An ultra-compact integrated system for brain activity recording and stimulation validated over cortical slow oscillations in vivo and in vitro

Thalamic Foxp2 regulates output connectivity and sensory-motor impairments in a model of Huntington's Disease

BACKGROUND

Huntington's Disease (HD) is a disorder that affects body movements. Altered glutamatergic innervation of the striatum is a major hallmark of the disease. Approximately 30% of those glutamatergic inputs come from thalamic nuclei. Foxp2 is a transcription factor involved in cell differentiation and reported low in patients with HD. However, the role of the Foxp2 in the thalamus in HD remains unexplored.

METHODS

We used two different mouse models of HD, the R6/1 and the HdhQ111 mice, to demonstrate a consistent thalamic Foxp2 reduction in the context of HD. We used in vivo electrophysiological recordings, microdialysis in behaving mice and rabies virus-based monosynaptic tracing to study thalamo-striatal and thalamo-cortical synaptic connectivity in R6/1 mice. Micro-structural synaptic plasticity was also evaluated in the striatum and cortex of R6/1 mice. We over-expressed Foxp2 in the thalamus of R6/1 mice or reduced Foxp2 in the thalamus of wild type mice to evaluate its role in sensory and motor skills deficiencies, as well as thalamo-striatal and thalamo-cortical connectivity in such mouse models.

RESULTS

Here, we demonstrate in a HD mouse model a clear and early thalamo-striatal aberrant connectivity associated with a reduction of thalamic Foxp2 levels. Recovering thalamic Foxp2 levels in the mouse rescued motor coordination and sensory skills concomitant with an amelioration of neuropathological features and with a repair of the structural and functional connectivity through a restoration of neurotransmitter release. In addition, reduction of thalamic Foxp2 levels in wild type mice induced HD-like phenotypes.

CONCLUSIONS

In conclusion, we show that a novel identified thalamic Foxp2 dysregulation alters basal ganglia circuits implicated in the pathophysiology of HD.

Materials for Implantable Surface Electrode Arrays: Current Status and Future Directions

Surface electrode arrays are mainly fabricated from rigid or elastic materials, and precisely manipulated ductile metal films, which offer limited stretchability. However, the living tissues to which they are applied are nonlinear viscoelastic materials, which can undergo significant mechanical deformation in dynamic biological environments. Further, the same arrays and compositions are often repurposed for vastly different tissues rather than optimizing the materials and mechanical properties of the implant for the target application. By first characterizing the desired biological environment, and then designing a technology for a particular organ, surface electrode arrays may be more conformable, and offer better interfaces to tissues while causing less damage. Here, the various materials used in each component of a surface electrode array are first reviewed, and then electrically active implants in three specific biological systems, the nervous system, the muscular system, and skin, are described. Finally, the fabrication of next-generation surface arrays that overcome current limitations is discussed.

Theta and gamma oscillatory dynamics in mouse models of Alzheimer's disease: A path to prospective therapeutic intervention

Understanding the neural basis of cognitive deficits, a key feature of Alzheimer's disease (AD), is imperative for achieving the therapy of the disease. Rhythmic oscillatory activities in neural systems are a fundamental mechanism for diverse brain functions, including cognition. In several neurological conditions like AD, aberrant neural oscillations have been shown to play a central role. Furthermore, manipulation of brain oscillations in animals has confirmed their impact on cognition and disease. In this article, we review the evidence from mouse models that shows how synchronized oscillatory activity is intricately linked to AD machinery. We primarily focus on recent reports showing abnormal oscillatory activities at theta and gamma frequencies in AD condition and their influence on cellular disturbances and cognitive impairments. A thorough comprehension of the role that neuronal oscillations play in AD pathology should pave the way to therapeutic interventions that can curb the disease.

Slow waves form expanding, memory-rich mesostates steered by local excitability in fading anesthesia

In the arousal process, the brain restores its integrative activity from the synchronized state of slow wave activity (SWA). The mechanisms underpinning this state transition remain, however, to be elucidated. Here we simultaneously probed neuronal assemblies throughout the whole cortex with micro-electrocorticographic recordings in mice. We investigated the progressive shaping of propagating SWA at different levels of isoflurane. We found a form of memory of the wavefront shapes at deep anesthesia, tightly alternating posterior-anterior-posterior patterns. At low isoflurane, metastable patterns propagated in more directions, reflecting an increased complexity. The wandering across these mesostates progressively increased its randomness, as predicted by simulations of a network of spiking neurons, and confirmed in our experimental data. The complexity increase is explained by the elevated excitability of local assemblies with no modifications of the network connectivity. These results shed new light on the functional reorganization of the cortical network as anesthesia fades out.

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Complexity of isoflurane-induced slow waves reliably determines anesthesia level

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In deep anesthesia, the propagation strictly alternates between front-back-front patterns

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In light anesthesia, there is a continuum of directions and faster propagation

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Local excitability underpins the cortical reorganization in fading anesthesia

Energy-Based Hierarchical Clustering of Cortical Slow Waves in Multi-Electrode Recordings

The recent development of novel multi-electrode recording technologies has revealed the existence of traveling patterns of cortical activity in many species and under different states of awareness. Among these, slow activation waves occurring under sleep and anesthesia have been widely investigated as they provide unique insights into network features such as excitability, connectivity, structure, and dynamics of the cerebral cortex. Such characterization is usually based on clustering methods which are constrained by a priori assumptions as to the number of clusters to be used or rely on wave-by-wave pattern reconstruction. Here, we introduce a new computational tool based on modal analysis of fluid flows which is robustly applied to multivariate electrophysiological data from cortical networks, namely the Energy-based Hierarchical Waves Clustering method (EHWC). EHWC is composed of three main steps: (1) detecting the occurrence of global waves; (2) reducing the data dimensionality via singular value decomposition; (3) clustering hierarchically the singled-out waves. The analysis does not require the single-channel contribution to the waves, which is a typical bottleneck in this kind of analysis due to the unavoidable intrinsic variability of locally recorded activity. For testing and validation, here we used in vivo extracellular recordings from mice cortex under three different levels of anesthesia. As a result, we found slow waves with an increasing number of propagation modes as the anesthesia level decreases, giving an estimate of the increasing complexity of network dynamics. This and other wave's features replicate and extend the findings from previous literature, paving the way to extend the same approach to non-invasive electrophysiological recordings like EEG and fMRI used clinically for the characterization of brain dynamics and clinical stratification in brain lesions.

Brain injuries can set up an epileptogenic neuronal network

Development of epilepsy or epileptogenesis promotes recurrent seizures. As of today, there are no effective prophylactic therapies to prevent the onset of epilepsy. Contributing to this deficiency of preventive therapy is the lack of clarity in fundamental neurobiological mechanisms underlying epileptogenesis and lack of reliable biomarkers to identify patients at risk for developing epilepsy. This limits the development of prophylactic therapies in epilepsy. Here, neural network dysfunctions reflected by oscillopathies and microepileptiform activities, including neuronal hyperexcitability and hypersynchrony, drawn from both clinical and experimental epilepsy models, have been reviewed. This review suggests that epileptogenesis reflects a progressive and dynamic dysfunction of specific neuronal networks which recruit further interconnected groups of neurons, with this resultant pathological network mediating seizure occurrence, recurrence, and progression. In the future, combining spatial and temporal resolution of neuronal non-invasive recordings from patients at risk of developing epilepsy, together with analytics and computational tools, may contribute to determining whether the brain is undergoing epileptogenesis in asymptomatic patients following brain injury.

Glial Interfaces: Advanced Materials and Devices to Uncover the Role of Astroglial Cells in Brain Function and Dysfunction

Research over the past four decades has highlighted the importance of certain brain cells, called glial cells, and has moved the neurocentric vision of structure, function, and pathology of the nervous system toward a more holistic perspective. In this view, the demand for technologies that are able to target and both selectively monitor and control glial cells is emerging as a challenge across neuroscience, engineering, chemistry, and material science. Frequently neglected or marginally considered as a barrier to be overcome between neural implants and neuronal targets, glial cells, and in particular astrocytes, are increasingly considered as active players in determining the outcomes of device implantation. This review provides a concise overview not only of the previously established but also of the emerging physiological and pathological roles of astrocytes. It also critically discusses the most recent advances in biomaterial interfaces and devices that interact with glial cells and thus have enabled scientists to reach unprecedented insights into the role of astroglial cells in brain function and dysfunction. This work proposes glial interfaces and glial engineering as multidisciplinary fields that have the potential to enable significant advancement of knowledge surrounding cognitive function and acute and chronic neuropathologies.

Wireless, miniaturized, semi-implantable electrocorticography microsystem validated in vivo

This paper reports on the design, development, and test of a multi-channel wireless micro-electrocorticography (µECoG) system. The system consists of a semi-implantable, ultra-compact recording unit and an external unit, interfaced through a 2.4 GHz radio frequency data telemetry link with 2 Mbps (partially used) data transfer rate. Encased in a 3D-printed 2.9 cm × 2.9 cm × 2.5 cm cubic package, the semi-implantable recording unit consists of a microelectrode array, a vertically-stacked PCB platform containing off-the-shelf components, and commercially-available small-size 3.7-V, 50 mAh lithium-ion batteries. Two versions of microelectrode array were developed for the recording unit: a rigid 4 × 2 microelectrode array, and a flexible 12 × 6 microelectrode array, 36 of which routed to bonding pads for actual recording. The external unit comprises a transceiver board, a data acquisition board, and a host computer, on which reconstruction of the received signals is performed. After development, assembly, and integration, the system was tested and validated in vivo on anesthetized rats. The system successfully recorded both spontaneous and evoked activities from the brain of the subject.

Modulation of cortical slow oscillations and complexity across anesthesia levels

The ability of different groups of cortical neurons to engage in causal interactions that are at once differentiated and integrated results in complex dynamic patterns. Complexity is low during periods of unconsciousness (deep sleep, anesthesia, unresponsive wakefulness syndrome) in which the brain tends to generate a stereotypical pattern consisting of alternating active and silent periods of neural activity-slow oscillations- and is high during wakefulness. But how is cortical complexity built up? Is it a continuum? An open question is whether cortical complexity can vary within the same brain state. Here we recorded with 32-channel multielectrode arrays from the cortical surface of the mouse and used both spontaneous dynamics (wave propagation entropy and functional complexity) and a perturbational approach (a variation of the perturbation complexity index) to measure complexity at different anesthesia levels. Variations in anesthesia level within the bistable regime of slow oscillations (0.1-1.5 Hz) resulted in a modulation of the slow oscillation frequency. Both perturbational and spontaneous complexity increased with decreasing anesthesia levels, in correlation with the decrease in coherence of the underlying network. Changes in complexity level are related to, but not dependent on, changes in excitability. We conclude that cortical complexity can vary within a single brain state dominated by slow oscillations, building up to the higher complexity associated with consciousness.

A Glial-Silicon Nanowire Electrode Junction Enabling Differentiation and Noninvasive Recording of Slow Oscillations from Primary Astrocytes

The correct human brain function is dependent on the activity of non-neuronal cells called astrocytes. The bioelectrical properties of astrocytes in vitro do not closely resemble those displayed in vivo and the former are incapable of generating action potential; thus, reliable approaches in vitro for noninvasive electrophysiological recording of astrocytes remain challenging for biomedical engineering. Here it is found that primary astrocytes grown on a device formed by a forest of randomly oriented gold coated-silicon nanowires, resembling the complex structural and functional phenotype expressed by astrocytes in vivo. The device enables noninvasive extracellular recording of the slow-frequency oscillations generated by differentiated astrocytes, while flat electrodes failed on recording signals from undifferentiated cells. Pathophysiological concentrations of extracellular potassium, occurring during epilepsy and spreading depression, modulate the power of slow oscillations generated by astrocytes. A reliable approach to study the role of astrocytes function in brain physiology and pathologies is presented.

Analysis and Model of Cortical Slow Waves Acquired with Optical Techniques

Slow waves (SWs) are spatio-temporal patterns of cortical activity that occur both during natural sleep and anesthesia and are preserved across species. Even though electrophysiological recordings have been largely used to characterize brain states, they are limited in the spatial resolution and cannot target specific neuronal population. Recently, large-scale optical imaging techniques coupled with functional indicators overcame these restrictions, and new pipelines of analysis and novel approaches of SWs modelling are needed to extract relevant features of the spatio-temporal dynamics of SWs from these highly spatially resolved data-sets. Here we combined wide-field fluorescence microscopy and a transgenic mouse model expressing a calcium indicator (GCaMP6f) in excitatory neurons to study SW propagation over the meso-scale under ketamine anesthesia. We developed a versatile analysis pipeline to identify and quantify the spatio-temporal propagation of the SWs. Moreover, we designed a computational simulator based on a simple theoretical model, which takes into account the statistics of neuronal activity, the response of fluorescence proteins and the slow waves dynamics. The simulator was capable of synthesizing artificial signals that could reliably reproduce several features of the SWs observed in vivo, thus enabling a calibration tool for the analysis pipeline. Comparison of experimental and simulated data shows the robustness of the analysis tools and its potential to uncover mechanistic insights of the Slow Wave Activity (SWA).

Analysis Pipeline for Extracting Features of Cortical Slow Oscillations

Cortical slow oscillations (≲1 Hz) are an emergent property of the cortical network that integrate connectivity and physiological features. This rhythm, highly revealing of the characteristics of the underlying dynamics, is a hallmark of low complexity brain states like sleep, and represents a default activity pattern. Here, we present a methodological approach for quantifying the spatial and temporal properties of this emergent activity. We improved and enriched a robust analysis procedure that has already been successfully applied to both in vitro and in vivo data acquisitions. We tested the new tools of the methodology by analyzing the electrocorticography (ECoG) traces recorded from a custom 32-channel multi-electrode array in wild-type isoflurane-anesthetized mice. The enhanced analysis pipeline, named SWAP (Slow Wave Analysis Pipeline), detects Up and Down states, enables the characterization of the spatial dependency of their statistical properties, and supports the comparison of different subjects. The SWAP is implemented in a data-independent way, allowing its application to other data sets (acquired from different subjects, or with different recording tools), as well as to the outcome of numerical simulations. By using the SWAP, we report statistically significant differences in the observed slow oscillations (SO) across cortical areas and cortical sites. Computing cortical maps by interpolating the features of SO acquired at the electrode positions, we give evidence of gradients at the global scale along an oblique axis directed from fronto-lateral toward occipito-medial regions, further highlighting some heterogeneity within cortical areas. The results obtained using the SWAP will be essential for producing data-driven brain simulations. A spatial characterization of slow oscillations will also trigger a discussion on the role of, and the interplay between, the different regions in the cortex, improving our understanding of the mechanisms of generation and propagation of delta rhythms and, more generally, of cortical properties.

Conductive Polymer Hydrogel Microfibers from Multiflow Microfluidics

Conductive hydrogels are receiving increasing attention for their utility in electronic area applications requiring flexible conductors. Here, it is presented novel conductive hydrogel microfibers with alginate shells and poly (3, 4-ethylenedioxythiophene): poly (4-styrenesulfonate) (PEDOT: PSS) cores fabricated using a multiflow capillary microfluidic spinning approach. Based on multiflow microfluidics, alginate shells are formed immediately from the fast gelation reaction between sodium alginate (Na-Alg) and sheath laminar calcium chloride flows, while PEDOT: PSS cores are solidified slowly in the hollow alginate hydrogel shell microreactors after their precursor solutions are injected in situ as the center fluids. The resultant PEDOT: PSS-containing microfibers are with features of designed morphology and highly controllable package, because material compositions or the sizes of their shell hydrogels can be tailored by using different concentrations or flow rates of pregel solutions. Moreover, the practical values of these microfibers in stretch sensitivity and bending stability are explored based on various electrical characterizations of the compound materials. Thus, it is believed that these microfluidic spinning PEDOT: PSS conductive microfibers will find important utility in electronic applications requiring flexible electronic systems.