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'My Virtual Dream': Collective Neurofeedback in an Immersive Art Environment.

Kovacevic N, Ritter P, Tays W, Moreno S, McIntosh AR - PLoS ONE (2015)

Bottom Line: While human brains are specialized for complex and variable real world tasks, most neuroscience studies reduce environmental complexity, which limits the range of behaviours that can be explored.The unusually large sample size allowed us to detect unprecedented speed of learning changes in the power spectrum (~ 1 min).Besides revealing these training effects, which are relevant for BCI applications, our results validate a novel platform engaging art and science and fostering the understanding of brains under natural conditions.

View Article: PubMed Central - PubMed

Affiliation: Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada.

ABSTRACT
While human brains are specialized for complex and variable real world tasks, most neuroscience studies reduce environmental complexity, which limits the range of behaviours that can be explored. Motivated to overcome this limitation, we conducted a large-scale experiment with electroencephalography (EEG) based brain-computer interface (BCI) technology as part of an immersive multi-media science-art installation. Data from 523 participants were collected in a single night. The exploratory experiment was designed as a collective computer game where players manipulated mental states of relaxation and concentration with neurofeedback targeting modulation of relative spectral power in alpha and beta frequency ranges. Besides validating robust time-of-night effects, gender differences and distinct spectral power patterns for the two mental states, our results also show differences in neurofeedback learning outcome. The unusually large sample size allowed us to detect unprecedented speed of learning changes in the power spectrum (~ 1 min). Moreover, we found that participants' baseline brain activity predicted subsequent neurofeedback beta training, indicating state-dependent learning. Besides revealing these training effects, which are relevant for BCI applications, our results validate a novel platform engaging art and science and fostering the understanding of brains under natural conditions.

No MeSH data available.


Related in: MedlinePlus

Neurofeedback performance measures.(A) Group mean alpha performance aP and beta performance bP for all participants taken together (yellow bullets), with 95% CI’s shown as error bars, beta learners (gray bullets) and non-learners (white bullets). Conditions where neurofeedback did not depend on the respective band of interest are shown in desaturated color. Black asterisks indicate conditions which expressed reliable PLS difference between learners and non-learners. (B) Analysis of differences in baseline RSP between beta learners and non-learners. Top: mean participant scores with error bars representing 95% CI. Bottom: associated frequency pattern for the left frontal channel with reliable positive (negative) bootstrap ratios indicated by red (blue) circles. High power in delta range and low power in beta/gamma range during baseline predicted subsequent beta learning.
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pone.0130129.g007: Neurofeedback performance measures.(A) Group mean alpha performance aP and beta performance bP for all participants taken together (yellow bullets), with 95% CI’s shown as error bars, beta learners (gray bullets) and non-learners (white bullets). Conditions where neurofeedback did not depend on the respective band of interest are shown in desaturated color. Black asterisks indicate conditions which expressed reliable PLS difference between learners and non-learners. (B) Analysis of differences in baseline RSP between beta learners and non-learners. Top: mean participant scores with error bars representing 95% CI. Bottom: associated frequency pattern for the left frontal channel with reliable positive (negative) bootstrap ratios indicated by red (blue) circles. High power in delta range and low power in beta/gamma range during baseline predicted subsequent beta learning.

Mentions: We evaluated the two performance measures across all conditions. Besides the overall difference between aP and bP due to different threshold settings, we observed striking training-related differences between the two performance measures: while aP mostly stayed at the baseline level throughout the game, bP steadily increased, though with large standard error actross the entire sample (Fig 7A). Percent increase in bP from the start to the end, i.e., from Tutorial-relax to Group-freestyle was taken as the beta training effect, bTE. The mean value of bTE was 87% (SE: 9%). To better understand the large variability in bTE we split the sample into two groups, ‘beta learners’ and ‘beta non-learners’, which we defined according to bTE > 0 and bTE < = 0. There were 201 non-learners and 322 learners. The mean bTE for learners and non-learners were 169% (SE: 13%) and -44% (SE: 2%), respectively, and were statstically different according to the t-test at p<0.001.


'My Virtual Dream': Collective Neurofeedback in an Immersive Art Environment.

Kovacevic N, Ritter P, Tays W, Moreno S, McIntosh AR - PLoS ONE (2015)

Neurofeedback performance measures.(A) Group mean alpha performance aP and beta performance bP for all participants taken together (yellow bullets), with 95% CI’s shown as error bars, beta learners (gray bullets) and non-learners (white bullets). Conditions where neurofeedback did not depend on the respective band of interest are shown in desaturated color. Black asterisks indicate conditions which expressed reliable PLS difference between learners and non-learners. (B) Analysis of differences in baseline RSP between beta learners and non-learners. Top: mean participant scores with error bars representing 95% CI. Bottom: associated frequency pattern for the left frontal channel with reliable positive (negative) bootstrap ratios indicated by red (blue) circles. High power in delta range and low power in beta/gamma range during baseline predicted subsequent beta learning.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4496007&req=5

pone.0130129.g007: Neurofeedback performance measures.(A) Group mean alpha performance aP and beta performance bP for all participants taken together (yellow bullets), with 95% CI’s shown as error bars, beta learners (gray bullets) and non-learners (white bullets). Conditions where neurofeedback did not depend on the respective band of interest are shown in desaturated color. Black asterisks indicate conditions which expressed reliable PLS difference between learners and non-learners. (B) Analysis of differences in baseline RSP between beta learners and non-learners. Top: mean participant scores with error bars representing 95% CI. Bottom: associated frequency pattern for the left frontal channel with reliable positive (negative) bootstrap ratios indicated by red (blue) circles. High power in delta range and low power in beta/gamma range during baseline predicted subsequent beta learning.
Mentions: We evaluated the two performance measures across all conditions. Besides the overall difference between aP and bP due to different threshold settings, we observed striking training-related differences between the two performance measures: while aP mostly stayed at the baseline level throughout the game, bP steadily increased, though with large standard error actross the entire sample (Fig 7A). Percent increase in bP from the start to the end, i.e., from Tutorial-relax to Group-freestyle was taken as the beta training effect, bTE. The mean value of bTE was 87% (SE: 9%). To better understand the large variability in bTE we split the sample into two groups, ‘beta learners’ and ‘beta non-learners’, which we defined according to bTE > 0 and bTE < = 0. There were 201 non-learners and 322 learners. The mean bTE for learners and non-learners were 169% (SE: 13%) and -44% (SE: 2%), respectively, and were statstically different according to the t-test at p<0.001.

Bottom Line: While human brains are specialized for complex and variable real world tasks, most neuroscience studies reduce environmental complexity, which limits the range of behaviours that can be explored.The unusually large sample size allowed us to detect unprecedented speed of learning changes in the power spectrum (~ 1 min).Besides revealing these training effects, which are relevant for BCI applications, our results validate a novel platform engaging art and science and fostering the understanding of brains under natural conditions.

View Article: PubMed Central - PubMed

Affiliation: Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada.

ABSTRACT
While human brains are specialized for complex and variable real world tasks, most neuroscience studies reduce environmental complexity, which limits the range of behaviours that can be explored. Motivated to overcome this limitation, we conducted a large-scale experiment with electroencephalography (EEG) based brain-computer interface (BCI) technology as part of an immersive multi-media science-art installation. Data from 523 participants were collected in a single night. The exploratory experiment was designed as a collective computer game where players manipulated mental states of relaxation and concentration with neurofeedback targeting modulation of relative spectral power in alpha and beta frequency ranges. Besides validating robust time-of-night effects, gender differences and distinct spectral power patterns for the two mental states, our results also show differences in neurofeedback learning outcome. The unusually large sample size allowed us to detect unprecedented speed of learning changes in the power spectrum (~ 1 min). Moreover, we found that participants' baseline brain activity predicted subsequent neurofeedback beta training, indicating state-dependent learning. Besides revealing these training effects, which are relevant for BCI applications, our results validate a novel platform engaging art and science and fostering the understanding of brains under natural conditions.

No MeSH data available.


Related in: MedlinePlus