# Emergence of the Affect from the Variation in the Whole-Brain Flow of Information

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## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

#### 2.1. The Dataset

#### 2.2. Data Selection and Validation

#### 2.3. Causal Density and Causal Flow Computations

#### 2.4. Statistical Analysis

#### 2.4.1. Correlation

**Hypothesis**

**1 (H1).**

**Hypothesis**

**2 (H2).**

#### 2.4.2. Test of Significance

**Hypothesis**

**3 (H3).**

**Hypothesis**

**4 (H4).**

**Hypothesis**

**5 (H5).**

**Hypothesis**

**6 (H6).**

#### 2.4.3. Importance of Channels’ Unit Causal Densities

**Hypothesis**

**7 (H7).**

**Hypothesis**

**8 (H8).**

#### 2.5. Ethics Statement

## 3. Results

#### 3.1. Correlation

#### 3.2. Unit Causal Density

#### 3.3. Unit Causal Flow

#### 3.4. Importance of Channels’ Unit Causal Densities

## 4. Discussion

## 5. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## Appendix A. Correlations Prior to One-Sample Bootstrap Test Correction of Unit Causal Densities

**Figure A1.**Paired Spearman correlation between participants’ ucd values and prior to considering the ucd values above the upper bound of their 95.0% confidence interval. (

**A**) Positive versus Negative; (

**B**) Positive versus Neutral; (

**C**) Negative versus Neutral. The subplots on the right column correspond to the bootstrap correlation test (10,000 simulation runs) at 95.0% confidence interval. Values associated with the right-column subplots are given in Table A1.

**Table A1.**Bootstrap (10,000 simulation runs) 95.0% confidence intervals (CI) associated with the Spearman correlation between Negative, Neutral, and Positive affects. These correlations were calculated prior to considering the ucd values above the upper bound of their 95.0% confidence interval.

Conditions | r | p (Two-Tailed) | CI${}_{95\%}$ |
---|---|---|---|

Positive vs. Negative | 0.66 | 0.00001 | [0.61 0.71] |

ine Positive vs. Neutral | 0.69 | 0.00001 | [0.65 0.73] |

ine Negative vs. Neutral | 0.60 | 0.00001 | [0.55 0.65] |

## Appendix B. Channel-Wise Wilcoxon Test of Significant Difference between the Information Flow in Negative, Neutral, and Positive Affects

**Table A2.**Positive versus Neutral channel-wise paired Wilcoxon rank sum test. Columns p, W(122), and r correspond to the Wilcoxon’s p-values, test-statistics, and effect size. Mean and standard deviation of each of these affect states are their respective M and SD columns. Neutral > Positive and Positive > Neutral refer to the cases in which channels’ information flow in Neutral/Positive were higher than Positive/Neutral. This table corresponds to Figure 5 in Section 3.3.

Condition | Channel | p < | Effect Size | W(122) | M${}_{\mathit{Positive}}$ | SD${}_{\mathit{Positive}}$ | M${}_{\mathit{Neutral}}$ | SD${}_{\mathit{Neutral}}$ |
---|---|---|---|---|---|---|---|---|

Neutral > Positive | F5 | 0.01 | 3.04 | 0.27 | 0.03 | 0.04 | 0.03 | 0.05 |

F4 | 0.05 | 2.00 | 0.18 | 0.007 | 0.01 | 0.009 | 0.01 | |

F6 | 0.001 | 3.54 | 0.32 | 0.02 | 0.03 | 0.03 | 0.05 | |

FC3 | 0.03 | 2.71 | 0.24 | 0.02 | 0.02 | 0.02 | 0.02 | |

C2 | 0.05 | 2.13 | 0.19 | 0.09 | 0.08 | 0.01 | 0.01 | |

C4 | 0.03 | 2.59 | 0.23 | 0.01 | 0.01 | 0.02 | 0.02 | |

CPZ | 0.001 | 3.52 | 0.32 | 0.03 | 0.02 | 0.05 | 0.03 | |

CP6 | 0.03 | 2.58 | 0.23 | 0.01 | 0.02 | 0.02 | 0.02 | |

TP8 | 0.05 | 2.05 | 0.18 | 0.03 | 0.04 | 0.04 | 0.05 | |

Positive > Neutral | FT7 | 0.0001 | 4.17 | 0.37 | 0.05 | 0.07 | 0.02 | 0.02 |

FT8 | 0.05 | 2.09 | 0.19 | 0.05 | 0.08 | 0.03 | 0.03 | |

TP7 | 0.03 | 2.55 | 0.23 | 0.03 | 0.03 | 0.02 | 0.03 | |

CP3 | 0.03 | 2.22 | 0.20 | 0.08 | 0.01 | 0.08 | 0.01 | |

P5 | 0.00001 | 6.82 | 0.61 | 0.02 | 0.02 | 0.004 | 0.01 | |

P1 | 0.001 | 3.70 | 0.33 | 0.08 | 0.01 | 0.004 | 0.005 | |

P4 | 0.00001 | 4.58 | 0.41 | 0.01 | 0.01 | 0.002 | 0.003 | |

P6 | 0.00001 | 5.40 | 0.48 | 0.02 | 0.03 | 0.01 | 0.01 | |

P8 | 0.03 | 2.29 | 0.21 | 0.03 | 0.05 | 0.02 | 0.03 | |

PO5 | 0.00001 | 8.47 | 0.76 | 0.003 | 0.003 | 0.001 | 0.001 | |

POZ | 0.00001 | 8.00 | 0.72 | 0.01 | 0.01 | 0.001 | 0.002 | |

PO6 | 0.05 | 2.00 | 0.18 | 0.001 | 0.002 | 0.0004 | 0.001 | |

OZ | 0.0001 | 4.10 | 0.37 | 0.02 | 0.03 | 0.01 | 0.012 | |

O2 | 0.01 | 2.94 | 0.26 | 0.01 | 0.01 | 0.01 | 0.01 |

**Table A3.**Positive versus Negative channel-wise paired Wilcoxon rank sum test. Columns p, W(122), and r correspond to the Wilcoxon’s p-values, test-statistics, and effect size. Mean and standard deviation of each of these affect states are their respective M and SD columns. Negative > Positive and Positive > Negative refer to the cases in which channels’ information flow in Negative/Positive were higher than Positive/Negative. This table corresponds to Figure 6 in Section 3.3.

Condition | Channel | p < | Effect Size | W(122) | M${}_{\mathit{Positive}}$ | SD${}_{\mathit{Positive}}$ | M${}_{\mathit{Neutral}}$ | SD${}_{\mathit{Neutral}}$ |
---|---|---|---|---|---|---|---|---|

Negative > Positive | F5 | 0.01 | 2.72 | 0.24 | 0.03 | 0.04 | 0.03 | 0.05 |

F3 | 0.001 | 4.03 | 0.36 | 0.002 | 0.003 | 0.01 | 0.01 | |

F6 | 0.00001 | 4.76 | 0.43 | 0.02 | 0.03 | 0.03 | 0.05 | |

FT7 | 0.03 | 2.50 | 0.22 | 0.05 | 0.07 | 0.07 | 0.09 | |

FC3 | 0.03 | 2.63 | 0.24 | 0.018 | 0.02 | 0.024 | 0.02 | |

FC2 | 0.03 | 2.56 | 0.23 | 0.005 | 0.01 | 0.007 | 0.01 | |

C3 | 0.05 | 2.15 | 0.19 | 0.02 | 0.02 | 0.02 | 0.02 | |

CP3 | 0.05 | 2.03 | 0.18 | 0.007 | 0.01 | 0.008 | 0.01 | |

CPZ | 0.05 | 2.12 | 0.19 | 0.03 | 0.02 | 0.04 | 0.02 | |

CP6 | 0.01 | 2.94 | 0.26 | 0.01 | 0.019 | 0.021 | 0.02 | |

O2 | 0.01 | 2.75 | 0.25 | 0.009 | 0.012 | 0.012 | 0.01 | |

FP1 | 0.03 | 2.50 | 0.22 | 0.02 | 00.02 | 0.01 | 0.01 | |

FPZ | 0.05 | 2.19 | 0.20 | 0.013 | 0.02 | 0.007 | 0.014 | |

F7 | 0.01 | 3.34 | 0.30 | 0.014 | 0.01 | 0.009 | 0.01 | |

F1 | 0.001 | 3.50 | 0.31 | 0.01 | 0.01 | 0.003 | 0.01 | |

F2 | 0.0001 | 4.15 | 0.37 | 0.002 | 0.003 | 0.001 | 0.001 | |

Positive > Negative | F4 | 0.03 | 2.63 | 0.24 | 0.007 | 0.01 | 0.004 | 0.01 |

C4 | 0.03 | 2.72 | 0.24 | 0.014 | 0.01 | 0.010 | 0.01 | |

T8 | 0.01 | 3.12 | 0.28 | 0.06 | 0.08 | 0.03 | 0.03 | |

TP7 | 0.01 | 2.76 | 0.25 | 0.029 | 0.03 | 0.018 | 0.02 | |

CP2 | 0.03 | 2.47 | 0.22 | 0.005 | 0.005 | 0.003 | 0.003 | |

CP4 | 0.03 | 2.26 | 0.20 | 0.007 | 0.01 | 0.005 | 0.01 | |

P7 | 0.03 | 2.51 | 0.23 | 0.04 | 0.04 | 0.03 | 0.04 | |

P5 | 0.01 | 2.59 | 0.23 | 0.02 | 0.02 | 0.01 | 0.01 | |

P3 | 0.01 | 2.66 | 0.24 | 0.007 | 0.01 | 0.003 | 0.004 | |

P1 | 0.001 | 4.05 | 0.36 | 0.007 | 0.01 | 0.003 | 0.004 | |

P2 | 0.03 | 3.21 | 0.29 | 0.007 | 0.01 | 0.003 | 0.004 | |

P4 | 0.05 | 2.14 | 0.19 | 0.008 | 0.01 | 0.004 | 0.005 | |

PO5 | 0.03 | 2.23 | 0.20 | 0.003 | 0.003 | 0.003 | 0.002 | |

PO8 | 0.01 | 2.67 | 0.24 | 0.019 | 0.03 | 0.009 | 0.01 | |

OZ | 0.01 | 3.21 | 0.29 | 0.02 | 0.03 | 0.01 | 0.01 |

**Table A4.**Negative versus Neutral channel-wise paired Wilcoxon rank sum test. Columns p, W(122), and r correspond to the Wilcoxon’s p-values, test-statistics, and effect size. Mean and standard deviation of each of these affect states are their respective M and SD columns. Neutral > Negative and Negative > Neutral refer to the cases in which channels’ information flow in Neutral/Negative were higher than Negative/Neutral. This table corresponds to Figure 7 in Section 3.3.

Condition | Channel | p < | Effect Size (r) | W(122) | M${}_{\mathit{Positive}}$ | SD${}_{\mathit{Positive}}$ | M${}_{\mathit{Neutral}}$ | SD${}_{\mathit{Neutral}}$ |
---|---|---|---|---|---|---|---|---|

Neutral > Negative | FPZ | 0.05 | 2.06 | 0.19 | 0.007 | 0.01 | 0.009 | 0.01 |

F1 | 0.0001 | 4.23 | 0.38 | 0.003 | 0.01 | 0.006 | 0.01 | |

F2 | 0.01 | 2.90 | 0.26 | 0.0007 | 0.001 | 0.0013 | 0.002 | |

F4 | 0.0001 | 4.36 | 0.39 | 0.004 | 0.005 | 0.009 | 0.01 | |

FCZ | 0.01 | 2.92 | 0.26 | 0.005 | 0.01 | 0.010 | 0.01 | |

C4 | 0.0001 | 4.24 | 0.38 | 0.01 | 0.01 | 0.02 | 0.02 | |

T8 | 0.01 | 2.62 | 0.24 | 0.03 | 0.03 | 0.04 | 0.06 | |

CP2 | 0.01 | 3.04 | 0.28 | 0.003 | 0.003 | 0.006 | 0.005 | |

Negative > Neutral | F3 | 0.01 | 2.65 | 0.24 | 0.005 | 0.01 | 0.003 | 0.004 |

FZ | 0.03 | 2.38 | 0.21 | 0.006 | 0.01 | 0.003 | 0.01 | |

FT7 | 0.00001 | 5.62 | 0.50 | 0.07 | 0.09 | 0.02 | 0.02 | |

FT8 | 0.001 | 3.54 | 0.32 | 0.05 | 0.06 | 0.03 | 0.03 | |

CP3 | 0.001 | 3.42 | 0.31 | 0.008 | 0.01 | 0.007 | 0.01 | |

P5 | 0.000001 | 4.92 | 0.44 | 0.01 | 0.01 | 0.004 | 0.01 | |

P4 | 0.01 | 2.58 | 0.23 | 0.004 | 0.005 | 0.002 | 0.003 | |

P6 | 0.00001 | 4.57 | 0.41 | 0.01 | 0.01 | 0.01 | 0.01 | |

PO5 | 0.000001 | 7.59 | 0.68 | 0.002 | 0.002 | 0.0001 | 0.001 | |

PO3 | 0.03 | 2.45 | 0.22 | 0.01 | 0.01 | 0.006 | 0.01 | |

POZ | 0.000001 | 7.65 | 0.69 | 0.007 | 0.01 | 0.001 | 0.002 | |

PO4 | 0.03 | 2.20 | 0.20 | 0.007 | 0.01 | 0.005 | 0.01 | |

PO6 | 0.001 | 3.54 | 0.32 | 0.002 | 0.003 | 0.0005 | 0.001 | |

CB1 | 0.03 | 2.23 | 0.20 | 0.013 | 0.02 | 0.011 | 0.02 | |

O2 | 0.00001 | 4.64 | 0.42 | 0.01 | 0.01 | 0.006 | 0.01 |

## Appendix C. Channel-Wise Bootstrap Test of Significant Difference between the Information Flow in Negative, Neutral, and Positive Affects

**Figure A2.**Paired two-sample bootstrap test of significance (10,000 simulation runs) at 95.0% (i.e., p < 0.05) confidence interval (CI) between Positive and Neutral Information Flow. In these subplots, the blue line marks the null hypothesis $H0$ i.e., non-significant difference between the two states’ ucd values. The red lines are the boundaries of the 95.0% confidence interval. The yellow line shows the location of the average mean difference between two affect states for 10,000 simulation runs.

**Figure A3.**Paired two-sample bootstrap test of significance (10,000 simulation runs) at 95.0% (i.e., p < 0.05) confidence interval (CI) between Positive and Negative Information Flow. In these subplots, the blue line marks the null hypothesis $H0$ i.e., non-significant difference between the two states’ ucd values. The red lines are the boundaries of the 95.0% confidence interval. The yellow line shows the location of the average mean difference between two affect states for 10,000 simulation runs.

**Figure A4.**Paired two-sample bootstrap test of significance (10,000 simulation runs) at 95.0% (i.e., p < 0.05) confidence interval (CI) between Negative and Neutral Information Flow. In these subplots, the blue line marks the null hypothesis $H0$ i.e., non-significant difference between the two states’ ucd values. The red lines are the boundaries of the 95.0% confidence interval. The yellow line shows the location of the average mean difference between two affect states for 10,000 simulation runs.

**Table A5.**Positive versus Neutral channel-wise paired two-sample bootstrap test (10,000 simulation runs) at 95.0% confidence interval (CI) applied on the directional information flow. M and SD refer to the mean difference and the standard deviation of such a difference between the two compared states. CI shows the 95% confidence interval of their difference. Bold entry rows indicates the significant difference.

Conditions | M${}_{\mathit{difference}}$ | SD${}_{\mathit{difference}}$ | 95.0% CI${}_{\mathit{difference}}$ |
---|---|---|---|

F5 | −0.004 | 0.01 | [−0.02 0.01] |

F4 | −0.002 | 0.002 | [−0.005 0.002] |

F6 | −0.01 | 0.01 | [−0.03 0.003] |

FC3 | −0.005 | 0.004 | [−0.01 0.002] |

C2 | −0.003 | 0.002 | [−0.006 0.0001] |

C4 | −0.01 | 0.003 | [−0.01 0.0] |

CPZ | −0.02 | 0.004 | [−0.02 −0.008] |

CP6 | −0.006 | 0.004 | [−0.013 0.0013] |

TP8 | −0.01 | 0.008 | [−0.02 0.005] |

FT7 | 0.03 | 0.01 | [0.01 0.05] |

FT8 | 0.02 | 0.01 | [0.003 0.05] |

TP7 | 0.008 | 0.006 | [−0.003 0.02] |

CP3 | 0.0005 | 0.002 | [−0.004 0.005] |

P5 | 0.01 | 0.002 | [0.007 0.02] |

P1 | 0.003 | 0.001 | [0.001 0.006] |

P4 | 0.006 | 0.001 | [0.004 0.01] |

P6 | 0.02 | 0.003 | [0.01 0.02] |

P8 | 0.01 | 0.01 | [−0.001 0.03] |

PO5 | 0.003 | 0.0004 | [0.002 0.004] |

POZ | 0.01 | 0.002 | [0.007 0.014] |

PO6 | 0.001 | 0.0002 | [0.0002 0.001] |

OZ | 0.012 | 0.004 | [0.005 0.02] |

O2 | 0.003 | 0.002 | [−0.001 0.01] |

**Table A6.**Positive versus Negative channel-wise paired two-sample bootstrap test (10,000 simulation runs) at 95.0% confidence interval (CI) applied on the directional information flow. M and SD refer to the mean difference and the standard deviation of such a difference between the two compared states. CI shows the 95% confidence interval of their difference. Bold entry rows indicates the significant difference.

Conditions | M${}_{\mathit{difference}}$ | SD${}_{\mathit{difference}}$ | 95.0% CI${}_{\mathit{difference}}$ |
---|---|---|---|

F5 | −0.06 | 0.01 | [−0.02 0.01] |

F3 | −0.003 | 0.001 | [−0.004 −0.001] |

F6 | −0.01 | 0.01 | [−0.03 −0.001] |

FC3 | −0.01 | 0.004 | [−0.01 0.002] |

FT7 | −0.02 | 0.01 | [−0.04 0.01] |

FC2 | −0.002 | 0.001 | [−0.004 0.0003] |

C3 | −0.003 | 0.003 | [−0.01 0.003] |

CP3 | −0.001 | 0.002 | [−0.005 0.003] |

CPZ | −0.009 | 0.004 | [−0.02 −0.001] |

CP6 | −0.008 | 0.004 | [−0.02 −0.001] |

O2 | −0.003 | 0.002 | [−0.01 0.001] |

FP1 | 0.01 | 0.003 | [0.002 0.02] |

FPZ | 0.01 | 0.003 | [−0.0004 0.012] |

F7 | 0.004 | 0.002 | [0.001 0.008] |

F1 | 0.002 | 0.001 | [0.0 0.004] |

F2 | 0.001 | 0.0004 | [0.001 0.002] |

F4 | 0.003 | 0.001 | [0.001 0.01] |

C4 | 0.004 | 0.002 | [0.0 0.01] |

T8 | 0.03 | 0.01 | [0.01 0.05] |

TP7 | 0.01 | 0.01 | [0.001 0.02] |

CP2 | 0.002 | 0.001 | [0.001 0.004] |

CP4 | 0.001 | 0.001 | [−0.002 0.004] |

P7 | 0.01 | 0.01 | [−0.01 0.02] |

P5 | 0.006 | 0.003 | [0.001 0.011] |

P3 | 0.003 | 0.001 | [0.001 0.01] |

P1 | 0.004 | 0.001 | [0.002 0.01] |

P2 | 0.003 | 0.001 | [0.001 0.005] |

P4 | 0.004 | 0.002 | [0.001 0.01] |

PO5 | 0.001 | 0.0004 | [0.0004 0.002] |

PO8 | 0.011 | 0.004 | [0.003 0.02] |

OZ | 0.011 | 0.004 | [0.003 0.02] |

**Table A7.**Negative versus Neutral channel-wise paired two-sample bootstrap test (10,000 simulation runs) at 95.0% confidence interval (CI) applied on the directional information flow. M and SD refer to the mean difference and the standard deviation of such a difference between the two compared states. CI shows the 95% confidence interval of their difference. Bold entry rows indicates the significant difference.

Conditions | M${}_{\mathit{difference}}$ | SD${}_{\mathit{difference}}$ | 95.0% CI${}_{\mathit{difference}}$ |
---|---|---|---|

FPZ | −0.002 | 0.002 | [−0.007 0.002] |

F1 | −0.003 | 0.001 | [−0.005 −0.001] |

F2 | −0.001 | 0.0002 | [−0.001 0.0] |

F4 | −0.005 | 0.001 | [−0.008 −0.002] |

FCZ | −0.004 | 0.001 | [−0.007 −0.002] |

C4 | −0.01 | 0.003 | [−0.02 −0.004] |

T8 | −0.02 | 0.01 | [−0.04 0.0] |

CP2 | −0.003 | 0.001 | [−0.004 −0.001] |

F3 | 0.002 | 0.001 | [0.0 0.004] |

FZ | 0.003 | 0.001 | [0.0 0.01] |

FT7 | 0.05 | 0.01 | [0.03 0.07] |

FT8 | 0.02 | 0.01 | [0.01 0.04] |

CP3 | 0.001 | 0.002 | [−0.003 0.005] |

P5 | 0.01 | 0.002 | [0.003 0.01] |

P4 | 0.002 | 0.001 | [0.001 0.003] |

P6 | 0.01 | 0.002 | [0.005 0.012] |

PO5 | 0.002 | 0.0002 | [0.0015 0.0023] |

PO3 | 0.003 | 0.002 | [0.0 0.01] |

POZ | 0.01 | 0.001 | [0.004 0.007] |

PO4 | 0.002 | 0.001 | [0.0 0.005] |

PO6 | 0.001 | 0.0004 | [0.0 0.002] |

CB1 | 0.002 | 0.003 | [−0.004 0.01] |

O2 | 0.01 | 0.002 | [0.002 0.009] |

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**Figure 1.**(

**A**) schematic diagram of an experiment as described in [65]. Each experiment included a total of fifteen movie clips (i.e., n = 15, audiovisual), per participant. In this setting, each movie clip was proceeded with a five-second hint to prepare the participants for its start. This was then followed by a four-minute movie clip. At the end of each movie clip, the participants were asked to answer three questions that followed the Philippot [78]. These questions were the type of emotion that the participants actually felt while watching the movie clips, whether they watched the original movies from which the clips were taken, and whether they understood the content of those clips. The participants responded to these three questions by scoring them in the scale of 1 to 5; (

**B**) arrangement of the EEG electrodes in this experiment. The sixty-two EEG channels were: FP1, FPZ, FP2, AF3, AF4, F7, F5, F3, F1, FZ, F2, F4, F6, F8, FT7, FC5, FC3, FC1, FCZ, FC2, FC4, FC6, FT8, T7, C5, C3, C1, CZ, C2, C4, C6, T8, TP7, CP5, CP3, CP1, CPZ, CP2, CP4, CP6, TP8, P7, P5, P3, P1, PZ, P2, P4, P6, P8, PO7, PO5, PO3, POZ, PO4, PO6, PO8, CB1, O1, OZ, O2, CB2.

**Figure 2.**Paired Spearman correlation between participants’ unit causal density (ucd) values (

**A**) Positive versus Negative; (

**B**) Positive versus Neutral; (

**C**) Negative versus Neutral. The subplots on the right column correspond to the bootstrap correlation test (10,000 simulation runs) at 95.0% confidence interval. In these subplots, the zeros correspond to the ucd values that were below the significant level of 0.7 i.e., the upper bound of the one-sample test of significance (10,000 simulation runs) at 95.0% confidence interval (Mean (M) = 0.69, Standard Deviation (SD) = 0.30, Confidence Interval (CI)${}_{95.0\%}$ = [0.68 0.70]). For results prior to the application of the bootstrap test to determine the ucd values’ significant level, see Appendix A.

**Figure 3.**(

**A**) grand averages of the spatial map of unit causal density (ucd) in Negative, Neutral, and Positive affects states. Incremental pattern of ucd values from Negative to Positive affect is evident in these subplots; (

**B**) EEG channels’ arrangement associated with distribution of ucd values; (

**C**) descriptive statistics of the ucd values in Negative, Neutral, and Positive affects states. Asterisks mark the significant differences between these values.

**Figure 4.**Paired two-sample bootstrap test of significance (10,000 simulation runs) at 95.0% (i.e., p < 0.05) confidence interval (CI) associated with the participants’ whole-brain unit causal densities (ucd). Compared pairs of affect are (

**A**) Positive versus Neutral; (

**B**) Positive versus Negative; and (

**C**) Negative versus Neutral. In these subplots, the x-axis shows ${\mu}_{i}-{\mu}_{j},\phantom{\rule{3.33333pt}{0ex}}i\ne j$ where i and j refer to one of the Negative, Neutral, or Positive affect states. The blue line marks the null hypothesis $H0$ i.e., non-significant difference between the two states’ ucd values. The red lines are the boundaries of the 95.0% confidence interval. The yellow line shows the location of the average ${\mu}_{i}-{\mu}_{j},\phantom{\rule{3.33333pt}{0ex}}i\ne j$ for 10,000 simulation runs.

**Figure 5.**Negative affect’s channel-wise information flow. These subplots identify a bi-hemispheric brain activity in response to Negative affect. They also show that a number of channels are associated with higher short- as well as long-range information (e.g., F5, FC5, FT7, FC6, F8, F6, CZ’, CPZ, CB2). Although these channels appear to have higher local influence in the form of information flow, their corresponding flow of information extend beyond their designated hemispheres, thereby indicating the presence of cross-hemispheric whole-brain information flow and communication. The values in these subplots are scaled within $[0,\cdots ,1]$ for better comparison.

**Figure 6.**Neutral affect’s channel-wise information flow. These subplots identify a bi-hemispheric brain activity in response to Neutral affect. They also show that a number of channels are associated with higher short- as well as long-range information (e.g., F6, F8, FC5, FC6, CZ, CP5, T8, CB2). Although these channels appear to have higher local influence in the form of information flow, their corresponding flow of information extend beyond their designated hemispheres, thereby indicating the presence of cross-hemispheric whole-brain information flow and communication. The values in these subplots are scaled within $[0,\cdots ,1]$ for better comparison.

**Figure 7.**Positive affect’s channel-wise information flow. These subplots identify a bi-hemispheric brain activity in response to a Positive affect. They also show that a number of channels are associated with higher short- as well as long-range information (e.g., F8, FT7, FC5, FC6, FC8, C5, CZ, C6, CP5, CB2). Although these channels appear to have higher local influence in the form of information flow, their corresponding flow of information extend beyond their designated hemispheres, thereby indicating the presence of cross-hemispheric whole-brain information flow and communication. The values in these subplots are scaled within $[0,\cdots ,1]$ for better comparison.

**Figure 8.**(

**A**) spatial map of feature importance by Adaboost meta-estimator pertinent to the trained Adaboost meta-estimator on the ucd values associated with Negative, Neutral, and Positive affects (one-sample bootstrap test of significance at 95% confidence interval: M = 0.13, SD = 0.03, CI = [0.08 0.21]). The right subplot shows the EEG channels’ arrangement; (

**B**) Adaboost prediction accuracy in Negative, Neutral, and Positive affects in 1-holdout setting using whole-brain ucd values; (

**C**) Adaboost prediction accuracy in Negative, Neutral, and Positive affects in 1-holdout setting using subset of channels with their importance within or above the one-sample bootstrap test of significance (10,000 simulation runs) at 95.0% confidence interval on these feature importance values. In (

**B**,

**C**), the correct predictions, per affect, are the diagonal entries of these tables and the off-diagonal entries show the percentage of each of the affects that was misclassified (e.g., Positive affect misclassified as Negative affect).

**Table 1.**Bootstrap (10,000 simulation runs) 95.0% confidence intervals (CI) associated with the Spearman correlation between Negative, Neutral, and Positive affects.

Conditions | r | p (Two-Tailed) | CI${}_{95\%}$ |
---|---|---|---|

Positive vs. Negative | 0.58 | 0.00001 | [0.53 0.63] |

ine Positive vs. Neutral | 0.58 | 0.00001 | [0.53 0.63] |

ine Negative vs. Neutral | 0.53 | 0.00001 | [0.47 0.59] |

**Table 2.**Paired two-sample bootstrap test of significance (10,000 simulation runs) at 95.0% confidence interval (CI) associated with the participants’ whole-brain unit causal density (ucd) values. Compared pairs of affect are: Positive versus Neutral, Positive versus Negative, and Negative versus Neutral. M and SD refer to the mean difference and the standard deviation of such a difference between the two compared states. CI shows the 95% confidence interval of their difference. Bold entry rows indicate the significant difference.

Conditions | M${}_{\mathit{difference}}$ | SD${}_{\mathit{difference}}$ | 95.0% CI${}_{\mathit{difference}}$ |
---|---|---|---|

Positive versus Neutral | 0.07 | 0.02 | [0.02 0.11] |

ine Positive versus Negative | 0.09 | 0.02 | [0.04 0.14] |

ine Negative versus Neutral | −0.02 | 0.02 | [−0.07 0.02] |

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**MDPI and ACS Style**

Keshmiri, S.; Shiomi, M.; Ishiguro, H. Emergence of the Affect from the Variation in the Whole-Brain Flow of Information. *Brain Sci.* **2020**, *10*, 8.
https://doi.org/10.3390/brainsci10010008

**AMA Style**

Keshmiri S, Shiomi M, Ishiguro H. Emergence of the Affect from the Variation in the Whole-Brain Flow of Information. *Brain Sciences*. 2020; 10(1):8.
https://doi.org/10.3390/brainsci10010008

**Chicago/Turabian Style**

Keshmiri, Soheil, Masahiro Shiomi, and Hiroshi Ishiguro. 2020. "Emergence of the Affect from the Variation in the Whole-Brain Flow of Information" *Brain Sciences* 10, no. 1: 8.
https://doi.org/10.3390/brainsci10010008