12,118 research outputs found

    Learning, Arts, and the Brain: The Dana Consortium Report on Arts and Cognition

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    Reports findings from multiple neuroscientific studies on the impact of arts training on the enhancement of other cognitive capacities, such as reading acquisition, sequence learning, geometrical reasoning, and memory

    Music adapting to the brain: From diffusion chains to neurophysiology

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    During the last decade, the use of experimental approaches on cultural evolution research has provided novel insights, and supported theoretical predictions, on the principles driving the evolution of human cultural systems. Laboratory simulations of language evolution showed how general-domain constraints on learning, in addition to pressures for language to be expressive, may be responsible for the emergence of linguistic structure. Languages change when culturally transmitted, adapting to fit, among all, the cognitive abilities of their users. As a result, they become regular and compressed, easier to acquire and reproduce. Although a similar theory has been recently extended to the musical domain, the empirical investigation in this field is still scarce. In addition, no study to our knowledge directly addressed the role of cognitive constraints in cultural transmission with neurophysiological investigation. In my thesis I addressed both these issues with a combination of behavioral and neurophysiological methods, in three experimental studies. In study 1 (Chapter 2), I examined the evolution of structural regularities in artificial melodic systems while they were being transmitted across individuals via coordination and alignment. To this purpose I used a new laboratory model of music transmission: the multi-generational signaling games (MGSGs), a variant of the signaling games. This model combines classical aspects of lab-based semiotic models of communication, coordination and interaction (horizontal transmission), with the vertical transmission across generations of the iterated learning model (vertical transmission). Here, two-person signaling games are organized in diffusion chains of several individuals (generations). In each game, the two players (a sender and a receiver) must agree on a common code - here a miniature system where melodic riffs refer to emotions. The receiver in one game becomes the sender in the next game, possibly retransmitting the code previously learned to another generation of participants, and so on to complete the diffusion chain. I observed the gradual evolution of several structures features of musical phrases over generations: proximity, continuity, symmetry, and melodic compression. Crucially, these features are found in most of musical cultures of the world. I argue that we tapped into universal processing mechanisms of structured sequence processing, possibly at work in the evolution of real music. In study 2 (Chapter 3), I explored the link between cultural adaptation and neural information processing. To this purpose, I combined behavioral and EEG study on 2 successive days. I show that the latency of the mismatch negativity (MMN) recorded in a pre-attentive auditory sequence processing task on day 1, predicts how well participants learn and transmit an artificial tone system with affective semantics in two signaling games on day 2. Notably, MMN latencies also predict which structural changes are introduced by participants into the artificial tone system. In study 3 (Chapter 4), I replicated and extended behavioral and neurophysiological findings on the temporal domain of music, with two independent experiments. In the first experiment, I used MGSGs as a laboratory model of cultural evolution of rhythmic equitone patterns referring to distinct emotions. As a result of transmission, rhythms developed a universal property of music structure, namely temporal regularity (or isochronicity). In the second experiment, I anchored this result with neural predictors. I showed that neural information processing capabilities of individuals, as measured with the MMN on day 1, can predict learning, transmission, and regularization of rhythmic patterns in signaling games on day 2. In agreement with study 2, I observe that MMN brain timing may reflect the efficiency of sensory systems to process auditory patterns. Functional differences in those systems, across individuals, may produce a different sensitivity to pressures for regularities in the cultural system. Finally, I argue that neural variability can be an important source of variability of cultural traits in a population. My work is the first to systematically describe the emergence of structural properties of melodic and rhythmic systems in the laboratory, using an explicit game-theoretic model of cultural transmission in which agents freely interact and exchange information. Critically, it provides the first demonstration that social learning, transmission, and cultural adaptation are constrained and driven by individual differences in the functional organization of sensory systems

    Annotated Bibliography: Anticipation

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    Directional adposition use in English, Swedish and Finnish

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    Directional adpositions such as to the left of describe where a Figure is in relation to a Ground. English and Swedish directional adpositions refer to the location of a Figure in relation to a Ground, whether both are static or in motion. In contrast, the Finnish directional adpositions edellĂ€ (in front of) and jĂ€ljessĂ€ (behind) solely describe the location of a moving Figure in relation to a moving Ground (Nikanne, 2003). When using directional adpositions, a frame of reference must be assumed for interpreting the meaning of directional adpositions. For example, the meaning of to the left of in English can be based on a relative (speaker or listener based) reference frame or an intrinsic (object based) reference frame (Levinson, 1996). When a Figure and a Ground are both in motion, it is possible for a Figure to be described as being behind or in front of the Ground, even if neither have intrinsic features. As shown by Walker (in preparation), there are good reasons to assume that in the latter case a motion based reference frame is involved. This means that if Finnish speakers would use edellĂ€ (in front of) and jĂ€ljessĂ€ (behind) more frequently in situations where both the Figure and Ground are in motion, a difference in reference frame use between Finnish on one hand and English and Swedish on the other could be expected. We asked native English, Swedish and Finnish speakers’ to select adpositions from a language specific list to describe the location of a Figure relative to a Ground when both were shown to be moving on a computer screen. We were interested in any differences between Finnish, English and Swedish speakers. All languages showed a predominant use of directional spatial adpositions referring to the lexical concepts TO THE LEFT OF, TO THE RIGHT OF, ABOVE and BELOW. There were no differences between the languages in directional adpositions use or reference frame use, including reference frame use based on motion. We conclude that despite differences in the grammars of the languages involved, and potential differences in reference frame system use, the three languages investigated encode Figure location in relation to Ground location in a similar way when both are in motion. Levinson, S. C. (1996). Frames of reference and Molyneux’s question: Crosslingiuistic evidence. In P. Bloom, M.A. Peterson, L. Nadel & M.F. Garrett (Eds.) Language and Space (pp.109-170). Massachusetts: MIT Press. Nikanne, U. (2003). How Finnish postpositions see the axis system. In E. van der Zee & J. Slack (Eds.), Representing direction in language and space. Oxford, UK: Oxford University Press. Walker, C. (in preparation). Motion encoding in language, the use of spatial locatives in a motion context. Unpublished doctoral dissertation, University of Lincoln, Lincoln. United Kingdo

    Dissociation and interpersonal autonomic physiology in psychotherapy research: an integrative view encompassing psychodynamic and neuroscience theoretical frameworks

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    Interpersonal autonomic physiology is an interdisciplinary research field, assessing the relational interdependence of two (or more) interacting individual both at the behavioral and psychophysiological levels. Despite its quite long tradition, only eight studies since 1955 have focused on the interaction of psychotherapy dyads, and none of them have focused on the shared processual level, assessing dynamic phenomena such as dissociation. We longitudinally observed two brief psychodynamic psychotherapies, entirely audio and video-recorded (16 sessions, weekly frequency, 45 min.). Autonomic nervous system measures were continuously collected during each session. Personality, empathy, dissociative features and clinical progress measures were collected prior and post therapy, and after each clinical session. Two-independent judges, trained psychotherapist, codified the interactions\u2019 micro-processes. Time-series based analyses were performed to assess interpersonal synchronization and de-synchronization in patient\u2019s and therapist\u2019s physiological activity. Psychophysiological synchrony revealed a clear association with empathic attunement, while desynchronization phases (range of length 30-150 sec.) showed a linkage with dissociative processes, usually associated to the patient\u2019s narrative core relational trauma. Our findings are discussed under the perspective of psychodynamic models of Stern (\u201cpresent moment\u201d), Sander, Beebe and Lachmann (dyad system model of interaction), Lanius (Trauma model), and the neuroscientific frameworks proposed by Thayer (neurovisceral integration model), and Porges (polyvagal theory). The collected data allows to attempt an integration of these theoretical approaches under the light of Complex Dynamic Systems. The rich theoretical work and the encouraging clinical results might represents a new fascinating frontier of research in psychotherapy

    Event segmentation and biological motion perception in watching dance

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    We used a combination of behavioral, computational vision and fMRI methods to examine human brain activity while viewing a 386 s video of a solo Bharatanatyam dance. A computational analysis provided us with a Motion Index (MI) quantifying the silhouette motion of the dancer throughout the dance. A behavioral analysis using 30 naĂŻve observers provided us with the time points where observers were most likely to report event boundaries where one movement segment ended and another began. These behavioral and computational data were used to interpret the brain activity of a different set of 11 naĂŻve observers who viewed the dance video while brain activity was measured using fMRI. Results showed that the Motion Index related to brain activity in a single cluster in the right Inferior Temporal Gyrus (ITG) in the vicinity of the Extrastriate Body Area (EBA). Perception of event boundaries in the video was related to the BA44 region of right Inferior Frontal Gyrus as well as extensive clusters of bilateral activity in the Inferior Occipital Gyrus which extended in the right hemisphere towards the posterior Superior Temporal Sulcus (pSTS)

    Symbol Emergence in Robotics: A Survey

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    Humans can learn the use of language through physical interaction with their environment and semiotic communication with other people. It is very important to obtain a computational understanding of how humans can form a symbol system and obtain semiotic skills through their autonomous mental development. Recently, many studies have been conducted on the construction of robotic systems and machine-learning methods that can learn the use of language through embodied multimodal interaction with their environment and other systems. Understanding human social interactions and developing a robot that can smoothly communicate with human users in the long term, requires an understanding of the dynamics of symbol systems and is crucially important. The embodied cognition and social interaction of participants gradually change a symbol system in a constructive manner. In this paper, we introduce a field of research called symbol emergence in robotics (SER). SER is a constructive approach towards an emergent symbol system. The emergent symbol system is socially self-organized through both semiotic communications and physical interactions with autonomous cognitive developmental agents, i.e., humans and developmental robots. Specifically, we describe some state-of-art research topics concerning SER, e.g., multimodal categorization, word discovery, and a double articulation analysis, that enable a robot to obtain words and their embodied meanings from raw sensory--motor information, including visual information, haptic information, auditory information, and acoustic speech signals, in a totally unsupervised manner. Finally, we suggest future directions of research in SER.Comment: submitted to Advanced Robotic

    Towards a Novel Generation of Haptic and Robotic Interfaces: Integrating Active Physiology in Human-Robot Interaction

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    Haptic interfaces are special robots that interact with people to convey touch-related information. In addition to such a discriminative aspect, touch is also a highly emotion-related sense. However, while a lot of effort has been spent to investigate the perceptual mechanisms of discriminative touch and to suitably replicate them through haptic systems in human robot interaction (HRI), there is still a lot of work to do in order to take into account also the emotional aspects of tactual experience (i.e., the so-called affective haptics), for a more naturalistic human-robot communication. In this paper, we report evidences on how a haptic device designed to convey caress-like stimuli can influence physiological measures related to the autonomous nervous system (ANS), which is intimately connected to evoked emotions in humans. Specifically, a discriminant role of electrodermal response and heart rate variability can be associated to two different caressing velocities, which can also be linked to two different levels of pleasantness. Finally, we discuss how the results from this study could be profitably employed and generalized to pave the path towards a novel generation of robotic devices for HRI

    SEAI: Social Emotional Artificial Intelligence Based on Damasio's Theory of Mind

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    A socially intelligent robot must be capable to extract meaningful information in real-time from the social environment and react accordingly with coherent human-like behaviour. Moreover, it should be able to internalise this information, to reason on it at a higher abstract level, build its own opinions independently and then automatically bias the decision-making according to its unique experience. In the last decades, neuroscience research highlighted the link between the evolution of such complex behaviour and the evolution of a certain level of consciousness, which cannot leave out of a body that feels emotions as discriminants and prompters. In order to develop cognitive systems for social robotics with greater human-likeliness, we used an "understanding by building" approach to model and implement a well-known theory of mind in the form of an artificial intelligence, and we tested it on a sophisticated robotic platform. The name of the presented system is SEAI (Social Emotional Artificial Intelligence), a cognitive system specifically conceived for social and emotional robots. It is designed as a bio-inspired, highly modular, hybrid system with emotion modelling and high-level reasoning capabilities. It follows the deliberative/reactive paradigm where a knowledge-based expert system is aimed at dealing with the high-level symbolic reasoning, while a more conventional reactive paradigm is deputed to the low-level processing and control. The SEAI system is also enriched by a model which simulate the Damasio's theory of consciousness and the theory of Somatic Markers. After a review of similar bio-inspired cognitive systems, we present the scientific foundations and their computational formalisation at the basis of the SEAI framework. Then, a deeper technical description of the architecture is disclosed underlining the numerous parallelisms with the human cognitive system. Finally, the influence of artificial emotions and feelings, and their link with the robot's beliefs and decisions have been tested in a physical humanoid involved in Human-Robot Interaction (HRI)
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