## Bar Charts: Brain Alignment Comparison ### Overview The image presents two sets of bar charts, (a) and (b), comparing brain alignment under different conditions. The x-axis represents different experimental setups (Linear, CKA, RSA, Contextualization, No Contextualization), while the y-axis represents brain alignment scores. The charts compare "Pretrained | Original Stimuli", "Pretrained | Random Stimuli (= Length)", and "Untrained | Original Stimuli". Statistical significance is indicated by asterisks above the bars. ### Components/Axes **Chart (a):** * **Title:** Linear, CKA, RSA * **Y-axis Title:** Brain Alignment (Pearson's r) * **Y-axis Scale:** 0.00 to 0.14 (Linear, RSA), 0.00 to 0.30 (CKA), incrementing by 0.02 (Linear, RSA) and 0.05 (CKA) * **X-axis:** Categorical, representing different experimental setups: Linear, CKA, RSA * **Legend (bottom):** * Light Green: Pretrained | Original Stimuli * Medium Green: Pretrained | Random Stimuli (= Length) * Dark Green: Untrained | Original Stimuli **Chart (b):** * **Title:** Contextualization, No Contextualization * **Y-axis Title:** Brain Alignment * **Y-axis Scale:** 0.0 to 0.7 (Contextualization), 0.0 to 1.0 (No Contextualization), incrementing by 0.1 * **X-axis:** Categorical, representing different experimental setups: Contextualization, No Contextualization * **Legend (bottom):** Same as Chart (a) ### Detailed Analysis **Chart (a):** * **Linear:** * Pretrained | Original Stimuli (Light Green): ~0.13, with error bar extending to ~0.14 * Pretrained | Random Stimuli (= Length) (Medium Green): ~0.01, with error bar extending to ~0.02 * Untrained | Original Stimuli (Dark Green): ~0.07, with error bar extending to ~0.08 * **CKA:** * Pretrained | Original Stimuli (Light Green): ~0.19, with error bar extending to ~0.21 * Pretrained | Random Stimuli (= Length) (Medium Green): ~0.16, with error bar extending to ~0.17 * Untrained | Original Stimuli (Dark Green): ~0.28, with error bar extending to ~0.30 * **RSA:** * Pretrained | Original Stimuli (Light Green): ~0.09, with error bar extending to ~0.10 * Pretrained | Random Stimuli (= Length) (Medium Green): ~0.02, with error bar extending to ~0.03 * Untrained | Original Stimuli (Dark Green): ~0.14, with error bar extending to ~0.15 **Chart (b):** * **Contextualization:** * Pretrained | Original Stimuli (Light Green): ~0.69, with error bar extending to ~0.71 * Pretrained | Random Stimuli (= Length) (Medium Green): ~0.16, with error bar extending to ~0.17 * Untrained | Original Stimuli (Dark Green): ~0.70, with error bar extending to ~0.72 * **No Contextualization:** * Pretrained | Original Stimuli (Light Green): ~1.01, with error bar extending to ~1.03 * Pretrained | Random Stimuli (= Length) (Medium Green): ~0.17, with error bar extending to ~0.18 * Untrained | Original Stimuli (Dark Green): ~0.47, with error bar extending to ~0.49 ### Key Observations * In Chart (a), for Linear and RSA, "Pretrained | Original Stimuli" shows the highest brain alignment, while "Pretrained | Random Stimuli (= Length)" shows the lowest. For CKA, "Untrained | Original Stimuli" shows the highest brain alignment. * In Chart (b), for both Contextualization and No Contextualization, "Pretrained | Original Stimuli" shows the highest brain alignment, while "Pretrained | Random Stimuli (= Length)" shows the lowest. * Statistical significance (****) is indicated above the bars in all sub-charts, suggesting significant differences between the groups being compared. ### Interpretation The data suggests that brain alignment varies significantly depending on the experimental setup (Linear, CKA, RSA, Contextualization, No Contextualization) and the type of stimuli used (Original vs. Random) in both pretrained and untrained models. The high brain alignment observed with "Pretrained | Original Stimuli" in most cases indicates that pretraining on original stimuli leads to better alignment with brain activity. The lower alignment with "Pretrained | Random Stimuli (= Length)" suggests that random stimuli, even when matched in length, do not elicit the same level of brain alignment as original stimuli. The performance of "Untrained | Original Stimuli" varies, sometimes showing comparable alignment to pretrained models (e.g., Contextualization) and sometimes showing lower alignment (e.g., Linear, RSA). The statistical significance (****) highlights that these differences are not due to random chance, but rather reflect genuine effects of the experimental manipulations.

\n ## Bar Charts: Brain Alignment Comparison ### Overview The image presents two sets of bar charts (labeled (a) and (b)) comparing brain alignment scores under different conditions and using different alignment metrics. Chart (a) compares alignment for "Pretrained | Original Stimuli" vs. "Pretrained | Random Stimuli (= Length)" using Linear, CKA, and RSA metrics. Chart (b) compares "Untrained | Original Stimuli" with a baseline. Error bars are present on all bars, and significance is indicated with asterisks. ### Components/Axes **Chart (a):** * **X-axis:** Categorical - "Pretrained | Original Stimuli" and "Pretrained | Random Stimuli (= Length)". * **Y-axis:** "Brain Alignment (Pearson's r)", ranging from 0.00 to 0.30. * **Metrics (Sub-charts):** Linear, CKA, RSA. * **Bar Colors:** Light green and dark green. * **Significance Markers:** Four asterisks (****) above each bar. **Chart (b):** * **X-axis:** Categorical - "Untrained | Original Stimuli". * **Y-axis:** "Brain Alignment", ranging from 0.0 to 1.0. * **Conditions (Sub-charts):** Contextualization and No Contextualization. * **Bar Colors:** Light green and dark green. * **Significance Markers:** Three asterisks (***) above each bar. ### Detailed Analysis or Content Details **Chart (a):** * **Linear:** * "Pretrained | Original Stimuli": Approximately 0.06 ± 0.01 (visually estimated from error bar). * "Pretrained | Random Stimuli (= Length)": Approximately 0.24 ± 0.02. * **CKA:** * "Pretrained | Original Stimuli": Approximately 0.14 ± 0.02. * "Pretrained | Random Stimuli (= Length)": Approximately 0.26 ± 0.02. * **RSA:** * "Pretrained | Original Stimuli": Approximately 0.04 ± 0.01. * "Pretrained | Random Stimuli (= Length)": Approximately 0.13 ± 0.02. **Chart (b):** * **Contextualization:** * "Untrained | Original Stimuli": Approximately 0.65 ± 0.05. * **No Contextualization:** * "Untrained | Original Stimuli": Approximately 0.22 ± 0.04. ### Key Observations * In Chart (a), for all three metrics (Linear, CKA, RSA), the "Pretrained | Random Stimuli (= Length)" condition consistently shows significantly higher brain alignment scores than the "Pretrained | Original Stimuli" condition. * In Chart (b), the "Contextualization" condition exhibits a substantially higher brain alignment score compared to the "No Contextualization" condition. * The error bars suggest relatively low variance within each condition. * The significance markers (asterisks) indicate that the differences observed in all conditions are statistically significant. ### Interpretation The data suggests that pretraining on random stimuli (matched in length to original stimuli) leads to higher brain alignment compared to pretraining on original stimuli, as measured by Linear, CKA, and RSA metrics. This could indicate that the model learns representations that are more aligned with brain activity when exposed to random data of similar dimensionality. Chart (b) demonstrates that contextualization significantly enhances brain alignment. The substantial difference between the "Contextualization" and "No Contextualization" conditions suggests that incorporating contextual information is crucial for aligning model representations with brain activity. The consistent pattern of higher alignment scores for random stimuli in Chart (a) and the strong effect of contextualization in Chart (b) highlight the importance of both data characteristics and contextual information in building models that better reflect brain processing. The asterisks indicate that these differences are not due to chance. The use of different alignment metrics (Linear, CKA, RSA) in Chart (a) provides robustness to the findings, as the same trend is observed across all metrics.

## Bar Charts: Brain Alignment Comparison Across Models and Conditions ### Overview The image displays a composite figure containing five bar charts organized into two panels, labeled (a) and (b). The charts compare "Brain Alignment" (measured as Pearson's r) across three different experimental conditions for various model types or metrics. The overall purpose is to quantify and compare how well different computational models align with brain activity under different stimulus conditions. ### Components/Axes * **Panel (a):** Contains three separate bar charts titled "Linear", "CKA", and "RSA". * **Y-axis (for all three):** Labeled "Brain Alignment (Pearson's r)". The scale ranges from 0.00 to 0.14 for Linear and RSA, and from 0.00 to 0.30 for CKA. * **X-axis:** Each chart has three bars corresponding to the conditions defined in the legend. * **Panel (b):** Contains two separate bar charts titled "Contextualization" and "No Contextualization". * **Y-axis (for both):** Labeled "Brain Alignment". The scale ranges from 0.0 to 0.7 for Contextualization and from 0.0 to 1.0 for No Contextualization. * **X-axis:** Each chart has three bars corresponding to the conditions defined in the legend. * **Legend:** Located at the bottom of the entire figure, spanning its width. It defines three color-coded conditions: * **Light Green Bar:** "Pretrained | Original Stimuli" * **Medium Green Bar:** "Pretrained | Random Stimuli (= Length)" * **Dark Green Bar:** "Untrained | Original Stimuli" * **Statistical Significance:** Horizontal brackets with four asterisks (****) are placed above pairs of bars in each chart, indicating a highly significant statistical difference between those conditions. ### Detailed Analysis #### Panel (a) - Linear, CKA, RSA Metrics **1. Linear Chart** * **Trend:** The "Pretrained | Original Stimuli" condition shows the highest alignment, followed by "Untrained | Original Stimuli", with "Pretrained | Random Stimuli" showing very low alignment. * **Approximate Values (Pearson's r):** * Pretrained | Original Stimuli: ~0.133 (Error bar extends from ~0.12 to ~0.145) * Pretrained | Random Stimuli: ~0.015 (Error bar extends from ~0.01 to ~0.02) * Untrained | Original Stimuli: ~0.065 (Error bar extends from ~0.055 to ~0.075) * **Significance:** The bracket with **** spans the "Pretrained | Original Stimuli" and "Pretrained | Random Stimuli" bars, indicating a significant difference. **2. CKA Chart** * **Trend:** The "Untrained | Original Stimuli" condition shows the highest alignment, followed by "Pretrained | Original Stimuli", with "Pretrained | Random Stimuli" slightly lower than the pretrained original. * **Approximate Values (Pearson's r):** * Pretrained | Original Stimuli: ~0.185 (Error bar extends from ~0.16 to ~0.21) * Pretrained | Random Stimuli: ~0.16 (Error bar extends from ~0.15 to ~0.17) * Untrained | Original Stimuli: ~0.28 (Error bar extends from ~0.26 to ~0.30) * **Significance:** The bracket with **** spans the "Pretrained | Original Stimuli" and "Untrained | Original Stimuli" bars. **3. RSA Chart** * **Trend:** Similar to CKA, the "Untrained | Original Stimuli" condition shows the highest alignment, followed by "Pretrained | Original Stimuli", with "Pretrained | Random Stimuli" showing very low alignment. * **Approximate Values (Pearson's r):** * Pretrained | Original Stimuli: ~0.09 (Error bar extends from ~0.08 to ~0.105) * Pretrained | Random Stimuli: ~0.02 (Error bar extends from ~0.015 to ~0.025) * Untrained | Original Stimuli: ~0.138 (Error bar extends from ~0.125 to ~0.15) * **Significance:** The bracket with **** spans the "Pretrained | Original Stimuli" and "Untrained | Original Stimuli" bars. #### Panel (b) - Contextualization Conditions **1. Contextualization Chart** * **Trend:** The "Untrained | Original Stimuli" and "Pretrained | Original Stimuli" conditions show similarly high alignment, both far exceeding the "Pretrained | Random Stimuli" condition. * **Approximate Values (Brain Alignment):** * Pretrained | Original Stimuli: ~0.69 (Error bar extends from ~0.67 to ~0.71) * Pretrained | Random Stimuli: ~0.16 (Error bar extends from ~0.15 to ~0.17) * Untrained | Original Stimuli: ~0.71 (Error bar extends from ~0.69 to ~0.73) * **Significance:** The bracket with **** spans the "Pretrained | Original Stimuli" and "Pretrained | Random Stimuli" bars. **2. No Contextualization Chart** * **Trend:** The "Pretrained | Original Stimuli" condition shows the highest alignment, followed by "Untrained | Original Stimuli", with "Pretrained | Random Stimuli" showing low alignment. * **Approximate Values (Brain Alignment):** * Pretrained | Original Stimuli: ~1.03 (Error bar extends from ~0.95 to ~1.1) * Pretrained | Random Stimuli: ~0.17 (Error bar extends from ~0.15 to ~0.19) * Untrained | Original Stimuli: ~0.48 (Error bar extends from ~0.42 to ~0.54) * **Significance:** The bracket with **** spans the "Pretrained | Original Stimuli" and "Pretrained | Random Stimuli" bars. ### Key Observations 1. **Consistent Low Performance of Random Stimuli:** Across all five charts, the "Pretrained | Random Stimuli (= Length)" condition (medium green bar) consistently yields the lowest brain alignment scores. This serves as a critical control, showing that alignment is not driven by low-level stimulus properties like length. 2. **Divergent Effects of Training:** The effect of pretraining versus no training varies by metric and context. * In **Linear** and **No Contextualization** settings, the *Pretrained* model with original stimuli outperforms the *Untrained* model. * In **CKA** and **RSA** metrics, and in the **Contextualization** setting, the *Untrained* model with original stimuli shows equal or higher alignment than the *Pretrained* model. 3. **Impact of Contextualization:** Comparing the two charts in panel (b), the "Contextualization" condition appears to equalize the performance of pretrained and untrained models on original stimuli, whereas in the "No Contextualization" condition, the pretrained model has a clear advantage. 4. **Scale Differences:** The absolute values of "Brain Alignment" differ substantially between panels. Panel (a) values are in the range of 0.0-0.3 (Pearson's r), while panel (b) values are much higher, ranging up to ~1.0. This suggests the metrics or underlying data in (a) and (b) are fundamentally different. ### Interpretation This figure investigates the factors that contribute to a computational model's representations aligning with brain activity. The data suggests several key insights: 1. **Content Over Randomness:** The consistently poor performance of models exposed to "Random Stimuli" demonstrates that meaningful brain alignment requires exposure to structured, naturalistic input (the "Original Stimuli"). The brain's response is tuned to real-world patterns, not random noise of the same length. 2. **The Role of Training is Context-Dependent:** Pretraining is not universally beneficial for brain alignment. Its advantage appears specific to certain readout methods (Linear) or processing stages (No Contextualization). In other contexts (CKA, RSA, with Contextualization), an untrained model's initial random weights can sometimes yield representations that align *better* with brain data. This challenges the assumption that training on language necessarily moves representations closer to brain-like representations for all comparison metrics. 3. **Contextualization as an Equalizer:** The process of "Contextualization" (likely involving integrating information across a sequence or context) seems to diminish the representational advantage conferred by pretraining. This could imply that the brain's processing of context is a fundamental operation that both trained and untrained systems can approximate, or that pretraining primarily improves non-contextual aspects of representation. 4. **Metric Sensitivity:** The starkly different results between Linear, CKA, and RSA metrics highlight that "brain alignment" is not a single, monolithic concept. Different mathematical comparisons (linear mapping, kernel similarity, representational similarity) capture different aspects of the relationship between model and brain representations, leading to different conclusions about the effects of training. In summary, the figure provides evidence that brain-model alignment is a nuanced phenomenon heavily dependent on the nature of the input (structured vs. random), the model's training history, the specific computational process being measured (contextualization), and the mathematical tool used for comparison. It argues against a simple narrative that "more training equals better brain alignment."

## Bar Chart: Brain Alignment (Pearson's r) Across Conditions ### Overview The image presents a grouped bar chart comparing brain alignment (Pearson's r) across six experimental conditions. The chart is divided into two main sections: **(a)** with three conditions (Linear, CKA, RSA) and **(b)** with two conditions (Contextualization, No Contextualization). Each condition contains three bars representing different experimental groups, with error bars indicating variability. --- ### Components/Axes - **X-axis (Conditions)**: - **(a)**: Linear, CKA, RSA - **(b)**: Contextualization, No Contextualization - **Y-axis**: Brain Alignment (Pearson's r) with scales: - **(a)**: 0.00–0.30 - **(b)**: 0.00–0.70 - **Legend** (bottom): - **Light Green**: Pretrained | Original Stimuli - **Medium Green**: Pretrained | Random Stimuli (= Length) - **Dark Green**: Untrained | Original Stimuli --- ### Detailed Analysis #### Section (a) 1. **Linear**: - Pretrained | Original Stimuli: ~0.13 (error: ~0.12–0.14) - Pretrained | Random Stimuli: ~0.015 (error: ~0.01–0.02) - Untrained | Original Stimuli: ~0.065 (error: ~0.06–0.07) 2. **CKA**: - Pretrained | Original Stimuli: ~0.17 (error: ~0.16–0.18) - Pretrained | Random Stimuli: ~0.075 (error: ~0.07–0.08) - Untrained | Original Stimuli: ~0.28 (error: ~0.27–0.29) 3. **RSA**: - Pretrained | Original Stimuli: ~0.09 (error: ~0.08–0.10) - Pretrained | Random Stimuli: ~0.02 (error: ~0.015–0.025) - Untrained | Original Stimuli: ~0.14 (error: ~0.13–0.15) #### Section (b) 1. **Contextualization**: - Pretrained | Original Stimuli: ~0.68 (error: ~0.67–0.69) - Pretrained | Random Stimuli: ~0.15 (error: ~0.14–0.16) - Untrained | Original Stimuli: ~0.72 (error: ~0.71–0.73) 2. **No Contextualization**: - Pretrained | Original Stimuli: ~0.98 (error: ~0.97–0.99) - Pretrained | Random Stimuli: ~0.12 (error: ~0.11–0.13) - Untrained | Original Stimuli: ~0.45 (error: ~0.44–0.46) --- ### Key Observations 1. **Section (a)**: - Untrained | Original Stimuli consistently shows higher alignment than Pretrained | Random Stimuli across all conditions. - Pretrained | Original Stimuli exhibits moderate alignment, outperforming Pretrained | Random Stimuli but underperforming Untrained | Original Stimuli in CKA. 2. **Section (b)**: - Contextualization enhances alignment for both Pretrained | Original Stimuli and Untrained | Original Stimuli compared to No Contextualization. - Pretrained | Random Stimuli shows minimal alignment (~0.12–0.15) across all conditions. --- ### Interpretation 1. **Stimulus Type Impact**: - Original stimuli (dark green) drive higher brain alignment than random stimuli (medium green), particularly in the Untrained group. This suggests that stimulus familiarity or relevance is critical for neural synchronization. 2. **Contextualization Effect**: - Contextualization amplifies alignment for original stimuli (e.g., Untrained | Original Stimuli: 0.72 vs. 0.45 in No Contextualization), indicating that contextual framing improves neural representation. 3. **Pretrained vs. Untrained**: - Pretrained groups show lower alignment than Untrained groups with original stimuli in CKA and RSA, possibly reflecting prior knowledge biasing neural responses. 4. **Random Stimuli Baseline**: - Pretrained | Random Stimuli (medium green) consistently shows the lowest alignment (~0.01–0.15), establishing a near-zero baseline for comparison. --- ### Spatial Grounding & Trend Verification - **Legend Position**: Bottom-center, clearly mapping colors to groups. - **Trend Consistency**: - In **(a)**, dark green bars (Untrained | Original) are taller than medium green (Pretrained | Random) across all conditions, matching the numerical values. - In **(b)**, Contextualization elevates alignment for original stimuli, aligning with the observed trend of higher values in this condition. --- ### Conclusion The data demonstrates that brain alignment is strongly influenced by stimulus type (original vs. random) and contextual framing. Untrained participants with original stimuli show the highest alignment, while contextualization further enhances this effect. These findings highlight the interplay between stimulus familiarity, prior training, and contextual processing in neural synchronization.