Abstract: Short Term Memory Improvement through Peak Alpha Frequency Enhancement

Sergei Voskoboinik,  Cindy Heaster (Stradina Medical University, Riga, Latvia)

 

Background; Electroencephalographic (EEG) peak alpha frequency (PAF) has been shown to correlate with a variety of characteristics, including age, memory performance in healthy and demented individuals, different emotional states, schizophrenia, anxiety, recovery from stroke, cerebral blood flow velocity, brain oxygenation, as well as acute administration of stimulant substances. Our study focuses on shifting PAF to high alpha, with the aim to enhance short term memory ability and improve reaction time.

Among other phenomena, increased PAF can improve cognition, memory, concentration and reaction time which are related to academic performance.  PAF varies between different days, with individuals showing more increases PAF before the weekend than in the middle of the week.

Method; The dataset involved 10 EEG recording sessions from 2 young, healthy students (each session of duration 15-20 minutes). The affects of training on short term memory were assessed using Sternberg’s Short Term Memory Test (SMT). The typical alpha band (8-13 Hz) was divided into three separate bands. Band "A1"7-9 Hz,"A2"9-11,and "A3"11-13 Hz. The A3/A1 ratio was then examined.

Results; PAF A3/A1 ratio increased during sessions, also it showed significantly lower values in the middle of the week, than on Fridays before the weekend. Results on the SMT test showed improvement in short term memory recall percentage and also in reaction time after training.

Conclusions; It is possible to train PAF, and therefore improve short term memory and reaction time. Training of PAF is more successful on Fridays than on Wednesdays.   

 

                                           1.INTRODUCTION

Electroencephalograhic (EEG) biofeedback is an operant conditioning procedure where by an individual modifies the amplitude, frequency or coherency of the neurophysiological dynamics of their own brain at will1. EEG biofeedback requires that one be mindful of both inner state and the feedback from the machine.

  The human EEG is largely characterized by synchronous oscillating activity, ranging from 0.1 Hz to 100 Hz, when recorded at the scalp, with clinically relevant frequencies being restricted to 1-45 Hz. One EEG phenomena, and the first to be discovered, is the alpha rhythm, between 8-13 Hz recorded mostly at posterior cortical areas of conscious individuals. All activity between 8-13 Hz will be called "alpha".

The alpha rhythm has been extensively studied and its magnitude has been positively associated with states of relaxation and mental inactivity2. ‘Alpha’ is the name assigned to a posterior rhythm and, therefore, reflects activity of the sensory cortex, with similar phenomena being observed in the motor cortex. The reactivity of both alpha and ‘mu’ (Rolandic ‘mu’ is an oscillatory activity recorded over the motor cortex) are equivalent, since both decrease in magnitude during the activity of the underlying cortex, and increase in magnitude during rest of the underlying cortex2. An example of decrease in these values can be during open eyes, and movement of muscles. A state of increased alpha activity has been likened to the state of idle in a car12. It is the state from which you can move quickly and efficiently to whatever ‘gear’ you need to accomplish the task at hand.  When alpha is enhanced, people feel calm and ‘mindful’. Alpha predominates in those who are passively relaxed and in those who are visualizing. It has been shown that enhancement of alpha is associated with lowered anxiety, improved creativity and workload enhancement13, whereas high workloads produce a sustained suppression of alpha, which contributes to an external focus, anxiety and rigidity in problem solving14. It has been suggested12 that a progression from alpha amplitude training to alpha percentage training would help students improve attentional processes, problem solving and creativity.

The usual distribution of alpha rhythm is like bell shaped with an average peak of 10-11 Hz in healthy adults3, but lower in children and elderly. Alpha peak frequency varies in different individuals.

Different formulas have been used to quantify the variation of spectral distribution within the alpha range4. Peak alpha frequency (PAF) measures the discrete frequency with the highest magnitude within the alpha range. PAF is an EEG measure which shows the frequency distribution of magnitude, and therefore should not be compared to EEG alpha magnitude measures. High PAF means that there is more magnitude at the higher part of the alpha spectrum, and vice versa. One way to observe spectral alpha distribution is to divide the alpha spectrum into two frequency bands above and below average peak of 10-11 Hz, e.g. 8-10 Hz (low alpha), and 10-12  Hz (high alpha), and then observe the differential magnitude of this two sub-bands. This is based on assumption that alpha rhythms are generated by at least two independent pacemakers, one oscillating below 10 Hz and one another above 10 Hz. Although the production of the scalp-recorded alpha rhythm is obviously cortical, different theories support cortical and/or thalamic origin of the alpha pacemakers. Some researchers for example suggest a thalamic origin5, whilst others challenge this view and suggest a cortical origin6.  Still some others speculate a combined model, where low alpha generators react to attention and are thalamo-cortical, whilst high alpha generators are cortico-cortical and react to memory activation. Another hypothesis is that alpha can’t be divided and is one not sub-dividable spectrum7; that alpha peak is just shifted from one frequency band to another, depending on activity of the brain.

Several studies have shown PAF to reflect cognitive performance in various areas including attention, arousal, working memory, long-term memory and reading. PAF has also been found to increase during an auditory working memory task in contrast with a control task. It is suggested that PAF may be an index of memory ability3. It was found that lower memory performance corresponded with decreased PAF during increasing memory demands, whereas individuals with higher memory performance had a constant PAF under the same conditions. In a resting state immediately after reading, it was observed that high alpha increased in magnitude with no changes in low alpha3. PAF has been also related to developmental differences in cognitive performance. The same studies found that children with higher reading performance had a PAF similar to that of  older children with equal reading performance, and thus interpreted PAF as a maturational index of the brain.

Another observation is that PAF decrease with increasing age, and can be correlated with speed and performance in a number of cognitive tasks.

In diagnoses of psychiatric and neurological disorders, it has been found that affected patients have reduced PAF compared with age-matched controls, in almost all scalp areas3. Psychiatric syndromes involving decreased PAF include: Schizophrenia, chronic fatigue syndrome, and hemispheric stroke.

 

Peak Alpha Frequencies and Emotional States

PAF has been shown to reflect emotional and/ or autonomic states8. It was found that PAF increases during mental reproduction of joy and anger, and that PAF decreases during fear and sadness, when compared with a neutral baseline. The number of intracortical connections obtained by mapping of EEG data in the alpha range at the moment of maximum emotional tension increased with respect to the background. During mental reproduction of various emotional states the temporal cortical area became the centre of integration.

It has also been found that people suffering from sleep deprivation and higher anxiety levels had higher PAF than controls9. Stimulants such as nicotine and caffeine have been shown to increase PAF, as have meals10.

Improvements in learning ability have been demonstrated in children with brain or mental disorders, whilst playing with dolphins. After spending some time with dolphins it was found that reading, speech and counting abilities were greatly improved in these children. This kind of training showed immediate results in children with learning disabilities, and perhaps demonstrates for us the influence of relaxation and feelings of joy on learning ability.

 

In order to measure the affect of training, the Sternberg Short Term memory Test11 was used. In the Sternberg Short Term Memory test, subjects judge whether a test symbol is contained in a short memorized sequence of symbols and their mean reaction-time increases linearly with the length of the sequence. An improvement in short term memory leads to greater accuracy and decreased reaction time in the test.

 

PAF is an index of cognitive capacity, which depends on different disturbing factors and varies in different brain states. It also shows different results in healthy and clinical individuals. When tested for cognitive performance, clinical individuals are shown to score lower than their matched healthy controls, demonstrating their reduced cognitive preparedness. Moreover, PAF has been shown to depend on developmental stages of reading performance in children. Although it did not reflect intelligence in one large study, PAF has been found to be positively correlated with memory and with the speed of processing between healthy individuals.

Regarding its capacity to reflect states within individuals, PAF has been found to be affected by cognitive tasks, mental reproduction of emotional states, and acute administration of various substances.

Differences in PAF traits and states, between and within individuals, can partly be explained by the correlation between PAF and different levels of cerebral oxygenation. In brain pathology, lower PAF may reflect larger degrees of permanent or long-term in CBF.

The present study suggests that PAF has directional relationship with the emotional state of the brain, and that by increasing PAF, brain performance can be enhanced. This study will show the relationship between increased PAF with short term memory, and emotional states.
2. Method

Two medicinal university students participated in the experiment, one male and one female. Both individuals were healthy with no history of brain injury, brain pathology or clinical syndromes.

The PAF of both individuals was initially recorded in relaxed state, with eyes open.

A single electrode was places at the point Cz, with a grounding electrode attached to each ear lobe. The Cz point has been shown to reflect the activation of attention and working memory.

 

FIGURE 1: Electrode placement.

Measurement from just one point is satisfactory for these measurements, with extra electrodes being necessary only for the measurement of brain synchrony.

The Sternberg Short term memory test was then completed, and changes in PAF recorded for the duration of the test.

The alpha spectrum (from 7 - 13 Hz) was divided into 3 sub-bands; low alpha 7-9 Hz(A1), 9-11 Hz(A2),and high alpha 11-13 Hz(A3). Examination of the A3/A1 ratio has been shown to equate with mental performance. An A3/A1 ratio greater than 1 equates with better than average mental performance, whilst a score below 1 indicates poorer than average performance.

Both individuals had 10 training sessions, with each session lasting 15-20 minutes. After these 10 sessions both individuals again performed the SMT test. All recordings were made with eyes open, in a relaxed position with minimal muscular activity. The individuals were required not to eat, drink coffee or smoke cigarettes for an hour before each training session, in order to reduce disturbing factors which have been shown to influence PAF.

All training sessions and testing was conducted in a dimly lit room with minimal noise and other disturbances.

The 10 training sessions were conducted with the use of Brain Master (Brain Master Technology Inc.). A ‘reward sound’ in the form of a nice click was given when the subject was able to perform an increase in A3 above a certain threshold (set by trainer for each individual) in combination with repression of A1 below the set threshold. Other discriminative stimulus was provided visually on the computer screen which displayed both increases in A3 and decreases in A1.  

The Sternberg Scanning Memory test (SMT) was used to measure improvements in short term memory. The test involves the subject viewing a random series of numbers between 0 and 9. The length of the series occurs in groups of 4,6, or 8 numbers, with each number being displayed for 750ms. Upon completion of a series, a warning signal was given, followed immediately by the test number. Upon presentation of the test number, the subject provided feedback, as to whether or not the test number was included in the series. Both the accuracy of response, and mean reaction time were recorded for the duration of the test, which lasted approximately 15 minutes. The SMT is regarded as one of the best tests for short term memory performance.

 

3.RESULTS

Assessment of short term memory was conducted with use of the Sternberg Scanning Short Term Memory Test (SMT). Changes in the A3/A1 frequency were measured with Brain Master. A shift in PAF to higher values, increases in A3/A1 ratio, decreased reaction time, and increased accuracy on the SMT were regarded as successful results. Of the two subjects, one experienced overall improvement in these areas, whilst the other had no significant imrpovements.

The division of the alpha range into 7-9, 9-11 and 11-13Hz began at the third week of training.

FIGURE 2: A3/A1 ratio. Across training, the A3/A1 ratio was seen to dramatically improve in the subject with an initially lower PAF.

FIGURE 3: Increases in High Alpha, with simultaneous suppression of low alpha was observed most dramatically in the 6th week and onwards, once learning of the task had been accomplished.

 

After Training

Before Training

Length of Series

Accuracy

Speed (ms)

Accuracy

Speed (ms)

4

100.00

0.74

84.40

0.98

6

97.90

0.83

93.80

0.98

8

89.10

0.88

92.20

0.95

Average

95.67

0.8147

90.13333

0.970767

 

FIGURE 4: SMT results for successful training. A 6% improvement in accuracy, and a 16% decrease in reaction time was observed after 10 training sessions.

 

FIRGURE 5

FIGURE 6

Both figure 5 and 6 demonstrate a clear difference between A3/A1 ratios depending on the day of the week, with clearer improvements being seen on Fridays.

The median value across all subjects for A3/A1 ratios was 1.36 for Fridays, and 1.06 for Wednesdays, showing an increase of 28% in the A3/A1 ratio on Fridays.

 

 

 

 

 

 

 

 

 

4. DISCUSSION

In the participant with an initially lower PAF (9Hz), it was demonstrated that improvement in A3/A1 ratio results in enhancement of short term memory. However, the subject with an initially higher PAF (initially of 11Hz, in the high alpha range) showed no significant improvement with training.  Although improvements were seen within each individual training session, these improvements did not carry over to the next training session.

The participant with successful training experienced a 100% increase in the A3/A1 ratio by the end of training, showing a dramatic shift in PAF from the low alpha to the high alpha range. Successful training was demonstrated by better results in the SMT, hence indicating the correlation between improved PAF and short term memory.

Whilst undertaking the study, it was noted that increases in the A3/A1 ratio were more impressive on Fridays than on Wednesdays. Emotional states differ on Fridays and Wednesdays, with a heightened emotional state being shown on Fridays. This finding was not the focus of the study, though became obvious upon data analysis. Differences in high alpha, and learning on the different days of the week could have practical repercussions for the organisation of education programs, with particular relevance to personal study programs. Increases in high alpha correspond with heightened function of short term memory, therefore learning material requiring the use of memory should more effectively be learned on Fridays. Another practical application for this finding could be the simulation of Friday atmosphere to improve learning, i.e. using the promise of a reward to motivate study.

 

 

 

5.CONCLUSIONS

The present study supports the idea that activity of the brain has direct relationship with PAF. As expected, evoking a passively relaxed state increases A3/A1 ratio, with this change resulting in improved short term memory, as proved by the Short Term Memory Test. The A3/A1 ratio can be improved by training.

Emotional states play a role in learning abilities, with a direct correlation seen between emotional state, PAF, and the A3/A1 ratio. .Moreover, we suggest that passive relaxation activities, such as PAF training, in combination with the normal schooling curriculum of children and young adults (students) will enhance academic results due to improvement in short term memory.

However, the weakness of this study was in the small sample size, and lack of a control group. Therefore deductions that brain performance improves with the expectation of a reward is weak and in need of more comprehensive research.

 

 

 

 

 

REFERENCES

1. Thatcher, R. W. (1998). Normative EEG databases and EEG biofeedback. Journal of Neurotherapy, Vol 2(4): 8 – 39

2. Niedermeyer, E. (1999). The normal EEG of the waking adult. In Niedermeyer, E., & DaSilva, E.L. (Eds.) Encephalography: Basic principles, chemical applications, and related fields (4th ed., pp 131-152). Baltimore: Williams & Wilkins.

 

3. Klimesch, W., Schimke H., Ladurner, G. & Pfurtscheller, G. (1990). Alpha frequency and memory performance. Journal of Psychophysiology, 4:381-390.

 

4. Posthuma, D., Neale, M.C., Boomsma, D.I., & de Geus, E.J.C (2001). Are smarter brains running faster? Heritability of alpha peak frequency, IQ, and their interrelation. Behaviour-Genetics 31(6):567-579.

 

5. Andersen, P., & Andersson, S.A. (1968). Physiological Basis of the Alpha Rhythm. New York: Appleton-Century-Crofts.

 

6. Lopes da Silva, F., Van Lierop, T.H.M.T., Schrijer, C.F., & Storm van Leeuwen, W. (1973a). Organization of thalamic and cortical alpha rhythm: Spectra and coherences. Electroencephalography and Clinical Neurophysiology, 35:627-640

 

6. Lopes da Silva, F., Van Lierop, T.H.M.T., Schrijer, C.F., & Storm van Leeuwen, W. (1973b). Essential differences between alpha rhythms and barbiturate spindles: Spectra and thalamocortical coherences. Electroencephalography and Clinical Neurophysiology, 35:641-645

 

7. Pigeau, R.A., & Frame, A.M. (1992). Steady-state visual evoked responses in high and low alpha Subjects. Electroencephalography and Clinical Neurophysiology, 84(2): 101-109.

 

8. Kostyunina, M.B. & Kulikov, M.A. (1995). Frequency characteristics of different emotions: EEG spectral analysis. Zhurnal Vysshei Nervnoi Dyatel’nosti Imeni I P Pavlova, 45(3): 453-457.

 

9. Knott, V.T. (1988). Dynamic EEG changes during cigarette smoking. Neuropsychobiology, 19(1):54-60.

 

10. Tiffin, P., Ashton, H., Marsh, R. & Kamali, F. (1995). Pharmacokinetic and pharmacodynamic responses to caffeine in poor and normal sleepers. Psychopharmacology, 121 (4): 494-502.

 

11. Sternberg, S. (1966). High-speed scanning in human memory. Science, 153, 652-654.

 

12. Norris, S.L. & Currieri, M. (1999) Performance enhancement training through neurofeedback. Introduction to Quantitative EEG and Neurofeedback pp. 223-253. Academic Press.

 

13. Hardt, J.V. & Kamiya, J. (1978). Anxiety change through electroencephalographic alpha feedback seen only in high anxiety subjects. Science 201, 79-81.

 

14. Sterman, M.B., Mann, C.A., Kaiser, D.A. & Suyenobu, B.Y., & Brandall, Y. (1994). Multiband topographic EEG analysis of simulated visuomotor aviation task. Int. J. Psychophysiology 16:49-56.

 

Nunez, P.L., Wingenier, B.M., & Silberstein, R. B. (2001). Spatial-temporal structures of human alpha rhythms: Theory, microcurrent sources, multiscale measurements, and global binding of local networks. Human Brain Mapping, 13:125-164.

 

Budzinski, T.H., Jordy, J., Budzynski, H., Tang, H., & Claypoole, H. (1999). Academic performance enhancement with photic stimulation and EDR feedback. Journal of Neurotherapy, 3(3):11-21.

 

Osaka, M., Osaka N., Koyama, S., Okusa, T., & Kakigi, R. (1999). Cognitive Brain Research. 8(3):365-368.

 

Lindgren, M., Molander, L., Verbaan, C., Lunell, E., & Rosen, I. (1999). Electroencephalographic effects of intravenous nicotine: A dose-response study. Psychopharmacology, 145(3):342-350

 

Newman, F., Stein, M.B., Trettau, J.R., Coppola, R., & Uhde, T.W. (1992). Quantitative electroencephalographic effects of caffeine in panic disorder. Psychiatry Research, 45(2):105-113.

 

 

Klimesch, W., Schimke H., & Pfurtscheller, G. (1993). Alpha frequency, cognitive load, and memory performances. Brain Topography, 5(3):241-251.

 

Kostyunina, M.B. (1998). Human EEG during mental reproduction of emotionally significant events. Zhurnal Vysshei Nervnoi Dyatel’nosti Imeni I P Pavlova, 48(2): 213-221.

 

Shen MW, Yi YJ, Xu Q (2002) Study on sensitivity of event-related EEG sychronization and desychronization visual memory load  Space Med Med Eng (Beijing) Dec;15(6):445-7.