Forgetting things may sometimes be overlooked. But the persistence of the problem may be screaming a greater disease. Alzheimer’s disease is seldom predicted early, and later diagnosis is not of much use. However, scientists from the Penn State in collaboration with those from the Mayo College of Medicine, Rochester, Minn. say that an individual’s brain capacity to retain information is a reliable predictor of Alzheimer’s disease and can be cheaply and easily tested.
Mild cognitive impairment (MCI) is a condition that impacts language, memory and related mental capabilities. It is different from the usual ordinary mental degradation caused due to aging and may be a more serious Alzheimer’s disease. Both MCI and Alzheimer’s are said to be connected to a constant depletion in the volume of the hippocampus and the area of the brain responsible for the long term memory and spatial reasoning.
“We have developed a low-cost behavioral assessment that can clue someone in to Alzheimer’s disease at its earliest stage. By examining (information) processing capacity, we can detect changes in the progression of mild cognitive impairment (MCI),” remarked Michael Wenger, associate professor of psychology at Penn State.
Scientists are of the opinion that MRIs (Magnetic Reasonance imaging), are the most trusted and direct way of detecting hippocampal atrophy and diagnose MCI. However, many individuals may find the treatment far too expensive and equally unavailable.
Wenger further added that, “MRIs can cost hundreds of dollars an hour. We created a much cheaper alternative, based on a memory test, that correlates with hippocampal degradation.”
With the help of a computer image of the hippocampal atrophy, the team determined how to estimate the capacity with a statistical measure of how fast can the tasks be completed. By applying these findings to a memory test for people with MCI, the scientists were able to understand their hippocampal capacity and compare it to the progression of their disease.
“My collaborators at the Mayo Clinic backed up this study with MRIs for the MCI group. These capacity measures we developed showed a reliable relationship to the hippocampal volume measurements, so we know we are on the right track,” comments Wenger.
The study began with the modeling of the hippocampus as a complex electrical circuit Equations. This circuit controlled the electric current and voltage by mimicking the electrical firing of neurons within the circuit. The team then turned off neurons in the simulation to model atrophy of the hippocampus.
With less number of cells available to process electrical signals, the model hippocampus deteriorated. However, the capacity for processing information went down at an even faster rate. Capacity was the most sensitive measure of how the hippocampus was failing more than the average processing speed.
Wenger explained that, “We then applied this to the gold standard of the field — the Free and Cued Selective Reminding Test (FCSRT). This is a test that can discriminate between normal age-related memory changes and changes caused by impairment.”
The study was then administered on five groups of participants, which included college students, healthy middle-aged adults, healthy elderly individuals and people with diagnosed cases of MCI. There was also a control group of age-matched individuals without MCI. The first three groups comprised of 100 members and the last two each had 50 members.
During the FCSRT, participants were shown descriptive words like ‘part of the body’ and ‘artery’, and were asked to pick those pictures that fit these cues from a set of 24 images. The picture used in this case was the picture of a heart. The scientists then asked the participants to recall as many items as they could possibly. Incase of items not recalled, participants were provided with category cues. These cues were provided with intentions to test the limits of the subjects’ capacity.
The team then analyzed the response time for the tasks and the number of items that were recalled, with and without additional cues. It was discovered that the MCI group was the most sensitive to the added cues. The additional input for the MCI group either helped them considerably or inhibited their performance. Nevertheless, like the computer model, estimates of capacity threw light on the cognitive differences between the MCI group and the other groups.
It seems that this study’s approach to define processing capacity is different. The team combined the disparate principles of engineering and statistics, mathematically translating processing capacity into something known as the ‘hazard function’. This ‘hazard function’ is quite popular in engineering, but seems to be new to the subject of psychology. It signifies the probability of the completion of a task in the next time interval.
By calculating the time taken for a participant to recall the objects during FCSRT, the scientists designed a model based on the hazard function for each participant and derived the capacity for the memorization task.
The difference between the hazard function measurement between MCI and the other groups was statistically more prominent that the difference between all groups in the number of items they recalled. These hazard function differences also outweighed the contrasts between all groups in their response times. The hazard function model proved to be the most sensitive diagnostic for cognitive distinctions in the groups. It appears to be a trustworthy indicator of capacity and also a better signal of the underlying hippocampal atrophy as compared to only processing speed.
Wenger remarked that, “These results are still preliminary, but very encouraging. We plan to study what this approach can tell us about mental impairments related to other conditions, like iron deficiencies, in the future.”
The results garnered from the study are valid for each participant and not just for the whole group. As the modified FCSRT takes into consideration the personal reaction time, hazard analysis and performance, it is capable of tracking MCI for anyone. Moreover, the test does not even require access to a computer.
The results of the study are to be published in the current issue of the Journal of Mathematical Psychology.