The ability to access brain information in real-time is crucial both for a better understanding of cognitive functions and for the development of therapeutic applications based on brain-machine ...interfaces. Great success has been achieved in the field of neural motor prosthesis. Progress is still needed in the real-time decoding of higher-order cognitive processes such as covert attention. Recently, we showed that we can track the location of the attentional spotlight using classification methods applied to prefrontal multi-unit activity (MUA) in the non-human primates. Importantly, we demonstrated that the decoded (x,y) attentional spotlight parametrically correlates with the behavior of the monkeys thus validating our decoding of attention. We also demonstrate that this spotlight is extremely dynamic. Here, in order to get closer to non-invasive decoding applications, we extend our previous work to local field potential signals (LFP). Specifically, we achieve, for the first time, high decoding accuracy of the (x,y) location of the attentional spotlight from prefrontal LFP signals, to a degree comparable to that achieved from MUA signals, and we show that this LFP content is predictive of behavior. This LFP attention-related information is maximal in the gamma band (30–250 Hz), peaking between 60 to 120 Hz. In addition, we introduce a novel two-step decoding procedure based on the labelling of maximally attention-informative trials during the decoding procedure. This procedure strongly improves the correlation between our real-time MUA and LFP based decoding and behavioral performance, thus further refining the functional relevance of this real-time decoding of the (x,y) locus of attention. This improvement is more marked for LFP signals than for MUA signals. Overall, this study demonstrates that the attentional spotlight can be accessed from LFP frequency content, in real-time, and can be used to drive high-information content cognitive brain-machine interfaces for the development of new therapeutic strategies.
Abstract
In the context of visual attention, it has been classically assumed that missing the response to a target or erroneously selecting a distractor occurs as a consequence of the ...(miss)allocation of attention in space. In the present paper, we challenge this view and provide evidence that, in addition to encoding spatial attention, prefrontal neurons also encode a distractibility-to-impulsivity state. Using supervised dimensionality reduction techniques in prefrontal neuronal recordings in monkeys, we identify two partially overlapping neuronal subpopulations associated either with the focus of attention or overt behaviour. The degree of overlap accounts for the behavioral gain associated with the good allocation of attention. We further describe the neural variability accounting for distractibility-to-impulsivity behaviour by a two dimensional state associated with optimality in task and responsiveness. Overall, we thus show that behavioral performance arises from the integration of task-specific neuronal processes and pre-existing neuronal states describing task-independent behavioral states.
Open‐conduit conditions characterize several of the most hazardous and active volcanic systems of basaltic composition worldwide, persistently refilled by magmatic inputs. Eruptive products with ...similar bulk compositions, chemically buffered by continual mafic inputs, nevertheless exhibit heterogeneous glass compositions in response to variable magma mixing, crystallization, and differentiation processes within different parts of the plumbing system. Here, we document how multivariate statistics and magma differentiation modeling based on a large data set of glass compositions can be combined to constrain magma differentiation and plumbing system dynamics. Major and trace elements of matrix glasses erupted at Stromboli volcano (Italy) over the last 20 years provide a benchmark against which to test our integrated petrological approach. Principal component analysis, K‐means cluster analysis, and kernel density estimation reveal that trace elements define a multivariate space whose eigenvectors are more readily interpretable in terms of petrological processes than major elements, leading to improved clustering solutions. Comparison between open‐ and closed‐system differentiation models outlines that steady state magma compositions at constantly replenished and erupting magmatic systems approximate simple fractional crystallization trends, due to short magma residence times. Open‐system magma evolution is associated with magma storage crystallinities that are lower than those associated with closed‐system scenarios. Accordingly, open‐system dynamics determine the efficient crystal‐melt separation toward the top of the reservoir, where eruptible melts continuously supply the ordinary activity. Conversely, a mush‐like environment constitutes the bottom of the reservoir, where poorly evolved magmas result from mixing events between mush residual melts and primitive magmas injected from deeper crustal levels.
Plain Language Summary
Volcanoes characterized by continuous eruptive activity are typified by constant replenishment of new magma, rising from deeper regions of the crust. The volcanic glass (supercooled silicate melt), represents the residual liquid of magma crystallization, and is found as the intracrystalline matrix of eruptive products. The study of its chemical composition may provide insight into the processes occurring at depths beneath the volcanic vent, where magma compositional changes result from crystallization and mixing with new magma rising from depth. We combine statistical analyses and analytical equations based on the chemical composition of the matrix glasses from Stromboli volcano, in order to constrain the processes which produce their chemical variations, identifying different environments where magmas are stored at depth. Our results also show that when magma is stored for a short period of time, the chemical changes to which the magma is subjected in a constantly replenished system are similar to those occurring in a system which is closed to new inputs of magma.
Key Points
The combination of multivariate statistics with geochemical modeling provides new constraints on magma differentiation processes
Multivariate statistics based on trace elements allow better retrieval of petrological information than those based on major elements
Magma differentiation in open systems approximates that occurring in closed systems when magma residence timescales are short
Charge collection in irradiated HV-CMOS detectors Hiti, B.; Affolder, A.; Arndt, K. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
04/2019, Letnik:
924, Številka:
C
Journal Article
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Active silicon detectors built on p-type substrate are a promising technological solution for large area silicon trackers such as those at the High Luminosity LHC, but the radiation hardness of this ...novel approach has to be evaluated. Active n-in-p strip detector prototypes CHESS2 for ATLAS with different substrate resistivities in the range of 20–1000 Ωcm were irradiated with neutrons and protons up to a fluence of 2×1015neqcm−2 and 3.6×1015neqcm−2. Charge collection in passive test structures on the chip was evaluated using Edge-TCT and minimum ionising electrons from 90Sr. Results were used to assess radiation hardness of the detector in the given fluence range and to determine parameters of initial acceptor removal in different substrates.
•Irradiated samples of different initial resistivity between 20 and a few 1000 Ω cm.•Characterisation with edge transient current technique and 90Sr beta electrons.•Sensitive region increases after irradiation due to acceptor removal.•Parameters of acceptor removal estimated for neutron irradiation.•After proton irradiation larger sensitive region than after neutron irradiation.
ATLAS has formed strip CMOS project to study the use of CMOS MAPS devices as silicon strip sensors for the Phase-II Strip Tracker Upgrade. This choice of sensors promises several advantages over the ...conventional baseline design, such as better resolution, less material in the tracking volume, and faster construction speed. At the same time, many design features of the sensors are driven by the requirement of minimizing the impact on the rest of the detector. Hence the target devices feature long pixels which are grouped to form a virtual strip with binary-encoded z position. The key performance aspects are radiation hardness compatibility with HL-LHC environment, as well as extraction of the full hit position with full-reticle readout architecture. To date, several test chips have been submitted using two different CMOS technologies. The AMS 350nm is a high voltage CMOS process (HV-CMOS), that features the sensor bias of up to 120V. The TowerJazz 180nm high resistivity CMOS process (HR-CMOS) uses a high resistivity epitaxial layer to provide the depletion region on top of the substrate. We have evaluated passive pixel performance, and charge collection projections. The results strongly support the radiation tolerance of these devices to radiation dose of the HL-LHC in the strip tracker region. We also describe design features for the next chip submission that are motivated by our technology evaluation.
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