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61. Fast animal pose estimation using deep neural networks

Author(s):
Pereira, Talmo D.; Aldarondo, Diego E.; Willmore, Lindsay; Kislin, Mikhail; Wang, Samuel S.-H.; Murthy, Mala; Shaevitz, Joshua W.
Abstract:
Recent work quantifying postural dynamics has attempted to define the repertoire of behaviors performed by an animal. However, a major drawback to these techniques has been their reliance on dimensionality reduction of images which destroys information about which parts of the body are used in each behavior. To address this issue, we introduce a deep learning-based method for pose estimation, LEAP (LEAP Estimates Animal Pose). LEAP automatically predicts the positions of animal body parts using a deep convolutional neural network with as little as 10 frames of labeled data for training. This framework consists of a graphical interface for interactive labeling of body parts and software for training the network and fast prediction on new data (1 hr to train, 185 Hz predictions). We validate LEAP using videos of freely behaving fruit flies (Drosophila melanogaster) and track 32 distinct points on the body to fully describe the pose of the head, body, wings, and legs with an error rate of <3% of the animal's body length. We recapitulate a number of reported findings on insect gait dynamics and show LEAP's applicability as the first step in unsupervised behavioral classification. Finally, we extend the method to more challenging imaging situations (pairs of flies moving on a mesh-like background) and movies from freely moving mice (Mus musculus) where we track the full conformation of the head, body, and limbs.
Type:
Dataset
Issue Date:
30 May 2018

62. Regional hydroclimatic variability due to contemporary deforestation in southern Amazonia and associated boundary layer characteristics

Author(s):
Khanna, Jaya; Medvigy, David; Fisch, Gilberto; Neves, Theomar Trindade de Araújo Tiburtino
Abstract:
Amazonian deforestation causes systematic changes in regional dry season precipitation. Some of these changes at contemporary large scales (a few hundreds of kilometers) of deforestation have been associated with a ‘dynamical mesoscale circulation’, induced by the replacement of rough forest with smooth pasture. In terms of decadal averages, this dynamical mechanism yields increased precipitation in downwind regions and decreased precipitation in upwind regions of deforested areas. Daily, seasonal, and interannual variations in this phenomenon may exist, but have not yet been identified or explained. This study uses observations and numerical simulations to develop relationships between the dynamical mechanism and the local- and continental-scale atmospheric conditions across a range of time scales. It is found that the strength of the dynamical mechanism is primarily controlled by the regional-scale thermal and dynamical conditions of the boundary layer, and not by the continental- and global-scale atmospheric state. Lifting condensation level and wind speed within the boundary layer have large and positive correlations with the strength of the dynamical mechanism. The strength of these relationships depends on time scale and is strongest over the seasonal cycle. Overall, the dynamical mechanism is found to be strongest during times when the atmosphere is relatively stable. Hence, for contemporary large scales of deforestation this phenomenon is found to be the prevalent convective triggering mechanism during the dry and parts of transition seasons (especially during the dry-to-wet transition), significantly affecting the hydroclimate during this period.
Type:
Dataset and Software
Issue Date:
2018

63. Data for Nature Climate Change article 'Regional dry-season climate changes due to three decades of Amazonian deforestation'

Author(s):
Khanna, Jaya; Medvigy, David; Fueglistaler, Stephan; Walko, Robert
Abstract:
More than 20% Amazon rainforest has been cleared in the past three decades triggering important hydroclimatic changes. Small-scale (~few kilometers) deforestation in the 1980s has caused thermally-triggered atmospheric circulations that increase regional cloudiness and precipitation frequency. However, these circulations are predicted to diminish as deforestation increases. Here we use multi-decadal satellite records and numerical model simulations to show a regime shift in the regional hydroclimate accompanying increasing deforestation in Rondônia, Brazil. Compared to the 1980s, present-day deforested areas in downwind western Rondônia are found to be wetter than upwind eastern deforested areas during the local dry season. The resultant precipitation change in the two regions is approximately ±25% of the deforested area mean. Meso-resolution simulations robustly reproduce this transition when forced with increasing deforestation alone, showing a negligible role of large-scale climate variability. Furthermore, deforestation-induced surface roughness reduction is found to play an essential role in the present-day dry season hydroclimate. Our study illustrates the strong scale-sensitivity of the climatic response to Amazonian deforestation and suggests that deforestation is sufficiently advanced to have caused a shift from a thermally- to a dynamically-driven hydroclimatic regime.
Type:
Dataset and Software
Issue Date:
2017

65. Sherlock Movie Watching Dataset

Author(s):
Chen, Janice
Abstract:
Our daily lives revolve around sharing experiences and memories with others. When different people recount the same events, how similar are their underlying neural representations? In this study, participants viewed a fifty-minute audio-visual movie, then verbally described the events while undergoing functional MRI. These descriptions were completely unguided and highly detailed, lasting for up to forty minutes. As each person spoke, event-specific spatial patterns were reinstated (movie-vs.-recall correlation) in default network, medial temporal, and high-level visual areas; moreover, individual event patterns were highly discriminable and similar between people during recollection (recall-vs.-recall similarity), suggesting the existence of spatially organized memory representations. In posterior medial cortex, medial prefrontal cortex, and angular gyrus, activity patterns during recall were more similar between people than to patterns elicited by the movie, indicating systematic reshaping of percept into memory across individuals. These results reveal striking similarity in how neural activity underlying real-life memories is organized and transformed in the brains of different people as they speak spontaneously about past events.
Type:
Dataset
Issue Date:
26 October 2016

67. Dynamic reconfiguration of the default mode network during narrative comprehension

Author(s):
Simony, Erez; Honey, Christopher; Chen, Janice; Lositsky, Olga; Yeshurun, Yaara; Wiesel, Ami; Hasson, Uri
Abstract:
Does the default mode network (DMN) reconfigure to encode information about the changing environment? This question has proven difficult, because patterns of functional connectivity reflect a mixture of stimulus-induced neural processes, intrinsic neural processes and non-neuronal noise. Here we introduce inter-subject functional correlation (ISFC), which isolates stimulus-dependent inter-regional correlations between brains exposed to the same stimulus. During fMRI, we had subjects listen to a real-life auditory narrative and to temporally scrambled versions of the narrative. We used ISFC to isolate correlation patterns within the DMN that were locked to the processing of each narrative segment and specific to its meaning within the narrative context. The momentary configurations of DMN ISFC were highly replicable across groups. Moreover, DMN coupling strength predicted memory of narrative segments. Thus, ISFC opens new avenues for linking brain network dynamics to stimulus features and behaviour.
Type:
Dataset
Issue Date:
18 July 2016

68. Attentional Modulation of Brain Responses to Primary Appetitive and Aversive Stimuli

Author(s):
Cara L. Buck; Jonathan D. Cohen; Field, Brent; Daniel Kahneman; Samuel M. McClure; Leigh E. Nystrom
Abstract:
Studies of subjective well-being have conventionally relied upon self-report, which directs subjects’ attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure) by using functional magnetic resonance imaging (fMRI) to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly) the activity of brain mechanisms thought to represent hedonic value.
Type:
Dataset, Software, and text
Issue Date:
11 February 2015

69. Basin-Scale Leakage Risks from Geologic Carbon Sequestration: Impact on Carbon Capture and Storage Energy Market Competitiveness

Abstract:
This three-year project, performed by Princeton University in partnership with the University of Minnesota and Brookhaven National Laboratory, examined geologic carbon sequestration in regard to CO2 leakage and potential subsurface liabilities. The research resulted in basin-scale analyses of CO2 and brine leakage in light of uncertainties in the characteristics of leakage processes, and generated frameworks to monetize the risks of leakage interference with competing subsurface resources. The geographic focus was the Michigan sedimentary basin, for which a 3D topographical model was constructed to represent the hydrostratigraphy. Specifically for Ottawa County, a statistical analysis of the hydraulic properties of underlying sedimentary formations was conducted. For plausible scenarios of injection into the Mt. Simon sandstone, leakage rates were estimated and fluxes into shallow drinking-water aquifers were found to be less than natural analogs of CO2 fluxes. We developed the Leakage Impact Valuation (LIV) model in which we identified stakeholders and estimated costs associated with leakage events. It was found that costs could be incurred even in the absence of legal action or other subsurface interference because there are substantial costs of finding and fixing the leak and from injection interruption. We developed a model framework called RISCS, which can be used to predict monetized risk of interference with subsurface resources by combining basin-scale leakage predictions with the LIV method. The project has also developed a cost calculator called the Economic and Policy Drivers Module (EPDM), which comprehensively calculates the costs of carbon sequestration and leakage, and can be used to examine major drivers for subsurface leakage liabilities in relation to specific injection scenarios and leakage events. Finally, we examined the competitiveness of CCS in the energy market. This analysis, though qualitative, shows that financial incentives, such as a carbon tax, are needed for coal combustion with CCS to gain market share. In another part of the project we studied the role of geochemical reactions in affecting the probability of CO2 leakage. A basin-scale simulation tool was modified to account for changes in leakage rates due to permeability alterations, based on simplified mathematical rules for the important geochemical reactions between acidified brines and caprock minerals. In studies of reactive flows in fractured caprocks, we examined the potential for permeability increases, and the extent to which existing reactive transport models would or would not be able to predict it. Using caprock specimens from the Eau Claire and Amherstburg, we found that substantial increases in permeability are possible for caprocks that have significant carbonate content, but minimal alteration is expected otherwise. We also found that while the permeability increase may be substantial, it is much less than what would be predicted from hydrodynamic models based on mechanical aperture alone because the roughness that is generated tends to inhibit flow.
Type:
text
Issue Date:
5 June 2014

70. Bubble pinch-off in turbulence

Abstract:
Experimental data, simulation code, and Python scripts to reproduce the data presented in "Bubble pinch-off in turbulence"
Type:
Dataset and Software