Enactive and simondonian reflections on mental disorders

As an alternative to linear and unidimensional perspectives focused mainly on either organic or psychological processes, the enactive approach to life and mind-a branch of 4-E (embodied, embedded, enactive, extended) cognitive theories-offers an integrative framework to study mental disorders that encompasses and articulates organic, sensorimotor, and intersubjective dimensions of embodiment. These three domains are deeply entangled in a non-trivial manner. A question remains on how this systemic and multi-dimensional approach may be applied to our understanding of mental disorders and symptomatic behavior. Drawing on Gilbert Simondon's philosophy of individuation (focusing particularly on the concepts of tension, metastability, and preindividual), we provide some enactive conceptual tools to better understand the dynamic, interactive, and multi-dimensional nature of human bodies in mental disorders and psychopathological symptoms. One of such tools cursiva is sense-making, a key notion that captures the relational process of generating meaning by interacting with the sociomaterial environment. The article analyzes five aspects related to sense-making: temporality, adaptivity, the multiplicity of normativities it involves, the fundamental role of tension, and its participatory character. On this basis, we draw certain implications for our understanding of mental disorders and diverse symptoms, and suggest their interpretation in terms of difficulties to transform tensions and perform individuation processes, which result in a reduction of the field of potentialities for self-individuation and sense-making.This work was supported by the Basque Government under grant IT 1668-22 to the IAS-Research group and the research project "Outonomy" PID2019-104576GB-I00 by the Spanish Ministry of Science and Innovation. IA was supported by a Juan de la Cierva-Formacion Research Fellowship by the Spanish Ministry of Economy and Competitiveness. EG was supported by the Specialization of Postdoctoral Researchers Fellowship of the University of the Basque Country

Scaling of sensory information in largeneural populations shows signatures ofinformation-limiting correlations

How is information distributed across large neuronal populations within a given brain area? Information may be distributed roughly evenly across neuronal populations, so that total information scales linearly with the number of recorded neurons. Alternatively, the neural code might be highly redundant, meaning that total information saturates. Here we investigate how sensory information about the direction of a moving visual stimulus is distributed across hundreds of simultaneously recorded neurons in mouse primary visual cortex. We show that information scales sublinearly due to correlated noise in these populations. We compartmentalized noise correlations into information-limiting and nonlimiting components, then extrapolate to predict how information grows with even larger neural populations. We predict that tens of thousands of neurons encode 95% of the information about visual stimulus direction, much less than the number of neurons in primary visual cortex. These findings suggest that the brain uses a widely distributed, but nonetheless redundant code that supports recovering most sensory information from smaller subpopulations.We would like to thank Alexandre Pouget, Peter Latham, and members of the HMSNeurobiology Department for useful discussions and feedback on the work, and RachelWilson and Richard Born for comments on early versions of the manuscript. The workwas supported by a scholar award from the James S. McDonnell Foundation (grant#220020462 to J.D.), grants from the NIH (R01MH115554 to J.D.; R01MH107620 to C.D.H.; R01NS089521 to C.D.H.; R01NS108410 to C.D.H.; F31EY031562 to A.W.J.), theNSF’s NeuroNex program (DBI-1707398. to R.N.), MINECO (Spain; BFU2017-85936-Pto R.M.-B.), the Howard Hughes Medical Institute (HHMI, ref 55008742 to R.M.-B.), theICREA Academia (2016 to R.M.-B.), the Government of Aragon (Spain; ISAAC lab, codT33 17D to I.A.-R.), the Spanish Ministry of Economy and Competitiveness (TIN2016-80347-R to I.A.-R.), the Gatsby Charitable Foundation (to R.N.), and an NSF GraduateResearch Fellowship (to A.W.J.)

New applications of advanced instrumental techniques for the characterization of food allergenic proteins

Current approaches based on electrophoretic, chromatographic or immunochemical principles have allowed characterizing multiple allergens, mapping their epitopes, studying their mechanisms of action, developing detection and diagnostic methods and therapeutic strategies for the food and pharmaceutical industry. However, some of the common structural features related to the allergenic potential of food proteins remain unknown, or the pathological mechanism of food allergy is not yet fully understood. In addition, it is also necessary to evaluate new allergens from novel protein sources that may pose a new risk for consumers. Technological development has allowed the expansion of advanced technologies for which their whole potential has not been entirely exploited and could provide novel contributions to still unexplored molecular traits underlying both the structure of food allergens and the mechanisms through which they sensitize or elicit adverse responses in human subjects, as well as improving analytical techniques for their detection. This review presents cutting-edge instrumental techniques recently applied when studying structural and functional aspects of proteins, mechanism of action and interaction between biomolecules. We also exemplify their role in the food allergy research and discuss their new possible applications in several areas of the food allergy field

Cortical Variability and Challenges for Modeling Approaches.

The functional role of the observed neuronal variability (the disparity in neural responses across multiple instances of the same experiment) is again receiving close attention in Computational and Systems Neuroscience (e.g., Durstewitz et al., 2010; Moreno-Bote et al., 2011; Oram, 2011; Beck et al., 2012; Churchland and Abbott, 2012; Brunton et al., 2013; Masquelier, 2013; Mattia et al., 2013; Balaguer-Ballester et al., 2014; Renart and Machens, 2014; Bujan et al., 2015; Lin et al., 2015; Pachitariu et al., 2015; Arandia-Romero et al., 2016; Doiron et al., 2016; McDonnell et al., 2016). Special consideration is currently given to understanding how spiking (Bujan et al., 2015; Deneve and Machens, 2016; Doiron et al., 2016; Hartmann et al., 2016; Landau et al., 2016) and phenomenological (Goris et al., 2014; Lin et al., 2015; Mochol et al., 2015; Arandia-Romero et al., 2016; Doiron et al., 2016) models account for the wide range of classical and new phenomena associated with trial-to-trial uncorrelated activity. Specifically, it has often been proposed that a network state characterized by largely asynchronous spike times whilst maintaining slow oscillations in the firing-rates, may represent the default spontaneous cortical mode (e.g., Sanchez-Vives and Mattia, 2014; Deneve and Machens, 2016; Sancristobal et al., 2016); and similar states could also underlie observed stimulus-driven variability in rate (Litwin Kumar and Doiron, 2012; Deneve and Machens, 2016; Hartmann et al., 2016). However, the way in which such a computationally advantageous network state for neural coding is achieved can differ substantially between modeling approaches; this challenge will be the focus of this manuscript

Lateral orbitofrontal cortex anticipates choices and integrates prior with current information

Adaptive behavior requires integrating prior with current information to anticipate upcoming events. Brain structures related to this computation should bring relevant signals from the recent past into the present. Here we report that rats can integrate the most recent prior information with sensory information, thereby improving behavior on a perceptual decision-making task with outcome-dependent past trial history. We find that anticipatory signals in the orbitofrontal cortex about upcoming choice increase over time and are even present before stimulus onset. These neuronal signals also represent the stimulus and relevant second-order combinations of past state variables. The encoding of choice, stimulus and second-order past state variables resides, up to movement onset, in overlapping populations. The neuronal representation of choice before stimulus onset and its build-up once the stimulus is presented suggest that orbitofrontal cortex plays a role in transforming immediate prior and stimulus information into choices using a compact state-space representation

Impact of the first wave of the SARS-CoV-2 pandemic on the outcome of neurosurgical patients: A nationwide study in Spain

Objective To assess the effect of the first wave of the SARS-CoV-2 pandemic on the outcome of neurosurgical patients in Spain. Settings The initial flood of COVID-19 patients overwhelmed an unprepared healthcare system. Different measures were taken to deal with this overburden. The effect of these measures on neurosurgical patients, as well as the effect of COVID-19 itself, has not been thoroughly studied. Participants This was a multicentre, nationwide, observational retrospective study of patients who underwent any neurosurgical operation from March to July 2020. Interventions An exploratory factorial analysis was performed to select the most relevant variables of the sample. Primary and secondary outcome measures Univariate and multivariate analyses were performed to identify independent predictors of mortality and postoperative SARS-CoV-2 infection. Results Sixteen hospitals registered 1677 operated patients. The overall mortality was 6.4%, and 2.9% (44 patients) suffered a perioperative SARS-CoV-2 infection. Of those infections, 24 were diagnosed postoperatively. Age (OR 1.05), perioperative SARS-CoV-2 infection (OR 4.7), community COVID-19 incidence (cases/10 5 people/week) (OR 1.006), postoperative neurological worsening (OR 5.9), postoperative need for airway support (OR 5.38), ASA grade =3 (OR 2.5) and preoperative GCS 3-8 (OR 2.82) were independently associated with mortality. For SARS-CoV-2 postoperative infection, screening swab test <72 hours preoperatively (OR 0.76), community COVID-19 incidence (cases/10 5 people/week) (OR 1.011), preoperative cognitive impairment (OR 2.784), postoperative sepsis (OR 3.807) and an absence of postoperative complications (OR 0.188) were independently associated. Conclusions Perioperative SARS-CoV-2 infection in neurosurgical patients was associated with an increase in mortality by almost fivefold. Community COVID-19 incidence (cases/10 5 people/week) was a statistically independent predictor of mortality. Trial registration number CEIM 20/217

Models of Neuronal Stimulus-Response Functions: Elaboration, Estimation, and Evaluation

Rich, dynamic, and dense sensory stimuli are encoded within the nervous system by the time-varying activity of many individual neurons. A fundamental approach to understanding the nature of the encoded representation is to characterize the function that relates the moment-by-moment firing of a neuron to the recent history of a complex sensory input. This review provides a unifying and critical survey of the techniques that have been brought to bear on this effort thus far—ranging from the classical linear receptive field model to modern approaches incorporating normalization and other nonlinearities. We address separately the structure of the models; the criteria and algorithms used to identify the model parameters; and the role of regularizing terms or “priors.” In each case we consider benefits or drawbacks of various proposals, providing examples for when these methods work and when they may fail. Emphasis is placed on key concepts rather than mathematical details, so as to make the discussion accessible to readers from outside the field. Finally, we review ways in which the agreement between an assumed model and the neuron's response may be quantified. Re-implemented and unified code for many of the methods are made freely available

Reading out neural populations: shared variability, global fluctuations and information processing

Entendre l'origen i la funció de l'activitat de poblacions neuronals, i com aquesta activitat es relaciona amb els estímuls sensorials, les decisions o les accions motores és un gran repte per les neurociències. En aquest treball hem analitzat l'activitat de desenes de neurones enregistrades a l'escorça visual primària de micos mentre se'ls presentaven escletxes sinusoïdals en diferents orientacions. Hem trobat que les fluctuacions globals de la xarxa mesurades mitjançant l'activitat de la població modulen la selectivitat de les neurones de forma multiplicativa i additiva. A més, l'activitat de la població també afecta la informació present en grups petits de neurones, depenent de la modulació que ha provocat a la selectivitat d'aquestes. La informació de la població sencera, però, no canvia amb aquestes fluctuacions. A la segona part hem desenvolupat un mètode per mesurar 'correlacions diferencials' amb dades limitades. En aplicar-ho a les dades experimentals hem aconseguit la primera estimació preliminar de la grandària d'aquestes correlacions que limiten la informació. Els nostres resultats contribueixen a l'avenç en la comprensió de la codi ficació d'informació en poblacions neuronals, i alhora generen noves preguntes sobre com aquestes processen i transmeten informació.Entender el origen y la función de la actividad de poblaciones neuronales, y cómo esta actividad se relaciona con los estímulos sensoriales, las decisiones o las acciones motoras es un gran desafio en neurociencia. En este trabajo hemos analizado la actividad de decenas de neuronas registradas en la corteza visual primaria de monos mientras rejillas sinusoidales en diferentes orientaciones eran presentadas. Hemos encontrado que las fluctuaciones globales de la red medidas mediante la actividad de la población modulan la selectividad de las neuronas de manera multiplicativa y aditiva. Además, la actividad de la población también afecta a la información presente en grupos pequeños de neuronas, dependiendo de la modulación que ha provocado en la selectividad de estas neuronas. La información en la población completa, sin embargo, no varía con estas fluctuaciones. En la segunda parte hemos desarrollado un método para medir 'correlaciones diferenciales' con datos limitados. Al aplicarlo a los datos experimentales hemos obtenido la primera estimación preliminar del tamaño de estas correlaciones que limitan la información. Nuestros resultados contribuyen al avance del entendimiento sobre la codi ficación de la información en poblaciones neuronales, y al mismo tiempo generan más preguntas sobre cómo éstas procesan y transmiten información.Understanding the sources and the role of the spiking activity of neural populations, and how this activity is related to sensory stimuli, decisions or motor actions is a crucial challenge in neuroscience. In this work, we analyzed the spiking activity of tens of neurons recorded in the primary visual cortex of macaque monkeys while drifting sinusoidal gratings were presented in di erent orientations. We found that global uctuations of the network measured by the population activity a ect the tuning of individual neurons both multiplicatively and additively. Population activity also has an impact in the information of small ensembles, which depends on the kind of modulation that the tuning of those neurons undergoes. Interestingly, the total information of the network is not altered by these uctuations. In the second part, we developed a method to measure 'di erential correlations' from limited amount of data, and obtained the rst, although preliminary, estimate in experimental data. Our results have important implications for information coding, and they open new questions about the way information is processed and transmitted by the spiking activity of neural populations

Nuevas características del lenguaje OPScript para la creación de aplicaciones educativas

In this paper the authors make a brief introduction to the YADBrowser project which includes the educational browser YADBrowser and its language, OPScript. The authors show some features added to it recently. Using them the author of an educational application can achieve more functionality and adaptation with less code. Also, the YADBrowser reduces the interaction with the server, decreasing this way the application response time. In addition it can keep a record of the actions and preferences of the user during the session. These new features were added to facilitate the creation of dynamic applications, adaptable to student skills. They include “verbal” communication between objects, XML object models and reusable methods. Some features valuable in the development of educational applications with a mathematical component are also presented.Se presenta una breve introducción al proyecto YADBrowser, el cual incluye el navegador educativo YADBrowser y su lenguaje OPScript. Se exponen algunas características recientemente añadidas al lenguaje; con ellas el autor de una aplicación educativa puede lograr más funcionalidad y adaptabilidad con menos código. Además el navegador YADBrowser reduce la interacción con el servidor, disminuyendo de esta forma el tiempo de respuesta de la aplicación. También puede mantener un registro de las acciones y preferencias del usuario durante la sesión. Las nuevas características fueron añadidas para facilitar la creación de aplicaciones dinámicas, adaptables a las habilidades del estudiante. Estas incluyen comunicación “verbal” entre objetos, modelos de objetos basados en XML y métodos reutilizables. También se exponen algunas características que pueden ser de importancia en el desarrollo de aplicaciones educativas con un componente matemático