Understanding | EPFL Graph Search

Understanding is a cognitive process related to an abstract or physical object, such as a person, situation, or message whereby one is able to use concepts to model that object. Understanding is a relation between the knower and an object of understanding. Understanding implies abilities and dispositions with respect to an object of knowledge that are sufficient to support intelligent behavior. Understanding is often, though not always, related to learning concepts, and sometimes also the theory or theories associated with those concepts. However, a person may have a good ability to predict the behavior of an object, animal or system—and therefore may, in some sense, understand it—without necessarily being familiar with the concepts or theories associated with that object, animal, or system in their culture. They may have developed their own distinct concepts and theories, which may be equivalent, better or worse than the recognized standard concepts and theories of their culture. Thu

Financing Biomedical Ventures - Myths and Realities

Jeffrey Scott Behrens

Angel funding is an important source of capital for startup ventures (J. Sohl 2019), providing a similar level of capital as institutional venture capital (OECD 2011). But angel funding is challenging to study due to the informal nature of the activity. A common paradigm for new venture funding argues that new ventures initially fund their activities with angel investment and then, as they show success, make progress to commercialization and de-risk core venture propositions, ventures transition to more professional institutional (venture capital) funding. A belief in this paradigm can strongly influence early venture creation activities, and assumptions about the later availability of capital from institutional venture capital underpin many startup business plans. However, the literature exploring this phenomenon is very sparse, and the question of the relationship of angel to venture funding transition has rarely been studied. By analyzing a large and robust dataset, this thesis advances the understanding of the actual behavior of investors and the impact this early behavior, and the funding choices involved, have on company outcomes. This thesis also explores a novel form of venture investing and places it into a broader context of new venture funding that may help explain some of the key observations discussed. These fundamentally empirical studies examine the nature/reality of important entrepreneurial phenomena of interactions between angel and venture funding in novel ways, pose questions, and identify a set results that point to a potential market failure. Attempts are made to understand these results and place them into the contexts of both research theory and a broader understanding of entrepreneurial behavior; there certainly remain a set of unanswered questions and potential fruitful directions for future research.

EPFL2020

Genetic selection for low glucocorticoid responsiveness recapitulates PTSD-related phenotypes: a behavioral, neuroimaging and sleep-physiology study

Silvia Monari

Humans show inter-individual differences in vulnerability to develop post-traumatic stress disorder (PTSD) following exposure to trauma. Several critical biobehavioral features have been consistently described in PTSD patients, including blunted cortisol levels, smaller hippocampal size, sleep disturbances. However, because of the delay between trauma exposure and the onset of symptoms characteristic of PTSD, only a few longitudinal studies have tried to dissect whether these features constitute pre-trauma risk factors or consequences of the trauma. Enormous effort in animal and human studies has been dedicated to understanding mechanisms of conditioned fear and fear extinction, processes that are at the core of PTSD. However, the same progress has not been translated into psychiatric practice for PTSD. Deepening our understanding of the contribution of key factors to PTSD-related alterations can serve to develop effective treatments.In particular, with regard to low cortisol levels in PTSD pathophysiology, a causative role for blunted glucocorticoid responsiveness in PTSD has not been demonstrated yet.Here, we have addressed this question in lines of Wistar rats genetically-selected for their differential habituation of glucocorticoid responses to stress (LOW-, INTER-, HIGH-CORT Responder rats) and focused on fear extinction, a hallmark of PTSD symptomology, as one of the key features. As a first step, we looked whether divergent trajectories of glucocorticoid responsiveness were associated with brain volume abnormalities, prompted by the influential role of glucocorticoid in brain development. Notably, rats with low or high corticosterone responsiveness exhibit smaller hippocampi, regardless of trauma exposure, compared to rats with normative corticosterone levels. Similarly, the distribution of corticosteroid receptors in the hippocampus presented similarities between the LOW-CR and the HIGH-CR rats with higher mineralocorticoid receptors (MR) and less glucocorticoid receptors (GR). Although LOW- and HIGH-CR rats displayed a similar hippocampal profile at the structural and molecular levels, only LOW-CR male rats exhibited strong deficits in extinction consolidation compared to rats with 'normative' glucocorticoid responses (INTER-CR rats), and showed higher fear response both at few days and at several weeks after trauma exposure. We next tested the causal involvement of corticosterone in the fear extinction consolidation, and found that post-extinction corticosterone treatment markedly prevented the deficits in extinction memory and attenuated fear relapse. In addition, pharmacological inhibition of corticosterone levels during extinction memory consolidation, but not during training, in the INTER-CR rats led to extinction deficits at retrieval one day later. These results indicate that blunted corticosterone levels contribute to confer major vulnerability than having a small hippocampus, and that consolidation processes following extinction are mainly affected by low corticosterone levels.It is well known that glucocorticoids play an important role in memory consolidation processes and that sleep disturbances are a diagnostic criterion of PTSD. Therefore, we investigated in greater detail the sleep architecture in undisturbed condition and during the consolidation period of the extinction phase, which is known to be supported by sleep-dependent processes. In polysomnographic recordings, we found that rats with blunted corticos

EPFL2022

Computational Methods for Audio-Visual Analysis of Emergent Leadership in Teams

Dairazalia Sanchez Cortes

Face-to-face interactions are part of everyday life, ranging from family to working in teams and to global communities. Social psychologists have long studied these interactions with the aim of understanding behavior, motivations, and emergence of interaction patterns. An organization is environment rich in daily interactions including structured periodic meetings, planning, brainstorming, negotiations, decision-making and informal gatherings and leaders play a key role in many of them. Leader face problems, propose solutions, make decisions, and often are the main source of inspiration of the employees. Identifying emergent leaders at early stages in organizations is a key issue in organizational behavioral research, and a new problem in social computing. The study of this phenomenon requires sensing of natural face-to-face interactions, automatic extraction of behavioral cues and reliable machine learning algorithms to identify emergent leaders. In this thesis we present a computational approach to analyze emergence of leadership in small groups using multimodal audio and visual features. In the computational framework, we first present an analysis on how an emergent leader is perceived in newly formed, small groups. We present the ELEA (Emergent LEadership Analysis) corpus collected with the aim of analyzing emergence of leaders. We propose to analyze emergent leaders, using a variety of nonverbal cues studied in social psychology and automatically extracted from audio and video streams. Our analysis address how the emergent leader is perceived by his/her peers in terms of speaking and visual active, and its relation with the most dominant person (including external observers’ perception). We then propose to investigate which individual nonverbal channel (or combination of features from different channels) provides better inferences of the emergent leader and related concepts using unsupervised and supervised methods. We use a supervised collective approach which adds relational information to the nonverbal cues and compare its performance, with the performance of supervised (non-collective) and unsupervised methods. We also propose to capture the social visual attention patterns from automatically extracted features from video, in order to analyze who receives or gives the largest amount of visual attention in the group. Finally, with the aim of understanding who receives the largest amount of visual attention while speaking and who has the highest dominance ratio (i.e., many occurrences of looking at others while speaking and few occurrences of looking at others while not speaking). We synchronize the audio and video streams to capture the speaking and attention activity patterns. We end our analysis exploring the impact of the verbal content (language style) in the interactions and its influence in the perception of emergent leaders. For the language style analysis, we propose to compute word categories extracted from manual transcriptions of the discussions as well as from automatically detected keywords. We propose to use a supervised method to obtain the relevant features, and to use only the top word categories to predict the emergent leader and related concepts in each group. We then propose to differentiate word categories, between highly context-related and context-free, to explore the feasibility to infer the emergent leader in a fully automatic approach from the context-free language style. This dissertation address an audio and visual analysis of the ubiquitous phenomenon of emergent leadership in a fully automatic computational approach from face-to-face interactions. The nonverbal behavioral analysis is inspired in previous works on social psychology in the context of emergent leadership and related concepts. The automatically extracted nonverbal features are modeled to feed state-of-the-art machine learning techniques in order to infer emergent leaders.

EPFL2013