Figure 4 - available from: Scientific Reports
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Electrode localization for an example surgical patient (S2). Location of selected electrodes is indicated with the yellow arrows (Right Anterior Temporal 03/04, A: Coronal, B: Axial, C: Sagittal).
Source publication
Direct recordings from the human brain have historically involved epilepsy patients undergoing invasive electroencephalography (iEEG) for surgery. However, these measurements are temporally limited and affected by clinical variables. The RNS System (NeuroPace, Inc.) is a chronic, closed-loop electrographic seizure detection and stimulation system....
Context in source publication
Context 1
... direct comparison between suc- cessful and failed encoding trials is provided in Supplementary Figure S1. We also observed a simultaneous decrease in theta band power for surgical iEEG patients between 1.4-1.6 sec- onds, but not in our RNS System iEEG patients ( Supplementary Figure 4 and 5). The discrepancy in our surgical iEEG and RNS iEEG data may due to differences in acute versus chronic iEEG recordings, attenuation of low frequency activity outside of the RNS System bandpass filter, or task design. ...
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Objective
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Citations
... doi: 10.1080/02643294.2019 Davis, C. P., and Yee, E. (2019). Features, labels, space, and time: factors supporting taxonomic relationships in the anterior temporal lobe and thematic relationships in the angular gyrus. ...
Introduction
The hippocampus plays a crucial role in episodic memory. Given its complexity, the hippocampus participates in multiple aspects of higher cognitive functions, among which are semantics-based encoding and retrieval. However, the “where,” “when” and “how” of distinct aspects of memory processing in the hippocampus are still under debate.
Methods
Here, we employed a visual associative memory task that involved encoding three levels of subjective congruence to delineate the differential involvement of the rostral and caudal portions (also referred as anterior/posterior portions) of the human hippocampus during memory encoding, recognition and associative recall.
Results
Through stereo-EEG recordings in epilepsy patients we show that associative memory is reflected by rostral hippocampal activity during encoding, and caudal hippocampal activity during retrieval. In contrast, recognition memory encoding selectively activates the rostral hippocampus. The temporal dynamics of memory processing are manifested by gamma power increase, which partially overlaps with low-frequency power decrease during encoding and retrieval. Congruence levels modulate low-frequency activity prominently in the caudal hippocampus.
Discussion
These findings highlight an anatomical segregation in the hippocampus in accordance with the contributions of its partitions to associative and recognition memory.
... In contrast, gamma activity plays a crucial role in facilitating the consolidation of information from short-term to long-term memory by promoting neuronal synchronization and information integration (Fries P 2009;Nyhus and Curran 2010). Henin et al. (2019) found that gamma activity in the hippocampus and widespread cortical regions significantly increased during successful encoding, suggesting that gamma frequency may be a neural mechanism closely associated with successful memory encoding. Applying tACS at 60 Hz and 90 Hz to the left dorsolateral prefrontal cortex enhanced memory performance (Javadi AH et al. 2017). ...
Transcranial alternating current stimulation (tACS) has been reported to improve associative memory (AM) by modulating the frequency of neural oscillations in the brain; however, whether gamma-frequency (> 30 Hz) tACS in the left posterior parietal lobe (PPC) can enhance memory retention in AM remains unclear. This study aimed to investigate whether memory retention in AM could be improved after gamma-frequency tACS of the left PPC. We used a randomly assigned, double-blind, repeated-measures, sham-control design, in which 28 healthy adult participants were assigned to receive a single 20-min session of gamma-frequency (60 Hz) tACS or sham stimulation. The memory learning task consisted of studying and testing 50 unrelated word pairs three times on day 1. The number of correct responses in the cued recall task was measured at three time points: days 1, 7, and 28. The results revealed a significant difference in the number of correct responses between the interventions on day 7 and day 28. These data suggest that gamma-frequency tACS stimulation of the left PPC enhances the long-term retention of AM in healthy adults.
... In particular, gamma oscillations (30-80 Hz) are a physiological measure of brain function that is thought to support cognitive processes including working memory and other tasks of cognition [44][45][46]. Indeed, the power of hippocampal CA1 gamma oscillations is reported to predict the memory of spatial memory judgments and associative memory performance [47,48], while encoding impairment with age is associated with dysfunctional gamma oscillatory activity [49]. These findings suggest that gamma oscillation is closely linked to brain activity related to the memory process. ...
Accumulating evidence has suggested that a great proportion of sepsis survivors suffer from long-term cognitive impairments after hospital discharge, leading to decreased life quality and substantial caregiving burdens for family members. However, the underlying mechanism remains unclear. In the present study, we established a mouse model of systemic inflammation by repeated lipopolysaccharide (LPS) injections. A combination of behavioral tests, biochemical, and in vivo electrophysiology techniques were conducted to test whether abnormal NRG1/ErbB4 signaling, parvalbumin (PV) interneurons, and hippocampal neural oscillations were involved in memory decline after repeated LPS injections. Here, we showed that LPS induced long-term memory decline, which was accompanied by dysfunction of NRG1/ErbB4 signaling and PV interneurons, and decreased theta and gamma oscillations. Notably, NRG1 treatment reversed LPS-induced decreases in p-ErbB4 and PV expressions, abnormalities in theta and gamma oscillations, and long-term memory decline. Together, our study demonstrated that dysfunction of NRG1/ErbB4 signaling in the hippocampus might mediate long-term memory decline in a mouse model of systemic inflammation induced by repeated LPS injections. Thus, targeting NRG1/ErbB4 signaling in the hippocampus may be promising for the prevention and treatment of this long-term memory decline.
... In particular, gamma oscillations (30-80 Hz) are a physiological measure of brain function that is thought to support cognitive processes including working memory and other tasks of cognition [44][45][46]. Indeed, the power of hippocampal CA1 gamma oscillations is reported to predict the memory of spatial memory judgments and associative memory performance [47,48], while encoding impairment with age is associated with dysfunctional gamma oscillatory activity [49]. These findings suggest that gamma oscillation is closely linked to brain activity related to the memory process. ...
... By comparing overnight sleep and sleep deprivation, we could also investigate how protracted wakefulness affects the neural correlates of learning. Specifically, EEG recordings were acquired during paired-associates learning to test the hypothesis that sleep deprivation disrupts theta (4-8 Hz) and gamma (> 40 Hz) synchronisation, which support item binding in episodic memory (Henin et al. 2019;Köster et al. 2018;Osipova et al. 2006;Summerfield and Mangels 2005). Furthermore, in an exploratory analysis, we investigated the effect of sleep deprivation on 12-20 Hz beta desynchronization; an established marker of successful learning (Griffiths et al. 2016;Hanslmayr et al. 2014;Hanslmayr et al. 2009;Hanslmayr et al. 2012;Hanslmayr et al. 2011). ...
Sleep supports memory consolidation as well as next-day learning. The influential Active Systems account of offline consolidation suggests that sleep-associated memory processing paves the way for new learning, but empirical evidence in support of this idea is scarce. Using a within-subjects (N = 30), crossover design, we assessed behavioural and electrophysiological indices of episodic encoding after a night of sleep or total sleep deprivation in healthy adults (aged 18-25 years), and investigated whether behavioural performance was predicted by the overnight consolidation of episodic associations formed the previous day. Sleep supported memory consolidation and next-day learning, as compared to sleep deprivation. However, the magnitude of this sleep-associated consolidation benefit did not significantly predict the ability to form novel memories after sleep. Interestingly, sleep deprivation prompted a qualitative change in the neural signature of encoding: whereas 12-20 Hz beta desynchronization – an established marker of successful encoding – was observed after sleep, sleep deprivation disrupted beta desynchrony during successful learning. Taken together, these findings suggest that effective learning depends on sleep, but not necessarily sleep-associated consolidation.
... We compared overnight sleep and sleep deprivation so that we could also investigate how protracted sleep loss affects the neurocognitive mechanisms of learning. Specifically, EEG recordings were acquired during paired-associates learning to test the hypothesis that sleep deprivation would disrupt theta (4-8 Hz) and gamma (>40 Hz) synchronisation, which support item binding in episodic memory (Köster et al., 2018;Summerfield & Mangels, 2005;Henin et al., 2019). Furthermore, in exploratory analyses, we investigated the effect of sleep deprivation on 12-20 Hz beta desynchronization; an established marker of successful learning that reflects depth of information processing (Hanslmayr et al., 2009;. ...
Sleep supports memory consolidation as well as next-day learning. The Active Systems account of offline consolidation suggests that sleep-associated memory processing paves the way for new learning, but empirical evidence in support of this idea is scarce. Using a within-subjects, crossover design, we assessed behavioural and electrophysiological indices of episodic encoding after a night of sleep or total sleep deprivation in healthy adult humans (aged 18-25 years), and investigated whether the behavioural measures were predicted by the overnight consolidation of episodic associations formed the previous day. Sleep supported memory consolidation and next-day learning, as compared to sleep deprivation. However, the magnitude of this sleep-associated consolidation benefit did not significantly predict the ability to form novel memories after sleep. Interestingly, sleep deprivation prompted a qualitative change in the neural signature of encoding: whereas 12-20 Hz beta desynchronization - an established EEG marker of successful encoding - was observed after sleep, sleep deprivation disrupted beta desynchrony during successful learning. Taken together, our findings suggest that effective learning mechanisms are critically dependent on sleep, but not necessarily sleep-associated consolidation.
... Another FDA-approved neurostimulation device for epilepsy, the RNS Ò System, operates with a closed-loop design [22] and is one of only two commercial devices that stores a limited form of chronic intracranial electroencephalography (cEEG) [23]. RNS cEEG has been used to address challenges in clinical epilepsy-seizure lateralization [24] and localization [25], spell characterization [26], evaluating anti-seizure medications (ASMs) [27], and seizure forecasting [28]-and it has also proven to be a powerful tool for basic neuroscience research on cortical language representation [29], spatial memory [30], and other cognitive functions [31,32]. RNS cEEG has helped characterize neural desynchronization related to vagus nerve stimulation [33] but, to our knowledge, it has not been used to quantify neurophysiological effects of an ANT DBS device implanted in the same individual. ...
Implanted neurostimulation devices are gaining traction as palliative treatment options for certain forms of drug-resistant epilepsy, but clinical utility of these devices is hindered by incomplete mechanistic understanding of their therapeutic effects. Approved devices for anterior thalamic nuclei deep brain stimulation (ANT DBS) are thought to work at a network level, but limited sensing capability precludes characterization of neurophysiological effects outside the thalamus. Here, we describe a patient with drug-resistant temporal lobe epilepsy who was implanted with a responsive neurostimulation device (RNS System), involving hippocampal and ipsilateral temporal neocortical leads, and subsequently received ANT DBS. Over 1.5 years, RNS System electrocorticography enabled multiscale characterization of neurophysiological effects of thalamic stimulation. In brain regions sampled by the RNS System, ANT DBS produced acute, phasic, frequency-dependent responses, including suppression of hippocampal low frequency local field potentials. ANT DBS modulated functional connectivity between hippocampus and neocortex. Finally, ANT DBS progressively suppressed hippocampal epileptiform activity in relation to the extent of hippocampal theta suppression, which informs stimulation parameter selection for ANT DBS. Taken together, this unique clinical scenario, involving hippocampal recordings of unprecedented chronicity alongside ANT DBS, sheds light on the therapeutic mechanism of thalamic stimulation and highlights capabilities needed in next-generation devices.
... A few neuroscientists have begun to capitalize on the opportunity to use chronically implanted neural devices, such as the RNS System (NeuroPace) (Aghajan et al., 2017;Meisenhelter et al., 2019;Henin et al., 2019;Rao et al., 2017). However, these studies did not provide methods for real-time viewing and control or the ability to deliver intracranial electrical stimulation (iES) and perform precise synchronization of intracranial electroencephalography (iEEG) with externally acquired data during free movement. ...
... The Mo-DBRS platform includes three key improvements compared to previous work (Aghajan et al., 2017;Meisenhelter et al., 2019;Henin et al., 2019;Rao et al., 2017): (1) improved accuracy of synchronization, (2) mobility, and (3) integration with multiple wearables. More important, the Mark-based Three key features are compared, including capability for use during ambulatory behaviors (mobility), integration with wearable technologies (wearables), synchronization method (sync method), relative latency (mean) of iEEG synchronization with the experimental task paradigm (task-iEEG sync relative latency [mean]), and relative latency (SD) of iEEG synchronization with the experimental task paradigm (task-iEEG sync relative latency [SD]). ...
... These Research Tools are listed ll NeuroResource below, some of which come with the commercially available RNS System and others that can be provided by NeuroPace upon request or built by the user using the circuit and software code details provided here. Previous studies (Aghajan et al., 2017;Meisenhelter et al., 2019;Henin et al., 2019;Rao et al., 2017) have used variations of the Programmer, Programmer Tool, Wand, Wand Tool, and Electromagnet. ...
Uncovering the neural mechanisms underlying human natural ambulatory behavior is a major challenge for neuroscience. Current commercially available implantable devices that allow for recording and stimulation of deep brain activity in humans can provide invaluable intrinsic brain signals but are not inherently designed for research and thus lack flexible control and integration with wearable sensors. We developed a mobile deep brain recording and stimulation (Mo-DBRS) platform that enables wireless and programmable intracranial electroencephalographic recording and electrical stimulation integrated and synchronized with virtual reality/augmented reality (VR/AR) and wearables capable of external measurements (e.g., motion capture, heart rate, skin conductance, respiration, eye tracking, and scalp EEG). When used in freely moving humans with implanted neural devices, this platform is adaptable to ecologically valid environments conducive to elucidating the neural mechanisms underlying naturalistic behaviors and to the development of viable therapies for neurologic and psychiatric disorders.
... A few neuroscientists have begun to capitalize on the opportunity to use chronically implanted neural devices, such as the RNS System (NeuroPace) (Aghajan et al., 2017;Meisenhelter et al., 2019;Henin et al., 2019;Rao et al., 2017). However, these studies did not provide methods for real-time viewing and control or the ability to deliver intracranial electrical stimulation (iES) and perform precise synchronization of intracranial electroencephalography (iEEG) with externally acquired data during free movement. ...
... The Mo-DBRS platform includes three key improvements compared to previous work (Aghajan et al., 2017;Meisenhelter et al., 2019;Henin et al., 2019;Rao et al., 2017): (1) improved accuracy of synchronization, (2) mobility, and (3) integration with multiple wearables. More important, the Mark-based Three key features are compared, including capability for use during ambulatory behaviors (mobility), integration with wearable technologies (wearables), synchronization method (sync method), relative latency (mean) of iEEG synchronization with the experimental task paradigm (task-iEEG sync relative latency [mean]), and relative latency (SD) of iEEG synchronization with the experimental task paradigm (task-iEEG sync relative latency [SD]). ...
... These Research Tools are listed ll NeuroResource below, some of which come with the commercially available RNS System and others that can be provided by NeuroPace upon request or built by the user using the circuit and software code details provided here. Previous studies (Aghajan et al., 2017;Meisenhelter et al., 2019;Henin et al., 2019;Rao et al., 2017) have used variations of the Programmer, Programmer Tool, Wand, Wand Tool, and Electromagnet. ...
Current implantable devices that allow for recording and stimulation of brain activity in humans are not inherently designed for research and thus lack programmable control and integration with wearable sensors. We developed a platform that enables wireless and programmable intracranial electroencephalographic recording and deep brain stimulation integrated with wearable technologies. This methodology, when used in freely moving humans with implanted neural devices, can provide an ecologically valid environment conducive to elucidating the neural mechanisms underlying naturalistic behaviors and developing viable therapies for neurologic and psychiatric disorders.
... The technique allows investigators to probe neuronal activity with the same temporal resolution within which related cognitive functions are postulated to occur. Gamma oscillations have been investigated in a free recall memory paradigm, and shown to predict successful memory formation during encoding and to distinguish true from false memories at recall (Henin et al., 2019;Sederberg, Kahana, Howard, Donner, & Madsen, 2003;Sederberg et al., 2007). However, no study to date has used high gamma activity to investigate the spatiotemporal dynamics of the verbal fluency task, which combines a free recall format with long-term memory and word production processes, in real time. ...
Verbal fluency is commonly used to evaluate cognitive dysfunction in a variety of neuropsychiatric diseases, yet the neurobiology underlying performance of this task is incompletely understood. Electrocorticography (ECoG) provides a unique opportunity to investigate temporal activation patterns during cognitive tasks with high spatial and temporal precision. We used ECoG to study high gamma activity (HGA) patterns in patients undergoing presurgical evaluation for intractable epilepsy as they completed an overt, free-recall verbal fluency task. We examined regions demonstrating changes in HGA during specific timeframes relative to speech onset. Early pre-speech high gamma activity was present in left frontal regions during letter fluency and in bifrontal regions during category fluency. During timeframes typically associated with word planning, a distributed network was engaged including left inferior frontal, orbitofrontal and posterior temporal regions. Peri-Rolandic activation was observed during speech onset, and there was post-speech activation in the bilateral posterior superior temporal regions. Based on these observations in the context of prior studies, we propose a model of neocortical activity patterns underlying verbal fluency.
