Recent meta-analyses indicate that non-neurobiological treatments for mental disorders, such as psychotherapy, demonstrate variable success rates ranging from 30% to 60% [Munder et al., 2019] . However, there is no consensus on the theoretical upper limit of these treatments [Cuijpers et al., 2024]. This study aims to estimate this upper bound by examining the alignment between network control properties of emotional and whole-brain fMRI responses to visual emotional stimuli. We hypothesize that the upper limit of non-neurobiological treatments (i.e., treatments that do not monitor brain responses and do not directly affect neural dynamics) cannot exceed the alignment threshold between cognitive response networks and neural response networks. To test this hypothesis, we analyzed emotional and fMRI brain responses from five subjects who viewed 2,185 emotionally evocative videos (each 3-15 seconds long) [Horikawa et al., 2020]. We estimated the network of cognitive properties by assessing emotions across 27 categories and 14 dimensions [Cowen and Keltner, 2017]. The subject-level network of fMRI responses was then estimated by calculating the partial correlation between emotional gradients, derived from contrasting fMRI responses to the top 10% and bottom 10% scored stimuli. We compared the geometric and network control properties of these two networks using pairwise correlation, similarity assessment of their eigenvectors and eigenvalues, and their controllability properties [Gu et al., 2015]. Our findings reveal a high modular structure similarity (r ≈ 0.6) between the partial correlation matrices of emotional gradients and emotional measures. There is also visual similarity in the eigenvectors of these matrices, although they are not perfectly aligned, showing significant similarity in corresponding eigenvectors. Additionally, we found similar rankings in average controllability for the highest control emotions (e.g., anxiety, fear, horror, depression) across both matrices, while the rest showed minimal correlation (r ≈ 0.2). Taken together, our data provide the first account of the efficacy threshold for non-neurobiological treatment options in mental disorders, estimating this to be less than 60%. These findings suggest that a paradigm shift in mental health treatment can only occur by incorporating neurobiological interventions.