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This paper presents an overview of a novel approach called Transcendental Psychology Methodology (TPM), largely inspired by Bach-y-Rita's work and developed by A.I. Mirakyan (1929–1995) and his associates. Beginning with the perceptual constancy problem, in which stimuli do not change perceptually despite variations in their physical characteristics, Mirakyan recognized that contemporary accounts of constancy included both theoretical contradictions and empirical discrepancies. This led him to propose TPM as an alternative to the traditional Product Basis Paradigm (PBP). Whilst PBP focuses upon perceptual phenomena, TPM focuses upon the underlying processes and upon the principles that support the flexibility needed to create complex, coherent representations under different stimulus conditions. The central idea that generative perceptual processes may be universal is grounded in Bach-y-Rita's famous experiments and has important parallels with present day conceptions of the construction of meaning in neurophysiological process. TPM inspired studies of a wide range of perceptual phenomena have so far suggested basic principles that can be applied to all perceptual processes, regardless of their modality. Its new conception of the perception of spatial extent can contribute to our understanding of the visual effects that Bach-y-Rita's blind subjects experience and it may provide a useful general tool for uncovering the psychological principles behind Bach-y-Rita's findings. Because of its axiomatic approach and its focus upon universal, generative processes, TPM may also be useful in other disciplines, e.g., in providing a line between neurophysiological and psychological levels of investigation. It may ultimately serve as a general theory of how sensory experience is created.

Behavioral and electrophysiological studies of schizophrenia have consistently demonstrated impairments in the integration of visual features into unified perceptual representations. Specific brain regions involved in this dysfunction, however, remain to be clarified. This study used functional Magnetic Resonance Imaging (fMRI) to examine the relative involvement of visual cortex areas (involved in form perception) and parietal and frontal regions (involved in attention), in the visual integration impairment in schizophrenia. Fourteen patients with schizophrenia and 14 healthy controls were compared on behavioral performance and data acquired via fMRI while completing a contour integration task that had previously been used to identify a visual integration deficit in schizophrenia. The schizophrenia patients demonstrated poorer visual integration than controls. Analyses of peak signal change indicated that while the groups were equivalent in area V1, the schizophrenia group demonstrated reduced signal in areas V2–V4, which are the earliest regions sensitive to global configurations of stimuli. Moreover, whereas the control group demonstrated greater recruitment of prefrontal and parietal areas during perception of integrated forms compared to random stimuli, the schizophrenia group demonstrated greater recruitment of frontal regions during perception of random stimuli. The two groups differed on brain regions involved in form perception even when they were matched on accuracy levels. The visual integration disturbance in schizophrenia involves both deficient basic visual processes (beginning as early as occipital region V2), as well as reduced feedback from visual attention regions that normally serves to amplify relevant visual representations relative to irrelevant information.

This paper explores the implications of a recently published theory that relates the experience of qualia to the attractor activity in networks of pyramidal cells in the cerebral cortex. The paper builds on this theory, and aims to link activity in different networks to the nature of the qualia experienced. Some basic links between network activity and qualia experiences are initially presented, showing the importance of learning, and the paper then proceeds to relate these mechanisms to the qualia experienced during sensory perception. The paper argues that attractor behavior in networks of layer 2/3 pyramidal neurons could underpin the vivid sensory qualia of perception, and attractor behavior in networks of layer 5A pyramidal neurons could have a role in the more understanding kind of perceptual qualia. Communication between these networks is explored to suggest their involvement in putting incoming sensory information into the context of all prior experience, and the understanding that could result.

Metacontrast is a form of visual masking in which the target and mask are non-overlapping. In metacontrast, the masking effect is typically largest when the mask is presented some time after the target. This is known as Type-B masking. The present report examines to what extent Type-B metacontrast masking can be explained based on the stimuli involved. The assumption is made that the visibility of the target is, at least in part, determined by the correlation between the amplitude spectrum of the target-and-mask combination and that of the target alone. It is found that the correlation is higher when the stimuli are presented at the same time relative to when they are presented at different times. This relationship follows from the stimuli alone. Thus, one would expect the masking to be weakest when the two stimuli are simultaneous. Type-B correlation functions, in which the largest reductions occur only when the mask is presented after the target, can be obtained by further assuming a temporal integration window with a rapid onset and a shallow decline. In agreement with psychophysical masking studies; the analyses yield functions that are most similar to Type-B masking for moderate mask intensities and become less Type-B like at higher mask intensities. The effects of dark adaptation and spatial separation of target and mask are also modeled.

The issue of integration in neural networks is intimately connected with that of consciousness. In this paper, integration as an effective level of physical organization is contrasted with a methodological integrative approach. Understanding how consciousness arises out of neural processes requires a model of integration in just causal physical terms. Based on a set of feasible criteria (physical grounding, causal efficacy, no circularity and scaling), a causal account of physical integration for consciousness centered on joint causation is outlined.

Functional significance of the neural oscillations has been debated since long. In particular, oscillations have been suggested to play a major role in formation of communication channels between brain regions. It has been previously suggested that gamma coherence increases during communication between hemispheres when subjects perceive a horizontal motion in Stroboscopic Alternative Motion (SAM) stimulus. In addition, disruption of this coherence may change the horizontal perception of SAM. In this study, we investigated the changes of Cross-Frequency Coupling (CFC) in EEG signals from parietal and occipital cortices during horizontal and vertical perception of SAM. Our results suggested that while the strength of CFC in parietal electrodes showed no significant change, CFC in P3-P4 electrode-pair demonstrated a significant correlation during horizontal perception of SAM. Therefore, the CFC between theta- and gamma-band oscillations seems to be correlated with changes in functional interactions between brain regions. Accordingly, we propose that in addition to gamma coherence, CFC is perhaps another neurophysiological mechanism involved in neural communication.

The object of this research is to present a theoretical model about the process of management perception of the factors which intervene in the export decision (strategic interest and accessibility to overseas markets). With that aim, the phases which constitute the perception process are identified — the selection of stimuli and interpretation — and the associated bias. Specifically, we identify two: bias by omission and bias by imprecise meaning. The use of different sources of information as well as the influence of the network of relations of the management allows us to investigate thoroughly the filters through which the informative stimuli pass which converge in the decision to export.

This paper aims to present what we call knowledge geometry, an alternative theory for spatial representation of features related to information processing, information management, and knowledge management. It is a unique geometric approach for representing intuition, reification, interpretation, and deduction processes, as well as their relations. We employ the concept of cultural filter and use what we call real, conceptual, and symbolic planes in order to support transformations which occur along the perception of a phenomenon. After that, we discuss the use of evaluation systems to judge concepts and also the use of semantic systems as a communication language. Finally, a framework of the knowledge acquisition process in the field of the proposed theory is offered, proving the feasibility of its automation.

The software industry depends intensively on its actor’s knowledge to develop its products. This knowledge is crucial to leverage innovation and market sustainability within the software industry companies. Knowledge Management (KM) processes are accomplished in the small- and medium-sized software industry companies daily, however, sometimes not formally. This paper proposes a questionnaire aimed to diagnose KM in small- and medium-sized enterprises (SME) of the software industry, namely, KMD Quest-SW. The KMD Quest-SW was designed to fill up the gap of KM diagnosis in SME in the software industry. The KMD Quest-SW has 46 statements distributed in six dimensions: so-called creation process, registration process, knowledge sharing, knowledge use, innovation process, and knowledge in the software industry. From the software industry perspective, our proposal appears as a promising tool to diagnose and map the knowledge flow in SMEs. From a scientific perspective, the questionnaire breaks new grounds for KM theoretically and practitioners to be adapted for other SME companies interested in KM.

Tourism-related messages can alter the images of tourism destinations. In the new media time, messages from individual perception of the destination can spread among the social networks. Here, based on three basic assumptions, we developed a model to investigate the spread dynamics of tourism-related messages. In the model, two variables of individual behaviour, representing the probabilities of sharing or forgetting the messages, respectively, and a variable to represent the message’s importance were integrated. Within the simulated small-world networks, we observed two distinct patterns in the spread dynamics. The patterns were determined by individuals’ willingness to share messages and the message’s importance. If a majority of people choose not to send a message that they have received, the informed population will eventually become negligible; whereas, while they are inclined to spread, the informed population will remain constant over time. These patterns were influenced by neither the density of network connections nor the message sources. The message sources only determine the speed and the scale of diffusion. In summary, our model revealed the patterns of the spread of tourism-related messages.

Switching from traditional to online learning during the COVID-19 pandemic bore the associated opportunities and challenges. The study presents the clout of Perception, Emotion, Attitude, Teacher-Student, and Peer interaction on Learner Satisfaction (LS) partially mediated by motivation among business management students of Russia, India, and Bangladesh. The psychological framework used in the study, followed by Structural Equation Modelling, displayed a significant association between all exogenous and endogenous variables. The responses from the 1008 students during the pandemic corroborate two critical learning theories, i.e. Social Constructivism and Media Richness Theory, by confirming a significant and positive relationship between attitude and motivation. The learners’ perception of the content and administration is pivotal for LS. Whereas peer learning was an important aspect in Russia and India, assisted learning was preferred by the students of Bangladesh.

This paper gives an overview on current and forthcoming research activities of the Collaborative Research Center 588 "Humanoid Robots — Learning and Cooperating Multimodal Robots" which is located in Karlsruhe, Germany. Its research activities can be divided into the following areas: mechatronic robot system components like lightweight 7 DOF arms, 5-fingered dexterous hands, an active sensor head and a spine type central body and skills of the humanoid robot system; multimodal man-machine interfaces; augmented reality for modeling and simulation of robots, environment and user; and finally, cognitive abilities. Some of the research activities are described in this paper, and we introduce the application scenario testing the robot system. In particular, we present a robot teaching center and the execution which is of type "household."

This paper gives an overview of the current and forthcoming research projects of the Collaborative Research Center 588 "Humanoid Robots — Learning and Cooperating Multimodal Robots." The activities can be divided into several areas: development of mechatronic components and construction of a demonstrator system, perception of user and environment, modeling and simulation of robots, environment and user, and finally cooperation and learning. The research activities in each of these areas are described in detail. Finally, we give an insight into the application scenario of our robot system, i.e. the training setup and the experimental setup "household."

As computer vision enables the robot to be aware of its human counterpart, such algorithms could help machines to achieve human-like interaction. However, many video tracking algorithms are not able to cope with some robot vision requirements. The articulated tracking system we develop solves some of those issues. It relies on model-based algorithms, which we believe are more suitable to robot vision than appearance-based ones. Indeed, as they update all the relevant parameters of a surrounding world model, results include some knowledge of the camera and objects relative positions. Our system relies on 3D model silhouette matching and runs in real time. We increase the algorithm robustness by introducing a pre-processing step based on image moments. This allows the iteration refinement to start in a better position by roughly estimating the body motion from one frame to the next.

A distinct property of robot vision systems is that they are embodied. Visual information is extracted for the purpose of moving in and interacting with the environment. Thus, different types of perception-action cycles need to be implemented and evaluated.

In this paper, we study the problem of designing a vision system for the purpose of object grasping in everyday environments. This vision system is firstly targeted at the interaction with the world through recognition and grasping of objects and secondly at being an interface for the reasoning and planning module to the real world. The latter provides the vision system with a certain task that drives it and defines a specific context, i.e. search for or identify a certain object and analyze it for potential later manipulation. We deal with cases of: (i) known objects, (ii) objects similar to already known objects, and (iii) unknown objects. The perception-action cycle is connected to the reasoning system based on the idea of affordances. All three cases are also related to the state of the art and the terminology in the neuroscientific area.

Robust vision in dynamic environments using limited processing power is one of the main challenges in robot vision. This is especially true in the case of biped humanoids that use low-end computers. Techniques such as active vision, context-based vision, and multi-resolution are currently in use to deal with these highly demanding requirements. Thus, having as main motivation the development of robust and high performing robot vision systems, which can operate in dynamic environments, with limited computational resources, we propose a spatiotemporal context integration framework that improves the perceptual capabilities of a given robot vision system. Furthermore, we try to link the vision, tracking, and self-localization problems using a context filter to improve the performance of all these parts together more than to improve them separately. This framework computes: (i) an estimation of the poses of visible and nonvisible objects using Kalman filters; (ii) the spatial coherence of each current detection with all other simultaneous detections and with all tracked objects; and (iii) the spatial coherence of each tracked object with all current detections. Using a Bayesian approach, we calculate the a-posteriori probabilities for each detected and tracked object, which is used in a filtering stage. We choose as a first application of this framework, the detection of static objects in the RoboCup Standard Platform League domain, where Nao humanoid robots are employed. The proposed system is validated in simulations and using real video sequences. In noisy environments, the system is able to decrease largely the number of false detections and to improve effectively the self-localization of the robot.

A key support mechanism for early-stage entrepreneurs is business incubator programs, which provide tailored assistance and a conducive work environment for new business development. However, incubators are not created equal in terms of their effectiveness and reach. Extant research on business incubation is also largely gender-neutral. In addition, a scholarly gap exists when it comes to our understanding of the cognitive, behavioral and socio-cultural barriers to incubation and entrepreneurship. This research contributes to filling this gap by designing a pre-experiential behavioral intention model rooted in social psychology theories to explain the entrepreneur’s intention to participate in incubation programs. A multidimensional construct of perception and its underlying dimensions (e.g., usefulness, ease of use and self-efficacy) is developed and tested. Studying 344 early-stage entrepreneurs, it is found that perceived utility and ease of use relate to the decision to join an incubation program. Furthermore, when female entrepreneurs are not convinced whether incubation programs are beneficial considering their use and access, they are less likely to join incubation. Our empirical results highlight the need for adopting behavioral interventions and inclusionary best practices to expand the effect of business incubation programs.

This paper describes and provides support for a non-representational theory of perception called the Fractal Catalytic theory, which proposes that perception is a catalytic type of process that occurs at multiple scales.¹ Enzyme catalysis involves a vibratory facilitation of a reaction. A catalytic model for smell at the molecular level is supported by evidence that smell involves a vibratory process.² This type of facilitation can be generalized to the neural level, where many neuroscientists have observed vibratory neural patterns. At the level of the organism, we describe research with blind individuals who experience a visuo-spatial world through patterns of sounds or tactile vibrations. Such research argues against the standard theory that people are representing objects and events, and supports the view that experience arises as an organism mediates (catalyzes) the transitions in its surround. The theory relates to the biologically-grounded theory of Autopoiesis³ as well as proposals that catalysis is central in biological evolution. We examine the implications of this theory for the nature of consciousness.

Successes of information and cognitive science brought a growing understanding that mind is based on intelligent cognitive processes, which are not limited by language and logic only. A nice overview can be found in the excellent work of Jeff Hawkins "On Intelligence." This view is that thought is a set of informational processes in the brain, and such processes have the same rationale as any other systematic informational processes. Their specifics are determined by the ways of how brain stores, structures and process this information. Systematic approach allows representing them in a diagrammatic form that can be formalized and programmed. Semiotic approach allows for the universal representation of such diagrams. In our approach, logic is just a way of synthesis of such structures, which is a small but clearly visible top of the iceberg. However, most of the efforts were traditionally put into logics without paying much attention to the rest of the mechanisms that make the entire thought system working autonomously. Dynamic fuzzy logic is reviewed and its connections with semiotics are established. Dynamic fuzzy logic extends fuzzy logic in the direction of logic-processes, which include processes of fuzzification and defuzzification as parts of logic. This extension of fuzzy logic is inspired by processes in the brain-mind. The paper reviews basic cognitive mechanisms, including instinctual drives, emotional and conceptual mechanisms, perception, cognition, language, a model of interaction between language and cognition upon the new semiotic models. The model of interacting cognition and language is organized in an approximate hierarchy of mental representations from sensory percepts at the "bottom" to objects, contexts, situations, abstract concepts-representations, and to the most general representations at the "top" of mental hierarchy. Knowledge instinct and emotions are driving feedbacks for these representations. Interactions of bottom-up and top-down processes in such hierarchical semiotic representation are essential for modeling cognition. Dynamic fuzzy logic is analyzed as a fundamental mechanism of these processes. In this paper we are trying to formalize cognitive processes of the human mind using approaches above, and provide interfaces that could allow for their practical realization in software and hardware. Future research directions are discussed.

Engineering self-conscious robotic systems is a challenging issue because of the intrinsic complexity of such systems; a self-conscious robot has to acquire knowledge, to understand its world and to autonomously interact with its environment. In this paper, the externalist point of view is used for developing a complete process for the design and implementation of a conscious robotic system that is able to interact with a dynamic environment in a human-like fashion without possessing detailed knowledge about the environment and pre-programmed tasks and algorithms. The paper mainly focuses on the configuration part of the whole process that make the robot able to decide and to learn from experiences.