Cortical gray and subcortical white matter associations in Parkinson's disease

Cortical atrophy has been documented in both Parkinson’s disease (PD) and healthy aging, but its relationship to changes in subcortical white matter is unknown. This was investigated by obtaining T1- and diffusion-weighted images from 76 PD and 70 controls at baseline, 18-, and 36-months, from which cortical volumes and underlying subcortical white matter axial (AD), radial (RD) diffusivities, and fractional anisotropy (FA) were determined. Twelve of 69 cortical subregions had significant group differences, and for these underlying subcortical white matter was explored. At baseline, higher cortical volumes were significantly correlated with lower underlying subcortical white matter AD, RD, and higher FA (Ps ≤0.017) in PD. Longitudinally, higher rates of cortical atrophy in PD were associated with increased rates of change in AD RD, and FA values (Ps ≤ 0.0013) in two subregions explored. The significant gray-white matter associations were not found in controls. Thus, unlike healthy aging, cortical atrophy and subcortical white matter changes may not be independent events in PD

Stage-dependent loss of cortical gyrification as Parkinson disease “unfolds”

Nigrostriatal terminal losses are known to progress most rapidly in early-stage Parkinson disease (PD) and then plateau, whereas cortical pathology continues and may provide a better marker of PD progression in later stages. We investigated cortical gyrification indices in patients with different durations of PD, since cortical folding may capture complex processes involving transverse forces of neuronal sheets or underlying axonal connectivity. Longitudinal cohort structural MRI were obtained at baseline, 18 months, and 36 months from 70 patients with PD without dementia and 70 control participants. Cortical local gyrification index (LGI) was compared between controls and PD subgroups based upon duration of illness (DOI, 5 years [PDL, n = 24]) and adjusted using false discovery rate. Associations between LGI and clinical measurements were assessed using multiple linear regression. Areas having significantly reduced LGI also were analyzed using baseline data from a newly established cohort (PD n = 87, control n = 66) to validate our findings. In the longitudinal cohort, PDL had significantly reduced overall gyrification, and bilaterally in the inferior parietal, postcentral, precentral, superior frontal, and supramarginal areas, compared to controls (p < 0.05). Longitudinally, loss of gyrification was accelerated in PDM participants, compared to controls. LGI showed robust correlations with DOI and also was correlated with PD-related clinical measurements. Similar results were obtained in the validation sample. Loss of cortical gyrification may be accelerated within the first few years after PD diagnosis, and become particularly prominent in later stages. Thus, it may provide a metric for monitoring progression in vivo

The pattern of gray matter atrophy in Parkinson’s disease differs in cortical and subcortical regions

Cortical and subcortical gray matter (GM) atrophy may progress differently during the course of Parkinson's disease (PD). We delineated and compared the longitudinal pattern of these PD-related changes

Striatal shape in Parkinson's disease

Parkinson’s disease (PD) is marked pathologically by nigrostriatal dopaminergic terminal loss. Histopathological and in vivo labeling studies demonstrate that this loss occurs most extensively in the caudal putamen and caudate head. Previous structural studies have suggested reduced striatal volume and atrophy of the caudate head in PD subjects. The spatial distribution of atrophy in the putamen, however, has not been characterized. We aimed to delineate the specific locations of atrophy in both of these striatal structures. T1- and T2-weighted brain MR (3T) images were obtained from 40 PD and 40 control subjects having no dementia and similar age and gender distributions. Shape analysis was performed using doubly segmented regions of interest. Compared to controls, PD subjects had lower putamen (p=0.0003) and caudate (p=0.0003) volumes. Surface contraction magnitudes were greatest on the caudal putamen (p≤0.005) and head and dorsal body of the caudate (p≤0.005). This spatial distribution of striatal atrophy is consistent with the known pattern of dopamine depletion in PD and may reflect global consequences of known cellular remodeling phenomena

Consensus-based care recommendations for adults with myotonic dystrophy type 1

Purpose of review Myotonic dystrophy type 1 (DM1) is a severe, progressive genetic disease that affects between 1 in 3,000 and 8,000 individuals globally. No evidence-based guideline exists to inform the care of these patients, and most do not have access to multidisciplinary care centers staffed by experienced professionals, creating a clinical care deficit. Recent findings The Myotonic Dystrophy Foundation (MDF) recruited 66 international clinicians experienced in DM1 patient care to develop consensus-based care recommendations. MDF created a 2-step methodology for the project using elements of the Single Text Procedure and the Nominal Group Technique. The process generated a 4-page Quick Reference Guide and a comprehensive, 55-page document that provides clinical care recommendations for 19 discrete body systems and/or care considerations. Summary The resulting recommendations are intended to help standardize and elevate care for this patient population and reduce variability in clinical trial and study environments. Described as “one of the more variable diseases found in medicine,” myotonic dystrophy type 1 (DM1) is an autosomal dominant, triplet-repeat expansion disorder that affects somewhere between 1:3,000 and 1:8,000 individuals worldwide.1 There is a modest association between increased repeat expansion and disease severity, as evidenced by the average age of onset and overall morbidity of the condition. An expansion of over 35 repeats typically indicates an unstable and expanding mutation. An expansion of 50 repeats or higher is consistent with a diagnosis of DM1. DM1 is a multisystem and heterogeneous disease characterized by distal weakness, atrophy, and myotonia, as well as symptoms in the heart, brain, gastrointestinal tract, endocrine, and respiratory systems. Symptoms may occur at any age. The severity of the condition varies widely among affected individuals, even among members of the same family. Comprehensive evidence-based guidelines do not currently exist to guide the treatment of DM1 patients. As a result, the international patient community reports varied levels of care and care quality, and difficulty accessing care adequate to manage their symptoms, unless they have access to multidisciplinary neuromuscular clinics. Consensus-based care recommendations can help standardize and improve the quality of care received by DM1 patients and assist clinicians who may not be familiar with the significant variability, range of symptoms, and severity of the disease. Care recommendations can also improve the landscape for clinical trial success by eliminating some of the inconsistencies in patient care to allow more accurate understanding of the benefit of potential therapies

Measurement-Induced State Transitions in a Superconducting Qubit: Within the Rotating Wave Approximation

Superconducting qubits typically use a dispersive readout scheme, where a resonator is coupled to a qubit such that its frequency is qubit-state dependent. Measurement is performed by driving the resonator, where the transmitted resonator field yields information about the resonator frequency and thus the qubit state. Ideally, we could use arbitrarily strong resonator drives to achieve a target signal-to-noise ratio in the shortest possible time. However, experiments have shown that when the average resonator photon number exceeds a certain threshold, the qubit is excited out of its computational subspace, which we refer to as a measurement-induced state transition. These transitions degrade readout fidelity, and constitute leakage which precludes further operation of the qubit in, for example, error correction. Here we study these transitions using a transmon qubit by experimentally measuring their dependence on qubit frequency, average photon number, and qubit state, in the regime where the resonator frequency is lower than the qubit frequency. We observe signatures of resonant transitions between levels in the coupled qubit-resonator system that exhibit noisy behavior when measured repeatedly in time. We provide a semi-classical model of these transitions based on the rotating wave approximation and use it to predict the onset of state transitions in our experiments. Our results suggest the transmon is excited to levels near the top of its cosine potential following a state transition, where the charge dispersion of higher transmon levels explains the observed noisy behavior of state transitions. Moreover, occupation in these higher energy levels poses a major challenge for fast qubit reset

Readout of a quantum processor with high dynamic range Josephson parametric amplifiers

We demonstrate a high dynamic range Josephson parametric amplifier (JPA) in which the active nonlinear element is implemented using an array of rf-SQUIDs. The device is matched to the 50 $\Omega$ environment with a Klopfenstein-taper impedance transformer and achieves a bandwidth of 250-300 MHz, with input saturation powers up to -95 dBm at 20 dB gain. A 54-qubit Sycamore processor was used to benchmark these devices, providing a calibration for readout power, an estimate of amplifier added noise, and a platform for comparison against standard impedance matched parametric amplifiers with a single dc-SQUID. We find that the high power rf-SQUID array design has no adverse effect on system noise, readout fidelity, or qubit dephasing, and we estimate an upper bound on amplifier added noise at 1.6 times the quantum limit. Lastly, amplifiers with this design show no degradation in readout fidelity due to gain compression, which can occur in multi-tone multiplexed readout with traditional JPAs.Comment: 9 pages, 8 figure

Overcoming leakage in scalable quantum error correction

Leakage of quantum information out of computational states into higher energy states represents a major challenge in the pursuit of quantum error correction (QEC). In a QEC circuit, leakage builds over time and spreads through multi-qubit interactions. This leads to correlated errors that degrade the exponential suppression of logical error with scale, challenging the feasibility of QEC as a path towards fault-tolerant quantum computation. Here, we demonstrate the execution of a distance-3 surface code and distance-21 bit-flip code on a Sycamore quantum processor where leakage is removed from all qubits in each cycle. This shortens the lifetime of leakage and curtails its ability to spread and induce correlated errors. We report a ten-fold reduction in steady-state leakage population on the data qubits encoding the logical state and an average leakage population of less than $1 \times 10^{-3}$ throughout the entire device. The leakage removal process itself efficiently returns leakage population back to the computational basis, and adding it to a code circuit prevents leakage from inducing correlated error across cycles, restoring a fundamental assumption of QEC. With this demonstration that leakage can be contained, we resolve a key challenge for practical QEC at scale.Comment: Main text: 7 pages, 5 figure

Measurement-induced entanglement and teleportation on a noisy quantum processor

Measurement has a special role in quantum theory: by collapsing the wavefunction it can enable phenomena such as teleportation and thereby alter the "arrow of time" that constrains unitary evolution. When integrated in many-body dynamics, measurements can lead to emergent patterns of quantum information in space-time that go beyond established paradigms for characterizing phases, either in or out of equilibrium. On present-day NISQ processors, the experimental realization of this physics is challenging due to noise, hardware limitations, and the stochastic nature of quantum measurement. Here we address each of these experimental challenges and investigate measurement-induced quantum information phases on up to 70 superconducting qubits. By leveraging the interchangeability of space and time, we use a duality mapping, to avoid mid-circuit measurement and access different manifestations of the underlying phases -- from entanglement scaling to measurement-induced teleportation -- in a unified way. We obtain finite-size signatures of a phase transition with a decoding protocol that correlates the experimental measurement record with classical simulation data. The phases display sharply different sensitivity to noise, which we exploit to turn an inherent hardware limitation into a useful diagnostic. Our work demonstrates an approach to realize measurement-induced physics at scales that are at the limits of current NISQ processors