Role of the monkey ventrolateral prefrontal cortex in the integration of contextual information for the selection and understanding of goal-directed actions

Action selection and organization are very complex processes that need to exploit contextual information and the retrieval of previously memorized information, as well as the integration of these different types of data. On the basis of anatomical connection with premotor and parietal areas involved in action goal coding, and on the data about the literature it seems appropriate to suppose that one of the most candidate involved in the selection of neuronal pools for the selection and organization of intentional actions is the prefrontal cortex. We recorded single ventrolateral prefrontal (VLPF) neurons activity while monkeys performed simple and complex manipulative actions aimed at distinct final goals, by employing a modified and more strictly controlled version of the grasp-to-eat(a food pellet)/grasp-to-place(an object) paradigm used in previous studies on parietal (Fogassi et al., 2005) and premotor neurons (Bonini et al., 2010). With this task we have been able both to evaluate the processing and integration of distinct (visual and auditory) contextual sequentially presented information in order to select the forthcoming action to perform and to examine the possible presence of goal-related activity in this portion of cortex. Moreover, we performed an observation task to clarify the possible contribution of VLPF neurons to the understanding of others’ goal-directed actions. Simple Visuo Motor Task (sVMT). We found four main types of neurons: unimodal sensory-driven, motor-related, unimodal sensory-and-motor, and multisensory neurons. We found a substantial number of VLPF neurons showing both a motor-related discharge and a visual presentation response (sensory-and-motor neurons), with remarkable visuo-motor congruence for the preferred target. Interestingly the discharge of multisensory neurons reflected a behavioural decision independently from the sensory modality of the stimulus allowing the monkey to make it: some encoded a decision to act/refraining from acting (the majority), while others specified one among the four behavioural alternatives. Complex Visuo Motor Task (cVMT). The cVMT was similar to the sVMT, but included a further grasping motor act (grasping a lid in order to remove it, before grasping the target) and was run in two modalities: randomized and in blocks. Substantially, motor-related and sensory-and-motor neurons tested in the cVMTrandomized were activated already during the first grasping motor act, but the selectivity for one of the two graspable targets emerged only during the execution of the second grasping. In contrast, when the cVMT was run in block, almost all these neurons not only discharged during the first grasping motor act, but also displayed the same target selectivity showed in correspondence of the hand contact with the target. Observation Task (OT). A great part of the neurons active during the OT showed a firing rate modulation in correspondence with the action performed by the experimenter. Among them, we found neurons significantly activated during the observation of the experimenter’s action (action observation-related neurons) and neurons responding not only to the action observation, but also to the presented cue stimuli (sensory-and-action observation-related neurons. Among the neurons of the first set, almost the half displayed a target selectivity, with a not clear difference between the two presented targets; Concerning to the second neuronal set, sensory-and-action related neurons, we found a low target selectivity and a not strictly congruence between the selectivity exhibited in the visual response and in the action observation.

Towards a unified framework for opinion retrieval, mining and summarization

The exponential increase of subjective, user-generated content since the birth of the Social Web, has led to the necessity of developing automatic text processing systems able to extract, process and present relevant knowledge. In this paper, we tackle the Opinion Retrieval, Mining and Summarization task, by proposing a unified framework, composed of three crucial components (information retrieval, opinion mining and text summarization) that allow the retrieval, classification and summarization of subjective information. An extensive analysis is conducted, where different configurations of the framework are suggested and analyzed, in order to determine which is the best one, and under which conditions. The evaluation carried out and the results obtained show the appropriateness of the individual components, as well as the framework as a whole. By achieving an improvement over 10% compared to the state-of-the-art approaches in the context of blogs, we can conclude that subjective text can be efficiently dealt with by means of our proposed framework.

The utilitarian and hedonic outcomes of music information seeking in everyday life

This qualitative study focuses on what contributes to making a music information-seeking experience satisfying in the context of everyday life. Data were collected through in-depth interviews conducted with 15 younger adults (18 to 29 years old). The analysis revealed that satisfaction could depend on both hedonic (i.e., experiencing pleasure) and utilitarian outcomes. It was found that two types of utilitarian outcomes contributed to satisfaction: (1) the acquisition of music, and (2) the acquisition of information about music. Information about music was gathered to (1) enrich the listening experience, (2) increase one's music knowledge, and/or (3) optimize future acquisition. This study contributes to a better understanding of music information-seeking behavior in recreational contexts. It also has implications for music information retrieval systems design: results suggest that these systems should be engaging, include a wealth of extra-musical information, allow users to navigate among music items, and encourage serendipitous encountering of music.

The utilitarian and hedonic outcomes of music information seeking in everyday life

This qualitative study focuses on what contributes to making a music information-seeking experience satisfying in the context of everyday life. Data were collected through in-depth interviews conducted with 15 younger adults (18 to 29 years old). The analysis revealed that satisfaction could depend on both hedonic (i.e., experiencing pleasure) and utilitarian outcomes. It was found that two types of utilitarian outcomes contributed to satisfaction: (1) the acquisition of music, and (2) the acquisition of information about music. Information about music was gathered to (1) enrich the listening experience, (2) increase one's music knowledge, and/or (3) optimize future acquisition. This study contributes to a better understanding of music information-seeking behavior in recreational contexts. It also has implications for music information retrieval systems design: results suggest that these systems should be engaging, include a wealth of extra-musical information, allow users to navigate among music items, and encourage serendipitous encountering of music.

Digital Classics Outside the Echo-Chamber : Teaching, Knowledge Exchange and Public Engagement /

The international perspectives on these issues are especially valuable in an increasingly connected, but still institutionally and administratively diverse world. The research addressed in several chapters in this volume includes issues around technical standards bodies like EpiDoc and the TEI, engaging with ways these standards are implemented, documented, taught, used in the process of transcribing and annotating texts, and used to generate publications and as the basis for advanced textual or corpus research. Other chapters focus on various aspects of philological research and content creation, including collaborative or community driven efforts, and the issues surrounding editorial oversight, curation, maintenance and sustainability of these resources. Research into the ancient languages and linguistics, in particular Greek, and the language teaching that is a staple of our discipline, are also discussed in several chapters, in particular for ways in which advanced research methods can lead into language technologies and vice versa and ways in which the skills around teaching can be used for public engagement, and vice versa. A common thread through much of the volume is the importance of open access publication or open source development and distribution of texts, materials, tools and standards, both because of the public good provided by such models (circulating materials often already paid for out of the public purse), and the ability to reach non-standard audiences, those who cannot access rich university libraries or afford expensive print volumes. Linked Open Data is another technology that results in wide and free distribution of structured information both within and outside academic circles, and several chapters present academic work that includes ontologies and RDF, either as a direct research output or as essential part of the communication and knowledge representation. Several chapters focus not on the literary and philological side of classics, but on the study of cultural heritage, archaeology, and the material supports on which original textual and artistic material are engraved or otherwise inscribed, addressing both the capture and analysis of artefacts in both 2D and 3D, the representation of data through archaeological standards, and the importance of sharing information and expertise between the several domains both within and without academia that study, record and conserve ancient objects. Almost without exception, the authors reflect on the issues of interdisciplinarity and collaboration, the relationship between their research practice and teaching and/or communication with a wider public, and the importance of the role of the academic researcher in contemporary society and in the context of cutting edge technologies. How research is communicated in a world of instant- access blogging and 140-character micromessaging, and how our expectations of the media affect not only how we publish but how we conduct our research, are questions about which all scholars need to be aware and self-critical.

Approaches and Strategy for Cancer Research and Surveillance Data: Integration, Information Pipeline, Data Models, and Informatics Opportunities

Thesis (Ph.D.)--University of Washington, 2016-04

Hierarchical indexing structure for efficient similarity search in video retrieval

With the rapid increase in both centralized video archives and distributed WWW video resources, content-based video retrieval is gaining its importance. To support such applications efficiently, content-based video indexing must be addressed. Typically, each video is represented by a sequence of frames. Due to the high dimensionality of frame representation and the large number of frames, video indexing introduces an additional degree of complexity. In this paper, we address the problem of content-based video indexing and propose an efficient solution, called the Ordered VA-File (OVA-File) based on the VA-file. OVA-File is a hierarchical structure and has two novel features: 1) partitioning the whole file into slices such that only a small number of slices are accessed and checked during k Nearest Neighbor (kNN) search and 2) efficient handling of insertions of new vectors into the OVA-File, such that the average distance between the new vectors and those approximations near that position is minimized. To facilitate a search, we present an efficient approximate kNN algorithm named Ordered VA-LOW (OVA-LOW) based on the proposed OVA-File. OVA-LOW first chooses possible OVA-Slices by ranking the distances between their corresponding centers and the query vector, and then visits all approximations in the selected OVA-Slices to work out approximate kNN. The number of possible OVA-Slices is controlled by a user-defined parameter delta. By adjusting delta, OVA-LOW provides a trade-off between the query cost and the result quality. Query by video clip consisting of multiple frames is also discussed. Extensive experimental studies using real video data sets were conducted and the results showed that our methods can yield a significant speed-up over an existing VA-file-based method and iDistance with high query result quality. Furthermore, by incorporating temporal correlation of video content, our methods achieved much more efficient performance.

Multi-topic information filtering with a single user profile

In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.

Designing a safety management support system using open architecture databases: the requirements of information representation in the support of managers' risk-related decision-making

This research was conducted at the Space Research and Technology Centre o the European Space Agency at Noordvijk in the Netherlands. ESA is an international organisation that brings together a range of scientists, engineers and managers from 14 European member states. The motivation for the work was to enable decision-makers, in a culturally and technologically diverse organisation, to share information for the purpose of making decisions that are well informed about the risk-related aspects of the situations they seek to address. The research examined the use of decision support system DSS) technology to facilitate decision-making of this type. This involved identifying the technology available and its application to risk management. Decision-making is a complex activity that does not lend itself to exact measurement or precise understanding at a detailed level. In view of this, a prototype DSS was developed through which to understand the practical issues to be accommodated and to evaluate alternative approaches to supporting decision-making of this type. The problem of measuring the effect upon the quality of decisions has been approached through expert evaluation of the software developed. The practical orientation of this work was informed by a review of the relevant literature in decision-making, risk management, decision support and information technology. Communication and information technology unite the major the,es of this work. This allows correlation of the interests of the research with European public policy. The principles of communication were also considered in the topic of information visualisation - this emerging technology exploits flexible modes of human computer interaction (HCI) to improve the cognition of complex data. Risk management is itself an area characterised by complexity and risk visualisation is advocated for application in this field of endeavour. The thesis provides recommendations for future work in the fields of decision=making, DSS technology and risk management.

Clustering web documents using hierarchical representation with multi-granularity

Web document cluster analysis plays an important role in information retrieval by organizing large amounts of documents into a small number of meaningful clusters. Traditional web document clustering is based on the Vector Space Model (VSM), which takes into account only two-level (document and term) knowledge granularity but ignores the bridging paragraph granularity. However, this two-level granularity may lead to unsatisfactory clustering results with “false correlation”. In order to deal with the problem, a Hierarchical Representation Model with Multi-granularity (HRMM), which consists of five-layer representation of data and a twophase clustering process is proposed based on granular computing and article structure theory. To deal with the zero-valued similarity problemresulted from the sparse term-paragraphmatrix, an ontology based strategy and a tolerance-rough-set based strategy are introduced into HRMM. By using granular computing, structural knowledge hidden in documents can be more efficiently and effectively captured in HRMM and thus web document clusters with higher quality can be generated. Extensive experiments show that HRMM, HRMM with tolerancerough-set strategy, and HRMM with ontology all outperform VSM and a representative non VSM-based algorithm, WFP, significantly in terms of the F-Score.

Comparing dissimilarity measures for content-based image retrieval

Dissimilarity measurement plays a crucial role in content-based image retrieval, where data objects and queries are represented as vectors in high-dimensional content feature spaces. Given the large number of dissimilarity measures that exist in many fields, a crucial research question arises: Is there a dependency, if yes, what is the dependency, of a dissimilarity measure’s retrieval performance, on different feature spaces? In this paper, we summarize fourteen core dissimilarity measures and classify them into three categories. A systematic performance comparison is carried out to test the effectiveness of these dissimilarity measures with six different feature spaces and some of their combinations on the Corel image collection. From our experimental results, we have drawn a number of observations and insights on dissimilarity measurement in content-based image retrieval, which will lay a foundation for developing more effective image search technologies.

Innovation and policy networks:the social shaping of BSE-related technologies and the inadequate assessmant of related risks

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR CONSULTATION

Who is really in charge of contemporary education? People and technologies in, against and beyond the neoliberal university

This article reflects on the position of people in, against and beyond information and communication technologies. Firstly, using Jandrić and Kuzmanić’s work on digital postcolonialism, Raymond Williams's work on residual and emergent cultures, and Deleuze and Guattari's insights into the dynamics between territorialization, de-territorialization and re-territorialization, it develops a theoretical framework for inquiry into the hybrid identity of the contemporary university. Then, through critical discourse analysis (CDA), the article moves on to analyse the ways in which technology discourse resides in the dominating ideology of technological determinism and co-opts with neoliberal agendas by omitting humans from explicit mention in UK policy documents. It shows that true counter-hegemonic practice against dominating social practices is possible only through reinvigorating the central position of human beings in regards to information and communication technologies. Within the developed theoretical framework, it seeks openings to intervene subversively into current relationships between technologies, people, and (higher) education, and to identify opportunities for building a non-determinist identity of the contemporary university that reaches beyond the single-minded logic of techno-scientific development. In the process, it situates Paulo Freire's insights into critical pedagogy in the context of the network society, and places the relationships between human beings, language and information and communication technologies amongst central questions of today's (higher) education and society at large.