Intersubject variability and induced gamma in the visual cortex: DCM with empirical Bayes and neural fields

This article describes the first application of a generic (empirical) Bayesian analysis of between‐subject effects in the dynamic causal modeling (DCM) of electrophysiological (MEG) data. It shows that (i) non‐invasive (MEG) data can be used to characterize subject‐specific differences in cortical microcircuitry and (ii) presents a validation of DCM with neural fields that exploits intersubject variability in gamma oscillations. We find that intersubject variability in visually induced gamma responses reflects changes in the excitation‐inhibition balance in a canonical cortical circuit. Crucially, this variability can be explained by subject‐specific differences in intrinsic connections to and from inhibitory interneurons that form a pyramidal‐interneuron gamma network. Our approach uses Bayesian model reduction to evaluate the evidence for (large sets of) nested models—and optimize the corresponding connectivity estimates at the within and between‐subject level. We also consider Bayesian cross‐validation to obtain predictive estimates for gamma‐response phenotypes, using a leave‐one‐out procedure

Advancing Extraterrestrial Exploration Through Automated Ground Vehicles

The project focuses on the development and fabrication of two multi-terrain rovers with autonomous tracking, navigation, and recovery capabilities. Driven by mission requirements for autonomous terrain maneuverability and flexible payload hosting, this team proposes a design that addresses the diverse needs of extraterrestrial exploration. The project features: a rocker-bogie chassis, with six-wheel drive capabilities, that will be providing the necessary stability and mobility across challenging terrains. A mounting place with universal spacing allows for the attachment of multiple payload types, ensuring adaptability for various scientific missions. The integration of micro controllers facilitates communication between the rovers and operators. Two distinct rovers are proposed for this initiative, each equipped with autonomous tracking and navigation systems. The primary rover assumes the role of a leader, taking charge of tracking and independent navigation, while the secondary rover, known as the ”mule”, follows the primary directly. Beyond their immediate objectives, the project envisions future applications for these autonomous rovers, thus a modular design shall be implemented for applications including tracking and communication, the integration of soil sampling analysis devices, and additional scientific payloads

Following the genes: a framework for animal modeling of psychiatric disorders

The number of individual cases of psychiatric disorders that can be ascribed to identified, rare, single mutations is increasing with great rapidity. Such mutations can be recapitulated in mice to generate animal models with direct etiological validity. Defining the underlying pathogenic mechanisms will require an experimental and theoretical framework to make the links from mutation to altered behavior in an animal or psychopathology in a human. Here, we discuss key elements of such a framework, including cell type-based phenotyping, developmental trajectories, linking circuit properties at micro and macro scales and definition of neurobiological phenotypes that are directly translatable to humans

Schizophrenia and reelin: a model based on prenatal stress to study epigenetics, brain development and behavior

Schizophrenia is a severe psychiatric disorder that results in a significant disability for the patient. The disorder is characterized by impairment of the adaptive orchestration of actions, a cognitive function that is mainly dependent on the prefrontal cortex. This behavioral deficit, together with cellular and neurophysiological alterations in the prefrontal cortex, as well as reduced density of GABAergic cells and aberrant oscillatory activity, all indicate structural and functional deficits of the prefrontal cortex in schizophrenia. Among the several risk factors for the development of schizophrenia, stress during the prenatal period has been identified as crucial. Thus, it is proposed that prenatal stress induces neurodevelopmental alterations in the prefrontal cortex that are expressed as cognitive impairment observed in schizophrenia. However, the precise mechanisms that link prenatal stress with the impairment of prefrontal cortex function is largely unknown. Reelin is an extracellular matrix protein involved in the development of cortical neural connectivity at embryonic stages, and in synaptic plasticity at postnatal stages. Interestingly, down-regulation of reelin expression has been associated with epigenetic changes in the reelin gene of the prefrontal cortex of schizophrenic patients. We recently showed that, similar to schizophrenic patients, prenatal stress induces down-expression of reelin associated with the methylation of its promoter in the rodent prefrontal cortex. These alterations were paralleled with altered prefrontal cortex functional connectivity and impairment in prefrontal cortex-dependent behavioral tasks. Therefore, considering molecular, cellular, physiological and behavioral evidence, we propose a unifying framework that links prenatal stress and prefrontal malfunction through epigenetic alterations of the reelin gene