OBJECTIVE: Deep brain stimulation of the thalamus was introduced more than 40 years ago with the objective of improving the performance and attention of patients in a vegetative or minimally conscious state. Here, the authors report the results of the Cortical Activation by Thalamic Stimulation (CATS) study, a prospective multiinstitutional study on the effects of bilateral chronic stimulation of the anterior intralaminar thalamic nuclei and adjacent paralaminar regions in patients affected by a disorder of consciousness. METHODS: The authors evaluated the clinical and radiological data of 29 patients in a vegetative state (unresponsive wakefulness syndrome) and 11 in a minimally conscious state that lasted for more than 6 months. Of these patients, 5 were selected for bilateral stereotactic implantation of deep brain stimulating electrodes into their thalamus. A definitive consensus for surgery was obtained for 3 of the selected patients. All 3 patients (2 in a vegetative state and 1 in a minimally conscious state) underwent implantation of bilateral thalamic electrodes and submitted to chronic stimulation for a minimum of 18 months and a maximum of 48 months. RESULTS: In each case, there was an increase in desynchronization and the power spectrum of electroencephalograms, and improvement in the Coma Recovery Scale–Revised scores was found. Furthermore, the severity of limb spasticity and the number and severity of pathological movements were reduced. However, none of these patients returned to a fully conscious state. CONCLUSIONS: Despite the limited number of patients studied, the authors confirmed that bilateral thalamic stimulation can improve the clinical status of patients affected by a disorder of consciousness, even though this stimulation did not induce persistent, clinically evident conscious behavior in the patients. Clinical trial registration no.: NCT01027572 (ClinicalTrials.gov)

The stomach is inhabited by diverse microbial communities, co-existing in a dynamic balance. Long-term use of drugs such as proton pump inhibitors (PPIs), or bacterial infection such as Helicobacter pylori, cause significant microbial alterations. Yet, studies revealing how the commensal bacteria re-organize, due to these perturbations of the gastric environment, are in early phase and rely principally on linear techniques for multivariate analysis. Here we disclose the importance of complementing linear dimensionality reduction techniques with nonlinear ones to unveil hidden patterns that remain unseen by linear embedding. Then, we prove the advantages to complete multivariate pattern analysis with differential network analysis, to reveal mechanisms of bacterial network re-organizations which emerge from perturbations induced by a medical treatment (PPIs) or an infectious state (H. pylori). Finally, we show how to build bacteria-metabolite multilayer networks that can deepen our understanding of the metabolite pathways significantly associated to the perturbed microbial communities.

Instinctive defensive behaviors, consisting of stereotyped sequences of movements and postures, are an essential component of the mouse behavioral repertoire. Since defensive behaviors can be reliably triggered by threatening sensory stimuli, the selection of the most appropriate action depends on the stimulus property. However, since the mouse has a wide repertoire of motor actions, it is not clear which set of movements and postures represent the relevant action. So far, this has been empirically identified as a change in locomotion state. However, the extent to which locomotion alone captures the diversity of defensive behaviors and their sensory specificity is unknown. To tackle this problem, we developed a method to obtain a faithful 3D reconstruction of the mouse body that enabled to quantify a wide variety of motor actions. This higher dimensional description revealed that defensive behaviors are more stimulus specific than indicated by locomotion data. Thus, responses to distinct stimuli that were equivalent in terms of locomotion (e.g., freezing induced by looming and sound) could be discriminated along other dimensions. The enhanced stimulus specificity was explained by a surprising diversity. A clustering analysis revealed that distinct combinations of movements and postures, giving rise to at least 7 different behaviors, were required to account for stimulus specificity. Moreover, each stimulus evoked more than one behavior, revealing a robust one-to-many mapping between sensations and behaviors that was not apparent from locomotion data. Our results indicate that diversity and sensory specificity of mouse defensive behaviors unfold in a higher dimensional space, spanning multiple motor actions.

Brain functional networks show high variability in short time windows but mechanisms governing these transient dynamics remain unknown. In this work, we studied the temporal evolution of functional brain networks involved in a working memory (WM) task while recording high-density electroencephalography (EEG) in human normal subjects. We found that functional brain networks showed an initial phase characterized by an increase of the functional segregation index followed by a second phase where the functional segregation faded after the prevailing the functional integration. Notably, wrong trials were associated with different or disrupted sequences of the segregation-integration profiles and measures of network centrality and modularity were able to identify crucial aspects of the oscillatory network dynamics. Additionally, computational investigations further supported the experimental results. The brain functional organization may respond to the information processing demand of a WM task following a 2-step atomic scheme wherein segregation and integration alternately dominate the functional configurations.

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role.

The microwave emitting Radio Electric Asymmetric Conveyor (REAC) is a technology able to interact with biological tissues at low emission intensity (2 mW at the emitter and 2.4 or 5.8 GHz) by inducing radiofrequency generated microcurrents. It shows remarkable biological effects at many scales from gene modulations up to functional global remodeling even in human subjects. Previous REAC experiments by functional Magnetic Resonance Imaging (fMRI) on healthy human subjects have shown deep modulations of cortical BOLD signals. In this paper we studied the effects of REAC application on spontaneous and evoked neuronal activities simultaneously recorded by microelectrode matrices from the somatosensory thalamo-cortical axis in control and chronic pain experimental animal models. We analyzed the spontaneous spiking activity and the Local Field Potentials (LFPs) before and after REAC applied with a different protocol. The single neuron spiking activities, the neuronal responses to peripheral light mechanical stimuli, the population discharge synchronies as well as the correlations and the network dynamic connectivity characteristics have been analyzed. Modulations of the neuronal frequency associated with changes of functional correlations and significant LFP temporal realignments have been diffusely observed. Analyses by topological methods have shown changes in functional connectivity with significant modifications of the network features.