Visual stimulus-seeking in dark-reared kittens

1976 ◽  
Author(s):  
P. C. Dodwell ◽  
B. N. Timney ◽  
V. F. Emerson
Keyword(s):  
Visual Stimulus

VISUAL STIMULUS REDINTEGRATION IN THE CHIMPANZEE.

1966 ◽  
Author(s):  
DONALD N. FARRER ◽  
JIM MILNER
Keyword(s):  
Visual Stimulus

Gaze and Postural Coupling to Visual Stimulus Oscillations of Complex Motion Organization

2012 ◽  
Author(s):  
Joshua Haworth ◽  
Nathaniel Hunt ◽  
Yawen Yu ◽  
Nicholas Stergiou
Keyword(s):  
Visual Stimulus ◽  
Complex Motion

scholarly journals Visual stimulus complexity and food vs. food alone as rewards for rats

1965 ◽  
Vol 3 (1-12) ◽  
pp. 403-404 ◽  
Author(s):  
R. B. May ◽  
K. L. Beauchamp ◽  
S. Pollock
Keyword(s):  
Visual Stimulus ◽  
Stimulus Complexity

Activity of single neurons in the monkey amygdala during performance of a visual discrimination task

1992 ◽  
Vol 67 (6) ◽  
pp. 1447-1463 ◽  
Author(s):  
K. Nakamura ◽  
A. Mikami ◽  
K. Kubota
Keyword(s):  
Visual Stimulus ◽  
Visual Discrimination ◽  
Discrimination Task ◽  
Discharge Rate ◽  
Visual Stimuli ◽  
Delay Period ◽  
Visual Discrimination Task ◽  
Single Neurons ◽  
Visual Neurons ◽  
Human Faces

1. The activity of single neurons was recorded extracellularly from the monkey amygdala while monkeys performed a visual discrimination task. The monkeys were trained to remember a visual stimulus during a delay period (0.5-3.0 s), to discriminate a new visual stimulus from the stimulus, and to release a lever when the new stimulus was presented. Colored photographs (human faces, monkeys, foods, and nonfood objects) or computer-generated two-dimensional shapes (a yellow triangle, a red circle, etc.) were used as visual stimuli. 2. The activity of 160 task-related neurons was studied. Of these, 144 (90%) responded to visual stimuli, 13 (8%) showed firing during the delay period, and 9 (6%) responded to the reward. 3. Task-related neurons were categorized according to the way in which various stimuli activated the neurons. First, to evaluate the proportion of all tested stimuli that elicited changes in activity of a neuron, selectivity index 1 (SI1) was employed. Second, to evaluate the ability of a neuron to discriminate a stimulus from another stimulus, SI2 was employed. On the basis of the calculated values of SI1 and SI2, neurons were classified as selective and nonselective. Most visual neurons were categorized as selective (131/144), and a few were characterized as nonselective (13/144). Neurons active during the delay period were also categorized as selective visual and delay neurons (6/13) and as nonselective delay neurons (7/13). 4. Responses of selective visual neurons had various temporal and stimulus-selective properties. Latencies ranged widely from 60 to 300 ms. Response durations also ranged widely from 20 to 870 ms. When the natures of the various effective stimuli were studied for each neuron, one-fourth of the responses of these neurons were considered to reflect some categorical aspect of the stimuli, such as human, monkey, food, or nonfood object. Furthermore, the responses of some neurons apparently reflected a certain behavioral significance of the stimuli that was separate from the task, such as the face of a particular person, smiling human faces, etc. 5. Nonselective visual neurons responded to a visual stimulus, regardless of its nature. They also responded in the absence of a visual stimulus when the monkey anticipated the appearance of the next stimulus. 6. Selective visual and delay neurons fired in response to particular stimuli and throughout the subsequent delay periods. Nonselective delay neurons increased their discharge rates gradually during the delay period, and the discharge rate decreased after the next stimulus was presented. 7. Task-related neurons were identified in six histologically distinct nuclei of the amygdala.(ABSTRACT TRUNCATED AT 400 WORDS)

Receiver operating characteristic (ROC) analysis of neurons in the cat's lateral geniculate nucleus during tonic and burst response mode

1995 ◽  
Vol 12 (4) ◽  
pp. 723-741 ◽  
Author(s):  
W. Guido ◽  
S.-M. Lu ◽  
J.W. Vaughan ◽  
Dwayne W. Godwin ◽  
S. Murray Sherman
Keyword(s):  
Visual Stimulus ◽  
Action Potentials ◽  
Operating Characteristic ◽  
Visual Stimuli ◽  
Roc Curves ◽  
Response Mode ◽  
Burst Mode ◽  
Low Threshold Spike ◽  
Low Threshold ◽  
Roc Area

AbstractRelay cells of the lateral geniculate nucleus respond to visual stimuli in one of two modes: burst and tonic. The burst mode depends on the activation of a voltage-dependent, Ca2+ conductance underlying the low threshold spike. This conductance is inactivated at depolarized membrane potentials, but when activated from hyperpolarized levels, it leads to a large, triangular, nearly all-or-none depolarization. Typically, riding its crest is a high-frequency barrage of action potentials. Low threshold spikes thus provide a nonlinear amplification allowing hyperpolarized relay neurons to respond to depolarizing inputs, including retinal EPSPs. In contrast, the tonic mode is characterized by a steady stream of unitary action potentials that more linearly reflects the visual stimulus. In this study, we tested possible differences in detection between response modes of 103 geniculate neurons by constructing receiver operating characteristic (ROC) curves for responses to visual stimuli (drifting sine-wave gratings and flashing spots). Detectability was determined from the ROC curves by computing the area under each curve, known as the ROC area. Most cells switched between modes during recording, evidently due to small shifts in membrane potential that affected the activation state of the low threshold spike. We found that the more often a cell responded in burst mode, the larger its ROC area. This was true for responses to optimal and nonoptimal visual stimuli, the latter including nonoptimal spatial frequencies and low stimulus contrasts. The larger ROC areas associated with burst mode were due to a reduced spontaneous activity and roughly equivalent level of visually evoked response when compared to tonic mode. We performed a within-cell analysis on a subset of 22 cells that switched modes during recording. Every cell, whether tested with a low contrast or high contrast visual stimulus exhibited a larger ROC area during its burst response mode than during its tonic mode. We conclude that burst responses better support signal detection than do tonic responses. Thus, burst responses, while less linear and perhaps less useful in providing a detailed analysis of visual stimuli, improve target detection. The tonic mode, with its more linear response, seems better suited for signal analysis rather than signal detection.

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