Visual Categorization and Object Representation in Monkeys and Humans

2002 ◽  
Vol 14 (2) ◽  
pp. 187-198 ◽  
Author(s):  
N. Sigala ◽  
F. Gabbiani ◽  
N. K. Logothetis
Keyword(s):  
Object Representation ◽  
Rating Task ◽  
Linear Boundary ◽  
Conditional Probabilities ◽  
Diagnostic Features ◽  
Categorization Task ◽  
Visual Categorization ◽  
Perceptual Features ◽  
Subordinate Categorization

We investigated the influence of a categorization task on the extraction and representation of perceptual features in humans and monkeys. The use of parameterized stimuli (schematic faces and fish) with fixed diagnostic features in combination with a similarity-rating task allowed us to demonstrate perceptual sensitization to the diagnostic dimensions of the categorization task for the monkeys. Moreover, our results reveal important similarities between human and monkey visual subordinate categorization strategies. Neither the humans nor the monkeys compared the new stimuli to class prototypes or based their decisions on conditional probabilities along stimulus dimensions. Instead, they classified each object according to its similarity to familiar members of the alternative categories, or with respect to its position to a linear boundary between the learned categories.

scholarly journals Adaptive Sampling of the Electrocardiogram Based on Generalized Perceptual Features

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 373 ◽  
Author(s):  
Piotr Augustyniak
Keyword(s):  
Adaptive Sampling ◽  
Medical Information ◽  
Temporal Distribution ◽  
Diagnostic Features ◽  
Gaze Tracking ◽  
Perceptual Features ◽  
Information Density ◽  
Low Pass ◽  
Mean Square Difference ◽  
Local Sampling

A non-uniform distribution of diagnostic information in the electrocardiogram (ECG) has been commonly accepted and is the background to several compression, denoising and watermarking methods. Gaze tracking is a widely recognized method for identification of an observer’s preferences and interest areas. The statistics of experts’ scanpaths were found to be a convenient quantitative estimate of medical information density for each particular component (i.e., wave) of the ECG record. In this paper we propose the application of generalized perceptual features to control the adaptive sampling of a digital ECG. Firstly, based on temporal distribution of the information density, local ECG bandwidth is estimated and projected to the actual positions of components in heartbeat representation. Next, the local sampling frequency is calculated pointwise and the ECG is adaptively low-pass filtered in all simultaneous channels. Finally, sample values are interpolated at new time positions forming a non-uniform time series. In evaluation of perceptual sampling, an inverse transform was used for the reconstruction of regularly sampled ECG with a percent root-mean-square difference (PRD) error of 3–5% (for compression ratios 3.0–4.7, respectively). Nevertheless, tests performed with the use of the CSE Database show good reproducibility of ECG diagnostic features, within the IEC 60601-2-25:2015 requirements, thanks to the occurrence of distortions in less relevant parts of the cardiac cycle.

scholarly journals A Comparison of Lateral and Medial Intraparietal Areas during a Visual Categorization Task

2013 ◽  
Vol 33 (32) ◽  
pp. 13157-13170 ◽  
Author(s):  
S. K. Swaminathan ◽  
N. Y. Masse ◽  
D. J. Freedman
Keyword(s):  
Categorization Task ◽  
Visual Categorization

scholarly journals Task- and Time-Dependent Memory Enhancement by Dehydroepiandosterone in Day-Old Chicks

2001 ◽  
Vol 8 (4) ◽  
pp. 255-270 ◽  
Author(s):  
A. N. B. Johnston ◽  
P. V. Migues
Keyword(s):  
Open Field Test ◽  
Time Dependent ◽  
Avoidance Task ◽  
Intracerebral Injection ◽  
Chick Brain ◽  
Memory Enhancement ◽  
Categorization Task ◽  
Visual Categorization ◽  
Per Se ◽  
The Brain

We have previously reported the presence of dehydroepiandosterone (DHEA) in the dayold- chick brain, and a role for it in enhanced memory formation. Here we confirm that intracerebral injections of DHEA 5 min before training on the weak passive avoidance task enhanced recall 24 hours after training. Recall per se on an appetitive visual categorization task was not altered by administration of DHEA 5 min before training. However administration of DHEA 5 min before limited or very limited training on a visual categorization task (20 or 10 pecks only) appeared to enhance consolidation of this task at test 24 h after training; reducing the latency and total time taken to complete the test (60 pecks), while not detrimentally altering accuracy. Moreover, DHEA is unlikely to induce this effect via possible anxiolytic effects because it did not alter behavior in the open field test. We also examined diffusion of DHEA throughout the brain at various stages following intracerebral injection.

Learning selective top-down control enhances performance in a visual categorization task

2012 ◽  
Vol 108 (11) ◽  
pp. 3124-3137 ◽  
Author(s):  
Mario Pannunzi ◽  
Guido Gigante ◽  
Maurizio Mattia ◽  
Gustavo Deco ◽  
Stefano Fusi ◽  
...  
Keyword(s):  
Time Course ◽  
Signal To Noise Ratio ◽  
Temporal Cortex ◽  
Inferior Temporal Cortex ◽  
Feedback Signal ◽  
Top Down ◽  
Categorization Task ◽  
Tuning Curves ◽  
Visual Categorization ◽  
Neural Activities

We model the putative neuronal and synaptic mechanisms involved in learning a visual categorization task, taking inspiration from single-cell recordings in inferior temporal cortex (ITC). Our working hypothesis is that learning the categorization task involves both bottom-up, ITC to prefrontal cortex (PFC), and top-down (PFC to ITC) synaptic plasticity and that the latter enhances the selectivity of the ITC neurons encoding the task-relevant features of the stimuli, thereby improving the signal-to-noise ratio. We test this hypothesis by modeling both areas and their connections with spiking neurons and plastic synapses, ITC acting as a feature-selective layer and PFC as a category coding layer. This minimal model gives interesting clues as to properties and function of the selective feedback signal from PFC to ITC that help solving a categorization task. In particular, we show that, when the stimuli are very noisy because of a large number of nonrelevant features, the feedback structure helps getting better categorization performance and decreasing the reaction time. It also affects the speed and stability of the learning process and sharpens tuning curves of ITC neurons. Furthermore, the model predicts a modulation of neural activities during error trials, by which the differential selectivity of ITC neurons to task-relevant and task-irrelevant features diminishes or is even reversed, and modulations in the time course of neural activities that appear when, after learning, corrupted versions of the stimuli are input to the network.

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