Unsupervised Motion Artifact Detection in Wrist-Measured Electrodermal Activity Data

One of the main benefits of a wrist-worn computer is its ability to collect a variety of physiological data in a minimally intrusive manner. Among these data, electrodermal activity (EDA) is readily collected and provides a window into a person's emotional and sympathetic responses. EDA data collected using a wearable wristband are easily influenced by motion artifacts (MAs) that may significantly distort the data and degrade the quality of analyses performed on the data if not identified and removed. Prior work has demonstrated that MAs can be successfully detected using supervised machine learning algorithms on a small data set collected in a lab setting. In this paper, we demonstrate that unsupervised learning algorithms perform competitively with supervised algorithms for detecting MAs on EDA data collected in both a lab-based setting and a real-world setting comprising about 23 hours of data. We also find, somewhat surprisingly, that incorporating accelerometer data as well as EDA improves detection accuracy only slightly for supervised algorithms and significantly degrades the accuracy of unsupervised algorithms.Comment: To appear at International Symposium on Wearable Computers (ISWC) 201

Impact of physiological rhythms on energy homeostasis in rodents

Obesity and related metabolic disorders such as type 2 diabetes are a major health issue of our modern society. The brain has been identified to play an essential role in the pathogenesis of these diseases. Disruptions of the neuroendocrine system, such as the development of hypothalamic leptin resistance, are strongly correlated with the manifestation of diet-induced obesity (DIO). To date, the molecular mechanisms underlying these metabolic derangements are incompletely understood. Over the last decade, a close connection of energy metabolism and the circadian clock has been established, but the link between DIO and disruptions of physiological rhythms still needs further investigation. Therefore, the aim of this thesis was to gain new insights into neuroendocrine mechanisms that lead to the development of leptin resistance and the role of physiological rhythms in the disruption of energy metabolism. In this study, we investigated the implication of the adipocyte-derived hormone adiponectin in neuroendocrine control of energy metabolism. We detected expression of all investigated genes involved in the adiponectin signalling pathway in the hypothalamus of mice. Expression levels of adiponectin were reduced during states of food deprivation, potentially presenting a regulatory mechanism to counteract the anorexigenic traits that had been previously described for central adiponectin signalling and that were confirmed by us in this study, in order to prevent further reduction in body weight. In both fasted control mice as well as DIO mice, gene expression of the adiponectin receptor AdipoR1 was elevated, suggesting multiple regulatory mechanisms to maintain sufficient adiponectin signal transduction. The upregulation of AdipoR1 during DIO might be an attempt to support the beneficial effects of the hormone on metabolic health that have been reported for peripheral adiponectin. In line with this, we demonstrated that adiponectin holds insulin-sensitising, blood glucose-lowering and anti-inflammatory properties in control as well as DIO mice and that these effects are mediated via central signal transduction. We furthermore investigated the role of the WNT/β-catenin pathway in the neuroendocrine control of energy metabolism. Here, we found gene expression of members of the WNT pathway on all regulatory levels (ligands, intracellular pathway enzymes, target genes) in the hypothalamus of adult Djungarian hamsters, Phodopus sungorus, a seasonal rodent that exhibits profound annual changes in body weight and leptin sensitivity. Expression of all ligands as well as target genes was upregulated in hamsters acclimated to long day (LD) relative to short day (SD) conditions. Confirming our results from these transcriptional studies, we furthermore found increased phosphorylation of the WNT pathway co-receptor LRP-6, demonstrating elevated activation of canonical WNT signalling, in LD hamsters. These findings provide strong evidence for increased WNT signalling during LD compared with SD photoperiod. We found a 24-hour rhythm in the hypothalamic expression of WNT target genes, with decreasing levels during the light and increasing levels during the dark phase in both LD and SD hamsters. Moreover, leptin administration led to a further increase in LRP-6 activation in hamsters from both photoperiods. Taken together, we demonstrate a novel integration site for the leptin signal in the hypothalamus, potentially linking the WNT pathway to body weight regulation. Furthermore, our results suggest an important role of canonical WNT signalling in the seasonal as well as daily neuroendocrine control of energy metabolism in Djungarian hamsters. By examining whether hypothalamic leptin signalling and whole body metabolism are modulated by a daily rhythm, we detected a 24-hour rhythm of STAT3 phosphorylation, a marker for activated leptin signalling on a molecular level, in the hypothalamus of wild-type mice. Both basal as well as leptin-induced leptin sensitivity were highest at the end of the dark (active) phase and lowest at the end of the light (inactive) phase. Furthermore, we found that leptin sensitivity on a behavioural level followed the same rhythm, with mice showing a greater response to exogenous leptin at the end of the dark phase at Zeitgeber time (ZT) 0 compared with the end of the light phase at ZT12. Throughout the 24-hour cycle, mice displayed a robust rhythm in food intake, locomotor activity as well as oxygen consumption and energy expenditure, with reduced whole body metabolism during their inactive and increased metabolic rate during their active phase. In DIO mice that were subjected to high-fat diet (HFD) feeding, we found a disruption of the 24-hour rhythmic regulation of leptin pathway activation on a molecular level for both basal and leptin-induced leptin sensitivity. Intriguingly, we demonstrated that this hypothalamic leptin resistance is a temporary phenomenon that persists only at specific times during the day. Responsiveness to leptin was deteriorated during the second part of the dark and the first half of the light phase (ZT21 – ZT6), but identical to mice fed low-fat diet (LFD) at all other times on both the molecular and behavioural level. Furthermore, DIO mice displayed a disruption of the daily rhythms in food intake, locomotor activity, oxygen consumption and energy expenditure. We found that the daily caloric overconsumption observed in mice fed HFD was restricted to the phase when DIO mice were leptin resistant relative to mice fed LFD. In conclusion, these findings provide strong evidence for a crucial role of the 24-hour rhythm of leptin sensitivity in the control of energy metabolism. We furthermore demonstrated that mice with access to HFD exclusively during their leptin resistant phase (ZT21 – ZT3) displayed impairments in a variety of parameters that indicate metabolic health, such as compromised rhythms of locomotor activity, metabolic rate, and energy expenditure as well as increased circulating insulin levels. Restricting HFD exclusively to the leptin sensitive phase (ZT9 – ZT15), on the other hand, protected mice from the development of these severe metabolic impairments. To date it is still largely unknown whether HFD-induced development of metabolic diseases results from an increase in body fat content, diet composition or disrupted circadian rhythms. We observed these differences between TRF groups despite an identical reduction in body weight and plasma leptin levels in all TRF mice, suggesting that they are based on the time of food intake during the 24-hour rhythm of leptin sensitivity, but independent from factors such as body composition or HFD content. Nonetheless, all mice fed HFD displayed a reduction in the absolute values of average metabolic rate and energy expenditure relative to mice fed LFD, demonstrating that also the HFD itself affects energy metabolism. In conclusion, these results demonstrate that TRF is efficient in the reduction of body weight and the amelioration of metabolic health. However, our findings also highlight the importance of synchronising food intake with daily physiological rhythms to maintain metabolic health. Taken together, this thesis identifies novel pathways that are involved in the neuroendocrine regulation of energy metabolism and provides new insights into the connection between physiological rhythms and the development of metabolic diseases

Precisely Timed Signal Transmission in Neocortical Networks with Reliable Intermediate-Range Projections

The mammalian neocortex has a remarkable ability to precisely reproduce behavioral sequences or to reliably retrieve stored information. In contrast, spiking activity in behaving animals shows a considerable trial-to-trial variability and temporal irregularity. The signal propagation and processing underlying these conflicting observations is based on fundamental neurophysiological processes like synaptic transmission, signal integration within single cells, and spike formation. Each of these steps in the neuronal signaling chain has been studied separately to a great extend, but it has been difficult to judge how they interact and sum up in active sub-networks of neocortical cells. In the present study, we experimentally assessed the precision and reliability of small neocortical networks consisting of trans-columnar, intermediate-range projections (200–1000 μm) on a millisecond time-scale. Employing photo-uncaging of glutamate in acute slices, we activated a number of distant presynaptic cells in a spatio-temporally precisely controlled manner, while monitoring the resulting membrane potential fluctuations of a postsynaptic cell. We found that signal integration in this part of the network is highly reliable and temporally precise. As numerical simulations showed, the residual membrane potential variability can be attributed to amplitude variability in synaptic transmission and may significantly contribute to trial-to-trial output variability of a rate signal. However, it does not impair the temporal accuracy of signal integration. We conclude that signals from intermediate-range projections onto neocortical neurons are propagated and integrated in a highly reliable and precise manner, and may serve as a substrate for temporally precise signal transmission in neocortical networks

Deep Adaptation - The Spatial Dimension

The future, which we thought we had maybe another decade to prepare for, is now suddenly here. In all likelihood, we can expect further crises such as the Covid-19 pandemic or of similar severity, especially in the context of climate change. They will render the 21st century radically different from the 20th: conventions, techniques, and social practices we are familiar with will disappear. Our responsibilities and roles as architects and urban planners will also change fundamentally in this process. We will work in increasingly volatile and vulnerable contexts and constellations. Until now, many actors in politics, but also in academia and research, have played down or denied the vulnerability of our urban structures to the risks that are the direct effects of our current way of life. In the search for alternative and, in a sense, more realistic perspectives, Jem Bendell’s concept of “Deep Adaptation”, which has been widely and controversially discussed since its first publication in 2018, calls for a shift: he urges us to prepare for the collapse of certain systems that currently govern our lives – and to see this as an opportunity for positive change. This change and the resulting challenges we are facing are primarily not technological, but above all social, economic, and organisational in nature. Moreover, they are highly interdependent and all-encompassing; they require systemic change, profound transformations, and adaptations of action. It is therefore not a question of developing technical solutions in isolation, but rather of fundamentally rethinking the way we live, operate, work, travel, and interact. This issue of SPOOL seeks to explore the spatial dimension of the Deep Adaptation concept and how it can be put to use in the spatial disciplines such as urban planning, landscape planning, urban design, and architecture

Beyond the Cortical Column: Abundance and Physiology of Horizontal Connections Imply a Strong Role for Inputs from the Surround

Current concepts of cortical information processing and most cortical network models largely rest on the assumption that well-studied properties of local synaptic connectivity are sufficient to understand the generic properties of cortical networks. This view seems to be justified by the observation that the vertical connectivity within local volumes is strong, whereas horizontally, the connection probability between pairs of neurons drops sharply with distance. Recent neuroanatomical studies, however, have emphasized that a substantial fraction of synapses onto neocortical pyramidal neurons stems from cells outside the local volume. Here, we discuss recent findings on the signal integration from horizontal inputs, showing that they could serve as a substrate for reliable and temporally precise signal propagation. Quantification of connection probabilities and parameters of synaptic physiology as a function of lateral distance indicates that horizontal projections constitute a considerable fraction, if not the majority, of inputs from within the cortical network. Taking these non-local horizontal inputs into account may dramatically change our current view on cortical information processing

It’s too late for pessimism: How the Deep Adaptation Agenda is relevant for teaching in the spatial disciplines

The crises we face today call for a careful assessment of our collective and individual understandings and responses. The past decades have shown us that acknowledgement of the emergencies alone is not sufficient to address the problems, especially within the complex context and conditions of the built environment. In the face of ‘inevitable’ change, and of current and future challenges, this urges us to direct a critical glance towards how we understand and frame the problems as spatial practitioners, how we position ourselves towards them, and how our ethical and professional responsibilities and agencies must change. As an open question and a long-term endeavour, this echoes within the context of academia. However, a central position has yet to emerge. In this article, we give an account of our experiences by taking a closer look at the approaches, formats, and method we have employed at the Professorship of Urban Design at TU Munich and elaborate on how these concerns can be embedded in the content, systems, and structures of teaching, and how the Deep Adaptation Agenda plays a facilitating role in this ongoing attempt

Skin Admittance Measurement for Emotion Recognition: A Study over Frequency Sweep

The electrodermal activity (EDA) is a reliable physiological signal for monitoring the sympathetic nervous system. Several studies have demonstrated that EDA can be a source of effective markers for the assessment of emotional states in humans. There are two main methods for measuring EDA: endosomatic (internal electrical source) and exosomatic (external electrical source). Even though the exosomatic approach is the most widely used, differences between alternating current (AC) and direct current (DC) methods and their implication in the emotional assessment field have not yet been deeply investigated. This paper aims at investigating how the admittance contribution of EDA, studied at different frequency sources, affects the EDA statistical power in inferring on the subject?s arousing level (neutral or aroused). To this extent, 40 healthy subjects underwent visual affective elicitations, including neutral and arousing levels, while EDA was gathered through DC and AC sources from 0 to 1 kHz. Results concern the accuracy of an automatic, EDA feature-based arousal recognition system for each frequency source. We show how the frequency of the external electrical source affects the accuracy of arousal recognition. This suggests a role of skin susceptance in the study of affective stimuli through electrodermal response

Breathe Easy EDA: a MATLAB toolbox for psychophysiology data management, cleaning, and analysis

Electrodermal activity (EDA) recordings are widely used in experimental psychology to measure skin conductance responses (SCRs) that reflect sympathetic nervous system arousal. However, irregular respiration patterns and deep breaths can cause EDA fluctuations that are difficult to distinguish from genuine arousal-related SCRs, presenting a methodological challenge that increases the likelihood of false positives in SCR analyses. Thus, it is crucial to identify respiration-related artifacts in EDA data. Here we developed a novel and freely distributed MATLAB toolbox, Breathe Easy EDA (BEEDA). BEEDA is a flexible toolbox that facilitates EDA visual inspection, allowing users to identify and eliminate respiration artifacts. BEEDA further includes functionality for EDA data analyses (measuring tonic and phasic EDA components) and reliability analyses for artifact identification. The toolbox is suitable for any experiment recording both EDA and respiration data, and flexibly adjusts to experiment-specific parameters (e.g., trial structure and analysis parameters)

Validation of wireless sensors for psychophysiological studies

James One (MindProber Labs) is a wireless psychophysiological device comprising two sensors: one measuring electrodermal activity (EDA), the other photoplethysmography (PPG). This paper reports the validation of James One's EDA sensor by comparing its signal against a research grade polygraph. Twenty participants were instructed to perform breathing exercises to elicit the modulation of EDA and heart rate, while the physiological signal was captured simultaneously on James One and a Biopac MP36. The resulting EDA and PPG records collected from both systems were comprehensively compared. Results suggest that James One captures EDA signal with a quality comparable to a research grade equipment, this constituting a reliable means of capturing data while minimizing setup time and intrusiveness.P.S.M. was supported by an FCT fellowship grant (PhD-iHES program) with the reference PDE/BDE/113601/2015