Faculty Bibliography

OBJECTIVE Since the first clinical application of the incisionless magnetic resonance-guided focused ultrasound (MRgFUS) technology only small series of patients have been reported, and thus only extrapolations of the procedure-related risks could be offered. In this study, the authors analyze side-effects and targeting accuracy in 180 consecutive treatments with MRgFUS for chronic therapy-resistant idiopathic Parkinson's disease (PD), essential tremor (ET), cerebellar tremor (CT), and neuropathic pain (NP), all performed in their dedicated center. METHODS A total of 180 treatments with MRgFUS for chronic therapy-resistant idiopathic PD, ET, CT, and NP were prospectively assessed for side-effects and targeting accuracy. Monitoring for later side-effects was continued for at least 3 months after the procedure in all but 1 case (0.6%); in that single case, the patient was lost to follow-up after an uneventful early postoperative course. The surgical targets were the pallidothalamic tract (pallidothalamic tractotomy, n = 105), the cerebellothalamic tract (cerebellothalamic tractotomy, n = 50), the central lateral nucleus (central lateral thalamotomy, n = 84), the centrum medianum (centrum medianum thalamotomy, n = 12), and the globus pallidus (pallidotomy, n = 2). Cognitive testing was performed before, 1-2 days after, and 1 year after the procedure. The Mini-Mental State Examination (MMSE) was used for the first 29 cases and was then replaced by the Montreal Cognitive Assessment (MoCA). Lesion reconstruction and measurement of targeting accuracy were done on 2-day posttreatment MR images for each performed target. To determine targeting accuracy measurement, 234 out of the 253 lesions depicted in the 2-day postoperative MR examination could be 3D-reconstructed. RESULTS The mean MoCA score was slightly improved 2 days postoperatively (p = 0.002) and remained stable at 1-year follow-up (p = 0.03). The mean MMSE score was also slightly improved 2 days postoperatively and at 1-year follow-up, but the improvement was not statistically significant (p = 0.06 and p = 0.2, respectively). The mean (± SD) accuracy was 0.32 ± 0.29 mm, 0.29 ± 0.28 mm, and 0.44 ± 0.39 mm for the mediolateral, anteroposterior, and dorsoventral dimensions, respectively. The mean 3D accuracy was 0.73 ± 0.39 mm. As to side-effects, 14 events over 180 treatments were documented. They were classified into procedure-related (n = 4, 2.2%), effect on neighboring structures (n = 3, 1.7%), and disease-related (n = 7, 3.9%). There was no bleeding. CONCLUSIONS The incisionless transcranial MRgFUS technology demonstrates a higher targeting accuracy and a lower side-effect profile than techniques requiring cerebral penetration. In the absence of penetration brain shift, this technique avoids the placement of a thermolesion away from the chosen target, thus suppressing the need for reversible therapeutic energy application. With the use of proper physiopathology-based targets, definitive therapeutic effects can be coupled with sparing of sensory, motor, and paralimbic/multimodal thalamocortical functions. Clinical efficacy, not analyzed in this investigation, will ultimately rest in proper target selection and optimized thermolesional coverage of the target.

Acute pain evokes protective neural and behavioral responses. Chronic pain, however, disrupts normal nociceptive processing. The prefrontal cortex (PFC) is known to exert top-down regulation of sensory inputs; unfortunately, how individual PFC neurons respond to an acute pain signal is not well characterized. We found that neurons in the prelimbic region of the PFC increased firing rates of the neurons after noxious stimulations in free-moving rats. Chronic pain, however, suppressed both basal spontaneous and pain-evoked firing rates. Furthermore, we identified a linear correlation between basal and evoked firing rates of PFC neurons, whereby a decrease in basal firing leads to a nearly 2-fold reduction in pain-evoked response in chronic pain states. In contrast, enhancing basal PFC activity with low-frequency optogenetic stimulation scaled up prefrontal outputs to inhibit pain. These results demonstrate a cortical gain control system for nociceptive regulation and establish scaling up prefrontal outputs as an effective neuromodulation strategy to inhibit pain.

High-throughput electron microscopy has started to reveal synaptic connectivity maps of single circuits and whole brain regions, for example, in the Drosophila olfactory system. However, efficacy, timing, and frequency tuning of synaptic vesicle release are also highly diversified across brain synapses. These features critically depend on the nanometer-scale coupling distance between voltage-gated Ca²⁺ channels (VGCCs) and the synaptic vesicle release machinery. Combining light super resolution microscopy with in vivo electrophysiology, we show here that two orthogonal scaffold proteins (ELKS family Bruchpilot, BRP, and Syd-1) cluster-specific (M)Unc13 release factor isoforms either close (BRP/Unc13A) or further away (Syd-1/Unc13B) from VGCCs across synapses of the Drosophila olfactory system, resulting in different synapse-characteristic forms of short-term plasticity. Moreover, BRP/Unc13A versus Syd-1/Unc13B ratios were different between synapse types. Thus, variation in tightly versus loosely coupled scaffold protein/(M)Unc13 modules can tune synapse-type-specific release features, and "nanoscopic molecular fingerprints" might identify synapses with specific temporal features.

BACKGROUND:The choice for drugs over alternative reinforcers is a translational hallmark feature of drug addiction. The neural basis of such drug-biased choice is not well understood, particularly in individuals with protracted drug abstinence who cannot ethically participate in studies that offer drug-using opportunities. METHODS:We developed a functional magnetic resonance imaging drug-choice task to examine the choice for viewing drug-related images, rather than for actually consuming a drug. Actively using (n = 18) and abstaining (n = 19) individuals with a history of cocaine use disorder (CUD: dependence or abuse) and matched healthy control subjects (n = 26) participated. RESULTS:Individuals with CUD, especially those actively using cocaine outside the laboratory, made more choices than control subjects to view images depicting cocaine (especially when directly compared against images depicting an alternative appetitive reinforcer [food]). Functional magnetic resonance imaging data revealed that in individuals with CUD, the act of making drug-related choices engaged brain regions implicated in choice difficulty or ambivalence (i.e., dorsal anterior cingulate cortex, which was higher in all individuals with CUD than control subjects). Drug-related choices in CUD also engaged brain regions implicated in reward (e.g., midbrain/ventral tegmental area, which was most activated in active users, although this region was not hypothesized a priori). CONCLUSIONS:These results help clarify the neural mechanisms underlying drug-biased choice in human addiction, which, beyond mechanisms involved in value assignment or reward, may critically involve mechanisms that contribute to resolving difficult decisions. Future studies are needed to validate these behavioral and neural abnormalities as markers of drug seeking and relapse in treatment contexts.

Multiple system atrophy (MSA) may be difficult to distinguish clinically from other disorders, particularly in the early stages of the disease. An autonomic-only presentation can be indistinguishable from pure autonomic failure. Patients presenting with parkinsonism may be misdiagnosed as having Parkinson disease. Patients presenting with the cerebellar phenotype of MSA can mimic other adult-onset ataxias due to alcohol, chemotherapeutic agents, lead, lithium, and toluene, or vitamin E deficiency, as well as paraneoplastic, autoimmune, or genetic ataxias. A careful medical history and meticulous neurological examination remain the cornerstone for the accurate diagnosis of MSA. Ancillary investigations are helpful to support the diagnosis, rule out potential mimics, and define therapeutic strategies. This review summarizes diagnostic investigations useful in the differential diagnosis of patients with suspected MSA. Currently used techniques include structural and functional brain imaging, cardiac sympathetic imaging, cardiovascular autonomic testing, olfactory testing, sleep study, urological evaluation, and dysphagia and cognitive assessments. Despite advances in the diagnostic tools for MSA in recent years and the availability of consensus criteria for clinical diagnosis, the diagnostic accuracy of MSA remains sub-optimal. As other diagnostic tools emerge, including skin biopsy, retinal biomarkers, blood and cerebrospinal fluid biomarkers, and advanced genetic testing, a more accurate and earlier recognition of MSA should be possible, even in the prodromal stages. This has important implications as misdiagnosis can result in inappropriate treatment, patient and family distress, and erroneous eligibility for clinical trials of disease-modifying drugs.

In recent years, two-photon calcium imaging has become a standard tool to probe the function of neural circuits and to study computations in neuronal populations. However, the acquired signal is only an indirect measurement of neural activity due to the comparatively slow dynamics of fluorescent calcium indicators. Different algorithms for estimating spike rates from noisy calcium measurements have been proposed in the past, but it is an open question how far performance can be improved. Here, we report the results of the spikefinder challenge, launched to catalyze the development of new spike rate inference algorithms through crowd-sourcing. We present ten of the submitted algorithms which show improved performance compared to previously evaluated methods. Interestingly, the top-performing algorithms are based on a wide range of principles from deep neural networks to generative models, yet provide highly correlated estimates of the neural activity. The competition shows that benchmark challenges can drive algorithmic developments in neuroscience.