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Along with the growing number of students with disabilities in higher education comes an opportunity to explore the difficulties they experience, especially in the post-pandemic era, as well as how to better support them, thus making post-secondary education more inclusive. A considerable amount of research has been done in providing accommodation for students with physical disabilities, but other hindrances to accessibility such as mental health conditions are prone to be overlooked, perhaps in part due to the stigmatization and subjective invisibility of this topic, specifically in rigorous, competitive fields such as Computer Science (CS). In order to bridge this gap, we conducted a nationwide survey in which 53 undergraduate CS students who identify as living with a mental health condition shared their experiences in their CS courses, instructor and TA office hours, interactions with other students, and the rest of the field. This paper summarizes the most common negative and positive experiences, as well as respondents' recommendations for CS instructors, including recognizing these students' struggles, making themselves approachable, and providing flexible formats of lectures and office hours. The results of this study provide a glimpse of the academic lives of CS students living with mental health conditions, so that CS instructors could foster a more inclusive environment by supporting more students in their paths of pursuing higher education. 

Background:Ketamine has emerged as one of the most promising therapies for treatment-resistant depression. However, inter-individual variability in response to ketamine is still not well understood and it is unclear how ketamine’s molecular mechanisms connect to its neural and behavioral effects. Methods:We conducted a single-blind placebo-controlled study, with participants blinded to their treatment condition. 40 healthy participants received acute ketamine (initial bolus 0.23 mg/kg, continuous infusion 0.58 mg/kg/hr). We quantified resting-state functional connectivity via data-driven global brain connectivity and related it to individual ketamine-induced symptom variation and cortical gene expression targets. Results:We found that: (i) both the neural and behavioral effects of acute ketamine are multi-dimensional, reflecting robust inter-individual variability; (ii) ketamine’s data-driven principal neural gradient effect matched somatostatin (SST) and parvalbumin (PVALB) cortical gene expression patterns in humans, while the mean effect did not; and (iii) behavioral data-driven individual symptom variation mapped onto distinct neural gradients of ketamine, which were resolvable at the single-subject level. Conclusions:These results highlight the importance of considering individual behavioral and neural variation in response to ketamine. They also have implications for the development of individually precise pharmacological biomarkers for treatment selection in psychiatry. Funding:This study was supported by NIH grants DP5OD012109-01 (A.A.), 1U01MH121766 (A.A.), R01MH112746 (J.D.M.), 5R01MH112189 (A.A.), 5R01MH108590 (A.A.), NIAAA grant 2P50AA012870-11 (A.A.); NSF NeuroNex grant 2015276 (J.D.M.); Brain and Behavior Research Foundation Young Investigator Award (A.A.); SFARI Pilot Award (J.D.M., A.A.); Heffter Research Institute (Grant No. 1–190420) (FXV, KHP); Swiss Neuromatrix Foundation (Grant No. 2016–0111) (FXV, KHP); Swiss National Science Foundation under the framework of Neuron Cofund (Grant No. 01EW1908) (KHP); Usona Institute (2015 – 2056) (FXV). Clinical trial number:NCT03842800