The Sound of Feelings:Electrophysiological Responses Emotional Speech in Alexithymia

BACKGROUND: Alexithymia is a personality trait characterized by difficulties in the cognitive processing of emotions (cognitive dimension) and in the experience of emotions (affective dimension). Previous research focused mainly on visual emotional processing in the cognitive alexithymia dimension. We investigated the impact of both alexithymia dimensions on electrophysiological responses to emotional speech in 60 female subjects. METHODOLOGY: During unattended processing, subjects watched a movie while an emotional prosody oddball paradigm was presented in the background. During attended processing, subjects detected deviants in emotional prosody. The cognitive alexithymia dimension was associated with a left-hemisphere bias during early stages of unattended emotional speech processing, and with generally reduced amplitudes of the late P3 component during attended processing. In contrast, the affective dimension did not modulate unattended emotional prosody perception, but was associated with reduced P3 amplitudes during attended processing particularly to emotional prosody spoken in high intensity. CONCLUSIONS: Our results provide evidence for a dissociable impact of the two alexithymia dimensions on electrophysiological responses during the attended and unattended processing of emotional prosody. The observed electrophysiological modulations are indicative of a reduced sensitivity to the emotional qualities of speech, which may be a contributing factor to problems in interpersonal communication associated with alexithymia

Individual Differences in Temporal Selective Attention as Reflected in Pupil Dilation

Attention is restricted for the second of two targets when it is presented within 200-500 ms of the first target. This attentional blink (AB) phenomenon allows one to study the dynamics of temporal selective attention by varying the interval between the two targets (T1 and T2). Whereas the AB has long been considered as a robust and universal cognitive limitation, several studies have demonstrated that AB task performance greatly differs between individuals, with some individuals showing no AB whatsoever.Here, we studied these individual differences in AB task performance in relation to differences in attentional timing. Furthermore, we investigated whether AB magnitude is predictive for the amount of attention allocated to T1. For both these purposes pupil dilation was measured, and analyzed with our recently developed deconvolution method. We found that the dynamics of temporal attention in small versus large blinkers differ in a number of ways. Individuals with a relatively small AB magnitude seem better able to preserve temporal order information. In addition, they are quicker to allocate attention to both T1 and T2 than large blinkers. Although a popular explanation of the AB is that it is caused by an unnecessary overinvestment of attention allocated to T1, a more complex picture emerged from our data, suggesting that this may depend on whether one is a small or a large blinker.The use of pupil dilation deconvolution seems to be a powerful approach to study the temporal dynamics of attention, bringing us a step closer to understanding the elusive nature of the AB. We conclude that the timing of attention to targets may be more important than the amount of allocated attention in accounting for individual differences

Testing the skill-based approach:Consolidation strategy impacts attentional blink performance

Humans can learn simple new tasks very quickly. This ability suggests that people can reuse previously learned procedural knowledge when it applies to a new context. We have proposed a modeling approach based on this idea and used it to create a model of the attentional blink (AB). The main idea of the skill-based approach is that models are not created from scratch but, instead, built up from reusable pieces of procedural knowledge (skills). This approach not only provides an explanation for the fast learning of simple tasks but also shows much promise to improve certain aspects of cognitive modeling (e.g., robustness and generalizability). We performed two experiments, in order to collect empirical support for the model’s prediction that the AB will disappear when the two targets are consolidated as a single chunk. Firstly, we performed an unsuccessful replication of a study reporting that the AB disappears when participants are instructed to remember the targets as a syllable. However, a subsequent experiment using easily combinable stimuli supported the model’s prediction and showed a strongly reduced AB in a large group of participants. This result suggests that it is possible to avoid the AB with the right consolidation strategy. The skill-based approach allowed relating this finding to a general cognitive process, thereby demonstrating that incorporating this approach can be very helpful to generalize the findings of cognitive models, which otherwise tends to be rather difficult

An analysis of the impact of LED tilt on visible light positioning accuracy

Whereas the impact of photodiode noise and reflections is heavily studied in Visible Light Positioning (VLP), an often underestimated deterioration of VLP accuracy is caused by tilt of the Light Emitting Diodes (LEDs). Small LED tilts may be hard to avoid and can have a significant impact on the claimed centimeter-accuracy of VLP systems. This paper presents a Monte-Carlo-based simulation study of the impact of LED tilt on the accuracy of Received Signal Strength (RSS)-based VLP for different localization approaches. Results show that trilateration performs worse than (normalized) Least Squares algorithms, but mainly outside the LED square. Moreover, depending on inter-LED distance and LED height, median tilt-induced errors are in the range between 1 and 6 cm for small LED tilts, with errors scaling linearly with the LED tilt severity. Two methods are proposed to estimate and correct for LED tilts and their performance is compared

Response adaptive modelling for reducing the storage and computation of RSS-based VLP

The precise (location) tracking of automated guided vehicles will be key in enlarging the productivity, efficiency and safety in the connected warehouse or production infrastructure. Combining the modest price tag, the adequate coverage and the potential centimetre accuracy makes Visible Light Positioning (VLP) systems appealing as replacements for the current, high-cost, tracking systems. Model-fingerprinting-based received signal strength (RSS) VLP enables the required accuracy. It requires an elaborate optical channel model fingerprinted in a fine-grained, and predefined positioning grid. Depending on the grid's granularity, constructing the fingerprint database demands a significant computation and storage effort. This paper employs response adaptive or sequential experimental design to form sparse channel models, vastly reducing the storage and computation. It is shown that model-fingerprinting-based RSS only requires modelling less than 1 percent of the grid points, in an elementary positioning cell. The sparse model can be re-evaluated as a way to cope with environment changeover. Model recomputation as a way of compensating for LED ageing is also studied

Training the attentional blink:subclinical depression decreases learning potential

The attentional blink (AB) reflects a temporal restriction of selective attention and is generally regarded as a very robust phenomenon. However, previous studies have found large individual differences in AB performance, and under some training conditions the AB can be reduced significantly. One factor that may account for individual differences in AB magnitude is the ability to accurately time attention. In the current study, we focus on the sensitivity for temporal information on the ability to control attention. Following a visual AB task, a time estimation task was presented in either the visual or auditory modality, followed by another visual AB task. It was found that the time estimation training in both the auditory and visual modality reduced AB magnitude. Although a reduction in AB magnitude was also observed when individuals were trained on a control task (either an auditory frequency or visual line length estimation task), the effect was significantly larger following the time estimation tasks. In addition, it was found that individuals who showed most improvement on the visual time estimation task, also showed the largest reduction in AB magnitude, which was not the case for individuals who were trained on the control tasks. Finally, a negative correlation was observed between depression scores (tested by Beck Depression Inventory-Short Form (BDI-SF) scores and the improvement in the AB and time estimation tasks. Our findings demonstrate clear links between timing ability and mechanisms to control attention and emotion

Monte-Carlo simulation of the impact of LED power uncertainty on visible light positioning accuracy

This paper presents a simulation study of the impact of Light Emitting Diode (LED) output power uncertainty on the accuracy of Received Signal Strength (RSS)-based Visible Light Positioning (VLP). The actual emitted power of a LED is never exactly equal to the value that is tabulated in the datasheet, with possible variations (or tolerances) up to 20%. Since RSS-based VLP builds on converting estimated channel attenuations to distances and locations, this uncertainty will impact VLP accuracy in real-life setups. A typical configuration with four LEDs is assumed here, and a Monte-Carlo simulation is executed to investigate the distribution of the resulting positioning errors for four tolerance values at seven locations. It is shown that median errors are the highest just below the LEDs. When tolerance values on the LED power increase from 5% to 20%, median errors vary from at most 2 cm to at most 10 cm. Maximal errors can be as high as 17 cm just below the LED, already for tolerance values of only 5%, and increase up to 40 cm for tolerance values of 20%

On the impact of LED power uncertainty on the accuracy of 2D and 3D visible light positioning

This paper presents a simulation study of the impact of Light Emitting Diode (LED) output power uncertainty on the accuracy of Received Signal Strength (RSS)-based two-dimensional (2D) and three-dimensional (3D) Visible Light Positioning (VLP). The actual emitted power of a LED is never exactly equal to the value that is tabulated in the datasheet, with possible variations (or tolerances) up to 20%. Since RSS-based VLP builds on converting estimated channel attenuations to distances and locations, this uncertainty will impact VLP accuracy in real-life setups. For 2D, a typical configuration with four LEDs is assumed here, and a Monte-Carlo simulation is executed to investigate the distribution of the resulting positioning errors for four tolerance values at seven locations. It is shown that median errors are the highest just below the LEDs, when using a traditional Least-Squares minimization metric. When tolerance values on the LED power increase from 5% to 20%, median errors vary from at most 2 cm to at most 10 cm. Maximal errors can be as high as 17 cm just below the LED, already for tolerance values of only 5%, and increase up to 40 cm for tolerance values of 20%. An alternative cost metric using normalized Least-Squares minimization makes the errors spatially more homogeneously distributed and reduces them by 35%. For a 3D case, median errors of around 5 cm for a tolerance value of 5% increase to as much as 22 cm for a tolerance value of 20%. As the receiver heights increase, positioning errors decrease significantly

Time to see the bigger picture:Individual differences in the attentional blink

If two to-be-identified targets are presented in close temporal succession, identification for the second target is typically impaired. This attentional blink (AB) phenomenon has long been considered as a robust, universal cognitive limitation. However, more recent studies have demonstrated that AB task performance greatly differs between individuals, with some individuals even showing no AB in certain paradigms. Several studies have focused on these individual differences in an attempt to reveal the mechanism underlying the AB, but an overview of this approach is currently missing. Here, by reviewing studies regarding individual differences in AB task performance, we investigate how individual differences have contributed to our understanding of the AB. We show that the individual differences AB literature provides reliable indications that the AB is a multifaceted phenomenon that presumably arises from a combination of factors; individuals with higher levels of executive working memory (WM) functioning and broad attentional focus perform better in the AB paradigm than individuals with lower executive functioning of WM and narrow attentional focus. As it turns out, seeing the bigger picture certainly seems helpful for AB task performance

A comprehensive study on light signals of opportunity for subdecimetre unmodulated visible light positioning

Currently, visible light positioning (VLP) enabling an illumination infrastructure requires a costly retrofit. Intensity modulation systems not only necessitate changes to the internal LED driving module, but decrease the LEDs' radiant flux as well. This hinders the infrastructure's ability to meet the maintained illuminance standards. Ideally, the LEDs could be left unmodulated, i.e., unmodulated VLP (uVLP). uVLP systems, inherently low-cost, exploit the characteristics of the light signals of opportunity (LSOOP) to infer a position. In this paper, it is shown that proper signal processing allows using the LED's characteristic frequency (CF) as a discriminative feature in photodiode (PD)-based received signal strength (RSS) uVLP. This manuscript investigates and compares the aptitude of (future) RSS-based uVLP and VLP systems in terms of their feasibility, cost and accuracy. It demonstrates that CF-based uVLP exhibits an acceptable loss of accuracy compared to (regular) VLP. For point source-like LEDs, uVLP only worsens the trilateration-based median p50 and 90th percentile root-mean-square error p90 from 5.3cm to 7.9cm (+50%) and from 9.6cm to 15.6cm (+62%), in the 4m x 4m room under consideration. A large experimental validation shows that employing a robust model-based fingerprinting localisation procedure, instead of trilateration, further boosts uVLP's p50 and p90 accuracy to 5.0cm and 10.6cm. When collating with VLP's p50=3.5cm and p90=6.8cm, uVLP exhibits a comparable positioning performance at a significantly lower cost and at a higher maintained illuminance, all of which underline uVLP's high adoption potential. With this work, a significant step is taken towards the development of an accurate and low-cost tracking system