MTL neurons phase-lock to human hippocampal theta.

Memory formation depends on neural activity across a network of regions, including the hippocampus and broader medial temporal lobe (MTL). Interactions between these regions have been studied indirectly using functional MRI, but the bases for interregional communication at a cellular level remain poorly understood. Here, we evaluate the hypothesis that oscillatory currents in the hippocampus synchronize the firing of neurons both within and outside the hippocampus. We recorded extracellular spikes from 1854 single- and multi-units simultaneously with hippocampal local field potentials (LFPs) in 28 neurosurgical patients who completed virtual navigation experiments. A majority of hippocampal neurons phase-locked to oscillations in the slow (2-4 Hz) or fast (6-10 Hz) theta bands, with a significant subset exhibiting nested slow theta × beta frequency (13-20 Hz) phase-locking. Outside of the hippocampus, phase-locking to hippocampal oscillations occurred only at theta frequencies and primarily among neurons in the entorhinal cortex and amygdala. Moreover, extrahippocampal neurons phase-locked to hippocampal theta even when theta did not appear locally. These results indicate that spike-time synchronization with hippocampal theta is a defining feature of neuronal activity in the hippocampus and structurally connected MTL regions. Theta phase-locking could mediate flexible communication with the hippocampus to influence the content and quality of memories.

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.

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.

TMS provokes target-dependent intracranial rhythms across human cortical and subcortical sites.

Transcranial magnetic stimulation (TMS) is increasingly deployed in the treatment of neuropsychiatric illness, under the presumption that stimulation of specific cortical targets can alter ongoing neural activity and cause circuit-level changes in brain function. While the electrophysiological effects of TMS have been extensively studied with scalp electroencephalography (EEG), this approach is most useful for evaluating low-frequency neural activity at the cortical surface. As such, little is known about how TMS perturbs rhythmic activity among deeper structures - such as the hippocampus and amygdala - and whether stimulation can alter higher-frequency oscillations. Recent work has established that TMS can be safely used in patients with intracranial electrodes (iEEG), allowing for direct neural recordings at sufficient spatiotemporal resolution to examine localized oscillatory responses across the frequency spectrum. To that end, we recruited 17 neurosurgical patients with indwelling electrodes and recorded neural activity while patients underwent repeated trials of single-pulse TMS at several cortical sites. Stimulation to the dorsolateral prefrontal cortex (DLPFC) drove widespread low-frequency increases (3-8Hz) in frontolimbic cortices, as well as high-frequency decreases (30-110Hz) in frontotemporal areas, including the hippocampus. Stimulation to parietal cortex specifically provoked low-frequency responses in the medial temporal lobe. While most low-frequency activity was consistent with brief evoked responses, anterior frontal regions exhibited induced theta oscillations following DLPFC stimulation. Taken together, we established that non-invasive stimulation can (1) provoke a mixture of low-frequency evoked power and induced theta oscillations and (2) suppress high-frequency activity in deeper brain structures not directly accessed by stimulation itself.

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.

Complete genomes and comparative analyses of Streptomyces phages that influence secondary metabolism and sporulation.

Bacteria in the genus Streptomyces are found ubiquitously in nature and are known for the number and diversity of specialized metabolites they produce, as well as their complex developmental lifecycle. Studies of the viruses that prey on Streptomyces, known as phages, have aided the development of tools for genetic manipulation of these bacteria, as well as contributing to a deeper understanding of Streptomyces and their behaviours in the environment. Here, we present the genomic and biological characterization of twelve Streptomyces phages. Genome analyses reveal that these phages are closely related genetically, while experimental approaches show that they have broad overlapping host ranges, infect early in the Streptomyces lifecycle, and induce secondary metabolite production and sporulation in some Streptomyces species. This work expands the group of characterized Streptomyces phages and improves our understanding of Streptomyces phage-host dynamics.

Theta-burst stimulation entrains frequency-specific oscillatory responses.

BACKGROUND: Brain stimulation has emerged as a powerful tool in human neuroscience, becoming integral to next-generation psychiatric and neurologic therapeutics. Theta-burst stimulation (TBS), in which electrical pulses are delivered in rhythmic bouts of 3-8 Hz, seeks to recapitulate neural activity seen endogenously during cognitive tasks. A growing literature suggests that TBS can be used to alter or enhance cognitive processes, but little is known about how these stimulation events influence underlying neural activity. OBJECTIVE: Our study sought to investigate the effect of direct electrical TBS on mesoscale neural activity in humans by asking (1) whether TBS evokes persistent theta oscillations in cortical areas, (2) whether these oscillations occur at the stimulated frequency, and (3) whether stimulation events propagate in a manner consistent with underlying functional and structural brain architecture. METHODS: We recruited 20 neurosurgical epilepsy patients with indwelling electrodes and delivered direct cortical TBS at varying locations and frequencies. Simultaneous iEEG was recorded from non-stimulated electrodes and analyzed to understand how TBS influences mesoscale neural activity. RESULTS: We found that TBS rapidly evoked theta rhythms in widespread brain regions, preferentially at the stimulation frequency, and that these oscillations persisted for hundreds of milliseconds post stimulation offset. Furthermore, the functional connectivity between recording and stimulation sites predicted the strength of theta response, suggesting that underlying brain architecture guides the flow of stimulation through the brain. CONCLUSIONS: By demonstrating that cortical TBS induces frequency-specific oscillatory responses, our results suggest this technology can be used to directly and predictably influence the activity of cognitively-relevant brain networks.

Biomarkers of memory variability in traumatic brain injury.

Traumatic brain injury is a leading cause of cognitive disability and is often associated with significant impairment in episodic memory. In traumatic brain injury 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 traumatic brain injury (n = 37) and a group of controls without traumatic brain injury (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 traumatic brain injury patients and controls. The two groups also displayed similar patterns of theta-frequency connectivity during successful encoding periods. These biomarkers of successful memory, highly conserved between traumatic brain injury patients and controls, could serve as the basis for novel therapies that target disordered memory across diverse forms of neurological disease.

Theta Oscillations in Human Memory.

Theta frequency (4-8 Hz) fluctuations of the local field potential have long been implicated in learning and memory. Human studies of episodic memory, however, have provided mixed evidence for theta's role in successful learning and remembering. Re-evaluating these conflicting findings leads us to conclude that: (i) successful memory is associated both with increased narrow-band theta oscillations and a broad-band tilt of the power spectrum; (ii) theta oscillations specifically support associative memory, whereas the spectral tilt reflects a general index of activation; and (iii) different cognitive contrasts (generalized versus specific to memory), recording techniques (invasive versus noninvasive), and referencing schemes (local versus global) alter the balance between the two phenomena to make one or the other more easily detectable.

Hippocampal theta codes for distances in semantic and temporal spaces.

The medial temporal lobe (MTL) is known to support episodic memory and spatial navigation, raising the possibility that its true function is to form "cognitive maps" of any kind of information. Studies in humans and animals support the idea that the hippocampal theta rhythm (4 to 8 Hz) is key to this mapping function, as it has been repeatedly observed during spatial navigation tasks. If episodic memory and spatial navigation are 2 sides of the same coin, we hypothesized that theta oscillations might reflect relations between explicitly nonspatial items, such as words. We asked 189 neurosurgical patients to perform a verbal free-recall task, of which 96 had indwelling electrodes placed in the MTL. Subjects were instructed to remember short lists of sequentially presented nouns. We found that hippocampal theta power and connectivity during item retrieval coded for semantic distances between words, as measured using word2vec-derived subspaces. Additionally, hippocampal theta indexed temporal distances between words after filtering lists on recall performance, to ensure adequate dynamic range in time. Theta effects were noted only for semantic subspaces of 1 dimension, indicating a substantial compression of the possible semantic feature space. These results lend further support to our growing confidence that the MTL forms cognitive maps of arbitrary representational spaces, helping to reconcile longstanding differences between the spatial and episodic memory literatures.

Functional control of electrophysiological network architecture using direct neurostimulation in humans.

Chronically implantable neurostimulation devices are becoming a clinically viable option for treating patients with neurological disease and psychiatric disorders. Neurostimulation offers the ability to probe and manipulate distributed networks of interacting brain areas in dysfunctional circuits. Here, we use tools from network control theory to examine the dynamic reconfiguration of functionally interacting neuronal ensembles during targeted neurostimulation of cortical and subcortical brain structures. By integrating multimodal intracranial recordings and diffusion-weighted imaging from patients with drug-resistant epilepsy, we test hypothesized structural and functional rules that predict altered patterns of synchronized local field potentials. We demonstrate the ability to predictably reconfigure functional interactions depending on stimulation strength and location. Stimulation of areas with structurally weak connections largely modulates the functional hubness of downstream areas and concurrently propels the brain towards more difficult-to-reach dynamical states. By using focal perturbations to bridge large-scale structure, function, and markers of behavior, our findings suggest that stimulation may be tuned to influence different scales of network interactions driving cognition.

Multivariate stochastic volatility modeling of neural data.

Because multivariate autoregressive models have failed to adequately account for the complexity of neural signals, researchers have predominantly relied on non-parametric methods when studying the relations between brain and behavior. Using medial temporal lobe (MTL) recordings from 96 neurosurgical patients, we show that time series models with volatility described by a multivariate stochastic latent-variable process and lagged interactions between signals in different brain regions provide new insights into the dynamics of brain function. The implied volatility inferred from our process positively correlates with high-frequency spectral activity, a signal that correlates with neuronal activity. We show that volatility features derived from our model can reliably decode memory states, and that this classifier performs as well as those using spectral features. Using the directional connections between brain regions during complex cognitive process provided by the model, we uncovered perirhinal-hippocampal desynchronization in the MTL regions that is associated with successful memory encoding.

Dynamic Theta Networks in the Human Medial Temporal Lobe Support Episodic Memory.

The medial temporal lobe (MTL) is a locus of episodic memory in the human brain. It is comprised of cytologically distinct subregions that, in concert, give rise to successful encoding and retrieval of context-dependent memories. However, the functional connections between these subregions are poorly understood. To determine functional connectivity among MTL subregions, we had 131 subjects fitted with indwelling electrodes perform a verbal memory task and asked how encoding or retrieval correlated with inter-regional synchronization. Using phase-based measures of connectivity, we found that synchronous theta (4-8 Hz) activity underlies successful episodic memory. During encoding, we observed a dynamic pattern of connections converging on the left entorhinal cortex, beginning with the perirhinal cortex and shifting through hippocampal subfields. Retrieval-associated networks demonstrated enhanced involvement of the subiculum and CA1, reflecting a substantial reorganization of the encoding network. We posit that coherent theta activity within the MTL marks periods of successful memory, but distinct patterns of connectivity dissociate key stages of memory processing.

Safety, Tolerability, and Feasibility of Young Plasma Infusion in the Plasma for Alzheimer Symptom Amelioration Study: A Randomized Clinical Trial.

Importance: Young mouse plasma restores memory in aged mice, but, to our knowledge, the effects are unknown in patients with Alzheimer disease (AD). Objective: To assess the safety, tolerability, and feasibility of infusions of young fresh frozen plasma (yFFP) from donors age 18 to 30 years in patients with AD. Design, Setting, and Participants: The Plasma for Alzheimer Symptom Amelioration (PLASMA) study randomized 9 patients under a double-blind crossover protocol to receive 4 once-weekly infusions of either 1 unit (approximately 250 mL) of yFFP from male donors or 250 mL of saline, followed by a 6-week washout and crossover to 4 once-weekly infusions of an alternate treatment. Patients and informants were masked to treatment and subjective measurements. After an open-label amendment, 9 patients received 4 weekly yFFP infusions only and their subjective measurements were unmasked. Patients were enrolled solely at Stanford University, a tertiary academic medical center, from September 2014 to December 2016, when enrollment reached its target. Eighteen consecutive patients with probable mild to moderate AD dementia, a Mini-Mental State Examination (score of 12 to 24 inclusive), and an age of 50 to 90 years were enrolled. Thirty-one patients were screened and 13 were excluded: 11 failed the inclusion criteria and 2 declined to participate. Interventions: One unit of yFFP from male donors/placebo infused once weekly for 4 weeks. Main Outcome and Measures: The primary outcomes were the safety, tolerability, and feasibility of 4 weekly yFFP infusions. Safety end point analyses included all patients who received the study drug/placebo. Results: There was no difference in the age (mean [SD], 74.17 [7.96] years), sex (12 women [67%]), or baseline Mini-Mental State Examination score (mean [SD], 19.39 [3.24]) between the crossover (n = 9) and open-label groups (n = 9). There were no related serious adverse events. One patient discontinued participation because of urticaria and another because of an unrelated stroke. There was no statistically significant difference between the plasma (17 [94.4%]) and placebo (9 [100.0%]) cohorts for other adverse events, which were mild to moderate in severity. The most common adverse events in the plasma group included hypertension (3 [16.7%]), dizziness (2 [11.1%]), sinus bradycardia (3 [16.7%]), headache (3 [16.7%]), and sinus tachycardia (3 [16.7%]). The mean visit adherence (n = 18) was 86% (interquartile range, 87%-100%) and adherence, accounting for a reduction in the total visit requirement due to early patient discontinuation, was 96% (interquartile range, 89%-100%). Conclusions and Relevance: The yFFP treatment was safe, well tolerated, and feasible. The study's limitations were the small sample size, short duration, and change in study design. The results warrant further exploration in larger, double-blinded placebo-controlled clinical trials. Trial Registration: ClinicalTrials.gov Identifier: NCT02256306.

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior.

Deep neural networks rival the representation of primate IT cortex for core visual object recognition.

The primate visual system achieves remarkable visual object recognition performance even in brief presentations, and under changes to object exemplar, geometric transformations, and background variation (a.k.a. core visual object recognition). This remarkable performance is mediated by the representation formed in inferior temporal (IT) cortex. In parallel, recent advances in machine learning have led to ever higher performing models of object recognition using artificial deep neural networks (DNNs). It remains unclear, however, whether the representational performance of DNNs rivals that of the brain. To accurately produce such a comparison, a major difficulty has been a unifying metric that accounts for experimental limitations, such as the amount of noise, the number of neural recording sites, and the number of trials, and computational limitations, such as the complexity of the decoding classifier and the number of classifier training examples. In this work, we perform a direct comparison that corrects for these experimental limitations and computational considerations. As part of our methodology, we propose an extension of "kernel analysis" that measures the generalization accuracy as a function of representational complexity. Our evaluations show that, unlike previous bio-inspired models, the latest DNNs rival the representational performance of IT cortex on this visual object recognition task. Furthermore, we show that models that perform well on measures of representational performance also perform well on measures of representational similarity to IT, and on measures of predicting individual IT multi-unit responses. Whether these DNNs rely on computational mechanisms similar to the primate visual system is yet to be determined, but, unlike all previous bio-inspired models, that possibility cannot be ruled out merely on representational performance grounds.

Performance-optimized hierarchical models predict neural responses in higher visual cortex.

The ventral visual stream underlies key human visual object recognition abilities. However, neural encoding in the higher areas of the ventral stream remains poorly understood. Here, we describe a modeling approach that yields a quantitatively accurate model of inferior temporal (IT) cortex, the highest ventral cortical area. Using high-throughput computational techniques, we discovered that, within a class of biologically plausible hierarchical neural network models, there is a strong correlation between a model's categorization performance and its ability to predict individual IT neural unit response data. To pursue this idea, we then identified a high-performing neural network that matches human performance on a range of recognition tasks. Critically, even though we did not constrain this model to match neural data, its top output layer turns out to be highly predictive of IT spiking responses to complex naturalistic images at both the single site and population levels. Moreover, the model's intermediate layers are highly predictive of neural responses in the V4 cortex, a midlevel visual area that provides the dominant cortical input to IT. These results show that performance optimization--applied in a biologically appropriate model class--can be used to build quantitative predictive models of neural processing.

Olfaction in aging and Alzheimer's disease: event-related potentials to a cross-modal odor-recognition memory task discriminate ApoE epsilon4+ and ApoE epsilon 4- individuals.

Alzheimer's disease (AD) is a devastating neurodegenerative condition that affects more than 5 million Americans. Currently, a definitive and unequivocal diagnosis of AD can only be confirmed histopathogically via postmortem autopsy, demonstrating the need for objective measures of cognitive functioning for those at risk for AD. The single most important genetic risk factor of AD is the apolipoprotein E (ApoE) epsilon4 allele. The present study investigated olfactory and cognitive processing deficits in ApoE epsilon4(+) individuals using a cross-modal recognition memory task and an objective electrophysiological measure, the event-related potential (ERP). Ten epsilon4(+) individuals (5 M, 5 F, mean [M]= 75.1 years) and 10 age- and gender-matched epsilon4(-) individuals (5 M, 5 F, M = 71 years) sequentially encoded a set of 16 olfactory stimuli and were subsequently shown names of odors previously presented (targets) or not (foils). EEG activity was recorded from 19 electrodes as participants distinguished targets from foils using a two-button mouse. P3 latencies were significantly longer in epsilon4(+) individuals, and intraclass correlations demonstrated differential activity between the two groups. These findings are consistent with a compensatory hypothesis, which posits that nondemented epsilon4(+) individuals will expend greater effort in cognitive processing or engage in alternative strategies and therefore require greater activation of neural tissue or recruitment of different neural populations. The findings also suggest that cross-modal ERP studies of recognition memory discriminate early neurocognitive changes in ApoE epsilon4(+) and ApoE epsilon4(-) individuals and may contribute to identifying the phenotype of persons who will develop Alzheimer's disease.