LFP publications

Animals can capitalize on invariance in the environment by learning and automating highly consistent actions; however, they must also remain flexible and adapt to environmental changes. It remains unclear how primary motor cortex (M1) can drive precise movements, yet also support behavioral exploration when faced with consistent errors. Using a reach-to-grasp task in rats, along with simultaneous electrophysiological monitoring in M1 and dorsolateral striatum (DLS), we find that behavioral exploration to overcome consistent task errors is closely associated with tandem increases in M1 and DLS neural variability; subsequently, consistent ensemble patterning returns with convergence to a new successful strategy. We also show that compared to reliably patterned intracranial microstimulation in M1, variable stimulation patterns result in significantly greater movement variability. Our results thus indicate that motor and striatal areas can flexibly transition between two modes, reliable neural pattern generation for automatic and precise movements versus variable neural patterning for behavioral exploration.

Background Sensory perception is profoundly shaped by attention. Attending to an odor strongly regulates if and how it is perceived – yet the brain systems involved in this process are unknown. Here we report integration of the medial prefrontal cortex (mPFC), a collection of brain regions integral to attention, with the olfactory system in the context of selective attention to odors. Methods First, we used tracing methods to establish the tubular striatum (TuS, also known as the olfactory tubercle) as the primary olfactory region to receive direct mPFC input in rats. Next, we recorded (i) local field potentials from the olfactory bulb (OB), mPFC, and TuS, or (ii) sniffing, while rats completed an olfactory selective attention task. Results Gamma power and coupling of gamma oscillations with theta phase were consistently high as rats flexibly switched their attention to odors. Beta and theta synchrony between mPFC and olfactory regions were elevated as rats switched their attention to odors. Finally, we found that sniffing was consistent despite shifting attentional demands, suggesting that the mPFC-OB theta coherence is independent of changes in active sampling. Conclusions Together, these findings begin to define an olfactory attention network wherein mPFC activity, as well as that within olfactory regions, are coordinated based upon attentional states.

Because aberrant network-level functional connectivity underlies a variety of neural disorders, the ability to induce targeted functional reorganization would be a profound development toward therapies for neural disorders. Brain stimulation has been shown to induce large-scale network-wide functional connectivity changes (FCC), but the mapping from stimulation to the induced changes is unclear. Here, we develop a model which jointly considers the stimulation protocol and the cortical network structure to accurately predict network-wide FCC in response to optogenetic stimulation of non-human primate primary sensorimotor cortex. We observe that the network structure has a much stronger effect than the stimulation protocol on the resulting FCC. We also observe that the mappings from these input features to the FCC diverge over frequency bands and successive stimulations. Our framework represents a paradigm shift for targeted neural stimulation and can be used to interrogate, improve, and develop stimulation-based interventions for neural disorders.

Decades of hippocampal neurophysiology research have linked the hippocampal theta rhythm to voluntary movement. A consistent observation has been a robust correlation between the amplitude (or power) and frequency of hippocampal theta and running speed. Recently, however, it has been suggested that acceleration, not running speed, is the dominating influence on theta frequency. There is an inherent interdependence among these two variables, as acceleration is the rate of change in velocity. Therefore, we investigated theta frequency and amplitude of the local-field potential recorded from the stratum pyramidale, stratum radiatum, and stratum lacunosum moleculare of the CA1 subregion, considering both speed and acceleration in tandem as animals traversed a circular task or performed continuous alternation. In male and female rats volitionally controlling their own running characteristics, we found that running speed carries nearly all of the variability in theta frequency and power, with a minute contribution from acceleration. These results contradicted a recent publication using a speed-clamping task, where acceleration and movement are compelled through the use of a bottomless car (Kropff et al., 2021a). Therefore, we reanalyzed the speed-clamping data replicating a transient increase in theta frequency during acceleration. Compared with track running rats, the speed-clamped animals exhibited lower velocities and acceleration values but still showed a stronger influence of speed on theta frequency relative to acceleration. As navigation is the integration of many sensory inputs that are not necessarily linearly related, we offer caution in making absolute claims regarding hippocampal physiology from correlates garnered from a single behavioral repertoire. SIGNIFICANCE STATEMENT A long-standing, replicable observation has been the increase of hippocampal theta power and frequency with increasing running speed. Recently, however, an experimental approach that clamps the running speed of an animal has suggested that acceleration is the dominant influence. Therefore, we analyzed data from freely behaving rats as well as data from the speed-clamping experiment. In unrestrained behavior, speed remains the dominant behavioral correlate to theta amplitude and frequency. Positive acceleration in the speed-clamp experiment induced a transient increase in theta frequency and power. However, speed retained the dominant influence over theta frequency, changing with velocity in both acceleration and deceleration conditions.

Angelman syndrome is a neurodevelopmental disorder caused by deficiency of the maternally inherited UBE3A gene in neurons. Antisense oligonucleotide therapies are under development to reinstate UBE3A protein production. Non-invasive biomarkers to detect target engagement and treatment response are needed to support clinical trials. Delta power measured in the scalp EEG is a reliable biomarker for Angelman syndrome but varies widely across individuals and throughout development, making detection of a treatment effect using single measurements challenging. We utilized a longitudinal dataset of 204 EEG recordings from 56 subjects with Angelman syndrome to develop a natural history model of delta (2–4 Hz) power, with predictors of age, elapsed time, and relative delta power at an initial recording. Using this model, we computed the sample and effect sizes needed to detect a treatment effect in a human clinical trial with 80% power. We applied the same model structure to a mouse model of Angelman syndrome (n = 41) to detect antisense oligonucleotide-mediated treatment effects on absolute delta activity and Ube3a expression. In humans, delta power at a second time point can be reliably predicted using the natural history model. In mice, a treatment effect can be detected after antisense oligonucleotide treatment targeting the Ube3a-antisense transcript through at least 8 weeks post-treatment (P < 1e-15). Deviations in delta power from the expected natural history correlated with Ube3a expression in the mouse model (P < 0.001). Deviations in delta power from a human natural history model in Angelman syndrome can detect antisense oligonucleotide-mediated improvement in Ube3a expression in Angelman syndrome mice and may be relevant for human clinical trials.

Circuits of excitatory and inhibitory neurons generate gamma-rhythmic activity (30–80 Hz). Gamma-cycles show spontaneous variability in amplitude and duration. To investigate the mechanisms underlying this variability, we recorded local-field-potentials (LFPs) and spikes from awake macaque V1. We developed a noise-robust method to detect gamma-cycle amplitudes and durations, which showed a weak but positive correlation. This correlation, and the joint amplitude-duration distribution, is well reproduced by a noise-driven damped harmonic oscillator. This model accurately fits LFP power-spectra, is equivalent to a linear, noise-driven E-I circuit, and recapitulates two additional features of gamma: (1) Amplitude-duration correlations decrease with oscillation strength; (2) amplitudes and durations exhibit strong and weak autocorrelations, respectively, depending on oscillation strength. Finally, longer gamma-cycles are associated with stronger spike-synchrony, but lower spike-rates in both (putative) excitatory and inhibitory neurons. In sum, V1 gamma-dynamics are well described by the simplest possible model of gamma: A damped harmonic oscillator driven by noise.

Predictive coding is an important candidate theory of self-supervised learning in the brain. Its central idea is that sensory responses result from comparisons between bottom-up inputs and contextual predictions, a process in which rates and synchronization may play distinct roles. We recorded from awake macaque V1 and developed a technique to quantify stimulus predictability for natural images based on self-supervised, generative neural networks. We find that neuronal firing rates were mainly modulated by the contextual predictability of higher-order image features, which correlated strongly with human perceptual similarity judgments. By contrast, V1 gamma (γ)-synchronization increased monotonically with the contextual predictability of low-level image features and emerged exclusively for larger stimuli. Consequently, γ-synchronization was induced by natural images that are highly compressible and low-dimensional. Natural stimuli with low predictability induced prominent, late-onset beta (β)-synchronization, likely reflecting cortical feedback. Our findings reveal distinct roles of synchronization and firing rates in the predictive coding of natural images.

Parkinson’s disease is a neurological disease with cardinal motor signs including bradykinesia and tremor. Although beta-band hypersynchrony in the cortico-basal ganglia network is thought to contribute to disease manifestation, the resulting effects on network connectivity are unclear. We examined local field potentials from a non-human primate across the naïve, mild, and moderate disease states (model was asymmetric, left-hemispheric dominant) and probed power spectral density as well as cortico-cortical and cortico-subthalamic connectivity using both coherence and Granger causality, which measure undirected and directed effective connectivity, respectively. Our network included the left subthalamic nucleus (L-STN), bilateral primary motor cortices (L-M1, R-M1), and bilateral premotor cortices (L-PMC, R-PMC). Results showed two distinct peaks (Peak A at 5–20 Hz, Peak B at 25–45 Hz) across all analyses. Power and coherence analyses showed widespread increases in power and connectivity in both the Peak A and Peak B bands with disease progression. For Granger causality, increases in Peak B connectivity and decreases in Peak A connectivity were associated with the disease. Induction of mild disease was associated with several changes in connectivity: (1) the cortico-subthalamic connectivity in the descending direction (L-PMC to L-STN) decreased in the Peak A range while the reciprocal, ascending connectivity (L-STN to L-PMC) increased in the Peak B range; this may play a role in generating beta-band hypersynchrony in the cortex, (2) both L-M1 to L-PMC and R-M1 to R-PMC causalities increased, which may either be compensatory or a pathologic effect of disease, and (3) a decrease in connectivity occurred from the R-PMC to R-M1. The only significant change seen between mild and moderate disease was increased right cortical connectivity, which may reflect compensation for the left-hemispheric dominant moderate disease state.

Decreased responsiveness to sensory stimuli during sleep is presumably mediated via thalamic gating. Without an obligatory thalamic relay in the olfactory system, the anterior piriform cortex (APC) is suggested to be a gate in anesthetized states. However, olfactory processing in natural sleep states remains undetermined. Here, we simultaneously record local field potentials (LFPs) in hierarchical olfactory regions (olfactory bulb [OB], APC, and orbitofrontal cortex) while optogenetically activating olfactory sensory neurons, ensuring consistent peripheral inputs across states in behaving mice. Surprisingly, evoked LFPs in sleep states (both non-rapid eye movement [NREM] and rapid eye movement [REM]) are larger and contain greater gamma-band power and cross-region coherence (compared to wakefulness) throughout the olfactory pathway, suggesting the lack of a central gate. Single-unit recordings from the OB and APC reveal a higher percentage of responsive neurons during sleep with a higher incidence of suppressed firing. Additionally, nasal breathing is slower and shallower during sleep, suggesting a partial peripheral gating mechanism.

Serotonergic psychedelic drugs, such as psilocin (4-hydroxy-N,N-dimethyltryptamine), profoundly alter the quality of consciousness through mechanisms which are incompletely understood. Growing evidence suggests that a single psychedelic experience can positively impact long-term psychological well-being, with relevance for the treatment of psychiatric disorders, including depression. A prominent factor associated with psychiatric disorders is disturbed sleep, and the sleep-wake cycle is implicated in the homeostatic regulation of neuronal activity and synaptic plasticity. However, it remains largely unknown to what extent psychedelic agents directly affect sleep, in terms of both acute arousal and homeostatic sleep regulation. Here, chronic electrophysiological recordings were obtained in mice to track sleep-wake architecture and cortical activity after psilocin injection. Administration of psilocin led to delayed REM sleep onset and reduced NREM sleep maintenance for up to approximately 3 h after dosing, and the acute EEG response was associated primarily with an enhanced oscillation around 4 Hz. No long-term changes in sleep-wake quantity were found. When combined with sleep deprivation, psilocin did not alter the dynamics of homeostatic sleep rebound during the subsequent recovery period, as reflected in both sleep amount and EEG slow-wave activity. However, psilocin decreased the recovery rate of sleep slow-wave activity following sleep deprivation in the local field potentials of electrodes targeting the medial prefrontal and surrounding cortex. It is concluded that psilocin affects both global vigilance state control and local sleep homeostasis, an effect which may be relevant for its antidepressant efficacy.

Background To localize sound sources accurately in a reverberant environment, human binaural hearing strongly favors analyzing the initial wave front of sounds. Behavioral studies of this “precedence effect” have so far largely been confined to human subjects, limiting the scope of complementary physiological approaches. Similarly, physiological studies have mostly looked at neural responses in the inferior colliculus, the main relay point between the inner ear and the auditory cortex, or used modeling of cochlear auditory transduction in an attempt to identify likely underlying mechanisms. Studies capable of providing a direct comparison of neural coding and behavioral measures of sound localization under the precedence effect are lacking. Results We adapted a “temporal weighting function” paradigm previously developed to quantify the precedence effect in human for use in laboratory rats. The animals learned to lateralize click trains in which each click in the train had a different interaural time difference. Computing the “perceptual weight” of each click in the train revealed a strong onset bias, very similar to that reported for humans. Follow-on electrocorticographic recording experiments revealed that onset weighting of interaural time differences is a robust feature of the cortical population response, but interestingly, it often fails to manifest at individual cortical recording sites. Conclusion While previous studies suggested that the precedence effect may be caused by early processing mechanisms in the cochlea or inhibitory circuitry in the brainstem and midbrain, our results indicate that the precedence effect is not fully developed at the level of individual recording sites in the auditory cortex, but robust and consistent precedence effects are observable only in the auditory cortex at the level of cortical population responses. This indicates that the precedence effect emerges at later cortical processing stages and is a significantly “higher order” feature than has hitherto been assumed.

Disruption of subthalamic nucleus dynamics in Parkinson’s disease leads to impairments during walking. Here, we aimed to uncover the principles through which the subthalamic nucleus encodes functional and dysfunctional walking in people with Parkinson’s disease. We conceived a neurorobotic platform that allowed us to deconstruct the key components of walking under well-controlled conditions. We exploited this platform in 18 patients with Parkinson’s disease, which allowed us to demonstrate that the subthalamic nucleus encodes the initiation, termination, and vigor of leg muscle activation. We found that the same fundamental principles determine the encoding of walking. We translated this understanding into a machine-learning framework that decoded muscle activation, walking states, locomotor vigor, and freezing of gait. These results expose key principles through which subthalamic nucleus dynamics encode walking, opening the possibility to operate neuroprosthetic systems with these signals to improve walking in people with Parkinson’s disease. One Sentence Summary The subthalamic nucleus encodes the initiation, termination, and vigor of muscle activity, which supports real-time decoding of gait in people with Parkinson’s disease.

Although the etiology of major depressive disorder remains poorly understood, impairment of gamma oscillations recently emerged as a potential biomarker for major depression. The olfactory bulb (OB) is a major source of brain wide gamma oscillations and bulbectomy is an animal model for depression. Here we demonstrate that chemogenetic suppression of OB neuronal activity or temporally suppressing the OB to pyriform cortex synaptic transmission decreased gamma oscillation power in multiple brain areas associated with depression-like behaviors. To assess the hypothesized link between depression and diffuse depression of gamma oscillations, we employed gamma phase-dependent closed loop neuromodulation of cortical areas, paced by the native OB output. This procedure alleviated depressive-like behaviors in animals and suggests that restoring gamma oscillations may improve depression in humans. One Sentence Summary Role of limbic gamma oscillations in depression

Objective. Extracellular microelectrode techniques are the most widely used approach to interrogate neuronal populations. However, regardless of the manufacturing method used, damage to the vasculature and circuit function during probe insertion remains a concern. This issue can be mitigated by minimising the footprint of the probe used. Reducing the size of probes typically requires either a reduction in the number of channels present in the probe, or a reduction in the individual channel area. Both lead to less effective coupling between the probe and extracellular signals of interest. Approach. Here, we show that continuously drawn SiO 2 -insulated ultra-microelectrode fibres offer an attractive substrate to address these challenges. Individual fibres can be fabricated to >10 m continuous stretches and a selection of diameters below 30 µ m with low resistance (<100 Ω mm −1 ) continuously conductive metal core of <10 µ m and atomically flat smooth shank surfaces. To optimize the properties of the miniaturised electrode-tissue interface, we electrodeposit rough Au structures followed by ∼20 nm IrOx film resulting in the reduction of the interfacial impedance to <500 kΩ at 1 kHz. Main results . We demonstrate that these ultra-low impedance electrodes can record and stimulate both single and multi-unit activity with minimal tissue disturbance and exceptional signal-to-noise ratio in both superficial (∼40 µ m) and deep (∼6 mm) structures of the mouse brain. Further, we show that sensor modifications are stable and probe manufacturing is reproducible. Significance. Minimally perturbing bidirectional neural interfacing can reveal circuit function in the mammalian brain in vivo.

The contactin-associated protein-like 2 gene, CNTNAP2, is a highly penetrant risk gene thought to play a role in the genetic etiology of language-related disorders, such as autism spectrum disorder and developmental language disorder. Despite its candidacy for influencing language development, few preclinical studies have examined the role of CNTNAP2 in auditory processing. Using in vivo and in vitro electrophysiological recordings in a rat model with translational validity, we report that a loss of the Cntnap2 gene function caused immature-like cortical evoked potentials, delayed multiunit response latencies to acoustic stimuli, impaired temporal processing, and led to a pattern of hyperexcitability in both multiunit and single cell recordings in adulthood. These collective results provide direct evidence that a constitutive loss of Cntnap2 gene function in rats can cause auditory processing impairments similar to those seen in language-related human disorders, indicating that its contribution in maintaining cortical neuron excitability may underlie the cortical activity alterations observed in Cntnap2−/− rats.

Cognitive operations are widely studied by measuring electric fields through EEG and ECoG. However, despite their widespread use, the neural circuitry giving rise to these signals remains unknown because the functional architecture of cortical columns producing attention-associated electric fields has not been explored. Here, we detail the laminar cortical circuitry underlying an attention-associated electric field measured over posterior regions of the brain in humans and monkeys. First, we identified visual cortical area V4 as one plausible contributor to this attention-associated electric field through inverse modeling of cranial EEG in macaque monkeys performing a visual attention task. Next, we performed laminar neurophysiological recordings on the prelunate gyrus and identified the electric-field-producing dipoles as synaptic activity in distinct cortical layers of area V4. Specifically, activation in the extragranular layers of cortex resulted in the generation of the attention-associated dipole. Feature selectivity of a given cortical column determined the overall contribution to this electric field. Columns selective for the attended feature contributed more to the electric field than columns selective for a different feature. Last, the laminar profile of synaptic activity generated by V4 was sufficient to produce an attention-associated signal measurable outside of the column. These findings suggest that the top-down recipient cortical layers produce an attention-associated electric field that can be measured extracortically with the relative contribution of each column depending upon the underlying functional architecture.

Neuropeptides are contained in nearly every neuron in the central nervous system and can be released from somatodendritic sites as well as from nerve terminals. Cholecystokinin (CCK), among the most abundant neuropeptides in the brain, is expressed in the majority of midbrain dopamine neurons. Here we report that ventral tegmental area (VTA) dopamine neurons release CCK from somatodendritic regions, where it triggers long-term potentiation of GABAergic synapses. The somatodendritic release occurs with trains of action potentials or prolonged but modest depolarization and is dependent on synaptotagmin 7 and T-type Ca 2+ channels. Depolarization-induced LTP is blocked by the CCK2R antagonist, LY225910, and mimicked by exogenously added CCK. To test the behavioral role of CCK, we infused it into the mouse VTA. Ca 2+ imaging in vivo demonstrated that infused CCK reduced dopamine cell signals during fasted food consumption. Moreover, local infusion of CCK also inhibited food consumption and decreased distance traveled in an open field test. Together our experiments introduce somatodendritic neuropeptide release as a previously unknown feedback regulator of VTA dopamine cell excitability and dopamine-related behaviors.

Dopamine degeneration in Parkinson's disease (PD) dysregulates the striatal neural network and causes motor deficits. However, it is unclear how altered striatal circuits relate to dopamine-acetylcholine chemical imbalance and abnormal local field potential (LFP) oscillations observed in PD. We perform a multimodal analysis of the dorsal striatum using cell-type-specific calcium imaging and LFP recording. We reveal that dopamine depletion selectively enhances LFP beta oscillations during impaired locomotion, supporting beta oscillations as a biomarker for PD. We further demonstrate that dynamic cholinergic interneuron activity during locomotion remains unaltered, even though cholinergic tone is implicated in PD. Instead, dysfunctional striatal output arises from elevated coordination within striatal output neurons, which is accompanied by reduced locomotor encoding of parvalbumin interneurons and transient pathological LFP high-gamma oscillations. These results identify a pathological striatal circuit state following dopamine depletion where distinct striatal neuron subtypes are selectively coordinated with LFP oscillations during locomotion.

Dysregulated homeostasis of neural activity has been hypothesized to drive Alzheimer's disease (AD) pathogenesis. AD begins with a decades-long presymptomatic phase, but whether homeostatic mechanisms already begin failing during this silent phase is unknown. We show that before the onset of memory decline and sleep disturbances, familial AD (fAD) model mice display no deficits in CA1 mean firing rate (MFR) during active wakefulness. However, homeostatic down-regulation of CA1 MFR is disrupted during non-rapid eye movement (NREM) sleep and general anesthesia in fAD mouse models. The resultant hyperexcitability is attenuated by the mitochondrial dihydroorotate dehydrogenase (DHODH) enzyme inhibitor, which tunes MFR toward lower set-point values. Ex vivo fAD mutations impair downward MFR homeostasis, resulting in pathological MFR set points in response to anesthetic drug and inhibition blockade. Thus, firing rate dyshomeostasis of hippocampal circuits is masked during active wakefulness but surfaces during low-arousal brain states, representing an early failure of the silent disease stage.

Dominant neuroanatomical models hold that humans regulate their movements via loop-like cortico-subcortical networks, which include the subthalamic nucleus (STN), motor thalamus, and sensorimotor cortex (SMC). Inhibitory commands across these networks are purportedly sent via transient, burst-like signals in the β frequency (15–29 Hz). However, since human depth-recording studies are typically limited to one recording site, direct evidence for this proposition is hitherto lacking. Here, we present simultaneous multi-site recordings from SMC and either STN or motor thalamus in humans performing the stop-signal task. In line with their purported function as inhibitory signals, subcortical β-bursts were increased on successful stop-trials. STN bursts in particular were followed within 50 ms by increased β-bursting over SMC. Moreover, between-site comparisons (including in a patient with simultaneous recordings from SMC, thalamus, and STN) confirmed that β-bursts in STN temporally precede thalamic β-bursts. This highly unique set of recordings provides empirical evidence for the role of β-bursts in conveying inhibitory commands along long-proposed cortico-subcortical networks underlying movement regulation in humans.