Enhancement of encoding and retrieval functions through theta phase-specific manipulation of hippocampus

Entorhinal cortex represents task-relevant remote locations independent of CA1

Neurons can collectively represent the current sensory experience while an animal is exploring its environment or remote experiences while the animal is immobile. These remote representations can reflect learned associations1-3 and be required for learning4. Neurons in the medial entorhinal cortex (MEC) reflect the animal's current location during movement5, but little is known about what MEC neurons collectively represent during immobility. Here, we recorded thousands of neurons in superficial MEC and dorsal CA1 as mice learned to associate two pairs of rewarded locations. We found that during immobility, the MEC neural population frequently represented positions far from the animal's location, which we defined as 'non-local coding'. Cells with spatial firing fields at remote locations drove non-local coding, even as cells representing the current position remained active. While MEC non-local coding has been reported during sharp-wave ripples in downstream CA16, we observed non-local coding more often outside of ripples. In fact, CA1 activity was less coordinated with MEC during non-local coding. We further observed that non-local coding was pertinent to the task, as MEC preferentially represented remote task-relevant locations at appropriate times, while rarely representing task-irrelevant locations. Together, this work raises the possibility that MEC non-local coding could strengthen associations between locations independently from CA1.

Hippocampal-prefrontal communication subspaces align with behavioral and network patterns in a spatial memory task

Rhythmic network states have been theorized to facilitate communication between brain regions, but how these oscillations influence communication subspaces, i.e, the low-dimensional neural activity patterns that mediate inter-regional communication, and in turn how subspaces impact behavior remains unclear. Using a spatial memory task in rats, we simultaneously recorded ensembles from hippocampal CA1 and the prefrontal cortex (PFC) to address this question. We found that task behaviors best aligned with low-dimensional, shared subspaces between these regions, rather than local activity in either region. Critically, both network oscillations and speed modulated the structure and performance of this communication subspace. Contrary to expectations, theta coherence did not better predict CA1-PFC shared activity, while theta power played a more significant role. To understand the communication space, we visualized shared CA1-PFC communication geometry using manifold techniques and found ring-like structures. We hypothesize that these shared activity manifolds are utilized to mediate the task behavior. These findings suggest that memory-guided behaviors are driven by shared CA1-PFC interactions that are dynamically modulated by oscillatory states, offering a novel perspective on the interplay between rhythms and behaviorally relevant neural communication.

Brain-machine interactive neuromodulation research tool with edge AI computing

Closed-loop neuromodulation with intelligence methods has shown great potentials in providing novel neuro-technology for treating neurological and psychiatric diseases. Development of brain-machine interactive neuromodulation strategies could lead to breakthroughs in precision and personalized electronic medicine. The neuromodulation research tool integrating artificial intelligent computing and performing neural sensing and stimulation in real-time could accelerate the development of closed-loop neuromodulation strategies and translational research into clinical application. In this study, we developed a brain-machine interactive neuromodulation research tool (BMINT), which has capabilities of neurophysiological signals sensing, computing with mainstream machine learning algorithms and delivering electrical stimulation pulse by pulse in real-time. The BMINT research tool achieved system time delay under 3 ms, and computing capabilities in feasible computation cost, efficient deployment of machine learning algorithms and acceleration process. Intelligent computing framework embedded in the BMINT enable real-time closed-loop neuromodulation developed with mainstream AI ecosystem resources. The BMINT could provide timely contribution to accelerate the translational research of intelligent neuromodulation by integrating neural sensing, edge AI computing and stimulation with AI ecosystems.

Retuning of hippocampal representations during sleep

Hippocampal representations that underlie spatial memory undergo continuous refinement following formation1. Here, to track the spatial tuning of neurons dynamically during offline states, we used a new Bayesian learning approach based on the spike-triggered average decoded position in ensemble recordings from freely moving rats. Measuring these tunings, we found spatial representations within hippocampal sharp-wave ripples that were stable for hours during sleep and were strongly aligned with place fields initially observed during maze exploration. These representations were explained by a combination of factors that included preconfigured structure before maze exposure and representations that emerged during θ-oscillations and awake sharp-wave ripples while on the maze, revealing the contribution of these events in forming ensembles. Strikingly, the ripple representations during sleep predicted the future place fields of neurons during re-exposure to the maze, even when those fields deviated from previous place preferences. By contrast, we observed tunings with poor alignment to maze place fields during sleep and rest before maze exposure and in the later stages of sleep. In sum, the new decoding approach allowed us to infer and characterize the stability and retuning of place fields during offline periods, revealing the rapid emergence of representations following new exploration and the role of sleep in the representational dynamics of the hippocampus.

Formation and Retrieval of Cell Assemblies in a Biologically Realistic Spiking Neural Network Model of Area CA3 in the Mouse Hippocampus

The hippocampal formation is critical for episodic memory, with area Cornu Ammonis 3 (CA3) a necessary substrate for auto-associative pattern completion. Recent theoretical and experimental evidence suggests that the formation and retrieval of cell assemblies enable these functions. Yet, how cell assemblies are formed and retrieved in a full-scale spiking neural network (SNN) of CA3 that incorporates the observed diversity of neurons and connections within this circuit is not well understood. Here, we demonstrate that a data-driven SNN model quantitatively reflecting the neuron type-specific population sizes, intrinsic electrophysiology, connectivity statistics, synaptic signaling, and long-term plasticity of the mouse CA3 is capable of robust auto-association and pattern completion via cell assemblies. Our results show that a broad range of assembly sizes could successfully and systematically retrieve patterns from heavily incomplete or corrupted cues after a limited number of presentations. Furthermore, performance was robust with respect to partial overlap of assemblies through shared cells, substantially enhancing memory capacity. These novel findings provide computational evidence that the specific biological properties of the CA3 circuit produce an effective neural substrate for associative learning in the mammalian brain.

Simultaneous two-photon imaging and wireless EEG recording in mice

Background

In vivo two-photon imaging is a reliable method with high spatial resolution that allows observation of individual neuron and dendritic activity longitudinally. Neurons in local brain regions can be influenced by global brain states such as levels of arousal and attention that change over relatively short time scales, such as minutes. As such, the scientific rigor of investigating regional neuronal activities could be enhanced by considering the global brain state.

New method

In order to assess the global brain state during in vivo two-photon imaging, CBRAIN (collective brain research platform aided by illuminating neural activity), a wireless EEG collecting and labeling device, was controlled by the same computer of two-photon microscope. In an experiment to explore neuronal responses to isoflurane anesthesia through two-photon imaging, we investigated whether the response of individual cells correlated with concurrent EEG changes induced by anesthesia.

Results

In two-photon imaging, calcium activities of the excitatory neurons in the primary somatosensory cortex disappeared in about 30s after to the initiation of isoflurane anesthesia. The simultaneously recorded EEG showed various transitional activity for about 7 min from the initiation of anesthesia and continued with burst and suppression alternating pattern thereafter. As such, there was a dissociation between excitatory neuron activity of the primary somatosensory cortex and the global brain activity under anesthesia.

Comparison with existing methods

Existing methods to combine two-photon and EEG recording used wired EEG recording. In this study, wireless EEG was used in conjunction with two-photon imaging, facilitated by CBRAIN. More importantly, built-in algorithms of the CBRAIN can automatically detect brain state such as sleep. The codes used for EEG classification are easy to use, with no prior experience required.

Conclusion

Simultaneous recording of wireless EEG and two-photon imaging provides a practical way to capture individual neuronal activities with respect to global brain state in an experimental set-up.

Distinguishing examples while building concepts in hippocampal and artificial networks

The hippocampal subfield CA3 is thought to function as an auto-associative network that stores experiences as memories. Information from these experiences arrives directly from the entorhinal cortex as well as indirectly through the dentate gyrus, which performs sparsification and decorrelation. The computational purpose for these dual input pathways has not been firmly established. We model CA3 as a Hopfield-like network that stores both dense, correlated encodings and sparse, decorrelated encodings. As more memories are stored, the former merge along shared features while the latter remain distinct. We verify our model's prediction in rat CA3 place cells, which exhibit more distinct tuning during theta phases with sparser activity. Finally, we find that neural networks trained in multitask learning benefit from a loss term that promotes both correlated and decorrelated representations. Thus, the complementary encodings we have found in CA3 can provide broad computational advantages for solving complex tasks.

Opto-electronic feedback control of membrane potential for real-time control of action potentials

To unlock new research possibilities by acquiring control of action potential (AP) morphologies in excitable cells, we developed an opto-electronic feedback loop-based system integrating cellular electrophysiology, real-time computing, and optogenetic approaches and applied it to monolayers of heart muscle cells. This allowed accurate restoration and preservation of cardiac AP morphologies in the presence of electrical perturbations of different origin in an unsupervised, self-regulatory manner, without any prior knowledge of the disturbance. Moreover, arbitrary AP waveforms could be enforced onto these cells. Collectively, these results set the stage for the refinement and application of opto-electronic control systems to enable in-depth investigation into the regulatory role of membrane potential in health and disease.

Transcranial ultrasound stimulation at the peak-phase of theta-cycles in the hippocampus improve memory performance

The present study aimed to investigate the effectiveness of closed-loop transcranial ultrasound stimulation (closed-loop TUS) as a non-invasive, high temporal-spatial resolution method for modulating brain function to enhance memory. For this purpose, we applied closed-loop TUS to the CA1 region of the rat hippocampus for 7 consecutive days at different phases of theta cycles. Following the intervention, we evaluated memory performance through behavioral testing and recorded the neural activity. Our results indicated that closed-loop TUS applied at the peak phase of theta cycles significantly improves the memory performance in rats, as evidenced by behavioral testing. Furthermore, we observed that closed-loop TUS modifies the power and cross-frequency coupling strength of local field potentials (LFPs) during memory task, as well as modulates neuronal activity patterns and synaptic transmission, depending on phase of stimulation relative to theta rhythm. We demonstrated that closed-loop TUS can modulate neural activity and memory performance in a phase-dependent manner. Specifically, we observed that effectiveness of closed-loop TUS in regulating neural activity and memory is dependent on the timing of stimulation in relation to different theta phase. The findings implied that closed-loop TUS may have the capability to alter neural activity and memory performance in a phase-sensitive manner, and suggested that the efficacy of closed-loop TUS in modifying neural activity and memory was contingent on timing of stimulation with respect to the theta rhythm. Moreover, the improvement in memory performance after closed-loop TUS was found to be persistent.

A Review on Motor Imagery with Transcranial Alternating Current Stimulation: Bridging Motor and Cognitive Welfare for Patient Rehabilitation

Research has shown the effectiveness of motor imagery in patient motor rehabilitation. Transcranial electrical stimulation has also demonstrated to improve patient motor and non-motor performance. However, mixed findings from motor imagery studies that involved transcranial electrical stimulation suggest that current experimental protocols can be further improved towards a unified design for consistent and effective results. This paper aims to review, with some clinical and neuroscientific findings from literature as support, studies of motor imagery coupled with different types of transcranial electrical stimulation and their experiments onhealthy and patient subjects. This review also includes the cognitive domains of working memory, attention, and fatigue, which are important for designing consistent and effective therapy protocols. Finally, we propose a theoretical all-inclusive framework that synergizes the three cognitive domains with motor imagery and transcranial electrical stimulation for patient rehabilitation, which holds promise of benefiting patients suffering from neuromuscular and cognitive disorders.

Optogenetic Stimulation of CA1 Pyramidal Neurons at Theta Enhances Recognition Memory in Brain Injured Animals

Abstract The hippocampus plays a prominent role in learning and memory formation. The functional integrity of this structure is often compromised after traumatic brain injury (TBI), resulting in lasting cognitive dysfunction. The activity of hippocampal neurons, particularly place cells, is coordinated by local theta oscillations. Previous studies aimed at examining hippocampal theta oscillations after experimental TBI have reported disparate findings. Using a diffuse brain injury model, the lateral fluid percussion injury (FPI; 2.0 atm), we report a significant reduction in hippocampal theta power that persists for at least three weeks after injury. We questioned whether the behavioral deficit associated with this reduction of theta power can be overcome by optogenetically stimulating CA1 neurons at theta in brain injured rats. Our results show that memory impairments in brain injured animals could be reversed by optogenetically stimulating CA1 pyramidal neurons expressing channelrhodopsin (ChR2) during learning. In contrast, injured animals receiving a control virus (lacking ChR2) did not benefit from optostimulation. These results suggest that direct stimulation of CA1 pyramidal neurons at theta may be a viable option for enhancing memory after TBI.

The medial septum controls hippocampal supra-theta oscillations

Hippocampal theta oscillations orchestrate faster beta-to-gamma oscillations facilitating the segmentation of neural representations during navigation and episodic memory. Supra-theta rhythms of hippocampal CA1 are coordinated by local interactions as well as inputs from the entorhinal cortex (EC) and CA3 inputs. However, theta-nested gamma-band activity in the medial septum (MS) suggests that the MS may control supra-theta CA1 oscillations. To address this, we performed multi-electrode recordings of MS and CA1 activity in rodents and found that MS neuron firing showed strong phase-coupling to theta-nested supra-theta episodes and predicted changes in CA1 beta-to-gamma oscillations on a cycle-by-cycle basis. Unique coupling patterns of anatomically defined MS cell types suggested that indirect MS-to-CA1 pathways via the EC and CA3 mediate distinct CA1 gamma-band oscillations. Optogenetic activation of MS parvalbumin-expressing neurons elicited theta-nested beta-to-gamma oscillations in CA1. Thus, the MS orchestrates hippocampal network activity at multiple temporal scales to mediate memory encoding and retrieval.

Gamma oscillations and episodic memory

Enhanced gamma oscillatory activity (30-80 Hz) accompanies the successful formation and retrieval of episodic memories. While this co-occurrence is well documented, the mechanistic contributions of gamma oscillatory activity to episodic memory remain unclear. Here, we review how gamma oscillatory activity may facilitate spike timing-dependent plasticity, neural communication, and sequence encoding/retrieval, thereby ensuring the successful formation and/or retrieval of an episodic memory. Based on the evidence reviewed, we propose that multiple, distinct forms of gamma oscillation can be found within the canonical gamma band, each of which has a complementary role in the neural processes listed above. Further exploration of these theories using causal manipulations may be key to elucidating the relevance of gamma oscillatory activity to episodic memory.

Septo-hippocampal dynamics and the encoding of space and time

Encoding an event in memory requires neural activity to represent multiple dimensions of behavioral experience in space and time. Recent experiments have explored the influence of neural dynamics regulated by the medial septum on the functional encoding of space and time by neurons in the hippocampus and associated structures. This review addresses these dynamics, focusing on the role of theta rhythm, the differential effects of septal inactivation and activation on the functional coding of space and time by individual neurons, and the influence on phase coding that appears as phase precession. We also discuss data indicating that theta rhythm plays a role in timing the internal dynamics of memory encoding and retrieval, as well as the behavioral influences of these neuronal manipulations with regard to memory function.

Theta-phase-specific modulation of dentate gyrus memory neurons

The theta rhythm, a quasi-periodic 4-10 Hz oscillation, is observed during memory processing in the hippocampus, with different phases of theta hypothesized to separate independent streams of information related to the encoding and recall of memories. At the cellular level, the discovery of hippocampal memory cells (engram neurons), as well as the modulation of memory recall through optogenetic activation of these cells, has provided evidence that certain memories are stored, in part, in a sparse ensemble of neurons in the hippocampus. In previous research, however, engram reactivation has been carried out using open-loop stimulation at fixed frequencies; the relationship between engram neuron reactivation and ongoing network oscillations has not been taken into consideration. To address this concern, we implemented a closed-loop reactivation of engram neurons that enabled phase-specific stimulation relative to theta oscillations in the local field potential in CA1. Using this real-time approach, we tested the impact of activating dentate gyrus engram neurons during the peak (encoding phase) and trough (recall phase) of theta oscillations. Consistent with previously hypothesized functions of theta oscillations in memory function, we show that stimulating dentate gyrus engram neurons at the trough of theta is more effective in eliciting behavioral recall than either fixed-frequency stimulation or stimulation at the peak of theta. Moreover, phase-specific trough stimulation is accompanied by an increase in the coupling between gamma and theta oscillations in CA1 hippocampus. Our results provide a causal link between phase-specific activation of engram cells and the behavioral expression of memory.

Anxiety and depression: A top-down, bottom-up model of circuit function

A functional interplay of bottom-up and top-down processing allows an individual to appropriately respond to the dynamic environment around them. These processing modalities can be represented as attractor states using a dynamical systems model of the brain. The transition probability to move from one attractor state to another is dependent on the stability, depth, neuromodulatory tone, and tonic changes in plasticity. However, how does the relationship between these states change in disease states, such as anxiety or depression? We describe bottom-up and top-down processing from Marr's computational-algorithmic-implementation perspective to understand depressive and anxious disease states. We illustrate examples of bottom-up processing as basolateral amygdala signaling and projections and top-down processing as medial prefrontal cortex internal signaling and projections. Understanding these internal processing dynamics can help us better model the multifaceted elements of anxiety and depression.

Theoretical Considerations for Optimizing the Use of Optogenetics with Complex Behavior

Optogenetic approaches have allowed researchers to address complex questions about behavior that were previously unanswerable. However, as optogenetic procedures involve a large parameter space across multiple dimensions, it is crucial to consider such parameters in conjunction with the behaviors under study. Here, we discuss strategies to optimize optogenetic approaches with complex behavior by identifying critical experimental design considerations, including frequency specificity, temporal precision, activity-controlled optogenetics, stimulation pattern, and cell-type specificity. We highlight potential limitations or theoretical considerations to be made when manipulating each of these factors of optogenetic experiments. This overview emphasizes the importance of optimizing optogenetic study design to enhance the conclusions that can be drawn about the neuroscience of behavior. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Gated transformations from egocentric to allocentric reference frames involving retrosplenial cortex, entorhinal cortex, and hippocampus

This paper reviews the recent experimental finding that neurons in behaving rodents show egocentric coding of the environment in a number of structures associated with the hippocampus. Many animals generating behavior on the basis of sensory input must deal with the transformation of coordinates from the egocentric position of sensory input relative to the animal, into an allocentric framework concerning the position of multiple goals and objects relative to each other in the environment. Neurons in retrosplenial cortex show egocentric coding of the position of boundaries in relation to an animal. These neuronal responses are discussed in relation to existing models of the transformation from egocentric to allocentric coordinates using gain fields and a new model proposing transformations of phase coding that differ from current models. The same type of transformations could allow hierarchical representations of complex scenes. The responses in rodents are also discussed in comparison to work on coordinate transformations in humans and non-human primates.

Hippocampal inactivation during rearing on hind legs impairs spatial memory

Spatial memory requires an intact hippocampus. Hippocampal function during epochs of locomotion and quiet rest (e.g., grooming and reward consumption) has been the target of extensive study. However, during navigation rats frequently rear up onto their hind legs, and the importance of hippocampal activity during these periods of attentive sampling for spatial memory is unknown. To address this, we tested the necessity of dorsal hippocampal activity during rearing epochs in the study phase of a delayed win-shift task for memory performance in the subsequent test phase. Hippocampal activity was manipulated with closed-loop, bilateral, optogenetic inactivation. Spatial memory accuracy was significantly and selectively reduced when the dorsal hippocampus was inactivated during rearing epochs at encoding. These data show that hippocampal activity during periods of rearing can be important for spatial memory, revealing a novel link between hippocampal function during epochs of rearing and spatial memory.

Theta oscillations represent collective dynamics of multineuronal membrane potentials of murine hippocampal pyramidal cells

Theta (θ) oscillations are one of the characteristic local field potentials (LFPs) in the hippocampus that emerge during spatial navigation, exploratory sniffing, and rapid eye movement sleep. LFPs are thought to summarize multineuronal events, including synaptic currents and action potentials. However, no in vivo study to date has directly interrelated θ oscillations with the membrane potentials (Vm) of multiple neurons, and it remains unclear whether LFPs can be predicted from multineuronal Vms. Here, we simultaneously patch-clamp up to three CA1 pyramidal neurons in awake or anesthetized mice and find that the temporal evolution of the power and frequency of θ oscillations in Vms (θ_Vms) are weakly but significantly correlate with LFP θ oscillations (θ_LFP) such that a deep neural network could predict the θ_LFP waveforms based on the θ_Vm traces of three neurons. Therefore, individual neurons are loosely interdependent to ensure freedom of activity, but they partially share information to collectively produce θ_LFP.

Gamma amplitude is coupled to opposed hippocampal theta-phase states during the encoding and retrieval of episodic memories in humans

Computational models and in vivo studies in rodents suggest that the emergence of gamma activity (40-140 Hz) during memory encoding and retrieval is coupled to opposed-phase states of the underlying hippocampal theta rhythm (4-9 Hz).^{1,2,3,4,5,6,7,8,9,10} However, direct evidence for whether human hippocampal gamma-modulated oscillatory activity in memory processes is coupled to opposed-phase states of the ongoing theta rhythm remains elusive. Here, we recorded local field potentials (LFPs) directly from the hippocampus of 10 patients with epilepsy, using depth electrodes. We used a memory encoding and retrieval task whereby trial unique sequences of pictures depicting real-life episodes were presented, and 24 h later, participants were asked to recall them upon the appearance of the first picture of the encoded episodic sequence. We found theta-to-gamma cross-frequency coupling that was specific to the hippocampus during both the encoding and retrieval of episodic memories. We also revealed that gamma was coupled to opposing theta phases during both encoding and recall processes. Additionally, we observed that the degree of theta-gamma phase opposition between encoding and recall was associated with participants' memory performance, so gamma power was modulated by theta phase for both remembered and forgotten trials, although only for remembered trials the dominant theta phase was different for encoding and recall trials. The current results offer direct empirical evidence in support of hippocampal theta-gamma phase opposition models in human long-term memory and provide fundamental insights into mechanistic predictions derived from computational and animal work, thereby contributing to establishing similarities and differences across species.

Closed-loop optogenetic control of the dynamics of neural activity in non-human primates

Electrical neurostimulation is effective in the treatment of neurological disorders, but associated recording artefacts generally limit its applications to open-loop stimuli. Real-time and continuous closed-loop control of brain activity can, however, be achieved by pairing concurrent electrical recordings and optogenetics. Here we show that closed-loop optogenetic stimulation with excitatory opsins enables the precise manipulation of neural dynamics in brain slices from transgenic mice and in anaesthetized non-human primates. The approach generates oscillations in quiescent tissue, enhances or suppresses endogenous patterns in active tissue and modulates seizure-like bursts elicited by the convulsant 4-aminopyridine. A nonlinear model of the phase-dependent effects of optical stimulation reproduced the modulation of cycles of local-field potentials associated with seizure oscillations, as evidenced by the systematic changes in the variability and entropy of the phase-space trajectories of seizures, which correlated with changes in their duration and intensity. We also show that closed-loop optogenetic neurostimulation could be delivered using intracortical optrodes incorporating light-emitting diodes. Closed-loop optogenetic approaches may be translatable to therapeutic applications in humans.

Optogenetic modulation of hippocampal oscillations ameliorates spatial cognition and hippocampal dysrhythmia following early-life seizures

There is increasing human and animal evidence that brain oscillations play a critical role in the development of spatial cognition. In rat pups, disruption of hippocampal rhythms via optogenetic stimulation during the critical period for memory development impairs spatial cognition. Early-life seizures are associated with long-term deficits in spatial cognition and aberrant hippocampal oscillatory activity. Here we asked whether modulation of hippocampal rhythms following early-life seizures can reverse or improve hippocampal connectivity and spatial cognition. We used optogenetic stimulation of the medial septum to induce physiological 7 Hz theta oscillations in the hippocampus during the critical period of spatial cognition following early-life seizures. Optogenetic stimulation of the medial septum in control and rats subjected to early-life seizures resulted in precisely regulated frequency-matched hippocampal oscillations. Rat pups receiving active blue light stimulation performed better than the rats receiving inert yellow light in a test of spatial cognition. The improvement in spatial cognition in these rats was associated with a faster theta frequency and higher theta power, coherence and phase locking value in the hippocampus than rats with early-life seizures receiving inert yellow light. These findings indicate that following early life seizures, modification of hippocampal rhythms may be a potential novel therapeutic modality.

Manipulating single-unit theta phase-locking with PhaSER: An open-source tool for real-time phase estimation and manipulation

The precise timing of neuronal spiking relative to the brain's endogenous oscillations (i.e., phase-locking or spike-phase coupling) has long been hypothesized to coordinate cognitive processes and maintain excitatory-inhibitory homeostasis. Indeed, disruptions in theta phase-locking have been described in models of neurological diseases with associated cognitive deficits and seizures, such as Alzheimer's disease, temporal lobe epilepsy, and autism spectrum disorders. However, due to technical limitations, determining if phase-locking causally contributes to these disease phenotypes has not been possible until recently. To fill this gap and allow for the flexible manipulation of single-unit phase-locking to on-going endogenous oscillations, we developed PhaSER, an open-source tool that allows for phase-specific manipulations. PhaSER can deliver optogenetic stimulation at defined phases of theta in order to shift the preferred firing phase of neurons relative to theta in real-time. Here, we describe and validate this tool in a subpopulation of inhibitory neurons that express somatostatin (SOM) in the CA1 and dentate gyrus (DG) regions of the dorsal hippocampus. We show that PhaSER is able to accurately deliver a photo-manipulation that activates opsin+ SOM neurons at specified phases of theta in real-time in awake, behaving mice. Further, we show that this manipulation is sufficient to alter the preferred firing phase of opsin+ SOM neurons without altering the referenced theta power or phase. All software and hardware requirements to implement real-time phase manipulations during behavior are available online (https://github.com/ShumanLab/PhaSER).

Frequency matters: how changes in hippocampal theta frequency can influence temporal coding, anxiety-reduction, and memory

Hippocampal theta frequency is a somewhat neglected topic relative to theta power, phase, coherence, and cross-frequency coupling. Accordingly, here we review and present new data on variation in hippocampal theta frequency, focusing on functional associations (temporal coding, anxiety reduction, learning, and memory). Taking the rodent hippocampal theta frequency to running-speed relationship as a model, we identify two doubly-dissociable frequency components: (a) the slope component of the theta frequency-to-stimulus-rate relationship ("theta slope"); and (b) its y-intercept frequency ("theta intercept"). We identify three tonic determinants of hippocampal theta frequency. (1) Hotter temperatures increase theta frequency, potentially consistent with time intervals being judged as shorter when hot. Initial evidence suggests this occurs via the "theta slope" component. (2) Anxiolytic drugs with widely-different post-synaptic and pre-synaptic primary targets share the effect of reducing the "theta intercept" component, supporting notions of a final common pathway in anxiety reduction involving the hippocampus. (3) Novelty reliably decreases, and familiarity increases, theta frequency, acting upon the "theta slope" component. The reliability of this latter finding, and the special status of novelty for learning, prompts us to propose a Novelty Elicits Slowing of Theta frequency (NEST) hypothesis, involving the following elements: (1) Theta frequency slowing in the hippocampal formation is a generalised response to novelty of different types and modalities; (2) Novelty-elicited theta slowing is a hippocampal-formation-wide adaptive response functioning to accommodate the additional need for learning entailed by novelty; (3) Lengthening the theta cycle enhances associativity; (4) Even part-cycle lengthening may boost associativity; and (5) Artificial theta stimulation aimed at enhancing learning should employ low-end theta frequencies.

Modulation effect of mouse hippocampal neural oscillations by closed-loop transcranial ultrasound stimulation

Objective. Closed-loop transcranial ultrasound stimulation (TUS) can be applied at a specific time according to the state of neural activity to achieve timely and precise neuromodulation and improve the modulation effect. In a previous study, we found that closed-loop TUS at the peaks and troughs of the theta rhythm in the mouse hippocampus was able to increase the absolute power and decrease the relative power of the theta rhythm of local field potentials (LFPs) independent of the peaks and troughs of the stimulus. However, it remained unclear whether the modulation effect of this closed-loop TUS-induced mouse hippocampal neural oscillation depended on the peaks and troughs of the theta rhythm.Approach. In this study, we used ultrasound with different stimulation modes and durations to stimulate the peaks (peak stimulation) and troughs (trough stimulation) of the hippocampal theta rhythm. The LFPs in the area of ultrasound stimulation were recorded and the amplitudes and power spectra of the theta rhythm before and after ultrasound stimulation were analyzed.Main results. The results showed that (a) the relative change in amplitude of theta rhythm decreases as the number of stimulation trials under peak stimulation increases; (b) the relative change in the absolute power of the theta rhythm decreases as the number of stimulation trials under peak stimulation increases; (c) the relative change in amplitude of the theta rhythm increases nonlinearly with the stimulation duration (SD) under peak stimulation, and; (d) the relative change in absolute power exhibits a nonlinear increase with SD under peak stimulation.Significance. These results suggest that the modulation effect of closed-loop TUS on theta rhythm is dependent on the stimulation mode and duration under peak stimulation. TUS has the potential to precisely modulate theta rhythm-related neural activity.

Large-scale, closed-loop interrogation of neural circuits underlying cognition

Cognitive functions are increasingly understood to involve coordinated activity patterns between multiple brain regions, and their disruption by neuropsychiatric disorders is similarly complex. Closed-loop neurostimulation can directly modulate neural signals with temporal and spatial precision. How to leverage such an approach to effectively identify and target distributed neural networks implicated in mediating cognition remains unclear. We review current conceptual and technical advances in this area, proposing that devices that enable large-scale acquisition, integrated processing, and multiregion, arbitrary waveform stimulation will be critical for mechanistically driven manipulation of cognitive processes in physiological and pathological brain networks.

Disrupting ripples: Methods, results, and caveats in closed-loop approaches in rodents

Hippocampal ripple oscillations have been associated with memory reactivations during wake and sleep. These reactivations should contribute to working memory and memory consolidation respectively. In the past decade studies have moved from being observational to actively disrupting ripple-related activity in closed-loop approaches to enable causal investigations into their function. All together these studies have been able to provide evidence that wake, task-related ripple activity is important for working memory and planning but less important for stabilisation of spatial representations. Rest and sleep-related ripple activity, in contrast, is important for long-term memory performance and thus memory consolidation. In this review, we summarise results from different closed-loop approaches in rodents. Further, we highlight differences in detection and stimulation methods as well as controls and discuss how these differences could influence outcomes.

The Theta Paradox: 4-8 Hz EEG Oscillations Reflect Both Sleep Pressure and Cognitive Control

Human electroencephalographic (EEG) oscillations characterize specific behavioral and vigilance states. The frequency of these oscillations is typically sufficient to distinguish a given state; however, theta oscillations (4-8 Hz) have instead been found in near-opposite conditions of drowsiness during sleep deprivation and alert cognitive control. While the latter has been extensively studied and is often referred to as "frontal midline theta," (fmTheta) the former has been investigated far less but is considered a marker for sleep pressure during wake. In this study we investigated to what extent theta oscillations differed during cognitive tasks and sleep deprivation. We measured high-density EEG in 18 young healthy adults (nine female) performing six tasks under three levels of sleep deprivation. We found both cognitive load and sleep deprivation increased theta power in medial prefrontal cortical areas; however, sleep deprivation caused additional increases in theta in many other, predominantly frontal, areas. The sources of sleep deprivation theta (sdTheta) were task dependent, with a visual-spatial task and short-term memory (STM) task showing the most widespread effects. Notably, theta was highest in supplementary motor areas during passive music listening, and highest in the inferior temporal cortex (responsible for object recognition) during a spatial game. Furthermore, while changes in task performance were correlated with increases in theta during sleep deprivation, this relationship was not specific to the EEG of the same task and did not survive correction for multiple comparisons. Altogether, these results suggest that both during sleep deprivation and cognition theta oscillations may preferentially occur in cortical areas not involved in ongoing behavior.SIGNIFICANCE STATEMENT Electroencephalographic (EEG) research in sleep has often remained separate from research in cognition. This has led to two incompatible interpretations of the function of theta brain oscillations (4-8 Hz): that they reflect local sleep events during sleep deprivation, or that they reflect cognitive processing during tasks. With this study, we found no fundamental differences between theta oscillations during cognition and theta during sleep deprivation that would suggest different functions. Instead, our results indicate that in both cases, theta oscillations are generated by cortical areas not required for ongoing behavior. Therefore, at least in humans, theta may reflect either cortical disengagement or inhibition.

Stable, interactive modulation of neuronal oscillations produced through brain-machine equilibrium

Closed-loop interaction has the potential to regulate ongoing brain activity by continuously binding an external stimulation to specific dynamics of a neural circuit. Achieving interactive modulation requires a stable brain-machine feedback loop. Here, we demonstrate that it is possible to maintain oscillatory brain activity in a desired state by delivering stimulation accurately aligned with the timing of each cycle. We develop a fast algorithm that responds on a cycle-by-cycle basis to stimulate basal ganglia nuclei at predetermined phases of successive cortical beta cycles in parkinsonian rats. Using this approach, an equilibrium emerges between the modified brain signal and feedback-dependent stimulation pattern, leading to sustained amplification or suppression of the oscillation depending on the phase targeted. Beta amplification slows movement speed by biasing the animal's mode of locomotion. Together, these findings show that highly responsive, phase-dependent stimulation can achieve a stable brain-machine interaction that leads to robust modulation of ongoing behavior.

Reward-based decision-making in mesial temporal lobe epilepsy patients with unilateral hippocampal sclerosis pre- and post-surgery

BACKGROUND

Correct functioning of the reward processing system is critical for optimizing decision-making as well as preventing the development of addictions and/or neuropsychiatric symptoms such as depression, apathy, and anhedonia. Consequently, patients with mesial temporal lobe epilepsy due to unilateral hippocampal sclerosis (mTLE-UHS) represent an excellent opportunity to study the brain networks involved in this system.

OBJECTIVE

The aim of the current study was to evaluate decision-making and the electrophysiological correlates of feedback processing in a sample of mTLE-UHS patients, compared to healthy controls. In addition, we assessed the impact of mesial temporal lobe surgical resection on these processes, as well as general, neuropsychological functioning.

METHOD

17 mTLE-UHS patients and 17 matched healthy controls completed: [1] a computerized version of the Game of Dice Task, [2] a Standard Iowa Gambling Task, and [3] a modified ERP version of a probabilistic gambling task coupled with multichannel electroencephalography. Neuropsychological scores were also obtained both pre- and post-surgery.

RESULTS

Behavioral analyses showed a pattern of increased risk for the mTLE-UHS group in decision-making under ambiguity compared to the control group. A decrease in the amplitude of the Feedback Related Negativity (FRN), a weaker effect of valence on delta power, and a general reduction of delta and theta power in the mTLE-UHS group, as compared to the control group, were also found. The beta-gamma activity associated with the delivery of positive reward was similar in both groups. Behavioral performance and electrophysiological measures did not worsen post-surgery.

CONCLUSIONS

Patients with mTLE-UHS showed impairments in decision-making under ambiguity, particularly when they had to make decisions based on the outcomes of their choices, but not in decision-making under risk. No group differences were observed in decision-making when feedbacks were random. These results might be explained by the abnormal feedback processing seen in the EEG activity of patients with mTLE-UHS, and by concomitant impairments in working memory, and memory. These impairments may be linked to the disruption of mesial temporal lobe networks. Finally, feedback processing and decision-making under ambiguity were already affected in mTLE-UHS patients pre-surgery and did not show evidence of clear worsening post-surgery.

Correcting the hebbian mistake: Toward a fully error-driven hippocampus

The hippocampus plays a critical role in the rapid learning of new episodic memories. Many computational models propose that the hippocampus is an autoassociator that relies on Hebbian learning (i.e., "cells that fire together, wire together"). However, Hebbian learning is computationally suboptimal as it does not learn in a way that is driven toward, and limited by, the objective of achieving effective retrieval. Thus, Hebbian learning results in more interference and a lower overall capacity. Our previous computational models have utilized a powerful, biologically plausible form of error-driven learning in hippocampal CA1 and entorhinal cortex (EC) (functioning as a sparse autoencoder) by contrasting local activity states at different phases in the theta cycle. Based on specific neural data and a recent abstract computational model, we propose a new model called Theremin (Total Hippocampal ERror MINimization) that extends error-driven learning to area CA3-the mnemonic heart of the hippocampal system. In the model, CA3 responds to the EC monosynaptic input prior to the EC disynaptic input through dentate gyrus (DG), giving rise to a temporal difference between these two activation states, which drives error-driven learning in the EC→CA3 and CA3↔CA3 projections. In effect, DG serves as a teacher to CA3, correcting its patterns into more pattern-separated ones, thereby reducing interference. Results showed that Theremin, compared with our original Hebbian-based model, has significantly increased capacity and learning speed. The model makes several novel predictions that can be tested in future studies.

GRINtrode: a neural implant for simultaneous two-photon imaging and extracellular electrophysiology in freely moving animals

Significance

In vivo imaging and electrophysiology are powerful tools to explore neuronal function that each offer unique complementary information with advantages and limitations. Capturing both data types from the same neural population in the freely moving animal would allow researchers to take advantage of the capabilities of both modalities and further understand how they relate to each other.

Aim

Here, we present a head-mounted neural implant suitable for in vivo two-photon imaging of neuronal activity with simultaneous extracellular electrical recording in head-fixed or fiber-coupled freely moving animals.

Approach

A gradient refractive index (GRIN) lens-based head-mounted neural implant with extracellular electrical recording provided by tetrodes on the periphery of the GRIN lens was chronically implanted. The design of the neural implant allows for recording from head-fixed animals, as well as freely moving animals by coupling the imaging system to a coherent imaging fiber bundle.

Results

We demonstrate simultaneous two-photon imaging of GCaMP and extracellular electrophysiology of neural activity in awake head-fixed and freely moving mice. Using the collected information, we perform correlation analysis to reveal positive correlation between optical and local field potential recordings.

Conclusion

Simultaneously recording neural activity using both optical and electrical methods provides complementary information from each modality. Designs that can provide such bi-modal recording in freely moving animals allow for the investigation of neural activity underlying a broader range of behavioral paradigms.

High-resolution optogenetics in space and time

To understand the neural mechanisms of behavior, it is necessary to both monitor and perturb the activity of ensembles of neurons with high specificity. While neural ensemble recordings have been available for decades, progress in high-resolution manipulation techniques has lagged behind. Optogenetics has enabled the manipulation of genetically defined cell types in behaving animals, and recent developments, including multipoint nanofabricated light sources, provide spatiotemporal resolution on a par with that of physiological recordings. Here we review current advances in optogenetic methods for cellular-resolution stimulation and intervention, as well as their integration with real-time neural recordings for closed-loop experimentation. We discuss how these approaches open the door to new kinds of experiments aimed at dissecting the role of specific neural patterns and discrete cellular populations in orchestrating the activity of brain circuits that support behavior and cognition.

Hippocampal-prefrontal theta coupling develops as mice become proficient in associative odorant discrimination learning

Learning and memory requires coordinated activity between different regions of the brain. Here we studied the interaction between infralimbic medial prefrontal cortex (mPFC) and hippocampal dorsal CA1 during associative odorant discrimination learning in the mouse. We found that as the animal learns to discriminate odorants in a go-no go task, the coupling of high frequency neural oscillations to the phase of theta oscillations (theta-referenced phase-amplitude coupling or tPAC) changes in a manner that results in divergence between rewarded and unrewarded odorant-elicited changes in the theta-phase referenced power (tPRP) for beta and gamma oscillations. In addition, in the proficient animal there was a decrease in the coordinated oscillatory activity between CA1 and mPFC in the presence of the unrewarded odorant. Furthermore, the changes in tPAC resulted in a marked increase in the accuracy for decoding contextual odorant identity from tPRP when the animal became proficient. Finally, we studied the role of Ca2+/calmodulin-dependent protein kinase II α (CaMKIIα), a protein involved in learning and memory, in oscillatory neural processing in this task. We find that the accuracy for decoding the contextual odorant identity from tPRP decreases in CaMKIIα knockout mice and that this accuracy correlates with behavioral performance. These results implicate a role for tPAC and CaMKIIα in olfactory go-no go associative learning in the hippocampal-prefrontal circuit.Significance statementCoupling of neural oscillations within and between hippocampal CA1 and medial prefrontal cortex (mPFC) is involved in spatial learning and memory, but the role of oscillation coupling for other learning tasks is not well understood. Here we performed local field potential recording in CA1 and mPFC in mice learning to differentiate rewarded from unrewarded odorants in an associative learning task. We find that odorant-elicited changes in the power of bursts of gamma oscillations at distinct phases of theta oscillations become divergent as the animal becomes proficient allowing decoding of contextual odorant identity. Finally, we find that the accuracy to decode contextual odorant identity decreases in mice deficient for the expression of Ca2+/calmodulin-dependent protein kinase II α, a protein involved in synaptic plasticity.

Phase-locked closed-loop ultrasound stimulation modulates theta and gamma rhythms in the mouse hippocampus

Previous studies have demonstrated that open-loop transcranial ultrasound stimulation (TUS) can modulate theta and gamma rhythms of the local field potentials (LFPs) in the mouse hippocampus; however, the manner in which closed-loop TUS with different pressures based on phase-locking of theta rhythms modulates theta and gamma rhythm remains unclear. In this study, we established a closed-loop TUS system, which can perform closed-loop TUS by predicting the peaks and troughs of the theta rhythm. Comparison of the power, sample entropy and complexity, and phase-amplitude coupling (PAC) between the theta and gamma rhythms under peak and trough stimulation of the theta rhythm revealed the following: (1) the variation in the absolute power of the gamma rhythm and the relative power of the theta rhythm under TUS at 0.6–0.8 MPa differ between peak and trough stimulation; (2) the relationship of the sample entropy of the theta and gamma rhythms with ultrasound pressure depends on peak and trough stimulation; and (3) peak and trough stimulation affect the PAC strength between the theta and gamma rhythm as a function of ultrasound pressure. These results demonstrate that the modulation of the theta and gamma rhythms by ultrasound pressure depends on peak and trough stimulation of the theta rhythm in the mouse hippocampus.

Reversal learning: It's just a phase

Being able to let go of behaviors that are no longer valuable and adopt actions that achieve the same outcome is fundamental for animal survival. A new study offers clues on the neural mechanisms that allow animals to reverse their behavior as needed.

Implantable Micro-Light-Emitting Diode (µLED)-based optogenetic interfaces toward human applications

Optogenetics has received wide attention in biomedical fields because of itsadvantages in temporal precision and spatial resolution. Beyond contributions to important advances in fundamental research, optogenetics is inspiring a shift towards new methods of improving human well-being and treating diseases. Soft, flexible and biocompatible systems using µLEDs as a light source have been introduced to realize brain-compatible optogenetic implants, but there are still many technical challenges to overcome before their human applications. In this review, we address progress in the development of implantable µLED probes and recent achievements in (i) device engineering design, (ii) driving power, (iii) multifunctionality and (iv) closed-loop systems. (v) Expanded optogenetic applications based on remarkable advances in µLED implants will also be discussed.

Integrating music-based interventions with Gamma-frequency stimulation: Implications for healthy ageing

In recent years, music-based interventions (MBIs) have risen in popularity as a non-invasive, sustainable form of care for treating dementia-related disorders, such as Mild Cognitive Impairment (MCI) and Alzheimer's disease (AD). Despite their clinical potential, evidence regarding the efficacy of MBIs on patient outcomes is mixed. Recently, a line of related research has begun to investigate the clinical impact of non-invasive Gamma-frequency (e.g., 40 Hz) sensory stimulation on dementia. Current work, using non-human-animal models of AD, suggests that non-invasive Gamma-frequency stimulation can remediate multiple pathophysiologies of dementia at the molecular, cellular and neural-systems scales, and, importantly, improve cognitive functioning. These findings suggest that the efficacy of MBIs could, in theory, be enhanced by incorporating Gamma-frequency stimulation into current MBI protocols. In the current review, we propose a novel clinical framework for non-invasively treating dementia-related disorders that combines previous MBIs with current approaches employing Gamma-frequency sensory stimulation. We theorize that combining MBIs with Gamma-frequency stimulation could increase the therapeutic power of MBIs by simultaneously targeting multiple biomarkers of dementia, restoring neural activity that underlies learning and memory (e.g., Gamma-frequency neural activity, Theta-Gamma coupling), and actively engaging auditory and reward networks in the brain to promote behavioural change.

Impact of optogenetic pulse design on CA3 learning and replay: A neural model

Optogenetic manipulation of hippocampal circuitry is an important tool for investigating learning in vivo. Numerous approaches to pulse design have been employed to elicit desirable circuit and behavioral outcomes. Here, we systematically test the outcome of different single-pulse waveforms in a rate-based model of hippocampal memory function at the level of mnemonic replay extension and de novo synaptic weight formation in CA3 and CA1. Lower-power waveforms with long forward or forward and backward ramps yield more natural sequence replay dynamics and induce synaptic plasticity that allows for more natural memory replay timing, in contrast to square or backward ramps. These differences between waveform shape and amplitude are preserved with the addition of noise in membrane potential, light scattering, and protein expression, improving the potential validity of predictions for in vivo work. These results inform future optogenetic experimental design choices in the field of learning and memory.

Low-Power Lossless Data Compression for Wireless Brain Electrophysiology

Wireless electrophysiology opens important possibilities for neuroscience, especially for recording brain activity in more natural contexts, where exploration and interaction are not restricted by the usual tethered devices. The limiting factor is transmission power and, by extension, battery life required for acquiring large amounts of neural electrophysiological data. We present a digital compression algorithm capable of reducing electrophysiological data to less than 65.5% of its original size without distorting the signals, which we tested in vivo in experimental animals. The algorithm is based on a combination of delta compression and Huffman codes with optimizations for neural signals, which allow it to run in small, low-power Field-Programmable Gate Arrays (FPGAs), requiring few hardware resources. With this algorithm, a hardware prototype was created for wireless data transmission using commercially available devices. The power required by the algorithm itself was less than 3 mW, negligible compared to the power saved by reducing the transmission bandwidth requirements. The compression algorithm and its implementation were designed to be device-agnostic. These developments can be used to create a variety of wired and wireless neural electrophysiology acquisition systems with low power and space requirements without the need for complex or expensive specialized hardware.

Stimulating at the right time to recover network states in a model of the cortico-basal ganglia-thalamic circuit

Synchronization of neural oscillations is thought to facilitate communication in the brain. Neurodegenerative pathologies such as Parkinson’s disease (PD) can result in synaptic reorganization of the motor circuit, leading to altered neuronal dynamics and impaired neural communication. Treatments for PD aim to restore network function via pharmacological means such as dopamine replacement, or by suppressing pathological oscillations with deep brain stimulation. We tested the hypothesis that brain stimulation can operate beyond a simple “reversible lesion” effect to augment network communication. Specifically, we examined the modulation of beta band (14–30 Hz) activity, a known biomarker of motor deficits and potential control signal for stimulation in Parkinson’s. To do this we setup a neural mass model of population activity within the cortico-basal ganglia-thalamic (CBGT) circuit with parameters that were constrained to yield spectral features comparable to those in experimental Parkinsonism. We modulated the connectivity of two major pathways known to be disrupted in PD and constructed statistical summaries of the spectra and functional connectivity of the resulting spontaneous activity. These were then used to assess the network-wide outcomes of closed-loop stimulation delivered to motor cortex and phase locked to subthalamic beta activity. Our results demonstrate that the spatial pattern of beta synchrony is dependent upon the strength of inputs to the STN. Precisely timed stimulation has the capacity to recover network states, with stimulation phase inducing activity with distinct spectral and spatial properties. These results provide a theoretical basis for the design of the next-generation brain stimulators that aim to restore neural communication in disease.

Diseases of the brain lead to a wide range of disabling symptoms for patients, by affecting their ability to move or think properly. These symptoms arise from disruption to both the organization of networks in the brain, but also the timing of neural activity that propagates around it. Treatments for disease with drugs can restore the organization of these networks to some extent, yet it is very difficult to deliver drugs with good spatial or temporal selectivity. Brain stimulation provides one way in which to improve the spatial specificity of treatment, yet understanding how to stimulate at the right time to achieve the best outcome for patients, remains an outstanding question. In this work we use simulations of an important circuit involved in Parkinson’s disease that has parameters chosen to reflect recordings made in animal models of the disease. Using this computer model, we show how brain rhythms can act as signatures of underlying changes in networks. Further, we simulate intervention with temporally precise stimulation to show how future approaches to brain stimulation can act to restore or even augment neural networks following their degeneration in disease.

Prefrontal theta phase-dependent rTMS-induced plasticity of cortical and behavioral responses in human cortex

BACKGROUND

Prefrontal theta oscillations are involved in neuronal information transfer and retention. Phases along the theta cycle represent varied excitability states, whereby high-excitability states correspond to high-frequency neuronal activity and heightened capacity for plasticity induction, as demonstrated in animal studies. Human studies corroborate this model and suggest a core role of prefrontal theta activity in working memory (WM).

OBJECTIVE/HYPOTHESIS

We aimed at modulating prefrontal neuronal excitability and WM performance in healthy humans, using real-time EEG analysis for triggering repetitive transcranial magnetic stimulation (rTMS) theta-phase synchronized to the left dorsomedial prefrontal cortex.

METHODS

16 subjects underwent 3 different rTMS interventions on separate days, with pulses triggered according to the individual's real-time EEG activity: 400 rTMS gamma-frequency (100 Hz) triplet bursts applied during either the negative peak of the prefrontal theta oscillation, the positive peak, or at random phase. Changes in cortical excitability were assessed with EEG responses following single-pulse TMS, and behavioral effects by using a WM task.

RESULTS

Negative-peak rTMS increased single-pulse TMS-induced prefrontal theta power and theta-gamma phase-amplitude coupling, and decreased WM response time. In contrast, positive-peak rTMS decreased prefrontal theta power, while no changes were observed after random-phase rTMS.

CONCLUSION

Findings point to the feasibility of EEG-TMS technology in a theta-gamma phase-amplitude coupling mode for effectively modifying WM networks in human prefrontal cortex, with potential for therapeutic applications.

Coupling of pupil- and neuronal population dynamics reveals diverse influences of arousal on cortical processing

Fluctuations in arousal, controlled by subcortical neuromodulatory systems, continuously shape cortical state, with profound consequences for information processing. Yet, how arousal signals influence cortical population activity in detail has so far only been characterized for a few selected brain regions. Traditional accounts conceptualize arousal as a homogeneous modulator of neural population activity across the cerebral cortex. Recent insights, however, point to a higher specificity of arousal effects on different components of neural activity and across cortical regions. Here, we provide a comprehensive account of the relationships between fluctuations in arousal and neuronal population activity across the human brain. Exploiting the established link between pupil size and central arousal systems, we performed concurrent magnetoencephalographic (MEG) and pupillographic recordings in a large number of participants, pooled across three laboratories. We found a cascade of effects relative to the peak timing of spontaneous pupil dilations: Decreases in low-frequency (2-8 Hz) activity in temporal and lateral frontal cortex, followed by increased high-frequency (>64 Hz) activity in mid-frontal regions, followed by monotonic and inverted U relationships with intermediate frequency-range activity (8-32 Hz) in occipito-parietal regions. Pupil-linked arousal also coincided with widespread changes in the structure of the aperiodic component of cortical population activity, indicative of changes in the excitation-inhibition balance in underlying microcircuits. Our results provide a novel basis for studying the arousal modulation of cognitive computations in cortical circuits.

Rhythmic coordination and ensemble dynamics in the hippocampal-prefrontal network during odor-place associative memory and decision making

Memory-guided decision making involves long-range coordination across sensory and cognitive brain networks, with key roles for the hippocampus and prefrontal cortex (PFC). In order to investigate the mechanisms of such coordination, we monitored activity in hippocampus (CA1), PFC, and olfactory bulb (OB) in rats performing an odor-place associative memory guided decision task on a T-maze. During odor sampling, the beta (20-30 Hz) and respiratory (7-8 Hz) rhythms (RR) were prominent across the three regions, with beta and RR coherence between all pairs of regions enhanced during the odor-cued decision making period. Beta phase modulation of phase-locked CA1 and PFC neurons during this period was linked to accurate decisions, with a key role of CA1 interneurons in temporal coordination. Single neurons and ensembles in both CA1 and PFC encoded and predicted animals' upcoming choices, with different cell ensembles engaged during decision-making and decision execution on the maze. Our findings indicate that rhythmic coordination within the hippocampal-prefrontal-olfactory bulb network supports utilization of odor cues for memory-guided decision making.

Human hippocampal responses to network intracranial stimulation vary with theta phase

Hippocampal-dependent memory is thought to be supported by distinct connectivity states, with strong input to the hippocampus benefitting encoding and weak input benefitting retrieval. Previous research in rodents suggests that the hippocampal theta oscillation orchestrates the transition between these states, with opposite phase angles predicting minimal versus maximal input. We investigated whether this phase dependence exists in humans using network-targeted intracranial stimulation. Intracranial local field potentials were recorded from individuals with epilepsy undergoing medically necessary stereotactic electroencephalographic recording. In each subject, biphasic bipolar direct electrical stimulation was delivered to lateral temporal sites with demonstrated connectivity to hippocampus. Lateral temporal stimulation evoked ipsilateral hippocampal potentials with distinct early and late components. Using evoked component amplitude to measure functional connectivity, we assessed whether the phase of hippocampal theta predicted relatively high versus low connectivity. We observed an increase in the continuous phase-amplitude relationship selective to the early and late components of the response evoked by lateral temporal stimulation. The maximal difference in these evoked component amplitudes occurred across 180 degrees of separation in the hippocampal theta rhythm; that is, the greatest difference in component amplitude was observed when stimulation was delivered at theta peak versus trough. The pattern of theta-phase dependence observed for hippocampus was not identified for control locations. These findings demonstrate that hippocampal receptivity to input varies with theta phase, suggesting that theta phase reflects connectivity states of human hippocampal networks. These findings confirm a putative mechanism by which neural oscillations modulate human hippocampal function.

Theta rhythmicity governs human behavior and hippocampal signals during memory-dependent tasks

Memory formation and reinstatement are thought to lock to the hippocampal theta rhythm, predicting that encoding and retrieval processes appear rhythmic themselves. Here, we show that rhythmicity can be observed in behavioral responses from memory tasks, where participants indicate, using button presses, the timing of encoding and recall of cue-object associative memories. We find no evidence for rhythmicity in button presses for visual tasks using the same stimuli, or for questions about already retrieved objects. The oscillations for correctly remembered trials center in the slow theta frequency range (1-5 Hz). Using intracranial EEG recordings, we show that the memory task induces temporally extended phase consistency in hippocampal local field potentials at slow theta frequencies, but significantly more for remembered than forgotten trials, providing a potential mechanistic underpinning for the theta oscillations found in behavioral responses.