The generational brain: Introduction

Lux, Vanessa; Ommen, Clifford van

doi:10.1177/0959354316659554

Cited by 2 publications

(2 citation statements)

References 37 publications

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“…The brain is comprised of telencephalon and diencephalon, with the former being responsible for regulating behavior, generating affective states, as well as executing cognitive functions. The diencephalon is divided into the thalamus and hypothalamus [1], which are independently responsible for directing movement, transmitting sensation and maintaining emotional stability. Due to the intricate structure and multifaceted functions of the brain, the conveyed messages it transmits are of the utmost significance.…”

Section: Introductionmentioning

confidence: 99%

A Customized ECA-CRNN Model for Emotion Recognition Based on EEG Signals

Song

Yin

2023

Electronics

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Electroencephalogram (EEG) signals are electrical signals generated by changes in brain potential. As a significant physiological signal, EEG signals have been applied in various fields, including emotion recognition. However, current deep learning methods based on EEG signals for emotion recognition lack consideration of important aspects and comprehensive analysis of feature extraction interactions. In this paper, we propose a novel model named ECA-CRNN for emotion recognition using EEG signals. Our model integrates the efficient channel attention (ECA-Net) module into our modified combination of a customized convolutional neural network (CNN) and gated circulation unit (GRU), which enables more comprehensive feature extraction, enhances the internal relationship between frequency bands and improves recognition performance. Additionally, we utilize four-dimensional data as input to our model, comprising temporal, spatial and frequency information. The test on the DEAP dataset demonstrates that it enhances the recognition accuracy of EEG signals in both arousal and valence to 95.70% and 95.33%, respectively, while also reducing the standard deviation during five-fold cross-validation to 1.16 and 1.45 for arousal and valence, respectively, surpassing most methods.

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Section: Introductionmentioning

confidence: 99%

A Customized ECA-CRNN Model for Emotion Recognition Based on EEG Signals

Song

Yin

2023

Electronics

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“…This turn to neuroscience constitutes more than a significant development in the academy since its influence can be traced throughout society (Bluhm, Jacobson, & Maibom, 2012; Choudhury & Slaby, 2012; Dumit, 2003; Rose, 2007, 2013). Since this neurologic now criss-crosses—especially liberal democratic—societies, it can be claimed that we currently live in a “brain generation” (Lux & van Ommen, 2016) and a “biological age” (Rose, 2013). In such a society, subjectivity is increasingly conceptualised in neurological terms establishing what Rose (2003, 2007) calls the neurochemical self.…”

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confidence: 99%

Negotiating neuroscience: LeDoux’s “dramatic ensemble”

Ommen

Deventer

2016

Theory & Psychology

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Some argue we now live in a “brain society” in which our subjectivity is increasingly mediated through neurological discourses. Unless we are to surrender neuroscience to neoliberal colonisation, we need to articulate effective forms of engagement with this discipline. One route is to read mainstream neuroscience texts for resistances they offer to the homo economicus. Instead of a terrain that inevitably leads to neoliberal conclusions, we find a materiality in excess of dubious ideological circumscriptions. In this article we engage with Joseph LeDoux’s notion of the self as a “dramatic ensemble,” where the self is a vulnerable, constantly reiterated achievement marked by the partial and passing play of dominances. Simultaneously, however, LeDoux undermines this account by evoking a traditional notion of the self. This play of tensions is articulated and an argument is made to privilege a subjectivity which both resists LeDoux’s flight from his own implications and neoliberal assumptions of subjectivity.

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The generational brain: Introduction

Cited by 2 publications

References 37 publications

A Customized ECA-CRNN Model for Emotion Recognition Based on EEG Signals

A Customized ECA-CRNN Model for Emotion Recognition Based on EEG Signals

Negotiating neuroscience: LeDoux’s “dramatic ensemble”

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