New Tinnitus-Detecting Research Combines Electrodes & Algorithms


New research published in the journal, PLOS ONE, reveals for the first time how disorder, marked by phantom ringing and other noises, can be detected by using a brain imaging technique called functional near-infrared spectroscopy, or fNIRS. 

Previously, different functional imaging techniques had been used to analyze brain areas related to tinnitus. These include electroencephalography (EEG), magnetoencephalography (MEG), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI). This study marks the first time fNIRS was assessed to determine tinnitus and its severity. 

The technique uses light to measure oxygen level and activity in the brain. The detection of tinnitus was also assessed by a computer algorithm. In the experiment, 25 volunteers with chronic tinnitus wore a special cap with 16 detectors covering all areas of the brain. The cap is designed to shine light into specific areas of the head and record the reflected light. The amount of light reflected differs when the body is in a rested state, i.e. sleep, in comparison to when the brain responds to noise. 

Different noise stimuli also reflect light in differing amounts. For example, so-called “pink noise” (think: a soothing, cascading small waterfall) differs from loud, cacophonic sounds (heavy metal music). The research also analyzed reflected light from visual stimulus.  

Recording parts of the brain that get activated in the presence of visual stimuli is important because several studies of tinnitus patients have found reduced activity in an area of the brain’s occipital region called the cuneus, which is involved in visual processing. If there is an abnormality in the auditory cortex due to tinnitus, the cuneus may function abnormally. reports that in those with tinnitus, the “temporal-occipital connectivity showed a significant increase with subject ratings of loudness.” The imaging also showed which cortical regions are active in tinnitus such as the auditory cortex and frontal cortex. 

Based on which regions of the brain are more active, the computer algorithm would play doctor, diagnosing the pattern of tinnitus as well as its severity. 

According to the study, the infrared technique and algorithm was over 78% accurate in determining that the participants had tinnitus. As for the algorithm itself, it was even more impressive in accuracy, correctly analyzing tinnitus over 87%. 

Despite the preliminary success of the study, there is one drawback: the near-infrared light is incapable of reaching the deepest parts of the cortical regions. Furthermore, tinnitus isn’t a one-size-fits-all diagnosis; there are different patterns of the condition, however, the cap can only assess whether someone has general tinnitus. 

However, the researchers note in their study that “fNIRS has great potential to transform clinical practice as it is non-invasive and non-radioactive (unlike PET) and, importantly for routine clinical use, is quiet, portable and cost-effective.”

And although MRIs are also able to detect and measure changes in blood oxygen levels in the brain, “fNIRS has better temporal resolution and does not produce scanner noise[,] making it more suited to hearing[-]related research.”

So what, if anything, does the new research offer for the approximately 15% of all Americans who experience some level of tinnitus? For starters, by being able to objectively measure the severity of the condition, the technology may one day be able to assess whether or not a patient is improving. The researchers involved with the innovative technique are hopeful that new treatments are developed because of their work.

This research falls on the heels of two other tinnitus therapies: tongue electro-stimulation therapy combined with ambient electronic music and oxytocin nasal spray.


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