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Accuracy optimized neural networks do not effectively model optic flow tuning in brain area MSTd

Accuracy-optimized convolutional neural networks (CNNs) have emerged as highly effective models at predicting neural responses in brain areas along the primate ventral stream, but it is largely unknown whether they effectively model neurons in the complementary primate dorsal stream. We explored how well CNNs model the optic flow tuning properties of neurons in dorsal area MSTd and we compared our results with the Non-Negative Matrix Factorization (NNMF) model, which successfully models many tuning properties of MSTd neurons. To better understand the role of computational properties in the NNMF model that give rise to optic flow tuning that resembles that of MSTd neurons, we created additional CNN model variants that implement key NNMF constraints – non-negative weights and sparse coding of optic flow. While the CNNs and NNMF models both accurately estimate the observer's self-motion from purely translational or rotational optic flow, NNMF and the CNNs with nonnegative weights yield substantially less accurate estimates than the other CNNs when tested on more complex optic flow that combines observer translation and rotation. Despite its poor accuracy, NNMF gives rise to tuning properties that align more closely with those observed in primate MSTd than any of the accuracy-optimized CNNs. This work offers a step toward a deeper understanding of the computational properties and constraints that describe the optic flow tuning of primate area MSTd.

60 APPLIED LIFE SCIENCES↗

Autoencoding is All You Need (for MSTd)

We explore various neural network task and architectural constraints to find the minimal set that produces network activity similar to that found in primate MSTd. MSTd is a brain region in the dorsal visual pathway associated with self motion estimation from visual motion (i.e. optic flow).

Layton, Oliver W [Colby College]↗

Ultrasonic Measurements of Temperature Profile and Heat Fluxes in Coal-Fired Power Plants (Final Report)

Many industrial processes are inaccessible or inhospitable to characterization by traditional temperature measurement methods, such as thermocouples, especially over prolonged exposure to harsh environments. Ultrasound is an established characterization technology with diverse applications ranging from medical imaging to therapies to flaw detection to nondestructive evaluation. Ultrasound may characterize solid materials and components noninvasively as a nondestructive evaluation modality and obtain internal measurements of material properties. For example, the speed of ultrasound propagation changes with Young’s modulus and Poisson’s ratio, which can be found from its measurements. Traditional ultrasonic characterization assumes all material properties remain constant with the position. When this assumption holds, a property of interest may be measured by relating it to the speed of ultrasound propagation (or a speed of sound, SOS) and measuring the SOS by timing the ultrasound propagation through a known distance. However, when a property of interest is spatially distributed, the propagation time depends on the SOS changing with the position along the ultrasound propagation path. The multiple temperature distributions may lead to an identical time of flight (TOF). Temperature is one property that impacts the speed of ultrasound and often cannot be assumed to remain constant with the position. Previously, in the context of temperature, we addressed the challenge of ultrasonic characterization of spatially distributed properties by developing a method for measuring segmental temperature distributions (MSTD). This method divides the ultrasonic propagation into segments bound by echogenic features. These features provide ultrasonic interfaces where some energy is reflected toward the receiving transducer, and the rest continues through the medium. The time-of-flight between the echoes reflected from echogenic features characterizes the spatial distribution in the properties of interest in the corresponding segment of the ultrasonic propagation path. This project demonstrated the application of the MSTD method in industrial conditions of the coal-fired power plant. We implemented the MSTD using metals and alloys waveguides, which may be the existing structure for which the temperature distribution is characterized or purposefully designed waveguides added to the structure by welding or other means specifically to quantify thermal properties using the MSTD method. Previous iterations of the MSTD method used ceramic and cementitious waveguides, which significantly attenuate ultrasound. On the other hand, low attenuation in metallic waveguides creates interactions between echogenic features which compilates the signal analysis in the segmental TOF measurements. We have established the WG design principles that minimize the interferences between trailing and primary echoes and, in some cases, eliminate them. The waveguides in which echoes do not interfere improve the timing accuracy and the robustness of ultrasonic measurements of the spatial distributions in material properties. Our emphasis remained on the estimation of the temperature distributions. We have developed general recommendations for designing ultrasonically segmented waveguides with the reduced influence of trailing echoes. Two of our waveguide designs were tested in the industry. The first waveguide was designed for insertion into a combustion zone of the utility-scale coal-fired power plant boiler. The second design allows the characterization of temperature distribution in the direction normal to the boiler’s water wall, a large heat exchanger converting the chemical energy released during combustion to the steam driving the electrical power generation turbines. These waveguides were designed to operate within a restrictive space of thermally insulated water wall and incorporate densely located echogenic features while combatting the influence of trailing echoes. The project has successfully demonstrated the feasibility of using the developed method for accurate, continuous, and robust temperature measurements in extreme environments of power generation and other industrial processes. It, therefore, has achieved its overarching goal of advancing the technology readiness level of the novel Ultrasound Measurements of Segmental Temperature Distribution (US-MSTD) method for real-time measurements of the temperature distribution and heat fluxes closer to commercial availability, developing a prototype multipoint measurement system, and validating its performance on coal-fired utility boilers. The success of this project was achieved in collaboration with the power generator, Rocky Mountain Power, and set the stage for the transfer of this technology from the laboratory to the industry.

01 COAL, LIGNITE, AND PEAT↗

Ultrasonic Measurements of Temperature Distribution in Extreme Environments: Results of Power Plant Testing

The most hardened insertion sensors do not perform reliably in extreme environmental conditions. We address this problem by developing an ultrasonic thermometry system for the measurements of segmental temperature distributions (MSTD) in solid materials and, specifically, across containments of energy conversion processes. The MSTD approach uses an echogenically segmented ultrasound propagation path, structured to contain engineered or naturally occurring echogenic features. In pulse-echo mode, these features produce a train of echoes in response to an external pulse of ultrasonic excitation created and acquired by a transducer located outside the extreme environment. The delays between the echoes encode the information on the temperature distribution in the corresponding segments of the ultrasonic propagation path, which we use to reconstruct an unknown temperature profile. This note describes the preliminary results and initial experience in applying the developed MSTD ultrasonic thermometry system to the measurements of temperatures in a utility-scale 500MW coal-fired boiler.

John, Mason↗

Quantitative Simulations of MST Visual Receptive Field Properties Using a Template Model of Heading Estimation

We previously developed a template model of primate visual self-motion processing that proposes a specific set of projections from MT-like local motion sensors onto output units to estimate heading and relative depth from optic flow. At the time, we showed that that the model output units have emergent properties similar to those of MSTd neurons, although there was little physiological evidence to test the model more directly. We have now systematically examined the properties of the model using stimulus paradigms used by others in recent single-unit studies of MST: 1) 2-D bell-shaped heading tuning. Most MSTd neurons and model output units show bell-shaped heading tuning. Furthermore, we found that most model output units and the finely-sampled example neuron in the Duffy-Wurtz study are well fit by a 2D gaussian (sigma approx. 35deg, r approx. 0.9). The bandwidth of model and real units can explain why Lappe et al. found apparent sigmoidal tuning using a restricted range of stimuli (+/-40deg). 2) Spiral Tuning and Invariance. Graziano et al. found that many MST neurons appear tuned to a specific combination of rotation and expansion (spiral flow) and that this tuning changes little for approx. 10deg shifts in stimulus placement. Simulations of model output units under the same conditions quantitatively replicate this result. We conclude that a template architecture may underlie MT inputs to MST.

Stone, Leland S.↗