Canonical Source Reconstruction for MEG

We describe a simple and efficient solution to the problem of reconstructing electromagnetic sources into a canonical or standard anatomical space. Its simplicity rests upon incorporating subject-specific anatomy into the forward model in a way that eschews the need for cortical surface extraction. The forward model starts with a canonical cortical mesh, defined in a standard stereotactic space. The mesh is warped, in a nonlinear fashion, to match the subject's anatomy. This warping is the inverse of the transformation derived from spatial normalization of the subject's structural MRI image, using fully automated procedures that have been established for other imaging modalities. Electromagnetic lead fields are computed using the warped mesh, in conjunction with a spherical head model (which does not rely on individual anatomy). The ensuing forward model is inverted using an empirical Bayesian scheme that we have described previously in several publications. Critically, because anatomical information enters the forward model, there is no need to spatially normalize the reconstructed source activity. In other words, each source, comprising the mesh, has a predetermined and unique anatomical attribution within standard stereotactic space. This enables the pooling of data from multiple subjects and the reporting of results in stereotactic coordinates. Furthermore, it allows the graceful fusion of fMRI and MEG data within the same anatomical framework

Towards a computational phenomenology of mental action: modelling meta-awareness and attentional control with deep parametric active inference

Meta-awareness refers to the capacity to explicitly notice the current content of consciousness and has been identified as a key component for the successful control of cognitive states, such as the deliberate direction of attention. This paper proposes a formal model of meta-awareness and attentional control using hierarchical active inference. To do so, we cast mental action as policy selection over higher-level cognitive states and add a further hierarchical level to model meta-awareness states that modulate the expected confidence (precision) in the mapping between observations and hidden cognitive states. We simulate the example of mind-wandering and its regulation during a task involving sustained selective attention on a perceptual object. This provides a computational case study for an inferential architecture that is apt to enable the emergence of these central components of human phenomenology, namely, the ability to access and control cognitive states. We propose that this approach can be generalized to other cognitive states, and hence, this paper provides the first steps towards the development of a computational phenomenology of mental action and more broadly of our ability to monitor and control our own cognitive states. Future steps of this work will focus on fitting the model with qualitative, behavioural, and neural data

Hearing faces: how the infant brain matches the face it sees with the speech it hears

Speech is not a purely auditory signal. From around 2 months of age, infants are able to correctly match the vowel they hear with the appropriate articulating face. However, there is no behavioral evidence of integrated audiovisual perception until 4 months of age, at the earliest, when an illusory percept can be created by the fusion of the auditory stimulus and of the facial cues (McGurk effect). To understand how infants initially match the articulatory movements they see with the sounds they hear, we recorded high-density ERPs in response to auditory vowels that followed a congruent or incongruent silently articulating face in 10-week-old infants. In a first experiment, we determined that auditory–visual integration occurs during the early stages of perception as in adults. The mismatch response was similar in timing and in topography whether the preceding vowels were presented visually or aurally. In the second experiment, we studied audiovisual integration in the linguistic (vowel perception) and nonlinguistic (gender perception) domain. We observed a mismatch response for both types of change at similar latencies. Their topographies were significantly different demonstrating that cross-modal integration of these features is computed in parallel by two different networks. Indeed, brain source modeling revealed that phoneme and gender computations were lateralized toward the left and toward the right hemisphere, respectively, suggesting that each hemisphere possesses an early processing bias. We also observed repetition suppression in temporal regions and repetition enhancement in frontal regions. These results underscore how complex and structured is the human cortical organization which sustains communication from the first weeks of life on

Canonical source reconstruction for MEG.

We describe a simple and efficient solution to the problem of reconstructing electromagnetic sources into a canonical or standard anatomical space. Its simplicity rests upon incorporating subject-specific anatomy into the forward model in a way that eschews the need for cortical surface extraction. The forward model starts with a canonical cortical mesh, defined in a standard stereotactic space. The mesh is warped, in a nonlinear fashion, to match the subject's anatomy. This warping is the inverse of the transformation derived from spatial normalization of the subject's structural MRI image, using fully automated procedures that have been established for other imaging modalities. Electromagnetic lead fields are computed using the warped mesh, in conjunction with a spherical head model (which does not rely on individual anatomy). The ensuing forward model is inverted using an empirical Bayesian scheme that we have described previously in several publications. Critically, because anatomical information enters the forward model, there is no need to spatially normalize the reconstructed source activity. In other words, each source, comprising the mesh, has a predetermined and unique anatomical attribution within standard stereotactic space. This enables the pooling of data from multiple subjects and the reporting of results in stereotactic coordinates. Furthermore, it allows the graceful fusion of fMRI and MEG data within the same anatomical framework.Peer Reviewe

The Insulin-Mediated Modulation of Visually Evoked Magnetic Fields Is Reduced in Obese Subjects

BACKGROUND: Insulin is an anorexigenic hormone that contributes to the termination of food intake in the postprandial state. An alteration in insulin action in the brain, named "cerebral insulin resistance", is responsible for overeating and the development of obesity. METHODOLOGY/PRINCIPAL FINDINGS: To analyze the direct effect of insulin on food-related neuronal activity we tested 10 lean and 10 obese subjects. We conducted a magnetencephalography study during a visual working memory task in both the basal state and after applying insulin or placebo spray intranasally to bypass the blood brain barrier. Food and non-food pictures were presented and subjects had to determine whether or not two consecutive pictures belonged to the same category. Intranasal insulin displayed no effect on blood glucose, insulin or C-peptide concentrations in the periphery; however, it led to an increase in the components of evoked fields related to identification and categorization of pictures (at around 170 ms post stimuli in the visual ventral stream) in lean subjects when food pictures were presented. In contrast, insulin did not modulate food-related brain activity in obese subjects. CONCLUSIONS/SIGNIFICANCE: We demonstrated that intranasal insulin increases the cerebral processing of food pictures in lean whereas this was absent in obese subjects. This study further substantiates the presence of a "cerebral insulin resistance" in obese subjects and might be relevant in the pathogenesis of obesity

Heterochromatin Protein 1β (HP1β) has distinct functions and distinct nuclear distribution in pluripotent versus differentiated cells

Background: Pluripotent embryonic stem cells (ESCs) have the unique ability to differentiate into every cell type and to self-renew. These characteristics correlate with a distinct nuclear architecture, epigenetic signatures enriched for active chromatin marks and hyperdynamic binding of structural chromatin proteins. Recently, several chromatin-related proteins have been shown to regulate ESC pluripotency and/or differentiation, yet the role of the major heterochromatin proteins in pluripotency is unknown. Results: Here we identify Heterochromatin Protein 1β (HP1β) as an essential protein for proper differentiation, and, unexpectedly, for the maintenance of pluripotency in ESCs. In pluripotent and differentiated cells HP1β is differentially localized and differentially associated with chromatin. Deletion of HP1β, but not HP1aα, in ESCs provokes a loss of the morphological and proliferative characteristics of embryonic pluripotent cells, reduces expression of pluripotency factors and causes aberrant differentiation. However, in differentiated cells, loss of HP1β has the opposite effect, perturbing maintenance of the differentiation state and facilitating reprogramming to an induced pluripotent state. Microscopy, biochemical fractionation and chromatin immunoprecipitation reveal a diffuse nucleoplasmic distribution, weak association with chromatin and high expression levels for HP1β in ESCs. The minor fraction of HP1β that is chromatin-bound in ESCs is enriched within exons, unlike the situation in differentiated cells, where it binds heterochromatic satellite repeats and chromocenters. Conclusions: We demonstrate an unexpected duality in the role of HP1β: it is essential in ESCs for maintaining pluripotency, while it is required for proper differentiation in differentiated cells. Thus, HP1β function both depends on, and regulates, the pluripotent state

Beyond in-phase and anti-phase coordination in a model of joint action

In 1985, Haken, Kelso and Bunz proposed a system of coupled nonlinear oscillators as a model of rhythmic movement patterns in human bimanual coordination. Since then, the Haken–Kelso–Bunz (HKB) model has become a modelling paradigm applied extensively in all areas of movement science, including interpersonal motor coordination. However, all previous studies have followed a line of analysis based on slowly varying amplitudes and rotating wave approximations. These approximations lead to a reduced system, consisting of a single differential equation representing the evolution of the relative phase of the two coupled oscillators: the HKB model of the relative phase. Here we take a different approach and systematically investigate the behaviour of the HKB model in the full four-dimensional state space and for general coupling strengths. We perform detailed numerical bifurcation analyses and reveal that the HKB model supports previously unreported dynamical regimes as well as bistability between a variety of coordination patterns. Furthermore, we identify the stability boundaries of distinct coordination regimes in the model and discuss the applicability of our findings to interpersonal coordination and other joint action tasks