Information Accumulation over Time in Monkey Inferior Temporal Cortex Neurons Explains Pattern Recognition Reaction Time under Visual Noise

The Application of Pattern Recognition System in Design Field Based on Aesthetic Principles

The design system based on aesthetic principles is the most representative in the field of design and has a certain significance for the research and construction of design aesthetics and the development of design education. Therefore, this paper studies the application of pattern recognition system in the field of design based on aesthetic principles and designs a new type of aesthetic principle design system based on pattern recognition in computer vision. This paper proposes pattern similarity measurement and image preprocessing technology to improve the traditional aesthetic principle design system through pattern recognition and then further refine the research of the whole system through histogram equalization and gamma correction. Finally, the MNIST dataset experiment is used to verify the effect of multicolumn convolutional neural network pattern recognition on the aesthetic principle design system. The questionnaire survey experiment in this article and the traditional comparative experiment show that 76% of the public are very satisfied with this design system based on the aesthetic principles of pattern recognition in computer vision. Also, the improved aesthetic principle system scores as high as 90-95 points.

Invariant neural responses for sensory categories revealed by the time-varying information for communication calls

Although information theoretic approaches have been used extensively in the analysis of the neural code, they have yet to be used to describe how information is accumulated in time while sensory systems are categorizing dynamic sensory stimuli such as speech sounds or visual objects. Here, we present a novel method to estimate the cumulative information for stimuli or categories. We further define a time-varying categorical information index that, by comparing the information obtained for stimuli versus categories of these same stimuli, quantifies invariant neural representations. We use these methods to investigate the dynamic properties of avian cortical auditory neurons recorded in zebra finches that were listening to a large set of call stimuli sampled from the complete vocal repertoire of this species. We found that the time-varying rates carry 5 times more information than the mean firing rates even in the first 100 ms. We also found that cumulative information has slow time constants (100–600 ms) relative to the typical integration time of single neurons, reflecting the fact that the behaviorally informative features of auditory objects are time-varying sound patterns. When we correlated firing rates and information values, we found that average information correlates with average firing rate but that higher-rates found at the onset response yielded similar information values as the lower-rates found in the sustained response: the onset and sustained response of avian cortical auditory neurons provide similar levels of independent information about call identity and call-type. Finally, our information measures allowed us to rigorously define categorical neurons; these categorical neurons show a high degree of invariance for vocalizations within a call-type. Peak invariance is found around 150 ms after stimulus onset. Surprisingly, call-type invariant neurons were found in both primary and secondary avian auditory areas.

Just as the recognition of faces requires neural representations that are invariant to scale and rotation, the recognition of behaviorally relevant auditory objects, such as spoken words, requires neural representations that are invariant to the speaker uttering the word and to his or her location. Here, we used information theory to investigate the time course of the neural representation of bird communication calls and of behaviorally relevant categories of these same calls: the call-types of the bird’s repertoire. We found that neurons in both the primary and secondary avian auditory cortex exhibit invariant responses to call renditions within a call-type, suggestive of a potential role for extracting the meaning of these communication calls. We also found that time plays an important role: first, neural responses carry significantly more information when represented by temporal patterns calculated at the small time scale of 10 ms than when measured as average rates and, second, this information accumulates in a non-redundant fashion up to long integration times of 600 ms. This rich temporal neural representation is matched to the temporal richness found in the communication calls of this species.

Recency memory effects in Macaques during sequential delayed match-to-sample task with visual noise

Visual object recognition requires both visual sensory information and memory, and its mechanisms are often studied using old-world monkeys. Wittig et al. (2014, 2016) reported that Rhesus monkeys and humans seem to adopt different strategies in a short-term visual memory task. The Rhesus monkeys seemed to rely on recency of stimulus repetition, whereas humans relied on specific memorization. We conducted experiments using a sequential delayed match-to-sample task with random dot visual noise using Rhesus and Japanese monkeys and found that recency effect was observed in both species. There were differences in the noise effect on behavioral performances across species.