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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.

The hippocampus plays a vital role in various aspects of cognition including both memory and spatial navigation. To understand electrophysiologically how the hippocampus supports these processes, we recorded intracranial electroencephalographic activity from 46 neurosurgical patients as they performed a spatial memory task. We measure signals from multiple brain regions, including both left and right hippocampi, and we use spectral analysis to identify oscillatory patterns related to memory encoding and navigation. We show that in the left but not right hippocampus, the amplitude of oscillations in the 1–3-Hz “low theta” band increases when viewing subsequently remembered object–location pairs. In contrast, in the right but not left hippocampus, low-theta activity increases during periods of navigation. The frequencies of these hippocampal signals are slower than task-related signals in the neocortex. These results suggest that the human brain includes multiple lateralized oscillatory networks that support different aspects of cognition. Theta oscillations are implicated in memory formation. Here, the authors show that low-theta oscillations in the hippocampus are differentially modulated between each hemisphere, with oscillations in the left increasing when successfully learning object–location pairs and in the right during spatial navigation.

The role of the left ventral lateral parietal cortex (VPC) in episodic memory is hypothesized to include bottom-up attentional orienting to recalled items, according to the dual-attention model (Cabeza et al., 2008). However, its role in memory encoding could be further clarified, with studies showing both positive and negative subsequent memory effects (SMEs). Furthermore, few studies have compared the relative contributions of sub-regions in this functionally heterogeneous area, specifically the anterior VPC (supramarginal gyrus/BA40) and the posterior VPC (angular gyrus/BA39), on a within-subject basis. To elucidate the role of the VPC in episodic encoding, we compared SMEs in the intracranial EEG across multiple frequency bands in the supramarginal gyrus (SmG) and angular gyrus (AnG), as twenty-four epilepsy patients with indwelling electrodes performed a free recall task. We found a significant SME of decreased theta power and increased high gamma power in the VPC overall, and specifically in the SmG. Furthermore, SmG exhibited significantly greater spectral tilt SME from 0.5 to 1.6 s post-stimulus, in which power spectra slope differences between recalled and unrecalled words were greater than in the AnG (p = 0.04). These results affirm the contribution of VPC to episodic memory encoding, and suggest an anterior-posterior dissociation within VPC with respect to its electrophysiological underpinnings. [Display omitted]

Every movement we make represents one of many possible actions. In reaching tasks with multiple targets, dorsal premotor cortex (PMd) appears to represent all possible actions simultaneously. However, in many situations we are not presented with explicit choices. Instead, we must estimate the best action based on noisy information and execute it while still uncertain of our choice. Here we asked how both primary motor cortex (M1) and PMd represented reach direction during a task in which a monkey made reaches based on noisy, uncertain target information. We found that with increased uncertainty, neurons in PMd actually enhanced their representation of unlikely movements throughout both planning and execution. The magnitude of this effect was highly variable across sessions, and was correlated with a measure of the monkeys’ behavioral uncertainty. These effects were not present in M1. Our findings suggest that PMd represents and maintains a full distribution of potentially correct actions. Whether it is trying to find the light switch in a dimly lit room or reaching for your glasses when you wake in the morning, we often need to reach toward objects that we cannot see clearly. In these situations, we plan our movements based both on the limited sensory information that is available, as well as what we have learned from similar situations in the past. The brain areas involved in using information to decide on the best movement plan appear to be different from those involved in actually executing that plan. One area in particular, called the dorsal premotor cortex (or PMd), is thought to help a person decide where to reach when they are presented with two or more alternative targets. However, it was not known how this brain area is involved in choosing a direction to reach when the targets are fuzzy, or unable to be seen clearly. Dekleva et al. trained Rhesus macaque monkeys to reach in various directions, towards targets that were represented by fuzzy, uncertain visual cues. These targets were not simply positioned randomly; instead they were more likely to require reaches in certain directions over other directions. Because there were many such training and experimental sessions, the monkeys were able to learn where targets were more likely to be located. Dekleva et al. found that, like humans, the monkeys combined this knowledge from previous experience with the fuzzy visual information; like people, the monkeys also weighted each source of information based on how well they trusted it. For example, blurrier targets were treated as less trustworthy. Further analysis showed that neurons in the PMd signaled the chosen direction well before the monkey began to reach. However, throughout the entire time the monkey was reaching, the same neurons also seemed to hold in reserve the other, less likely reach directions. In contrast, neurons in the area of the brain that directly controls movement – the primary motor cortex – only ever signaled the direction in which the monkey actually reached. Further work is now needed to understand the decision-making process that appears to start in the PMd and resolve in the primary motor cortex. In particular, future experiments could explore why the retained information about other possible reach decisions persists throughout the movement, including if this helps the individual to rapidly correct errors or to slowly improve movements over time.

We have exposed human participants to both full-movement and pulsatile viscous force perturbations to study the effect of force duration on the incremental transformation of sensation into adaptation. Traditional views of movement biomechanics could suggest that pulsatile forces would largely be attenuated as stiffness and viscosity act as a natural low-pass filter. Sensory transduction, however, tends to react to changes in stimuli and therefore could underlie heightened sensitivity to briefer, pulsatile forces. Here, participants adapted within perturbation duration conditions in a manner proportionate to sensed force and positional errors. Across perturbation conditions, we found participants had greater adaptive sensitivity when experiencing pulsatile forces rather than full-movement forces. In a follow-up experiment, we employed error-clamped, force channel trials to determine changes in predictive force generation. We found that while participants learned to closely compensate for the amplitude and breadth of full-movement forces, they exhibited a persistent mismatch in amplitude and breadth between adapted motor output and experienced pulsatile forces. This mismatch could generate higher salience of error signals that contribute to heightened sensitivity to pulsatile forces.

Closed-loop direct brain stimulation is a promising tool for modulating neural activity and behavior. However, it remains unclear how to optimally target stimulation to modulate brain activity in particular brain networks that underlie particular cognitive functions. Here, we test the hypothesis that stimulation's behavioral and physiological effects depend on the stimulation target's anatomical and functional network properties. We delivered closed-loop stimulation as 47 neurosurgical patients studied and recalled word lists. Multivariate classifiers, trained to predict momentary lapses in memory function, triggered stimulation of the lateral temporal cortex (LTC) during the study phase of the task. We found that LTC stimulation specifically improved memory when delivered to targets near white matter pathways. Memory improvement was largest for targets near white matter that also showed high functional connectivity to the brain's memory network. These targets also reduced low-frequency activity in this network, an established marker of successful memory encoding. These data reveal how anatomical and functional networks mediate stimulation's behavioral and physiological effects, provide further evidence that closed-loop LTC stimulation can improve episodic memory, and suggest a method for optimizing neuromodulation through improved stimulation targeting.

We have exposed human participants to both full-movement and pulsatile viscous force perturbations to study the effect of force duration on the incremental transformation of sensation into adaptation. Traditional views of movement biomechanics could suggest that pulsatile forces would largely be attenuated as stiffness and viscosity act as a natural low-pass filter. Sensory transduction, however, tends to react to changes in stimuli and therefore could underlie heightened sensitivity to briefer, pulsatile forces. Here, participants adapted within perturbation duration conditions in a manner proportionate to sensed force and positional errors. Across perturbation conditions, we found participants had greater adaptive sensitivity when experiencing pulsatile forces rather than full-movement forces. In a follow-up experiment, we employed error-clamped, force channel trials to determine changes in predictive force generation. We found that while participants learned to closely compensate for the amplitude and breadth of full-movement forces, they exhibited a persistent mismatch in amplitude and breadth between adapted motor output and experienced pulsatile forces. This mismatch could generate higher salience of error signals that contribute to heightened sensitivity to pulsatile forces.

Distinct lines of research in both humans and animals point to a specific role of the hippocampus in both spatial and episodic memory function. The discovery of concept cells in the hippocampus and surrounding medial-temporal lobe (MTL) regions suggests that the MTL maps physical and semantic spaces with a similar neural architecture. Here, we studied the emergence of such maps using MTL micro-wire recordings from 20 patients navigating a virtual environment featuring salient landmarks with established semantic meaning. We present several key findings: The array of local field potentials in the MTL contains sufficient information to decode subjects' instantaneous location in the environment. Closer examination revealed that the field potentials represent both the subjects' locations in virtual space and in high-dimensional semantic space. We further show that both spatial and semantic representations strengthen over time. This learning effect appears as subjects increase their knowledge of the environment's spatial and semantic layout. Similarly, we observe a learning effect on temporal sequence coding. Over time, field potentials come to represent future locations, even after controlling for spatial proximity. This predictive coding of future states, more so than the strength of spatial representations per se, explains variability in subjects' navigation performance. Our results thus support the conceptualization of the MTL as a memory space, building semantic knowledge, spatial and non-spatial, from episodic experience to plan future actions and predict their outcomes. Competing Interest Statement The authors have declared no competing interest.

Traumatic brain injury (TBI) is a leading cause of cognitive disability and is often associated with significant impairment in episodic memory. In TBI survivors, as in healthy controls, there is marked variability between individuals in memory ability. Using recordings from indwelling electrodes, we characterized and compared the oscillatory biomarkers of mnemonic variability in two cohorts of epilepsy patients: a group with a history of moderate- to-severe TBI (n = 37) and a group of non-TBI controls (n = 111) closely matched for demographics and electrode coverage. Analysis of these recordings demonstrated that increased high frequency power and decreased theta power across a broad set of brain regions mark periods of successful memory formation in both groups. As features in a logistic- regression classifier, spectral power biomarkers effectively predicted recall probability, with little difference between TBI and non-TBI controls. The two groups also displayed similar patterns of theta-frequency connectivity during successful encoding periods. These biomarkers of successful memory, highly conserved between TBI patients and controls, could serve as the basis for novel therapies that target disordered memory across diverse forms of neurological disease. Competing Interest Statement B.J. receives research funding from NeuroPace and Medtronic not relating to this research. R.G. serves as a consultant to Medtronic, which was a subcontractor on the DARPA RAM project, and receives compensation for these services, approved by Emory University. M.K. has started a company, Nia Therapeutics, LLC ('Nia'), intended to develop and commercialize brain stimulation therapies for memory restoration and has more than 5% equity interest in Nia. All other authors declare no competing financial interests.

Background: Patients with medically refractory epilepsy often undergo intracranial electroencephalography (iEEG) monitoring to identify a seizure focus and determine their candidacy for surgical intervention. This clinically necessary monitoring period provides an increasingly utilized research opportunity to study human neurophysiology, however, ethical concerns demand a thorough appreciation of the associated risks. Objective: We measured the incidence of research stimulation-associated seizures in a large multi-institutional study on brain stimulation's effect on memory in order to determine if brain stimulation was statistically associated with seizure incidence, and identify potential risk factors for stimulation-associated seizures. Methods: 188 subjects undergoing iEEG monitoring across 10 institutions participated in 770 research stimulation sessions over 3.5 years. Seizures within 30 minutes of a stimulation session were included in our retrospective analysis. We analyzed stimulation parameters, seizure incidence, and typical seizure patterns, to assess the likelihood that recorded seizures were stimulation-induced, rather than events that occurred by chance in epilepsy patients prone to seizing. Results: In total, 14 seizures were included in our analysis. All events were single seizures, and no adverse events occurred. The mean amplitude of seizure-associated stimulation did not differ significantly from the mean amplitude delivered in sessions without seizures. In order to determine the likelihood that seizures were stimulation induced, we used three sets of analyses: Visual iEEG analysis, statistical frequency, and power analyses. We determined that three of the 14 seizures were likely stimulation-induced, five were possibly stimulation-induced, and six were unlikely stimulation-induced. Overall, we estimate a rate of stimulation-induced seizures between 0.39% and 1.82% of sessions. Conclusions: The rarity of stimulation-associated seizures, and that none added morbidity or affected the clinical course of any patient, are important findings for understanding the feasibility and safety of intracranial stimulation for research purposes.