Sing the mind electric - principles of deep brain stimulation

Deep Brain Stimulation beyond the Clinic: Navigating the Future of Parkinson's and Alzheimer's Disease Therapy

Deep brain stimulation (DBS) is a surgical procedure that uses electrical neuromodulation to target specific regions of the brain, showing potential in the treatment of neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD). Despite similarities in disease pathology, DBS is currently only approved for use in PD patients, with limited literature on its effectiveness in AD. While DBS has shown promise in ameliorating brain circuits in PD, further research is needed to determine the optimal parameters for DBS and address any potential side effects. This review emphasizes the need for foundational and clinical research on DBS in different brain regions to treat AD and recommends the development of a classification system for adverse effects. Furthermore, this review suggests the use of either a low-frequency system (LFS) or high-frequency system (HFS) depending on the specific symptoms of the patient for both PD and AD.

Targeting neuroplasticity in patients with neurodegenerative diseases using brain stimulation techniques

Deficits in synaptic transmission and plasticity are thought to contribute to the pathophysiology of Alzheimer’s disease (AD) and Parkinson’s disease (PD). Several brain stimulation techniques are currently available to assess or modulate human neuroplasticity, which could offer clinically useful interventions as well as quantitative diagnostic and prognostic biomarkers. In this review, we discuss several brain stimulation techniques, with a special emphasis on transcranial magnetic stimulation and deep brain stimulation (DBS), and review the results of clinical studies that applied these techniques to examine or modulate impaired neuroplasticity at the local and network levels in patients with AD or PD. The impaired neuroplasticity can be detected in patients at the earlier and later stages of both neurodegenerative diseases. However, current brain stimulation techniques, with a notable exception of DBS for PD treatment, cannot serve as adequate clinical tools to assist in the diagnosis, treatment, or prognosis of individual patients with AD or PD. Targeting the impaired neuroplasticity with improved brain stimulation techniques could offer a powerful novel approach for the treatment of AD and PD.

Neuronal inhibition and synaptic plasticity of basal ganglia neurons in Parkinson's disease

Deep brain stimulation of the subthalamic nucleus is an effective treatment for Parkinson’s disease symptoms. The therapeutic benefits of deep brain stimulation are frequency-dependent, but the underlying physiological mechanisms remain unclear. To advance deep brain stimulation therapy an understanding of fundamental mechanisms is critical. The objectives of this study were to (i) compare the frequency-dependent effects on cell firing in subthalamic nucleus and substantia nigra pars reticulata; (ii) quantify frequency-dependent effects on short-term plasticity in substantia nigra pars reticulata; and (iii) investigate effects of continuous long-train high frequency stimulation (comparable to conventional deep brain stimulation) on synaptic plasticity. Two closely spaced (600 µm) microelectrodes were advanced into the subthalamic nucleus (n = 27) and substantia nigra pars reticulata (n = 14) of 22 patients undergoing deep brain stimulation surgery for Parkinson’s disease. Cell firing and evoked field potentials were recorded with one microelectrode during stimulation trains from the adjacent microelectrode across a range of frequencies (1–100 Hz, 100 µA, 0.3 ms, 50–60 pulses). Subthalamic firing attenuated with ≥20 Hz (P < 0.01) stimulation (silenced at 100 Hz), while substantia nigra pars reticulata decreased with ≥3 Hz (P < 0.05) (silenced at 50 Hz). Substantia nigra pars reticulata also exhibited a more prominent increase in transient silent period following stimulation. Patients with longer silent periods after 100 Hz stimulation in the subthalamic nucleus tended to have better clinical outcome after deep brain stimulation. At ≥30 Hz the first evoked field potential of the stimulation train in substantia nigra pars reticulata was potentiated (P < 0.05); however, the average amplitude of the subsequent potentials was rapidly attenuated (P < 0.01). This is suggestive of synaptic facilitation followed by rapid depression. Paired pulse ratios calculated at the beginning of the train revealed that 20 Hz (P < 0.05) was the minimum frequency required to induce synaptic depression. Lastly, the average amplitude of evoked field potentials during 1 Hz pulses showed significant inhibitory synaptic potentiation after long-train high frequency stimulation (P < 0.001) and these increases were coupled with increased durations of neuronal inhibition (P < 0.01). The subthalamic nucleus exhibited a higher frequency threshold for stimulation-induced inhibition than the substantia nigra pars reticulata likely due to differing ratios of GABA:glutamate terminals on the soma and/or the nature of their GABAergic inputs (pallidal versus striatal). We suggest that enhancement of inhibitory synaptic plasticity, and frequency-dependent potentiation and depression are putative mechanisms of deep brain stimulation. Furthermore, we foresee that future closed-loop deep brain stimulation systems (with more frequent off stimulation periods) may benefit from inhibitory synaptic potentiation that occurs after high frequency stimulation.

An Invasive Method for the Activation of the Mouse Dentate Gyrus by High-frequency Stimulation

Electrical high-frequency stimulation (HFS), using implanted electrodes targeting various brain regions, has been proven as an effective treatment for various neurological and psychiatric disorders. HFS in the deep region of the brain, also named deep-brain stimulation (DBS), is becoming increasingly important in clinical trials. Recent progress in the field of high-frequency DBS (HF-DBS) surgery has begun to spread the possibility of utilizing this invasive technique to other situations, such as treatment for major depression disorder (MDD), obsessive-compulsive disorder (OCD), and so on. Despite these expanding indications, the underlying mechanisms of the beneficial effects of HF-DBS remain enigmatic. To address this question, one approach is to use implanted electrodes that sparsely activate distributed subpopulations of neurons by HFS. It has been reported that HFS in the anterior nucleus of the thalamus could be used for the treatment of refractory epilepsy in the clinic. The underlying mechanisms might be related to the increased neurogenesis and altered neuronal activity. Therefore, we are interested in exploring the physiological alterations by the detection of neuronal activity as well as neurogenesis in the mouse dentate gyrus (DG) before and after HFS treatment. In this manuscript, we describe methodologies for HFS to target the activation of the DG in mice, directly or indirectly and in an acute or chronic manner. In addition, we describe a detailed protocol for the preparation of brain slices for c-fos and Notch1 immunofluorescent staining to monitor the neuronal activity and signaling activation and for bromodeoxyuridine (BrdU) labeling to determine the neurogenesis after the HF-DBS induction. The activation of the neuronal activity and neurogenesis after the HF-DBS treatment provides direct neurobiological evidence and potential therapeutic benefits. Particularly, this methodology can be modified and applied to target other interested brain regions such as the basal ganglia and subthalamic regions for specific brain disorders in the clinic.

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep

A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states.

Uncovering the underlying mechanisms and whole-brain dynamics of deep brain stimulation for Parkinson's disease

Deep brain stimulation (DBS) for Parkinson's disease is a highly effective treatment in controlling otherwise debilitating symptoms. Yet the underlying brain mechanisms are currently not well understood. Whole-brain computational modeling was used to disclose the effects of DBS during resting-state functional Magnetic Resonance Imaging in ten patients with Parkinson's disease. Specifically, we explored the local and global impact that DBS has in creating asynchronous, stable or critical oscillatory conditions using a supercritical bifurcation model. We found that DBS shifts global brain dynamics of patients towards a Healthy regime. This effect was more pronounced in very specific brain areas such as the thalamus, globus pallidus and orbitofrontal regions of the right hemisphere (with the left hemisphere not analyzed given artifacts arising from the electrode lead). Global aspects of integration and synchronization were also rebalanced. Empirically, we found higher communicability and coherence brain measures during DBS-ON compared to DBS-OFF. Finally, using our model as a framework, artificial in silico DBS was applied to find potential alternative target areas for stimulation and whole-brain rebalancing. These results offer important insights into the underlying large-scale effects of DBS as well as in finding novel stimulation targets, which may offer a route to more efficacious treatments.

Neuromodulation interventions for addictive disorders: challenges, promise, and roadmap for future research

Addictive disorders are a major public health concern, associated with high relapse rates, significant disability and substantial mortality. Unfortunately, current interventions are only modestly effective. Preclinical studies as well as human neuroimaging studies have provided strong evidence that the observable behaviours that characterize the addiction phenotype, such as compulsive drug consumption, impaired self-control, and behavioural inflexibility, reflect underlying dysregulation and malfunction in specific neural circuits. These developments have been accompanied by advances in neuromodulation interventions, both invasive as deep brain stimulation, and non-invasive such as repetitive transcranial magnetic stimulation and transcranial direct current stimulation. These interventions appear particularly promising as they may not only allow us to probe affected brain circuits in addictive disorders, but also seem to have unique therapeutic applications to directly target and remodel impaired circuits. However, the available literature is still relatively small and sparse, and the long-term safety and efficacy of these interventions need to be confirmed. Here we review the literature on the use of neuromodulation in addictive disorders to highlight progress limitations with the aim to suggest future directions for this field.

Detecting a Cortical Fingerprint of Parkinson's Disease for Closed-Loop Neuromodulation

Recent evidence suggests that deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD) mediates its clinical effects by modulating cortical oscillatory activity, presumably via a direct cortico-subthalamic connection. This observation might pave the way for novel closed-loop approaches comprising a cortical sensor. Enhanced beta oscillations (13-35 Hz) have been linked to the pathophysiology of PD and may serve as such a candidate marker to localize a cortical area reliably modulated by DBS. However, beta-oscillations are widely distributed over the cortical surface, necessitating an additional signal source for spotting the cortical area linked to the pathologically synchronized cortico-subcortical motor network. In this context, both cortico-subthalamic coherence and cortico-muscular coherence (CMC) have been studied in PD patients. Whereas, the former requires invasive recordings, the latter allows for non-invasive detection, but displays a rather distributed cortical synchronization pattern in motor tasks. This distributed cortical representation may conflict with the goal of detecting a cortical localization with robust biomarker properties which is detectable on a single subject basis. We propose that this limitation could be overcome when recording CMC at rest. We hypothesized that-unlike healthy subjects-PD would show CMC at rest owing to the enhanced beta oscillations observed in PD. By performing source space analysis of beta CMC recorded during resting-state magnetoencephalography, we provide preliminary evidence in one patient for a cortical hot spot that is modulated most strongly by subthalamic DBS. Such a spot would provide a prominent target region either for direct neuromodulation or for placing a potential sensor in closed-loop DBS approaches, a proposal that requires investigation in a larger cohort of PD patients.

Tractography Study of Deep Brain Stimulation of the Anterior Cingulate Cortex in Chronic Pain: Key to Improve the Targeting

BACKGROUND

Deep brain stimulation (DBS) of the anterior cingulate cortex (ACC) is a new treatment for alleviating intractable neuropathic pain. However, it fails to help some patients. The large size of the ACC and the intersubject variability make it difficult to determine the optimal site to position DBS electrodes. The aim of this work was therefore to compare the ACC connectivity of patients with successful versus unsuccessful DBS outcomes to help guide future electrode placement.

METHODS

Diffusion magnetic resonance imaging (dMRI) and probabilistic tractography were performed preoperatively in 8 chronic pain patients (age 53.4 ± 6.1 years, 2 females) with ACC DBS, of whom 6 had successful (SO) and 2 unsuccessful outcomes (UOs) during a period of trialing.

RESULTS

The number of patients was too small to demonstrate any statistically significant differences. Nevertheless, we observed differences between patients with successful and unsuccessful outcomes in the fiber tract projections emanating from the volume of activated tissue around the electrodes. A strong connectivity to the precuneus area seems to predict unsuccessful outcomes in our patients (UO: 160n/SO: 27n), with (n), the number of streamlines per nonzero voxel. On the other hand, connectivity to the thalamus and brainstem through the medial forebrain bundle (MFB) was only observed in SO patients.

CONCLUSIONS

These findings could help improve presurgical planning by optimizing electrode placement, to selectively target the tracts that help to relieve patients' pain and to avoid those leading to unwanted effects.

An active method for tracking connectivity in temporally changing brain networks

The inference of connectivity in brain networks has typically been performed using passive measurements of ongoing activity across recording sites. Passive measures of connectivity are harder to interpret, however, in terms of causality - how evoked activity in one region might induce activity in another. To obviate this issue, recent work has proposed the use of active stimulation in conjunction with network estimation. By actively stimulating the network, more accurate information can be gleaned regarding evoked connectivity. The assumption in these previous works, however, was that the underlying networks were static and do not change in time. Such an assumption may be limiting in situations of clinical relevance, where the introduction of a drug or of brain pathology, might change the underlying networks structure. Here, an extension of the evoked connectivity paradigm is introduced that enables tracking networks that change in time.

Evidence from a rare case study for Hebbian-like changes in structural connectivity induced by long-term deep brain stimulation

It is unclear whether Hebbian-like learning occurs at the level of long-range white matter connections in humans, i.e., where measurable changes in structural connectivity (SC) are correlated with changes in functional connectivity. However, the behavioral changes observed after deep brain stimulation (DBS) suggest the existence of such Hebbian-like mechanisms occurring at the structural level with functional consequences. In this rare case study, we obtained the full network of white matter connections of one patient with Parkinson’s disease (PD) before and after long-term DBS and combined it with a computational model of ongoing activity to investigate the effects of DBS-induced long-term structural changes. The results show that the long-term effects of DBS on resting-state functional connectivity is best obtained in the computational model by changing the structural weights from the subthalamic nucleus (STN) to the putamen and the thalamus in a Hebbian-like manner. Moreover, long-term DBS also significantly changed the SC towards normality in terms of model-based measures of segregation and integration of information processing, two key concepts of brain organization. This novel approach using computational models to model the effects of Hebbian-like changes in SC allowed us to causally identify the possible underlying neural mechanisms of long-term DBS using rare case study data. In time, this could help predict the efficacy of individual DBS targeting and identify novel DBS targets.

Role of radiology in central nervous system stimulation

Central nervous system (CNS) stimulation is becoming increasingly prevalent. Deep brain stimulation (DBS) has been proven to be an invaluable treatment for movement disorders and is also useful in many other neurological conditions refractory to medical treatment, such as chronic pain and epilepsy. Neuroimaging plays an important role in operative planning, target localization and post-operative follow-up. The use of imaging in determining the underlying mechanisms of DBS is increasing, and the dependence on imaging is likely to expand as deep brain targeting becomes more refined. This article will address the expanding role of radiology and highlight issues, including MRI safety concerns, that radiologists may encounter when confronted with a patient with CNS stimulation equipment in situ.

Electrical stimuli in the central nervous system microenvironment

Electrical stimulation to manipulate the central nervous system (CNS) has been applied as early as the 1750s to produce visual sensations of light. Deep brain stimulation (DBS), cochlear implants, visual prosthetics, and functional electrical stimulation (FES) are being applied in the clinic to treat a wide array of neurological diseases, disorders, and injuries. This review describes the history of electrical stimulation of the CNS microenvironment; recent advances in electrical stimulation of the CNS, including DBS to treat essential tremor, Parkinson's disease, and depression; FES for the treatment of spinal cord injuries; and alternative electrical devices to restore vision and hearing via neuroprosthetics (retinal and cochlear implants). It also discusses the role of electrical cues during development and following injury and, importantly, manipulation of these endogenous cues to support regeneration of neural tissue.

A critical reflection on the technological development of deep brain stimulation (DBS)

Since the translational research findings of Benabid and colleagues which partly led to their seminal paper regarding the treatment of mainly tremor-dominant Parkinson patients through thalamic high-frequency-stimulation (HFS) in 1987, we still struggle with identifying a satisfactory mechanistic explanation of the underlying principles of deep brain stimulation (DBS). Furthermore, the technological advance of DBS devices (electrodes and implantable pulse generators, IPG’s) has shown a distinct lack of dynamic progression. In light of this we argue that it is time to leave the paleolithic age and enter hellenistic times: the device-manufacturing industry and the medical community together should put more emphasis on advancing the technology rather than resting on their laurels.

Neural plasticity in human brain connectivity: the effects of long term deep brain stimulation of the subthalamic nucleus in Parkinson's disease

BACKGROUND

Positive clinical outcomes are now well established for deep brain stimulation, but little is known about the effects of long-term deep brain stimulation on brain structural and functional connectivity. Here, we used the rare opportunity to acquire pre- and postoperative diffusion tensor imaging in a patient undergoing deep brain stimulation in bilateral subthalamic nuclei for Parkinson's Disease. This allowed us to analyse the differences in structural connectivity before and after deep brain stimulation. Further, a computational model of spontaneous brain activity was used to estimate the changes in functional connectivity arising from the specific changes in structural connectivity.

RESULTS

We found significant localised structural changes as a result of long-term deep brain stimulation. These changes were found in sensory-motor, prefrontal/limbic, and olfactory brain regions which are known to be affected in Parkinson's Disease. The nature of these changes was an increase of nodal efficiency in most areas and a decrease of nodal efficiency in the precentral sensory-motor area. Importantly, the computational model clearly shows the impact of deep brain stimulation-induced structural alterations on functional brain changes, which is to shift the neural dynamics back towards a healthy regime. The results demonstrate that deep brain stimulation in Parkinson's Disease leads to a topological reorganisation towards healthy bifurcation of the functional networks measured in controls, which suggests a potential neural mechanism for the alleviation of symptoms.

CONCLUSIONS

The findings suggest that long-term deep brain stimulation has not only restorative effects on the structural connectivity, but also affects the functional connectivity at a global level. Overall, our results support causal changes in human neural plasticity after long-term deep brain stimulation and may help to identify the underlying mechanisms of deep brain stimulation.

Biodegradable electroactive polymers for electrochemically-triggered drug delivery

We report biodegradable electroactive polymer (EAP)-based materials and their application as drug delivery devices.

The emergence of two anti-phase oscillatory neural populations in a computational model of the Parkinsonian globus pallidus

Experiments in rodent models of Parkinson's disease have demonstrated a prominent increase of oscillatory firing patterns in neurons within the Parkinsonian globus pallidus (GP) which may underlie some of the motor symptoms of the disease. There are two main pathways from the cortex to GP: via the striatum and via the subthalamic nucleus (STN), but it is not known how these inputs sculpt the pathological pallidal firing patterns. To study this we developed a novel neural network model of conductance-based spiking pallidal neurons with cortex-modulated input from STN neurons. Our results support the hypothesis that entrainment occurs primarily via the subthalamic pathway. We find that as a result of the interplay between excitatory input from the STN and mutual inhibitory coupling between GP neurons, a homogeneous population of GP neurons demonstrates a self-organizing dynamical behavior where two groups of neurons emerge: one spiking in-phase with the cortical rhythm and the other in anti-phase. This finding mirrors what is seen in recordings from the GP of rodents that have had Parkinsonism induced via brain lesions. Our model also includes downregulation of Hyperpolarization-activated Cyclic Nucleotide-gated (HCN) channels in response to burst firing of GP neurons, since this has been suggested as a possible mechanism for the emergence of Parkinsonian activity. We found that the downregulation of HCN channels provides even better correspondence with experimental data but that it is not essential in order for the two groups of oscillatory neurons to appear. We discuss how the influence of inhibitory striatal input will strengthen our results.

Deep brain stimulation (DBS) at the interface of neurology and psychiatry

Deep brain stimulation (DBS) is an emerging interventional therapy for well-screened patients with specific treatment-resistant neuropsychiatric diseases. Some neuropsychiatric conditions, such as Parkinson disease, have available and reasonable guideline and efficacy data, while other conditions, such as major depressive disorder and Tourette syndrome, have more limited, but promising results. This review summarizes both the efficacy and the neuroanatomical targets for DBS in four common neuropsychiatric conditions: Parkinson disease, Tourette syndrome, major depressive disorder, and obsessive-compulsive disorder. Based on emerging new research, we summarize novel approaches to optimization of stimulation for each neuropsychiatric disease and we review the potential positive and negative effects that may be observed following DBS. Finally, we summarize the likely future innovations in the field of electrical neural-network modulation.

Future of brain stimulation: new targets, new indications, new technology

In the last quarter of a century, DBS has become an established neurosurgical treatment for Parkinson's disease (PD), dystonia, and tremors. Improved understanding of brain circuitries and their involvement in various neurological and psychiatric illnesses, coupled with the safety of DBS and its exquisite role as a tool for ethical study of the human brain, have unlocked new opportunities for this technology, both for future therapies and in research. Serendipitous discoveries and advances in structural and functional imaging are providing abundant "new" brain targets for an ever-increasing number of pathologies, leading to investigations of DBS in diverse neurological, psychiatric, behavioral, and cognitive conditions. Trials and "proof of concept" studies of DBS are underway in pain, epilepsy, tinnitus, OCD, depression, and Gilles de la Tourette syndrome, as well as in eating disorders, addiction, cognitive decline, consciousness, and autonomic states. In parallel, ongoing technological development will provide pulse generators with longer battery longevity, segmental electrode designs allowing a current steering, and the possibility to deliver "on-demand" stimulation based on closed-loop concepts. The future of brain stimulation is certainly promising, especially for movement disorders-that will remain the main indication for DBS for the foreseeable future-and probably for some psychiatric disorders. However, brain stimulation as a technique may be at risk of gliding down a slippery slope: Some reports indicate a disturbing trend with suggestions that future DBS may be proposed for enhancement of memory in healthy people, or as a tool for "treatment" of "antisocial behavior" and for improving "morality."

More than meets the eye-myelinated axons crowd the subthalamic nucleus

High frequency deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a successful treatment for patients with advanced Parkinson's disease (PD). Although its exact mechanism of action is unknown, it is currently believed that the beneficial effects of the stimulation are mediated either by alleviating pathological basal ganglia output patterns of activity or by activation of the axons of passage that arise from the cerebral cortex and other sources. In this study, we show that the anatomical composition of the primate STN provides a substrate through which DBS may elicit widespread changes in brain activity via stimulation of fibers of passage. Using quantitative high-resolution electron microscopy, we found that the primate STN is traversed by numerous myelinated axons, which occupy as much as 45% of its sensorimotor territory and 36% of its associative region. In comparison, myelinated axons occupy only 27% of the surface areas of the sensorimotor and associative regions of the internal segment of the globus pallidus (GPi), another target for therapeutic DBS in PD. We also noted that myelinated axons in the STN, on average, have a larger diameter than those in GPi, which may render them more susceptible to electrical stimulation. Because axons are more excitable than other neuronal elements, our findings support the hypothesis that STN DBS, even when carried out entirely within the confines of the nucleus, mediates some of its effects by activating myelinated axons of passage.

Suppression of epileptiform activity by a single short-duration electric field in rat hippocampus in vitro

The mechanisms behind the therapeutic effects of electrical stimulation of the brain in epilepsy and other disorders are poorly understood. Previous studies in vitro have shown that uniform electric fields can suppress epileptiform activity through a direct polarizing effect on neuronal membranes. Such an effect depends on continuous DC stimulation with unbalanced charge. Here we describe a suppressive effect of a brief (10 ms) DC field on stimulus-evoked epileptiform activity in rat hippocampal brain slices exposed to Cs+ (3.5 mM). This effect was independent of field polarity, was uncorrelated to changes in synchronized population activity, and persisted during blockade of synaptic transmission with Cd2+ (500 μM). Antagonists of A1, P2X, or P2Y receptors were without effect. The suppressive effect depended on the alignment of the external field with the somato-dendritic axis of CA1 pyramidal cells; however, temporal coincidence with the epileptiform activity was not essential, as suppression was detectable for up to 1 s after the field. Pyramidal cells, recorded during epileptiform activity, showed decreased discharge duration and truncation of depolarizing plateau potentials in response to field application. In the absence of hyperactivity, the applied field was followed by slow membrane potential changes, accompanied by decreased input resistance and attenuation of the depolarizing afterpotential following action potentials. These effects recovered over a 1-s period. The study suggests that a brief electric field induces a prolonged suppression of epileptiform activity, which can be related to changes in neuronal membrane properties, including attenuation of signals depending on the persisting Na+ current.

Behavioral and neurobiological effects of deep brain stimulation in a mouse model of high anxiety- and depression-like behavior

Increasing evidence suggests that high-frequency deep brain stimulation of the nucleus accumbens (NAcb-DBS) may represent a novel therapeutic strategy for individuals suffering from treatment-resistant depression, although the underlying mechanisms of action remain largely unknown. In this study, using a unique mouse model of enhanced depression- and anxiety-like behavior (HAB), we investigated behavioral and neurobiological effects of NAcb-DBS. HAB mice either underwent chronic treatment with one of three different selective serotonin reuptake inhibitors (SSRIs) or received NAcb-DBS for 1 h per day for 7 consecutive days. Animals were tested in established paradigms revealing depression- and anxiety-related behaviors. The enhanced depression-like behavior of HAB mice was not influenced by chronic SSRI treatment. In contrast, repeated, but not single, NAcb-DBS induced robust antidepressant and anxiolytic responses in HAB animals, while these behaviors remained unaffected in normal depression/anxiety animals (NAB), suggesting a preferential effect of NAcb-DBS on pathophysiologically deranged systems. NAcb-DBS caused a modulation of challenge-induced activity in various stress- and depression-related brain regions, including an increase in c-Fos expression in the dentate gyrus of the hippocampus and enhanced hippocampal neurogenesis in HABs. Taken together, these findings show that the normalization of the pathophysiologically enhanced, SSRI-insensitive depression-like behavior by repeated NAcb-DBS was associated with the reversal of reported aberrant brain activity and impaired adult neurogenesis in HAB mice, indicating that NAcb-DBS affects neuronal activity as well as plasticity in a defined, mood-associated network. Thus, HAB mice may represent a clinically relevant model for elucidating the neurobiological correlates of NAcb-DBS.

From prediction error to incentive salience: mesolimbic computation of reward motivation

Reward contains separable psychological components of learning, incentive motivation and pleasure. Most computational models have focused only on the learning component of reward, but the motivational component is equally important in reward circuitry, and even more directly controls behavior. Modeling the motivational component requires recognition of additional control factors besides learning. Here I discuss how mesocorticolimbic mechanisms generate the motivation component of incentive salience. Incentive salience takes Pavlovian learning and memory as one input and as an equally important input takes neurobiological state factors (e.g. drug states, appetite states, satiety states) that can vary independently of learning. Neurobiological state changes can produce unlearned fluctuations or even reversals in the ability of a previously learned reward cue to trigger motivation. Such fluctuations in cue-triggered motivation can dramatically depart from all previously learned values about the associated reward outcome. Thus, one consequence of the difference between incentive salience and learning can be to decouple cue-triggered motivation of the moment from previously learned values of how good the associated reward has been in the past. Another consequence can be to produce irrationally strong motivation urges that are not justified by any memories of previous reward values (and without distorting associative predictions of future reward value). Such irrationally strong motivation may be especially problematic in addiction. To understand these phenomena, future models of mesocorticolimbic reward function should address the neurobiological state factors that participate to control generation of incentive salience.

Inferring evoked brain connectivity through adaptive perturbation

Inference of functional networks-representing the statistical associations between time series recorded from multiple sensors-has found important applications in neuroscience. However, networksexhibiting time-locked activity between physically independent elements can bias functional connectivity estimates employing passive measurements. Here, a perturbative and adaptive method of inferring network connectivity based on measurement and stimulation-so called "evoked network connectivity" is introduced. This procedure, employing a recursive Bayesian update scheme, allows principled network stimulation given a current network estimate inferred from all previous stimulations and recordings. The method decouples stimulus and detector design from network inference and can be suitably applied to a wide range of clinical and basic neuroscience related problems. The proposed method demonstrates improved accuracy compared to network inference based on passive observation of node dynamics and an increased rate of convergence relative to network estimation employing a naïve stimulation strategy.

MEG can map short and long-term changes in brain activity following deep brain stimulation for chronic pain

Deep brain stimulation (DBS) has been shown to be clinically effective for some forms of treatment-resistant chronic pain, but the precise mechanisms of action are not well understood. Here, we present an analysis of magnetoencephalography (MEG) data from a patient with whole-body chronic pain, in order to investigate changes in neural activity induced by DBS for pain relief over both short- and long-term. This patient is one of the few cases treated using DBS of the anterior cingulate cortex (ACC). We demonstrate that a novel method, null-beamforming, can be used to localise accurately brain activity despite the artefacts caused by the presence of DBS electrodes and stimulus pulses. The accuracy of our source localisation was verified by correlating the predicted DBS electrode positions with their actual positions. Using this beamforming method, we examined changes in whole-brain activity comparing pain relief achieved with deep brain stimulation (DBS ON) and compared with pain experienced with no stimulation (DBS OFF). We found significant changes in activity in pain-related regions including the pre-supplementary motor area, brainstem (periaqueductal gray) and dissociable parts of caudal and rostral ACC. In particular, when the patient reported experiencing pain, there was increased activity in different regions of ACC compared to when he experienced pain relief. We were also able to demonstrate long-term functional brain changes as a result of continuous DBS over one year, leading to specific changes in the activity in dissociable regions of caudal and rostral ACC. These results broaden our understanding of the underlying mechanisms of DBS in the human brain.

Deep brain stimulation in addiction: a review of potential brain targets

Deep brain stimulation (DBS) is an adjustable, reversible, non-destructive neurosurgical intervention using implanted electrodes to deliver electrical pulses to areas in the brain. DBS is currently investigated in psychiatry for the treatment of refractory obsessive-compulsive disorder, Tourette syndrome and depressive disorder. Although recent research in both animals and humans has indicated that DBS may be an effective intervention for patients with treatment-refractory addiction, it is not yet entirely clear which brain areas should be targeted. The objective of this review is to provide a systematic overview of the published literature on DBS and addiction and outline the most promising target areas using efficacy and adverse event data from both preclinical and clinical studies. We found 7 animal studies targeting six different brain areas: nucleus accumbens (NAc), subthalamic nucleus (STN), dorsal striatum, lateral habenula, medial prefrontal cortex (mPFC) and hypothalamus, and 11 human studies targeting two different target areas: NAc and STN. Our analysis of the literature suggests that the NAc is currently the most promising DBS target area for patients with treatment-refractory addiction. The mPFC is another promising target, but needs further exploration to establish its suitability for clinical purposes. We conclude the review with a discussion on translational issues in DBS research, medical ethical considerations and recommendations for clinical trials with DBS in patients with addiction.

"Connectomic surgery": diffusion tensor imaging (DTI) tractography as a targeting modality for surgical modulation of neural networks

Deep brain stimulation (DBS) is being used to treat a growing number of neurological disorders. Until recently, DBS has been thought to act mainly by suppressing local neuronal activity, essentially producing a functional lesion. Numerous studies are now demonstrating that DBS has widespread network effects mediated by white matter pathways. The new science of connectomics aims to map the connectivity between brain regions in health and disease. Targeting DBS specifically to pathways which exhibit pathological connectivity could greatly expand the possibilities for treating brain diseases. This brief review examines the current state of brain imaging for visualization of these networks and describes how DBS might be used to restore normal connectivity in pathological states.

Deep brain stimulation of the forniceal area enhances memory functions in experimental dementia: the role of stimulation parameters

Deep brain stimulation (DBS) is currently being evaluated as a potential therapy in improving memory functions in Alzheimer's disease. The target for DBS and the stimulation parameters to be used are unknown. Here, we implanted bilateral electrodes in the vicinity of the fornix, a key element of the memory circuitry, and applied DBS with different stimulation frequencies and amplitudes in an experimental model of dementia. Rats received scopolamine, a muscarinic acetylcholine receptor antagonist, to mimic memory impairment. Rats were then tested in the object location task with the following conditions: (i) with attachment of stimulation cable (off stimulation), and (ii) with DBS at various amplitudes (50 μA, 100 μA and 200 μA), 100 μs pulse width and 100 Hz or 10 Hz stimulation frequency. DBS reversed the memory impairing effects of scopolamine when compared to sham rats. We found that the fornix is not sensitive to the frequency of stimulation, but rather to current levels. With the most optimal stimulation parameter, we found no side-effects on anxiety levels and general motor activity. These findings identify the fornix as a key region in controlling spatial memory functions. DBS of this region, using tailored stimulation parameters, has the potential to improve memory functions in conditions characterised by memory impairment.

Yoga lessons for consciousness research: a paralimbic network balancing brain resource allocation

Consciousness has been proposed to play a key role in shaping flexible learning and as such is thought to confer an evolutionary advantage. Attention and awareness are the perhaps most important underlying processes, yet their precise relationship is presently unclear. Both of these processes must, however, serve the evolutionary imperatives of survival and procreation. They are thus intimately bound by reward and emotion to help to prioritize efficient brain resource allocation in order to predict and optimize behavior. Here we show how this process is served by a paralimbic network consisting primarily of regions located on the midline of the human brain. Using many different techniques, experiments have demonstrated that this network is effective and specific for self-awareness and contributes to the sense of unity of consciousness by acting as a common neural path for a wide variety of conscious experiences. Interestingly, hemodynamic activity in the network decreases with focusing on external stimuli, which has led to the idea of a default mode network. This network is one of many networks that wax and vane as resources are allocated to accommodate the different cyclical needs of the organism primarily related to the fundamental pleasures afforded by evolution: food, sex, and conspecifics. Here we hypothesize, however, that the paralimbic network serves a crucial role in balancing and regulating brain resource allocation, and discuss how it can be thought of as a link between current theories of so-called “default mode,” “resting state networks,” and “global workspace.” We show how major developmental disorders of self-awareness and self-control can arise from problems in the paralimbic network as demonstrated here by the example of Asperger syndrome. We conclude that attention, awareness, and emotion are integrated by a paralimbic network that helps to efficiently allocate brain resources to optimize behavior and help survival.

Balancing the brain: resting state networks and deep brain stimulation

Over the last three decades, large numbers of patients with otherwise treatment-resistant disorders have been helped by deep brain stimulation (DBS), yet a full scientific understanding of the underlying neural mechanisms is still missing. We have previously proposed that efficacious DBS works by restoring the balance of the brain's resting state networks. Here, we extend this proposal by reviewing how detailed investigations of the highly coherent functional and structural brain networks in health and disease (such as Parkinson's) have the potential not only to increase our understanding of fundamental brain function but of how best to modulate the balance. In particular, some of the newly identified hubs and connectors within and between resting state networks could become important new targets for DBS, including potentially in neuropsychiatric disorders. At the same time, it is of essence to consider the ethical implications of this perspective.

Optimizing a rodent model of Parkinson's disease for exploring the effects and mechanisms of deep brain stimulation

Deep brain stimulation (DBS) has become a treatment for a growing number of neurological and psychiatric disorders, especially for therapy-refractory Parkinson's disease (PD). However, not all of the symptoms of PD are sufficiently improved in all patients, and side effects may occur. Further progress depends on a deeper insight into the mechanisms of action of DBS in the context of disturbed brain circuits. For this, optimized animal models have to be developed. We review not only charge transfer mechanisms at the electrode/tissue interface and strategies to increase the stimulation's energy-efficiency but also the electrochemical, electrophysiological, biochemical and functional effects of DBS. We introduce a hemi-Parkinsonian rat model for long-term experiments with chronically instrumented rats carrying a backpack stimulator and implanted platinum/iridium electrodes. This model is suitable for (1) elucidating the electrochemical processes at the electrode/tissue interface, (2) analyzing the molecular, cellular and behavioral stimulation effects, (3) testing new target regions for DBS, (4) screening for potential neuroprotective DBS effects, and (5) improving the efficacy and safety of the method. An outlook is given on further developments of experimental DBS, including the use of transgenic animals and the testing of closed-loop systems for the direct on-demand application of electric stimulation.

Building a neuroscience of pleasure and well-being

BACKGROUND: How is happiness generated via brain function in lucky individuals who have the good fortune to be happy? Conceptually, well-being or happiness has long been viewed as requiring at least two crucial ingredients: positive affect or pleasure (hedonia) and a sense of meaningfulness or engagement in life (eudaimonia). Science has recently made progress in relating hedonic pleasure to brain function, and so here we survey new insights into how brains generate the hedonic ingredient of sustained or frequent pleasure. We also briefly discuss how brains might connect hedonia states of pleasure to eudaimonia assessments of meaningfulness, and so create balanced states of positive well-being. RESULTS: Notable progress has been made in understanding brain bases of hedonic processing, producing insights into that brain systems that cause and/or code sensory pleasures. Progress has been facilitated by the recognition that hedonic brain mechanisms are largely shared between humans and other mammals, allowing application of conclusions from animal studies to a better understanding of human pleasures. In the past few years, evidence has also grown to indicate that for humans, brain mechanisms of higher abstract pleasures strongly overlap with more basic sensory pleasures. This overlap may provide a window into underlying brain circuitry that generates all pleasures, including even the hedonic quality of pervasive well-being that detaches from any particular sensation to apply to daily life in a more sustained or frequent fashion. CONCLUSIONS: Hedonic insights are applied to understanding human well-being here. Our strategy combines new findings on brain mediators that generate the pleasure of sensations with evidence that human brains use many of the same hedonic circuits from sensory pleasures to create the higher pleasures. This in turn may be linked to how hedonic systems interact with other brain systems relevant to self-understanding and the meaning components of eudaimonic happiness. Finally, we speculate a bit about how brains that generate hedonia states might link to eudaimonia assessments to create properly balanced states of positive well-being that approach true happiness.