Measurement of brain lactate during visual stimulation using a long TE semi‐LASER sequence at 7 T

AbstractThe Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.

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How virtual avatar experience interplays with self-concepts: the use of anthropometric 3D body models in the visual stimulation process

Fashion and Textiles ◽

10.1186/s40691-021-00257-6 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Juyeon Park ◽

Jennifer Paff Ogle

Keyword(s):

Body Image ◽

Visual Stimulation ◽

The Body ◽

Control Group ◽

Body Perception ◽

Self Compassion ◽

Quantitative Results ◽

Novel Applications ◽

Experimental Group ◽

Virtual Avatar

AbstractWe explored how viewing one’s anthropometric virtual avatar would affect the viewer’s self-body perception through the comparative evaluation of self-concepts—self-esteem and self-compassion, within the framework of allocentric lock theory. We recruited 18 female adults, aged 18–21, who identified themselves to have some level of body image concerns, and who had had no clinical treatment for their body image. Participants were randomly assigned either to the experimental or control group. The experimental group participated in both body positivity program and virtual avatar program, whereas the control group attended the body positivity program, only. The results affirmed that the body positivity program served as a psychological buffer prior to the virtual avatar stimulus. After the virtual avatar experience, the participants demonstrated self-acceptance by lowering their expectation on how they should look like. The findings from exit interviews enriched the quantitative results. This study verified the mechanism of the altered processing of the stored bodily memory by the egocentric sensory input of virtual avatars, and offered practical potential of the study outcomes to be applied in various emerging fields where novel applications of virtual 3D technology are sought, such as fashion e-commerce.

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Conscious perception and perceptual echoes: a binocular rivalry study

Neuroscience of Consciousness ◽

10.1093/nc/niab007 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Canhuang Luo ◽

Rufin VanRullen ◽

Andrea Alamia

Keyword(s):

Binocular Rivalry ◽

Visual Information ◽

Visual Stimulation ◽

Brain Regions ◽

Travelling Wave ◽

Alpha Power ◽

Conscious Perception ◽

Impulse Response Functions ◽

Band Frequency ◽

Underlying Mechanisms

Abstract Alpha rhythms (∼10Hz) in the human brain are classically associated with idling activities, being predominantly observed during quiet restfulness with closed eyes. However, recent studies demonstrated that alpha (∼10Hz) rhythms can directly relate to visual stimulation, resulting in oscillations, which can last for as long as one second. This alpha reverberation, dubbed perceptual echoes (PE), suggests that the visual system actively samples and processes visual information within the alpha-band frequency. Although PE have been linked to various visual functions, their underlying mechanisms and functional role are not completely understood. In this study, we investigated the relationship between conscious perception and the generation and the amplitude of PE. Specifically, we displayed two coloured Gabor patches with different orientations on opposite sides of the screen, and using a set of dichoptic mirrors, we induced a binocular rivalry between the two stimuli. We asked participants to continuously report which one of two Gabor patches they consciously perceived, while recording their EEG signals. Importantly, the luminance of each patch fluctuated randomly over time, generating random sequences from which we estimated two impulse-response functions (IRFs) reflecting the PE generated by the perceived (dominant) and non-perceived (suppressed) stimulus, respectively. We found that the alpha power of the PE generated by the consciously perceived stimulus was comparable with that of the PE generated during monocular vision (control condition) and higher than the PE induced by the suppressed stimulus. Moreover, confirming previous findings, we found that all PEs propagated as a travelling wave from posterior to frontal brain regions, irrespective of conscious perception. All in all our results demonstrate a correlation between conscious perception and PE, suggesting that the synchronization of neural activity plays an important role in visual sampling and conscious perception.

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An analysis framework for the integration of broadband NIRS and EEG to assess neurovascular and neurometabolic coupling

Scientific Reports ◽

10.1038/s41598-021-83420-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

P. Pinti ◽

M. F. Siddiqui ◽

A. D. Levy ◽

E. J. H. Jones ◽

Ilias Tachtsidis

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Visual Stimulation ◽

Finite Impulse Response ◽

Occipital Cortex ◽

Integrated Analysis ◽

Impulse Response Functions ◽

Functional Near Infrared Spectroscopy ◽

Brain Functioning

AbstractWith the rapid growth of optical-based neuroimaging to explore human brain functioning, our research group has been developing broadband Near Infrared Spectroscopy (bNIRS) instruments, a technological extension to functional Near Infrared Spectroscopy (fNIRS). bNIRS has the unique capacity of monitoring brain haemodynamics/oxygenation (measuring oxygenated and deoxygenated haemoglobin), and metabolism (measuring the changes in the redox state of cytochrome-c-oxidase). When combined with electroencephalography (EEG), bNIRS provides a unique neuromonitoring platform to explore neurovascular coupling mechanisms. In this paper, we present a novel pipeline for the integrated analysis of bNIRS and EEG signals, and demonstrate its use on multi-channel bNIRS data recorded with concurrent EEG on healthy adults during a visual stimulation task. We introduce the use of the Finite Impulse Response functions within the General Linear Model for bNIRS and show its feasibility to statistically localize the haemodynamic and metabolic activity in the occipital cortex. Moreover, our results suggest that the fusion of haemodynamic and metabolic measures unveils additional information on brain functioning over haemodynamic imaging alone. The cross-correlation-based analysis of interrelationships between electrical (EEG) and haemodynamic/metabolic (bNIRS) activity revealed that the bNIRS metabolic signal offers a unique marker of brain activity, being more closely coupled to the neuronal EEG response.

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Face-selective responses in combined EEG/MEG recordings with Fast Periodic Visual Stimulation (FPVS)

NeuroImage ◽

10.1016/j.neuroimage.2021.118460 ◽

2021 ◽

pp. 118460

Author(s):

O. Hauk ◽

G.E. Rice ◽

A. Volfart ◽

F. Magnabosco ◽

M.A. Lambon Ralph ◽

...

Keyword(s):

Visual Stimulation

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