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Memory failures are frustrating and often the result of ineffective encoding. One approach to improving memory outcomes is through direct modulation of brain activity with electrical stimulation. Previous efforts, however, have reported inconsistent effects when using open-loop stimulation and often target the hippocampus and medial temporal lobes. Here we use a closed-loop system to monitor and decode neural activity from direct brain recordings in humans. We apply targeted stimulation to lateral temporal cortex and report that this stimulation rescues periods of poor memory encoding. This system also improves later recall, revealing that the lateral temporal cortex is a reliable target for memory enhancement. Taken together, our results suggest that such systems may provide a therapeutic approach for treating memory dysfunction. Memory lapses can occur due to ineffective encoding, but it is unclear if targeted brain stimulation can improve memory performance. Here, authors use a closed-loop system to decode and stimulate periods of ineffective encoding, showing that stimulation of lateral temporal cortex can enhance memory.

Neuronal firing in the substantia nigra (SN) immediately following reward is thought to play a crucial role in human reinforcement learning. As in Ramayya et al. (2014a) we applied microstimulation in the SN of patients undergoing deep brain stimulation (DBS) for the treatment of Parkinson's disease as they engaged in a two-alternative reinforcement learning task. We obtained microelectrode recordings to assess the proximity of the electrode tip to putative dopaminergic and GABAergic SN neurons and applied stimulation to assess the functional importance of these neuronal populations for learning. We found that the proximity of SN microstimulation to putative GABAergic neurons predicted the degree of stimulation-related changes in learning. These results extend previous work by supporting a specific role for SN GABA firing in reinforcement learning. Stimulation near these neurons appears to dampen the reinforcing effect of rewarding stimuli.

The brain's sensitivity to unexpected gains or losses plays an important role in our ability to learn new behaviors (Rescorla and Wagner, 1972; Sutton and Barto, 1990). Recent work suggests that gains and losses are ubiquitously encoded throughout the human brain (Vickery et al., 2011), however, the extent to which reward expectation modulates these valence representations is not known. To address this question, we analyzed recordings from 4306 intracranially implanted electrodes in 39 neurosurgical patients as they performed a two-alternative probability learning task. Using high-frequency activity (HFA, 70–200Hz) as an indicator of local firing rates, we found that expectation modulated reward-related neural activity in widespread brain regions, including regions that receive sparse inputs from midbrain dopaminergic neurons. The strength of unexpected gain signals predicted subjects' abilities to encode stimulus–reward associations. Thus, neural signals that are functionally related to learning are widely distributed throughout the human brain. •We analyzed intracranial high frequency activity during reinforcement learning.•Expectation modulated reward-related neural activity in widespread brain regions.•These included regions that receive sparse inputs from midbrain dopamine neurons.•The strength of unexpected gain signals predicted subjects' learning during the task.•Neural signals related to learning are widely distributed throughout the human brain.