A lateral inhibition mechanism explains the dissociation between mismatch negativity and behavioral pitch discrimination

Gu, Feng; Wong, Lena L. N.; Hu, Axu; Zhang, Xiaochu; Tong, Xiuli

doi:10.1016/j.brainres.2019.146308

Cited by 5 publications

(3 citation statements)

References 73 publications

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“…Despite decades of research, the mechanisms that elicit the MMN remain controversial. An alternate theory to predictive coding is neural adaptation (Garrido et al, 2009;Gu et al, 2019;Jaaskelainen et al, 2004; deviants differ in pattern, not stimulus features such as pitch, suggesting that MMN cannot be a result of neural habituation to acoustic features. It is possible, however, that MMN might operate at a pattern or auditory object level, with habituation occurring at these higher levels of representation.…”

Section: Introductionmentioning

confidence: 99%

“…Despite decades of research, the mechanisms that elicit the MMN remain controversial. An alternate theory to predictive coding is neural adaptation (Garrido et al, 2009; Gu et al, 2019; Jaaskelainen et al, 2004; May & Tiitinen, 2010). According to this theory, as a tone is repeated, neurons encoding its acoustic features habituate, leading to decreased neural firing.…”

Section: Introductionmentioning

confidence: 99%

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The sound of silence: Predictive error responses to unexpected sound omission in adults

Prete

Heikoop

McGillivray

et al. 2022

Eur J of Neuroscience

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The human auditory system excels at detecting patterns needed for processing speech and music. According to predictive coding, the brain predicts incoming sounds, compares predictions to sensory input and generates a prediction error whenever a mismatch between the prediction and sensory input occurs. Predictive coding can be indexed in electroencephalography (EEG) with the mismatch negativity (MMN) and P3a, two components of event‐related potentials (ERP) that are elicited by infrequent deviant sounds (e.g., differing in pitch, duration and loudness) in a stream of frequent sounds. If these components reflect prediction error, they should also be elicited by omitting an expected sound, but few studies have examined this. We compared ERPs elicited by infrequent randomly occurring omissions (unexpected silences) in tone sequences presented at two tones per second to ERPs elicited by frequent, regularly occurring omissions (expected silences) within a sequence of tones presented at one tone per second. We found that unexpected silences elicited significant MMN and P3a, although the magnitude of these components was quite small and variable. These results provide evidence for hierarchical predictive coding, indicating that the brain predicts silences and sounds.

show abstract

Section: Introductionmentioning

confidence: 99%

“…Despite decades of research, the mechanisms that elicit the MMN remain controversial. An alternate theory to predictive coding is neural adaptation (Garrido et al, 2009; Gu et al, 2019; Jaaskelainen et al, 2004; May & Tiitinen, 2010). According to this theory, as a tone is repeated, neurons encoding its acoustic features habituate, leading to decreased neural firing.…”

Section: Introductionmentioning

confidence: 99%

The sound of silence: Predictive error responses to unexpected sound omission in adults

Prete

Heikoop

McGillivray

et al. 2022

Eur J of Neuroscience

View full text Add to dashboard Cite

show abstract

“…Whether neuromorphic data or static data, background information cannot be ignored for object recognition, especially medical images in realistic scenes. erefore, the lateral inhibition mechanism is an effective means to suppress background information and improve recognition accuracy [20][21][22]. A lateral inhibition-based Fourier singlepixel imaging technique is proposed to improve the reconstruction contrast and quality for low-contrast scenes [23].…”

Section: Related Workmentioning

confidence: 99%

A Parallel Spiking Neural Network Based on Adaptive Lateral Inhibition Mechanism for Objective Recognition

Dong

2022

Computational Intelligence and Neuroscience

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Spiking neural network (SNN) has attracted extensive attention in the field of machine learning because of its biological interpretability and low power consumption. However, the accuracy of pattern recognition cannot completely surpass deep neural networks (DNNs). The main reason is that the inherent nondifferentiability of spiking neurons makes SNN unable to be trained directly by the gradient descent algorithm, and there is also no unified training algorithm for SNN. Inspired by the biological vision system, this paper proposes a parallel convolution SNN structure combined with an adaptive lateral inhibition mechanism. And, a way of dynamically evolving the time constant with the training of SNN is proposed to ensure the diversity of neurons. This paper verifies the effectiveness of the proposed methods on static datasets and neuromorphic datasets and extends it to the recognition of breast tumors. Experimental results show that the SNN has obvious advantages in dynamical datasets. For breast tumors, it is also an edge-based task, because the edge of a medical image contains the most important information in the image. This kind of information can provide great help for the noninvasive and accurate diagnosis of diseases. The Experimental results show that the proposed method is very close to the recognition results of DNNs on static datasets, and its performance on neuromorphic datasets exceeds that of DNNs.

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Effect of musical expertise on the perception of duration and pitch in language: A cross-linguistic study

Lyu,

Põldver,

Kask

et al. 2024

Acta Psychologica

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A lateral inhibition mechanism explains the dissociation between mismatch negativity and behavioral pitch discrimination

Cited by 5 publications

References 73 publications

The sound of silence: Predictive error responses to unexpected sound omission in adults

The sound of silence: Predictive error responses to unexpected sound omission in adults

A Parallel Spiking Neural Network Based on Adaptive Lateral Inhibition Mechanism for Objective Recognition

Effect of musical expertise on the perception of duration and pitch in language: A cross-linguistic study

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