Mohit Rana

• Ph.D. in Behavioral Neuroscience
• PostDoc Position at University of Tübingen

Most 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 brai...

Objective. Brain–computer interface (BCI) is a tool that can be used to train brain self-regulation and influence specific activity patterns, including functional connectivity, through neurofeedback. The functional connectivity of the primary motor area (M1) and cerebellum play a critical role in motor recovery after a brain injury, such as stroke....

One of the most important and early impairments in autism spectrum disorder (ASD) is the abnormal visual processing of human faces. This deficit has been associated with hypoactivation of the fusiform face area (FFA), one of the main hubs of the face-processing network. Neurofeedback based on real-time fMRI (rtfMRI-NF) is a technique that allows th...

Depression, one of the leading causes of disability and (self-inflicted) death in the world, requires a more robust method of treatment for treatment-resistant patients. Due to imaging techniques like fMRI, real-time neurofeedback (NF) has been shown to aid healthy individuals and patients to voluntarily control their hemodynamic activity, leading...

In this article, the affiliation for Mohit Rana was incorrectly listed as the Institute for Biological and Medical Engineering, Department of Psychiatry, and Section of Neuroscience, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860 Hernán Briones, piso 2, Macul 782–0436, Santiago, Chile. The listed affiliation should have been the fol...

Neurofeedback is a psychophysiological procedure in which online feedback of neural activation is provided to the participant for the purpose of self-regulation. Learning control over specific neural substrates has been shown to change specific behaviours. As a progenitor of brain–machine interfaces, neurofeedback has provided a novel way to invest...

Cognitive decline is a major concern in the aging population. It is normative to experience some deterioration in cognitive abilities with advanced age such as related to memory performance, attention distraction to interference, task switching, and processing speed. However, intact cognitive functioning in old age is important for leading an indep...

[This corrects the article DOI: 10.1371/journal.pone.0159959.].

Recently, studies have reported the use of Near Infrared Spectroscopy (NIRS) for developing Brain-Computer Interface (BCI) by applying online pattern classification of brain states from subject-specific fNIRS signals. The purpose of the present study was to develop and test a real-time method for subject-specific and subject-independent classificat...

The learning process involved in achieving brain self-regulation is presumed to be related to several factors, such as type of feedback, reward, mental imagery, duration of training, among others. Explicitly instructing participants to use mental imagery and monetary reward are common practices in real-time fMRI (rtfMRI) neurofeedback (NF), under t...

INTRODUCTION: Obsessive-compulsive disorder (OCD) is a common and chronic condition that can have disabling effects throughout the patient's lifespan. Frequent symptoms among OCD patients include fear of contamination and washing compulsions. Several studies have shown a link between contamination fears, disgust over-reactivity, and insula activati...

Background: Two thirds of stroke survivors experience motor impairment resulting in long-term disability. The anatomical substrate is often the disruption of cortico-subcortical pathways. It has been proposed that reestablishment of cortico-subcortical communication relates to functional recovery. Objective: In this study, we applied a novel tra...

While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofee...

Autism spectrum disorder (ASD) is a developmental disability characterized by early-onset difficulties in social communication and restricted repetitive behavior. One the most important impairments in ASD is the abnormal processes of human faces [1]. This deficit could be associated with an abnormal activity of fusiform face area (FFA) [2]. Therefo...

Introduction: Obsessive-compulsive disorder (OCD) is a common and chronic condition that can have disabling effects throughout the patient's lifespan. Frequent symptoms among OCD patients include fear of contamination and washing compulsions. Several studies have shown a link between contamination fears, disgust over-reactivity, and insula activat...

MANAS 4 is a tool to perform batch-processing of fMRI signals with a Pattern Classification approach, allowing a high degree of customization and letting the researcher to focus on the analysis of the data, rather than the building of the processing. Its execution is based on the preparation of JavaScript Object Notation (JSON) configuration files,...

Several neuroimaging studies have provided strong evidence of the possibility to decode mental states from brain activity. Compared to strictly location-based analysis, pattern classification can reveal new information about the way cognitive, emotional, and perceptual states are encoded in patterns of brain activity. By relying on mental state cla...

INTRODUCTION: Obsessive-compulsive disorder (OCD) is a common and chronic condition that can have disabling effects throughout the patient's lifespan. Frequent symptoms among OCD patients include fear of contamination and washing compulsions. Several studies have shown a link between contamination fears, disgust over-reactivity, and insula activati...

While earlier Brain-Computer Interface (BCI) studies have mostly focused on modulating specific brain regions or signals, new developments in pattern classification of brain states are enabling real-time decoding and modulation of an entire functional network. The present study proposes a new method for real-time pattern classification and neurofee...

. Thus far, most of the brain-computer interfaces (BCIs) developed for motor rehabilitation used electroencephalographic signals to drive prostheses that support upper limb movement. Only few BCIs used hemodynamic signals or were designed to control lower extremity prostheses. Recent technological developments indicate that functional near-infrared...

Several studies have reported on the feasibility of using Near Infra-Red Spectroscopty (NIRS) for developing brain-computer interface (BCI) devices as an alternate mode of communication and environmental control for the disabled, including its application in neurofeedback training. In the present study, we report the development of a real-time Supp...

It 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 SMA on han...

There is a recent increase in the use of multivariate analysis and pattern classification in prediction and real-time feedback of brain states from functional imaging signals and mapping of spatio-temporal patterns of brain activity. Here we present MANAS, a generalized software toolbox for performing online and offline classification of fMRI signa...

With the advent of brain computer interfaces based on real-time fMRI (rtfMRI-BCI), the possibility of performing neurofeedback based on brain hemodynamics has become a reality. In the early stage of the development of this field, studies have focused on the volitional control of activity in circumscribed brain regions. However, based on the underst...

A brain-computer interface (BCI) based on near-infrared spectroscopy (NIRS) could act as a tool for rehabilitation of stroke patients due to the neural activity induced by motor imagery aided by real-time feedback of hemodynamic activation. When combined with functional electrical stimulation (FES) of the affected limb, BCI is expected to have an e...

Background Alzheimer patients express their need of social interaction even when their communication abilities are highly impaired. (Mayhew et al., 2001). Brain-computer interfaces (BCI), already used with severely paralyzed patients, may be adapted for communicating with Alzheimer patients by shifting the paradigm from instrumental-operant learnin...

An 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 disc...