Multiplexed oscillations and phase rate coding in the basal forebrain

Functional architecture of the forebrain cholinergic system in rodents

The basal forebrain cholinergic system (BFCS) participates in functions that are global across the brain, such as sleep-wake cycles, but also participates in capacities that are more behaviorally and anatomically specific, including sensory perception. To better understand the underlying organization principles of the BFCS, more and higher quality anatomical data and analysis is needed. Here, we created a "virtual Basal Forebrain", combining data from numerous rats with cortical retrograde tracer injections into a common 3D reference coordinate space and developed a "spatial density correlation" methodology to analyze patterns in BFCS cortical projection targets, revealing that the BFCS is organized into three principal networks: somatosensory-motor, auditory, and visual. Within each network, clusters of cholinergic cells with increasing complexity innervate cortical targets. These networks represent hierarchically organized building blocks that may enable the BFCS to coordinate spatially selective signaling, including parallel modulation of multiple functionally interconnected yet diverse groups of cortical areas.

Induced neural phase precession through exogenous electric fields

The gradual shifting of preferred neural spiking relative to local field potentials (LFPs), known as phase precession, plays a prominent role in neural coding. Correlations between the phase precession and behavior have been observed throughout various brain regions. As such, phase precession is suggested to be a global neural mechanism that promotes local neuroplasticity. However, causal evidence and neuroplastic mechanisms of phase precession are lacking so far. Here we show a causal link between LFP dynamics and phase precession. In three experiments, we modulated LFPs in humans, a non-human primate, and computational models using alternating current stimulation. We show that continuous stimulation of motor cortex oscillations in humans lead to a gradual phase shift of maximal corticospinal excitability by ~90°. Further, exogenous alternating current stimulation induced phase precession in a subset of entrained neurons (~30%) in the non-human primate. Multiscale modeling of realistic neural circuits suggests that alternating current stimulation-induced phase precession is driven by NMDA-mediated synaptic plasticity. Altogether, the three experiments provide mechanistic and causal evidence for phase precession as a global neocortical process. Alternating current-induced phase precession and consequently synaptic plasticity is crucial for the development of novel therapeutic neuromodulation methods.

Induced neural phase precession through exogeneous electric fields

The gradual shifting of preferred neural spiking relative to local field potentials (LFPs), known as phase precession, plays a prominent role in neural coding. Correlations between the phase precession and behavior have been observed throughout various brain regions. As such, phase precession is suggested to be a global neural mechanism that promotes local neuroplasticity. However, causal evidence and neuroplastic mechanisms of phase precession are lacking so far. Here we show a causal link between LFP dynamics and phase precession. In three experiments, we modulated LFPs in humans, a non-human primate, and computational models using alternating current stimulation. We show that continuous stimulation of motor cortex oscillations in humans lead to a gradual phase shift of maximal corticospinal excitability by ~90°. Further, exogenous alternating current stimulation induced phase precession in a subset of entrained neurons (~30%) in the non-human primate. Multiscale modeling of realistic neural circuits suggests that alternating current stimulation-induced phase precession is driven by NMDA-mediated synaptic plasticity. Altogether, the three experiments provide mechanistic and causal evidence for phase precession as a global neocortical process. Alternating current-induced phase precession and consequently synaptic plasticity is crucial for the development of novel therapeutic neuromodulation methods.

Phase information is conserved in sparse, synchronous population-rate-codes via phase-to-rate recoding

Neural computation is often traced in terms of either rate- or phase-codes. However, most circuit operations will simultaneously affect information across both coding schemes. It remains unclear how phase and rate coded information is transmitted, in the face of continuous modification at consecutive processing stages. Here, we study this question in the entorhinal cortex (EC)- dentate gyrus (DG)- CA3 system using three distinct computational models. We demonstrate that DG feedback inhibition leverages EC phase information to improve rate-coding, a computation we term phase-to-rate recoding. Our results suggest that it i) supports the conservation of phase information within sparse rate-codes and ii) enhances the efficiency of plasticity in downstream CA3 via increased synchrony. Given the ubiquity of both phase-coding and feedback circuits, our results raise the question whether phase-to-rate recoding is a recurring computational motif, which supports the generation of sparse, synchronous population-rate-codes in areas beyond the DG.

Logarithmically scaled, gamma distributed neuronal spiking

Naturally log-scaled quantities abound in the nervous system. Distributions of these quantities have non-intuitive properties, which have implications for data analysis and the understanding of neural circuits. Here, we review the log-scaled statistics of neuronal spiking and the relevant analytical probability distributions. Recent work using log-scaling revealed that interspike intervals of forebrain neurons segregate into discrete modes reflecting spiking at different timescales and are each well-approximated by a gamma distribution. Each neuron spends most of the time in an irregular spiking 'ground state' with the longest intervals, which determines the mean firing rate of the neuron. Across the entire neuronal population, firing rates are log-scaled and well approximated by the gamma distribution, with a small number of highly active neurons and an overabundance of low rate neurons (the 'dark matter'). These results are intricately linked to a heterogeneous balanced operating regime, which confers upon neuronal circuits multiple computational advantages and has evolutionarily ancient origins.

Hippocampal beta rhythms as a bridge between sensory learning and memory-guided decision-making

A pillar of systems neuroscience has been the study of neural oscillations. Research into these oscillations spans brain areas, species, and disciplines, giving us common ground for discussing typically disparate fields of neuroscience. In this review, we aim to strengthen the dialog between sensory systems research and learning and memory systems research by examining a 15-40 Hz oscillation known as the beta rhythm. Starting with foundational observations based largely in olfactory systems neuroscience, we review evidence suggesting beta-based activity may extend across sensory systems generally, as well as into the hippocampus and areas well known for coordinating decisions and memory-guided behaviors. After evaluating this work, we propose a framework wherein the hippocampal beta oscillation and its diverse coupling with other brain areas can support both sensory learning and memory-guided decision-making. Using this framework, we also propose circuitries that may support these processes, and experiments to test our hypothesis.

Basal Forebrain Chemogenetic Inhibition Converts the Attentional Control Mode of Goal-Trackers to That of Sign-Trackers

Sign tracking versus goal tracking in rats indicate vulnerability and resistance, respectively, to Pavlovian cue-evoked addictive drug taking and relapse. Here, we tested hypotheses predicting that the opponent cognitive-behavioral styles indexed by sign tracking versus goal tracking include variations in attentional performance which differentially depend on basal forebrain projection systems. Pavlovian Conditioned Approach (PCA) testing was used to identify male and female sign-trackers (STs) and goal-trackers (GTs), as well as rats with an intermediate phenotype (INTs). Upon reaching asymptotic performance in an operant task requiring the detection of visual signals (hits) as well as the reporting of signal absence for 40 min per session, GTs scored more hits than STs, and hit rates across all phenotypes correlated with PCA scores. STs missed relatively more signals than GTs specifically during the last 15 min of a session. Chemogenetic inhibition of the basal forebrain decreased hit rates in GTs but was without effect in STs. Moreover, the decrease in hits in GTs manifested solely during the last 15 min of a session. Transfection efficacy in the horizontal limb of the diagonal band (HDB), but not substantia innominate (SI) or nucleus basalis of Meynert (nbM), predicted the behavioral efficacy of chemogenetic inhibition in GTs. Furthermore, the total subregional transfection space, not transfection of just cholinergic neurons, correlated with performance effects. These results indicate that the cognitive-behavioral phenotype indexed by goal tracking, but not sign tracking, depends on activation of the basal forebrain-frontal cortical projection system and associated biases toward top-down or model-based performance.

Complementary representations of time in the prefrontal cortex and hippocampus

Episodic memory binds the spatial and temporal relationships between the elements of experience. The hippocampus encodes space through place cells that fire at specific spatial locations. Similarly, time cells fire sequentially at specific time points within a temporally organized experience. Recent studies in rodents, monkeys, and humans have identified time cells with discrete firing fields and cells with monotonically changing activity in supporting the temporal organization of events across multiple timescales. Using in vivo electrophysiological tetrode recordings, we simultaneously recorded neurons from the prefrontal cortex and dorsal CA1 of the hippocampus while rats performed a delayed match to sample task. During the treadmill mnemonic delay, hippocampal time cells exhibited sparser firing fields with decreasing resolution over time, consistent with previous results. In comparison, temporally modulated cells in the prefrontal cortex showed more monotonically changing firing rates, ramping up or decaying with the passage of time, and exhibited greater temporal precision for Bayesian decoding of time at long time lags. These time cells show exquisite temporal resolution both in their firing fields and in the fine timing of spikes relative to the phase of theta oscillations. Here, we report evidence of theta phase precession in both the prefrontal cortex and hippocampus during the temporal delay, however, hippocampal cells exhibited steeper phase precession slopes and more punctate time fields. To disentangle whether time cell activity reflects elapsed time or distance traveled, we varied the treadmill running speed on each trial. While many neurons contained multiplexed representations of time and distance, both regions were more strongly influenced by time than distance. Overall, these results demonstrate the flexible integration of spatiotemporal dimensions and reveal complementary representations of time in the prefrontal cortex and hippocampus in supporting memory-guided behavior.

Spontaneous Spiking Is Governed by Broadband Fluctuations

Populations of cortical neurons generate rhythmic fluctuations in their ongoing spontaneous activity. These fluctuations can be seen in the local field potential (LFP), which reflects summed return currents from synaptic activity in the local population near a recording electrode. The LFP is spectrally broad, and many researchers view this breadth as containing many narrowband oscillatory components that may have distinct functional roles. This view is supported by the observation that the phase of narrowband oscillations is often correlated with cortical excitability and can relate to the timing of spiking activity and the fidelity of sensory evoked responses. Accordingly, researchers commonly tune in to these channels by narrowband filtering the LFP. Alternatively, neural activity may be fundamentally broadband and composed of transient, nonstationary rhythms that are difficult to approximate as oscillations. In this view, the instantaneous state of the broad ensemble relates directly to the excitability of the local population with no particular allegiance to any frequency band. To test between these alternatives, we asked whether the spiking activity of neocortical neurons in marmoset of either sex is better aligned with the phase of the LFP within narrow frequency bands or with a broadband measure. We find that the phase of broadband LFP fluctuations provides a better predictor of spike timing than the phase after filtering in narrow bands. These results challenge the view of the neocortex as a system composed of narrowband oscillators and supports a view in which neural activity fluctuations are intrinsically broadband.SIGNIFICANCE STATEMENT Research into the dynamical state of neural populations often attributes unique significance to the state of narrowband oscillatory components. However, rhythmic fluctuations in cortical activity are nonstationary and broad spectrum. We find that the timing of spontaneous spiking activity is better captured by the state of broadband fluctuations over any latent oscillatory component. These results suggest narrowband interpretations of rhythmic population activity may be limited, and broader representations may provide higher fidelity in describing moment-to-moment fluctuations in cortical activity.

Electrokinesis hypothesis of neuron selection for synapse formation and pruning

What neurons are connected and what neurons are disconnected? These are crucial questions since they determine the structural connectivity of the brain. We address this matter in question and propose a speculative hypothesis. We claim that the neuron selection for synapse formation and pruning process is an electrokinesis-based stochastic physical process. Propagating input signals generate a varying electromagnetic field in the interstitial fluid, which is filled with ions. Varying electromagnetic field exerts Lorentz force on the ions and causes local fluid flows. These fluid flows alter the position of presynaptic boutons and dendritic spines, and hence the likelihood of making contact. Above a certain level of field strength, the likelihood of pruning increases. If the proposed hypothesis is correct, in addition to explaining the natural process of neuron selection for synapse formation and pruning, it can also explain why and why not brain stimulation techniques work. Additionally, it will provide a controllable mechanism to alter brain connectivity as desired, which may have a profound impact on many connectivity-based psychiatric and neurological diseases.

Neuronal sequences during theta rely on behavior-dependent spatial maps

Navigation through space involves learning and representing relationships between past, current, and future locations. In mammals, this might rely on the hippocampal theta phase code, where in each cycle of the theta oscillation, spatial representations provided by neuronal sequences start behind the animal's true location and then sweep forward. However, the exact relationship between theta phase, represented position and true location remains unclear and even paradoxical. Here, we formalize previous notions of 'spatial' or 'temporal' theta sweeps that have appeared in the literature. We analyze single-cell and population variables in unit recordings from rat CA1 place cells and compare them to model simulations based on each of these schemes. We show that neither spatial nor temporal sweeps quantitatively accounts for how all relevant variables change with running speed. To reconcile these schemes with our observations, we introduce 'behavior-dependent' sweeps, in which theta sweep length and place field properties, such as size and phase precession, vary across the environment depending on the running speed characteristic of each location. These behavior-dependent spatial maps provide a structured heterogeneity that is essential for understanding the hippocampal code.

Large-scale collaboration in ENIGMA-EEG: A perspective on the meta-analytic approach to link neurological and psychiatric liability genes to electrophysiological brain activity

BACKGROUND AND PURPOSE

The ENIGMA-EEG working group was established to enable large-scale international collaborations among cohorts that investigate the genetics of brain function measured with electroencephalography (EEG). In this perspective, we will discuss why analyzing the genetics of functional brain activity may be crucial for understanding how neurological and psychiatric liability genes affect the brain.

METHODS

We summarize how we have performed our currently largest genome-wide association study of oscillatory brain activity in EEG recordings by meta-analyzing the results across five participating cohorts, resulting in the first genome-wide significant hits for oscillatory brain function located in/near genes that were previously associated with psychiatric disorders. We describe how we have tackled methodological issues surrounding genetic meta-analysis of EEG features. We discuss the importance of harmonizing EEG signal processing, cleaning, and feature extraction. Finally, we explain our selection of EEG features currently being investigated, including the temporal dynamics of oscillations and the connectivity network based on synchronization of oscillations.

RESULTS

We present data that show how to perform systematic quality control and evaluate how choices in reference electrode and montage affect individual differences in EEG parameters.

CONCLUSION

The long list of potential challenges to our large-scale meta-analytic approach requires extensive effort and organization between participating cohorts; however, our perspective shows that these challenges are surmountable. Our perspective argues that elucidating the genetic of EEG oscillatory activity is a worthwhile effort in order to elucidate the pathway from gene to disease liability.

Contribution of the basal forebrain to corticocortical network interactions

Basal forebrain (BF) cholinergic neurons provide the cerebral cortex with acetylcholine. Despite the long-established involvement of these cells in sensory processing, attention, and memory, the mechanisms by which cholinergic signaling regulates cognitive processes remain elusive. In this study, we recorded spiking and local field potential data simultaneously from several locations in the BF, and sites in the orbitofrontal and visual cortex in transgenic ChAT-Cre rats performing a visual discrimination task. We observed distinct differences in the fine spatial distributions of gamma coherence values between specific basalo-cortical and cortico-cortical sites that shifted across task phases. Additionally, cholinergic firing induced spatial changes in cortical gamma power, and optogenetic activation of BF increased coherence between specific cortico-cortical sites, suggesting that the cholinergic system contributes to selective modulation of cortico-cortical circuits. Furthermore, the results suggest that cells in specific BF locations are dynamically recruited across behavioral epochs to coordinate interregional cortical processes underlying cognition.

Phase precession in the human hippocampus and entorhinal cortex

Knowing where we are, where we have been, and where we are going is critical to many behaviors, including navigation and memory. One potential neuronal mechanism underlying this ability is phase precession, in which spatially tuned neurons represent sequences of positions by activating at progressively earlier phases of local network theta oscillations. Based on studies in rodents, researchers have hypothesized that phase precession may be a general neural pattern for representing sequential events for learning and memory. By recording human single-neuron activity during spatial navigation, we show that spatially tuned neurons in the human hippocampus and entorhinal cortex exhibit phase precession. Furthermore, beyond the neural representation of locations, we show evidence for phase precession related to specific goal states. Our findings thus extend theta phase precession to humans and suggest that this phenomenon has a broad functional role for the neural representation of both spatial and non-spatial information.

State-dependent entrainment of cerebellar nuclear neurons to the local field potential during voluntary movements

Understanding the relationship between the local field potential (LFP) and single neurons is essential if we are to understand network dynamics and the entrainment of neuronal activity. Here, we investigated the interaction between the LFP and single neurons recorded in the rat cerebellar nuclei (CN), which are part of the sensorimotor network, in freely moving rats. During movement, the LFP displayed persistent oscillations in the theta band frequency, whereas CN neurons displayed intermittent oscillations in the same frequency band contingent on the instantaneous LFP power; the neurons oscillated primarily when the concurrent LFP power was either high or low. Quantification of the relative instantaneous frequency and phase locking showed that CN neurons exhibited phase locked rhythmic activity at a frequency similar to that of the LFP or at a shifted frequency during high and low LFP power, respectively. We suggest that this nonlinear interaction between cerebellar neurons and the LFP power, which occurs solely during movement, contributes to the shaping of cerebellar output patterns.NEW & NOTEWORTHY We studied the interaction between single neurons and the LFP in the cerebellar nuclei of freely moving rats. We show that during movement, the neurons oscillated in the theta frequency band contingent on the concurrent LFP oscillation power in the same band; the neurons oscillated primarily when the LFP power was either high or low. We are the first to demonstrate a nonlinear, state-dependent entrainment of single neurons to the LFP.

Interindividual differences in memory system local field potential activity predict behavioral strategy on a dual-solution T-maze

Individuals can use diverse behavioral strategies to navigate their environment including hippocampal-dependent place strategies reliant upon cognitive maps and striatal-dependent response strategies reliant upon egocentric body turns. The existence of multiple memory systems appears to facilitate successful navigation across a wide range of environmental and physiological conditions. The mechanisms by which these systems interact to ultimately generate a unitary behavioral response, however, remain unclear. We trained 20 male, Sprague-Dawley rats on a dual-solution T-maze while simultaneously recording local field potentials that were targeted to the dorsolateral striatum and dorsal hippocampus. Eight rats spontaneously exhibited a place strategy while the remaining 12 rats exhibited a response strategy. Interindividual differences in behavioral strategy were associated with distinct patterns of LFP activity between the dorsolateral striatum and dorsal hippocampus. Specifically, striatal-hippocampal theta activity was in-phase in response rats and out-of-phase in place rats and response rats exhibited elevated striatal-hippocampal coherence across a wide range of frequency bands. These contrasting striatal-hippocampal activity regimes were (a) present during both maze-learning and a 30 min premaze habituation period and (b) could be used to train support vector machines to reliably predict behavioral strategy. Distinct patterns of neuronal activity across multiple memory systems, therefore, appear to bias behavioral strategy selection and thereby contribute to interindividual differences in behavior.

Optogenetic "low-theta" pacing of the septohippocampal circuit is sufficient for spatial goal finding and is influenced by behavioral state and cognitive demand

Hippocampal theta oscillations show prominent changes in frequency and amplitude depending on behavioral state or cognitive demands. How these dynamic changes in theta oscillations contribute to the spatial and temporal organization of hippocampal cells, and ultimately behavior, remain unclear. We used low-theta frequency optogenetic stimulation to pace coordination of cellular and network activity between the medial septum (MS) and hippocampus during baseline and MS stimulation while rats were at rest or performing a spatial accuracy task with a visible or hidden goal zone. Hippocampal receptivity to pan-neuronal septal stimulation at low-theta frequency was primarily determined by speed and secondarily by task demands. Competition between artificial and endogenous field potentials at theta frequency attenuated hippocampal phase preference relative to local theta, but the spike-timing activity of hippocampal pyramidal cells was effectively driven by artificial septal output, particularly during the hidden goal task. Notwithstanding temporal reorganization by artificial theta stimulation, place field properties were unchanged and alterations to spatial behavior were limited to goal zone approximation. Our results indicate that even a low-theta frequency timing signal in the septohippocampal circuit is sufficient for spatial goal finding behavior. The results also advance a mechanistic understanding of how endogenous or artificial somatodendritic timing signals relate to displacement computations during navigation and spatial memory.

Neurobiologically Inspired Self-Monitoring Systems

In this article, we explore neurobiological principles that could be deployed in systems requiring self-preservation, adaptive control, and contextual awareness. We start with low-level control for sensor processing and motor reflexes. We then discuss how critical it is at an intermediate level to maintain homeostasis and predict system set points. We end with a discussion at a high-level, or cognitive level, where planning and prediction can further monitor the system and optimize performance. We emphasize the information flow between these levels both from a systems neuroscience and an engineering point of view. Throughout the paper, we describe the brain systems that carry out these functions and provide examples from artificial intelligence, machine learning, and robotics that include these features. Our goal is to show how biological organisms performing self-monitoring can inspire the design of autonomous and embedded systems.

Neuromodulation in circuits of aversive emotional learning

Emotional learning and memory are functionally and dysfunctionally regulated by the neuromodulatory state of the brain. While the role of excitatory and inhibitory neural circuits mediating emotional learning and its control have been the focus of much research, we are only now beginning to understand the more diffuse role of neuromodulation in these processes. Recent experimental studies of the acetylcholine, noradrenaline and dopamine systems in fear learning and extinction of fear responding provide surprising answers to key questions in neuromodulation. One area of research has revealed how modular organization, coupled with context-dependent coding modes, allows for flexible brain-wide or targeted neuromodulation. Other work has shown how these neuromodulators act in downstream targets to enhance signal-to-noise ratios and gain, as well as to bind distributed circuits through neuronal oscillations. These studies elucidate how different neuromodulatory systems regulate aversive emotional processing and reveal fundamental principles of neuromodulatory function.

Specific Basal Forebrain-Cortical Cholinergic Circuits Coordinate Cognitive Operations

Based on recent molecular genetics, as well as functional and quantitative anatomical studies, the basal forebrain (BF) cholinergic projections, once viewed as a diffuse system, are emerging as being remarkably specific in connectivity. Acetylcholine (ACh) can rapidly and selectively modulate activity of specific circuits and ACh release can be coordinated in multiple areas that are related to particular aspects of cognitive processing. This review discusses how a combination of multiple new approaches with more established techniques are being used to finally reveal how cholinergic neurons, together with other BF neurons, provide temporal structure for behavior, contribute to local cortical state regulation, and coordinate activity between different functionally related cortical circuits. ACh selectively modulates dynamics for encoding and attention within individual cortical circuits, allows for important transitions during sleep, and shapes the fidelity of sensory processing by changing the correlation structure of neural firing. The importance of this system for integrated and fluid behavioral function is underscored by its disease-modifying role; the demise of BF cholinergic neurons has long been established in Alzheimer's disease and recent studies have revealed the involvement of the cholinergic system in modulation of anxiety-related circuits. Therefore, the BF cholinergic system plays a pivotal role in modulating the dynamics of the brain during sleep and behavior, as foretold by the intricacies of its anatomical map.

Space and Time: The Hippocampus as a Sequence Generator

Neural computations are often compared to instrument-measured distance or duration, and such relationships are interpreted by a human observer. However, neural circuits do not depend on human-made instruments but perform computations relative to an internally defined rate-of-change. While neuronal correlations with external measures, such as distance or duration, can be observed in spike rates or other measures of neuronal activity, what matters for the brain is how such activity patterns are utilized by downstream neural observers. We suggest that hippocampal operations can be described by the sequential activity of neuronal assemblies and their internally defined rate of change without resorting to the concept of space or time.