A different neuroscience community has had greater success in ‘reading out’ the brain: brain–computer interface (BCI) researchers. Their technologies ‘decode’ movement signals from the cortex, then convey movement goals to assistive devices. Closed-loop DBS researchers seek to do something similar, decoding a patient’s emotional state. BCI investigators have uncovered two insights that could assist psychiatry’s quest. First, encoding matters—decoding is better with a robust model of how cortical regions encode mental states. This matters for psychiatry, because disorders like depression and post-traumatic stress disorder are heterogeneous. Effective decoding may require identification of discrete circuit-based endophenotypes, analogous to research domain criteria constructs. For instance, preliminary data suggest that DBS response at the ventral striatum target may depend on changes in fronto-cingulate activity evoked by Stroop-like tasks (Widge et al, 2015). This cross-diagnostic approach may be broadly useful in dissecting DBS’ mechanisms of action.

Second, neural plasticity can help. A recent surprise from BCI studies is that models are helpful, but not always necessary. A motivated subject can learn to skillfully control a prosthetic limb or an internal neurostimulator, even if the mapping between neural firing and device behavior does not match ‘natural’ input–output relationships. As the user trains with the BCI, the brain re-maps its firing patterns to match the device’s control scheme (Moritz and Fetz, 2011). In effect, the decoded patterns become a readout of the user’s intention—what he/she wants the device to do at that moment. For a prosthetic limb, this is an instantaneous motion command. For psychiatry, it would be a stimulator command. For instance, one could place a recording electrode in an area that contains emotion-related signals, then link the amplitude of a DBS intervention to the intention-modulated signals in that area. The patient’s signals in the recorded area would then ‘tune’ the DBS intervention as needed. We recently showed that rodents can learn to use prefrontal cortex signals in precisely this fashion to activate DBS-like stimulation (Widge and Moritz, 2014). Similar strategies may be useful for modulating fear behaviors in anxiety disorders, using fronto-limbic networks as targets (Besnard and Sahay, 2015).

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