scholarly journals Inter-Brain Synchronization During Sandplay Therapy: Individual Analyses

2021 ◽  
Vol 12 ◽  
Author(s):  
Michiko Akimoto ◽  
Takuma Tanaka ◽  
Junko Ito ◽  
Yasutaka Kubota ◽  
Akitoshi Seiyama
Keyword(s):  
Near Infrared ◽  
Neural Basis ◽  
Sandplay Therapy ◽  
Therapeutic Alliances ◽  
Peripheral Oscillators ◽  
Therapy Technique ◽  
Interview Condition ◽  
Subsequent Interview ◽  
Spatio Temporal ◽  
Therapeutic Space

Interactions between the client (Cl) and therapist (Th) evolve therapeutic relationships in psychotherapy. An interpersonal link or therapeutic space is implicitly developed, wherein certain important elements are expressed and shared. However, neural basis of psychotherapy, especially of non-verbal modalities, have scarcely been explored. Therefore, we examined the neural backgrounds of such therapeutic alliances during sandplay, a powerful art/play therapy technique. Real-time and simultaneous measurement of hemodynamics was conducted in the prefrontal cortex (PFC) of Cl-Th pairs participating in sandplay and subsequent interview sessions through multichannel near-infrared spectroscopy. As sandplay is highly individualized, and no two sessions and products (sandtrays) are the same, we expected variation in interactive patterns in the Cl–Th pairs. Nevertheless, we observed a statistically significant correlation between the spatio-temporal patterns in signals produced by the homologous regions of the brains. During the sandplay condition, significant correlations were obtained in the lateral PFC and frontopolar (FP) regions in the real Cl-Th pairs. Furthermore, a significant correlation was observed in the FP region for the interview condition. The correlations found in our study were explained as a “remote” synchronization (i.e., unconnected peripheral oscillators synchronizing through a hub maintaining free desynchronized dynamics) between two subjects in a pair, possibly representing the neural foundation of empathy, which arises commonly in sandplay therapy (ST).

scholarly journals Cortical Activity Linked to Clocking in Deaf Adults: fNIRS Insights with Static and Animated Stimuli Presentation

2021 ◽  
Vol 11 (2) ◽  
pp. 196
Author(s):  
Sébastien Laurent ◽  
Laurence Paire-Ficout ◽  
Jean-Michel Boucheix ◽  
Stéphane Argon ◽  
Antonio Hidalgo-Muñoz
Keyword(s):  
Near Infrared ◽  
Brain Activity ◽  
Time Estimation ◽  
Cognitive Effort ◽  
Deaf People ◽  
Vehicle Speed ◽  
Neural Basis ◽  
Functional Near Infrared Spectroscopy ◽  
The Road ◽  
Deaf Adults

The question of the possible impact of deafness on temporal processing remains unanswered. Different findings, based on behavioral measures, show contradictory results. The goal of the present study is to analyze the brain activity underlying time estimation by using functional near infrared spectroscopy (fNIRS) techniques, which allow examination of the frontal, central and occipital cortical areas. A total of 37 participants (19 deaf) were recruited. The experimental task involved processing a road scene to determine whether the driver had time to safely execute a driving task, such as overtaking. The road scenes were presented in animated format, or in sequences of 3 static images showing the beginning, mid-point, and end of a situation. The latter presentation required a clocking mechanism to estimate the time between the samples to evaluate vehicle speed. The results show greater frontal region activity in deaf people, which suggests that more cognitive effort is needed to process these scenes. The central region, which is involved in clocking according to several studies, is particularly activated by the static presentation in deaf people during the estimation of time lapses. Exploration of the occipital region yielded no conclusive results. Our results on the frontal and central regions encourage further study of the neural basis of time processing and its links with auditory capacity.

scholarly journals Spectral Complexity of Hyperspectral Images: A New Approach for Mangrove Classification

2021 ◽  
Vol 13 (13) ◽  
pp. 2604
Author(s):  
Patrick Osei Darko ◽  
Margaret Kalacska ◽  
J. Pablo Arroyo-Mora ◽  
Matthew E. Fagan
Keyword(s):  
Statistical Physics ◽  
Near Infrared ◽  
Information Gain ◽  
Hyperspectral Imagery ◽  
Full Range ◽  
Surface Reflectance ◽  
Mangrove Species ◽  
New Approach ◽  
Spatio Temporal ◽  
Shortwave Infrared

Hyperspectral remote sensing across multiple spatio-temporal scales allows for mapping and monitoring mangrove habitats to support urgent conservation efforts. The use of hyperspectral imagery for assessing mangroves is less common than for terrestrial forest ecosystems. In this study, two well-known measures in statistical physics, Mean Information Gain (MIG) and Marginal Entropy (ME), have been adapted to high spatial resolution (2.5 m) full range (Visible-Shortwave-Infrared) airborne hyperspectral imagery. These two spectral complexity metrics describe the spatial heterogeneity and the aspatial heterogeneity of the reflectance. In this study, we compare MIG and ME with surface reflectance for mapping mangrove extent and species composition in the Sierpe mangroves in Costa Rica. The highest accuracy for separating mangroves from forest was achieved with visible-near infrared (VNIR) reflectance (98.8% overall accuracy), following by shortwave infrared (SWIR) MIG and ME (98%). Our results also show that MIG and ME can discriminate dominant mangrove species with higher accuracy than surface reflectance alone (e.g., MIG–VNIR = 93.6% vs. VNIR Reflectance = 89.7%).

scholarly journals Exploring the spatio-temporal neural basis of face learning

2017 ◽  
Vol 17 (6) ◽  
pp. 1 ◽  
Author(s):  
Ying Yang ◽  
Yang Xu ◽  
Carol A. Jew ◽  
John A. Pyles ◽  
Robert E. Kass ◽  
...  
Keyword(s):  
Neural Basis ◽  
Spatio Temporal

scholarly journals Validation of nine years of MOPITT V5 NIR using MOZAIC/IAGOS measurements: biases and long-term stability

2014 ◽  
Vol 7 (11) ◽  
pp. 3783-3799 ◽  
Author(s):  
A. T. J. de Laat ◽  
I. Aben ◽  
M. Deeter ◽  
P. Nédélec ◽  
H. Eskes ◽  
...  
Keyword(s):  
Near Infrared ◽  
Transport Model ◽  
A Priori ◽  
Validation Data ◽  
Chemistry Transport Model ◽  
Large Variability ◽  
Long Term Stability ◽  
Spatio Temporal ◽  
Good Agreement

Abstract. Validation results from a comparison between Measurement Of Pollution In The Troposphere (MOPITT) V5 Near InfraRed (NIR) carbon monoxide (CO) total column measurements and Measurement of Ozone and Water Vapour on Airbus in-service Aircraft (MOZAIC)/In-Service Aircraft for a Global Observing System (IAGOS) aircraft measurements are presented. A good agreement is found between MOPITT and MOZAIC/IAGOS measurements, consistent with results from earlier studies using different validation data and despite large variability in MOPITT CO total columns along the spatial footprint of the MOZAIC/IAGOS measurements. Validation results improve when taking the large spatial footprint of the MOZAIC/IAGOS data into account. No statistically significant drift was detected in the validation results over the period 2002–2010 at global, continental and local (airport) scales. Furthermore, for those situations where MOZAIC/IAGOS measurements differed from the MOPITT a priori, the MOPITT measurements clearly outperformed the MOPITT a priori data, indicating that MOPITT NIR retrievals add value to the MOPITT a priori. Results from a high spatial resolution simulation of the chemistry-transport model MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle) showed that the most likely explanation for the large MOPITT variability along the MOZAIC-IAGOS profile flight path is related to spatio-temporal CO variability, which should be kept in mind when using MOZAIC/IAGOS profile measurements for validating satellite nadir observations.

scholarly journals CrocO_v1.0 : a Particle Filter to assimilate snowpack observations in a spatialised framework

2020 ◽  
Author(s):  
Bertrand Cluzet ◽  
Matthieu Lafaysse ◽  
Emmanuel Cosme ◽  
Clément Albergel ◽  
Louis-François Meunier ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Particle Filter ◽  
Near Infrared ◽  
Snow Water Equivalent ◽  
Sources Of Information ◽  
Average Improvement ◽  
Modelling Uncertainties ◽  
Snow Water ◽  
Spatio Temporal ◽  
Snowpack Properties

Abstract. Monitoring the evolution of the snowpack properties in mountainous areas is crucial for avalanche hazard forecasting and water resources management. In-situ and remotely sensed observations provide precious information on the snowpack but usually offer a limited spatio-temporal coverage of bulk or surface variables only. In particular, visible-near infrared (VIS-NIR) reflectance observations can inform on the snowpack surface properties but are limited by terrain shading and clouds. Snowpack modelling enables to estimate any physical variable, virtually anywhere, but is affected by large errors and uncertainties. Data assimilation offers a way to combine both sources of information, and to propagate information from observed areas to non observed areas. Here, we present CrocO, (Crocus-Observations) an ensemble data assimilation system able to ingest any snowpack observation (applied as a first step to the height of snow (HS) and VIS-NIR reflectances) in a spatialised geometry. CrocO uses an ensemble of snowpack simulations to represent modelling uncertainties, and a Particle Filter (PF) to reduce them. The PF is known to collapse when assimilating a too large number of observations. Two variants of the PF were specifically implemented to ensure that observations information is propagated in space while tackling this issue. The global algorithm ingests all available observations with an iterative inflation of observation errors, while the klocal algorithm is a localised approach performing a selection of the observations to assimilate based on background correlation patterns. Experiments are carried out in a twin experiment setup, with synthetic observations of HS and VIS-NIR reflectances available in only a 1/6th of the simulation domain. Results show that compared against runs without assimilation, analyses exhibit an average improvement of snow water equivalent Continuous Rank Probability Score (CRPS) of 60 % when assimilating HS with a 40-member ensemble, and an average 20 % CRPS improvement when assimilating reflectance with a 160-member ensemble. Significant improvements are also obtained outside the observation domain. These promising results open a way for the assimilation of real observations of reflectance, or of any snowpack observations in a spatialised context.

scholarly journals Quality Assessment of PROBA-V Surface Albedo V1 for the Continuity of the Copernicus Climate Change Service

2020 ◽  
Vol 12 (16) ◽  
pp. 2596
Author(s):  
Jorge Sánchez-Zapero ◽  
Fernando Camacho ◽  
Enrique Martínez-Sánchez ◽  
Roselyne Lacaze ◽  
Dominique Carrer ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Albedo ◽  
Near Infrared ◽  
Accuracy Assessment ◽  
Performance Criteria ◽  
Climate Data ◽  
Residual Noise ◽  
Space Agency ◽  
Median Error ◽  
Spatio Temporal

The Copernicus Climate Change Service (C3S) includes estimates of Essential Climate Variables (ECVs) as a series of Climate Data Records (CDRs) derived from satellite data. The C3S Surface Albedo (SA) v1.0 CDR is composed of observations from National Oceanic and Atmospheric Administration (NOAA) Very High Resolution Radiometers (AVHRR) (1981–2005), and VEGETATION sensors onboard Satellites for the Observation of the Earth (SPOT/VGT) (1998–2014) and Project for Onboard Autonomy satellite (PROBA-V) (2014–2020), and will continue with Sentinel-3 (from 2020 onwards). The goal of this study is to assess the uncertainties associated with the C3S PROBA-V SA v1.0 product, with a focus on the transition from SPOT/VGT to PROBA-V. The methodology followed the good practices recommended by the Land Product Validation sub-group (LPV) of the Working Group on Calibration and Validation (WGCV) of the Committee on Earth Observing Satellites (CEOS) for the validation of satellite-derived global albedo products. Several performance criteria were evaluated, including an intercomparison with National Aeronautics and Space Agency (NASA) MCD43A3 C6 products. C3S PROBA-V SA v1.0 and MCD43A3 C6 showed similar completeness but had higher fractions of missing data than C3S SPOT/VGT SA v1.0. C3S PROBA-V SA v1.0 showed similar precision (~1%) to MCD43A3 C6, improving the results of SPOT/VGT SA v1.0 (2–3%), but C3S PROBA-V SA v1.0 provided residual noise in the near-infrared (NIR). Good spatio-temporal continuity between C3S PROBA-V and SPOT/VGT SA v1.0 products was found with a mean bias between ±2%. The comparison with MCD43A3 C6 showed positive mean biases (5%, 8%, and 12% for visible, NIR and total shortwave, respectively). The accuracy assessment with ground measurements showed a median error of 18.4% with systematic overestimation (positive bias of 11.5%). The percentage of PROBA-V retrievals complying with the C3S target requirements was 28.6%.

scholarly journals Spatio-temporal influence of tundra snow properties on Ku-band (17.2 GHz) backscatter

2015 ◽  
Vol 61 (226) ◽  
pp. 267-279 ◽  
Author(s):  
Joshua King ◽  
Richard Kelly ◽  
Andrew Kasurak ◽  
Claude Duguay ◽  
Grant Gunn ◽  
...  
Keyword(s):  
Near Infrared ◽  
Snow Water Equivalent ◽  
Sampling Procedure ◽  
Field Of View ◽  
Boreal Winter ◽  
Snow Properties ◽  
Snow Sampling ◽  
Temporal Influence ◽  
Spatio Temporal ◽  
Ku Band

AbstractDuring the 2010/11 boreal winter, a distributed set of backscatter measurements was collected using a ground-based Ku-band (17.2 GHz) scatterometer system at 26 open tundra sites. A standard snow-sampling procedure was completed after each scan to evaluate local variability in snow layering, depth, density and water equivalent (SWE) within the scatterometer field of view. The shallow depths and large basal depth hoar encountered presented an opportunity to evaluate backscatter under a set of previously untested conditions. Strong Ku-band response was found with increasing snow depth and snow water equivalent (SWE). In particular, co-polarized vertical backscatter increased by 0.82 dB for every 1 cm increase in SWE (R2 = 0.62). While the result indicated strong potential for Ku-band retrieval of shallow snow properties, it did not characterize the influence of sub-scan variability. An enhanced snow-sampling procedure was introduced to generate detailed characterizations of stratigraphy within the scatterometer field of view using near-infrared photography along the length of a 5 m trench. Changes in snow properties along the trench were used to discuss variations in the collocated backscatter response. A pair of contrasting observation sites was used to highlight uncertainties in backscatter response related to short length scale spatial variability in the observed tundra environment.

scholarly journals Cortical Mechanisms of Cognitive Control for Shifting Attention in Vision and Working Memory

2011 ◽  
Vol 23 (10) ◽  
pp. 2905-2919 ◽  
Author(s):  
Benjamin J. Tamber-Rosenau ◽  
Michael Esterman ◽  
Yu-Chin Chiu ◽  
Steven Yantis
Keyword(s):  
Working Memory ◽  
Cognitive Control ◽  
Relevant Information ◽  
Neural Basis ◽  
Cognitive Domains ◽  
Future Goals ◽  
Spatio Temporal ◽  
Past Experiences ◽  
Selection Of ◽  
Superior Frontal Sulcus

Organisms operate within both a perceptual domain of objects and events, and a mnemonic domain of past experiences and future goals. Each domain requires a deliberate selection of task-relevant information, through deployments of external (perceptual) and internal (mnemonic) attention, respectively. Little is known about the control of attention shifts in working memory, or whether voluntary control of attention in these two domains is subserved by a common or by distinct functional networks. We used human fMRI to examine the neural basis of cognitive control while participants shifted attention in vision and in working memory. We found that these acts of control recruit in common a subset of the dorsal fronto-parietal attentional control network, including the medial superior parietal lobule, intraparietal sulcus, and superior frontal sulcus/gyrus. Event-related multivoxel pattern classification reveals, however, that these regions exhibit distinct spatio-temporal patterns of neural activity during internal and external shifts of attention, respectively. These findings constrain theoretical accounts of selection in working memory and perception by showing that populations of neurons in dorsal fronto-parietal network regions exhibit selective tuning for acts of cognitive control in different cognitive domains.

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