258 resultados para Sensory Thresholds


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As a social species in a constantly changing environment, humans rely heavily on the informational richness and communicative capacity of the face. Thus, understanding how the brain processes information about faces in real-time is of paramount importance. The N170 is a high temporal resolution electrophysiological index of the brain's early response to visual stimuli that is reliably elicited in carefully controlled laboratory-based studies. Although the N170 has often been reported to be of greatest amplitude to faces, there has been debate regarding whether this effect might be an artifact of certain aspects of the controlled experimental stimulation schedules and materials. To investigate whether the N170 can be identified in more realistic conditions with highly variable and cluttered visual images and accompanying auditory stimuli we recorded EEG 'in the wild', while participants watched pop videos. Scene-cuts to faces generated a clear N170 response, and this was larger than the N170 to transitions where the videos cut to non-face stimuli. Within participants, wild-type face N170 amplitudes were moderately correlated to those observed in a typical laboratory experiment. Thus, we demonstrate that the face N170 is a robust and ecologically valid phenomenon and not an artifact arising as an unintended consequence of some property of the more typical laboratory paradigm.

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Wi-Fi is a commonly available source of localization information in urban environments but is challenging to integrate into conventional mapping architectures. Current state of the art probabilistic Wi-Fi SLAM algorithms are limited by spatial resolution and an inability to remove the accumulation of rotational error, inherent limitations of the Wi-Fi architecture. In this paper we leverage the low quality sensory requirements and coarse metric properties of RatSLAM to localize using Wi-Fi fingerprints. To further improve performance, we present a novel sensor fusion technique that integrates camera and Wi-Fi to improve localization specificity, and use compass sensor data to remove orientation drift. We evaluate the algorithms in diverse real world indoor and outdoor environments, including an office floor, university campus and a visually aliased circular building loop. The algorithms produce topologically correct maps that are superior to those produced using only a single sensor modality.

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Pavlovian fear conditioning is an evolutionary conserved and extensively studied form of associative learning and memory. In mammals, the lateral amygdala (LA) is an essential locus for Pavlovian fear learning and memory. Despite significant progress unraveling the cellular mechanisms responsible for fear conditioning, very little is known about the anatomical organization of neurons encoding fear conditioning in the LA. One key question is how fear conditioning to different sensory stimuli is organized in LA neuronal ensembles. Here we show that Pavlovian fear conditioning, formed through either the auditory or visual sensory modality, activates a similar density of LA neurons expressing a learning-induced phosphorylated extracellular signal-regulated kinase (p-ERK1/2). While the size of the neuron population specific to either memory was similar, the anatomical distribution differed. Several discrete sites in the LA contained a small but significant number of p-ERK1/2-expressing neurons specific to either sensory modality. The sites were anatomically localized to different levels of the longitudinal plane and were independent of both memory strength and the relative size of the activated neuronal population, suggesting some portion of the memory trace for auditory and visually cued fear conditioning is allocated differently in the LA. Presenting the visual stimulus by itself did not activate the same p-ERK1/2 neuron density or pattern, confirming the novelty of light alone cannot account for the specific pattern of activated neurons after visual fear conditioning. Together, these findings reveal an anatomical distribution of visual and auditory fear conditioning at the level of neuronal ensembles in the LA.

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Impaired driver alertness increases the likelihood of drivers’ making mistakes and reacting too late to unexpected events while driving. This is particularly a concern on monotonous roads, where a driver’s attention can decrease rapidly. While effective countermeasures do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behavior in real-time. The aim of this study is to predict drivers’ level of alertness through surrogate measures collected from in-vehicle sensors. Electroencephalographic activity is used as a reference to evaluate alertness. Based on a sample of 25 drivers, data was collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device. Various classification models were tested from linear regressions to Bayesians and data mining techniques. Results indicated that Neural Networks were the most efficient model in detecting lapses in alertness. Findings also show that reduced alertness can be predicted up to 5 minutes in advance with 90% accuracy, using surrogate measures such as time to line crossing, blink frequency and skin conductance level. Such a method could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring, in real-time, drivers' behavior on highways.

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Schizophrenia patients have been shown to be compromised in their ability to recognize facial emotion. This deficit has been shown to be related to negative symptoms severity. However, to date, most studies have used static rather than dynamic depictions of faces. Nineteen patients with schizophrenia were compared with seventeen controls on 2 tasks; the first involving the discrimination of facial identity, emotion, and butterfly wings; the second testing emotion recognition using both static and dynamic stimuli. In the first task, the patients performed more poorly than controls for emotion discrimination only, confirming a specific deficit in facial emotion recognition. In the second task, patients performed more poorly in both static and dynamic facial emotion processing. An interesting pattern of associations suggestive of a possible double dissociation emerged in relation to correlations with symptom ratings: high negative symptom ratings were associated with poorer recognition of static displays of emotion, whereas high positive symptom ratings were associated with poorer recognition of dynamic displays of emotion. However, while the strength of associations between negative symptom ratings and accuracy during static and dynamic facial emotion processing was significantly different, those between positive symptom ratings and task performance were not. The results confirm a facial emotion-processing deficit in schizophrenia using more ecologically valid dynamic expressions of emotion. The pattern of findings may reflect differential patterns of cortical dysfunction associated with negative and positive symptoms of schizophrenia in the context of differential neural mechanisms for the processing of static and dynamic displays of facial emotion.

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While the neural regions associated with facial identity recognition are considered to be well defined, the neural correlates of non-moving and moving images of facial emotion processing are less clear. This study examined the brain electrical activity changes in 26 participants (14 males M = 21.64, SD = 3.99; 12 females M = 24.42, SD = 4.36), during a passive face viewing task, a scrambled face task and separate emotion and gender face discrimination tasks. The steady state visual evoked potential (SSVEP) was recorded from 64-electrode sites. Consistent with previous research, face related activity was evidenced at scalp regions over the parieto-temporal region approximately 170 ms after stimulus presentation. Results also identified different SSVEP spatio-temporal changes associated with the processing of static and dynamic facial emotions with respect to gender, with static stimuli predominately associated with an increase in inhibitory processing within the frontal region. Dynamic facial emotions were associated with changes in SSVEP response within the temporal region, which are proposed to index inhibitory processing. It is suggested that static images represent non-canonical stimuli which are processed via different mechanisms to their more ecologically valid dynamic counterparts.

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Facial identity and facial expression matching tasks were completed by 5–12-year-old children and adults using stimuli extracted from the same set of normalized faces. Configural and feature processing were examined using speed and accuracy of responding and facial feature selection, respectively. Facial identity matching was slower than face expression matching for all age groups. Large age effects were found on both speed and accuracy of responding and feature use in both identity and expression matching tasks. Eye region preference was found on the facial identity task and mouth region preference on the facial expression task. Use of mouth region information for facial expression matching increased with age, whereas use of eye region information for facial identity matching peaked early. The feature use information suggests that the specific use of primary facial features to arrive at identity and emotion matching judgments matures across middle childhood.

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Discovering the means to prevent and cure schizophrenia is a vision that motivates many scientists. But in order to achieve this goal, we need to understand its neurobiological basis. The emergent metadiscipline of cognitive neuroscience fields an impressive array of tools that can be marshaled towards achieving this goal, including powerful new methods of imaging the brain (both structural and functional) as well as assessments of perceptual and cognitive capacities based on psychophysical procedures, experimental tasks and models developed by cognitive science. We believe that the integration of data from this array of tools offers the greatest possibilities and potential for advancing understanding of the neural basis of not only normal cognition but also the cognitive impairments that are fundamental to schizophrenia. Since sufficient expertise in the application of these tools and methods rarely reside in a single individual, or even a single laboratory, collaboration is a key element in this endeavor. Here, we review some of the products of our integrative efforts in collaboration with our colleagues on the East Coast of Australia and Pacific Rim. This research focuses on the neural basis of executive function deficits and impairments in early auditory processing in patients using various combinations of performance indices (from perceptual and cognitive paradigms), ERPs, fMRI and sMRI. In each case, integration of two or more sources of information provides more information than any one source alone by revealing new insights into structure-function relationships. Furthermore, the addition of other imaging methodologies (such as DTI) and approaches (such as computational models of cognition) offers new horizons in human brain imaging research and in understanding human behavior.

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Theoretical accounts suggest that mirror neurons play a crucial role in social cognition. The current study used transcranial-magnetic stimulation (TMS) to investigate the association between mirror neuron activation and facialemotion processing, a fundamental aspect of social cognition, among healthy adults (n = 20). Facial emotion processing of static (but not dynamic) images correlated significantly with an enhanced motor response, proposed to reflect mirror neuron activation. These correlations did not appear to reflect general facial processing or pattern recognition, and provide support to current theoretical accounts linking the mirror neuron system to aspects of social cognition. We discuss the mechanism by which mirror neurons might facilitate facial emotion recognition.

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Purpose Age-related changes in motion sensitivity have been found to relate to reductions in various indices of driving performance and safety. The aim of this study was to investigate the basis of this relationship in terms of determining which aspects of motion perception are most relevant to driving. Methods Participants included 61 regular drivers (age range 22–87 years). Visual performance was measured binocularly. Measures included visual acuity, contrast sensitivity and motion sensitivity assessed using four different approaches: (1) threshold minimum drift rate for a drifting Gabor patch, (2) Dmin from a random dot display, (3) threshold coherence from a random dot display, and (4) threshold drift rate for a second-order (contrast modulated) sinusoidal grating. Participants then completed the Hazard Perception Test (HPT) in which they were required to identify moving hazards in videos of real driving scenes, and also a Direction of Heading task (DOH) in which they identified deviations from normal lane keeping in brief videos of driving filmed from the interior of a vehicle. Results In bivariate correlation analyses, all motion sensitivity measures significantly declined with age. Motion coherence thresholds, and minimum drift rate threshold for the first-order stimulus (Gabor patch) both significantly predicted HPT performance even after controlling for age, visual acuity and contrast sensitivity. Bootstrap mediation analysis showed that individual differences in DOH accuracy partly explained these relationships, where those individuals with poorer motion sensitivity on the coherence and Gabor tests showed decreased ability to perceive deviations in motion in the driving videos, which related in turn to their ability to detect the moving hazards. Conclusions The ability to detect subtle movements in the driving environment (as determined by the DOH task) may be an important contributor to effective hazard perception, and is associated with age, and an individuals' performance on tests of motion sensitivity. The locus of the processing deficits appears to lie in first-order, rather than second-order motion pathways.

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Purpose To investigate longitudinal changes of subbasal nerve plexus (SNP) morphology and its relationship with conventional measures of neuropathy in individuals with diabetes. Methods A cohort of 147 individuals with type 1 diabetes and 60 age-balanced controls underwent detailed assessment of clinical and metabolic factors, neurologic deficits, quantitative sensory testing, nerve conduction studies and corneal confocal microscopy at baseline and four subsequent annual visits. The SNP parameters included corneal nerve fiber density (CNFD), branch density (CNBD) and fiber length (CNFL) and were quantified using a fully-automated algorithm. Linear mixed models were fitted to examine the changes in corneal nerve parameters over time. Results At baseline, 27% of the participants had mild diabetic neuropathy. All SNP parameters were significantly lower in the neuropathy group compared to controls (P<0.05). Overall, 89% of participants examined at baseline also completed the final visit. There was no clinically significant change to health and metabolic parameters and neuropathy measures from baseline to the final visit. Linear mixed model revealed a significant linear decline of CNFD (annual change rate, -0.9 nerve/mm2, P=0.01) in the neuropathy group compared to controls, which was associated with age (β=-0.06, P=0.04) and duration of diabetes (β=-0.08, P=0.03). In the neuropathy group, absolute changes of CNBD and CNFL showed moderate correlations with peroneal conduction velocity and cold sensation threshold, respectively (rs, 0.38 and 0.40, P<0.05). Conclusion This study demonstrates dynamic small fiber damage at the SNP, thus providing justification for our ongoing efforts to establish corneal nerve morphology as an appropriate adjunct to conventional measures of DPN.

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Introduction: Ten years after the publication of Elaborated Intrusion (EI) Theory, there is now substantial research into its key predictions. The distinction between intrusive thoughts, which are driven by automatic processes, and their elaboration, involving controlled processing, is well established. Desires for both addictive substances and other desired targets are typically marked by imagery, especially when they are intense. Attention training strategies such as body scanning reduce intrusive thoughts, while concurrent tasks that introduce competing sensory information interfere with elaboration, especially if they compete for the same limited-capacity working memory resources. Conclusion: EI Theory has spawned new assessment instruments that are performing strongly and offer the ability to more clearly delineate craving from correlated processes. It has also inspired new approaches to treatment. In particular, training people to use vivid sensory imagery for functional goals holds promise as an intervention for substance misuse, since it is likely to both sustain motivation and moderate craving.

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This sensory ethnography explores the affordances and constraints of multimodal design to represent emotions and appraisal associated with experiencing local places. Digital video production, walking with the camera, and the use of a think-aloud protocol to reflect on the videos, provided an opportunity for the primary school children to represent their emotions and appraisal of places multimodally. Applying a typology from Martin and White's (2005) framework for the Language of Evaluation, children's multimodal emotional responses to places in this study tended toward happiness, security, and satisfaction. The findings demonstrate an explicit connection between children's emotions in response to local places through video, while highlighting the potential for teachers to use digital filmmaking to allow children to reflect actively on their placed experiences and represent their emotional reactions to places through multiple modes.

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Impairments in social cognitive functioning are well documented in schizophrenia, however the neural basis of these deficits is unclear. A recent explanatory model of social cognition centers upon the activity of mirror neurons, which are cortical brain cells that become active during both the performance and observation of behavior. Here, we test for the first time whether mirror neuron functioning is reduced in schizophrenia. Fifteen individuals with schizophrenia or schizoaffective disorder and fifteen healthy controls completed a transcranial magnetic stimulation (TMS) experiment designed to assess mirror neuron activation. While patients demonstrated no abnormalities in cortical excitability, motor facilitation during action observation, putatively reflecting mirror neuron activity, was reduced in schizophrenia. Dysfunction within the mirror neuron system may contribute to the pathophysiology of schizophrenia.

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A new mesh adaptivity algorithm that combines a posteriori error estimation with bubble-type local mesh generation (BLMG) strategy for elliptic differential equations is proposed. The size function used in the BLMG is defined on each vertex during the adaptive process based on the obtained error estimator. In order to avoid the excessive coarsening and refining in each iterative step, two factor thresholds are introduced in the size function. The advantages of the BLMG-based adaptive finite element method, compared with other known methods, are given as follows: the refining and coarsening are obtained fluently in the same framework; the local a posteriori error estimation is easy to implement through the adjacency list of the BLMG method; at all levels of refinement, the updated triangles remain very well shaped, even if the mesh size at any particular refinement level varies by several orders of magnitude. Several numerical examples with singularities for the elliptic problems, where the explicit error estimators are used, verify the efficiency of the algorithm. The analysis for the parameters introduced in the size function shows that the algorithm has good flexibility.