Accurately perceiving the velocity of an object during smooth pursuit is a complex challenge: although the object is moving in the world, it is almost still on the retina. Yet we can perceive the veridical motion of a visual stimulus in such conditions, suggesting a nonretinal representation of the motion vector. To explore this issue, we studied the frames of representation of the motion vector by evoking the well known motion aftereffect during smooth-pursuit eye movements (SPEM). In the retinotopic configuration, due to an accompanying smooth pursuit, a stationary adapting random-dot stimulus was actually moving on the retina. Motion adaptation could therefore only result from motion in retinal coordinates. In contrast, in the spatiotopic configuration, the adapting stimulus moved on the screen but was practically stationary on the retina due to a matched SPEM. Hence, adaptation here would suggest a representation of the motion vector in spatiotopic coordinates. We found that exposure to spatiotopic motion led to significant adaptation. Moreover, the degree of adaptation in that condition was greater than the adaptation induced by viewing a random-dot stimulus that moved only on the retina. Finally, pursuit of the same target, without a random-dot array background, yielded no adaptation. Thus, in our experimental conditions, adaptation is not induced by the SPEM per se. Our results suggest that motion computation is likely to occur in parallel in two distinct representations: a low-level, retinal-motion dependent mechanism and a high-level representation, in which the veridical motion is computed through integration of information from other sources.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1167/12.6.30 | DOI Listing |
[This corrects the article DOI: 10.1371/journal.pone.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Institute of Communications Engineering, National Yang Ming Chiao Tung University, Hsinchu 30010, Taiwan.
A core dielectric cylindrical rod wrapped in a dielectric circular pipe whose outer surface is enclosed by a helical conducting strip grating that is skewed along the axial direction is herein analyzed using the asymptotic strip boundary conditions along with classical vector potential analysis. Targeted for use as a cylindrical holographic antenna, the resultant field solutions facilitate the aperture integration of the equivalent cylindrical surface currents to obtain the radiated far fields. As each rod section of a certain skew angle exhibits a distinct modal attribute; this topology allows for the distribution of the cylindrical surface impedance via the effective refractive index to be modulated, as in gradient-index (GRIN) materials.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Instrument Science & Engineering, Southeast University, Nanjing 210096, China.
To solve the problem of slow convergence seen in the traditional fine alignment algorithm based on linear Kalman filtering, a forward-forward backtracking fine alignment algorithm for SINS is proposed after reanalyzing the fine alignment model in this paper. First, the forward-forward backtracking fine alignment model in initial navigation frame was derived. The displacement vector of the carrier in the initial navigation frame solved by GNSS positioning was utilized as the observation of the fine alignment model.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical and Computer Engineering, Hawassa University, Hawassa 05, Ethiopia.
Understanding human behavior and human action recognition are both essential components of effective surveillance video analysis for the purpose of guaranteeing public safety. However, existing approaches such as three-dimensional convolutional neural networks (3D CNN) and two-stream neural networks (2SNN) have computational hurdles due to the significant parameterization they require. In this paper, we offer HARNet, a specialized lightweight residual 3D CNN that is built on directed acyclic graphs and was created expressly to handle these issues and achieve effective human action detection.
View Article and Find Full Text PDFGait Posture
December 2024
Marquette University, 1250 W. Wisconsin Ave, Milwaukee, WI 53233, United States; Shriners Children's Chicago, 2211 N. Oak Park Ave, Chicago, IL 60707, United States.
Background: Understanding midfoot joint kinetics is valuable for improved treatment of foot pathologies. Segmental foot kinetics cannot currently be obtained in a standard gait lab without the use of multiple force plates or a pedobarographic plate overlaid with a force plate due to the single ground reaction force (GRF) vector.
Research Question: Can an algorithm be created to distribute the GRF into multiple segmental vectors that will allow for calculation of accurate midfoot and ankle moments?
Methods: 20 pediatric subjects (10 typically developing, 10 with foot pathology) underwent multi-segment foot gait analysis using the Milwaukee Foot Model.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!