A Tale of Two Animats: What does it take to have goals?

What does it take for a system, biological or not, to have goals? Here, this question is approached in the context of in silico artificial evolution. By examining the informational and causal properties of artificial organisms ('animats') controlled by small, adaptive neural networks (Markov Brains), this essay discusses necessary requirements for intrinsic information, autonomy, and meaning. The focus lies on comparing two types of Markov Brains that evolved in the same simple environment: one with purely feedforward connections between its elements, the other with an integrated set of elements that causally constrain each other. While both types of brains 'process' information about their environment and are equally fit, only the integrated one forms a causally autonomous entity above a background of external influences. This suggests that to assess whether goals are meaningful for a system itself, it is important to understand what the system is, rather than what it does.Comment: This article is a contribution to the FQXi 2016-2017 essay contest "Wandering Towards a Goal

The effects of age-bias on neural correlates of successful and unsuccessful response inhibition

Response inhibition is important for adherence to social norms, especially when norms conflict with biases based on one’s social identity. While previous studies have shown that in-group bias generally modulates neural activity related to stimulus appraisal, it is unclear whether and how an in-group bias based on age affects neural information processing during response inhibition. To assess this potential influence, young adults completed a Go/NoGo task incorporating younger face (in-group) and older face (out-group) stimuli while undergoing functional magnetic resonance imaging (fMRI). Our results replicated previous findings by demonstrating higher accuracy in successful Go compared to NoGo trials, as well as the engagement of nodes of the response inhibition network during successful response inhibition, and brain regions comprising the salience network during unsuccessful response inhibition. Importantly, despite a lack of behavioural differences, our results showed that younger and older face stimuli modulated activity in the response inhibition and salience networks during successful and unsuccessful inhibition, respectively. Interestingly, these effects were not uniform across networks. During successful response inhibition, in-group stimuli increased activity in medial prefrontal cortex and temporo-parietal junction, whereas out-group stimuli more strongly engaged pre-supplemental motor area. During unsuccessful response inhibition, in-group stimuli increased activity in posterior insula, whereas out-group stimuli more strongly engaged angular gyrus and intraparietal sulcus. Consequently, the results infer the presence of an age-bias effect in the context of inhibitory control, which has substantial implications for future experimental design and may also provide the means of investigating the neural correlates of implicit beliefs that contribute to ageis

The evolution of representation in simple cognitive networks

Representations are internal models of the environment that can provide guidance to a behaving agent, even in the absence of sensory information. It is not clear how representations are developed and whether or not they are necessary or even essential for intelligent behavior. We argue here that the ability to represent relevant features of the environment is the expected consequence of an adaptive process, give a formal definition of representation based on information theory, and quantify it with a measure R. To measure how R changes over time, we evolve two types of networks---an artificial neural network and a network of hidden Markov gates---to solve a categorization task using a genetic algorithm. We find that the capacity to represent increases during evolutionary adaptation, and that agents form representations of their environment during their lifetime. This ability allows the agents to act on sensorial inputs in the context of their acquired representations and enables complex and context-dependent behavior. We examine which concepts (features of the environment) our networks are representing, how the representations are logically encoded in the networks, and how they form as an agent behaves to solve a task. We conclude that R should be able to quantify the representations within any cognitive system, and should be predictive of an agent's long-term adaptive success.Comment: 36 pages, 10 figures, one Tabl

The effects of age bias on neural correlates of successful and unsuccessful response inhibition in younger and older adults.

Facilitating communication between generations has become increasingly important. However, individuals often demonstrate a preference for their own age group, which can impact social interactions, and such bias in young adults even extends to inhibitory control. To assess whether older adults also experience this phenomenon, a group of younger and older adults completed a Go/NoGo task incorporating young and old faces, while undergoing functional magnetic resonance imaging. Within the networks subserving successful and unsuccessful response inhibition, patterns of activity demonstrated distinct neural age bias effects in each age group. During successful inhibition, the older adult group demonstrated significantly increased activity to other-age faces, whereas unsuccessful inhibition in the younger group produced significantly enhanced activity to other-age faces. Consequently, the findings of the study confirm that neural responses to successful and unsuccessful inhibition can be contingent on the stimulus-specific attribute of age in both younger and older adults. These findings have important implications in regard to minimizing the emergence of negative consequences, such as ageism, as a result of related implicit biases

Activating Natural Killer Cell Receptors, Selectins, and Inhibitory Siglecs Recognize Ebolavirus Glycoprotein

Expression of the extensively glycosylated Ebolavirus glycoprotein (EBOV-GP) induces physical alterations of surface molecules and plays a crucial role in viral pathogenicity. Here we investigate the interactions of EBOV-GP with host surface molecules using purified EBOV-GP, EBOV-GP-transfected cell lines, and EBOV-GP-pseudotyped lentiviral particles. Subsequently, we wanted to examine which receptors are involved in this recognition by binding studies to cells transfected with the EBOV-GP as well as to recombinant soluble EBOV-GP. As the viral components can also bind to inhibitory receptors of immune cells (e.g., Siglecs, TIM-1), they can even suppress the activity of immune effector cells. Our data show that natural killer (NK) cell receptors NKp44 and NKp46, selectins (CD62E/P/L), the host factors DC-SIGNR/DC-SIGN, and inhibitory Siglecs function as receptors for EBOV-GP. Our results show also moderate to strong avidity of homing receptors (P-, L-, and E-selectin) and DC-SIGNR/DC-SIGN to purified EBOV-GP, to cells transfected with EBOV-GP, as well as to the envelope of a pseudotyped lentiviral vector carrying the EBOV-GP. The concomitant activation and inhibition of the immune system exemplifies the evolutionary antagonism between the immune system and pathogens. Altogether these interactions with activating and inhibitory receptors result in a reduced NK cell-mediated lysis of EBOV-GP-expressing cells. Modulation of these interactions may provide new strategies for treating infections caused by this virus.publishedVersio

The whole and its parts : why and how to disentangle plant communities and synusiae in vegetation classification

Most plant communities consist of different structural and ecological subsets, ranging from cryptogams to different tree layers. The completeness and approach with which these subsets are sampled have implications for vegetation classification. Non‐vascular plants are often omitted or sometimes treated separately, referring to their assemblages as “synusiae” (e.g. epiphytes on bark, saxicolous species on rocks). The distinction of complete plant communities (phytocoenoses or holocoenoses) from their parts (synusiae or merocoenoses) is crucial to avoid logical problems and inconsistencies of the resulting classification systems. We here describe theoretical differences between the phytocoenosis as a whole and its parts, and outline consequences of this distinction for practise and terminology in vegetation classification. To implement a clearer separation, we call for modifications of the International Code of Phytosociological Nomenclature and the EuroVegChecklist. We believe that these steps will make vegetation classification systems better applicable and raise the recognition of the importance of non‐vascular plants in the vegetation as well as their interplay with vascular plants

Requirements for a system to analyze HEP events using database computing

We describe the requirements for the design and prototyping of an object-oriented database designed to analyze data in high energy physics. Our goal is to satisfy the data processing and analysis needs of a generic high energy physics experiment to be proposed for the Superconducting SuperCollider (SSC), and requires the collection and analysis of between 10 and 100 million sets of vectors (events), each approximately one megabyte in length. We sketch how this analysis would proceed using an object-oriented database which support the basic data types used in HEP

The association between stress and mood across the adult lifespan on default mode network

Aging of brain structure and function is a complex process characterized by high inter- and intra-individual variability. Such variability may arise from the interaction of multiple factors, including exposure to stressful experience and mood variation, across the lifespan. Using a multimodal neuroimaging and neurocognitive approach, we investigated the association of stress, mood and their interaction, in the structure and function of the default mode network (DMN), both during rest and task-induced deactivation, throughout the adult lifespan. Data confirmed a decreased functional connectivity (FC) and task-induced deactivation of the DMN during the aging process and in subjects with lower mood; on the contrary, an increased FC was observed in subjects with higher perceived stress. Surprisingly, the association of aging with DMN was altered by stress and mood in specific regions. An increased difficulty to deactivate the DMN was noted in older participants with lower mood, contrasting with an increased deactivation in individuals presenting high stress, independently of their mood levels, with aging. Interestingly, this constant interaction across aging was globally most significant in the combination of high stress levels with a more depressed mood state, both during resting state and task-induced deactivations. The present results contribute to characterize the spectrum of FC and deactivation patterns of the DMN, highlighting the crucial association of stress and mood levels, during the adult aging process. These combinatorial approaches may help to understand the heterogeneity of the aging process in brain structure and function and several states that may lead to neuropsychiatric disorders.The work was supported by SwitchBox-FP7-HEALTH-2010-Grant 259772-2 and by ON.2, O NOVO NORTE, North Portugal Regional Operational Programme 2007/2013, of the National strategic Reference Framework (NSRF) 2007/2013, through the European Regional Development Fund (ERDF)info:eu-repo/semantics/publishedVersio

High gamma oscillations in medial temporal lobe during overt production of speech and gestures

The study of the production of co-speech gestures (CSGs), i.e., meaningful hand movements that often accompany speech during everyday discourse, provides an important opportunity to investigate the integration of language, action, and memory because of the semantic overlap between gesture movements and speech content. Behavioral studies of CSGs and speech suggest that they have a common base in memory and predict that overt production of both speech and CSGs would be preceded by neural activity related to memory processes. However, to date the neural correlates and timing of CSG production are still largely unknown. In the current study, we addressed these questions with magnetoencephalography and a semantic association paradigm in which participants overtly produced speech or gesture responses that were either meaningfully related to a stimulus or not. Using spectral and beamforming analyses to investigate the neural activity preceding the responses, we found a desynchronization in the beta band (15-25 Hz), which originated 900 ms prior to the onset of speech and was localized to motor and somatosensory regions in the cortex and cerebellum, as well as right inferior frontal gyrus. Beta desynchronization is often seen as an indicator of motor processing and thus reflects motor activity related to the hand movements that gestures add to speech. Furthermore, our results show oscillations in the high gamma band (50-90 Hz), which originated 400 ms prior to speech onset and were localized to the left medial temporal lobe. High gamma oscillations have previously been found to be involved in memory processes and we thus interpret them to be related to contextual association of semantic information in memory. The results of our study show that high gamma oscillations in medial temporal cortex play an important role in the binding of information in human memory during speech and CSG production