COMMUNICATION | doi:10.20944/preprints202308.0072.v1
Subject: Public Health And Healthcare, Other Keywords: Dopamine; Brain; Reward; Stress; Pathological Adaptation; Behavior; Covid19 pandemic; Digital Addiction; Global Mental Health
Online: 1 August 2023 (10:09:42 CEST)
When “hijacked” by compulsive behaviors that affect the reward and stress centers of the brain, functional changes in dopamine circuitry occur as the consequence of pathological brain adaptation. As a brain explanans for mental health, with a central functional role in behavioral regulation from healthy reward seeking to pathological adaptation to stress in response to adversity, we may use dopamine regulation in interaction with other brain mechanisms, as discussed herein, to gather a deeper insight into environmentally triggered mental health changes to understand, for example, specific behavioral changes observed during and after the COVID-19 pandemic. Pandemic-related adversities, the stresses they engendered, and the long lockdown periods where people had to rely on digital tools to get feed-back rewards via the internet can be seen as the major triggers of changes in motivation and reward seeking behavior worldwide. The pathological adaptation of dopamine-mediated reward circuitry in the brain offers a highly plausible explanation why, when pushed by fate and circumstance into a physiological brain state of anti-reward, human behavior and mental health changes almost inevitably depending on individual vulnerability to stress. A unified conceptual account that places dopamine function at the centre of the current global mental health context is proposed.
REVIEW | doi:10.20944/preprints202003.0258.v1
Subject: Public Health And Healthcare, Primary Health Care Keywords: digital environments; over exposure; children; vitamin D; melatonin; myopia; sleep loss; depression; obesity internet addiction; serotonin; dopamine; oxidative stress
Online: 16 March 2020 (04:22:15 CET)
Environmental studies, metabolic research, and state of the art neurobiology point towards the reduced amount of natural day and sunlight exposure of the developing child’s organism as the consequence of increasingly long hours spent indoors online as the single unifying source of a whole set of health risks identified worldwide, as is made clear in this review of the current literature. Over exposure to digital environments, from abuse to addiction, now concerns even the youngest (ages 0 to 2), and triggers, as argued on the basis of clear examples herein, a chain of interdependent negative and potentially long-term metabolic changes. This leads to a deregulation of the serotonin and dopamine neurotransmitter pathways in the developing brain, currently associated with online activity abuse and/or internet addiction, and akin to that found in severe substance abuse syndromes. A general functional working model is proposed under the light of evidence brought to the forefront in this review.
ARTICLE | doi:10.20944/preprints201810.0379.v1
Subject: Social Sciences, Psychology Keywords: surgical simulator training; individual performance trend; speed-accuracy function; automatic detection; performance feed-back
Online: 17 October 2018 (08:40:08 CEST)
Simulator training for image-guided surgical interventions may benefit from artificial intelligence systems that control the evolution of task skills in terms of time and precision of a trainee's performance on the basis of fully automatic feed-back systems. At the earliest stages of training, novice trainees frequently focus on getting faster at the task, and may thereby compromise the optimal evolution of the precision of their performance. For automatically guiding them towards attaining an optimal speed-accuracy trade-off, an effective control system for the reinforcement/correction of strategies must be able to exploit the right individual performance criteria in the right way, reliably detect individual performance trends at any given moment in time, and alert the trainee, as early as necessary, when to slow down and focus on precision, or when to focus on getting faster. This article addresses several aspects of this challenge for speed-accuracy controlled simulator training before any training on specific surgical tasks or clinical models should be envisaged. Analyses of individual learning curves from the simulator training sessions of novices and benchmark performance data of one expert surgeon, who had no specific training in the simulator task, validate the suggested approach.
ARTICLE | doi:10.20944/preprints202001.0319.v1
Subject: Arts And Humanities, Architecture Keywords: monocular depth cues; luminance contrast; colour; visual arts; image plane; human perception; brain; 3D structure; figure-ground; Gestalt Theory
Online: 27 January 2020 (01:54:27 CET)
Victor Vasarely’s (1906-1997) important legacy to the study of human perception is brought to the forefront and discussed. A large part of his impressive work conveys the appearance of striking three-dimensional shapes and structures in a large-scale pictorial plane. Current perception science explains such effects by invoking brain mechanisms for the processing of monocular (2D) depth cues. Here in this study, we illustrate and explain the local effects of 2D color and contrast cues on the perceptual organization in terms of figure-ground assignments, i.e. which local surfaces are likely to be seen as “nearer” or “bigger” in the image plane. Paired configurations are embedded in a larger, structurally ambivalent pictorial context inspired by some of Vasarely’s creations. The figure-ground effects these configurations produce reveal a significant correlation between perceptual solutions for “nearer” and “bigger” when no other monocular depth cues are given in the image. In consistency with previous findings on similar, albeit simpler visual displays, a specific color may compete with luminance contrast in resolving the planar ambiguity of a complex pattern context. Vasarely intuitively understood, and successfully exploited, this kind of subtle context effect in his art, well before empirical investigations had set out to study and explain their genesis in terms of information processing by the visual brain.
ARTICLE | doi:10.20944/preprints201910.0247.v1
Subject: Social Sciences, Behavior Sciences Keywords: visual contrast; perceived relative object depth; 2D images; sound frequency; two alternative forced-choice; response times; high-probability decision; readiness to respond; probability summation
Online: 22 October 2019 (03:34:45 CEST)
Pieron's and Chocholle’s seminal psychophysical work predicts that human response time to information relative to visual contrast and/or sound frequency decreases when contrast intensity or sound frequency increases. The goal of this study is to bring to the fore the ability of individuals to use visual contrast intensity and sound frequency in combination for faster perceptual decisions of relative depth (“nearer”) in planar (2D) object configurations on the basis of physical variations in luminance contrast. Computer controlled images with two abstract patterns of varying contrast intensity, one on the left and one on the right, preceded or not by a pure tone of varying frequency, were shown to healthy young humans in controlled experimental sequences. Their task (two-alternative forced-choice) was to decide as quickly as possible which of two patterns, the left or the right one, in a given image appeared to “stand out as if it were nearer” in terms of apparent (subjective) visual depth. The results show that the combinations of varying relative visual contrast with sounds of varying frequency exploited here produced an additive effect on choice response times in terms of facilitation, where a stronger visual contrast combined with a higher sound frequency produced shorter forced-choice response times. This new effect is predicted by cross-modal audio-visual probability summation.
ARTICLE | doi:10.20944/preprints202101.0313.v1
Subject: Computer Science And Mathematics, Computer Science Keywords: symmetry; shape; local color; self-organized visual map; quantization error; SOM-QE; choice response time; human decision; uncertainty
Online: 18 January 2021 (10:18:03 CET)
Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human observers. To this end, we exploit a neural network metric in the output of a biologically inspired Self-Organizing Map, the Quantization Error (SOM-QE). Shape pairs with perfect geometric mirror symmetry but a non-homogenous appearance, caused by local variations in hue, saturation, or lightness within and/or across the shapes in a given pair produce, as shown here, longer choice RT for ‘yes’ responses relative to symmetry. These data are consistently mirrored by the variations in the SOM-QE from unsupervised neural network analysis of the same stimulus images. The neural network metric is thus capable of detecting and scaling human symmetry uncertainty in response to patterns. Such capacity is tightly linked to the metric’s proven selectivity to local contrast and color variations in large and highly complex image data.
ARTICLE | doi:10.20944/preprints201608.0046.v1
Subject: Social Sciences, Cognitive Science Keywords: visual symmetry; affine projection; fractals; visual sensation; aesthetics; preference
Online: 5 August 2016 (05:15:32 CEST)
Evolution and geometry generate complexity in similar ways. Evolution drives natural selection while geometry may capture the logic of this selection and express it visually, in terms of specific generic properties representing some kind of advantage. Geometry is ideally suited for expressing the logic of evolutionary selection for symmetry, which is found in the shape curves of vein systems and other natural objects such as leaves, cell membranes, or tunnel systems built by ants. The topology and geometry of symmetry is controlled by numerical parameters, which act in analogy with a biological organism's DNA. The introductory part of this paper reviews findings from experiments illustrating the critical role of two-dimensional design parameters and shape symmetry for visual or tactile shape sensation, and for perception-based decision making in populations of experts and non-experts. Thereafter, results from a pilot study on the effects of fractal symmetry, referred to herein as the symmetry of things in a thing, on aesthetic judgments and visual preference are presented. In a first experiment (psychophysical scaling procedure), non-expert observers had to rate (scale from 0 to 10) the perceived beauty of a random series of 2D fractal trees with varying degrees of fractal symmetry. In a second experiment (two-alternative forced choice procedure), they had to express their preference for one of two shapes from the series. The shape pairs were presented successively in random order. Results show that the smallest possible fractal deviation from "symmetry of things in a thing" significantly reduces the perceived attractiveness of such shapes. The potential of future studies where different levels of complexity of fractal patterns are weighed against different degrees of symmetry is pointed out in the conclusion.
ARTICLE | doi:10.20944/preprints201710.0166.v2
Subject: Computer Science And Mathematics, Information Systems Keywords: satellite images; image analysis; self organizing maps; quantization error; structural change; demographic data
Online: 20 March 2018 (10:38:43 CET)
The quantization error (QE) from Self-Organizing Map (SOM) output after learning is exploited in this studies. SOM learning is applied on time series of spatial contrast images with variable relative amount of white and dark pixel contents, as in monochromatic medical images or satellite images. It is proven that the QE from the SOM output after learning provides a reliable indicator of potentially critical changes in images across time. The QE increases linearly with the variability in spatial contrast contents of images across time when contrast intensity is kept constant. The hitherto unsuspected capacity of this metric to capture even the smallest changes in large bodies of image time series after using ultra-fast SOM learning is illustrated on examples from SOM learning studies on computer generated images, MRI image time series, and satellite image time series. Linear trend analysis of the changes in QE as a function of the time an image of a given series was taken gives proof of the statistical reliability of this metric as an indicator of local change. It is shown that the QE is correlated with significant clinical, demographic, and environmental data from the same reference time period during which test image series were recorded. The findings show that the QE from SOM, which is easily implemented and requires computation times no longer than a few minutes for a given image series of 20 to 25, is useful for a fast analysis of whole series of image data when the goal is to provide an instant statistical decision relative to change/no change between images.
ARTICLE | doi:10.20944/preprints202010.0328.v1
Subject: Engineering, Automotive Engineering Keywords: wearable biosensors; wireless technology; human grip force; motor control; complex task-user systems; expertise; multivariate data; correlation analysis; functional analysis
Online: 15 October 2020 (15:13:43 CEST)
Biosensors and wearable sensor systems with transmitting capabilities are currently developed and used for the monitoring of health data, exercise activities, and other performance data. Unlike conventional approaches, these devices enable convenient, continuous, and unobtrusive monitoring of a user’s behavioral signals in real time. Examples include signals relative to hand an finger movement/pressure control reflected by individual grip force data. As will be shown here, these directly translate into task, skill and hand-specific (dominant versus non-dominant hand) grip force profiles for different measurement loci in the fingers and palm of the hand. On the basis of thousands of sensor data from multiple sensor locations, individual grip force profiles of an task expert, a trained user and a highly proficient user (expert) performing an image-guided and robot-assisted precision task with the dominant or the non-dominant hand are analyzed in several steps following Tukey’s “detective work” approach. Correlation analyses (Person’s Product Moment) reveal skill-specific differences in individual grip force profiles across multiple sources of variation, functionally mapped to the somatosensory brain networks which ensure grip force control and its evolution with control expertise. Implications for the real-time monitoring of individual grip force profiles and their evolution with training in complex task-user systems are brought forward.
ARTICLE | doi:10.20944/preprints201909.0208.v1
Subject: Social Sciences, Psychology Keywords: surgical robotics; wearable force-sensor systems; grip-force profiling; surgical expertise; robot-assisted surgery training
Online: 18 September 2019 (13:07:40 CEST)
STRAS (Single access Transluminal Robotic Assistant for Surgeons) is a flexible robotic system based on the Anubis® platform of Karl Storz for application to intra-luminal surgical procedures. It consists of three cable-driven systems, one endoscope serving as guide and two inserted instruments. The flexible and bendable instruments have three degrees of freedom and can be teleoperated by a single user via two specially designed master interfaces. In this research, a pair of specific sensor gloves, which ergonomically fit to the master handles of the system was designed and the forces applied by one expert and one novice user during system-specific task execution in a simulator task (4-step-pick-and-drop) were compared. The results show that user expertise is not only reflected by shorter task execution times but also, more importantly, by specific differences in handgrip force profiles for specific sensor locations on anatomically relevant parts of the fingers and hand controlling the surgical instruments of the robotic master/slave system.