Gabriel Fajardo
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gabefajardo.bsky.social
Gabriel Fajardo
@gabefajardo.bsky.social
100 followers 270 following 10 posts
Computational social neuroscientist interested in person perception, emotion, and Neuro-AI | Graduate Student in the SCRAP Lab at Dartmouth
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gabefajardo.bsky.social
Using artificial neural networks, we examined the relationship between multivariate response patterns in the auditory cortex, the two visual streams, and the rest of the brain, revealing that distinct portions of the STS combine information from the two visual streams with auditory information.
Fig. 2. a. Voxels showing significant effects (p < 0.05, FWE corrected) for the combination of auditory responses with responses in V3d and V5 (red), and auditory responses with responses in V3v and V4 (green). b. Voxels showing significant effects for the combination of responses in V3v and V4 with responses in V3d and V5 (blue). c. Fisher transformed Pearson correlation values between the auditory+dorsal and auditory+ventral combined-minus-max models, computed across the top 50 voxels in the STS (left) and the top 100 voxels across the whole brain (right) showing the greatest change in variance explained across both models. d. Pearson correlation values between combined-minus-max effect patterns from the auditory+dorsal and auditory+ventral models within an STS ROI. We computed these correlations across 500 splits of the participants into two equal groups, comparing pattern similarity within the same model across splits (e.g. AUD+dorsal and AUD+dorsal) to the similarity of patterns between different models across splits (e.g. AUD+dorsal in split 1 to AUD+ventral in split 2: “AD1 / AV2”).
October 2, 2025 at 3:20 PM
gabefajardo.bsky.social
I’m excited to share my 1st first-authored paper, “Distinct portions of superior temporal sulcus combine auditory representations with different visual streams” (with @mtfang.bsky.social and @steanze.bsky.social ), now out in The Journal of Neuroscience!
www.jneurosci.org/content/earl...
Fig. 1. a. Visual and auditory regions of interest (ROIs). b. Responses in a combination of visual (e.g., early dorsal visual stream; Fig. 1a, middle panel) and auditory regions were used to predict responses in the rest of the brain using MVPN. c. In order to identify brain regions that combine responses from auditory and visual regions, we identified voxels where predictions generated using the combined patterns from auditory regions and one set of visual regions jointly (as shown in Fig. 1b) are significantly more accurate than predictions generated using only auditory regions or only that set of visual regions.
October 2, 2025 at 3:20 PM