Studying the Evolutionary Basis of Emotions Through Adaptive Neuroagents: Preliminary Settings and Results

We propose a method to investigate the adaptive and evolutionary function of emotions and affective states, in our case of ancestral fear - using Artificial Life and Evolutionary Robotics techniques. For this purpose, we developed a hybrid software-hardware capable to train artificial neuroagents equipped with a sensory-motor apparatus inspired on the iCub humanoid robot features. We trained populations of these agents throughout a genetic algorithm to perform a well-known neuropsychological task adapted to study emotional phenomena. The robots learnt to discriminate stressful emotional conditions (coping with “dangerous” stimuli) and no-stress conditions. Varying the network structures, the experimental conditions and comparing the outcomes we were able to delineate a very initial snapshot of behavioral and neural prerequisite for emotional-based actions. On the other hand, we have to stress that the main contribution we brought is setting-up a methodology to support future studies on emotions in natural and artificial agents

HFR1 Is Crucial for Transcriptome Regulation in the Cryptochrome 1-Mediated Early Response to Blue Light in Arabidopsis thaliana

Cryptochromes are blue light photoreceptors involved in development and circadian clock regulation. They are found in both eukaryotes and prokaryotes as light sensors. Long Hypocotyl in Far-Red 1 (HFR1) has been identified as a positive regulator and a possible transcription factor in both blue and far-red light signaling in plants. However, the gene targets that are regulated by HFR1 in cryptochrome 1 (cry1)-mediated blue light signaling have not been globally addressed. We examined the transcriptome profiles in a cry1- and HFR1-dependent manner in response to 1 hour of blue light. Strikingly, more than 70% of the genes induced by blue light in an HFR1-dependent manner were dependent on cry1, and vice versa. High overrepresentation of W-boxes and OCS elements were found in these genes, indicating that this strong cry1 and HFR1 co-regulation on gene expression is possibly through these two cis-elements. We also found that cry1 was required for maintaining the HFR1 protein level in blue light, and that the HFR1 protein level is strongly correlated with the global gene expression pattern. In summary, HFR1, which is fine-tuned by cry1, is crucial for regulating global gene expression in cry1-mediated early blue light signaling, especially for the function of genes containing W-boxes and OCS elements

Influence of antisynthetase antibodies specificities on antisynthetase syndrome clinical spectrum time course

Antisynthetase syndrome (ASSD) is a rare clinical condition that is characterized by the occurrence of a classic clinical triad, encompassing myositis, arthritis, and interstitial lung disease (ILD), along with specific autoantibodies that are addressed to different aminoacyl tRNA synthetases (ARS). Until now, it has been unknown whether the presence of a different ARS might affect the clinical presentation, evolution, and outcome of ASSD. In this study, we retrospectively recorded the time of onset, characteristics, clustering of triad findings, and survival of 828 ASSD patients (593 anti-Jo1, 95 anti-PL7, 84 anti-PL12, 38 anti-EJ, and 18 anti-OJ), referring to AENEAS (American and European NEtwork of Antisynthetase Syndrome) collaborative group's cohort. Comparisons were performed first between all ARS cases and then, in the case of significance, while using anti-Jo1 positive patients as the reference group. The characteristics of triad findings were similar and the onset mainly began with a single triad finding in all groups despite some differences in overall prevalence. The "ex-novo" occurrence of triad findings was only reduced in the anti-PL12-positive cohort, however, it occurred in a clinically relevant percentage of patients (30%). Moreover, survival was not influenced by the underlying anti-aminoacyl tRNA synthetase antibodies' positivity, which confirmed that antisynthetase syndrome is a heterogeneous condition and that antibody specificity only partially influences the clinical presentation and evolution of this condition

Immunohistochemical Method and Histopathology Judging for the Systemic Synuclein Sampling Study (S4)

Immunohistochemical (IHC) α-synuclein (Asyn) pathology in peripheral biopsies may be a biomarker of Parkinson disease (PD). The multi-center Systemic Synuclein Sampling Study (S4) is evaluating IHC Asyn pathology within skin, colon and submandibular gland biopsies from 60 PD and 20 control subjects. Asyn pathology is being evaluated by a blinded panel of specially trained neuropathologists. Preliminary work assessed 2 candidate immunoperoxidase methods using a set of PD and control autopsy-derived sections from formalin-fixed, paraffin-embedded blocks of the 3 tissues. Both methods had 100% specificity; one, utilizing the 5C12 monoclonal antibody, was more sensitive in skin (67% vs 33%), and was chosen for further use in S4. Four trainee neuropathologists were trained to perform S4 histopathology readings; in subsequent testing, their scoring was compared to that of the trainer neuropathologist on both glass slides and digital images. Specificity and sensitivity were both close to 100% with all readers in all tissue types on both glass slides and digital images except for skin, where sensitivity averaged 75% with digital images and 83.5% with glass slides. Semiquantitative (0-3) density score agreement between trainees and trainer averaged 67% for glass slides and 62% for digital images

Developing sensorimotor associations through attachment bonds.

Attachment bonds and positive affect help cognitive development and social interactions in infants and animals. In this paper we present a neural architecture to enable a robot to develop an attachment bond with a person or an object, and to discover the correct sensorimotor associations to maintain a desired affective state of well-being using a minimum amount of prior knowledge about the possible interactions with this object. We also discuss how our research on attachment bonds could further developmental robotics in the near future. 1

Receptor response and soma leakiness in a simulated spiking neural controller for a robot

This paper investigates different models of leakiness for the soma of a simulated spiking neural controller for a robot exhibiting negative photo-taxis. It also investigates two models of receptor response to stimulus levels. The results show that exponential decay of ions across the soma and of a receptor response function where intensity is proportional to intensity is the best combination for dark seeking behaviour

Фундаментальные и прикладные проблемы современной механики : (Доклады Всероссийской научной конференции) Томск, 2-4 июня 1998 г

We propose an evolving ecosystem approach to evolving complex agent behaviour based on the principle of natural selection. The agents start with very limited functional design and morphology and neural controllers are concurrently evolved as functional wholes. The agents are ‘grounded’ in an increasingly complex environment by a complex model metabolism and interaction dynamics. Furthermore, we introduce a novel criterion for evaluating differential reproductive success aimed at maximising evolutionary freedom. We also present first experimental results suggesting that this approach may be conducive to widening the scope of artificial evolution for the generation of agents exhibiting non-trivial behaviours in a complex ecosystem

Developing preferential attention to a speaker: a robot learning to recognise its carer

In this paper we present a socially interactive multi-modal robotic head, ERWIN - Emotional Robot With Intelligent Networks, capable of emotion expression and interaction via speech and vision. The model presented shows how a robot can learn to attend to the voice of a specific speaker, providing a relevant emotional expressive response based on previous interactions. We show three aspects of the system; first, the learning phase, allowing the robot to learn faces and voices from interaction. Second, recognition of the learnt faces and voices, and third, the emotion expression aspect of the system. We show this from the perspective of an adult and child interacting and playing a small game, much like an infant and caregiver situation. We also discuss the importance of speaker recognition in terms of human-robot-interaction and emotion, showing how the interaction process between a participant and ERWIN can allow the robot to prefer to attend to that person.</p