The Functional Role of the N2B Region Within the Elastic Sarcomeric Protein Titin

Utilizing a N2B knockout (KO) mouse model in which the exon that encodes the cardiac-specific N2B unique sequence (N2B-Us) spring element (exon 49) has been deleted, I investigated the mechanical role of the N2B-Us, one of the three extensible regions of cardiac titin. I was able to show that the extensibility provided by the N2B-Us limits energy loss during stretch and shortening cycles of the heart (i.e., during diastole and systole). In a range of conditions, KO mice showed significant increases in hysteresis, a measure of energy loss determined from the area between the stretch and release force-sarcomere length curves, over wild type (WT) mice. Most prominently, hysteresis increased significantly from 320±46 pJ/mm2 /sarcomere in WT tissue to 650±94 pJ/mm2 /sarcomere in KO tissue that had been preconditioned with a physiological stretch-release protocol (p < 0.005). To complement this KO model, oxidative stress was used to mechanically inactivate portions of the N2B-Us of WT titin through cysteine crosslinking. This inactivation displayed a greater increase in hysteresis response in WT compared to KO tissue, (32.3±5% vs. 12.9±2.2%, p-value < 0.05). The results of this study support the concept that the mechanical function of the N2B-Us of titin is to reduce hysteresis and increase the efficiency of the cardiac cycle.Digitized from a paper copy provided by the Physiological Sciences Graduate Interdisciplinary Program

Behavior Classification Using Multi-site LFP and ECoG Signals

Abstract-Deep Brain Stimulation (DBS) is an effective therapy that alleviates the motor signs of Parkinson’s disease (PD). Existing DBS is open loop, providing a time invariant stimulation pulse train that may generate cognitive, speech, and balance side effects. A closed-loop DBS system that utilizes appropriate physiological control variables may improve therapeutic results, reduce stimulation side effects, and extend battery life of pulse generators. Furthermore, by customizing DBS to a patient’s behavioral goal, side effects of stimulation may arise only when they are non-detrimental to the patient’s current goals. Therefore, classification of human behavior using physiological signals is an important step in the design of the next generation of closed-loop DBS systems. Ten subjects who were undergoing DBS implantation were recruited for the study. DBS leads were used to record bilateral STN-LFP activity and an electrocorticography (ECoG) strip was used to record field potentials over left prefrontal cortex. Subjects were cued to perform voluntary behaviors including left and right hand movement, left and right arm movement, mouth movement, and speech. Two types of algorithms were used to classify the subjects’ behavior, support vector machine (SVM) using linear, polynomial, and RBF kernels as well as lp-norm multiple kernel learning (MKL). Behavioral classification was performed using only LFP channels, only ECoG channels, and both LFP and ECoG channels. Features were extracted from the time-frequency representation of the signals. Phase locking values (PLV) between ECoG and LFP channels were calculated to determine connectivity between sites and aid in feature selection. Classification performance improved when multi-site signals were used with either SVM or MKL algorithms. Our experiments further show that the lp-norm MKL outperforms single kernel SVM-based classifiers in classifying behavioral tasks. References [1] H. M. Golshan, A. O. Hebb, S. J. Hanrahan, J. Nedrud, and M. H. Mahoor, “A multiple kernel learning approach for human behavioral task classification using STN-LFP signal,” EMBC, 38th IEEE International Conference on., pp.1030-1033, 2016. [2] H. M. Golshan, A. O. Hebb, S. J. Hanrahan, J. Nedrud, and M. H. Mahoor, “An FFT-based synchronization approach to recognize human behaviors using STN-LFP signal,” To appear in ICASSP, 42nd IEEE International Conference on., 2017

Human Behavior Recognition Ssing Brain LFP Signal in the Presence of the Stimulation Pulse

Design and Methodology This study concentrates on human behavior classification task using local field potential (LFP) signals recorded from three subjects with Parkinson’s disease (PD). Existing approaches mainly employ the LFP signals acquired under the stimulation/off condition. In practical situations, however, it is necessary to design a classification method capable of recognizing different human activities under the stimulation/on condition, where the classification task is more complicated due to the artifacts imposed by the high amplitude stimulation pulse (~1-3volts). We utilize the time-frequency representation of the acquired LFPs in the Beta frequency range (~10-30Hz) to develop a feature space based on which the classification is efficiently performed while the high frequency stimulation pulse (~130-180Hz) has no/limited impact on the classification performance. Original Data and Results All three participants had undergone DBS surgery with implanted DBS leads (Medtronic 3389, Minneapolis, MN, USA) in the subthalamic nucleus of the brain. The recording sessions required the participants to do several repetitions of designed “button press” and “reach” trials under the condition of stimulation on/off. On average, 60 recordings were performed for each trial. Our analysis on the power spectral density (PSD) of the data showed that the stimulation pulse mostly impacts the frequency components around the stimulation frequency (~140Hz). Using a linear-kernel SVM classifier for classifying the aforementioned trials based on the proposed feature space, we obtained a classification accuracy of ~88% and ~87% respectively for stimulation off and on cases. Conclusion PD incidence increases with advancing age and peaks among people in their 60s and 70s. The cost of PD in the United States is estimated to be $25 billion per year. Thus, advanced techniques to improve the performance of existing devices are highly demanded. Human behavior classification from brain signals is essential in developing the next generation of closed-loop deep brain stimulation (DBS) systems. A closed-loop DBS system that utilizes appropriate physiological control variables may improve therapeutic results, reduce stimulation side effects, and extend battery life of pulse generators

Mouse intact cardiac myocyte mechanics: cross-bridge and titin-based stress in unactivated cells

A carbon fiber–based cell attachment and force measurement system was used to measure the diastolic stress–sarcomere length (SL) relation of mouse intact cardiomyocytes, before and after the addition of actomyosin inhibitors (2,3-butanedione monoxime [BDM] or blebbistatin). Stress was measured during the diastolic interval of twitching myocytes that were stretched at 100% base length/second. Diastolic stress increased close to linear from 0 at SL 1.85 µm to 4.2 mN/mm2 at SL 2.1 µm. The actomyosin inhibitors BDM and blebbistatin significantly lowered diastolic stress by ∼1.5 mN/mm2 (at SL 2.1 µm, ∼30% of total), suggesting that during diastole actomyosin interaction is not fully switched off. To test this further, calcium sensitivity of skinned myocytes was studied under conditions that simulate diastole: 37°C, presence of Dextran T500 to compress the myofilament lattice to the physiological level, and [Ca2+] from below to above 100 nM. Mean active stress was significantly increased at [Ca2+] > 55 nM (pCa 7.25) and was ∼0.7 mN/mm2 at 100 nM [Ca2+] (pCa 7.0) and ∼1.3 mN/mm2 at 175 nM Ca2+ (pCa 6.75). Inhibiting active stress in intact cells attached to carbon fibers at their resting SL and stretching the cells while first measuring restoring stress (pushing outward) and then passive stress (pulling inward) made it possible to determine the passive cell’s mechanical slack SL as ∼1.95 µm and the restoring stiffness and passive stiffness of the cells around the slack SL each as ∼17 mN/mm2/µm/SL. Comparison between the results of intact and skinned cells shows that titin is the main contributor to restoring stress and passive stress of intact cells, but that under physiological conditions, calcium sensitivity is sufficiently high for actomyosin interaction to contribute to diastolic stress. These findings are relevant for understanding diastolic function and for future studies of diastolic heart failure

Motor Task Detection From Human STN Using Interhemispheric Connectivity

Deep brain stimulation (DBS) provides significant therapeutic benefit for movement disorders, such as Parkinson\u27s disease (PD). Current DBS devices lack real-time feedback (thus are open loop) and stimulation parameters are adjusted during scheduled visits with a clinician. A closed-loop DBS system may reduce power consumption and side effects by adjusting stimulation parameters based on patient\u27s behavior. Subthalamic nucleus (STN) local field potential (LFP) is a great candidate signal for the neural feedback, because it can be recorded from the stimulation lead and does not require additional sensors. In this paper, we introduce a behavior detection method capable of asynchronously detecting the finger movements of PD patients. Our study indicates that there is a motor-modulated inter-hemispheric connectivity between LFP signals recorded bilaterally from the STN. We utilize a non-linear regression method to measure this inter-hemispheric connectivity for detecting finger movement. Our experimental results, using the recordings from 11 patients with PD, demonstrate that this approach is applicable for behavior detection in the majority of subjects (average area under curve of 70±12%)