Browsing by Author "Rana, Mohit"
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- ItemA real-time fMRI neurofeedback system for the clinical alleviation of depression with a subject-independent classification of brain states: A proof of principle study(2022) Pereira, Jaime A.; Ray, Andreas; Rana, Mohit; Silva, Claudio; Salinas, Cesar; Zamorano, Francisco; Irani, Martin; Opazo, Patricia; Sitaram, Ranganatha; Ruiz, SergioMost clinical neurofeedback studies based on functional magnetic resonance imaging use the patient's own neural activity as feedback. The objective of this study was to create a subject-independent brain state classifier as part of a real-time fMRI neurofeedback (rt-fMRI NF) system that can guide patients with depression in achieving a healthy brain state, and then to examine subsequent clinical changes. In a first step, a brain classifier based on a support vector machine (SVM) was trained from the neural information of happy autobiographical imagery and motor imagery blocks received from a healthy female participant during an MRI session. In the second step, 7 right-handed female patients with mild or moderate depressive symptoms were trained to match their own neural activity with the neural activity corresponding to the "happiness emotional brain state" of the healthy participant. The training (4 training sessions over 2 weeks) was carried out using the rt-fMRI NF system guided by the brain-state classifier we had created. Thus, the informative voxels previously obtained in the first step, using SVM classification and Effect Mapping, were used to classify the Blood-Oxygen-Level Dependent (BOLD) activity of the patients and converted into real-time visual feedback during the neurofeedback training runs. Improvements in the classifier accuracy toward the end of the training were observed in all the patients [Session 4-1 Median = 6.563%; Range = 4.10-27.34; Wilcoxon Test (0), 2-tailed p = 0.031]. Clinical improvement also was observed in a blind standardized clinical evaluation [HDRS CE2-1 Median = 7; Range 2 to 15; Wilcoxon Test (0), 2-tailed p = 0.016], and in self-report assessments [BDI-II CE2-1 Median = 8; Range 1-15; Wilcoxon Test (0), 2-tailed p = 0.031]. In addition, the clinical improvement was still present 10 days after the intervention [BDI-II CE3-2_Median = 0; Range -1 to 2; Wilcoxon Test (0), 2-tailed p = 0.50/ HDRS CE3-2 Median = 0; Range -1 to 2; Wilcoxon Test (0), 2-tailed p = 0.625]. Although the number of participants needs to be increased and a control group included to confirm these findings, the results suggest a novel option for neural modulation and clinical alleviation in depression using noninvasive stimulation technologies.
- ItemA subject-independent pattern-based Brain-Computer Interface(2015) Ray, Andreas M.; Sitaram, Ranganatha; Rana, Mohit; Pasqualotto, Emanuele; Buyukturkoglu, Korhan; Guan, Cuntai; Ang, Kai-Keng; Tejos Núñez, Cristián Andrés; Zamorano, Francisco; Ruiz Poblete, Sergio Marcelo; Birbaumer, Niels; Aboitiz, Francisco
- ItemFour methods of brain pattern analyses of fMRI signals associated with wrist extension versus wrist flexion studied for potential use in future motor learning BCI(2021) Ravindran, Aniruddh; Rieke, Jake D.; Zapata, Jose Daniel Alcantara; White, Keith D.; Matarasso, Avi; Yusufali, M. Minhal; Rana, Mohit; Gunduz, Aysegul; Modarres, Mo; Sitaram, Ranganatha; Daly, Janis J.Objective
- ItemNon-Invasive Functional Evaluation of the Human Spinal Cord by Assessing the Peri-Spinal Neurovascular Network With Near Infrared Spectroscopy(2021) Valenzuela, Felipe; Rana, Mohit; Sitaram, Ranganatha; Uribe, Sergio; Eblen-Zajjur, AntonioCurrent medical care lacks an effective functional evaluation for the spinal cord. Magnetic resonance imaging and computed tomography mainly provide structural information of the spinal cord, while spinal somatosensory evoked potentials are limited by a low signal to noise ratio. We developed a non-invasive approach based on near-infrared spectroscopy in dual-wavelength (760 and 850 nm for deoxy- or oxyhemoglobin respectively) to record the neurovascular response (NVR) of the peri-spinal vascular network at the 7th cervical and 10th thoracic vertebral levels of the spinal cord, triggered by unilateral median nerve electrical stimulation (square pulse, 5-10 mA, 5 ms, 1 pulse every 4 minutes) at the wrist. Amplitude, rise-time, and duration of NVR were characterized in 20 healthy participants. A single, painless stimulus was able to elicit a high signal-to-noise ratio and multi-segmental NVR (mainly from Oxyhemoglobin) with a fast rise time of 6.18 [4.4-10.4] seconds (median [Percentile 25-75]) followed by a slow decay phase for about 30 seconds toward the baseline. Cervical NVR was earlier and larger than thoracic and no left/right asymmetry was detected. Stimulus intensity/NVR amplitude fitted to a 2nd order function. The characterization and feasibility of the peri-spinal NVR strongly support the potential clinical applications for a functional assessment of spinal cord lesions.
- ItemReal-time fMRI brain computer interfaces : Self-regulation of single brain regions to networks(2014) Ruiz Poblete, Sergio Marcelo; Buyukturkoglu, Korhan; Rana, Mohit; Birbaumer, Niels; Sitaram, Ranganatha
- ItemReal-Time fMRI Neurofeedback Training of Selective Attention in Older Adults(2024) Lin, Tian; Rana, Mohit; Liu, Peiwei; Polk, Rebecca; Heemskerk, Amber; Weisberg, Steven M.; Bowers, Dawn; Sitaram, Ranganatha; Ebner, Natalie C.Background: Selective attention declines with age, due to age-related functional changes in dorsal anterior cingulate cortex (dACC). Real-time functional magnetic resonance imaging (rtfMRI) neurofeedback has been used in young adults to train volitional control of brain activity, including in dACC. Methods: For the first time, this study used rtfMRI neurofeedback to train 19 young and 27 older adults in volitional up- or down-regulation of bilateral dACC during a selective attention task. Results: Older participants in the up-regulation condition (experimental group) showed greater reward points and dACC BOLD signal across training sessions, reflective of neurofeedback training success; and faster reaction time and better response accuracy, suggesting behavioral benefits on selective attention. These effects were not observed for older participants in the down-regulation condition (inverse condition control group), supporting specificity of volitional dACC up-regulation training in older adults. These effects were, unexpectedly, also not observed for young participants in the up-regulation condition (age control group), perhaps due to a lack of motivation to continue the training. Conclusions: These findings provide promising first evidence of functional plasticity in dACC in late life via rtfMRI neurofeedback up-regulation training, enhancing selective attention, and demonstrate proof of concept of rtfMRI neurofeedback training in cognitive aging.
- ItemReal-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS. Signals(2016) Robinson, Neethu; Zaidi, Ali Danish; Rana, Mohit; Prasad, Vinod A.; Guan, Cuntai; Birbaumer, Niels; Sitaram, Ranganatha
- ItemReal-time support vector classification and feedback of multiple emotional brain states(2011) Sitaram, Ranganatha; Lee, Sangkyun; Ruiz, Sergio; Rana, Mohit; Veit, Ralf; Birbaumer, NielsAn important question that confronts current research in affective neuroscience as well as in the treatment of emotional disorders is whether it is possible to determine the emotional state of a person based on the measurement of brain activity alone. Here, we first show that an online support vector machine (SVM) can be built to recognize two discrete emotional states, such as happiness and disgust from fMRI signals, in healthy individuals instructed to recall emotionally salient episodes from their lives. We report the first application of real-time head motion correction, spatial smoothing and feature selection based on a new method called Effect mapping. The classifier also showed robust prediction rates in decoding three discrete emotional states (happiness, disgust and sadness) in an extended group of participants. Subjective reports ascertained that participants performed emotion imagery and that the online classifier decoded emotions and not arbitrary states of the brain. Offline whole brain classification as well as region-of-interest classification in 24 brain areas previously implicated in emotion processing revealed that the frontal cortex was critically involved in emotion induction by imagery. We also demonstrate an fMRI-BCI based on real-time classification of BOLD signals from multiple brain regions, for each repetition time (TR) of scanning, providing visual feedback of emotional states to the participant for potential applications in the clinical treatment of dysfunctional affect. (C) 2010 Elsevier Inc. All rights reserved.
- ItemUse of Real-Time Functional Magnetic Resonance Imaging-Based Neurofeedback to Downregulate Insular Cortex in Nicotine-Addicted Smokers(2020) Rana, Mohit; Ruiz, Sergio; Sanchez Corzo, Andrea; Muehleck, Axel; Eck, Sandra; Salinas, Cesar; Zamorano, Francisco; Silva, Claudio; Rea, Massimiliano; Batra, Anil; Birbaumer, Niels; Sitaram, RanganathaIt has been more than a decade since the first functional magnetic resonance imaging (fMRI)-based neurofeedback approach was successfully implemented. Since then, various studies have demonstrated that participants can learn to voluntarily control a circumscribed brain region. Consequently, real-time fMRI (rtfMRI) provided a novel opportunity to study modifications of behavior due to manipulation of brain activity. Hence, reports of rtfMRI applications to train self-regulation of brain activity and the concomitant modifications in behavioral and clinical conditions such as neurological and psychiatric disorders [e.g., schizophrenia, obsessive compulsive Disorder (OCD), stroke] have rapidly increased.
- ItemVolitional regulation of the supplementary motor area with fMRI-BCI neurofeedback in Parkinson's disease: A pilot study(IEEE, 2013) Buyukturkoglu, Korhan; Rana, Mohit; Ruiz Poblete, Sergio Marcelo; Hackley, Steven A.; Soekadar, Surjo R.; Birbaumer, Niels; Sitaram, RanganathaIt is hypothesized that a dysfunction of the supplementary motor area (SMA), secondary to a deficit of the nigrostriatal dopamine system, partially contributes to the symptomatology of Parkinson's disease (PD), i.e., akinesia. In this pilot study we investigated the effect of real-time fMRI neurofeedback based volitional up-regulation of the SMA on hand motor performance of one PD patient and 3 healthy volunteers. The effect of learned self-regulation was evaluated with speeded, bimanual, sequenced button-pressing trials, assessed immediately after each baseline and up-regulation block. Our pilot results indicate that volitional up-regulation of SMA is accompanied by slowing of sequenced button presses.