Imaging Flow Cytometry Analysis to Identify Differences of Survival Motor Neuron Protein Expression in Patients With Spinal Muscular Atrophy

BackgroundSpinal muscular atrophy is a neurodegenerative disorder caused by the deficient expression of survival motor neuron protein in motor neurons. A major goal of disease-modifying therapy is to increase survival motor neuron expression. Changes in survival motor neuron protein expression can be monitored via peripheral blood cells in patients; therefore we tested the sensitivity and utility of imaging flow cytometry for this purpose.MethodsAfter the immortalization of peripheral blood lymphocytes from a human healthy control subject and two patients with spinal muscular atrophy type 1 with two and three copies of SMN2 gene, respectively, we used imaging flow cytometry analysis to identify significant differences in survival motor neuron expression. A bright detail intensity analysis was used to investigate differences in the cellular localization of survival motor neuron protein.ResultsSurvival motor neuron expression was significantly decreased in cells derived from patients with spinal muscular atrophy relative to those derived from a healthy control subject. Moreover, survival motor neuron expression correlated with the clinical severity of spinal muscular atrophy according to SMN2 copy number. The cellular accumulation of survival motor neuron protein was also significantly decreased in cells derived from patients with spinal muscular atrophy relative to those derived from a healthy control subject.ConclusionsThe benefits of imaging flow cytometry for peripheral blood analysis include its capacities for analyzing heterogeneous cell populations; visualizing cell morphology; and evaluating the accumulation, localization, and expression of a target protein. Imaging flow cytometry analysis should be implemented in future studies to optimize its application as a tool for spinal muscular atrophy clinical trials.     

Motion‐induced disturbance of auditory–motor synchronization and its modulation by transcranial direct current stimulation

The timing of personal movement with respect to external events has previously been investigated using a synchronized finger‐tapping task with a sequence of auditory or visual stimuli. While visuomotor synchronization is more accurate with moving stimuli than with stationary stimuli, it remains unclear whether the same principle holds true in the auditory domain. Although the right inferior–superior parietal lobe (IPL/SPL), a center of auditory motion processing, is expected to be involved in auditory–motor synchronization with moving sounds, its functional relevance has not yet been investigated. The aim of the present study was thus to clarify whether horizontal auditory motion affects the accuracy of finger‐tapping synchronized with sounds, as well as whether the application of transcranial direct current stimulation (tDCS) to the right IPL/SPL affects this. Nineteen healthy right‐handed participants performed a task in which tapping was synchronized with both stationary sounds and sounds that created apparent horizontal motion. This task was performed before and during anodal, cathodal and sham tDCS application to the right IPL/SPL in separate sessions. The time difference between the onset of the sounds and tapping was larger with apparently moving sounds than with stationary sounds. Cathodal tDCS decreased this difference, anodal tDCS increased the variance of the difference and sham stimulation had no effect. These results supported the hypothesis that auditory motion disturbs efficient auditory–motor synchronization and that the right IPL/SPL plays an important role in tapping in synchrony with moving sounds via auditory motion processing.     

Unihemispheric concurrent dual‐site cathodal transcranial direct current stimulation: the effects on corticospinal excitability

We aimed to assess the effects of concurrent cathodal transcranial direct current stimulation (c‐tDCS) of two targets in a hemisphere, termed unihemispheric concurrent dual‐site cathodal tDCS (c‐tDCS_UHCDS), on the size of M1 corticospinal excitability and its lasting effect. Secondary aims were to identify the mechanisms behind the efficacy of c‐tDCS_UHCDS and to evaluate the side effects of this new technique. Twelve healthy volunteers received 20 min c‐tDCS under five conditions in a random order: M1 c‐tDCS, c‐tDCS_UHCDS of M1–dorsolateral prefrontal cortex (DLPFC), M1–primary sensory cortex (S1), M1–primary visual cortex (V1) and sham. The M1 corticospinal excitability of the first dorsal interossei muscle was assessed before, immediately after, and 30 min, 60 min and 24 h after the interventions. Short‐interval intracortical inhibition (SICI) and intracortical facilitation (ICF) were also assessed, using a paired‐pulse paradigm. Compared to conventional M1 c‐tDCS, corticospinal excitability significantly increased following c‐tDCS_UHCDS of M1‐DLPFC and M1‐V1 for up to 24 h (P = 0.001). Significant increases in ICF were observed following c‐tDCS_UHCDS of M1‐DLPFC (P = 0.005) and M1‐V1 (P = 0.002). Compared to baseline values, ICF and SICI increased significantly at T₆₀ (P < 0.001) and T_24 h (P < 0.001) following the concurrent c‐tDCS of M1 and V1. Sham c‐tDCS_UHCDS did not induce any significant alteration. The corticospinal excitability increase was mainly accompanied by ICF increase, which indirectly indicates the activity of glutamergic mechanisms. The findings may help us to more fully understand the brain function and develop future motor learning studies. No significant excitability change induced by sham c‐tDCS_UHCDS suggests that there is no placebo effect associated with this new tDCS technique.     

Between‐ and within‐site variability of fMRI localizations

This study provides first data about the spatial variability of fMRI sensorimotor localizations when investigating the same subjects at different fMRI sites. Results are comparable to a previous patient study. We found a median between‐site variability of about 6 mm independent of task (motor or sensory) and experimental standardization (high or low). An intraclass correlation coefficient analysis using data quality measures indicated a major influence of the fMRI site on variability. In accordance with this, within‐site localization variability was considerably lower (about 3 mm). We conclude that the fMRI site is a considerable confound for localization of brain activity. However, when performed by experienced clinical fMRI experts, brain pathology does not seem to have a relevant impact on the reliability of fMRI localizations. Hum Brain Mapp 37:2151–2160, 2016. © 2016 Wiley Periodicals, Inc.     

Bihemispheric network dynamics coordinating vocal feedback control

Modulation of vocal pitch is a key speech feature that conveys important linguistic and affective information. Auditory feedback is used to monitor and maintain pitch. We examined induced neural high gamma power (HGP) (65–150 Hz) using magnetoencephalography during pitch feedback control. Participants phonated into a microphone while hearing their auditory feedback through headphones. During each phonation, a single real‐time 400 ms pitch shift was applied to the auditory feedback. Participants compensated by rapidly changing their pitch to oppose the pitch shifts. This behavioral change required coordination of the neural speech motor control network, including integration of auditory and somatosensory feedback to initiate change in motor plans. We found increases in HGP across both hemispheres within 200 ms of pitch shifts, covering left sensory and right premotor, parietal, temporal, and frontal regions, involved in sensory detection and processing of the pitch shift. Later responses to pitch shifts (200–300 ms) were right dominant, in parietal, frontal, and temporal regions. Timing of activity in these regions indicates their role in coordinating motor change and detecting and processing of the sensory consequences of this change. Subtracting out cortical responses during passive listening to recordings of the phonations isolated HGP increases specific to speech production, highlighting right parietal and premotor cortex, and left posterior temporal cortex involvement in the motor response. Correlation of HGP with behavioral compensation demonstrated right frontal region involvement in modulating participant's compensatory response. This study highlights the bihemispheric sensorimotor cortical network involvement in auditory feedback‐based control of vocal pitch. Hum Brain Mapp 37:1474‐1485, 2016. © 2016 Wiley Periodicals, Inc.     

Motor imagery of hand actions: Decoding the content of motor imagery from brain activity in frontal and parietal motor areas

How motor maps are organized while imagining actions is an intensely debated issue. It is particularly unclear whether motor imagery relies on action‐specific representations in premotor and posterior parietal cortices. This study tackled this issue by attempting to decode the content of motor imagery from spatial patterns of Blood Oxygen Level Dependent (BOLD) signals recorded in the frontoparietal motor imagery network. During fMRI‐scanning, 20 right‐handed volunteers worked on three experimental conditions and one baseline condition. In the experimental conditions, they had to imagine three different types of right‐hand actions: an aiming movement, an extension–flexion movement, and a squeezing movement. The identity of imagined actions was decoded from the spatial patterns of BOLD signals they evoked in premotor and posterior parietal cortices using multivoxel pattern analysis. Results showed that the content of motor imagery (i.e., the action type) could be decoded significantly above chance level from the spatial patterns of BOLD signals in both frontal (PMC, M1) and parietal areas (SPL, IPL, IPS). An exploratory searchlight analysis revealed significant clusters motor‐ and motor‐associated cortices, as well as in visual cortices. Hence, the data provide evidence that patterns of activity within premotor and posterior parietal cortex vary systematically with the specific type of hand action being imagined. Hum Brain Mapp 37:81–93, 2016. © 2015 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.