Inducing γ oscillations and precise spike synchrony by operant conditioning via brain-machine interface

The gamma rhythm as a guardian of brain health

Gamma oscillations in brain activity (30-150 Hz) have been studied for over 80 years. Although in the past three decades significant progress has been made to try to understand their functional role, a definitive answer regarding their causal implication in perception, cognition, and behavior still lies ahead of us. Here, we first review the basic neural mechanisms that give rise to gamma oscillations and then focus on two main pillars of exploration. The first pillar examines the major theories regarding their functional role in information processing in the brain, also highlighting critical viewpoints. The second pillar reviews a novel research direction that proposes a therapeutic role for gamma oscillations, namely the gamma entrainment using sensory stimulation (GENUS). We extensively discuss both the positive findings and the issues regarding reproducibility of GENUS. Going beyond the functional and therapeutic role of gamma, we propose a third pillar of exploration, where gamma, generated endogenously by cortical circuits, is essential for maintenance of healthy circuit function. We propose that four classes of interneurons, namely those expressing parvalbumin (PV), vasointestinal peptide (VIP), somatostatin (SST), and nitric oxide synthase (NOS) take advantage of endogenous gamma to perform active vasomotor control that maintains homeostasis in the neuronal tissue. According to this hypothesis, which we call GAMER (GAmma MEdiated ciRcuit maintenance), gamma oscillations act as a 'servicing' rhythm that enables efficient translation of neural activity into vascular responses that are essential for optimal neurometabolic processes. GAMER is an extension of GENUS, where endogenous rather than entrained gamma plays a fundamental role. Finally, we propose several critical experiments to test the GAMER hypothesis.

Neurofeedback training can modulate task-relevant memory replay rate in rats

Hippocampal replay - the time-compressed, sequential reactivation of ensembles of neurons related to past experience - is a key neural mechanism of memory consolidation. Replay typically coincides with a characteristic pattern of local field potential activity, the sharp-wave ripple (SWR). Reduced SWR rates are associated with cognitive impairment in multiple models of neurodegenerative disease, suggesting that a clinically viable intervention to promote SWRs and replay would prove beneficial. We therefore developed a neurofeedback paradigm for rat subjects in which SWR detection triggered rapid positive feedback in the context of a memory-dependent task. This training protocol increased the prevalence of task-relevant replay during the targeted neurofeedback period by changing the temporal dynamics of SWR occurrence. This increase was also associated with neural and behavioral forms of compensation after the targeted period. These findings reveal short-timescale regulation of SWR generation and demonstrate that neurofeedback is an effective strategy for modulating hippocampal replay.

Towards therapeutic electrophysiological neurofeedback in Parkinson's disease

Neurofeedback (NF) techniques support individuals to self-regulate specific features of brain activity, which has been shown to impact behavior and potentially ameliorate clinical symptoms. Electrophysiological NF (epNF) may be particularly impactful for patients with Parkinson's disease (PD), as evidence mounts to suggest a central role of pathological neural oscillations underlying symptoms in PD. Exaggerated beta oscillations (12-30 Hz) in the basal ganglia-cortical network are linked to motor symptoms (e.g., bradykinesia, rigidity), and beta is reduced by successful therapy with dopaminergic medication and Deep Brain Stimulation (DBS). PD patients also experience non-motor symptoms related to sleep, mood, motivation, and cognitive control. Although less is known about the mechanisms of non-motor symptoms in PD and how to successfully treat them, low frequency neural oscillations (1-12 Hz) in the basal ganglia-cortical network are particularly implicated in non-motor symptoms. Here, we review how cortical and subcortical epNF could be used to target motor and non-motor specific oscillations, and potentially serve as an adjunct therapy that enables PD patients to endogenously control their own pathological neural activities. Recent studies have demonstrated that epNF protocols can successfully support volitional control of cortical and subcortical beta rhythms. Importantly, this endogenous control of beta has been linked to changes in motor behavior. epNF for PD, as a casual intervention on neural signals, has the potential to increase understanding of the neurophysiology of movement, mood, and cognition and to identify new therapeutic approaches for motor and non-motor symptoms.

High-Gamma Activity Is Coupled to Low-Gamma Oscillations in Precentral Cortices and Modulates with Movement and Speech

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger-flexion or word-reading tasks. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

Enhancement of low gamma oscillations by volitional conditioning of local field potential in the primary motor and visual cortex of mice

Volitional control of local field potential oscillations in low gamma band via brain machine interface can not only uncover the relationship between low gamma oscillation and neural synchrony but also suggest a therapeutic potential to reverse abnormal local field potential oscillation in neurocognitive disorders. In nonhuman primates, the volitional control of low gamma oscillations has been demonstrated by brain machine interface techniques in the primary motor and visual cortex. However, it is not clear whether this holds in other brain regions and other species, for which gamma rhythms might involve in highly different neural processes. Here, we established a closed-loop brain-machine interface and succeeded in training mice to volitionally elevate low gamma power of local field potential in the primary motor and visual cortex. We found that the mice accomplished the task in a goal-directed manner and spiking activity exhibited phase-locking to the oscillation in local field potential in both areas. Moreover, long-term training made the power enhancement specific to direct and adjacent channel, and increased the transcriptional levels of NMDA receptors as well as that of hypoxia-inducible factor relevant to metabolism. Our results suggest that volitionally generated low gamma rhythms in different brain regions share similar mechanisms and pave the way for employing brain machine interface in therapy of neurocognitive disorders.

Neural Plasticity in Sensorimotor Brain-Machine Interfaces

Brain-machine interfaces (BMIs) aim to treat sensorimotor neurological disorders by creating artificial motor and/or sensory pathways. Introducing artificial pathways creates new relationships between sensory input and motor output, which the brain must learn to gain dexterous control. This review highlights the role of learning in BMIs to restore movement and sensation, and discusses how BMI design may influence neural plasticity and performance. The close integration of plasticity in sensory and motor function influences the design of both artificial pathways and will be an essential consideration for bidirectional devices that restore both sensory and motor function.

High-gamma activity is coupled to low-gamma oscillations in precentral cortices and modulates with movement and speech

Planning and executing motor behaviors requires coordinated neural activity among multiple cortical and subcortical regions of the brain. Phase-amplitude coupling between the high-gamma band amplitude and the phase of low frequency oscillations (theta, alpha, beta) has been proposed to reflect neural communication, as has synchronization of low-gamma oscillations. However, coupling between low-gamma and high-gamma bands has not been investigated. Here, we measured phase-amplitude coupling between low- and high-gamma in monkeys performing a reaching task and in humans either performing finger movements or speaking words aloud. We found significant coupling between low-gamma phase and high-gamma amplitude in multiple sensorimotor and premotor cortices of both species during all tasks. This coupling modulated with the onset of movement. These findings suggest that interactions between the low and high gamma bands are markers of network dynamics related to movement and speech generation.

Basal ganglia-cortical connectivity underlies self-regulation of brain oscillations in humans

Brain-computer interfaces provide an artificial link by which the brain can directly interact with the environment. To achieve fine brain-computer interface control, participants must modulate the patterns of the cortical oscillations generated from the motor and somatosensory cortices. However, it remains unclear how humans regulate cortical oscillations, the controllability of which substantially varies across individuals. Here, we performed simultaneous electroencephalography (to assess brain-computer interface control) and functional magnetic resonance imaging (to measure brain activity) in healthy participants. Self-regulation of cortical oscillations induced activity in the basal ganglia-cortical network and the neurofeedback control network. Successful self-regulation correlated with striatal activity in the basal ganglia-cortical network, through which patterns of cortical oscillations were likely modulated. Moreover, basal ganglia-cortical network and neurofeedback control network connectivity correlated with strong and weak self-regulation, respectively. The findings indicate that the basal ganglia-cortical network is important for self-regulation, the understanding of which should help advance brain-computer interface technology.

Simultaneous fMRI-EEG in 26 healthy participants indicate that the basal ganglia cortical network and the neurofeedback control network play different roles in self-regulation, providing further insight into the neural correlates for brain-machine interface control and feedback.

Spatially bivariate EEG-neurofeedback can manipulate interhemispheric inhibition

Human behavior requires inter-regional crosstalk to employ the sensorimotor processes in the brain. Although external neuromodulation techniques have been used to manipulate interhemispheric sensorimotor activity, a central controversy concerns whether this activity can be volitionally controlled. Experimental tools lack the power to up- or down-regulate the state of the targeted hemisphere over a large dynamic range and, therefore, cannot evaluate the possible volitional control of the activity. We addressed this difficulty by using the recently developed method of spatially bivariate electroencephalography (EEG)-neurofeedback to systematically enable the participants to modulate their bilateral sensorimotor activities. Here, we report that participants learn to up- and down-regulate the ipsilateral excitability to the imagined hand while maintaining constant contralateral excitability; this modulates the magnitude of interhemispheric inhibition (IHI) assessed by the paired-pulse transcranial magnetic stimulation (TMS) paradigm. Further physiological analyses revealed that the manipulation capability of IHI magnitude reflected interhemispheric connectivity in EEG and TMS, which was accompanied by intrinsic bilateral cortical oscillatory activities. Our results show an interesting approach for neuromodulation, which might identify new treatment opportunities, e.g., in patients suffering from a stroke.

Closed-loop neuromodulation for studying spontaneous activity and causality

Having established that spontaneous brain activity follows meaningful coactivation patterns and correlates with behavior, researchers have turned their attention to understanding its function and behavioral significance. We suggest closed-loop neuromodulation as a neural perturbation tool uniquely well suited for this task. Closed-loop neuromodulation has primarily been viewed as an interventionist tool to teach subjects to directly control their own brain activity. We examine an alternative operant conditioning model of closed-loop neuromodulation which, through implicit feedback, can manipulate spontaneous activity at the network level, without violating the spontaneous or endogenous nature of the signal, thereby providing a direct test of network causality.

Test–Retest Reliability of Synchrony and Metastability in Resting State fMRI

In recent years, interest has been growing in dynamic characteristic of brain signals from resting-state functional magnetic resonance imaging (rs-fMRI). Synchrony and metastability, as neurodynamic indexes, are considered as one of methods for analyzing dynamic characteristics. Although much research has studied the analysis of neurodynamic indices, few have investigated its reliability. In this paper, the datasets from the Human Connectome Project have been used to explore the test–retest reliabilities of synchrony and metastability from multiple angles through intra-class correlation (ICC). The results showed that both of these indexes had fair test–retest reliability, but they are strongly affected by the field strength, the spatial resolution, and scanning interval, less affected by the temporal resolution. Denoising processing can help improve their ICC values. In addition, the reliability of neurodynamic indexes was affected by the node definition strategy, but these effects were not apparent. In particular, by comparing the test–retest reliability of different resting-state networks, we found that synchrony of different networks was basically stable, but the metastability varied considerably. Among these, DMN and LIM had a relatively higher test–retest reliability of metastability than other networks. This paper provides a methodological reference for exploring the brain dynamic neural activity by using synchrony and metastability in fMRI signals.

Evaluating the Use of Cortical Entrainment to Measure Atypical Speech Processing: A Systematic Review

BACKGROUND

Cortical entrainment has emerged as promising means for measuring continuous speech processing in young, neurotypical adults. However, its utility for capturing atypical speech processing has not been systematically reviewed.

OBJECTIVES

Synthesize evidence regarding the merit of measuring cortical entrainment to capture atypical speech processing and recommend avenues for future research.

METHOD

We systematically reviewed publications investigating entrainment to continuous speech in populations with auditory processing differences.

RESULTS

In the 25 publications reviewed, most studies were conducted on older and/or hearing-impaired adults, for whom slow-wave entrainment to speech was often heightened compared to controls. Research conducted on populations with neurodevelopmental disorders, in whom slow-wave entrainment was often reduced, was less common. Across publications, findings highlighted associations between cortical entrainment and speech processing performance differences.

CONCLUSIONS

Measures of cortical entrainment offer useful means of capturing speech processing differences and future research should leverage them more extensively when studying populations with neurodevelopmental disorders.

Closed-loop Modulation of the Self-regulating Brain: A Review on Approaches, Emerging Paradigms, and Experimental Designs

Closed-loop approaches, setups, and experimental designs have been applied within the field of neuroscience to enhance the understanding of basic neurophysiology principles (closed-loop neuroscience; CLNS) and to develop improved procedures for modulating brain circuits and networks for clinical purposes (closed-loop neuromodulation; CLNM). The contents of this review are thus arranged into the following sections. First, we describe basic research findings that have been made using CLNS. Next, we provide an overview of the application, rationale, and therapeutic aspects of CLNM for clinical purposes. Finally, we summarize methodological concerns and critics in clinical practice of neurofeedback and novel applications of closed-loop perspective and techniques to improve and optimize its experiments. Moreover, we outline the theoretical explanations and experimental ideas to test animal models of neurofeedback and discuss technical issues and challenges associated with implementing closed-loop systems. We hope this review is helpful for both basic neuroscientists and clinical/ translationally-oriented scientists interested in applying closed-loop methods to improve mental health and well-being.

The Influence of Frequency Bands and Brain Region on ECoG-Based BMI Learning Performance

Numerous brain–machine interface (BMI) studies have shown that various frequency bands (alpha, beta, and gamma bands) can be utilized in BMI experiments and modulated as neural information for machine control after several BMI learning trial sessions. In addition to frequency range as a neural feature, various areas of the brain, such as the motor cortex or parietal cortex, have been selected as BMI target brain regions. However, although the selection of target frequency and brain region appears to be crucial in obtaining optimal BMI performance, the direct comparison of BMI learning performance as it relates to various brain regions and frequency bands has not been examined in detail. In this study, ECoG-based BMI learning performances were compared using alpha, beta, and gamma bands, respectively, in a single rodent model. Brain area dependence of learning performance was also evaluated in the frontal cortex, the motor cortex, and the parietal cortex. The findings indicated that BMI learning performance was best in the case of the gamma frequency band and worst in the alpha band (one-way ANOVA, F = 4.41, p < 0.05). In brain area dependence experiments, better BMI learning performance appears to be shown in the primary motor cortex (one-way ANOVA, F = 4.36, p < 0.05). In the frontal cortex, two out of four animals failed to learn the feeding tube control even after a maximum of 10 sessions. In conclusion, the findings reported in this study suggest that the selection of target frequency and brain region should be carefully considered when planning BMI protocols and for performing optimized BMI.

Gamma-band modulation in the human amygdala during reaching movements

OBJECTIVE

Motor brain-computer interface (BCI) represents a new frontier in neurological surgery that could provide significant benefits for patients living with motor deficits. Both the primary motor cortex and posterior parietal cortex have successfully been used as a neural source for human motor BCI, leading to interest in exploring other brain areas involved in motor control. The amygdala is one area that has been shown to have functional connectivity to the motor system; however, its role in movement execution is not well studied. Gamma oscillations (30-200 Hz) are known to be prokinetic in the human cortex, but their role is poorly understood in subcortical structures. Here, the authors use direct electrophysiological recordings and the classic "center-out" direct-reach experiment to study amygdaloid gamma-band modulation in 8 patients with medically refractory epilepsy.

METHODS

The study population consisted of 8 epilepsy patients (2 men; age range 21-62 years) who underwent implantation of micro-macro depth electrodes for seizure localization and EEG monitoring. Data from the macro contacts sampled at 2000 Hz were used for analysis. The classic center-out direct-reach experiment was used, which consists of an intertrial interval phase, a fixation phase, and a response phase. The authors assessed the statistical significance of neural modulation by inspecting for nonoverlapping areas in the 95% confidence intervals of spectral power for the response and fixation phases.

RESULTS

In 5 of the 8 patients, power spectral analysis showed a statistically significant increase in power within regions of the gamma band during the response phase compared with the fixation phase. In these 5 patients, the 95% bootstrapped confidence intervals of trial-averaged power in contiguous frequencies of the gamma band during the response phase were above, and did not overlap with, the confidence intervals of trial-averaged power during the fixation phase.

CONCLUSIONS

To the authors' knowledge, this is the first time that direct neural recordings have been used to show gamma-band modulation in the human amygdala during the execution of voluntary movement. This work indicates that gamma-band modulation in the amygdala could be a contributing source of neural signals for use in a motor BCI system.

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.

Phase-Specific Microstimulation Differentially Modulates Beta Oscillations and Affects Behavior

It is widely accepted that Beta-band oscillations play a role in sensorimotor behavior. To further explore this role, we developed a hybrid platform to combine neural operant conditioning and phase-specific intracortical microstimulation (ICMS). We trained monkeys, implanted with 96 electrode arrays in the motor cortex, to volitionally enhance local field potential (LFP) Beta-band (20-30 Hz) activity at selected sites using a brain-machine interface. We find that Beta oscillations of LFP and single-unit spiking activity increase dramatically with brain-machine interface training and that pre-movement Beta power is anti-correlated with task performance. We also find that phase-specific ICMS modulates the power and phase of oscillations, shifting local networks between oscillatory and non-oscillatory states. Furthermore, ICMS induces phase-dependent effects in animal reaction times and success rates. These findings contribute to unraveling the functional role of cortical oscillations and to the future development of clinical tools for ameliorating abnormal neuronal activities in brain disease.

Neurofeedback Training of Gamma Oscillations in Monkey Primary Visual Cortex

In humans, neurofeedback (NFB) training has been used extensively and successfully to manipulate brain activity. Feedback signals were derived from EEG, fMRI, MEG, and intracranial recordings and modifications were obtained of the BOLD signal, of the power of oscillatory activity in distinct frequency bands and of single unit activity. The purpose of the present study was to examine whether neuronal activity could also be controlled by NFB in early sensory cortices whose activity is thought to be influenced mainly by sensory input rather than volitional control. We trained 2 macaque monkeys to enhance narrow band gamma oscillations in the primary visual cortex by providing them with an acoustic signal that reflected the power of gamma oscillations in a preselected band and rewarding increases of the feedback signal. Oscillations were assessed from local field potentials recorded with chronically implanted microelectrodes. Both monkeys succeeded to raise gamma activity in the absence of visual stimulation in the selected frequency band and at the site from which the NFB signal was derived. This suggests that top-down signals are not confined to just modulate stimulus induced responses but can actually drive or facilitate the gamma generating microcircuits even in a primary sensory area.

Is there an Intrinsic Relationship between LFP Beta Oscillation Amplitude and Firing Rate of Individual Neurons in Macaque Motor Cortex?

The properties of motor cortical local field potential (LFP) beta oscillations have been extensively studied. Their relationship to the local neuronal spiking activity was also addressed. Yet, whether there is an intrinsic relationship between the amplitude of beta oscillations and the firing rate of individual neurons remains controversial. Some studies suggest a mapping of spike rate onto beta amplitude, while others find no systematic relationship. To help resolve this controversy, we quantified in macaque motor cortex the correlation between beta amplitude and neuronal spike count during visuomotor behavior. First, in an analysis termed “task-related correlation”, single-trial data obtained across all trial epochs were included. These correlations were significant in up to 32% of cases and often strong. However, a trial-shuffling control analysis recombining beta amplitudes and spike counts from different trials revealed these task-related correlations to reflect systematic, yet independent, modulations of the 2 signals with the task. Second, in an analysis termed “trial-by-trial correlation”, only data from fixed trial epochs were included, and correlations were calculated across trials. Trial-by-trial correlations were weak and rarely significant. We conclude that there is no intrinsic relationship between the firing rate of individual neurons and LFP beta oscillation amplitude in macaque motor cortex.

The Degree of Nesting between Spindles and Slow Oscillations Modulates Neural Synchrony

Spindles and slow oscillations (SOs) both appear to play an important role in memory consolidation. Spindle and SO "nesting," or the temporal overlap between the two events, is believed to modulate consolidation. However, the neurophysiological processes modified by nesting remain poorly understood. We thus recorded activity from the primary motor cortex of 4 male sleeping rats to investigate how SO and spindles interact to modulate the correlation structure of neural firing. During spindles, primary motor cortex neurons fired at a preferred phase, with neural pairs demonstrating greater neural synchrony, or correlated firing, during spindle peaks. We found a direct relationship between the temporal proximity between SO and spindles, and changes to the distribution of neural correlations; nesting was associated with narrowing of the distribution, with a reduction in low- and high-correlation pairs. Such narrowing may be consistent with greater exploration of neural states. Interestingly, after animals practiced a novel motor task, pairwise correlations increased during nested spindles, consistent with targeted strengthening of functional interactions. These findings may be key mechanisms through which spindle nesting supports memory consolidation.SIGNIFICANCE STATEMENT Our analysis revealed changes in cortical spiking structure that followed the waxing and waning of spindles; firing rates increased, spikes were more phase-locked to spindle-band local field potential, and synchrony across units peaked during spindles. Moreover, we showed that the degree of nesting between spindles and slow oscillations modified the correlation structure across units by narrowing the distribution of pairwise correlations. Finally, we demonstrated that engaging in a novel motor task increased pairwise correlations during nested spindles. These phenomena suggest key mechanisms through which the interaction of spindles and slow oscillations may support sensorimotor learning. More broadly, this work helps link large-scale measures of population activity to changes in spiking structure, a critical step in understanding neuroplasticity across multiple scales.

Oscillations in the auditory system and their possible role

GOURÉVITCH, B., C. Martin, O. Postal, J.J. Eggermont. Oscillations in the auditory system, their possible role. NEUROSCI BIOBEHAV REV XXX XXX-XXX, 2020. - Neural oscillations are thought to have various roles in brain processing such as, attention modulation, neuronal communication, motor coordination, memory consolidation, decision-making, or feature binding. The role of oscillations in the auditory system is less clear, especially due to the large discrepancy between human and animal studies. Here we describe many methodological issues that confound the results of oscillation studies in the auditory field. Moreover, we discuss the relationship between neural entrainment and oscillations that remains unclear. Finally, we aim to identify which kind of oscillations could be specific or salient to the auditory areas and their processing. We suggest that the role of oscillations might dramatically differ between the primary auditory cortex and the more associative auditory areas. Despite the moderate presence of intrinsic low frequency oscillations in the primary auditory cortex, rhythmic components in the input seem crucial for auditory processing. This allows the phase entrainment between the oscillatory phase and rhythmic input, which is an integral part of stimulus selection within the auditory system.

Real-time detection of neural oscillation bursts allows behaviourally relevant neurofeedback

Neural oscillations as important information carrier in the brain, are increasingly interpreted as transient bursts rather than as sustained oscillations. Short (<150 ms) bursts of beta-waves (15-30 Hz) have been documented in humans, monkeys and mice. These events were correlated with memory, movement and perception, and were even suggested as the primary ingredient of all beta-band activity. However, a method to measure these short-lived events in real-time and to investigate their impact on behaviour is missing. Here we present a real-time data analysis system, capable to detect short narrowband bursts, and demonstrate its usefulness to increase the beta-band burst-rate in rats. This neurofeedback training induced changes in overall oscillatory power, and bursts could be decoded from the movement of the rats, thus enabling future investigation of the role of oscillatory bursts.

Reinforcement schedules differentially affect learning in neuronal operant conditioning in rats

Operant conditioning of neuronal activity is a core process for better operation of brain-machine interfaces. However, few studies have investigated the role of reinforcement schedules in neuronal operant conditioning, although they are very effective in behavioral operant conditioning. To test the effect of different reinforcement schedules, the authors trained single-neuron activity in the motor cortex using fixed ratio (FR) and variable ratio (VR) schedules in rats. Neuronal firing rates were enhanced in the FR but not in the VR schedule during conditioning, suggesting that the principles of operant conditioning of neuronal activity are different from those of behavioral responses.

Brain-Machine Interfaces: Powerful Tools for Clinical Treatment and Neuroscientific Investigations

Brain-machine interfaces (BMIs) have exploded in popularity in the past decade. BMIs, also called brain-computer interfaces, provide a direct link between the brain and a computer, usually to control an external device. BMIs have a wide array of potential clinical applications, ranging from restoring communication to people unable to speak due to amyotrophic lateral sclerosis or a stroke, to restoring movement to people with paralysis from spinal cord injury or motor neuron disease, to restoring memory to people with cognitive impairment. Because BMIs are controlled directly by the activity of prespecified neurons or cortical areas, they also provide a powerful paradigm with which to investigate fundamental questions about brain physiology, including neuronal behavior, learning, and the role of oscillations. This article reviews the clinical and neuroscientific applications of BMIs, with a primary focus on motor BMIs.

Volitional control of single-electrode high gamma local field potentials by people with paralysis

Intracortical brain-computer interfaces (BCIs) can enable individuals to control effectors, such as a computer cursor, by directly decoding the user's movement intentions from action potentials and local field potentials (LFPs) recorded within the motor cortex. However, the accuracy and complexity of effector control achieved with such "biomimetic" BCIs will depend on the degree to which the intended movements used to elicit control modulate the neural activity. In particular, channels that do not record distinguishable action potentials and only record LFP modulations may be of limited use for BCI control. In contrast, a biofeedback approach may surpass these limitations by letting the participants generate new control signals and learn strategies that improve the volitional control of signals used for effector control. Here, we show that, by using a biofeedback paradigm, three individuals with tetraplegia achieved volitional control of gamma LFPs (40-400 Hz) recorded by a single microelectrode implanted in the precentral gyrus. Control was improved over a pair of consecutive sessions up to 3 days apart. In all but one session, the channel used to achieve control lacked distinguishable action potentials. Our results indicate that biofeedback LFP-based BCIs may potentially contribute to the neural modulation necessary to obtain reliable and useful control of effectors. NEW & NOTEWORTHY Our study demonstrates that people with tetraplegia can volitionally control individual high-gamma local-field potential (LFP) channels recorded from the motor cortex, and that this control can be improved using biofeedback. Motor cortical LFP signals are thought to be both informative and stable intracortical signals and, thus, of importance for future brain-computer interfaces.

Neural activity related to volitional regulation of cortical excitability

To date there exists no reliable method to non-invasively upregulate or downregulate the state of the resting human motor system over a large dynamic range. Here we show that an operant conditioning paradigm which provides neurofeedback of the size of motor evoked potentials (MEPs) in response to transcranial magnetic stimulation (TMS), enables participants to self-modulate their own brain state. Following training, participants were able to robustly increase (by 83.8%) and decrease (by 30.6%) their MEP amplitudes. This volitional up-versus down-regulation of corticomotor excitability caused an increase of late-cortical disinhibition (LCD), a TMS derived read-out of presynaptic GABAB disinhibition, which was accompanied by an increase of gamma and a decrease of alpha oscillations in the trained hemisphere. This approach paves the way for future investigations into how altered brain state influences motor neurophysiology and recovery of function in a neurorehabilitation context.

Concurrent control of a brain-computer interface and natural overt movements

OBJECTIVE

A primary control signal in brain-computer interfaces (BCIs) have been cortical signals related to movement. However, in cases where natural motor function remains, BCI control signals may interfere with other possibly simultaneous activity for useful ongoing movement. We sought to determine if the brain could learn to control both a BCI and concurrent overt movement execution in such cases.

APPROACH

We designed experiments where BCI and overt movements must be used concurrently and in coordination to achieve a 2D centre out control. Power in the 70-90 Hz band of human electrocorticography (ECoG) signals, was used to generate BCI control commands for vertical movement of the cursor. These signals were deliberately recorded from the same human cortical site that produced the strongest movement related activity associated with the concurrent overt finger movements required for the horizontal movement of the cursor.

MAIN RESULTS

We demonstrate that three subjects were able to perform the concurrent BCI task, controlling BCI and natural movements simultaneously and to a large extent independently. We conclude that the brain is capable of dissociating the original control signal dependency on movement, producing specific BCI control signals in the presence of motor related responses from the ongoing overt behaviour with which the BCI signal was initially correlated.

SIGNIFICANCE

We demonstrate a novel human brain-computer interface (BCI) which can be used to control movement concurrently and in coordination with movements of the natural limbs. This demonstrates the dissociation of cortical activity from the behaviour with which it was originally associated despite the ongoing behaviour and shows the feasibility of achieving simultaneous BCI control of devices with natural movements.

Endogenously generated gamma-band oscillations in early visual cortex: A neurofeedback study

Human subjects were trained with neurofeedback (NFB) to enhance the power of narrow-band gamma oscillations in circumscribed regions of early visual cortex. To select the region and the oscillation frequency for NFB training, gamma oscillations were induced with locally presented drifting gratings. The source and frequency of these induced oscillations were determined using beamforming methods. During NFB training the power of narrow band gamma oscillations was continuously extracted from this source with online beamforming and converted into the pitch of a tone signal. We found that seven out of ten subjects were able to selectively increase the amplitude of gamma oscillations in the absence of visual stimulation. One subject however failed completely and two subjects succeeded to manipulate the feedback signal by contraction of muscles. In all subjects the attempts to enhance visual gamma oscillations were associated with an increase of beta oscillations over precentral/frontal regions. Only successful subjects exhibited an additional marked increase of theta oscillations over precentral/prefrontal and temporal regions whereas unsuccessful subjects showed an increase of alpha band oscillations over occipital regions. We argue that spatially confined networks in early visual cortex can be entrained to engage in narrow band gamma oscillations not only by visual stimuli but also by top down signals. We interpret the concomitant increase in beta oscillations as indication for an engagement of the fronto-parietal attention network and the increase of theta oscillations as a correlate of imagery. Our finding support the application of NFB in disease conditions associated with impaired gamma synchronization.

Phase-Locked Stimulation during Cortical Beta Oscillations Produces Bidirectional Synaptic Plasticity in Awake Monkeys

The functional role of cortical beta oscillations, if any, remains unresolved. During oscillations, the periodic fluctuation in excitability of entrained cells modulates transmission of neural impulses and periodically enhances synaptic interactions. The extent to which oscillatory episodes affect activity-dependent synaptic plasticity remains to be determined. In nonhuman primates, we delivered single-pulse electrical cortical stimulation to a "stimulated" site in sensorimotor cortex triggered on a specific phase of ongoing beta (12-25 Hz) field potential oscillations recorded at a separate "triggering" site. Corticocortical connectivity from the stimulated to the triggering site as well as to other (non-triggering) sites was assessed by cortically evoked potentials elicited by test stimuli to the stimulated site, delivered outside of oscillatory episodes. In separate experiments, connectivity was assessed by intracellular recordings of evoked excitatory postsynaptic potentials. The conditioning paradigm produced transient (1-2 s long) changes in connectivity between the stimulated and the triggering site that outlasted the duration of the oscillatory episodes. The direction of the plasticity effect depended on the phase from which stimulation was triggered: potentiation in depolarizing phases, depression in hyperpolarizing phases. Plasticity effects were also seen at non-triggering sites that exhibited oscillations synchronized with those at the triggering site. These findings indicate that cortical beta oscillations provide a spatial and temporal substrate for short-term, activity-dependent synaptic plasticity in primate neocortex and may help explain the role of oscillations in attention, learning, and cortical reorganization.

Motor Cortical Gamma Oscillations: What Have We Learnt and Where Are We Headed?

PURPOSE OF REVIEW

An increase in oscillatory activity in the γ-frequency band (approximately 50-100 Hz) has long been noted during human movement. However, its functional role has been difficult to elucidate. The advent of novel techniques, particularly transcranial alternating current stimulation (tACS), has dramatically increased our ability to study γ oscillations. Here, we review our current understanding of the role of γ oscillations in the human motor cortex, with reference to γ activity outside the motor system, and evidence from animal models.

RECENT FINDINGS

Evidence for the neurophysiological basis of human γ oscillations is beginning to emerge. Multimodal studies, essential given the necessarily indirect measurements acquired in humans, are beginning to provide convergent evidence for the role of γ oscillations in movement, and their relationship to plasticity.

SUMMARY

Human motor cortical γ oscillations appear to play a key role in movement, and relate to learning. However, there are still major questions to be answered about their physiological basis and precise role in human plasticity. It is to be hoped that future research will take advantage of recent technical advances and the physiological basis and functional significance of this intriguing and important brain rhythm will be fully elucidated.

Electrical Stimulation Modulates High γ Activity and Human Memory Performance

Direct electrical stimulation of the brain has emerged as a powerful treatment for multiple neurological diseases, and as a potential technique to enhance human cognition. Despite its application in a range of brain disorders, it remains unclear how stimulation of discrete brain areas affects memory performance and the underlying electrophysiological activities. Here, we investigated the effect of direct electrical stimulation in four brain regions known to support declarative memory: hippocampus (HP), parahippocampal region (PH) neocortex, prefrontal cortex (PF), and lateral temporal cortex (TC). Intracranial EEG recordings with stimulation were collected from 22 patients during performance of verbal memory tasks. We found that high γ (62–118 Hz) activity induced by word presentation was modulated by electrical stimulation. This modulatory effect was greatest for trials with “poor” memory encoding. The high γ modulation correlated with the behavioral effect of stimulation in a given brain region: it was negative, i.e., the induced high γ activity was decreased, in the regions where stimulation decreased memory performance, and positive in the lateral TC where memory enhancement was observed. Our results suggest that the effect of electrical stimulation on high γ activity induced by word presentation may be a useful biomarker for mapping memory networks and guiding therapeutic brain stimulation.

Changes in cortical network connectivity with long-term brain-machine interface exposure after chronic amputation

Studies on neural plasticity associated with brain-machine interface (BMI) exposure have primarily documented changes in single neuron activity, and largely in intact subjects. Here, we demonstrate significant changes in ensemble-level functional connectivity among primary motor cortical (MI) neurons of chronically amputated monkeys exposed to control a multiple-degree-of-freedom robot arm. A multi-electrode array was implanted in M1 contralateral or ipsilateral to the amputation in three animals. Two clusters of stably recorded neurons were arbitrarily assigned to control reach and grasp movements, respectively. With exposure, network density increased in a nearly monotonic fashion in the contralateral monkeys, whereas the ipsilateral monkey pruned the existing network before re-forming a denser connectivity. Excitatory connections among neurons within a cluster were denser, whereas inhibitory connections were denser among neurons across the two clusters. These results indicate that cortical network connectivity can be modified with BMI learning, even among neurons that have been chronically de-efferented and de-afferented due to amputation.

Gamma oscillations in the superior colliculus and pulvinar in response to faces support discrimination performance in monkeys

The subcortical visual pathway including the superior colliculus (SC), pulvinar, and amygdala has been implicated in unconscious visual processing of faces, eyes, and gaze direction in blindsight. Our previous studies reported that monkey SC and pulvinar neurons responded preferentially to images of faces while performing a delayed non-matching to sample (DNMS) task to discriminate different visual stimuli (Nguyen et al., 2013, 2014). However, the contribution of SC and pulvinar neurons to the discrimination of the facial images and subsequent behavioral performance remains unknown. Since gamma oscillations have been implicated in sensory and cognitive processes as well as behavioral execution, we hypothesized that gamma oscillations during neuronal responses might contribute to achieving the appropriate behavioral performance (i.e., a correct response). In the present study, we re-analyzed those neuronal responses in the monkey SC and pulvinar to investigate possible relationships between gamma oscillations in these neurons and behavioral performance (correct response ratios) during the DNMS task. Gamma oscillations of SC and pulvinar neuronal activity were analyzed in three phases around the stimulus onset [inter-trial interval (ITI): 1000ms before trial onset; Early: 0-200ms after stimulus onset; and Late: 300-500ms after stimulus onset]. We found that human facial images elicited stronger gamma oscillations in the early phase than the ITI and late phase in both the SC and pulvinar neurons. Furthermore, there was a significant correlation between strengths of gamma oscillations in the early phase and behavioral performance in both the SC and pulvinar. The results suggest that gamma oscillatory activity in the SC and pulvinar contributes to successful behavioral performance during unconscious perceptual and behavioral processes.

Rapid Integration of Artificial Sensory Feedback during Operant Conditioning of Motor Cortex Neurons

Neuronal motor commands, whether generating real or neuroprosthetic movements, are shaped by ongoing sensory feedback from the displacement being produced. Here we asked if cortical stimulation could provide artificial feedback during operant conditioning of cortical neurons. Simultaneous two-photon imaging and real-time optogenetic stimulation were used to train mice to activate a single neuron in motor cortex (M1), while continuous feedback of its activity level was provided by proportionally stimulating somatosensory cortex. This artificial signal was necessary to rapidly learn to increase the conditioned activity, detect correct performance, and maintain the learned behavior. Population imaging in M1 revealed that learning-related activity changes are observed in the conditioned cell only, which highlights the functional potential of individual neurons in the neocortex. Our findings demonstrate the capacity of animals to use an artificially induced cortical channel in a behaviorally relevant way and reveal the remarkable speed and specificity at which this can occur.

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All-optical brain-machine-brain interface for neuroprosthetic control

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Mice rapidly learn to activate single neurons under optogenetically evoked feedback

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Population imaging reveals that learning is restricted to the conditioned neuron

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Novel “in cerebro” learning paradigm for neural circuit dissection

Physiological properties of brain-machine interface input signals

Brain-machine interfaces (BMIs), also called brain-computer interfaces (BCIs), decode neural signals and use them to control some type of external device. Despite many experimental successes and terrific demonstrations in animals and humans, a high-performance, clinically viable device has not yet been developed for widespread usage. There are many factors that impact clinical viability and BMI performance. Arguably, the first of these is the selection of brain signals used to control BMIs. In this review, we summarize the physiological characteristics and performance-including movement-related information, longevity, and stability-of multiple types of input signals that have been used in invasive BMIs to date. These include intracortical spikes as well as field potentials obtained inside the cortex, at the surface of the cortex (electrocorticography), and at the surface of the dura mater (epidural signals). We also discuss the potential for future enhancements in input signal performance, both by improving hardware and by leveraging the knowledge of the physiological characteristics of these signals to improve decoding and stability.

Learned control of inter-hemispheric connectivity: Effects on bimanual motor performance

Bimanual movements involve the interactions between both primary motor cortices. These interactions are assumed to involve phase-locked oscillatory brain activity referred to as inter-hemispheric functional coupling. So far, inter-hemispheric functional coupling has been investigated as a function of motor performance. These studies report mostly a negative correlation between the performance in motor tasks and the strength of functional coupling. However, correlation might not reflect a causal relationship. To overcome this limitation, we opted for an alternative approach by manipulating the strength of inter-hemispheric functional coupling and assessing bimanual motor performance as a dependent variable. We hypothesize that an increase/decrease of functional coupling deteriorates/facilitates motor performance in an out-of-phase bimanual finger-tapping task. Healthy individuals were trained to volitionally regulate functional coupling in an operant conditioning paradigm using real-time magnetoencephalography neurofeedback. During operant conditioning, two discriminative stimuli were associated with upregulation and downregulation of functional coupling. Effects of training were assessed by comparing motor performance prior to (pre-test) and after the training (post-test). Participants receiving contingent feedback learned to upregulate and downregulate functional coupling. Comparing motor performance, as indexed by the ratio of tapping speed for upregulation versus downregulation trials, no change was found in the control group between pre- and post-test. In contrast, the group receiving contingent feedback evidenced a significant decrease of the ratio implicating lower tapping speed with stronger functional coupling. Results point toward a causal role of inter-hemispheric functional coupling for the performance in bimanual tasks. Hum Brain Mapp 38:4353-4369, 2017. © 2017 Wiley Periodicals, Inc.

Beta band oscillations in motor cortex reflect neural population signals that delay movement onset

Motor cortical beta oscillations have been reported for decades, yet their behavioral correlates remain unresolved. Some studies link beta oscillations to changes in underlying neural activity, but the specific behavioral manifestations of these reported changes remain elusive. To investigate how changes in population neural activity, beta oscillations, and behavior are linked, we recorded multi-scale neural activity from motor cortex while three macaques performed a novel neurofeedback task. Subjects volitionally brought their beta oscillatory power to an instructed state and subsequently executed an arm reach. Reaches preceded by a reduction in beta power exhibited significantly faster movement onset times than reaches preceded by an increase in beta power. Further, population neural activity was found to shift farther from a movement onset state during beta oscillations that were neurofeedback-induced or naturally occurring during reaching tasks. This finding establishes a population neural basis for slowed movement onset following periods of beta oscillatory activity.

A network engineering perspective on probing and perturbing cognition with neurofeedback

Network science and engineering provide a flexible and generalizable tool set to describe and manipulate complex systems characterized by heterogeneous interaction patterns among component parts. While classically applied to social systems, these tools have recently proven to be particularly useful in the study of the brain. In this review, we describe the nascent use of these tools to understand human cognition, and we discuss their utility in informing the meaningful and predictable perturbation of cognition in combination with the emerging capabilities of neurofeedback. To blend these disparate strands of research, we build on emerging conceptualizations of how the brain functions (as a complex network) and how we can develop and target interventions or modulations (as a form of network control). We close with an outline of current frontiers that bridge neurofeedback, connectomics, and network control theory to better understand human cognition.

Proprioceptive Feedback Facilitates Motor Imagery-Related Operant Learning of Sensorimotor β-Band Modulation

Motor imagery (MI) activates the sensorimotor system independent of actual movements and might be facilitated by neurofeedback. Knowledge on the interaction between feedback modality and the involved frequency bands during MI-related brain self-regulation is still scarce. Previous studies compared the cortical activity during the MI task with concurrent feedback (MI with feedback condition) to cortical activity during the relaxation task where no feedback was provided (relaxation without feedback condition). The observed differences might, therefore, be related to either the task or the feedback. A proper comparison would necessitate studying a relaxation condition with feedback and a MI task condition without feedback as well. Right-handed healthy subjects performed two tasks, i.e., MI and relaxation, in alternating order. Each of the tasks (MI vs. relaxation) was studied with and without feedback. The respective event-driven oscillatory activity, i.e., sensorimotor desynchronization (during MI) or synchronization (during relaxation), was rewarded with contingent feedback. Importantly, feedback onset was delayed to study the task-related cortical activity in the absence of feedback provision during the delay period. The reward modality was alternated every 15 trials between proprioceptive and visual feedback. Proprioceptive input was superior to visual input to increase the range of task-related spectral perturbations in the α- and β-band, and was necessary to consistently achieve MI-related sensorimotor desynchronization (ERD) significantly below baseline. These effects occurred in task periods without feedback as well. The increased accuracy and duration of learned brain self-regulation achieved in the proprioceptive condition was specific to the β-band. MI-related operant learning of brain self-regulation is facilitated by proprioceptive feedback and mediated in the sensorimotor β-band.

Decoding Local Field Potentials for Neural Interfaces

The stability and frequency content of local field potentials (LFPs) offer key advantages for long-term, low-power neural interfaces. However, interpreting LFPs may require new signal processing techniques which should be informed by a scientific understanding of how these recordings arise from the coordinated activity of underlying neuronal populations. We review current approaches to decoding LFPs for brain-machine interface (BMI) applications, and suggest several directions for future research. To facilitate an improved understanding of the relationship between LFPs and spike activity, we share a dataset of multielectrode recordings from monkey motor cortex, and describe two unsupervised analysis methods we have explored for extracting a low-dimensional feature space that is amenable to biomimetic decoding and biofeedback training.

Voluntary control of intracortical oscillations for reconfiguration of network activity

Voluntary control of oscillatory activity represents a key target in the self-regulation of brain function. Using a real-time closed-loop paradigm and simultaneous macro- and micro-electrode recordings, we studied the effects of self-induced intracortical oscillatory activity (4–8 Hz) in seven neurosurgical patients. Subjects learned to robustly and specifically induce oscillations in the target frequency, confirmed by increased oscillatory event density. We have found that the session-to-session variability in performance was explained by the functional long-range decoupling of the target area suggesting a training-induced network reorganization. Downstream effects on more local activities included progressive cross-frequency-coupling with gamma oscillations (30–120 Hz), and the dynamic modulation of neuronal firing rates and spike timing, indicating an improved temporal coordination of local circuits. These findings suggest that effects of voluntary control of intracortical oscillations can be exploited to specifically target plasticity processes to reconfigure network activity, with a particular relevance for memory function or skill acquisition.

Neurofeedback Control in Parkinsonian Patients Using Electrocorticography Signals Accessed Wirelessly With a Chronic, Fully Implanted Device

Parkinson's disease (PD) is characterized by motor symptoms such as rigidity and bradykinesia that prevent normal movement. Beta band oscillations (13-30 Hz) in neural local field potentials (LFPs) have been associated with these motor symptoms. Here, three PD patients implanted with a therapeutic deep brain neural stimulator that can also record and wirelessly stream neural data played a neurofeedback game where they modulated their beta band power from sensorimotor cortical areas. Patients' beta band power was streamed in real-time to update the position of a cursor that they tried to drive into a cued target. After playing the game for 1-2 hours each, all three patients exhibited above chance-level performance regardless of subcortical stimulation levels. This study, for the first time, demonstrates using an invasive neural recording system for at-home neurofeedback training. Future work will investigate chronic neurofeedback training as a potentially therapeutic tool for patients with neurological disorders.

Analysis of Neuronal Spike Trains, Deconstructed

As information flows through the brain, neuronal firing progresses from encoding the world as sensed by the animal to driving the motor output of subsequent behavior. One of the more tractable goals of quantitative neuroscience is to develop predictive models that relate the sensory or motor streams with neuronal firing. Here we review and contrast analytical tools used to accomplish this task. We focus on classes of models in which the external variable is compared with one or more feature vectors to extract a low-dimensional representation, the history of spiking and other variables are potentially incorporated, and these factors are nonlinearly transformed to predict the occurrences of spikes. We illustrate these techniques in application to datasets of different degrees of complexity. In particular, we address the fitting of models in the presence of strong correlations in the external variable, as occurs in natural sensory stimuli and in movement. Spectral correlation between predicted and measured spike trains is introduced to contrast the relative success of different methods.

Dysfunction of sensory oscillations in Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is a highly prevalent developmental disability characterized by deficits in social communication and interaction, restricted interests, and repetitive behaviors. Recently, anomalous sensory and perceptual function has gained an increased level of recognition as an important feature of ASD. A specific impairment in the ability to integrate information across brain networks has been proposed to contribute to these disruptions. A crucial mechanism for these integrative processes is the rhythmic synchronization of neuronal excitability across neural populations; collectively known as oscillations. In ASD there is believed to be a deficit in the ability to efficiently couple functional neural networks using these oscillations. This review discusses evidence for disruptions in oscillatory synchronization in ASD, and how disturbance of this neural mechanism contributes to alterations in sensory and perceptual function. The review also frames oscillatory data from the perspective of prevailing neurobiologically-inspired theories of ASD.