View from India: Neuroimaging reveals that music is good for your brain
The International Institute of Information Technology-Hyderabad (IIIT-Hyderabad) is gearing up to showcase its first-ever summer school on neuroimaging in July. It is hoped that event will attract a sizeable number of students into the field of neuroimaging.
Neuroimaging or brain imaging is the use of various techniques to either directly or indirectly image the structure, function/pharmacology of the nervous system. It is a relatively new discipline within medicine, neuroscience, and psychology.
The upcoming event will take into account various aspects of Neuroimaging including Magnetic Resonance Imaging (MRI), Functional magnetic resonance imaging or functional MRI (fMRI) and magnetoencephalography (MEG). Of course, electroencephalogram (EEG) as a neuroimaging technique has been around for a long time.
“In the clinical community, the radiologists who specialize in imaging and interpreting nervous system are called Neuroradiologists and this is a small community in India. The academic research neuroimaging community that is engaged in Cognitive Neuroscience research is very small, at most 15. There are several electrical engineers who do medical imaging research, not necessarily interested in Cognitive NeuroScience issues,” said Prof Bapi Raju from the Cognitive Science Lab, IIIT-Hyderabad.
The summer school aims to cover applications of the statistical and machine learning approaches in the analysis of neuroimaging data, comprising both structural and functional images, and appreciating the related cognitive neuroscience research. Inputs from all the researchers have been taken in designing the course and the practical sessions.
Through the summer school, it is hoped that students gain familiarity with neuroimaging as a tool for Cognitive Neuroscience investigation, exposure to the data processing pipeline and appreciation of recent advances and open research questions in the domain of neuroimaging.
The summer school will focus on processing T1 and DTI structural data, besides giving an introduction to functional magnetic resonance imaging (fMRI) experiments such as epoch-based and event-related designs and cover image processing methods to preprocess functional imaging data.
A session on popular machine-learning algorithms and network analysis methods focuses on the application of these methods in neuroimaging data analysis on both task-based and resting-state data.
“Machine learning and Neuroscience are connected in two different ways. Firstly, machine-learning techniques can be used to analyse data. For example, identifying sequential patterns in the neural spike train data from different neurons or trying to predict what object a person is thinking about by combining evidence from different voxels in a functional magnetic resonance imaging (fMRI) scan,” said Dr Naresh Manwani, Machine Learning Lab, IIIT-H.
Another interesting relationship is that the machine-learning algorithms give theoretical insights about how the brain works (and vice versa). For example, a currently influential theory of the functional role of an increase in dopamine level was inspired by an algorithm called td-learning (temporal difference learning), which was good at learning to select actions in games such as backgammon, in which the future contains uncertainty.
“Thus, it is very important to understand machine learning algorithms and their underlying assumptions. This is the same reason why machine leaning has been integrated in this summer school,” highlighted Prof Manwani.
In the last decade or more, there has been significant research on the effects of music on the brain. The studies include investigating cognitive and emotional aspects of the human brain (neurosciences) that music can affect, and thereby also the positive effect on human behaviour.
All these studies demonstrate that music is a powerful tool — it can alter the brain across lifespan — both in response to training and after recovery from brain injury and helps foster mental health and wellbeing.
Neuroimaging done in the past on adult musicians have revealed significant lasting changes in the brain throughout an individual’s lifetime. Music is by definition, inherently spiritual with healing properties; this sharpening of temporal processing has displayed visible enhancements in an individual’s reading and verbal memory irrespective of their cultural exposure and experience.
Dr Vinoo Alluri, an engineer with a Masters degree in music engineering technology will deliver a lecture on music information retrieval (MIR) at the event. An interdisciplinary science of retrieving information from music, MIR has many real-world applications. Those involved in MIR may have a background in musicology, psychology, academic music study, signal processing and machine learning.
“Music is known for improving one’s mood and evokes a feeling of pleasure. The act of listening to music engages various parts of the brain. Besides mood enhancement, medically music is known for its therapeutic qualities. We know it as music improvisation therapy,” added Dr Alluri.
Music is today being seen as a successful physiological and medical method for treating diagnoses such as dyslexia, autism, post-traumatic stress disorder, dementia, stroke, NICU (neonatal intensive care unit) infants, language acquisition, pain management, stress and anxiety, coma and many more conditions.
Undergraduate and graduate students of engineering, psychology, clinical psychology, neuroscience, cognitive science, mathematics and management from reputed institutions across the country will participate in the summer school. They have been selected based on their academic credentials and a statement of purpose.
The idea of the summer school originated and was conceptualized in the annual general body meeting (GBM) of the Association for Cognitive Science (ACS). GBM is held normally at the annual meeting of ACS and they are the technical sponsors of the summer school.
The Neuroimaging summer school will be held at the IIIT-H campus from July 16-20.