Developing Alternative Methods for Urban Imageability Research

This paper discusses the devising of an alternative data collection technique for a research project that investigated the urban imageability of the World Heritage City of Kandy in Sri Lanka. Kevin Lynch argues that people form mental images of environments based on environments’ noticeable features, spatial relationships of those features, and the meanings attributed to the environment and its features. The overall capacity of the environment, derived by these attributes, in evoking strong mental schemata of it is called the imageability of the place. Any research on city image and imageability should derive data on these attributes of identity, structure, and meaning of the place imageability. The usual methods followed, such as mapping, verbal direction-giving, map construction, distance/direction judgment, picture recognition, and simulation techniques, are primarily focused on eliciting the visuo-spatial schema and are analyzed appropriately with quantitative methods. However, these methods have severe limitations in different cultural settings. Moreover, these conventional quantitative methods have limitations with regard to eliciting knowledge of environmental meanings. Since environmental meanings are too numerous and people’s interpretation of them is context-dependent – subjective, cultural, and changeable over time - the type of data required to be rich in detail, embedded in the context, and describe the participants’ subjective and cultural biases in meaning construction. This required using qualitative approaches as adopted in research in the fields of anthropology, social studies, and human geography in order to elicit meanings. The current study, therefore, followed an ethnographic design primarily involving interviewing along with a modified version of the free listing survey technique adopted from cognitive anthropological research into cultural domain analysis in order to derive both visuo-spatial information and environmental meanings. The free listing survey proved to be very valuable for the study. It is an easy task to perform by anyone; it elicits more information on people’s image of an environment than other popularly-used elicitation techniques, such as sketch mapping and map-making exercises; and it is also useful in devising measures to evaluate the saliency of imageability of city features that cannot be achieved through most of the usual methods. With the free list method, it was easy to define the consensual city image, its core/periphery, and its structure. I found that the combined form of free list survey and semi-structured interview method is an effective alternative to widely-used mapping techniques in urban imageability research

Perceiving conspecifics as integrated body-gestalts is an embodied process.

We investigated the effect of posture congruence on social perception. Specifically, we tested the hypothesis that completing "body gestalts," rather than being a purely visual process, is mediated by congruence in the postures of observer and stimulus. We developed novel stimuli showing a face and 2 hands that could be combined in various ways to form "body gestalts" implying different postures. In 3 experiments we found that imitative finger movements were consistently faster when the observer's posture matched the posture implied by the configuration of face and hands shown onscreen, suggesting that participants intuitively used their own body schema to "fill in the gaps" in the stimuli. Besides shaping how humans perceive others' bodies, embodied body-gestalt (eBG) completion may be an essential social and survival mechanism, for example, allowing for quick recovery from deceptive actions. It may also partly explain why humans subconsciously align themselves in everyday interactions: This might facilitate optimal corepresentation at higher, conscious levels

Complex networks in brain electrical activity

We analyze the complex networks associated with brain electrical activity. Multichannel EEG measurements are first processed to obtain 3D voxel activations using the tomographic algorithm LORETA. Then, the correlation of the current intensity activation between voxel pairs is computed to produce a voxel cross-correlation coefficient matrix. Using several correlation thresholds, the cross-correlation matrix is then transformed into a network connectivity matrix and analyzed. To study a specific example, we selected data from an earlier experiment focusing on the MMN brain wave. The resulting analysis highlights significant differences between the spatial activations associated with Standard and Deviant tones, with interesting physiological implications. When compared to random data networks, physiological networks are more connected, with longer links and shorter path lengths. Furthermore, as compared to the Deviant case, Standard data networks are more connected, with longer links and shorter path lengths--i.e., with a stronger ``small worlds'' character. The comparison between both networks shows that areas known to be activated in the MMN wave are connected. In particular, the analysis supports the idea that supra-temporal and inferior frontal data work together in the processing of the differences between sounds by highlighting an increased connectivity in the response to a novel sound.Comment: 22 pages, 5 figures. Starlab preprint. This version is an attempt to include better figures (no content change

A hierarchical system for a distributed representation of the peripersonal space of a humanoid robot

Reaching a target object in an unknown and unstructured environment is easily performed by human beings. However, designing a humanoid robot that executes the same task requires the implementation of complex abilities, such as identifying the target in the visual field, estimating its spatial location, and precisely driving the motors of the arm to reach it. While research usually tackles the development of such abilities singularly, in this work we integrate a number of computational models into a unified framework, and demonstrate in a humanoid torso the feasibility of an integrated working representation of its peripersonal space. To achieve this goal, we propose a cognitive architecture that connects several models inspired by neural circuits of the visual, frontal and posterior parietal cortices of the brain. The outcome of the integration process is a system that allows the robot to create its internal model and its representation of the surrounding space by interacting with the environment directly, through a mutual adaptation of perception and action. The robot is eventually capable of executing a set of tasks, such as recognizing, gazing and reaching target objects, which can work separately or cooperate for supporting more structured and effective behaviors