Concept of Regional Security in Philosophical Approaches

The paper focuses on regional security, which has become a significant issue in situations where there has been a growth in the level of regional identity and the desire for relative autonomy in the general pro- cess of security system development. The approaches to security in the history of philosophy are analyzed in order to highlight the evolution of the concept of “regional security”. Comparative, systematic and her- meneutic methods are employed to reveal the aspects of regional security in terms of the problems of state, national and public security. The novelty of the research is associated with the development of the evolu- tion of ideas concerning regional security from abstract representations to the various aspects of regional practice. The conclusion is that modern regional security concepts are based on the synthesis of the meth- odology of systemic and constructivist approaches. This methodology is used to substantiate the claim that any state has to deal with the security problems of its regions and pay attention to any threats and regional interests, which may be constructible in nature, and pose a real danger associated with challenges from political, economic, military, environmental, and social spheres.

Abstract representations emerge naturally in neural networks trained to perform multiple tasks

Humans and other animals demonstrate a remarkable ability to generalize knowledge across distinct contexts and objects during natural behavior. We posit that this ability depends on the geometry of the neural population representations of these objects and contexts. Specifically, abstract, or disentangled, neural representations -- in which neural population activity is a linear function of the variables important for making a decision -- are known to allow for this kind of generalization. Further, recent neurophysiological studies have shown that the brain has sufficiently abstract representations of some sensory and cognitive variables to enable generalization across distinct contexts. However, it is unknown how these abstract representations emerge. Here, using feedforward neural networks, we demonstrate a simple mechanism by which these abstract representations can be produced: The learning of multiple distinct classification tasks. We demonstrate that, despite heterogeneity in the task structure, abstract representations that enable reliable generalization can be produced from a variety of different inputs -- including standard nonlinearly mixed inputs, inputs that mimic putative representations from early sensory areas, and even simple image inputs from a standard machine learning data set. Thus, we conclude that abstract representations of sensory and cognitive variables emerge from the multiple behaviors that animals exhibit in the natural world, and may be pervasive in high-level brain regions. We make several specific predictions about which variables will be represented abstractly as well as show how these representations can be detected.

Learning of biased representations in LIP through interactions between recurrent connectivity and Hebbian plasticity

When monkeys learn to group visual stimuli into arbitrary categories, lateral intraparietal area (LIP) neurons become category-selective. Surprisingly, the representations of learned categories are overwhelmingly biased: nearly all LIP neurons in a given animal prefer the same category over other behaviorally equivalent categories. We propose a model where such biased representations develop through the interplay between Hebbian plasticity and the recurrent connectivity of LIP. In this model, two separable processes of positive feedback unfold in parallel: in one, category selectivity emerges from competition between prefrontal inputs; in the other, bias develops due to lateral interactions among LIP neurons. This model reproduces the levels of category selectivity and bias observed under a variety of conditions, as well as the redevelopment of bias after monkeys learn redefined categories. It predicts that LIP receptive fields would spatially cluster by preferred category, which we experimentally confirm. In summary, our model reveals a mechanism by which LIP learns abstract representations and assigns meaning to sensory inputs.

Emergent Interfaces: Vague, Complex, Bespoke and Embodied Interaction between Humans and Computers

Most Human–Computer Interfaces are built on the paradigm of manipulating abstract representations. This can be limiting when computers are used in artistic performance or as mediators of social connection, where we rely on qualities of embodied thinking: intuition, context, resonance, ambiguity and fluidity. We explore an alternative approach to designing interaction that we call the emergent interface: interaction leveraging unsupervised machine learning to replace designed abstractions with contextually derived emergent representations. The approach offers opportunities to create interfaces bespoke to a single individual, to continually evolve and adapt the interface in line with that individual’s needs and affordances, and to bridge more deeply with the complex and imprecise interaction that defines much of our non-digital communication. We explore this approach through artistic research rooted in music, dance and AI with the partially emergent system Sonified Body. The system maps the moving body into sound using an emergent representation of the body derived from a corpus of improvised movement from the first author. We explore this system in a residency with three dancers. We reflect on the broader implications and challenges of this alternative way of thinking about interaction, and how far it may help users avoid being limited by the assumptions of a system’s designer.

THE INFLUENCE OF DESIGN BRIEF INFORMATION ON CREATIVE OUTCOMES BY NOVICE AND ADVANCED STUDENTS

This study centers on using different types of brief information to support creative outcomes in architectural and engineering design and its relation to design expertise. We explore the influence of design briefs characterized by abstract representations and/or instructions to frame design problems on the creativity of concept sketches produced by novice and advanced students. Abstract representations of problem requirements served as stimuli to encourage associative thinking and knowledge transfer. The Ishikawa/Fishbone Diagram was used to foster design restructuring and to modify viewpoints about the main design drives and goals. The design outcomes generated by novice and advanced engineering/architecture students were assessed for their creativity using a pairwise experimental design. Results indicated that advanced students generated more novel design solutions while also contributing the most useful solutions overall. Implications for creativity in design education and professional practice are presented. Educational programs aimed at promoting creativity in the design studio may find it helpful to consider that the way design briefs are constructed can either promote or inhibit different aspects of design creativity.

Converging Evidence of Underlying Competence: Comprehension and Production in the Acquisition of Spanish Subject-Verb Agreement

A surprising comprehension-production asymmetry in subject-verb (SV) agreement acquisition has been suggested in the literature, and recent research indicates that task-specific as well as language-specific features may contribute to this apparent asymmetry across languages. The present study investigates when during development children acquiring Mexican Spanish gain competence with 3rd-person SV agreement, testing production as well as comprehension in the same children aged between 3;6 and 5;7 years, and whether comprehension of SV agreement is modulated by the sentential position of the verb (i.e., medial vs. final position). Accuracy and sensitivity analyses show that comprehension performance correlates with SV agreement production abilities, and that comprehension of singular and plural third-person forms is not influenced by the sentential position of the agreement morpheme. Issues of the appropriate outcome measure and the role of structural familiarity in the development of abstract representations are discussed.

Value signals guide abstraction during learning

The human brain excels at constructing and using abstractions, such as rules, or concepts. Here, in two fMRI experiments, we demonstrate a mechanism of abstraction built upon the valuation of sensory features. Human volunteers learned novel association rules based on simple visual features. Reinforcement-learning algorithms revealed that, with learning, high-value abstract representations increasingly guided participant behaviour, resulting in better choices and higher subjective confidence. We also found that the brain area computing value signals - the ventromedial prefrontal cortex - prioritized and selected latent task elements during abstraction, both locally and through its connection to the visual cortex. Such a coding scheme predicts a causal role for valuation. Hence, in a second experiment, we used multivoxel neural reinforcement to test for the causality of feature valuation in the sensory cortex, as a mechanism of abstraction. Tagging the neural representation of a task feature with rewards evoked abstraction-based decisions. Together, these findings provide a novel interpretation of value as a goal-dependent, key factor in forging abstract representations.

Understanding the Prefrontal Cortex

The primate prefrontal cortex sits at the top of the sensory, motor, and outcome processing hierarchies of the neocortex. It transforms sensory inputs into motor outputs, determining the response that is appropriate given the current context and desired outcome. This transformation involves conditional rules. The dorsal prefrontal cortex supports the learning of behavioural sequences, where the next action is conditional on the previous one. The ventral prefrontal cortex supports associations between objects, where the choice of one object is conditional on the presence of another object. However, because hierarchical processing supports the extraction of abstract representations, the primate prefrontal cortex is able to represent conditional rules that are abstract, meaning that they apply irrespective of the specific inputs. The selective advantage is that by learning these rules, primates can solve new problems rapidly when they have the same conditional logic as prior problems. The human prefrontal cortex has the same fundamental organization as in other primates. The dorsal prefrontal cortex supports the understanding of sequences and the ventral prefrontal cortex supports the ability to learn semantic associations. Thus the human prefrontal cortex has co-opted and elaborated mechanisms that were present in ancestral primates. These mechanisms can be used for new ends. For example, words have been associated with objects so as to communicate with others. This means that to understand human intelligence it is necessary to take into account the fact that the abstract rules are transmitted verbally from one generation to another.

Connecting Structure and Variation in Sound Change

“Structured heterogeneity”, a founding concept of variationist sociolinguistics, puts focus on the ordered social differentiation in language. We extend the notion of structured heterogeneity to formal phonological structure, i.e., representations based on contrasts, with implications for phonetic implementation. Phonology establishes parameters for what varies and how. Patterns of stability and variability with respect to a given feature’s relationship to representations allow us to ground variationist analysis in a framework that makes predictions about potential sound changes: more structure correlates to more stability; less structure corresponds to more variability. However, even though all change requires variability, not all variability leads to change. Two case studies illustrate this asymmetry, keeping a focus on phonetic change with phonological stability. First, Germanic rhotics (r-sounds) from prehistory to the present day are minimally specified. They show tremendous phonetic variability and change but phonological stability. Second, laryngeal contrasts (voicing or aspiration) vary and change in language contact. We track the accumulation of phonetic change in unspecified members of pairs of the type spelled <s> ≠ <z>, etc. This analysis makes predictions about the regularity of sound change, situating regularity in phonology and irregularity in phonetics and the lexicon. Structured heterogeneity involves the variation inherent within the system for various levels of phonetic and phonological representation. Phonological change, then, is about acquiring or learning different abstract representations based on heterogeneous and variable input.