Eustasy in the Aptian world: A vision from the eastern margin of the Iberian Plate

Eustatic controls on Early Cretaceous (Aptian) sedimentation in the western Tethys are discerned in outcrops of carbonate platforms that developed in the Maestrat rift basin located at the eastern margin of the Iberian Plate. The relative sea-level fluctuations with a dominant eustatic contribution investigated had estimated magnitudes of between 50 and 60 m in <0.9 My and ≥115 m in <3 My, and occurred respectively during the late early and early late Aptian. The major relative sea-level falls of mainly eustatic nature were recorded as forced regressive sedimentary wedges or as incised valleys carved into highstand carbonate platforms, whereas the subsequent sea- level rises back-filled the incised topographic lows created, or favoured the development of lowstand platforms. The finding of 50-115 m amplitude fluctuations of Aptian age is of relevance in that show magnitudes of relative sea-level fall in the order of that recorded during the last glacial maximum in the late Pleistocene (c. 120 m). The current knowledge on Cretaceous climate history shows an Earth with non-uniform greenhouse conditions. However, geological evidence of temporary icehouse states with ice-cap magnitudes close to late Pleistocene scales during the Aptian is absent, or at least has not been reported so far. Thus, although falling within the glacio-eustatic domain, the driving processes of these widespread drops and subsequent rises in relative sea level remain a mystery. Finally, this paper is an example of how sequence stratigraphy can be applied to carbonate successions, and of how this methodology indeed permits to unravel ancient relative sea-level fluctuations which controlled carbonate production and accumulation

Multiplexed neural sensor array of graphene solution-gated field-effect transistors

Altres ajuts: this work has made use of the Spanish ICTS Network MICRONANOFABS partially supported by MICINN and the ICTS 'NANBIOSIS', more specifically by the Micro-NanoTechnology Unit of the CIBER in Bioengineering, Biomaterials and Nanomedicine (CIBERBBN) at the IMB-CNM.Electrocorticography (ECoG) is a well-established technique to monitor electrophysiological activity from the surface of the brain and has proved crucial for the current generation of neural prostheses and brain-computer interfaces. However, existing ECoG technologies still fail to provide the resolution necessary to accurately map highly localized activity across large brain areas, due to the rapidly increasing size of connector footprint with sensor count. This work demonstrates the use of a flexible array of graphene solution-gated field-effect transistors (gSGFET), exploring the concept of multiplexed readout using an external switching matrix. This approach does not only allow for an increased sensor count, but due to the use of active sensing devices (i.e. transistors) over microelectrodes it makes additional buffer transistors redundant, which drastically eases the complexity of device fabrication on flexible substrates. The presented results pave the way for upscaling the gSGFET technology towards large-scale, high-density μECoG-arrays, eventually capable of resolving neural activity down to a single neuron level, while simultaneously mapping large brain regions

Bidirectional Modulation of Neuronal Cells Electrical and Mechanical Properties Through Pristine and Functionalized Graphene Substrates

[Abstract] In recent years, the quest for surface modifications to promote neuronal cell interfacing and modulation has risen. This course is justified by the requirements of emerging technological and medical approaches attempting to effectively interact with central nervous system cells, as in the case of brain-machine interfaces or neuroprosthetic. In that regard, the remarkable cytocompatibility and ease of chemical functionalization characterizing surface-immobilized graphene-based nanomaterials (GBNs) make them increasingly appealing for these purposes. Here, we compared the (morpho)mechanical and functional adaptation of rat primary hippocampal neurons when interfaced with surfaces covered with pristine single-layer graphene (pSLG) and phenylacetic acid-functionalized single-layer graphene (fSLG). Our results confirmed the intrinsic ability of glass-supported single-layer graphene to boost neuronal activity highlighting, conversely, the downturn inducible by the surface insertion of phenylacetic acid moieties. fSLG-interfaced neurons showed a significant reduction in spontaneous postsynaptic currents (PSCs), coupled to reduced cell stiffness and altered focal adhesion organization compared to control samples. Overall, we have here demonstrated that graphene substrates, both pristine and functionalized, could be alternatively used to intrinsically promote or depress neuronal activity in primary hippocampal cultures.This work was funded by the European Union’s Horizon 2020 Research and Innovation Program under the Grant Agreements 785219 and 881603 of the Graphene Flagship. DS acknowledges the support of the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement no. 838902. MP as the recipient of the AXA Bionanotechnology Chair, is grateful to the AXA Research Fund for financial support. This work was performed under the Maria de Maeztu Units of Excellence Program from the Spanish State Research Agency-grant no. MDM-2017- 0720. AC thanks Xunta de Galicia for his research grant Atracción de Talento (no. ED431H 2020/17). GR acknowledges funding from RYC-2016-21412. HH acknowledges funding from Juan de la Cierva – Incorporación no. IJC-2018-037396-IXunta de Galicia; ED431H 2020/1

Distortion-free sensing of neural activity using graphene transistors

Graphene solution-gated field-effect transistors (g-SGFETs) are promising sensing devices to transduce electrochemical potential signals in an electrolyte bath. However, distortion mechanisms in g-SGFET, which can affect signals of large amplitude or high frequency, have not been evaluated. Here, a detailed characterization and modeling of the harmonic distortion and non-ideal frequency response in g-SGFETs is presented. This accurate description of the input-output relation of the g-SGFETs allows to define the voltage- and frequency-dependent transfer functions, which can be used to correct distortions in the transduced signals. The effect of signal distortion and its subsequent calibration are shown for different types of electrophysiological signals, spanning from large amplitude and low frequency cortical spreading depression events to low amplitude and high frequency action potentials. The thorough description of the distortion mechanisms presented in this article demonstrates that g-SGFETs can be used as distortion-free signal transducers not only for neural sensing, but also for a broader range of applications in which g-SGFET sensors are used

Quantification of Signal-to-Noise Ratio in Cerebral Cortex Recordings Using Flexible MEAs With Co-localized Platinum Black, Carbon Nanotubes, and Gold Electrodes

Developing new standardized tools to characterize brain recording devices is critical to evaluate neural probes and for translation to clinical use. The signal-to-noise ratio (SNR) measurement is the gold standard for quantifying the performance of brain recording devices. Given the drawbacks with the SNR measure, our first objective was to devise a new method to calculate the SNR of neural signals to distinguish signal from noise. Our second objective was to apply this new SNR method to evaluate electrodes of three different materials (platinum black, Pt; carbon nanotubes, CNTs; and gold, Au) co-localized in tritrodes to record from the same cortical area using specifically designed multielectrode arrays. Hence, we devised an approach to calculate SNR at different frequencies based on the features of cortical slow oscillations (SO). Since SO consist in the alternation of silent periods (Down states) and active periods (Up states) of neuronal activity, we used these as noise and signal, respectively. The spectral SNR was computed as the power spectral density (PSD) of Up states (signal) divided by the PSD of Down states (noise). We found that Pt and CNTs electrodes have better recording performance than Au electrodes for the explored frequency range (5–1500 Hz). Together with two proposed SNR estimators for the lower and upper frequency limits, these results substantiate our SNR calculation at different frequency bands. Our results provide a new validated SNR measure that provides rich information of the performance of recording devices at different brain activity frequency bands (&lt;1500 Hz)

A 1024-Channel 10-Bit 36-μW/ch CMOS ROIC for Multiplexed GFET-Only Sensor Arrays in Brain Mapping

This paper presents a 1024-channel neural read-out integrated circuit (ROIC) for solution-gated GFET sensing probes in massive muECoG brain mapping. The proposed time-domain multiplexing of GFET-only arrays enables low-cost and scalable hybrid headstages. Low-power CMOS circuits are presented for the GFET analog frontend, including a CDS mechanism to improve preamplifier noise figures and 10-bit 10-kS/s A/D conversion. The 1024-channel ROIC has been fabricated in a standard 1.8-V 0.18-mum CMOS technology with 0.012 mm 2 and 36 mu W per channel. An automated methodology for the in-situ calibration of each GFET sensor is also proposed. Experimental ROIC tests are reported using a custom FPGA-based muECoG headstage with 16times 32 and 32times 32 GFET probes in saline solution and agar substrate. Compared to state-of-art neural ROICs, this work achieves the largest scalability in hybrid platforms and it allows the recording of infra-slow neural signals

Concurrent functional ultrasound imaging with graphene-based DC-coupled electrophysiology as a platform to study slow brain signals and cerebral blood flow under control and pathophysiological brain states

Current methodology used to investigate how shifts in brain states associated with regional cerebral blood volume (CBV) change in deep brain areas, are limited by either the spatiotemporal resolution of the CBV techniques, and/or compatibility with electrophysiological recordings; particularly in relation to spontaneous brain activity and the study of individual events. Additionally, infraslow brain signals (&lt;0.1 Hz), including spreading depolarisations, DC-shifts and infraslow oscillations (ISO), are poorly captured by traditional AC-coupled electrographic recordings; yet these very slow brain signals can profoundly change CBV. To gain an improved understanding of how infraslow brain signals couple to CBV we present a new method for concurrent CBV with wide bandwidth electrophysiological mapping using simultaneous functional ultrasound imaging (fUS) and graphene-based field effect transistor (gFET) DC-coupled electrophysiological acquisitions. To validate the feasibility of this methodology visually-evoked neurovascular coupling (NVC) responses were examined. gFET recordings are not affected by concurrent fUS imaging, and epidural placement of gFET arrays within the imaging window did not deteriorate fUS signal quality. To examine directly the impact of infra-slow potential shifts on CBV, cortical spreading depolarisations (CSDs) were induced. A biphasic pattern of decreased, followed by increased CBV, propagating throughout the ipsilateral cortex, and a delayed decrease in deeper subcortical brain regions was observed. In a model of acute seizures, CBV oscillations were observed prior to seizure initiation. Individual seizures occurred on the rising phase of both infraslow brain signal and CBV oscillations. When seizures co-occurred with CSDs, CBV responses were larger in amplitude, with delayed CBV decreases in subcortical structures. Overall, our data demonstrate that gFETs are highly compatible with fUS and allow concurrent examination of wide bandwidth electrophysiology and CBV. This graphene-enabled technological advance has the potential to improve our understanding of how infraslow brain signals relate to CBV changes in control and pathological brain states.</p

Frequency response of electrolyte-gated graphene electrodes and transistors

The interface between graphene and aqueous electrolytes is of high importance for applications of graphene in the field of biosensors and bioelectronics. The graphene/electrolyte interface is governed by the low density of states of graphene that limits the capacitance near the Dirac point in graphene and the sheet resistance. While several reports have focused on studying the capacitance of graphene as a function of the gate voltage, the frequency response of graphene electrodes and electrolyte-gated transistors has not been discussed so far. Here, we report on the impedance characterization of single layer graphene electrodes and transistors, showing that due to the relatively high sheet resistance of graphene, the frequency response is governed by the distribution of resistive and capacitive circuit elements along the graphene/electrolyte interface. Based on an analytical solution for the impedance of the distributed circuit elements, we model the graphene/electrolyte interface both for the electrode and the transistor configurations. Using this model, we can extract the relevant material and device parameters such as the voltage-dependent intrinsic sheet and series resistances as well as the interfacial capacitance. The model also provides information about the frequency threshold of electrolyte-gated graphene transistors, above which the device exhibits a non-resistive response, offering an important insight into the suitable frequency range of operation of electrolyte-gated graphene devices

Challenge 2: From genes & circuits to behavior

Understanding the brain from genes and circuits to behavior is a major scientific challenge. The large repertoire of cell activities supporting behavior stems from an equally diverse range of specialized cell types, from neuron to glia. To untangle mechanisms underlying brain function, elementary processes should be dissected, from the complex machinery of signaling pathways at the level of single cells and synapses, to the intricate phenomena leading to orchestrated ensemble activity and the establishment of engrams driving memory-guided behaviors. In this chapter we identify the main key tasks required to address some of the open questions in the field, and discuss on the main issues and strategies

Mapping brain activity with flexible graphene micro-transistors

Establishing a reliable communication interface between the brain and electronic devices is of paramount importance for exploiting the full potential of neural prostheses. Current microelectrode technologies for recording electrical activity, however, evidence important shortcomings, e.g. challenging high density integration. Solution-gated field-effect transistors (SGFETs), on the other hand, could overcome these shortcomings if a suitable transistor material were available. Graphene is particularly attractive due to its biocompatibility, chemical stability, flexibility, low intrinsic electronic noise and high charge carrier mobilities. Here, we report on the use of an array of flexible graphene SGFETs for recording spontaneous slow waves, as well as visually evoked and also pre-epileptic activity in vivo in rats. The flexible array of graphene SGFETs allows mapping brain electrical activity with excellent signal-to-noise ratio (SNR), suggesting that this technology could lay the foundation for a future generation of in vivo recording implants