Neuroimaging study for learning Morse code

Functional MRI studies have widened our view on what is going on in various cognition and behaviors. Remembrance of Morse code and, possibly, reading through it are not the exceptions. This paper tells us learning Morse code, one of the lexico-semantic skills, produces increased connectivity between the language networks and the anterior salience networks. As an amateur for those neuroimaging studies as well as brain physiology, I could not give proper explanation on this result. However, learning Morse code seems to be involved with the connection of sensory, emotional and cognitive functions with language acquisition functions.

In conversational CW, this change may be augmented or progressed to further combinations of neural networks. I have a hypothesis that conversational CW requires higher functions of the brain than simply deciphering codes. I could never be involved with such studies. Hopefully, some CW lover as well as neuroimaging researcher at the same time would be interested in epistemological understanding of conversation through Morse code, the simplest symbols in communication, and conduct some research work. If you would do this, just remember and acknowledge me in the end of the paper.

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Neuroimage. 2017 Feb 1;146:429-437. doi: 10.1016/j.neuroimage.2016.08.065. Epub 2016 Sep 1.

Dynamic changes of resting state connectivity related to the acquisition of a lexico-semantic skill.

Schlaffke L1, Schweizer L2, Rüther NN3, Luerding R4, Tegenthoff M2, Bellebaum C5, Schmidt-Wilcke T2.

Author information

Abstract

The brain undergoes adaptive changes during learning. Spontaneous neural activity has been proposed to play an important role in acquiring new information and/or improve the interaction of task related brain regions. A promising approach is the investigation of resting state functional connectivity (rs-fc) and resting state networks, which rely on the detection of interregional correlations of spontaneous BOLD fluctuations. Using Morse Code (MC) as a model to investigate neural correlates of lexico-semantic learning we sought to identify patterns in rs-fc that predict learning success and/or undergo dynamic changes during a 10-day training period. Thirty-five participants were trained to decode twelve letters of MC. Rs-fMRI data were collected before and after the training period and rs-fc analyses were performed using a group independent component analysis. Baseline connectivity between the language-network (LANG) and the anterior-salience-network (ASN) predicted learning success and learning was associated with an increase in LANG - ASN connectivity. Furthermore, a disconnection between the default mode network (DMN) and the ASN as well as the left fusiform gyrus, which is critically involved in MC deciphering, was observed. Our findings demonstrate that rs-fc can undergo behaviorally relevant changes within 10 training days, reflecting a learning dependent modulation of interference between task specific networks.

Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.