The relationship between eye movement and vision develops before birth

Schöpf, Veronika; Schlegl, Thomas; Jakab, András; Kasprian, Gregor; Woitek, Ramona; Prayer, Daniela

doi:10.3389/fnhum.2014.00775

Cited by 25 publications

(21 citation statements)

References 29 publications

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“…This suggests visual imagery in dreaming of the congenitally blind, because alpha activity attenuation is regarded as an indicator of visual imagery in general ( Lopes da Silva, 2003 ). Furthermore, REM-locked activation in visual brain areas in utero suggests a REM-locked primitive form of vision ( Schöpf et al, 2014 ). (2) In monkeys many binocular REMs are not conjugated ( Zhou and King, 1997 ).…”

Section: Neural and Perceptual Correlates Of Rems During Dreaming Slementioning

confidence: 99%

Rapid Eye Movements in Sleep Furnish a Unique Probe Into Consciousness

et al. 2018

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The neural correlates of rapid eye movements (REMs) in sleep are extraordinarily robust; including REM-locked multisensory-motor integration and accompanying activation in the retrosplenial cortex, the supplementary eye field and areas encompassing cholinergic basal nucleus (Hong et al., 2009). The phenomenology of REMs speaks to the notion that perceptual experience in both sleep and wakefulness is a constructive process – in which we generate predictions of sensory inputs and then test those predictions through actively sampling the sensorium with eye movements. On this view, REMs during sleep may index an internalized active sampling or ‘scanning’ of self-generated visual constructs that are released from the constraints of visual input. If this view is correct, it renders REMs an ideal probe to study consciousness as “an exclusively internal affair” (Metzinger, 2009). In other words, REMs offer a probe of active inference – in the sense of predictive coding – when the brain is isolated from the sensorium in virtue of the natural blockade of sensory afferents during REM sleep. Crucially, REMs are temporally precise events that enable powerful inferences based on time series analyses. As a natural, task-free probe, (REMs) could be used in non-compliant subjects, including infants and animals. In short, REMs constitute a promising probe to study the ontogenetic and phylogenetic development of consciousness and perhaps the psychopathology of schizophrenia and autism, which have been considered in terms of aberrant predictive coding.

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Section: Neural and Perceptual Correlates Of Rems During Dreaming Slementioning

confidence: 99%

Rapid Eye Movements in Sleep Furnish a Unique Probe Into Consciousness

et al. 2018

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“…One study examined the relation between fetal eye-movements and fetal brain FC and found that fetal eye-movements were associated to simultaneous networks in visual- and frontal areas of the brain [32]. Very recently, the first study associated fetal FC to prematurity [33] – a relatively common negative birth outcome associated with many complications later in life (e.g., [34]).…”

Section: Potential Of Fetal Fc Researchmentioning

confidence: 99%

Functional Connectivity of the Human Brain in Utero

Heuvel

Thomason

2016

Trends in Cognitive Sciences

109

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The brain is subject to dramatic developmental processes during the prenatal period. Nevertheless, information about the development of functional brain networks during gestation is scarce. Until recently it has not been possible to probe function in the living human fetal brain. Advances in functional MRI have changed the paradigm, making it possible to measure spontaneous activity in the fetal brain and to cross-correlate functional signals to attain information about neural connectional architecture across human gestation. We summarize the earliest MRI studies of fetal neural functional connectivity and highlight unique challenges and limitations inherent in the technique. In addition, we discuss future directions to unlock the potential of fetal brain functional MRI research.

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“…Considerable research has looked at the relationship between functional MR brain imaging and controlled sensory stimulation and a few of these studies have also incorporated MVA. Schopf et al ( 2014 ) used fMRI technology to study fetal eye movements in utero . Their approach included the use of the random forest machine learning algorithm (Breiman, 2001 ) to classify whether individual pixels were part of the fetal eye.…”

Section: Resultsmentioning

confidence: 99%

Multivariate Analyses Applied to Healthy Neurodevelopment in Fetal, Neonatal, and Pediatric MRI

Levman

Takahashi

2016

Front. Neuroanat.

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Multivariate analysis (MVA) is a class of statistical and pattern recognition techniques that involve the processing of data that contains multiple measurements per sample. MVA can be used to address a wide variety of neurological medical imaging related challenges including the evaluation of healthy brain development, the automated analysis of brain tissues and structures through image segmentation, evaluating the effects of genetic and environmental factors on brain development, evaluating sensory stimulation's relationship with functional brain activity and much more. Compared to adult imaging, pediatric, neonatal and fetal imaging have attracted less attention from MVA researchers, however, recent years have seen remarkable MVA research growth in pre-adult populations. This paper presents the results of a systematic review of the literature focusing on MVA applied to healthy subjects in fetal, neonatal and pediatric magnetic resonance imaging (MRI) of the brain. While the results of this review demonstrate considerable interest from the scientific community in applications of MVA technologies in brain MRI, the field is still young and significant research growth will continue into the future.

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The relationship between eye movement and vision develops before birth

Cited by 25 publications

References 29 publications

Rapid Eye Movements in Sleep Furnish a Unique Probe Into Consciousness

Rapid Eye Movements in Sleep Furnish a Unique Probe Into Consciousness

Functional Connectivity of the Human Brain in Utero

Multivariate Analyses Applied to Healthy Neurodevelopment in Fetal, Neonatal, and Pediatric MRI

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