Shifts of criteria or neural timing? The assumptions underlying timing perception studies

In timing perception studies, the timing of one event is usually manipulated relative to another, and participants are asked to judge if the two events were synchronous, or to judge which of the two events occurred first. Responses are analyzed to determine a measure of central tendency, which is taken as an estimate of the timing at which the two events are perceptually synchronous. When these estimates do not coincide with physical synchrony, it is often assumed that the sensory signals are asynchronous, as though the transfer of information concerning one input has been accelerated or decelerated relative to the other. Here we show that, while this is a viable interpretation, it is equally plausible that such effects are driven by shifts in the criteria used to differentiate simultaneous from asynchronous inputs. Our analyses expose important ambiguities concerning the interpretation of simultaneity judgement data, which have hitherto been underappreciated

Subjective evaluation of an emerging theory of low-frequency sound source localization in closed acoustic spaces

An earlier reported theory of low-frequency sound-source localization within closed acoustic spaces proposed that virtual image acuity is strongly dependent on sufficient inter-arrival time between a direct sound and its first reflection. This current study aims to test the theory’s predictions by subjective experiment where participants are required to indicate perceived sound source direction, but without knowledge of loudspeaker location. Test signals of frequencies 40 Hz to 115 Hz take the form of either windowed sine or square waves. Results confirm broad agreement with theoretical expectations and support the conjecture, contrary to common expectation, that low-frequency sound localization within the context of closed acoustic spaces is possible, although strongly dependent on system configuration and size of a listening space

Physical and neural entrainment to rhythm: human sensorimotor coordination across tasks and effector systems.

The human sensorimotor system can be readily entrained to environmental rhythms, through multiple sensory modalities. In this review, we provide an overview of theories of timekeeping that make this neuroentrainment possible. First, we present recent evidence that contests the assumptions made in classic timekeeper models. The role of state estimation, sensory feedback and movement parameters on the organization of sensorimotor timing are discussed in the context of recent experiments that examined simultaneous timing and force control. This discussion is extended to the study of coordinated multi-effector movements and how they may be entrained

The Noisy Silent Witness : The Misperception and Misuse of Criminal Video Evidence

This Note examines recent developments in the research of situational video evidence biases. Part I examines the current and growing body of psychological research into the various situational biases that can affect the reliability of video evidence and the gaps in this research that require further attention from researchers and legal academics. Because these biases do not “operate in a vacuum,” Part I also examines some of the recent and exciting research into the interaction between situational and dispositional biases. Part II examines the development of camera and video processing technology and its limitations as a means of mitigating such biases. Part III explains how such research could be used to develop heuristics to better assess the admissibility or presentation of video evidence and the need for greater judicial scrutiny of video evidence. This Note concludes by highlighting the potential research about the situational factors affecting the perception that video evidence has for producing insights useful for practitioners conducting criminal trials and municipalities and police forces adopting video technology, and closes with suggestions for further research

Unveiling the multimedia unconscious: implicit cognitive processes and multimedia content analysis

One of the main findings of cognitive sciences is that automatic processes of which we are unaware shape, to a significant extent, our perception of the environment. The phenomenon applies not only to the real world, but also to multimedia data we consume every day. Whenever we look at pictures, watch a video or listen to audio recordings, our conscious attention efforts focus on the observable content, but our cognition spontaneously perceives intentions, beliefs, values, attitudes and other constructs that, while being outside of our conscious awareness, still shape our reactions and behavior. So far, multimedia technologies have neglected such a phenomenon to a large extent. This paper argues that taking into account cognitive effects is possible and it can also improve multimedia approaches. As a supporting proof-of-concept, the paper shows not only that there are visual patterns correlated with the personality traits of 300 Flickr users to a statistically significant extent, but also that the personality traits (both self-assessed and attributed by others) of those users can be inferred from the images these latter post as "favourite"

Noise in Schools: A Holistic Approach to the Issue

Much of the research evidence relating to the physical learning environment of schools is inconclusive, contradictory or incomplete. Nevertheless, within this confusing area, research from a number of disciplines, using a range of methodologies, points to the negative impact of noise on students’ learning. In this paper, drawing on our systematic review of learning environments we review the weight of evidence in relation to noise, considering what implications the results of these studies have for the design and use of learning spaces in schools. We make four key points. Firstly that noise over a given level does appear to have a negative impact on learning. Secondly that beneath these levels noise may or may not be problematic, depending on the social, cultural and pedagogical expectations of the students and teachers. Thirdly we argue that when noise is deemed to be a difficulty, this finding cannot simply be translated into design prescriptions. The reasons for this indeterminacy include differing understandings of the routes through which noise produces learning deficits, as well as relationships between noise and other elements of the environment, particularly the impacts of physical solutions to noise problems. Finally, we suggest that solutions to noise problems will not be produced by viewing noise in isolation, or even as part of the physical environment, but through participatory approaches to understanding and adapting the structure, organisation and use of learning spaces in schools

Explicit Bayesian analysis for process tracing: guidelines, opportunities, and caveats

Bayesian probability holds the potential to serve as an important bridge between qualitative and quantitative methodology. Yet whereas Bayesian statistical techniques have been successfully elaborated for quantitative research, applying Bayesian probability to qualitative research remains an open frontier. This paper advances the burgeoning literature on Bayesian process tracing by drawing on expositions of Bayesian “probability as extended logic” from the physical sciences, where probabilities represent rational degrees of belief in propositions given the inevitably limited information we possess. We provide step-by-step guidelines for explicit Bayesian process tracing, calling attention to technical points that have been overlooked or inadequately addressed, and we illustrate how to apply this approach with the first systematic application to a case study that draws on multiple pieces of detailed evidence. While we caution that efforts to explicitly apply Bayesian learning in qualitative social science will inevitably run up against the difficulty that probabilities cannot be unambiguously specified, we nevertheless envision important roles for explicit Bayesian analysis in pinpointing the locus of contention when scholars disagree on inferences, and in training intuition to follow Bayesian probability more systematically

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Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis

In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments. The neuro-fuzzy synergy allows the diagnostic model to some extent "imitate" teachers in diagnosing students' characteristics, and equips the intelligent learning environment with reasoning capabilities that can be further used to drive pedagogical decisions depending on the student learning style. The neuro-fuzzy implementation helps to encode both structured and non-structured teachers' knowledge: when teachers' reasoning is available and well defined, it can be encoded in the form of fuzzy rules; when teachers' reasoning is not well defined but is available through practical examples illustrating their experience, then the networks can be trained to represent this experience. The proposed approach has been tested in diagnosing aspects of student's learning style in a discovery-learning environment that aims to help students to construct the concepts of vectors in physics and mathematics. The diagnosis outcomes of the model have been compared against the recommendations of a group of five experienced teachers, and the results produced by two alternative soft computing methods. The results of our pilot study show that the neuro-fuzzy model successfully manages the inherent uncertainty of the diagnostic process; especially for marginal cases, i.e. where it is very difficult, even for human tutors, to diagnose and accurately evaluate students by directly synthesizing subjective and, some times, conflicting judgments