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Thesis 

Posted by Admin July 08, 2014 Categories: Clinical Neurology Computational Neuroscience FSPS Goal-directed actions


Studio sperimentale sul ruolo dello real-time Fuzzy BCI (Brain-Computer Interface) in pazienti con la sindrome Locked-in /thesis in English/.

 
 
RELATORE:
Prof. Alessandro Padovani
 
CORRELATORE:
Prof. Nicola Latronico
LAUREANDO:
Andriy Oliynyk

  

ANNO ACCADEMICO 2013/2014

The experimental study of this thesis is a part of multidisciplinary scientific collaboration between the Department of Biomedical Science and Advanced Therapy, University of Ferrara and the Institute of Medical Psychology and Behavioral Neurobiology of the University of Tübingen (Germany), in the frame of research project "Real-Time Fuzzy BCI" funded by “Consorzio SPINNER” in 2013-2014 (Emilia-Romagna, prot.261/12, scientific coordinator is Andriy Oliynyk).

 

Activity in ventral premotor cortex is modulated by vision of own hand in action 

Luciano Fadiga, Luana Caselli, Laila Craighero, Benno Gesierich, Andriy Oliynyk, Banty Tia and Riccardo Viaro

Parietal and premotor cortices of the macaque monkey contain distinct populations of neurons which, in addition to their motor discharge, are also activated by visual stimulation. Among these visuomotor neurons, a population of grasping neurons located in the anterior intraparietal area (AIP) shows discharge modulation when the own hand is visible during object grasping. Given the dense connections between AIP and inferior frontal regions, we aimed at investigating whether two hand-related frontal areas, ventral premotor area F5 and primary motor cortex (area F1), contain
neurons with similar properties. Two macaques were involved in a grasping task executed in various light/dark conditions in which the to-be-grasped object was kept visible by a dim retro-illumination. Approximately 62% of F5 and 55% of F1 motor neurons showed light/dark modulations. To better isolate the effect of hand-related visual input, we introduced two further conditions characterized by kinematic features similar to the dark condition. The scene was briefly illuminated (i) during hand preshaping (pre-touch flash, PT-flash) and (ii) at hand-object contact (touch flash, T-flash). Approximately 48% of F5 and 44% of F1 motor neurons showed a flash-related modulation. Considering flash-modulated neurons in the
two flash conditions, 40% fromF5 and 52% fromF1 showed stronger activity in PT- than T-flash (PT-flash-dominant), whereas 60% from F5 and 48% from F1 showed stronger activity in T- than PT-flash (T-flash-dominant). Furthermore, F5, but not F1, flash-dominant neurons were characterized by a higher peak and mean discharge in the preferred flash condition as compared to light and dark conditions. Still considering F5, the distribution of the time of peak discharge was similar in light and preferred flash conditions. This study shows that the frontal cortex contains neurons, previously classified as motor neurons, which are sensitive to the observation of meaningful phases of the own grasping action.We conclude by discussing the
possible functional role of these populations.

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering 

Andriy Oliynyk, Claudio Bonifazzi, Fernando Montani, Luciano Fadiga
Posted by Admin February 05, 2013 Categories: ALL FSPS Software

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering

Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue.

Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize:

(i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike sorting algorithms.

This new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity. This feature could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces.

Deep brain stimulation: Subthalamic nucleus electrophysiological activity in awake and anesthetized patients 

Christian Lettieri, Sara Rinaldo, Grazia Devigili, Giada Pauletto, Lorenzo Verriello, Riccardo Budai, Luciano Fadiga, Andriy Oliynyk, Massimo Mondani, Stanislao D’Auria, Miran Skrap, Roberto Eleopra
Posted by Admin January 07, 2013 Categories: ALL Clinical Neurology FSPS

Journal paper

The purpose of this study was to evaluate changes in subthalamic nucleus (STN) neuronal activity in Parkinson's disease (PD) patients during deep brain stimulation (DBS) surgery under general anesthesia, and to compare these data with those recorded in the same subjects during previous surgery under local anesthesia.

Five patients with advanced PD, who had previously undergone bilateral STN-DBS under local anesthesia, underwent re-implantation under general anesthesia (with an anesthetic protocol based on the intravenous infusion of remifentanyl and ketamine) owing to surgical device complications. The microelectrode recording (MER) data obtained were analyzed by an off-line spike-sorting software. Neurophysiological data (number of spikes detected, mean firing rate, pause index and burst index) obtained under local and general anesthesia were then evaluated and compared by means of statistical analysis.

We found no statistically significant difference between the first and second surgical procedures in any of the neurophysiological parameters analyzed.

Bilateral STN-DBS for advanced PD with MER guidance is possible and reliable under a ketamine-based anesthetic protocol.

General anesthesia can be proposed for those patients who do not accept an "awake surgery" for clinical reasons, such as excessive fear, poor cooperation or severe "off"-medication effects.

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