Cortical signatures of sleep are altered following effective deep brain stimulation for depression.

Deep brain stimulation (DBS) of the subcallosal cingulate cortex (SCC) is an experimental therapy for treatment-resistant depression (TRD). Chronic SCC DBS leads to long-term changes in the electrophysiological dynamics measured from local field potential (LFP) during wakefulness, but it is unclear how it impacts sleep-related brain activity. This is a crucial gap in knowledge, given the link between depression and sleep disturbances, and an emerging interest in the interaction between DBS, sleep, and circadian rhythms. We therefore sought to characterize changes in electrophysiological markers of sleep associated with DBS treatment for depression. We analyzed key electrophysiological signatures of sleep-slow-wave activity (SWA, 0.5-4.5 Hz) and sleep spindles-in LFPs recorded from the SCC of 9 patients who responded to DBS for TRD. This allowed us to compare the electrophysiological changes before and after 24 weeks of therapeutically effective SCC DBS. SWA power was highly correlated between hemispheres, consistent with a global sleep state. Furthermore, SWA occurred earlier in the night after chronic DBS and had a more prominent peak. While we found no evidence for changes to slow-wave power or stability, we found an increase in the density of sleep spindles. Our results represent a first-of-its-kind report on long-term electrophysiological markers of sleep recorded from the SCC in patients with TRD, and provides evidence of earlier NREM sleep and increased sleep spindle activity following clinically effective DBS treatment. Future work is needed to establish the causal relationship between long-term DBS and the neural mechanisms underlying sleep.

Cingulate dynamics track depression recovery with deep brain stimulation.

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) can provide long-term symptom relief for treatment-resistant depression (TRD)1. However, achieving stable recovery is unpredictable2, typically requiring trial-and-error stimulation adjustments due to individual recovery trajectories and subjective symptom reporting3. We currently lack objective brain-based biomarkers to guide clinical decisions by distinguishing natural transient mood fluctuations from situations requiring intervention. To address this gap, we used a new device enabling electrophysiology recording to deliver SCC DBS to ten TRD participants (ClinicalTrials.gov identifier NCT01984710). At the study endpoint of 24 weeks, 90% of participants demonstrated robust clinical response, and 70% achieved remission. Using SCC local field potentials available from six participants, we deployed an explainable artificial intelligence approach to identify SCC local field potential changes indicating the patient's current clinical state. This biomarker is distinct from transient stimulation effects, sensitive to therapeutic adjustments and accurate at capturing individual recovery states. Variable recovery trajectories are predicted by the degree of preoperative damage to the structural integrity and functional connectivity within the targeted white matter treatment network, and are matched by objective facial expression changes detected using data-driven video analysis. Our results demonstrate the utility of objective biomarkers in the management of personalized SCC DBS and provide new insight into the relationship between multifaceted (functional, anatomical and behavioural) features of TRD pathology, motivating further research into causes of variability in depression treatment.

Neural Interoceptive Processing is Modulated by Deep Brain Stimulation for Treatment Resistant Depression.

Background: A critical advance in depression research is to clarify the hypothesized role of interoceptive processing in neural mechanisms of treatment efficacy. This study tests whether cortical interoceptive processing, as indexed by the heartbeat-evoked potential (HEP), is modulated by deep brain stimulation (DBS) to the subcallosal cingulate (SCC) for treatment resistant depression (TRD). Methods: Eight patients with TRD were enrolled in a study of SCC DBS safety and efficacy. Electroencephalography (EEG) and symptom severity measures were sampled in a laboratory setting over the course of a six-month treatment protocol. The primary outcome measure was an EEG-derived HEP, which reflects cortical processing of heartbeat sensation. Cluster-based permutation analyses were used to test the effect of stimulation and time in treatment on the HEP. The change in signal magnitude after treatment was correlated with change in depression severity as measured by the 17-item Hamilton Depression Rating Scale. Results: HEP amplitude was greater after 24 weeks of treatment ( t (7)=-4.40, p =.003, g= -1.38, 95% Cl [-2.3, -0.42]), and this change was inversely correlated with latency of treatment response (rho = -0.75, 95% Cl [-0.95, -0.11], p= .03). An acute effect of DBS was also observed, but as a decrease in HEP amplitude ( t (6) =6.66, p <.001, g= 2.19, 95% Cl [0.81, 3.54]). HEP differences were most pronounced over left posterior sensors from 405-425 ms post-stimulus. Conclusion: Brain-based evidence substantiates a theorized link between interoception and depression, and suggests an interoceptive contribution to the mechanism of treatment efficacy with deep brain stimulation for severe depression.

Time-frequency signatures evoked by single-pulse deep brain stimulation to the subcallosal cingulate.

Precision targeting of specific white matter bundles that traverse the subcallosal cingulate (SCC) has been linked to efficacy of deep brain stimulation (DBS) for treatment resistant depression (TRD). Methods to confirm optimal target engagement in this heterogenous region are now critical to establish an objective treatment protocol. As yet unexamined are the time-frequency features of the SCC evoked potential (SCC-EP), including spectral power and phase-clustering. We examined these spectral features-evoked power and phase clustering-in a sample of TRD patients (n = 8) with implanted SCC stimulators. Electroencephalogram (EEG) was recorded during wakeful rest. Location of electrical stimulation in the SCC target region was the experimental manipulation. EEG was analyzed at the surface level with an average reference for a cluster of frontal sensors and at a time window identified by prior study (50-150 ms). Morlet wavelets generated indices of evoked power and inter-trial phase clustering. Enhanced phase clustering at theta frequency (4-7 Hz) was observed in every subject and was significantly correlated with SCC-EP magnitude, but only during left SCC stimulation. Stimulation to dorsal SCC evinced stronger phase clustering than ventral SCC. There was a weak correlation between phase clustering and white matter density. An increase in evoked delta power (2-4 Hz) was also coincident with SCC-EP, but was less consistent across participants. DBS evoked time-frequency features index mm-scale changes to the location of stimulation in the SCC target region and correlate with structural characteristics implicated in treatment optimization. Results also imply a shared generative mechanism (inter-trial phase clustering) between evoked potentials evinced by electrical stimulation and evoked potentials evinced by auditory/visual stimuli and behavioral tasks. Understanding how current injection impacts downstream cortical activity is essential to building new technologies that adapt treatment parameters to individual differences in neurophysiology.

Proceedings of the Ninth Annual Deep Brain Stimulation Think Tank: Advances in Cutting Edge Technologies, Artificial Intelligence, Neuromodulation, Neuroethics, Pain, Interventional Psychiatry, Epilepsy, and Traumatic Brain Injury.

DBS Think Tank IX was held on August 25-27, 2021 in Orlando FL with US based participants largely in person and overseas participants joining by video conferencing technology. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging deep brain stimulation (DBS) technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank IX speakers was that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. After collectively sharing our experiences, it was estimated that globally more than 230,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. As such, this year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia and Australia; cutting-edge technologies, neuroethics, interventional psychiatry, adaptive DBS, neuromodulation for pain, network neuromodulation for epilepsy and neuromodulation for traumatic brain injury.

Network-Targeted, Multi-site Direct Cortical Stimulation Enhances Working Memory by Modulating Phase Lag of Low-Frequency Oscillations.

Working memory is mediated by the coordinated activation of frontal and parietal cortices occurring in the theta and alpha frequency ranges. Here, we test whether electrically stimulating frontal and parietal regions at the frequency of interaction is effective in modulating working memory. We identify working memory nodes that are functionally connected in theta and alpha frequency bands and intracranially stimulate both nodes simultaneously in participants performing working memory tasks. We find that in-phase stimulation results in improvements in performance compared to sham stimulation. In addition, in-phase stimulation results in decreased phase lag between regions within working memory network, while anti-phase stimulation results in increased phase lag, suggesting that shorter phase lag in oscillatory connectivity may lead to better performance. The results support the idea that phase lag may play a key role in information transmission across brain regions. Thus, brain stimulation strategies to improve cognition may require targeting multiple nodes of brain networks.

Active and Passive Rhythmic Music Therapy Interventions Differentially Modulate Sympathetic Autonomic Nervous System Activity.

Dysregulation of the autonomic nervous system (ANS) and the hypothalamic-pituitary-adrenal (HPA) axis has been implicated in psychiatric disorders. Music therapy (MT) has been shown to modulate heart-rate variability (HRV) and salivary stress markers, physiological markers of the ANS and HPA axes, respectively. Given the prominent role of arousal and stress physiology in many psychiatric disorders, MT has the potential to provide therapeutic benefits in psychiatry. Active MT requires patients to engage rhythmically with music; in contrast, passive MT requires patients to listen to music, eliminating the rhythmic movement seen in active MT. Yet, it remains unknown whether active or passive MT differentially modulates arousal and stress physiology. We contrasted the effects of active and passive MT experiences to examine the differential impact of rhythmic movement on the ANS and HPA axes in healthy participants. Individuals (N = 16) participated in a crossover study of 40 min of an active MT and a passive MT intervention. HRV recordings and saliva samples were collected both before and after each intervention. The high-frequency component (HF) and the ratio of low-frequency to high-frequency components (LF/HF) were calculated as cardiac markers of parasympathetic and sympathetic ANS activation, respectively. Saliva samples were analyzed for alpha-amylase and cortisol, markers of the sympathetic ANS and HPA axes, respectively. Active MT and passive MT interventions differentially modulated LF/HF, where active MT decreased LF/HF and passive MT increased LF/HF. These results indicate that MT affects the ANS and suggests that differences in engagement between active MT and passive MT lead to a differential modulation of the sympathetic ANS.

Double-blind, randomized pilot clinical trial targeting alpha oscillations with transcranial alternating current stimulation (tACS) for the treatment of major depressive disorder (MDD).

Major depressive disorder (MDD) is one of the most common psychiatric disorders, but pharmacological treatments are ineffective in a substantial fraction of patients and are accompanied by unwanted side effects. Here we evaluated the feasibility and efficacy of transcranial alternating current stimulation (tACS) at 10 Hz, which we hypothesized would improve clinical symptoms by renormalizing alpha oscillations in the left dorsolateral prefrontal cortex (dlPFC). To this end, 32 participants with MDD were randomized to 1 of 3 arms and received daily 40 min sessions of either 10 Hz-tACS, 40 Hz-tACS, or active sham stimulation for 5 consecutive days. Symptom improvement was assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS) as the primary outcome. High-density electroencephalograms (hdEEGs) were recorded to measure changes in alpha oscillations as the secondary outcome. For the primary outcome, we did not observe a significant interaction between treatment condition (10 Hz-tACS, 40 Hz-tACS, sham) and session (baseline to 4 weeks after completion of treatment); however, exploratory analyses show that 2 weeks after completion of the intervention, the 10 Hz-tACS group had more responders (MADRS and HDRS) compared with 40 Hz-tACS and sham groups (n = 30, p = 0.026). Concurrently, we found a significant reduction in alpha power over the left frontal regions in EEG after completion of the intervention for the group that received per-protocol 10 Hz-tACS (n = 26, p < 0.05). Our data suggest that targeting oscillations with tACS has potential as a therapeutic intervention for treatment of MDD.

Low-frequency direct cortical stimulation of left superior frontal gyrus enhances working memory performance.

The neural substrates of working memory are spread across prefrontal, parietal and cingulate cortices and are thought to be coordinated through low frequency cortical oscillations in the theta (3-8 Hz) and alpha (8-12 Hz) frequency bands. While the functional role of many subregions have been elucidated using neuroimaging studies, the role of superior frontal gyrus (SFG) is not yet clear. Here, we combined electrocorticography and direct cortical stimulation in three patients implanted with subdural electrodes to assess if superior frontal gyrus is indeed involved in working memory. We found left SFG exhibited task-related modulation of oscillations in the theta and alpha frequency bands specifically during the encoding epoch. Stimulation at the frequency matched to the endogenous oscillations resulted in reduced reaction times in all three participants. Our results provide evidence for SFG playing a functional role in working memory and suggest that SFG may coordinate working memory through low-frequency oscillations thus bolstering the feasibility of using intracranial electric stimulation for restoring cognitive function.

Modulating neural oscillations by transcranial static magnetic field stimulation of the dorsolateral prefrontal cortex: A crossover, double-blind, sham-controlled pilot study.

Transcranial static magnetic field stimulation (tSMS) is a novel non-invasive brain stimulation technique that has been shown to locally increase alpha power in the parietal and occipital cortex. We investigated if tSMS locally increased alpha power in the left or right prefrontal cortex, as the balance of left/right prefrontal alpha power (frontal alpha asymmetry) has been linked to emotional processing and mood disorders. Therefore, altering frontal alpha asymmetry with tSMS may serve as a novel treatment to psychiatric diseases. We performed a crossover, double-blind, sham-controlled pilot study to assess the effects of prefrontal tSMS on neural oscillations. Twenty-four right-handed healthy participants were recruited and received left dorsolateral prefrontal cortex (DLPFC) tSMS, right DLPFC tSMS, and sham tSMS in a randomized order. Electroencephalography data were collected before (2 min eyes-closed, 2 min eyes-open), during (10 min eyes-open), and after (2 min eyes-open) stimulation. In contrast with our hypothesis, neither left nor right tSMS locally increased frontal alpha power. However, alpha power increased in occipital cortex during left DLPFC tSMS. Right DLPFC tSMS increased post-stimulation fronto-parietal theta power, indicating possible relevance to memory and cognition. Left and right DLPFC tSMS increased post-stimulation left hemisphere beta power, indicating possible changes to motor behavior. Left DLPFC tSMS also increased post-stimulation right frontal beta power, demonstrating complex network effects that may be relevant to aggressive behavior. We concluded that DLPFC tSMS modulated the network oscillations in regions distant from the location of stimulation and that tSMS has region specific effects on neural oscillations.

Diffusion geometry approach to efficiently remove electrical stimulation artifacts in intracranial electroencephalography.

OBJECTIVE: Cortical oscillations, electrophysiological activity patterns, associated with cognitive functions and impaired in many psychiatric disorders can be observed in intracranial electroencephalography (iEEG). Direct cortical stimulation (DCS) may directly target these oscillations and may serve as therapeutic approaches to restore functional impairments. However, the presence of electrical stimulation artifacts in neurophysiological data limits the analysis of the effects of stimulation. Currently available methods suffer in performance in the presence of nonstationarity inherent in biological data. APPROACH: Our algorithm, shape adaptive nonlocal artifact removal (SANAR) is based on unsupervised manifold learning. By estimating the Euclidean median of k-nearest neighbors of each artifact in a nonlocal fashion, we obtain a faithful representation of the artifact which is then subtracted. This approach overcomes the challenges presented by nonstationarity. MAIN RESULTS: SANAR is effective in removing stimulation artifacts in the time domain while preserving the spectral content of the endogenous neurophysiological signal. We demonstrate the performance in a simulated dataset as well as in human iEEG data. Using two quantitative measures, that capture how much of information from endogenous activity is retained, we demonstrate that SANAR's performance exceeds that of one of the widely used approaches, independent component analysis, in the time domain as well as the frequency domain. SIGNIFICANCE: This approach allows for the analysis of iEEG data, single channel or multiple channels, during DCS, a crucial step in advancing our understanding of the effects of periodic stimulation and developing new therapies.

Targeting reduced neural oscillations in patients with schizophrenia by transcranial alternating current stimulation.

Transcranial alternating current stimulation (tACS) modulates endogenous neural oscillations in healthy human participants by the application of a low-amplitude electrical current with a periodic stimulation waveform. Yet, it is unclear if tACS can modulate and restore neural oscillations that are reduced in patients with psychiatric illnesses such as schizophrenia. Here, we asked if tACS modulates network oscillations in schizophrenia. We performed a randomized, double-blind, sham-controlled clinical trial to contrast tACS with transcranial direct current stimulation (tDCS) and sham stimulation in 22 schizophrenia patients with auditory hallucinations. We used high-density electroencephalography to investigate if a five-day, twice-daily 10Hz-tACS protocol enhances alpha oscillations and modulates network dynamics that are reduced in schizophrenia. We found that 10Hz-tACS enhanced alpha oscillations and modulated functional connectivity in the alpha frequency band. In addition, 10Hz-tACS enhanced the 40Hz auditory steady-state response (ASSR), which is reduced in patients with schizophrenia. Importantly, clinical improvement of auditory hallucinations correlated with enhancement of alpha oscillations and the 40Hz-ASSR. Together, our findings suggest that tACS has potential as a network-level approach to modulate reduced neural oscillations related to clinical symptoms in patients with schizophrenia.

Intrinsic Rhythmicity Predicts Synchronization-Continuation Entrainment Performance.

Rhythmic entrainment-defined as a stable temporal relationship between external periodic signals and endogenous rhythmic processes-allows individuals to coordinate with environmental rhythms. However, the impact of inter-individual differences on entrainment processes as a function of the tempo of external periodic signals remain poorly understood. To better understand the effects of endogenous differences and varying tempos on rhythmic entrainment, 20 young healthy adults participated in a spontaneous motor tempo (SMT) task and synchronization-continuation tasks at three experimental tempos (50, 70, and 128 bpm; 1200, 857, and 469 ms inter onset interval (IOI)). We hypothesized that SMT task performance and tempo would influence externally paced synchronization-continuation task behavior. Indeed, intrinsic rhythmicity assessed through the SMT task predicted performance in the externally paced task, allowing us to characterize differences in entrainment behavior between participants with low and high endogenous rhythmicity. High rhythmicity individuals, defined by better SMT performance, deviated from externally paced pulses sooner than individuals with low rhythmicity, who were able to maintain externally paced pulses for longer. The magnitude of these behavioral differences depended on the experimental tempo of the synchronization-continuation task. Our results indicate that differences in intrinsic rhythmicity vary between individuals and relate to tempo-dependent entrainment performance.

Randomized trial of transcranial alternating current stimulation for treatment of auditory hallucinations in schizophrenia.

BACKGROUND: Approximately 30% of patients with schizophrenia experience auditory hallucinations that are refractory to antipsychotic medications. Here, we evaluated the feasibility and efficacy of transcranial alternating current stimulation (tACS) that we hypothesized would improve auditory hallucination symptoms by enhancing synchronization between the frontal and temporo-parietal areas of the left hemisphere. METHOD: 22 participants were randomized to one of three arms and received twice daily, 20 min sessions of sham, 10 Hz 2 mA peak-to-peak tACS, or 2 mA tDCS over the course of 5 consecutive days. Symptom improvement was assessed using the Auditory Hallucination Rating Scale (AHRS) as the primary outcome measure. The Positive and Negative Syndrome Scale (PANSS) and the Brief Assessment of Cognition in Schizophrenia (BACS) were secondary outcomes. RESULTS: Primary and secondary behavioral outcomes were not significantly different between the three arms. However, effect size analyses show that tACS had the greatest effect based on the auditory hallucinations scale for the week of stimulation (1.31 for tACS; 1.06 and 0.17, for sham and tDCS, respectively). Effect size analysis for the secondary outcomes revealed heterogeneous results across measures and stimulation conditions. CONCLUSIONS: To our knowledge, this is the first clinical trial of tACS for the treatment of symptoms of a psychiatric condition. Further studies with larger sample sizes are needed to better understand the effect of tACS on auditory hallucinations.

High-density EEG characterization of brain responses to auditory rhythmic stimuli during wakefulness and NREM sleep.

Auditory rhythmic sensory stimulation modulates brain oscillations by increasing phase-locking to the temporal structure of the stimuli and by increasing the power of specific frequency bands, resulting in Auditory Steady State Responses (ASSR). The ASSR is altered in different diseases of the central nervous system such as schizophrenia. However, in order to use the ASSR as biological markers for disease states, it needs to be understood how different vigilance states and underlying brain activity affect the ASSR. Here, we compared the effects of auditory rhythmic stimuli on EEG brain activity during wake and NREM sleep, investigated the influence of the presence of dominant sleep rhythms on the ASSR, and delineated the topographical distribution of these modulations. Participants (14 healthy males, 20-33 years) completed on the same day a 60 min nap session and two 30 min wakefulness sessions (before and after the nap). During these sessions, amplitude modulated (AM) white noise auditory stimuli at different frequencies were applied. High-density EEG was continuously recorded and time-frequency analyses were performed to assess ASSR during wakefulness and NREM periods. Our analysis revealed that depending on the electrode location, stimulation frequency applied and window/frequencies analysed the ASSR was significantly modulated by sleep pressure (before and after sleep), vigilance state (wake vs. NREM sleep), and the presence of slow wave activity and sleep spindles. Furthermore, AM stimuli increased spindle activity during NREM sleep but not during wakefulness. Thus, (1) electrode location, sleep history, vigilance state and ongoing brain activity needs to be carefully considered when investigating ASSR and (2) auditory rhythmic stimuli during sleep might represent a powerful tool to boost sleep spindles.

Oscillatory Dynamics in the Frontoparietal Attention Network during Sustained Attention in the Ferret.

Sustained attention requires the coordination of neural activity across multiple cortical areas in the frontoparietal network, in particular the prefrontal cortex (PFC) and posterior parietal cortex (PPC). Previous work has demonstrated that activity in these brain regions is coordinated by neuronal oscillations of the local field potential (LFP). However, the underlying coordination of activity in terms of organization of single unit (SU) spiking activity has remained poorly understood, particularly in the freely moving animal. We found that long-range functional connectivity between anatomically connected PFC and PPC was mediated by oscillations in the theta frequency band. SU activity in PFC was phase locked to theta oscillations in PPC, and spiking activity in PFC and PPC was locked to local high-gamma activity. Together, our results support a model in which frequency-specific synchronization mediates functional connectivity between and within PFC and PPC of the frontoparietal attention network in the freely moving animal.

Feedback-Controlled Transcranial Alternating Current Stimulation Reveals a Functional Role of Sleep Spindles in Motor Memory Consolidation.

Transient episodes of brain oscillations are a common feature of both the waking and the sleeping brain. Sleep spindles represent a prominent example of a poorly understood transient brain oscillation that is impaired in disorders such as Alzheimer's disease and schizophrenia. However, the causal role of these bouts of thalamo-cortical oscillations remains unknown. Demonstrating a functional role of sleep spindles in cognitive processes has, so far, been hindered by the lack of a tool to target transient brain oscillations in real time. Here, we show, for the first time, selective enhancement of sleep spindles with non-invasive brain stimulation in humans. We developed a system that detects sleep spindles in real time and applies oscillatory stimulation. Our stimulation selectively enhanced spindle activity as determined by increased sigma activity after transcranial alternating current stimulation (tACS) application. This targeted modulation caused significant enhancement of motor memory consolidation that correlated with the stimulation-induced change in fast spindle activity. Strikingly, we found a similar correlation between motor memory and spindle characteristics during the sham night for the same spindle frequencies and electrode locations. Therefore, our results directly demonstrate a functional relationship between oscillatory spindle activity and cognition.

Feed-Forward Propagation of Temporal and Rate Information between Cortical Populations during Coherent Activation in Engineered In Vitro Networks.

Transient propagation of information across neuronal assembles is thought to underlie many cognitive processes. However, the nature of the neural code that is embedded within these transmissions remains uncertain. Much of our understanding of how information is transmitted among these assemblies has been derived from computational models. While these models have been instrumental in understanding these processes they often make simplifying assumptions about the biophysical properties of neurons that may influence the nature and properties expressed. To address this issue we created an in vitro analog of a feed-forward network composed of two small populations (also referred to as assemblies or layers) of living dissociated rat cortical neurons. The populations were separated by, and communicated through, a microelectromechanical systems (MEMS) device containing a strip of microscale tunnels. Delayed culturing of one population in the first layer followed by the second a few days later induced the unidirectional growth of axons through the microtunnels resulting in a primarily feed-forward communication between these two small neural populations. In this study we systematically manipulated the number of tunnels that connected each layer and hence, the number of axons providing communication between those populations. We then assess the effect of reducing the number of tunnels has upon the properties of between-layer communication capacity and fidelity of neural transmission among spike trains transmitted across and within layers. We show evidence based on Victor-Purpura's and van Rossum's spike train similarity metrics supporting the presence of both rate and temporal information embedded within these transmissions whose fidelity increased during communication both between and within layers when the number of tunnels are increased. We also provide evidence reinforcing the role of synchronized activity upon transmission fidelity during the spontaneous synchronized network burst events that propagated between layers and highlight the potential applications of these MEMs devices as a tool for further investigation of structure and functional dynamics among neural populations.

Modulation of Cortical Oscillations by Low-Frequency Direct Cortical Stimulation Is State-Dependent.

Cortical oscillations play a fundamental role in organizing large-scale functional brain networks. Noninvasive brain stimulation with temporally patterned waveforms such as repetitive transcranial magnetic stimulation (rTMS) and transcranial alternating current stimulation (tACS) have been proposed to modulate these oscillations. Thus, these stimulation modalities represent promising new approaches for the treatment of psychiatric illnesses in which these oscillations are impaired. However, the mechanism by which periodic brain stimulation alters endogenous oscillation dynamics is debated and appears to depend on brain state. Here, we demonstrate with a static model and a neural oscillator model that recurrent excitation in the thalamo-cortical circuit, together with recruitment of cortico-cortical connections, can explain the enhancement of oscillations by brain stimulation as a function of brain state. We then performed concurrent invasive recording and stimulation of the human cortical surface to elucidate the response of cortical oscillations to periodic stimulation and support the findings from the computational models. We found that (1) stimulation enhanced the targeted oscillation power, (2) this enhancement outlasted stimulation, and (3) the effect of stimulation depended on behavioral state. Together, our results show successful target engagement of oscillations by periodic brain stimulation and highlight the role of nonlinear interaction between endogenous network oscillations and stimulation. These mechanistic insights will contribute to the design of adaptive, more targeted stimulation paradigms.

Structure, Function, and Propagation of Information across Living Two, Four, and Eight Node Degree Topologies.

In this study, we created four network topologies composed of living cortical neurons and compared resultant structural-functional dynamics including the nature and quality of information transmission. Each living network was composed of living cortical neurons and were created using microstamping of adhesion promoting molecules and each was "designed" with different levels of convergence embedded within each structure. Networks were cultured over a grid of electrodes that permitted detailed measurements of neural activity at each node in the network. Of the topologies we tested, the "Random" networks in which neurons connect based on their own intrinsic properties transmitted information embedded within their spike trains with higher fidelity relative to any other topology we tested. Within our patterned topologies in which we explicitly manipulated structure, the effect of convergence on fidelity was dependent on both topology and time-scale (rate vs. temporal coding). A more detailed examination using tools from network analysis revealed that these changes in fidelity were also associated with a number of other structural properties including a node's degree, degree-degree correlations, path length, and clustering coefficients. Whereas information transmission was apparent among nodes with few connections, the greatest transmission fidelity was achieved among the few nodes possessing the highest number of connections (high degree nodes or putative hubs). These results provide a unique view into the relationship between structure and its affect on transmission fidelity, at least within these small neural populations with defined network topology. They also highlight the potential role of tools such as microstamp printing and microelectrode array recordings to construct and record from arbitrary network topologies to provide a new direction in which to advance the study of structure-function relationships.