Traumatic brain injury (TBI) is a leading cause of cognitive disability in adults, often characterized by marked deficits in episodic memory and executive function. Prior studies have found that direct electrical stimulation of the temporal cortex yielded improved memory in epilepsy patients, but it is not clear if these results generalize to patients with a specific history of TBI. Here we asked whether applying closed-loop, direct electrical stimulation to lateral temporal cortex could reliably improve memory in a TBI cohort. Among a larger group of patients undergoing neurosurgical evaluation for refractory epilepsy, we recruited a subset patients with a history of moderate-to-severe TBI. By analyzing neural data from indwelling electrodes as patients studied and recalled lists of words, we trained personalized machine-learning classifiers to predict momentary fluctuations in mnemonic function in each patient. We subsequently used these classifiers to trigger high-frequency stimulation of the lateral temporal cortex (LTC) at moments when memory was predicted to fail. This strategy yielded a 19% boost in recall performance on stimulated as compared with non-stimulated lists (P = 0.012). These results provide a proof-of-concept for using closed-loop stimulation of the brain in treatment of TBI-related memory impairment.
1Neural activity associated with successful cognition appears as a tilt in the power spectrum of 2 the local field potential, wherein increases in high-frequency power accompany decreases in low 3 frequency power. Whereas this pattern has been shown in a wide range of memory tasks, it is 4 unknown whether this increased spectral tilt reflects underlying memory-specific processes or 5 rather a domain-general index of task engagement. To address the question of whether increased 6 spectral tilt reflects increased attention to a cognitive task, we collected intracranial recordings 7 from three hundred thirty neurosurgical patients as they performed a mathematical problem 8 solving task. We used a mathematical problem solving task, because it allowed us to decouple 9 task-specific processes with domain-general attention in a novel way. Using a statistical model to 10 control for inherent problem complexity, we classified individual math problems based on whether 11 a subject performed faster than predicted (high-attention or fast) or slower than predicted (low-12 attention, or slow) based on residual response times. In contrast to the domain-general attentional 13 account, problems that took longer than predicted produced stronger evidence for the spectral 14 tilt: widespread increases in high frequency (31-180 Hz) power and decreases in low frequency 15 (3-17 Hz) power across frontal, temporal, and parietal cortices. The pattern emerged early within 16 each trial and was sustained throughout the response period but was not observed in the medial 17 temporal lobe. The data show that engaging in mathematical problem solving leads to a distributed 18 spectral tilt pattern, even when accounting for variability in performance driven by the arithmetic 19 demands of the problems themselves, and suggest that broadband changes in the power spectrum 20 reflect an index of information processing in the brain beyond simple attention to the cognitive 21 task. 22In the domain of episodic memory, extensive prior work using both intracranial and scalp elec-24 troencephalography (EEG), as well as magnetoencephalography (MEG), has shown that neural 25 activity during memory encoding exhibits broadband changes in power that correlate with mem-26 ory performance (Burke, Ramayya, & Kahana, 2015). Typically, increases in high-frequency activity 27 (HFA, >30 Hz) are associated with encoding of information that is later remembered compared 28 to information that is later forgotten
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