Ethical Issues Posed by Field Research Using Highly Portable and Cloud-Enabled Neuroimaging

Abstract

Highly portable, cloud-enabled neuroimaging technologies will fundamentally change neuroimaging research. Instead of participants traveling to the scanner, the scanner will now come to them. Field-based brain imaging research, including populations underrepresented in neuroscience research to date, will enlarge and diversify databases and pave the way for clinical and direct-to-consumer (DTC) applications. Yet these technological developments urgently require analysis of their ethical, legal, and social implications (ELSI). No consensus ethical frameworks for mobile neuroimaging exist, and existing policies for traditional MRI research are inadequate. Based on literature review and ethics analysis of neurotechnology development efforts, Shen et al. identify seven foundational, yet unresolved, ELSI issues posed by portable neuroimaging: (1) informed consent; (2) privacy; (3) capacity to accurately communicate neuroimaging results to remote participants; (4) extensive reliance on cloud-based artificial intelligence (AI) for data analysis; (5) potential bias of interpretive algorithms in diverse populations; (6) return of research results and incidental (or secondary) findings to research participants; and (7) responding to participant requests for access to their data. The article proposes a path forward to address these urgent issues.

Keywords: EEG; MEG; MRI; PET; artificial intelligence; bias; bioethics; diverse populations; fMRI; fNIRS; informed consent; neuroethics; neuroimaging; privacy; research ethics; return of results.

Figure 1.. Comparing the Data Flow in Current MRI Research (A) with the Anticipated Data Flow in Emerging, Field-Based MRI Research

(A) Current data flow for MRI research with local analysis and local data storage. (B) New data flow for MRI research that is highly portable, cloud-enabled, and field-based.