Concept

Punishment (psychology)

Publications associées (33)

Plasticity of sensory representations in the posterior insular cortex during fear learning

Aversively-motivated associative learning allows animals to avoid harm and thus ensures survival. Aversive learning can be studied by the fear learning paradigm, in which an innocuous sensory stimulus like a tone (conditioned stimulus, CS), acquires a nega ...

EPFL2023

Mechanisms underlying reinforcement learning of motor skills

Pierre Theopistos Vassiliadis

Motor learning allows animals, including human beings, to acquire skills that are es-sential for efficient interactions with the environment. This ability to learn new motor skills is of great practical relevance for daily-life activities (such as when lea ...

EPFL2023

Experimental investigation of dowel action using advanced measurement techniques

Aurelio Muttoni, Marko Pejatovic

Existing shear-cracked structures need to be reliably verified in order to avoid redundant interventions. Code provisions often raise shear safety and/or fatigue life concerns of the reinforcement subjected to stress concentrations due to cyclic dowel acti ...

2022

An insular cortex - lateral amygdala network in fear learning

Shriya Palchaudhuri

Animals are capable of evaluating sensory cues for possible threats and adapting their behaviours accordingly. Fear learning is an evolutionarily conserved behaviour crucial for animal survival, during which sensory percepts with a negative reinforcing qua ...

EPFL2022

Bio-inspired Reflex System for Learning Visual Information for Resilient Robotic Manipulation

Josephine Anna Eleanor Hughes, Kai Christian Junge

Humans have an incredible sense of self-preservation that is both instilled, and also learned through experience. One system which contributes to this is the pain and reflex system which both minimizes damage through involuntary reflex ac- tions and also s ...

2022

Reinforced Attention for Few-Shot Learning and Beyond

Tong Zhang

Few-shot learning aims to correctly recognize query samples from unseen classes given a limited number of support samples, often by relying on global embeddings of images. In this paper, we propose to equip the backbone network with an attention agent, whi ...

IEEE COMPUTER SOC2021

Neural Correlates of Reinforcement Learning: eligibility trace, reward prediction error, novelty and surprise

He Xu

In reinforcement learning (RL), an agent makes sequential decisions to maximise the reward it can obtain from an environment. During learning, the actual and expected outcomes are compared to tell whether a decision was good or bad. The difference between ...

EPFL2020

Robot Mirroring: Promoting Empathy with an Artificial Agent by Reflecting the User's Physiological Affective States

Diego Felipe Paez Granados

Self-tracking aims to increase awareness, decrease undesired behaviors, and ultimately lead towards a healthier lifestyle. However, inappropriate communication of self-tracking results might cause the opposite effect. Subtle self-tracking feedback is an al ...

IEEE2020

Insular cortex processes aversive somatosensory information and is crucial for threat learning

Ralf Schneggenburger, Olexiy Kochubey, Denys Osypenko, Wei Tang, Michael Kintscher, Shriya Palchaudhuri, Emmanuelle Marie Brigitte Berret

Learning about threats is essential for survival. During threat learning, an innocuous sensory percept such as a tone acquires an emotional meaning when paired with an aversive stimulus such as a mild footshock. The amygdala is critical for threat memory f ...

AMER ASSOC ADVANCEMENT SCIENCE2019

Time intermittency in nondiffusive transport regimes of suprathermal ions in turbulent plasmas

Ambrogio Fasoli, Ivo Furno, Paolo Ricci, Marcelo Baquero Ruiz, Oulfa Chellaï, Fabian Manke

Intermittent phenomena have long been studied in the context of nondiffusive transport across a variety of fields. In the TORPEX device, the cross-field spreading of an injected suprathermal ion beam by electrostatic plasma turbulence can access different ...

AMER PHYSICAL SOC2019

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