Bibliometric Analysis and Applications of a Modified H-Index Examining the Research Productivity of Neurosurgery Faculty at High-Ranking Academic Institutions.

OBJECTIVE: A major critique of the h-index is that it may be inflated by noncritical authorship. We propose a modified h-index (hm), incorporating critical authorship, complementary to the h-index. We analyze its relationship to the traditional h-index, and how each varies across professional categories relevant to academic neurosurgery. This analysis is not meant to critique authorship decisions, affect career development, alter academic legacy, or imply that the concepts of team science or midlevel authorship contributions are not valuable. METHODS: H-indices and hms were gathered and computed for clinical neurosurgical faculty at the top 32 ranked academic neurosurgical programs based on the current literature. Hm was computed for faculty at each program, using articles in which the individual was first, second, last, or co-corresponding author. Individuals were further identified based on chair status, leadership status, neurosurgical subspecialty, and National Institutes of Health funding status. Further analysis was performed to determine factors influencing h-index and hm. RESULTS: The median h-index for the 225 physicians included in the final dataset is 48 (interquartile range [IQR], 39-61), whereas the median hm was 32 (IQR, 24-43). The median difference between h-index and hm is 15 (IQR, 10-23). The median hm/h was 64% (IQR, 57-74). National Institutes of Health funding and subspecialty (neurosurgical oncology, neurocritical care, and cerebrovascular) were associated with significant change from h to hm. CONCLUSIONS: The h-index can be influenced by noncritical authorship, and hm, using critical contributions, can be used as a complement reflecting critical academic output in neurosurgery. Leaders deciding on hiring or promotion should consider disparities in productivity predicated on noncritical authorship contributions.

Functional and anatomical connectivity predict brain stimulation's mnemonic effects.

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 the 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.

Episodic boundaries affect neural features of representational drift in humans.

A core feature of episodic memory is representational drift, the gradual change in aggregate oscillatory features that supports temporal association of memory items. However, models of drift overlook the role of episodic boundaries, which indicate a shift from prior to current context states. Our study focuses on the impact of task boundaries on representational drift in the parietal and temporal lobes in 99 subjects during a free recall task. Using intracranial EEG recordings, we show boundary representations reset gamma band drift in the medial parietal lobe, selectively enhancing the recall of early list (primacy) items. Conversely, the lateral temporal cortex shows increased drift for recalled items but lacked sensitivity to task boundaries. Our results suggest regional sensitivity to varied contextual features: the lateral temporal cortex uses drift to differentiate items, while the medial parietal lobe uses drift-resets to associate items with the current context. We propose drift represents relational information tailored to a region's sensitivity to unique contextual elements. Our findings offer a mechanism to integrate models of temporal association by drift with event segmentation by episodic boundaries.

Functional and anatomical connectivity predict brain stimulation's mnemonic effects.

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.

Biomarker-guided neuromodulation aids memory in traumatic brain injury.

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 of 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.

Machine learning classifiers for electrode selection in the design of closed-loop neuromodulation devices for episodic memory improvement.

Successful neuromodulation approaches to alter episodic memory require closed-loop stimulation predicated on the effective classification of brain states. The practical implementation of such strategies requires prior decisions regarding electrode implantation locations. Using a data-driven approach, we employ support vector machine (SVM) classifiers to identify high-yield brain targets on a large data set of 75 human intracranial electroencephalogram subjects performing the free recall (FR) task. Further, we address whether the conserved brain regions provide effective classification in an alternate (associative) memory paradigm along with FR, as well as testing unsupervised classification methods that may be a useful adjunct to clinical device implementation. Finally, we use random forest models to classify functional brain states, differentiating encoding versus retrieval versus non-memory behavior such as rest and mathematical processing. We then test how regions that exhibit good classification for the likelihood of recall success in the SVM models overlap with regions that differentiate functional brain states in the random forest models. Finally, we lay out how these data may be used in the design of neuromodulation devices.

Riding brain "waves" to identify human memory genes.

While there is extensive research on memory-related oscillations and brain gene expression, the relationship between oscillations and gene expression has rarely been studied. Recently, progress has been made to identify specific genes associated with oscillations that are correlated with episodic memory. Neocortical regions, in particular the temporal pole, have been examined in this line of research due to their accessibility during neurosurgical procedures. By harnessing this accessibility, a unique and powerful study design has allowed gene expression and intracranial oscillatory data to be sourced from the same human patients. These studies have identified a plethora of understudied gene targets that should be further characterized with respect to human brain function. Future work should extend to other brain regions to increase our understanding of the genetic signatures of oscillations and, ultimately, human cognition.

A Control-Theoretical System for Modulating Hippocampal Gamma Oscillations Using Stimulation of the Posterior Cingulate Cortex.

Closed-loop stimulation for targeted modulation of brain signals has emerged as a promising strategy for episodic memory restoration. In parallel, closed-loop neuromodulation strategies have been applied to treat brain conditions including drug-resistant depression, Parkinson's Disease, and epilepsy. In this study, we seek to apply control theoretical principles to achieve closed loop modulation of hippocampal oscillatory activity. We focus on hippocampal gamma power, a signal with an established association for episodic memory processing, which may be a promising 'biomarker' for the modulation of memory performance. To develop a closed-loop stimulation paradigm that effectively modulates hippocampal gamma power, we use a novel data-set in which open-loop stimulation was applied to the posterior cingulate cortex and hippocampal gamma power was recorded during the encoding of episodic memories. The dataset was used to design and evaluate a linear quadratic integral (LQI) servo-controller in order to determine its viability for in-vivo use. In our simulation framework, we demonstrate that applying an LQI servo controller based on an autoregressive with exogenous input (ARX) plant model achieves effective control of hippocampal gamma power in 15 out of 17 experimental subjects. We demonstrate that we are able to modulate gamma power using stimulation thresholds that are physiologically safe and on time scales that are reasonable for application in a clinical system. We outline further experimentation to test our proposed system and compare our findings to emerging closed-loop neuromodulation strategies.

Nuclei isolation from surgically resected human hippocampus.

Single-nucleus RNA sequencing (snRNA-seq), where nuclear transcriptomes are a proxy to cellular transcriptomes, has been used to profile human brain. snRNA-seq is sensitive to tissue processing, tissue quality, postmortem interval time, and cellular debris. This protocol outlines steps for the isolation of high-quality nuclei from surgically resected human brain tissue followed by a sucrose gradient yielding neuronal and non-neuronal nuclei enabling unbiased analysis of various cell types. For complete details on the use and execution of this protocol, please refer to Ayhan et al. (2021).

Features of intracranial interictal epileptiform discharges associated with memory encoding.

OBJECTIVE: Interictal epileptiform discharges (IEDs) were shown to be associated with cognitive impairment in persons with epilepsy. Previous studies indicated that IED rate, location, timing, and spatial relation to the seizure onset zone could predict an IED's impact on memory encoding and retrieval if they occurred in lateral temporal, mesial temporal, or parietal regions. In this study, we explore the influence that other IED properties (e.g., amplitude, duration, white matter classification) have on memory performance. We were specifically interested in investigating the influence that lateral temporal IEDs have on memory encoding. METHODS: Two hundred sixty-one subjects with medication-refractory epilepsy undergoing intracranial electroencephalographic monitoring performed multiple sessions of a delayed free-recall task (n = 671). Generalized linear mixed models were utilized to examine the relationship between IED properties and memory performance. RESULTS: We found that increased IED rate, IEDs propagating in white matter, and IEDs localized to the left middle temporal region were associated with poorer memory performance. For lateral temporal IEDs, we observed a significant interaction between IED white matter categorization and amplitude, where IEDs with an increased amplitude and white matter propagation were associated with reduced memory performance. Additionally, changes in alpha power after an IED showed a significant positive correlation with memory performance. SIGNIFICANCE: Our results suggest that IED properties may be useful for predicting the impact an IED has on memory encoding. We provide an essential step toward understanding pathological versus potentially beneficial interictal epileptiform activity.

Interictal Epileptiform Discharges are Task Dependent and are Associated with Lasting Electrocorticographic Changes.

The factors that control the occurrence of interictal epileptiform discharges (IEDs) are not well understood. We suspected that this phenomenon reflects an attention-dependent suppression of interictal epileptiform activity. We hypothesized that IEDs would occur less frequently when a subject viewed a task-relevant stimulus compared with viewing a blank screen. Furthermore, IEDs have been shown to impair memory when they occur in certain regions during the encoding or recall phases of a memory task. Although these discharges have a short duration, their impact on memory suggests that they have longer lasting electrophysiological effects. We found that IEDs were associated with an increase in low-frequency power and a change in the balance between low- and high-frequency oscillations for several seconds. We found that the occurrence of IEDs is modified by whether a subject is attending to a word displayed on screen or is observing a blank screen. In addition, we found that discharges in brain regions in every lobe impair memory. These findings elucidate the relationship between IEDs and memory impairment and reveal the task dependence of the occurrence of IEDs.

Distinct cortical systems reinstate the content and context of episodic memories.

Episodic recall depends upon the reinstatement of cortical activity present during the formation of a memory. Evidence from functional neuroimaging and invasive recordings in humans suggest that reinstatement organizes our memories by time or content, yet the neural systems involved in reinstating these unique types of information remain unclear. Here, combining computational modeling and intracranial recordings from 69 epilepsy patients, we show that two cortical systems uniquely reinstate the semantic content and temporal context of previously studied items during free recall. Examining either the posterior medial or anterior temporal networks, we find that forward encoding models trained on the brain's response to the temporal and semantic attributes of items can predict the serial position and semantic category of unseen items. During memory recall, these models uniquely link reinstatement of temporal context and semantic content to these posterior and anterior networks, respectively. These findings demonstrate how specialized cortical systems enable the human brain to target specific memories.

Distinct neurophysiological correlates of the fMRI BOLD signal in the hippocampus and neocortex.

Functional magnetic resonance imaging (fMRI) is among the foremost methods for mapping human brain function but provides only an indirect measure of underlying neural activity. Recent findings suggest that the neurophysiological correlates of the fMRI blood-oxygen-level-dependent (BOLD) signal might be regionally specific. We examined the neurophysiological correlates of the fMRI BOLD signal in the hippocampus and neocortex, where differences in neural architecture might result in a different relationship between the respective signals. Fifteen human neurosurgical patients (10 female, 5 male) implanted with depth electrodes performed a verbal free recall task while electrophysiological activity was recorded simultaneously from hippocampal and neocortical sites. The same patients subsequently performed a similar version of the task during a later fMRI session. Subsequent memory effects (SMEs) were computed for both imaging modalities as patterns of encoding-related brain activity predictive of later free recall. Linear mixed-effects modelling revealed that the relationship between BOLD and gamma-band SMEs was moderated by the lobar location of the recording site. BOLD and high gamma (70-150 Hz) SMEs positively covaried across much of the neocortex. This relationship was reversed in the hippocampus, where a negative correlation between BOLD and high gamma SMEs was evident. We also observed a negative relationship between BOLD and low gamma (30-70 Hz) SMEs in the medial temporal lobe more broadly. These results suggest that the neurophysiological correlates of the BOLD signal in the hippocampus differ from those observed in the neocortex.Significance Statement:The blood-oxygen-level-dependent (BOLD) signal forms the basis of fMRI but provides only an indirect measure of neural activity. Task-related modulation of BOLD signals are typically equated with changes in gamma-band activity; however, relevant empirical evidence comes largely from the neocortex. We examined neurophysiological correlates of the BOLD signal in the hippocampus, where the differing neural architecture might result in a different relationship between the respective signals. We identified a positive relationship between encoding-related changes in BOLD and gamma-band activity in frontal and parietal cortex. This effect was reversed in the hippocampus, where BOLD and gamma-band effects negatively covaried. These results suggest regional variability in the transfer function between neural activity and the BOLD signal in the hippocampus and neocortex.

Resolving cellular and molecular diversity along the hippocampal anterior-to-posterior axis in humans.

The hippocampus supports many facets of cognition, including learning, memory, and emotional processing. Anatomically, the hippocampus runs along a longitudinal axis, posterior to anterior in primates. The structure, function, and connectivity of the hippocampus vary along this axis. In human hippocampus, longitudinal functional heterogeneity remains an active area of investigation, and structural heterogeneity has not been described. To understand the cellular and molecular diversity along the hippocampal long axis in human brain and define molecular signatures corresponding to functional domains, we performed single-nuclei RNA sequencing on surgically resected human anterior and posterior hippocampus from epilepsy patients, identifying differentially expressed genes at cellular resolution. We further identify axis- and cell-type-specific gene expression signatures that differentially intersect with human genetic signals, identifying cell-type-specific genes in the posterior hippocampus for cognitive function and the anterior hippocampus for mood and affect. These data are accessible as a public resource through an interactive website.

Gene-expression correlates of the oscillatory signatures supporting human episodic memory encoding.

In humans, brain oscillations support critical features of memory formation. However, understanding the molecular mechanisms underlying this activity remains a major challenge. Here, we measured memory-sensitive oscillations using intracranial electroencephalography recordings from the temporal cortex of patients performing an episodic memory task. When these patients subsequently underwent resection, we employed transcriptomics on the temporal cortex to link gene expression with brain oscillations and identified genes correlated with oscillatory signatures of memory formation across six frequency bands. A co-expression analysis isolated oscillatory signature-specific modules associated with neuropsychiatric disorders and ion channel activity, with highly correlated genes exhibiting strong connectivity within these modules. Using single-nucleus transcriptomics, we further revealed that these modules are enriched for specific classes of both excitatory and inhibitory neurons, and immunohistochemistry confirmed expression of highly correlated genes. This unprecedented dataset of patient-specific brain oscillations coupled to genomics unlocks new insights into the genetic mechanisms that support memory encoding.

Cross-regional phase amplitude coupling supports the encoding of episodic memories.

Phase amplitude coupling (PAC) between theta and gamma oscillations represents a key neurophysiological mechanism that promotes the temporal organization of oscillatory activity. For this reason, PAC has been implicated in item/context integration for episodic processes, including coordinating activity across multiple cortical regions. While data in humans has focused principally on PAC within a single brain region, data in rodents has revealed evidence that the phase of the hippocampal theta oscillation modulates gamma oscillations in the cortex (and vice versa). This pattern, termed cross-regional PAC (xPAC), has not previously been observed in human subjects engaged in mnemonic processing. We use a unique dataset with intracranial electrodes inserted simultaneously into the hippocampus and seven cortical regions across 40 human subjects to (1) test for the presence of significant cross-regional PAC (xPAC), (2) to establish that the magnitude of xPAC predicts memory encoding success, (3) to describe specific frequencies within the broad 2-9 Hz theta range that govern hippocampal-cortical interactions in xPAC, and (4) compare anterior versus posterior hippocampal xPAC patterns. We find that strong functional xPAC occurs principally between the hippocampus and other mesial temporal structures, namely entorhinal and parahippocampal cortices, and that xPAC is overall stronger for posterior hippocampal connections. We also show that our results are not confounded by alternative factors such as inter-regional phase synchrony, local PAC occurring within cortical regions, or artifactual theta oscillatory waveforms.

Factors correlated with intracranial interictal epileptiform discharges in refractory epilepsy.

OBJECTIVE: This study was undertaken to evaluate the influence that subject-specific factors have on intracranial interictal epileptiform discharge (IED) rates in persons with refractory epilepsy. METHODS: One hundred fifty subjects with intracranial electrodes performed multiple sessions of a free recall memory task; this standardized task controlled for subject attention levels. We utilized a dominance analysis to rank the importance of subject-specific factors based on their relative influence on IED rates. Linear mixed-effects models were employed to comprehensively examine factors with highly ranked importance. RESULTS: Antiseizure medication (ASM) status, time of testing, and seizure onset zone (SOZ) location were the highest-ranking factors in terms of their impact on IED rates. The average IED rate of electrodes in SOZs was 34% higher than the average IED rate of electrodes outside of SOZs (non-SOZ; p < .001). However, non-SOZ electrodes had similar IED rates regardless of the subject's SOZ location (p = .99). Subjects on older generation (p < .001) and combined generation (p < .001) ASM regimens had significantly lower IED rates relative to the group taking no ASMs; newer generation ASM regimens demonstrated a nonsignificant association with IED rates (p = .13). Of the ASMs included in this study, the following ASMs were associated with significant reductions in IED rates: levetiracetam (p < .001), carbamazepine (p < .001), lacosamide (p = .03), zonisamide (p = .01), lamotrigine (p = .03), phenytoin (p = .03), and topiramate (p = .01). We observed a nonsignificant association between time of testing and IED rates (morning-afternoon p = .15, morning-evening p = .85, afternoon-evening p = .26). SIGNIFICANCE: The current study ranks the relative influence that subject-specific factors have on IED rates and highlights the importance of considering certain factors, such as SOZ location and ASM status, when analyzing IEDs for clinical or research purposes.

Hippocampal Theta Oscillations Support Successful Associative Memory Formation.

Models of memory formation posit that episodic memory formation depends critically on the hippocampus, which binds features of an event to its context. For this reason, the contrast between study items that are later recollected with their associative pair versus those for which no association is made fails should reveal electrophysiological patterns in the hippocampus selectively involved in associative memory encoding. Extensive data from studies in rodents support a model in which theta oscillations fulfill this role, but results in humans have not been as clear. Here, we used an associative recognition memory procedure to identify hippocampal correlates of successful associative memory encoding and retrieval in patients (10 females and 9 males) undergoing intracranial EEG monitoring. We identified a dissociation between 2-5 Hz and 5-9 Hz theta oscillations, by which power increases in 2-5 Hz oscillations were uniquely linked with successful associative memory in both the anterior and posterior hippocampus. These oscillations exhibited a significant phase reset that also predicted successful associative encoding and distinguished recollected from nonrecollected items at retrieval, as well as contributing to relatively greater reinstatement of encoding-related patterns for recollected versus nonrecollected items. Our results provide direct electrophysiological evidence that 2-5 Hz hippocampal theta oscillations preferentially support the formation of associative memories, although we also observed memory-related effects in the 5-9 Hz frequency range using measures such as phase reset and reinstatement of oscillatory activity.SIGNIFICANCE STATEMENT Models of episodic memory encoding predict that theta oscillations support the formation of interitem associations. We used an associative recognition task designed to elicit strong hippocampal activation to test this prediction in human neurosurgical patients implanted with intracranial electrodes. The findings suggest that 2-5 Hz theta oscillatory power and phase reset in the hippocampus are selectively associated with associative memory judgments. Furthermore, reinstatement of oscillatory patterns in the hippocampus was stronger for successful recollection. Collectively, the findings support a role for hippocampal theta oscillations in human associative memory.

Direct brain recordings identify hippocampal and cortical networks that distinguish successful versus failed episodic memory retrieval.

Human data collected using noninvasive imaging techniques have established the importance of parietal regions towards episodic memory retrieval, including the angular gyrus and posterior cingulate cortex. Such regions comprise part of a putative core episodic retrieval network. In free recall, comparisons between contextually appropriate and inappropriate recall events (i.e. prior list intrusions) provide the opportunity to study memory retrieval networks supporting veridical recall, and existing findings predict that differences in electrical activity in these brain regions should be identified according to the accuracy of recall. However, prior iEEG studies, utilizing principally subdural grid electrodes, have not fully characterized brain activity in parietal regions during memory retrieval and have not examined connectivity between core recollection areas and the hippocampus or prefrontal cortex. Here, we employed a data set obtained from 100 human patients implanted with stereo EEG electrodes for seizure mapping purposes as they performed a free recall task. This data set allowed us to separately analyze activity in midline versus lateral parietal brain regions, and in anterior versus posterior hippocampus, to identify areas in which retrieval-related activity predicted the recollection of a correct versus an incorrect memory. With the wide coverage afforded by the stereo EEG approach, we were also able to examine interregional connectivity. Our key findings were that differences in gamma band activity in the angular gyrus, precuneus, posterior temporal cortex, and posterior (more than anterior) hippocampus discriminated accurate versus inaccurate recall as well as active retrieval versus memory search. The left angular gyrus exhibited a significant power decrease preceding list intrusions as well as unique phase-amplitude coupling properties, whereas the prefrontal cortex was unique in exhibiting a power increase during list intrusions. Analysis of connectivity revealed significant hemispheric asymmetry, with relatively sparse left-sided functional connections compared to the right hemisphere. One exception to this finding was elevated connectivity between the prefrontal cortex and left angular gyrus. This finding is interpreted as evidence for the engagement of prefrontal cortex in memory monitoring and mnemonic decision-making.

The effects of direct brain stimulation in humans depend on frequency, amplitude, and white-matter proximity.

BACKGROUND: Researchers have used direct electrical brain stimulation to treat a range of neurological and psychiatric disorders. However, for brain stimulation to be maximally effective, clinicians and researchers should optimize stimulation parameters according to desired outcomes. OBJECTIVE: The goal of our large-scale study was to comprehensively evaluate the effects of stimulation at different parameters and locations on neuronal activity across the human brain. METHODS: To examine how different kinds of stimulation affect human brain activity, we compared the changes in neuronal activity that resulted from stimulation at a range of frequencies, amplitudes, and locations with direct human brain recordings. We recorded human brain activity directly with electrodes that were implanted in widespread regions across 106 neurosurgical epilepsy patients while systematically stimulating across a range of parameters and locations. RESULTS: Overall, stimulation most often had an inhibitory effect on neuronal activity, consistent with earlier work. When stimulation excited neuronal activity, it most often occurred from high-frequency stimulation. These effects were modulated by the location of the stimulating electrode, with stimulation sites near white matter more likely to cause excitation and sites near gray matter more likely to inhibit neuronal activity. CONCLUSION: By characterizing how different stimulation parameters produced specific neuronal activity patterns on a large scale, our results provide an electrophysiological framework that clinicians and researchers may consider when designing stimulation protocols to cause precisely targeted changes in human brain activity.