Biology subjects

Millan, J. d. R.

Publications and source records attributed to Millan, J. d. R..

3 recordsLinked to original sources

bioRxiv2018

Differential contributions of subthalamic beta rhythms and neural noise to Parkinson motor symptoms

BackgroundExcessive beta oscillatory activity in the subthalamic nucleus (STN) is linked to Parkinsons disease and associated motor symptoms. However, the relationship between beta activity and motor symptoms has been inconsistent, which may influence the efficacy of closed-loop deep brain stimulation.\n\nHypothesisWe hypothesized that this variability is due to the degree of neural noise in STN recordings. Recent evidence has shown that neural noise is influenced by multiple factors, such as development, aging and disease, and could confound measures of beta activity. In this work, we propose a model that disentangles beta oscillatory activity and neural noise in the STN power spectrum.\n\nMethodsWe investigated the impact of neural noise on estimations of beta activity and motor symptoms from data recorded bilaterally from the subthalamic nuclei of thirteen Parkinsonian patients.\n\nResultsResults showed that the relationship between beta oscillatory amplitude and motor symptoms (bradykinesia and rigidity) significantly improved when neural noise was removed from the estimation of beta activity.\n\nConclusionThese findings emphasize the importance of modeling neural components independently for understanding physiological processes associated with Parkinsons disease, and identifying better biomarkers for characterizing symptom severity. Subsequently, we predict that our findings can have a direct application for closed-loop deep brain stimulation on Parkinsons Disease.

neuroscience↗

bioRxiv2017

Brain-Computer Interfaces for Post-Stroke Motor Rehabilitation: A Meta-Analysis

ObjectiveBrain-computer interfaces (BCIs) can provide sensory feedback of ongoing brain oscillations enabling stroke survivors to modulate their sensorimotor rhythms purposefully. A number of recent clinical studies indicate that repeated use of such BCIs might trigger neurological recovery and hence improvement in motor function. Here we provide a first meta-analysis evaluating the clinical effectiveness of BCI-based post-stroke motor rehabilitation.\n\nMethodsTrials were identified using MEDLINE, CENTRAL, PEDro and by inspection of references in several review articles. We selected randomized controlled trials that used BCIs for post-stroke motor rehabilitation and provided motor impairment scores before and after the intervention. A random-effects inverse variance method was used to calculate the summary effect size.\n\nResultsWe initially identified 524 articles and, after removing duplicates, we screened titles and abstracts of 473 articles. We found 26 articles corresponding to BCI clinical trials, of these, there were nine studies that involved a total of 235 post-stroke survivors fulfilling the inclusion criterion (randomized controlled trials that examined motor performance as an outcome measure) for the meta-analysis. Motor improvements, mostly quantified by the upper limb Fugl-Meyer Assessment (FMA-UE), exceeded the minimal clinical important difference (MCID=5.25) in six BCI studies, while such improvement was reached only in three control groups. Overall, the BCI training was associated with a standardized mean difference (SMD) of 0.79 (95% CI: 0.37 to 1.20) in FMA-UE compared to control conditions, which is in the range of medium to large summary effect size. In addition, several studies indicated BCI-induced functional and structural neuroplasticity at a sub-clinical level.\n\nInterpretationWe found a medium to large effect size of BCI therapy compared to controls. This suggests that BCI technology might be an effective intervention for post-stroke upper limb rehabilitation. However, more studies with larger sample size are required to increase the reliability of these results.

neuroscience↗

bioRxiv2017

Neural Encoding of Auditory Features during Music Perception and Imagery: Insight into the Brain of a Piano Player

It remains unclear how the human cortex represents spectrotemporal sound features during auditory imagery, and how this representation compares to auditory perception. To assess this, we recorded electrocorticographic signals from an epileptic patient with proficient music ability in two conditions. First, the participant played two piano pieces on an electronic piano with the sound volume of the digital keyboard on. Second, the participant replayed the same piano pieces, but without auditory feedback, and the participant was asked to imagine hearing the music in his mind. In both conditions, the sound output of the keyboard was recorded, thus allowing precise time-locking between the neural activity and the spectrotemporal content of the music imagery. For both conditions, we built encoding models to predict high gamma neural activity (70-150Hz) from the spectrogram representation of the recorded sound. We found robust similarities between perception and imagery - in frequency and temporal tuning properties in auditory areas.\n\nAbbreviations

neuroscience↗