We demonstrate that WT1 can self-associate in vitro and in vivo and that the responsible domain maps to the amino-terminal region of the protein. Oligomers of full-length protein form less efficiently or produce less stable complexes than oligomers between truncated polypeptides and full-length protein. Our data suggest a molecular mechanism to explain how WT1 mutations may act in deregulating cellular proliferation and differentiation.

Molecular approaches to smart materials via interface recognition and conformationally switchable cavitands

In this thesis the molecular level design of functional materials and systems is reported. In the first part, tetraphosphonate cavitand (Tiiii) recognition properties towards amino acids are studied both in the solid state, through single crystal X-ray diffraction, and in solution, via NMR and ITC experiments. The complexation ability of these supramolecular receptors is then applied to the detection of biologically remarkable N-methylated amino acids and peptides using complex dynamic emulsions-based sensing platforms. In the second part, a general supramolecular approach for surface decoration with single-molecule magnets (SMMs) is presented. The self-assembly of SMMs is achieved through the formation of a multiple hydrogen bonds architecture (UPy-NaPy complexation). Finally we explore the possibility to impart auxetic behavior to polymeric material through the introduction of conformationally switchable monomers, namely tetraquinoxaline cavitands (QxCav). Their interconversion from a closed vase conformation to an extended kite form is studied first in solution, then in polymeric matrixes via pH and tensile stimuli by UV-Vis spectroscopy.

Hand gesture recognition based on morphologic features

Comunicación presentada en el IX Simposium Nacional de Reconocimiento de Formas y Análisis de Imágenes, Benicàssim, Mayo, 2001.

A connectionist computational method for face recognition

In this work, a modified version of the elastic bunch graph matching (EBGM) algorithm for face recognition is introduced. First, faces are detected by using a fuzzy skin detector based on the RGB color space. Then, the fiducial points for the facial graph are extracted automatically by adjusting a grid of points to the result of an edge detector. After that, the position of the nodes, their relation with their neighbors and their Gabor jets are calculated in order to obtain the feature vector defining each face. A self-organizing map (SOM) framework is shown afterwards. Thus, the calculation of the winning neuron and the recognition process are performed by using a similarity function that takes into account both the geometric and texture information of the facial graph. The set of experiments carried out for our SOM-EBGM method shows the accuracy of our proposal when compared with other state-of the-art methods.