Influence of Spatial Information on Responses of Tonically Active Neurons in the Monkey Striatum

2006 ◽  
Vol 95 (5) ◽  
pp. 2975-2986 ◽  
Author(s):  
Sabrina Ravel ◽  
Pierangelo Sardo ◽  
Eric Legallet ◽  
Paul Apicella

Previous studies have demonstrated that tonically active neurons (TANs) in the primate striatum play an important role in the detection of rewarding events. However, the influence of the spatial features of stimuli or actions required to obtain reward remains unclear. Here, we examined the activity of TANs in the striatum of monkeys trained to make spatially directed movements elicited by visual stimuli presented ipsilaterally or contralaterally to the moving arm. Among 181 neurons responding to the trigger stimulus, 127 (70%) were nonselective for stimulus location and 54 (30%) responded to only one location of the stimulus. Most of the selective responses (63%) occurred when the stimulus was presented contralaterally to the moving arm. To examine whether TAN responses are related to the location of the stimulus or to the direction of the movement, we tested a subset of the trigger-responsive neurons ( n = 44) in a condition that elicited reaching toward or away from the stimulus. By comparing TAN activity between the two conditions, we found that half of the responses can be interpreted as being related to the location of the stimulus, one quarter to the direction of movement, and one quarter to the context in which stimulus–movement combination occurs. These results demonstrate that TANs are not limited to motivational processing, but may play a role in the processing of spatial attributes of stimulus and/or movement as well. These response properties suggest that TANs are involved in the flexible shifting of motor responses during spatially directed behavior.

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 708
Author(s):  
Wenbo Liu ◽  
Fei Yan ◽  
Jiyong Zhang ◽  
Tao Deng

The quality of detected lane lines has a great influence on the driving decisions of unmanned vehicles. However, during the process of unmanned vehicle driving, the changes in the driving scene cause much trouble for lane detection algorithms. The unclear and occluded lane lines cannot be clearly detected by most existing lane detection models in many complex driving scenes, such as crowded scene, poor light condition, etc. In view of this, we propose a robust lane detection model using vertical spatial features and contextual driving information in complex driving scenes. The more effective use of contextual information and vertical spatial features enables the proposed model more robust detect unclear and occluded lane lines by two designed blocks: feature merging block and information exchange block. The feature merging block can provide increased contextual information to pass to the subsequent network, which enables the network to learn more feature details to help detect unclear lane lines. The information exchange block is a novel block that combines the advantages of spatial convolution and dilated convolution to enhance the process of information transfer between pixels. The addition of spatial information allows the network to better detect occluded lane lines. Experimental results show that our proposed model can detect lane lines more robustly and precisely than state-of-the-art models in a variety of complex driving scenarios.


1996 ◽  
Vol 76 (3) ◽  
pp. 1439-1456 ◽  
Author(s):  
P. Mazzoni ◽  
R. M. Bracewell ◽  
S. Barash ◽  
R. A. Andersen

1. The lateral intraparietal area (area LIP) of the monkey's posterior parietal cortex (PPC) contains neurons that are active during saccadic eye movements. These neurons' activity includes visual and saccade-related components. These responses are spatially tuned and the location of a neuron's visual receptive field (RF) relative to the fovea generally overlaps its preferred saccade amplitude and direction (i.e., its motor field, MF). When a delay is imposed between the presentation of a visual stimulus and a saccade made to its location (memory saccade task), many LIP neurons maintain elevated activity during the delay (memory activity, M), which appears to encode the metrics of the next intended saccadic eye movements. Recent studies have alternatively suggested that LIP neurons encode the locations of visual stimuli regardless of where the animal intends to look. We examined whether the M activity of LIP neurons specifically encodes movement intention or the locations of recent visual stimuli, or a combination of both. In the accompanying study, we investigated whether the intended-movement activity reflects changes in motor plan. 2. We trained monkeys (Macaca mulatta) to memorize the locations of two visual stimuli and plan a sequence of two saccades, one to each remembered target, as we recorded the activity of single LIP neurons. Two targets were flashed briefly while the monkey maintained fixation; after a delay the fixation point was extinguished, and the monkey made two saccades in sequence to each target's remembered location, in the order in which the targets were presented. This "delayed double saccade" (DDS) paradigm allowed us to dissociate the location of visual stimulation from the direction of the planned saccade and thus distinguish neuronal activity related to the target's location from activity related to the saccade plan. By imposing a delay, we eliminated the confounding effect of any phasic responses coincident with the appearance of the stimulus and with the saccade. 3. We arranged the two visual stimuli so that in one set of conditions at least the first one was in the neuron's visual RF, and thus the first saccade was in the neuron's motor field (MF). M activity should be high in these conditions according to both the sensory memory and motor plan hypotheses. In another set of conditions, the second stimulus appeared in the RF but the first one was presented outside the RF, instructing the monkey to plan the first saccade away from the neuron's MF. If the M activity encodes the motor plan, it should be low in these conditions, reflecting the plan for the first saccade (away from the MF). If it is a sensory trace of the stimulus' location, it should be high, reflecting stimulation of the RF by the second target. 4. We tested 49 LIP neurons (in 3 hemispheres of 2 monkeys) with M activity on the DDS task. Of these, 38 (77%) had M activity related to the next intended saccade. They were active in the delay period, as expected, if the first saccade was in their preferred direction. They were less active or silent if the next saccade was not in their preferred direction, even when the second stimulus appeared in their RF. 5. The M activity of 8 (16%) of the remaining neurons specifically encoded the location of the most recent visual stimulus. Their firing rate during the delay reflected stimulation of the RF independently of the saccade being planned. The remaining 3 neurons had M activity that did not consistently encode either the next saccade or the stimulus' location. 6. We also recorded the activity of a subset of neurons (n = 38) in a condition in which no stimulus appeared in a neuron's RF, but the second saccade was in the neuron's MF. In this case the majority of neurons tested (23/38, 60%) became active in the period between the first and second saccade, even if neither stimulus had appeared in their RF. Moreover, this activity appeared only after the first saccade had started in all but two of


1984 ◽  
Vol 52 (3) ◽  
pp. 488-513 ◽  
Author(s):  
D. J. Felleman ◽  
J. H. Kaas

Response properties of single neurons in the middle temporal visual area (MT) of anesthetized owl monkeys were determined and quantified for flashed and moving bars of light under computer control for position, orientation, direction of movement, and speed. Receptive-field sizes, ranging from 4 to 25 degrees in width, were considerably larger than receptive fields with corresponding eccentricities in the striate cortex. Neurons were highly binocular with most cells equally or nearly equally activated by either eye. Neurons varied in selectivity for axis and direction of moving bars. Some neurons demonstrated little or no selectivity, others were bidirectional on a single axis, while the largest group was highly selective for direction with little or no response to bar movement opposite to the preferred direction. Over 70% of neurons were classified as highly selective and 90% showed some preference for direction and/or axis of stimulus movement. Neurons typically responded to bar movement only over a restricted range of velocities. The majority of neurons responded best to a particular velocity within the 5-60 degrees/s range, with marked attenuation of the response for velocities greater or less than the preferred. Some neurons failed to show significant response attenuation even at the lowest tested velocity, while other neurons preferred velocities of 100 degrees/s or more and failed to attenuate to the highest velocities. Response magnitude varied with stimulus dimensions. Increasing the length of the moving bar typically increased the magnitude of the response slightly until the stimulus exceeded the receptive-field borders. Other neurons responded less to increases in bar length within the excitatory receptive field. Neurons preferred narrow bars less than 1 degree in width, and marked reductions in responses characteristically occurred with wider stimuli. Moving patterns of randomly placed small dots were often as effective as or more effective than single bars in activating neurons. Selectivity for direction of movement remained for the dot pattern. for the dot pattern. Poststimulus time (PST) histograms of responses to bars flashed at a series of 21 different positions across the receptive field, in the "response-plane" format, indicated a spatially and temporally homogeneous receptive-field structure for nearly all neurons. Cells characteristically showed transient excitation at both stimulus onset and offset for all effective stimulus locations. Some cells responded mainly at bright stimulus onset or offset.


2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Ruru Shen ◽  
Haowen Yan ◽  
Qinke Sun ◽  
Xiaojun Li

<p><strong>Abstract.</strong> The spatial distribution of geotagged photos is a projection of the tourist's tourism activities in the geospatial space, which contains spatial attributes and interrelationships of tourists’ activities. Using the Flickr photo sharing website, the paper utilizes new data mining technologies to discover and capture the metadata of geotagged photos uploaded by visitors from January 2008 to October 2018 in the upper reach of the Yellow River in China. The spatial information processing and expression of the collected data are processed and the characteristics of the inbound tourists’ behavior are explored by the P-DBSCAN, the path tracking technology and the UCINET network analysis. The main results are as follows: (1) By using the P-DBSCAN cluster analysis, the area of interest (AOI) has a feature of high agglomeration and forms a “V” shaped in the Xining-Lanzhou-Yinchuan area. The concentration of AOIs is closely related to the urban functional area and has a clear Urban functional orientation. (2) Using tracking analysis, the paper reveals single node trajectory, intraregional path trajectory and interregional path trajectory. Among them, 68.42% visitors chose single node trajectory, 9.78% visitors chose intraregional path trajectory and 21.80% tourists chose interregional path trajectory. (3) Ten cross-regional tourism mainstream lines are picked by the UCINET network analysis mode. It has been found that the tourists tend to visit those famous scenic spots (points) such as the Qinghai Lake, the YaDan Geological Park, the ‘Danxia’ Landform, the Zhenbeibu China West Film Studio. It is apparent that the Gansu-Qinghai Great Circle Tour is a hot tourist route that tourists are keen to choose. The research results have certain reference significance for improving the transformation and upgrading of tourism industry in the upper reach of the Yellow River.</p>


1995 ◽  
Vol 04 (04) ◽  
pp. 489-500 ◽  
Author(s):  
NAOHIRO ISHII ◽  
KEN-ICHI NAKA

Asymmetrical neural networks are shown in the biological neural network as the catfish retina. Horizontal and bipolar cell responses are linearly related to the input modulation of light, while amacrine cells work linearly and nonlinearly in their responses. These cells make asymmetrical neural networks in the retina. Several mechanisms have been proposed for the detection of motion in biological system. To make clear the difference among asymmetrical networks, we applied non-linear analysis developed by N. Wiener. Then, we can derive α-equation of movement, which shows the direction of movement. During the movement, we also can derive the movement equation, which implies that the movement holds regardless of the parameter α. By analyzing the biological asymmetric neural networks, it is shown that the asymmetric networks are excellent in the ability of spatial information processing on the retinal level. Then, the symmetric network was discussed by applying the non-linear analysis. In the symmetric neural network, it was suggested that memory function is needed to perceive the movement.


2018 ◽  
Vol 8 (2) ◽  
pp. 20170039 ◽  
Author(s):  
Zhan Li ◽  
Michael Schaefer ◽  
Alan Strahler ◽  
Crystal Schaaf ◽  
David Jupp

The Dual-Wavelength Echidna Lidar (DWEL), a full waveform terrestrial laser scanner (TLS), has been used to scan a variety of forested and agricultural environments. From these scanning campaigns, we summarize the benefits and challenges given by DWEL's novel coaxial dual-wavelength scanning technology, particularly for the three-dimensional (3D) classification of vegetation elements. Simultaneous scanning at both 1064 nm and 1548 nm by DWEL instruments provides a new spectral dimension to TLS data that joins the 3D spatial dimension of lidar as an information source. Our point cloud classification algorithm explores the utilization of both spectral and spatial attributes of individual points from DWEL scans and highlights the strengths and weaknesses of each attribute domain. The spectral and spatial attributes for vegetation element classification each perform better in different parts of vegetation (canopy interior, fine branches, coarse trunks, etc.) and under different vegetation conditions (dead or live, leaf-on or leaf-off, water content, etc.). These environmental characteristics of vegetation, convolved with the lidar instrument specifications and lidar data quality, result in the actual capabilities of spectral and spatial attributes to classify vegetation elements in 3D space. The spectral and spatial information domains thus complement each other in the classification process. The joint use of both not only enhances the classification accuracy but also reduces its variance across the multiple vegetation types we have examined, highlighting the value of the DWEL as a new source of 3D spectral information. Wider deployment of the DWEL instruments is in practice currently held back by challenges in instrument development and the demands of data processing required by coaxial dual- or multi-wavelength scanning. But the simultaneous 3D acquisition of both spectral and spatial features, offered by new multispectral scanning instruments such as the DWEL, opens doors to study biophysical and biochemical properties of forested and agricultural ecosystems at more detailed scales.


2020 ◽  
Vol 39 (3) ◽  
pp. 3769-3781
Author(s):  
Zhisong Han ◽  
Yaling Liang ◽  
Zengqun Chen ◽  
Zhiheng Zhou

Video-based person re-identification aims to match videos of pedestrians captured by non-overlapping cameras. Video provides spatial information and temporal information. However, most existing methods do not combine these two types of information well and ignore that they are of different importance in most cases. To address the above issues, we propose a two-stream network with a joint distance metric for measuring the similarity of two videos. The proposed two-stream network has several appealing properties. First, the spatial stream focuses on multiple parts of a person and outputs robust local spatial features. Second, a lightweight and effective temporal information extraction block is introduced in video-based person re-identification. In the inference stage, the distance of two videos is measured by the weighted sum of spatial distance and temporal distance. We conduct extensive experiments on four public datasets, i.e., MARS, PRID2011, iLIDS-VID and DukeMTMC-VideoReID to show that our proposed approach outperforms existing methods in video-based person re-ID.


2020 ◽  
Vol 16 (3) ◽  
pp. 146-167
Author(s):  
Kanokwan Malang ◽  
Shuliang Wang ◽  
Yuanyuan Lv ◽  
Aniwat Phaphuangwittayakul

Skeleton network extraction has been adopted unevenly in transportation networks whose nodes are always represented as spatial units. In this article, the TPks skeleton network extraction method is proposed and applied to bicycle sharing networks. The method aims to reduce the network size while preserving key topologies and spatial features. The authors quantified the importance of nodes by an improved topology potential algorithm. The spatial clustering allows to detect high traffic concentrations and allocate the nodes of each cluster according to their spatial distribution. Then, the skeleton network is constructed by aggregating the most important indicated skeleton nodes. The authors examine the skeleton network characteristics and different spatial information using the original networks as a benchmark. The results show that the skeleton networks can preserve the topological and spatial information similar to the original networks while reducing their size and complexity.


1994 ◽  
Vol 71 (3) ◽  
pp. 1281-1284 ◽  
Author(s):  
D. J. Crammond ◽  
J. F. Kalaska

1. Neuronal activity was recorded in the dorsal premotor cortex (PMd) of two monkeys performing a multidirectional, instructed-delay (ID) reaching task in which visuospatial cues signaled the direction of movement either congruent with the instruction cue ("direct-delay" trials, DD) or redirected 180 degrees opposite to the cue ("redirected-delay" trials, RD). Therefore, this task had two degrees of stimulus-response (S-R) compatibility because in one-half of the trials the spatial attributes of the visual cue were incongruent with those of the intended movement. 2. The majority of PMd cells discharged both at short latency to the RD or DD cues and subsequently with sustained activity during the remaining ID period (IDP). The earliest responses (< 250 ms) in both DD and RD trials covaried with cue location and so could be either a "visuospatial" response or a neuronal correlate of the selection of action with highest S-R compatibility, namely move to the stimulus. In contrast, later IDP activity usually covaried with the direction of movement signaled by the cues, independent of their spatial location, supporting the hypothesis that IDP discharge in PMd ultimately encodes attributes of intended reaching movements.


1976 ◽  
Vol 43 (3) ◽  
pp. 756-758
Author(s):  
William H. Ton

The primary goal of this research was to study errors in stadimetric estimation. Earlier workers had hypothesized that differences in angular velocity of stimuli associated with direction of movement resulted in differences in error between incoming and outgoing stimuli. Therefore, an experiment was performed which investigated differences in range estimation error as a function of three rates of movement. The results for 6 observers showed that errors were consistent regardless of rate of movement.


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