scholarly journals Facilitation of neural responses to targets moving in three-dimensional optic flow

2020 ◽  
Author(s):  
Sarah Nicholas ◽  
Karin Nordström
Keyword(s):  
Biological Sciences ◽  
Opposite Direction ◽  
Optic Flow ◽  
Three Dimensional ◽  
Target Motion ◽  
Human Observer ◽  
Spatio Temporal ◽  
Small Targets ◽  
Target Pursuit ◽  
Temporal Profiles

AbstractFor the human observer, it can be difficult to follow the motion of small objects, especially when they move against background clutter. However, insects efficiently do this, as evidenced by their ability to capture prey, pursue conspecifics, or defend territories, even in highly textured surrounds. This behavior has been attributed to optic lobe neurons that are sharply tuned to the motion of small targets, as these neurons respond robustly even to a target moving against background motion. However, the target selective descending neurons (TSDNs), that more directly control behavioral output, do not. Importantly, though, the backgrounds used previously not only lacked 3D motion cues, but also high-contrast features, both of which would be encountered during natural behaviors. To redress this deficiency, we here use backgrounds consisting of many targets moving coherently to simulate the type of 3D optic flow that would be generated by an insect’s own motion through the world. We show that hoverfly TSDNs do not respond to this type of optic flow, even though it contains features with spatio-temporal profiles similar to optimal targets. However, TSDN responses are inhibited when this optic flow is shown together with a target. More surprisingly, TSDNs are facilitated by horizontal, frontal optic flow in the opposite direction to target motion. We show that these interactions are likely inherited from the pre-synaptic neurons, and argue that the facilitation could benefit the initiation of target pursuit.Significance statementTarget detection in visual clutter is a difficult computational task that insects, with their poor resolution compound eyes and small brains, do successfully and with extremely short behavioral delays. We here show that target neurons do not respond to widefield motion consisting of a multitude of “targets”, suggesting that the hoverfly visual system interprets coherent widefield motion differently from the motion of individual targets. In addition, we show that widefield motion in the opposite direction to target motion increases the neural response. This is an incredibly non-intuitive finding, and difficult to reconcile with current models for target selectivity, but has behavioral relevance.ClassificationBiological sciences: Neuroscience

scholarly journals Facilitation of neural responses to targets moving against optic flow

2021 ◽  
Vol 118 (38) ◽  
pp. e2024966118
Author(s):  
Sarah Nicholas ◽  
Karin Nordström
Keyword(s):  
Optic Flow ◽  
Target Motion ◽  
Human Observer ◽  
Neural Responses ◽  
Response Facilitation ◽  
Descending Neurons ◽  
The World ◽  
Background Clutter ◽  
Spatial Window ◽  
Target Pursuit

For the human observer, it can be difficult to follow the motion of small objects, especially when they move against background clutter. In contrast, insects efficiently do this, as evidenced by their ability to capture prey, pursue conspecifics, or defend territories, even in highly textured surrounds. We here recorded from target selective descending neurons (TSDNs), which likely subserve these impressive behaviors. To simulate the type of optic flow that would be generated by the pursuer’s own movements through the world, we used the motion of a perspective corrected sparse dot field. We show that hoverfly TSDN responses to target motion are suppressed when such optic flow moves syn-directional to the target. Indeed, neural responses are strongly suppressed when targets move over either translational sideslip or rotational yaw. More strikingly, we show that TSDNs are facilitated by optic flow moving counterdirectional to the target, if the target moves horizontally. Furthermore, we show that a small, frontal spatial window of optic flow is enough to fully facilitate or suppress TSDN responses to target motion. We argue that such TSDN response facilitation could be beneficial in modulating corrective turns during target pursuit.

scholarly journals Design of bio-inspired binocular UAV detection system based on improved STC algorithm of scale transformation and occlusion detection

2021 ◽  
Vol 13 ◽  
pp. 175682932110048
Author(s):  
Huajun Song ◽  
Yanqi Wu ◽  
Guangbing Zhou
Keyword(s):  
Detection System ◽  
Rapid Development ◽  
Reference Value ◽  
Scale Transformation ◽  
Hardware System ◽  
Time Requirements ◽  
Aerial Vehicle ◽  
Spatio Temporal ◽  
Small Targets ◽  
Vision Detection

With the rapid development of drones, many problems have arisen, such as invasion of privacy and endangering security. Inspired by biology, in order to achieve effective detection and robust tracking of small targets such as unmanned aerial vehicles, a binocular vision detection system is designed. The system is composed of long focus and wide-angle dual cameras, servo pan tilt, and dual processors for detecting and identifying targets. In view of the shortcomings of spatio-temporal context target tracking algorithm that cannot adapt to scale transformation and easy to track failure in complex scenes, the scale filter and loss criterion are introduced to make an improvement. Qualitative and quantitative experiments show that the designed system can adapt to the scale changes and partial occlusion conditions in the detection, and meets the real-time requirements. The hardware system and algorithm both have reference value for the application of anti-unmanned aerial vehicle systems.

scholarly journals SPATIO-TEMPORAL DATA ANALYSIS WITH NON-LINEAR FILTERS: BRAIN MAPPING WITH fMRI DATA

2011 ◽  
Vol 19 (3) ◽  
pp. 189
Author(s):  
Karsten Rodenacker ◽  
Klaus Hahn ◽  
Gerhard Winkler ◽  
Dorothea P Auer
Keyword(s):  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Digital Data ◽  
Linear Filters ◽  
Brain Functions ◽  
Non Linear ◽  
Long Time ◽  
Spatio Temporal ◽  
Sensory Activation ◽  
Temporal Data Analysis

Spatio-temporal digital data from fMRI (functional Magnetic Resonance Imaging) are used to analyse and to model brain activation. To map brain functions, a well-defined sensory activation is offered to a test person and the hemodynamic response to neuronal activity is studied. This so-called BOLD effect in fMRI is typically small and characterised by a very low signal to noise ratio. Hence the activation is repeated and the three dimensional signal (multi-slice 2D) is gathered during relatively long time ranges (3-5 min). From the noisy and distorted spatio-temporal signal the expected response has to be filtered out. Presented methods of spatio-temporal signal processing base on non-linear concepts of data reconstruction and filters of mathematical morphology (e.g. alternating sequential morphological filters). Filters applied are compared by classifications of activations.

scholarly journals Unsupervised video object segmentation: An affinity and edge learning approach.

2021 ◽  
Author(s):  
Sundaram Muthu ◽  
Ruwan Tennakoon ◽  
Reza Hoseinnezhad ◽  
Alireza Bab-Hadiashar
Keyword(s):  
Optic Flow ◽  
Object Segmentation ◽  
Video Object Segmentation ◽  
Video Object ◽  
Post Processing ◽  
Multiple Objects ◽  
Temporal Features ◽  
Image Edge ◽  
Spatio Temporal ◽  
Generalization Errors

<div>This paper presents a new approach to solve unsupervised video object segmentation~(UVOS) problem (called TMNet). The UVOS is still a challenging problem as prior methods suffer from issues like generalization errors to segment multiple objects in unseen test videos (category agnostic), over reliance on inaccurate optic flow, and problem towards capturing fine details at object boundaries. These issues make the UVOS, particularly in presence of multiple objects, an ill-defined problem. Our focus is to constrain the problem and improve the segmentation results by inclusion of multiple available cues such as appearance, motion, image edge, flow edge and tracking information through neural attention. To solve the challenging category agnostic multiple object UVOS, our model is designed to predict neighbourhood affinities for being part of the same object and cluster those to obtain accurate segmentation. To achieve multi cue based neural attention, we designed a Temporal Motion Attention module, as part of our segmentation framework, to learn the spatio-temporal features. To refine and improve the accuracy of object segmentation boundaries, an edge refinement module (using image and optic flow edges) and a geometry based loss function are incorporated. The overall framework is capable of segmenting and finding accurate objects' boundaries without any heuristic post processing. This enables the method to be used for unseen videos. Experimental results on challenging DAVIS16 and multi object DAVIS17 datasets shows that our proposed TMNet performs favourably compared to the state-of-the-art methods without post processing.</div>

scholarly journals PROTEIN TEACHING: AN APPROACH FOR TEACHER TRAINING APPLIED TO STUDENTS OF THE BIOLOGICAL SCIENCES COURSE AT UFRN

2015 ◽  
Vol 13 ◽  
pp. 34
Author(s):  
J. K.S. NASCIMENTO et al
Keyword(s):  
Biological Sciences ◽  
Teaching Practice ◽  
Basic Education ◽  
New Technologies ◽  
Lesson Plan ◽  
Three Dimensional ◽  
Structural Features ◽  
Dimensional Structure ◽  
Educational Models ◽  
Teaching Learning

Teaching biochemistry in higher education is increasingly becoming a challenge. It is notoriously difficult for students to assimilate the topic; in addition there are many complaints about the complexity of subjects and a lack of integration with the day-to-day. A recurrent problem in undergraduate courses is the absence of teaching practice in specific disciplines. This work aimed to stimulate students in the biological sciences course who were enrolled in the discipline of MOLECULAR DIVERSITY (MD), to create hypothetical classes focused on basic education highlighting the proteins topic. The methodology was applied in a class that contained 35 students. Seven groups were formed, and each group chose a protein to be used as a source of study for elementary school classes. A lesson plan was created focusing on the methodology that the group would use to manage a class. The class was to be presented orally. Students were induced to be creative and incorporate a teacher figure, and to propose teaching methodologies for research using the CTS approach (Science, Technology and Society). Each group presented a three-dimensional structure of the protein they had chosen, explained their structural features and functions and how they would develop the theme for a class of basic education, and what kind of methodology they would use for this purpose. At the end of the presentations, a questionnaire was given to students in order to evaluate the effectiveness of the methodology in the teaching-learning process. The activity improved the teacher’s training and developed skills and abilities, such as creativity, didactical planning, teaching ability, development of educational models and the use of new technologies. The methodology used in this work was extremely important to the training of future teachers, who were able to better understand the content covered in the discipline and relate it to day-to-day life.

scholarly journals Spatio-Temporal Dynamics of Impulse Responses to Figure Motion in Optic Flow Neurons

PLoS ONE ◽  
2015 ◽  
Vol 10 (5) ◽  
pp. e0126265 ◽  
Author(s):  
Yu-Jen Lee ◽  
H. Olof Jönsson ◽  
Karin Nordström
Keyword(s):  
Optic Flow ◽  
Temporal Dynamics ◽  
Impulse Responses ◽  
Spatio Temporal

Unsteady Hemodynamics in Intracranial Aneurysms With Varying Dome Orientations

2021 ◽  
Vol 143 (6) ◽  
Author(s):  
Abdullah Y. Usmani ◽  
K. Muralidhar
Keyword(s):  
Intracranial Aneurysm ◽  
Three Dimensional ◽  
Parent Artery ◽  
Fluid Loading ◽  
Image Velocimetry ◽  
Flow Reynolds Number ◽  
Fatal Hemorrhage ◽  
Wall Loading ◽  
Spatio Temporal ◽  
Finite Volume Simulation

Abstract Fluid loading within an intracranial aneurysm is difficult to measure but can be related to the shape of the flow passage. The outcome of excessive loading is a fatal hemorrhage, making it necessary for early diagnosis. However, arterial diseases are asymptomatic and clinical assessment is a challenge. A realistic approach to examining the severity of wall loading is from the morphology of the aneurysm itself. Accordingly, this study compares pulsatile flow (Reynolds number Re = 426, Womersley number Wo = 4.7) in three different intracranial aneurysm geometries. Specifically, the spatio-temporal movement of vortices is followed in high aspect ratio aneurysm models whose domes are inclined along with angles of 0, 45, and 90 deg relative to the plane of the parent artery. The study is based on finite volume simulation of unsteady three-dimensional flow while a limited set of particle image velocimetry experiments have been carried out. Within a pulsatile cycle, an increase in inclination (0–90 deg) is seen to shift the point of impingement from the distal end toward the aneurysmal apex. This change in flow pattern strengthens helicity, drifts vortex cores, enhances spatial displacement of the vortex, and generates skewed Dean's vortices on transverse planes. Patches of wall shear stress and wall pressure shift spatially from the distal end in models of low inclination (0–45 deg) and circumscribe the aneurysmal wall for an inclination angle of 90 deg. Accordingly, it is concluded that high angles of inclination increase rupture risks while lower inclinations are comparatively safe.

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