scholarly journals The stimulus familiarization effect as a function of stimulus similarity

1970 ◽  
Vol 18 (6) ◽  
pp. 367-368 ◽  
Author(s):  
Sunnan K. Kubose
Keyword(s):  
Stimulus Similarity ◽  
Stimulus Familiarization

Effects of stimulus similarity on discrimination learning.

1956 ◽  
Vol 51 (6) ◽  
pp. 393-395 ◽  
Author(s):  
Charles C. Spiker
Keyword(s):  
Discrimination Learning ◽  
Stimulus Similarity

Gustatory neural coding in the monkey cortex: stimulus quality

1991 ◽  
Vol 66 (4) ◽  
pp. 1156-1165 ◽  
Author(s):  
V. L. Smith-Swintosky ◽  
C. R. Plata-Salaman ◽  
T. R. Scott
Keyword(s):  
Cortical Neurons ◽  
Neural Coding ◽  
Monosodium Glutamate ◽  
Stimulus Array ◽  
Cortical Region ◽  
Stimulus Similarity ◽  
Somatosensory Stimulation ◽  
Wide Range ◽  
Response Profiles ◽  
Stimulation Of

1. Extracellular action potentials were recorded from 50 single neurons in the insular-opercular cortex of two alert cynomolgus monkeys during gustatory stimulation of the tongue and palate. 2. Sixteen stimuli, including salts, sugars, acids, alkaloids, monosodium glutamate, and aspartame, were chosen to represent a wide range of taste qualities. Concentrations were selected to elicit a moderate gustatory response, as determined by reference to previous electrophysiological data or to the human psychophysical literature. 3. The cortical region over which taste-evoked activity could be recorded included the frontal operculum and anterior insula, an area of approximately 75 mm3. Taste-responsive cells constituted 50 (2.7%) of the 1,863 neurons tested. Nongustatory cells responded to mouth movement (20.7%), somatosensory stimulation of the tongue (9.6%), stimulus approach or anticipation (1.7%), and tongue extension (0.6%). The sensitivities of 64.6% of these cortical neurons could not be identified by our stimulation techniques. 4. Taste cells had low spontaneous activity levels (3.7 +/- 3.0 spikes/s, mean +/- SD) and showed little inhibition. They were moderately broadly tuned, with a mean entropy coefficient of 0.76 +/- 0.17. Excitatory responses were typically not robust. 5. Hierarchical cluster analysis was used to determine whether neurons could be divided into discrete types, as defined by their response profiles to the entire stimulus array. There was an apparent division of response profiles into four general categories, with primary sensitivities to sodium (n = 18), glucose (n = 15), quinine (n = 12), and acid (n = 5). However, these categories were not statistically independent. Therefore the notion of functionally distinct neuron types was not supported by an analysis of the distribution of response profiles. It was the case, however, that neurons in the sodium category could be distinguished from other neurons by their relative specificity. 6. The similarity among the taste qualities represented by this stimulus array was assessed by calculating correlations between the activity profiles they elicited from these 50 neurons. The results generally confirmed expectations derived from human psychophysical studies. In a multidimensional representation of stimulus similarity, there were groups that contained acids, sodium salts, and chemicals that humans label bitter and sweet. 7. The small proportion of insular-opercular neurons that are taste sensitive and the low discharge rates that taste stimuli are able to evoke from them suggest a wider role for this cortical area than just gustatory coding.(ABSTRACT TRUNCATED AT 400 WORDS)

scholarly journals Object comparison in the lateral intraparietal area

2017 ◽  
Vol 118 (4) ◽  
pp. 2458-2469 ◽  
Author(s):  
Wei Song Ong ◽  
Koorosh Mirpour ◽  
James W. Bisley
Keyword(s):  
Prefrontal Cortex ◽  
Object Recognition ◽  
Visual Information ◽  
Posterior Parietal Cortex ◽  
Ventral Stream ◽  
Object Identity ◽  
Stimulus Similarity ◽  
Lateral Intraparietal Area ◽  
Dynamic Representation ◽  
And Task

We can search for and locate specific objects in our environment by looking for objects with similar features. Object recognition involves stimulus similarity responses in ventral visual areas and task-related responses in prefrontal cortex. We tested whether neurons in the lateral intraparietal area (LIP) of posterior parietal cortex could form an intermediary representation, collating information from object-specific similarity map representations to allow general decisions about whether a stimulus matches the object being looked for. We hypothesized that responses to stimuli would correlate with how similar they are to a sample stimulus. When animals compared two peripheral stimuli to a sample at their fovea, the response to the matching stimulus was similar, independent of the sample identity, but the response to the nonmatch depended on how similar it was to the sample: the more similar, the greater the response to the nonmatch stimulus. These results could not be explained by task difficulty or confidence. We propose that LIP uses its known mechanistic properties to integrate incoming visual information, including that from the ventral stream about object identity, to create a dynamic representation that is concise, low dimensional, and task relevant and that signifies the choice priorities in mental matching behavior. NEW & NOTEWORTHY Studies in object recognition have focused on the ventral stream, in which neurons respond as a function of how similar a stimulus is to their preferred stimulus, and on prefrontal cortex, where neurons indicate which stimulus is being looked for. We found that parietal area LIP uses its known mechanistic properties to form an intermediary representation in this process. This creates a perceptual similarity map that can be used to guide decisions in prefrontal areas.

Effects of task difficulty, stimulus similarity, and type of response on stimulus predifferentiation.

1958 ◽  
Vol 55 (2) ◽  
pp. 167-172 ◽  
Author(s):  
Bennet B. Murdock
Keyword(s):  
Task Difficulty ◽  
Stimulus Similarity

scholarly journals Color-based estimates of stimulus similarity predict perceptual similarity of image pairs to monkeys

2010 ◽  
Vol 3 (9) ◽  
pp. 511-511 ◽  
Author(s):  
S. R Allred ◽  
J. Y Skiver ◽  
B. Jagadeesh
Keyword(s):  
Perceptual Similarity ◽  
Stimulus Similarity ◽  
Image Pairs

Successive and Simultaneous Discrimination as a Function of Stimulus-Similarity

1954 ◽  
Vol 67 (2) ◽  
pp. 308 ◽  
Author(s):  
Eugene F. MacCaslin
Keyword(s):  
Simultaneous Discrimination ◽  
Stimulus Similarity

scholarly journals Stimulus familiarization (n) in nonverbal selective learning

1966 ◽  
Vol 5 (12) ◽  
pp. 453-454
Author(s):  
Clyde E. Noble ◽  
James P. Allison ◽  
Thomas A. Jones
Keyword(s):  
Selective Learning ◽  
Stimulus Familiarization

Q-SpAM: How to Efficiently Measure Similarity in Online Research

2020 ◽  
pp. 004912412091493 ◽  
Author(s):  
Alex Koch ◽  
Felix Speckmann ◽  
Christian Unkelbach
Keyword(s):  
Social Science ◽  
Spatial Arrangement ◽  
Online Research ◽  
Stimulus Similarity ◽  
Social Scientists ◽  
Large Stimulus ◽  
Computer Screen ◽  
Similarity Data ◽  
User Friendly ◽  
Do So

Measuring the similarity of stimuli is of great interest to a variety of social scientists. Spatial arrangement by dragging and dropping “more similar” targets closer together on the computer screen is a precise and efficient method to measure stimulus similarity. We present Qualtrics-spatial arrangement method (Q-SpAM), a feature-rich and user-friendly online version of spatial arrangement. Combined with crowdsourcing platforms, Q-SpAM provides fast and affordable access to similarity data even for large stimulus sets. Participants may spatially arrange up to 100 words or images, randomly selected targets, self-selected targets, self-generated targets, and targets self-marked in different colors. These and other Q-SpAM features can be combined. We exemplify how to collect, process, and visualize similarity data with Q-SpAM and provide R and Excel scripts to do so. We then illustrate Q-SpAM’s versatility for social science, concluding that Q-SpAM is a reliable and valid method to measure the similarity of lots of stimuli with little effort.

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