Executive functions | EPFL Graph Search

In cognitive science and neuropsychology, executive functions (collectively referred to as executive function and cognitive control) are a set of cognitive processes that are necessary for the cognitive control of behavior: selecting and successfully monitoring behaviors that facilitate the attainment of chosen goals. Executive functions include basic cognitive processes such as attentional control, cognitive inhibition, inhibitory control, working memory, and cognitive flexibility. Higher-order executive functions require the simultaneous use of multiple basic executive functions and include planning and fluid intelligence (e.g., reasoning and problem-solving). Executive functions gradually develop and change across the lifespan of an individual and can be improved at any time over the course of a person's life. Similarly, these cognitive processes can be adversely affected by a variety of events which affect an in

Electrical spinal cord stimulation protocols to regulate neurological functions after spinal cord injury

Salif Axel Komi

Spinal cord injury (SCI) is a life-changing event. People who suffer from it lose their abilityto move normally and are subject to life-threatening symptoms. When the insult is not toosevere, partial recovery is possible. Otherwise, for severely affected people, the perspectives toever retrieve normal functions is almost non-existent. A critically important window to promoteplasticity is in the acute phase after the trauma (weeks to months). However, at this stage,people cannot take active part in rehabilitation programs due to their incapacity to activate theirlimbs and to the apparition of severe autonomic symptoms such as orthostatic hypotension.Hence, current activity-based treatments are of little help for this population. Consequently, SCIdramatically affects their autonomy and quality of life on the life-long term.Continuous Epidural Electrical Stimulation (EES) of the spinal cord has been proposed as amethod to reactivate dormant neural networks innervated below the site of injury. It enablesrobust control over locomotion and autonomic functions. In animal models of severe lesion,continuous EES promoted long lasting recovery of motor abilities when coupled with an intensivetraining. In human, its recent application indeed supported overground walking in chronicallyand severely injured people, but only showed limited plastic effects when compared to animals.Why? Recent advances support that continuous EES abolishes proprioceptive feedback thatis essential to promote recovery. Moreover, late treatment of severe injuries consistently fail apromoting recuperation of functions. Alternatively, over the last decade, our laboratory developeda spatio-temporally patterned approach to EES. In addition to restore fine control over motorfunctions, this technique avoids the caveats of continuous EES, and hypothetically opens a windowof opportunity for plasticity to happen. In this thesis, we propose a translation of this concept tohumans. We first demonstrate that spatio-temporal EES restores robust and versatile locomotorcontrol in people with chronic incomplete, though severe, SCI. Furthermore, the results supportan aptitude of this approach to promote long lasting recovery of functions without stimulationafter 5 months of intensive training. We then report on a patient-tailored technology, thatincludes personalized computational models enabling precise pre-operative planning strategies, anew electrode-lead and control softwares. This technology enables restoration of various motorfunctions in people with chronic and motor-complete injuries within few hours after beginningof therapy. Finally, we transfer this targeted approach to the control of blood pressure. Wedemonstrate that closed-loop stimulation protocols support a precise control over arterial bloodpressure in rodents, non-humane primates and humans with severe SCI submitted to challengingcardiovascular conditions. Combined, the results presented in this manuscript open a clinicallyrealistic perspective for the application of EES acutely after injury and to potentially promoterobust recovery in severe SCI.

EPFL2021

Seascape Genomics of the Sugar Kelp Saccharina latissima along the North Eastern Atlantic Latitudinal Gradient

Chloé Christiane Laurence Jollivet, Stéphane Mauger

Temperature is one of the most important range-limiting factors for many seaweeds. Driven by the recent climatic changes, rapid northward shifts of species' distribution ranges can potentially modify the phylogeographic signature of Last Glacial Maximum. We explored this question in detail in the cold-tolerant kelp species Saccharina latissima, using microsatellites and double digest restriction site-associated DNA sequencing ( ddRAD-seq) derived single nucleotide polymorphisms (SNPs) to analyze the genetic diversity and structure in 11 sites spanning the entire European Atlantic latitudinal range of this species. In addition, we checked for statistical correlation between genetic marker allele frequencies and three environmental proxies (sea surface temperature, salinity, and water turbidity). Our findings revealed that genetic diversity was significantly higher for the northernmost locality (Spitsbergen) compared to the southern ones (Northern Iberia), which we discuss in light of the current state of knowledge on phylogeography of S. latissima and the potential influence of the recent climatic changes on the population structure of this species. Seven SNPs and 12 microsatellite alleles were found to be significantly associated with at least one of the three environmental variables. We speculate on the putative adaptive functions of the genes associated with the outlier markers and the importance of these markers for successful conservation and aquaculture strategies for S. latissima in this age of rapid global change.

MDPI2020

Streaming and Matching Problems with Submodular Functions

Paritosh Garg

Submodular functions are a widely studied topic in theoretical computer science. They have found several applications both theoretical and practical in the fields of economics, combinatorial optimization and machine learning. More recently, there have also been numerous works that study combinatorial problems with submodular objective functions. This is motivated by their natural diminishing returns property which is useful in real-world applications. The thesis at hand is concerned with the study of streaming and matching problems with submodular functions.Firstly, motivated by developing robust algorithms, we propose a new adversarial injections model, in which the input is ordered randomly, but an adversary may inject misleading elements at arbitrary positions. We study the maximum matching problem and cardinality constrained monotone submodular maximization. We show that even under this seemingly powerful adversary, it is possible to break the barrier of 1/2 for both these problems in the streaming setting. Our main result is a novel streaming algorithm that computes a 0.55-approximation for cardinality constrained monotone submodular maximization.In the second part of the thesis, we study the problem of matroid intersection in the semi-streaming setting. Our main result is a (2 + e)-approximate semi-streaming algorithm for weighted matroid inter- section improving upon the previous best guarantee of 4 + e. While our algorithm is based on the local ratio technique, its analysis differs from the related problem of weighted maximum matching and uses the concept of matroid kernels. We are also able to generalize our results to work for submodular functions by adapting ideas from a recent result by Levin and Wajc (SODA'21) on submodular maximization subject to matching constraints.Finally, we study the submodular Santa Claus problem in the restricted assignment case. The submodular Santa Claus problem was introduced in a seminal work by Goemans, Harvey, Iwata, and Mirrokni (SODA'09) as an application of their structural result. In the mentioned problem n unsplittable resources have to be assigned to m players, each with a monotone submodular utility function fi. The goal is to maximize mini fi(Si) where S1, . . . , Sm is a partition of the resources. The result by Goemans et al. implies a polynomial time O(n1/2+e)-approximation algorithm. In the restricted assignment case, each player is given a set of desired resources Gi and the individual valuation functions are defined as fi(S)= f(SnGi). OurmainresultisaO(loglog(n))-approximation algorithm for the problem. Our proof is inspired by the approach of Bansal and Srividenko (STOC'06) to the Santa Claus problem. Com- pared to the more basic linear setting, the introduction of submodularity requires a much more involved analysis and several new ideas.

EPFL2022