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Identifying neural correlates of conscious perception is a fundamental endeavor of cognitive neuroscience. Most studies so far have focused on visual awareness along with trial-by-trial reports of task relevant stimuli, which can confound neural measures of perceptual awareness with post-perceptual processing. Here, we used a three-phase sine-wave speech paradigm that dissociated between conscious speech perception and task relevance while recording EEG in humans of both sexes. Compared to tokens perceived as noise, physically identical sine-wave speech tokens that were perceived as speech elicited a left-lateralized, near-vertex negativity, which we interpret as a phonological version of a perceptual awareness negativity. This response appeared between 200 and 300 ms after token onset and was not present for frequency-flipped control tokens that were never perceived as speech. In contrast, the P3b elicited by task-irrelevant tokens did not significantly differ when the tokens were perceived as speech versus noise, and was only enhanced for tokens that were both perceived as speechandrelevant to the task. Our results extend the findings from previous studies on visual awareness and speech perception, and suggest that correlates of conscious perception, across types of conscious content, are most likely to be found in mid-latency negative-going brain responses in content-specific sensory areas.

Significance StatementHow patterns of brain activity give rise to conscious perception is a fundamental question of cognitive neuroscience. Here, we asked whether markers of conscious speech perception can be separated from task-related confounds. We combined sine-wave speech - a degraded speech signal that is heard as noise by naive individuals but can readily be heard as speech after minimal training - with a no-report paradigm that independently manipulated perception (speech versus non-speech) and task (relevant versus irrelevant). Using this paradigm, we were able to identify a marker of speech perception in mid-latency responses over left frontotemporal EEG channels that was independent of task. Our results demonstrate that the “perceptual awareness negativity” is present for a new type of perceptual content (speech).

Abstract. A comparison of polar stratospheric cloud (PSC) occurrence from 2006 to2010 is presented, as observed from the ground-based lidar station at McMurdo(Antarctica) and by the satellite-borne CALIOP lidar (Cloud-Aerosol Lidarwith Orthogonal Polarization) measuring over McMurdo. McMurdo (Antarctica) isone of the primary lidar stations for aerosol measurements of the NDACC (Network forDetection of Atmospheric Climate Change). The ground-based observations havebeen classified with an algorithm derived from the recent v2 detection andclassification scheme, used to classify PSCs observed by CALIOP.

A statistical approach has been used to compare ground-based and satellite-based observations, since point-to-point comparison is often troublesome dueto the intrinsic differences in the observation geometries and the imperfectoverlap of the observed areas.

A comparison of space-borne lidar observations and a selection of simulationsobtained from chemistry–climate models (CCMs) has been made by using a series ofquantitative diagnostics based on the statistical occurrence of different PSCtypes. The distribution of PSCs over Antarctica, calculated by severalCCMVal-2 and CCMI chemistry–climate models has been compared with the PSCcoverage observed by the satellite-borne CALIOP lidar. The use of severaldiagnostic tools, including the temperature dependence of the PSCoccurrences, evidences the merits and flaws of the different models. Thediagnostic methods have been defined to overcome (at least partially) thepossible differences due to the resolution of the models and to identifydifferences due to microphysics (e.g., the dependence of PSC occurrence onT−T_NAT).

A significant temperature bias of most models has been observed, as well as alimited ability to reproduce the longitudinal variations in PSC occurrencesobserved by CALIOP. In particular, a strong temperature bias has been observedin CCMVal-2 models with a strong impact on PSC formation. The WACCM-CCMI(Whole Atmosphere Community Climate Model – Chemistry-Climate ModelInitiative) model compares rather well with the CALIOP observations, althougha temperature bias is still present.