Robot-assisted fMRI assessment of early brain development

Preterm birth can interfere with the intra-uterine mechanisms driving cerebral development during the third trimester of gestation and often results in severe neuro-developmental impairments. Characterizing normal/abnormal patterns of early brain maturation could be fundamental in devising and guiding early therapeutic strategies aimed at improving clinical outcome by exploiting the enhanced early neuroplasticity. Over the last decade the morphology and structure of the developing human brain has been vastly characterized; however the concurrent maturation of brain function is still poorly understood. Task-dependent fMRI studies of the preterm brain can directly probe the emergence of fundamental neuroscientific notions and also provide clinicians with much needed early diagnostic and prognostic information. To date, task-fMRI studies of the preterm population have however been hampered by methodological challenges leading to inconsistent and contradictory results. In this thesis I present a modular and flexible system to provide clinicians and researchers with a simple and reliable solution to deliver computer-controlled stimulation patterns to preterm infants during task-fMRI experiments. The system is primarily aimed at studying the developing sensori-motor system as preterm infants are often affected by neuro-motor dysfunctions such as cerebral palsy. Wrist and ankle robotic stimulators were developed and firstly used to study the emerging somatosensory “homunculus”. The wrist robotic stimulator was then used to characterize the development of the sensori-motor system throughout the mid-to-late preterm period. An instrumented pacifier system was also developed to explore the potential sensorimotor modulation of early sucking activity; however, despite its clear potential to be employed in future fMRI studies, results have not yet been obtained on preterm infants. Functional difficulties associated with prematurity are likely to extend to multi-sensory integration, and the olfactory system currently remains under-investigated despite its clear developmental importance. A custom olfactometer was developed and used to assess its early functionality.Open Acces

Models of human preference for learning reward functions

The utility of reinforcement learning is limited by the alignment of reward functions with the interests of human stakeholders. One promising method for alignment is to learn the reward function from human-generated preferences between pairs of trajectory segments, a type of reinforcement learning from human feedback (RLHF). These human preferences are typically assumed to be informed solely by partial return, the sum of rewards along each segment. We find this assumption to be flawed and propose modeling human preferences instead as informed by each segment's regret, a measure of a segment's deviation from optimal decision-making. Given infinitely many preferences generated according to regret, we prove that we can identify a reward function equivalent to the reward function that generated those preferences, and we prove that the previous partial return model lacks this identifiability property in multiple contexts. We empirically show that our proposed regret preference model outperforms the partial return preference model with finite training data in otherwise the same setting. Additionally, we find that our proposed regret preference model better predicts real human preferences and also learns reward functions from these preferences that lead to policies that are better human-aligned. Overall, this work establishes that the choice of preference model is impactful, and our proposed regret preference model provides an improvement upon a core assumption of recent research. We have open sourced our experimental code, the human preferences dataset we gathered, and our training and preference elicitation interfaces for gathering a such a dataset.Comment: 16 pages (40 pages with references and appendix), 23 figure

Maturation of sensori-motor functional responses in the preterm brain

†Authors contributed equally to the work and have shared first authorship. Preterm birth engenders an increased risk of conditions like cerebral palsy and therefore this timemay be crucial for the brain’s developing sensori-motor system. However, little is known about how cortical sensori-motor function matures at this time, whether development is influencedbyexperience, andabout its role in spontaneousmotor behavior.Weaimed to systematically characterize spatial and temporal maturation of sensori-motor functional brain activity across this period using functional MRI and a custom-made robotic stimulation device. We studied 57 infants aged from 30+ 2 to 43 + 2 weeks postmenstrual age. Following both induced and spontaneous right wrist movements, we saw consistent positive blood oxygen level–dependent functional responses in the contralateral (left) primary somatosensory and motor cortices. In addition, we saw a maturational trend toward faster, higher amplitude, and more spatially dispersed functional responses; and increasing integration of the ipsilateral hemisphere and sensori-motor associative areas. We also found that interhemispheric functional connectivity was significantly related to ex-utero exposure, suggesting the influence of experience-dependent mechanisms. At term equivalent age, we saw a decrease in both response amplitude and interhemispheric functional connectivity, and an increase in spatial specificity, culminating in the establishment of a sensori-motor functional response similar to that seen in adults

2020 WSES guidelines for the detection and management of bile duct injury during cholecystectomy.

Bile duct injury (BDI) is a dangerous complication of cholecystectomy, with significant postoperative sequelae for the patient in terms of morbidity, mortality, and long-term quality of life. BDIs have an estimated incidence of 0.4-1.5%, but considering the number of cholecystectomies performed worldwide, mostly by laparoscopy, surgeons must be prepared to manage this surgical challenge. Most BDIs are recognized either during the procedure or in the immediate postoperative period. However, some BDIs may be discovered later during the postoperative period, and this may translate to delayed or inappropriate treatments. Providing a specific diagnosis and a precise description of the BDI will expedite the decision-making process and increase the chance of treatment success. Subsequently, the choice and timing of the appropriate reconstructive strategy have a critical role in long-term prognosis. Currently, a wide spectrum of multidisciplinary interventions with different degrees of invasiveness is indicated for BDI management. These World Society of Emergency Surgery (WSES) guidelines have been produced following an exhaustive review of the current literature and an international expert panel discussion with the aim of providing evidence-based recommendations to facilitate and standardize the detection and management of BDIs during cholecystectomy. In particular, the 2020 WSES guidelines cover the following key aspects: (1) strategies to minimize the risk of BDI during cholecystectomy; (2) BDI rates in general surgery units and review of surgical practice; (3) how to classify, stage, and report BDI once detected; (4) how to manage an intraoperatively detected BDI; (5) indications for antibiotic treatment; (6) indications for clinical, biochemical, and imaging investigations for suspected BDI; and (7) how to manage a postoperatively detected BDI

Environmental and health-related external costs of meat consumption in Italy: estimations and recommendations through life cycle assessment

The literature on the external costs of food consumption is limited. This study aims at advancing in this field by translating the environmental and health-related impacts generated by the life-cycle of meat into external costs via monetization. The main types of meat consumed in Italy are used as a case study. The potential external costs are estimated via attributional life cycle assessment (LCA), using: i) the ReCiPe method for the environmental impact assessment (fourteen impact categories), ii) the population attributional fractions for the health damage from meat ingestion, and iii) the CE Delft environmental prices for monetization. Results show that processed pork and beef generate the highest costs on society, with an external cost of approximately 2€ per 100 g. Fresh pork and poultry follow, with a cost of 1€ and 0.5€ per 100 g, respectively. For comparison, the potential external costs of legumes (i.e., a plant-based alternative to meat) are estimated to be from eight to twenty times lower than meat (around 0.05€ per 100 g of legumes). In 2018, meat consumed in Italy potentially generated a cost on society of 36.6 bn€. The burden arises almost equally from impacts generated before meat ingestion (mainly associated with the emissions arisen from farming), and after the ingestion (due to diseases potentially associated with meat consumption). A sensitivity analysis on the main parameters revealed a large uncertainty on the final yearly cost, ranging from 19 to 93 bn€. Although more research is needed to improve the accuracy and the validity of the models used in the study (e.g., human health impact assessment, monetization) and to include potential external costs currently unaccounted for (e.g., water use, animal welfare, occupational health), results show unequivocal significant costs associated with meat consumption. We thus advocate for policies aimed at reducing these costs and allocating them properly

Technology-aided assessment of sensorimotor function in early infancy

There is a pressing need for new techniques capable of providing accurate information about sensorimotor function during the first 2 years of childhood. Here, we review current clinical methods and challenges for assessing motor function in early infancy, and discuss the potential benefits of applying technology-assisted methods. We also describe how the use of these tools with neuroimaging, and in particular functional magnetic resonance imaging (fMRI), can shed new light on the intra-cerebral processes underlying neurodevelopmental impairment. This knowledge is of particular relevance in the early infant brain, which has an increased capacity for compensatory neural plasticity. Such tools could bring a wealth of knowledge about the underlying pathophysiological processes of diseases such as cerebral palsy; act as biomarkers to monitor the effects of possible therapeutic interventions; and provide clinicians with much needed early diagnostic information

The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications

In reinforcement learning (RL), a reward function that aligns exactly with a task's true performance metric is often necessarily sparse. For example, a true task metric might encode a reward of 1 upon success and 0 otherwise. The sparsity of these true task metrics can make them hard to learn from, so in practice they are often replaced with alternative dense reward functions. These dense reward functions are typically designed by experts through an ad hoc process of trial and error. In this process, experts manually search for a reward function that improves performance with respect to the task metric while also enabling an RL algorithm to learn faster. This process raises the question of whether the same reward function is optimal for all algorithms, i.e., whether the reward function can be overfit to a particular algorithm. In this paper, we study the consequences of this wide yet unexamined practice of trial-and-error reward design. We first conduct computational experiments that confirm that reward functions can be overfit to learning algorithms and their hyperparameters. We then conduct a controlled observation study which emulates expert practitioners' typical experiences of reward design, in which we similarly find evidence of reward function overfitting. We also find that experts' typical approach to reward design---of adopting a myopic strategy and weighing the relative goodness of each state-action pair---leads to misdesign through invalid task specifications, since RL algorithms use cumulative reward rather than rewards for individual state-action pairs as an optimization target. Code, data: github.com/serenabooth/reward-design-peril

Development of BOLD signal hemodynamic responses in the human brain

In the rodent brain the hemodynamic response to a brief external stimulus changes significantly during development. Analogous changes in human infants would complicate the determination and use of the hemodynamic response function (HRF) for functional magnetic resonance imaging (fMRI) in developing populations. We aimed to characterize HRF in human infants before and after the normal time of birth using rapid sampling of the Blood Oxygen Level Dependent (BOLD) signal. A somatosensory stimulus and an event related experimental design were used to collect data from 10 healthy adults, 15 sedated infants at term corrected post menstrual age (PMA) (median 41 + 1 weeks), and 10 preterm infants (median PMA 34 + 4 weeks). A positive amplitude HRF waveform was identified across all subject groups, with a systematic maturational trend in terms of decreasing time-to-peak and increasing positive peak amplitude associated with increasing age. Application of the age-appropriate HRF models to fMRI data significantly improved the precision of the fMRI analysis. These findings support the notion of a structured development in the brain's response to stimuli across the last trimester of gestation and beyond