The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Nicola Molinaro - One of the best experts on this subject based on the ideXlab platform.
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temporal uncertainty enhances suppression of neural responses to predictable Visual Stimuli
NeuroImage, 2021Co-Authors: Sanjeev Nara, Mikel Lizarazu, Craig G Richter, Diana C Dima, Radoslaw Martin Cichy, Mathieu Bourguignon, Nicola MolinaroAbstract:Abstract Contextual information triggers predictions about the content (“what”) of environmental Stimuli to update an internal generative model of the surrounding world. However, Visual information dynamically changes across time, and temporal predictability (“when”) may influence the impact of internal predictions on Visual processing. In this magnetoencephalography (MEG) study, we investigated how processing feature specific information (“what”) is affected by temporal predictability (“when”). Participants (N = 16) were presented with four consecutive Gabor patches (entrainers) with constant spatial frequency but with variable orientation and temporal onset. A fifth target Gabor was presented after a longer delay and with higher or lower spatial frequency that participants had to judge. We compared the neural responses to entrainers where the Gabor orientation could, or could not be temporally predicted along the entrainer sequence, and with inter-entrainer timing that was constant (predictable), or variable (unpredictable). We observed suppression of evoked neural responses in the Visual cortex for predictable Stimuli. Interestingly, we found that temporal uncertainty increased expectation suppression. This suggests that in temporally uncertain scenarios the neurocognitive system invests less resources in integrating bottom-up information. Multivariate pattern analysis showed that predictable Visual features could be decoded from neural responses. Temporal uncertainty did not affect decoding accuracy for early Visual responses, with the feature specificity of early Visual neural activity preserved across conditions. However, decoding accuracy was less sustained over time for temporally jittered than for isochronous predictable Visual Stimuli. These findings converge to suggest that the cognitive system processes Visual features of temporally predictable Stimuli in higher detail, while processing temporally uncertain Stimuli may rely more heavily on abstract internal expectations.
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temporal uncertainty enhances suppression of neural responses to predictable Visual Stimuli
bioRxiv, 2021Co-Authors: Sanjeev Nara, Mikel Lizarazu, Craig G Richter, Diana C Dima, Radoslaw Martin Cichy, Mathieu Bourguignon, Nicola MolinaroAbstract:Predictive processing has been proposed as a fundamental cognitive mechanism to account for how the brain interacts with the external environment via its sensory systems. In vision, contextual information triggers predictions about the content (″what″) of environmental Stimuli to update an internal generative model of the surrounding world. However, Visual information dynamically changes across time, and temporal predictability (″when″) may influence the impact of internal predictions on Visual processing. In this magnetoencephalography (MEG) study, we investigated how processing feature specific information (″what″) is affected by temporal predictability (″when″). In line with previous findings, we observed suppression of evoked neural responses in the Visual cortex for predictable Stimuli. Interestingly, we found that temporal uncertainty increased expectation suppression. This suggests that in temporally uncertain scenarios the neurocognitive system invests less resources in integrating bottom-up information. Multivariate pattern analysis showed that predictable Visual features could be decoded from neural responses. Temporal uncertainty did not affect decoding accuracy for early Visual responses, with the feature specificity of early Visual neural activity preserved across conditions. However, decoding accuracy was less sustained over time for temporally jittered than for isochronous predictable Visual Stimuli. These findings converge to suggest that the cognitive system processes Visual features of temporally predictable Stimuli in higher detail, while processing temporally uncertain Stimuli may rely more heavily on abstract internal expectations.
David Kleinfeld - One of the best experts on this subject based on the ideXlab platform.
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Visual Stimuli induce waves of electrical activity in turtle cortex
Proceedings of the National Academy of Sciences of the United States of America, 1997Co-Authors: James C Prechtl, Lawrence B Cohen, Bijan Pesaran, Partha P Mitra, David KleinfeldAbstract:The computations involved in the processing of a Visual scene invariably involve the interactions among neurons throughout all of Visual cortex. One hypothesis is that the timing of neuronal activity, as well as the amplitude of activity, provides a means to encode features of objects. The experimental data from studies on cat [Gray, C. M., Konig, P., Engel, A. K. & Singer, W. (1989) Nature (London) 338, 334-337] support a view in which only synchronous (no phase lags) activity carries information about the Visual scene. In contrast, theoretical studies suggest, on the one hand, the utility of multiple phases within a population of neurons as a means to encode independent Visual features and, on the other hand, the likely existence of timing differences solely on the basis of network dynamics. Here we use widefield imaging in conjunction with voltage-sensitive dyes to record electrical activity from the virtually intact, unanesthetized turtle brain. Our data consist of single-trial measurements. We analyze our data in the frequency domain to isolate coherent events that lie in different frequency bands. Low frequency oscillations (<5 Hz) are seen in both ongoing activity and activity induced by Visual Stimuli. These oscillations propagate parallel to the afferent input. Higher frequency activity, with spectral peaks near 10 and 20 Hz, is seen solely in response to stimulation. This activity consists of plane waves and spiral-like waves, as well as more complex patterns. The plane waves have an average phase gradient of approximately pi/2 radians/mm and propagate orthogonally to the low frequency waves. Our results show that large-scale differences in neuronal timing are present and persistent during Visual processing.
Kenji Kansaku - One of the best experts on this subject based on the ideXlab platform.
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use of high frequency Visual Stimuli above the critical flicker frequency in a ssvep based bmi
Clinical Neurophysiology, 2015Co-Authors: Takeshi Sakurada, Toshihiro Kawase, Tomoaki Komatsu, Kenji KansakuAbstract:Abstract Objective This study presents a new steady-state Visual evoked potential (SSVEP)-based brain–machine interface (BMI) using flickering Visual Stimuli at frequencies greater than the critical flicker frequency (CFF). Methods We first asked participants to fixate on a green/blue flicker (30–70 Hz), and SSVEP amplitude was evaluated. Participants were asked to indicate whether the stimulus was visibly flickering and to report their subjective level of discomfort. We then assessed visibly (41, 43, and 45 Hz) vs. invisibly (61, 63, and 65 Hz) flickering stimulus in an SSVEP-based BMI. Visual fatigue was assessed via the flicker test before and after operation of the BMI. Results Higher frequency Stimuli reduced participants’ subjective discomfort. Participants successfully controlled the SSVEP-based BMI using both the visibly and invisibly flickering Stimuli (93.1% and 88.0%, respectively); the flicker test revealed a decrease in CFF (i.e., Visual fatigue) under the visible condition only (–5.7%, P Conclusions The use of high-frequency Visual Stimuli above the CFF led to high classification accuracy and decreased Visual fatigue in an SSVEP-based BMI. Significance High-frequency flicker Stimuli above the CFF were able to induce SSVEPs and may prove useful in the development of BMI-based assistive products.
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Visual Stimuli for the p300 brain computer interface a comparison of white gray and green blue flicker matrices
Clinical Neurophysiology, 2009Co-Authors: Kouji Takano, Tomoaki Komatsu, Naoki Hata, Yasoichi Nakajima, Kenji KansakuAbstract:Abstract Objective The white/gray flicker matrix has been used as a Visual stimulus for the so-called P300 brain–computer interface (BCI), but the white/gray flash Stimuli might induce discomfort. In this study, we investigated the effectiveness of green/blue flicker matrices as Visual Stimuli. Methods Ten able-bodied, non-trained subjects performed Alphabet Spelling (Japanese Alphabet: Hiragana) using an 8 × 10 matrix with three types of intensification/rest flicker combinations (L, luminance; C, chromatic; LC, luminance and chromatic); both online and offline performances were evaluated. Results The accuracy rate under the online LC condition was 80.6%. Offline analysis showed that the LC condition was associated with significantly higher accuracy than was the L or C condition (Tukey–Kramer, p Conclusions The LC condition, which used the green/blue flicker matrix was associated with better performances in the P300 BCI. Significance The green/blue chromatic flicker matrix can be an efficient tool for practical BCI application.
Manuel Tapia - One of the best experts on this subject based on the ideXlab platform.
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an electrophysiological study on the interaction between emotional content and spatial frequency of Visual Stimuli
Neuropsychologia, 2007Co-Authors: Luis Carretie, Jose A Hinojosa, Sara Lopezmartin, Manuel TapiaAbstract:Previous studies suggest that the magnocellular pathway, a Visual processing system that rapidly provides low spatial frequency information to fast-responding structures such as the amygdala, is more involved in the processing of emotional facial expressions than the parvocellular pathway (which conveys all spatial frequencies). The present experiment explored the spatio-temporal characteristics of the spatial frequency modulation of affect-related neural processing, as well as its generalizability to non-facial Stimuli. To that aim, the event-related potentials (ERPs) elicited by low-pass filtered (i.e., high spatial frequencies are eliminated) and intact non-facial emotional images were recorded from 31 participants using a 60-electrode array. The earliest significant effect of spatial frequency was observed at 135 ms from stimulus onset: N135 component of the ERPs. In line with previous studies, the origin of N135 was localized at secondary Visual areas for low-pass filtered Stimuli and at primary areas for intact Stimuli. Importantly, this component showed an interaction between spatial frequency and emotional content: within low-pass filtered pictures, negative Stimuli elicited the highest N135 amplitudes. By contrast, within intact Stimuli, neutral pictures were those eliciting the highest amplitudes. These results suggest that high spatial frequencies are not essential for the initial affect-related processing of Visual Stimuli, which would mainly rely on low spatial frequency Visual information. According to present data, high spatial frequencies would come into play later on.
Mathieu Bourguignon - One of the best experts on this subject based on the ideXlab platform.
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temporal uncertainty enhances suppression of neural responses to predictable Visual Stimuli
NeuroImage, 2021Co-Authors: Sanjeev Nara, Mikel Lizarazu, Craig G Richter, Diana C Dima, Radoslaw Martin Cichy, Mathieu Bourguignon, Nicola MolinaroAbstract:Abstract Contextual information triggers predictions about the content (“what”) of environmental Stimuli to update an internal generative model of the surrounding world. However, Visual information dynamically changes across time, and temporal predictability (“when”) may influence the impact of internal predictions on Visual processing. In this magnetoencephalography (MEG) study, we investigated how processing feature specific information (“what”) is affected by temporal predictability (“when”). Participants (N = 16) were presented with four consecutive Gabor patches (entrainers) with constant spatial frequency but with variable orientation and temporal onset. A fifth target Gabor was presented after a longer delay and with higher or lower spatial frequency that participants had to judge. We compared the neural responses to entrainers where the Gabor orientation could, or could not be temporally predicted along the entrainer sequence, and with inter-entrainer timing that was constant (predictable), or variable (unpredictable). We observed suppression of evoked neural responses in the Visual cortex for predictable Stimuli. Interestingly, we found that temporal uncertainty increased expectation suppression. This suggests that in temporally uncertain scenarios the neurocognitive system invests less resources in integrating bottom-up information. Multivariate pattern analysis showed that predictable Visual features could be decoded from neural responses. Temporal uncertainty did not affect decoding accuracy for early Visual responses, with the feature specificity of early Visual neural activity preserved across conditions. However, decoding accuracy was less sustained over time for temporally jittered than for isochronous predictable Visual Stimuli. These findings converge to suggest that the cognitive system processes Visual features of temporally predictable Stimuli in higher detail, while processing temporally uncertain Stimuli may rely more heavily on abstract internal expectations.
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temporal uncertainty enhances suppression of neural responses to predictable Visual Stimuli
bioRxiv, 2021Co-Authors: Sanjeev Nara, Mikel Lizarazu, Craig G Richter, Diana C Dima, Radoslaw Martin Cichy, Mathieu Bourguignon, Nicola MolinaroAbstract:Predictive processing has been proposed as a fundamental cognitive mechanism to account for how the brain interacts with the external environment via its sensory systems. In vision, contextual information triggers predictions about the content (″what″) of environmental Stimuli to update an internal generative model of the surrounding world. However, Visual information dynamically changes across time, and temporal predictability (″when″) may influence the impact of internal predictions on Visual processing. In this magnetoencephalography (MEG) study, we investigated how processing feature specific information (″what″) is affected by temporal predictability (″when″). In line with previous findings, we observed suppression of evoked neural responses in the Visual cortex for predictable Stimuli. Interestingly, we found that temporal uncertainty increased expectation suppression. This suggests that in temporally uncertain scenarios the neurocognitive system invests less resources in integrating bottom-up information. Multivariate pattern analysis showed that predictable Visual features could be decoded from neural responses. Temporal uncertainty did not affect decoding accuracy for early Visual responses, with the feature specificity of early Visual neural activity preserved across conditions. However, decoding accuracy was less sustained over time for temporally jittered than for isochronous predictable Visual Stimuli. These findings converge to suggest that the cognitive system processes Visual features of temporally predictable Stimuli in higher detail, while processing temporally uncertain Stimuli may rely more heavily on abstract internal expectations.
