LOW-LEVEL X IRRADIATION OF THE BRAIN DURING DEVELOPMENT: MORPHOLOGICAL, PHYSIOLOGICAL, AND BEHAVIORAL CONSEQUENCES. Comprehensive Report, June 15, 1962--August 31, 1971.

Abstract Ideological behavior has traditionally been viewed as a product of social forces. Nonetheless, an emerging science suggests that ideological worldviews can also be understood in terms of neural and cognitive principles. The article proposes a neurocognitive model of ideological thinking, arguing that ideological worldviews may be manifestations of individuals’ perceptual and cognitive systems. This model makes two claims. First, there are neurocognitive antecedents to ideological thinking: the brain’s low-level neurocognitive dispositions influence its receptivity to ideological doctrines. Second, there are neurocognitive consequences to ideological engagement: strong exposure and adherence to ideological doctrines can shape perceptual and cognitive systems. This article details the neurocognitive model of ideological thinking and synthesizes the empirical evidence in support of its claims. The model postulates that there are bidirectional processes between the brain and the ideological environment, and so it can address the roles of situational and motivational factors in ideologically motivated action. This endeavor highlights that an interdisciplinary neurocognitive approach to ideologies can facilitate biologically informed accounts of the ideological brain and thus reveal who is most susceptible to extreme and authoritarian ideologies. By investigating the relationships between low-level perceptual processes and high-level ideological attitudes, we can develop a better grasp of our collective history as well as the mechanisms that may structure our political futures.

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Perceptual decisions are biased toward relevant prior choices

Scientific Reports ◽

10.1038/s41598-020-80128-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Helen Feigin ◽

Shira Baror ◽

Moshe Bar ◽

Adam Zaidel

Keyword(s):

Sensory Information ◽

Irrelevant Stimulus ◽

Stimulus Feature ◽

Serial Dependence ◽

Low Level ◽

Subsequent Test ◽

Key Factor ◽

High Level ◽

Motor Actions ◽

The Brain

AbstractPerceptual decisions are biased by recent perceptual history—a phenomenon termed 'serial dependence.' Here, we investigated what aspects of perceptual decisions lead to serial dependence, and disambiguated the influences of low-level sensory information, prior choices and motor actions. Participants discriminated whether a brief visual stimulus lay to left/right of the screen center. Following a series of biased ‘prior’ location discriminations, subsequent ‘test’ location discriminations were biased toward the prior choices, even when these were reported via different motor actions (using different keys), and when the prior and test stimuli differed in color. By contrast, prior discriminations about an irrelevant stimulus feature (color) did not substantially influence subsequent location discriminations, even though these were reported via the same motor actions. Additionally, when color (not location) was discriminated, a bias in prior stimulus locations no longer influenced subsequent location discriminations. Although low-level stimuli and motor actions did not trigger serial-dependence on their own, similarity of these features across discriminations boosted the effect. These findings suggest that relevance across perceptual decisions is a key factor for serial dependence. Accordingly, serial dependence likely reflects a high-level mechanism by which the brain predicts and interprets new incoming sensory information in accordance with relevant prior choices.

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Spiritual Education Mission in the Mufassirin Perspective

Al-Albab ◽

10.24260/alalbab.v8i2.1444 ◽

2019 ◽

Vol 8 (2) ◽

pp. 237-262

Author(s):

Syarif Syarif

Keyword(s):

Education System ◽

Social Life ◽

Research Method ◽

Spiritual Values ◽

Spiritual Education ◽

Modern Humans ◽

Educational Approach ◽

Low Level ◽

Library Research ◽

The Brain

Spiritual crisis is a factor leading to disorientation in today’s modern humans and the decline of morality of the nation. The low level of spirituality is caused by an educational approach that only focuses on the brain and ignores spiritual values. The Qur'an has actually affirmed the mission of spiritual education which should be used as a reference for the current education system. This article employs library research method through a comparison of the way the mufassirin interpret verses about the mission of spiritual education. The results show that the mission of spiritual education carried out by the Prophet Muhammad can be seen for example in Surat Al-Anbiya' verse 107, Surat Saba' verse 28 and Surat Al-Ahzab verse 21, namely rahmatan lil 'alamin (mercy to all creations). The prophet has brought evidence the truth to perfect the akhlậq, as well as to become the followers of uswah hasanah (perfect example) which must be imitated by all humans. Meanwhile, the stages of increasing spirituality in the Surat Luqman Verses 12-19, include: (1) instilling the tauhid values, (2) being filial to parents, (3) understanding the reciprocity of each deed, (4) command to worship, (5) introducing politeness in social life. Elements of spiritual education contained in Surat al-Muzzammil Verses 1-10 include qiyamul lail or night prayer, reciting the Qur’an in a tartil way, getting used to zikr, patience, jihad fi sabilillah or fighting on the path of Allah, and always praying and begging forgiveness from Allah.

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Reconstructing feedback representations in ventral visual pathway with a generative adversarial autoencoder

10.1101/2020.07.23.218859 ◽

2020 ◽

Author(s):

Haider Al-Tahan ◽

Yalda Mohsenzadeh

Keyword(s):

Neural Network ◽

Visual Information ◽

Visual Pathway ◽

Functional Magnetic Resonance ◽

Low Level ◽

Ventral Visual Pathway ◽

High Level ◽

Feedback Connections ◽

The Brain ◽

Insight Into

AbstractWhile vision evokes a dense network of feedforward and feedback neural processes in the brain, visual processes are primarily modeled with feedforward hierarchical neural networks, leaving the computational role of feedback processes poorly understood. Here, we developed a generative autoencoder neural network model and adversarially trained it on a categorically diverse data set of images. We hypothesized that the feedback processes in the ventral visual pathway can be represented by reconstruction of the visual information performed by the generative model. We compared representational similarity of the activity patterns in the proposed model with temporal (magnetoencephalography) and spatial (functional magnetic resonance imaging) visual brain responses. The proposed generative model identified two segregated neural dynamics in the visual brain. A temporal hierarchy of processes transforming low level visual information into high level semantics in the feedforward sweep, and a temporally later dynamics of inverse processes reconstructing low level visual information from a high level latent representation in the feedback sweep. Our results append to previous studies on neural feedback processes by presenting a new insight into the algorithmic function and the information carried by the feedback processes in the ventral visual pathway.Author summaryIt has been shown that the ventral visual cortex consists of a dense network of regions with feedforward and feedback connections. The feedforward path processes visual inputs along a hierarchy of cortical areas that starts in early visual cortex (an area tuned to low level features e.g. edges/corners) and ends in inferior temporal cortex (an area that responds to higher level categorical contents e.g. faces/objects). Alternatively, the feedback connections modulate neuronal responses in this hierarchy by broadcasting information from higher to lower areas. In recent years, deep neural network models which are trained on object recognition tasks achieved human-level performance and showed similar activation patterns to the visual brain. In this work, we developed a generative neural network model that consists of encoding and decoding sub-networks. By comparing this computational model with the human brain temporal (magnetoencephalography) and spatial (functional magnetic resonance imaging) response patterns, we found that the encoder processes resemble the brain feedforward processing dynamics and the decoder shares similarity with the brain feedback processing dynamics. These results provide an algorithmic insight into the spatiotemporal dynamics of feedforward and feedback processes in biological vision.

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