Does The Brain Register 10hz

Research article
Open Access
Published: 05 March 2006

x Hz flicker improves recognition retentivity in older people

BMC Neuroscience volume 7, Article number:21 (2006) Cite this article

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Abstract

Background

x Hz electroencephalographic (EEG) alpha rhythms correlate with memory performance. Blastoff and memory decline in older people. Nosotros wished to examination if alpha-like EEG activity contributes to retention formation. Flicker can arm-twist alpha-like EEG activity. We tested if alpha-frequency flicker enhances memory in older people. Pariticpants aged 67–92 identified short words that followed i due south of flicker at 9.0 Hz, ix.v Hz, 10.0 Hz, x.2 Hz, 10.five Hz, 11.0 Hz, xi.5 Hz or 500 Hz. A few minutes later, nosotros tested participants' recognition of the words (without flicker).

Results

Flicker frequencies shut to x Hz (9.5–11.0 Hz) facilitated the identification of the test words in older participants. The aforementioned flicker frequencies increased recognition of the words more than other frequencies (ix.0 Hz, 11.5 Hz and 500 Hz), irrespective of age.

Decision

The frequency-specificity of flicker'south effects in our participants paralleled the ability spectrum of EEG alpha in the general population. This indicates that alpha-like EEG activeness may subserve memory processes. Flicker may be able to help memory problems in older people.

Introduction

The primary electroencephalographic (EEG) rhythmic deadening activity (RSA) – the 10–12 Hz alpha rhythm – relates to memory functions in healthy adults [1–7]. Alpha power may relate peculiarly to episodic memory [8, nine]. It diminishes in former age [10] and in Alzheimer's disease [11–14], but anti-dementia drugs can increment it [15, xvi]. Earlier workers viewed EEG alpha rhythms every bit merely epiphenomenal [17, 18]. More than recent work has shown that EEG activity has a causal role in psychological functions [19–21], including memory [22, 23]. This piece of work is the basis of our study.

Creature studies provide experimental testify that EEG rhythms may attune retentiveness. Rhythmic slow action (RSA) in the hippocampus facilitates long-term potentiation (LTP) [24, 25], the likely neural substrate of memory [26]. Modulating RSA using drugs can heighten memory [27, 28]. Brain stimulation that elicits RSA can besides enhance retention [22, 23]. Moreover, the behavioural effects of RSA modulation are exquisitely frequency specific [21, 29]. This frequency-specificity excludes the possibility that the stimulation alters behaviour non-specifically (eastward.g. by metal ion deposition). Taken together, the findings of drug and stimulation studies indicate that RSA tin can enhance retentivity.

To test if EEG rhythms tin enhance memory in human being, we need to attune them experimentally. Flickering light induces frequency-locked EEG activeness that tin resemble endogenous alpha [30, 31]. Flicker may even induce alpha-like activeness [32]. Nosotros previously showed that alpha-frequency flicker could enhance memory [33]. Moreover, the flicker effects were highly frequency-specific: x.0 Hz flicker enhanced recognition, but viii.7 Hz and 11.7 Hz were ineffective. This frequency-specificity makes it very unlikely that the flicker in our previous study modulated retention by non-specific mechanisms. Instead, our previous findings supported the view that alpha-frequency EEG activity may contribute to memory formation.

In older people, a autumn of simply 0.5 Hz in the endogenous alpha frequency with peak power relates to memory impairment [34]. Nosotros previously studied effects of flicker only at 8.7 Hz, 10.0 Hz or eleven.vii Hz in immature adults [33]. The showtime goal of the present report was to test the frequency-specificity of flicker's effects on memory at a higher resolution. If flicker alters memory by eliciting EEG alpha-like activity, then frequencies very shut to the main EEG alpha frequency should enhance retention maximally. Nosotros tested this hypothesis by comparison flicker frequencies in 0.five Hz steps around 10.2 Hz – the endogenous EEG alpha frequency with peak ability [35]. Specifically, nosotros tested if simply flicker in the key range of endogenous blastoff frequencies, shut to 10.2 Hz, would enhance recognition, every bit in our previous study.

Our earlier study used a unmarried low intensity of flicker at participants' fixation point. The present study used iii intensities of flicker in the peripheral visual field. Higher intensities should elicit larger alpha-like EEG activeness. Our second goal was to test if whatever memory-enhancing effects of peripheral flicker would show a "dose-response" relation with its intensity

Flicker can arm-twist large blastoff-similar EEG action in healthy older people [36]. Yet, the amplitude and frequency of endogenous EEG alpha autumn with historic period [35]. This fall is greater in those with balmy memory problems [34]. This could take two possible corollaries for flicker's effect on retentiveness. Age-related impairments in encephalon systems that subserve EEG action might make older peoples' memories unresponsive to flicker. Conversely, if flicker-stimulated EEG activity tin can replace or restore endogenous alpha rhythms, and so flicker'due south effects might be stronger in older people with poorer memories. Our final goal was to choose between these alternatives. To this end, we tested if flicker's furnishings depended on age.

In our study, flicker at nine.v–xi.0 Hz (close to the frequency of alpha that shows elevation power in the general population) facilitated the identification of brusque words during the initial 'learning stage' of the study. The aforementioned flicker frequencies enhanced the recognition of the words a few minutes later on in the 'exam phase'. Both the above effects were frequency-specific: command flicker frequencies (9.0 Hz 11.5 Hz, and 500 Hz) farther from the central blastoff frequency had no effects. These results support our hypothesis that blastoff-like EEG rhythms contribute to memory in older people.

Results

Participant characteristics

The participants' median historic period was 78.5 years (range 67 to 92). 16 were men. The median MMSE score was thirty (range 28–30) and the median recall score in the HVLT was 29 (range 25 to 35).

Learning phase

Overall, participants identified 90% of the 48 real-word trigrams in the learning phase (median correct = ninety%, inter-quartile range 82–93%). The older participants (aged over 80) tended, non quite significantly, to identify fewer real words than the younger (t = -ane.78, 1400 df, p = 0.085). However, flicker frequencies close to 10.ii Hz (9.5–ten.five Hz) restored the older participants' accurateness in identifying real words to that seen in the younger (Figure 1) (Quadratic trend of frequency-within-flicker × Age: t = -2.12, 1400 df, p = 0.03).

Examination phase

As we predicted, flicker frequencies close to ten.2 Hz increased later on recognition of the real words from the learning phase (see Figure two) (Quadratic trend of frequency-within-flicker: t = -two.thirteen, 1400 df, p = 0.017, i-tailed). Moreover, this effect showed an intensity-response relation (Linear trend of intensity × quadratic trend of frequency-inside-flicker: t = -2.17, 1400 df, p = 0.015, 1-tailed).

Participants were less probable to recognize real words in the test stage that they had not identified during the learning stage. Hence, error rates in the two phases correlated (Spearman'due south ρ = 0.forty, p = 0.03). Nosotros therefore tested if flicker's furnishings on recognition in the exam stage were independent of its effects on identification in the learning phase. To this end, we covaried identification in the analysis of recognition. Even then, the quadratic trends over frequency-inside-flicker remained significant (Quadratic trend of frequency-within-flicker: t = -1.79, 1399 df, p = 0.037, one-tailed. Linear trend of intensity × quadratic trend of frequency-within-flicker: t = -1.69, 1399 df, p = 0.045, 1-tailed).

Give-and-take

Flicker induces frequency-locked EEG activeness over a wide range of frequencies, just maximally at the frequencies of the endogenous alpha rhythm (10 Hz) and its harmonics [31, 37]. We presented flicker during memory encoding and constitute that only frequencies closer to 10.two Hz –the endogenous alpha frequency with peak power – enhanced later recognition. Our study provides a stringent test of our a priori hypothesis that only flicker frequencies close to the height frequency of endogenous alpha would enhance memory. Our control frequencies (9.0 Hz and 11.5 Hz) are within the range of EEG alpha, but endogenous alpha power at these frequencies is normally less than that at frequencies closer to 10.2 Hz [35]. Hence our results support the hypothesis (encounter Introduction) that flicker-induced alpha-similar EEG activity selectively facilitates neural mechanisms of memory.

The present report did non record EEG responses. Our previous study showed stimulus- and frequency-locked EEG responses to flicker [33]. Even so, this does not testify that flicker contradistinct recognition by modulating EEG activity directly, because flicker tin elicit endogenous alpha [32]. The peak power of endogenous alpha varies within and between individuals [35]. Our unpublished analyses found important variation between individuals' responses to different flicker frequencies. Including this variation in the half-logit glmmPQL improved the model (reduced its Aikake Data Benchmark past 4.3%) and slightly increased the significance of the fixed effects. However, fifty-fifty if blastoff-frequency flicker enhanced memory by eliciting endogenous alpha, this would support our hypothesis that alpha-similar EEG action contributes to retentivity formation. Our results are thus consequent with previous work [38, 39] indicating that flicker can probe the functions of EEG rhythms. Even if flicker's effects on retention were even more indirect (e.g. via changes in mood or arousal – see below), the frequency-specificity of flicker's effects – with effective frequencies centred on 10.2 Hz, the frequency of endogenous alpha with top ability – makes it hard to ascribe flicker's effects to mechanisms that practice non relate to brain EEG-similar activity. Therefore, our results also support the wider view (see Introduction) that EEG activity is not merely epiphenomenal, simply tin cause psychological states [19–23].

Our memory task was difficult and recognition was at chance levels in the control condition. This makes the flicker-induced enhancement of retentiveness more striking. In effect, flicker close to ten.2 Hz caused recognition where in that location was none without information technology. We have previously shown that 10.0 Hz flicker enhanced recognition retentivity in young adults [33]. The present written report supports and extends those previous findings past showing that flicker frequencies close to 10.two Hz can enhance retention in cognitively-good for you older people. Moreover, before work [38, 39] showed that gamma-frequency flicker elicited gamma-similar activity and facilitated the perception of Kanisza figures. Taken together, the present and previous results back up the view that flicker-evoked EEG action tin have functional effects paralleling those of endogenous EEG rhythms.

The frequency-specificity of flicker'southward effect on memory showed an intensity-response relation. This was consistent with our expectation, since more than intense flicker should elicit larger EEG alpha-like action. The present LEDs were brighter than the flicker in our previous study [33], where flicker was key. In the present report, the LEDs were in the peripheral visual field and many participants reported that they were unaware of them during the examination. The fact that peripheral flicker can heighten memory ways that it may be easier to use flicker for this purpose outside the laboratory.

Our recognition task tested episodic memory. The stimuli were all short words in common use and the chore was to remember if they had occurred earlier in the paradigm. Our finding that flicker close to 10 Hz enhanced this episodic recognition retentivity parallels the ascertainment that retentivity tasks which emphasise episodic retentivity elicit EEG alpha synchronization [viii, 9]. A plausible mechanism for this enhancement is that flicker-induced rhythmic EEG activity may increment "gain" within recurrent cortico-cortical and cortico-thalamic loops [forty, 41]. A second possibility is that the flicker-induced activity may facilitate long-term potentiation (LTP) in the hippocampus [24–26, 42], which subserves episodic memory [43]. Our report cannot illuminate the neural mechanisms of filcker'due south effects. Even so, it can exclude the possibility that flicker altered recognition indirectly, via conditioning. This is because, if item flicker frequencies had unconditioned reinforcing properties, and so flicker should influence the recognition of words that precede information technology, not of those that follow information technology. Nosotros found no effect of flicker on retentiveness for the preceding words (unpublished analyses). Previous work has shown that flicker does not influence subjective mood, but may influence alertness [44]. This may fit with findings that EEG rhythms relate to attentional switching in man [45] and rodents [46]. Hence, if flicker-elicited EEG activity simulates endogenous alpha, this could facilitate memory via attentional mechanisms.

The duration of flicker stimulation in each trial was only i s. The fact that such short-elapsing stimulation could heighten recognition may exist consequent with evidence that endogenous alpha ability synchronises simply briefly during memory encoding [vii]. On the other hand, the interval between flicker epochs was simply 1 southward and photic stimulation effects may persist over this time [32]. Further studies should exam if the elapsing and timing of flicker alter its effects on memory. For now, we note that the efficacy of short-duration flicker has a practical corollary. It makes it easier to written report flicker's effects using within-participant designs to control stringently for non-EEG effects of flicker, as hither.

Flicker frequencies shut to 10.2 Hz enhanced the identification of real words in the learning phase just in older participants (anile over lxxx). Consequent with our previous report [33], flicker did non modify the identification of real words during the learning phase in younger participants. A probable mechanism of the enhanced identification that we found here is that flicker but accelerated responding in older participants, since they presumably knew the stimulus words equally well as the younger ones. Such elementary acceleration could apparently restore older participants' accuracy. Any its mechanism, this observation further supports the view that flicker frequencies most 10 Hz can raise psychological processing. It as well indicates that onetime age may amplify, rather than prevent, flicker's effects. The enhancement of retentivity by flicker frequencies shut to 10.2 Hz was contained of performance in the learning phase. It was also independent of historic period. It is tempting, therefore, to speculate that ten Hz flicker may help memory problems in older people. Cholinesterase inhibitors facilitate EEG alpha rhythms [15, 16]. Our results suggest that this facilitation may underlie their anti-dementia furnishings. If so, our nowadays results raise the possibility that flicker at frequencies close to 10 Hz could supplement or supplant the furnishings of cholinesterase inhibitors in patients with early dementia.

Participants and methods

Participants

All procedures complied with the Helsinki Declaraion and received prior approval from the Central Oxford Research Ethics Committee (COREC #1656). We recruited 30 cognitively healthy participants from the Foresight-Challenge cohort (meet [47]). Exclusion criteria were a history of epilepsy or caput injury (to minimise any risk of photosensitive seizures – [48]). Participants underwent the Mini Mental State Exam (MMSE – [49]) and Hopkins verbal learning exam (HVLT – [50]) a yr earlier the nowadays study.

Exam paradigm

Tests used a desktop computer in a windowless room with fluorescent lighting. The reckoner screen displayed examination items about its middle, in white messages ii.five cm loftier. 18 red (wavelength = 625 nm) light-emitting diodes (LEDs) (Kingbright 50-813ID, office number 179-026 Farnell InOne, Culvert Road, Leeds LS12 2TU), in two 3 × 3 arrays measuring three.iii × 3.three cm, stood on top of the screen. Each LED had a maximum luminance of 150 millicandelas, and emitted maximum light of 0.72 Lux. A flicker generator could drive the LEDs to flicker at nine.0 Hz, 9.5 Hz, x.0 Hz, 10.2 Hz, 10.5 Hz, 11.0 Hz, 11.5 Hz and 500 Hz (no discernible flicker). The flicker's waveform was triangular. The computer programmed flicker at these eight frequencies and at three intensities (maximal light = 0.24, 0.48 and 0.72 Lux), in a balanced design.

The test items were iii-alphabetic character character strings (trigrams) in consonant-vowel-consonant format. We created two pools of well-nigh 400 trigrams. The commencement consisted of iii-letter words in common utilize. This pool excluded salient trigrams (eastward.m. Sex activity) and uncommon words (due east.g. FEZ, which we used for practice items). The second pool consisted of about 400 nonsense trigrams (due east.chiliad. GEC). For each participant, the computer drew 96 trigrams, without replacement, from the pool of existent common words and 48 trigrams from the nonsense pool.

The job had 3 phases: practice, learning and test. There were ten trials in the practice, 48 in the learning, and 48 in the exam phases. Each trial lasted 2000 ms. For the kickoff 250 ms, the calculator screen was bare. Then, a pair of fixation crosses appeared for 250 ms, 3 cm on either side of the screen's center. Finally, a pair of trigrams replaced the fixation crosses. The screen displayed the trigrams in majuscule letters i.5 cm loftier and about ane.2 cm broad: the eye letters of each trigram occupied the locations of the fixation crosses. The trigrams remained on the screen for 1500 ms, until the beginning of the next trial. Trials in the learning stage began with one thousand ms of flicker, when the screen was bare. This continued for 500 ms before and 500 ms after the trigrams appeared. Participants held the computer mouse in both hands with a thumb on each of its buttons. They could respond by pressing 1 of the buttons. The estimator simply recorded responses made between 250 ms after the appearance of the trigrams and the beginning of the next trial.

Test procedure

All participants began with a practice run that presented 10 pairs of trigrams. In each pair, ane trigram was a real word and the other was a nonsense combination. We asked participants to identify the real give-and-take and printing the button on that side. Participants could only progress to the learning phase if they achieved 80% right responses during the practice phase. If participants did not achieve eighty% immediately, we recycled the do stimuli a maximum of 3 times. The practice used 10 uncommon real 3-letter of the alphabet words (eastward.g. FEZ) that did not occur in the test, afterward.

The learning phase gave participants the opportunity to learn 48 real-discussion trigrams. Information technology presented 48 pairs of trigrams, each with one real and ane nonsense word. The program randomly assigned the real give-and-take in each pair to appear the right or left side of the screen. We asked participants to identify the real give-and-take and click the push on the same side. We told them that we would test their retention for the real words after. A 1000 ms period of flicker preceded the appearance of each pair of trigrams past 500 ms (run across above). The reckoner varied the frequency and intensity of the flicker in a quasi-random, just balanced, pattern that was unique for each participant. Hence, 6 pairs of trigrams followed presentation of flicker at each frequency, with 2 at each frequency-intensity combination.

The test phase followed about 2 minutes after the learning phase. In that location was no flicker during the test. The computer presented 48 pairs of real words. One give-and-take of each pair was 'old', from the learning phase, and the other was 'new' in the test. Any real-discussion trigram could be old or new, for different participants. The plan randomly assigned the position of the old word to right or left. The participants' task was to cull the sometime word they had seen in the test phase past pressing the mouse push button on that side. The computer counted right responses to the old trigrams, according to the flicker frequency that had preceded each during the learning stage.

Statistics

All analyses used the R programming language [51]. Nosotros analysed our repeated-measures binary response information using generalised linear mixed modeling via penalised quasi likelihood (glmmPQL) [52] to estimate flicker frequency effects within participants. Our task had a forced-selection response format, and so participants must score at gamble (50%) if they cannot identify or recognise the target words. Therefore, our glmmPQL used a one-half-logit transformation of the logistic [1/2 + 1/2(logit)] equally its link role [53]. We used half-logit glmmPQL to analyse the identification of existent words in the learning stage, and the recognition of the same real words in the exam phase.

The one-half-logit regressions centred age at eighty years and included interaction terms of flicker with historic period and intensity. They first fitted a term to exam for frequency-not-specific effects of flicker by comparing trials with no discernible flicker (500 Hz) to all those with flicker in the alpha range (ix.0–eleven.5 Hz, combined). This term tests whether discernible flicker has overall effects that are non frequency-specific. The design then nested orthogonal terms coding linear and quadratic trends over flicker frequency within the non-specific flicker term. The quadratic trend stringently tests the hypothesis that merely flicker frequencies shut to ten.ii Hz would enhance memory.

To test if higher LED intensity would increase frequency-specific flicker effects, we included the interactions of the linear and quadratic trends over flicker frequency with the LED intensity. To test if flicker'due south effects vary with participants' historic period, we included the interactions of the polynomial trends over flicker frequency with age. The analyses included random intercepts and accounted for the temporal autocorrelation of errors over trials by modeling the mistake matrix with an car-correlation structure of order 1 [54].

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Acknowledgements

Nosotros thank the members of the Foresight-Claiming cohort who took part and the staff of OPTIMA who organised the tests. We too give thanks Professor Brian Ripley for advice on the statistical analysis and Martyn Preston for constructing and calibrating the flicker generator. JHW received support from The Takayama Foundation and AO from The Health Foundation.

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Authors and Affiliations

OPTIMA, Radcliffe Infirmary, Woodstock Road, Oxford, OX2 6HE, United kingdom

Jonathan Williams, Deepa Ramaswamy & Abderrahim Oulhaj
Dept. of Psychiatry Unit Two, Christian Medical College, Vellore, 632002, Bharat

Deepa Ramaswamy

Corresponding writer

Correspondence to Jonathan Williams.

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Authors' contributions

JHW conceived the study and wrote the Pascal program to perform information technology. DR recruited participants and guided them through the procedure. AO wrote the half-logit link office for the glmmPQL procedure. JW and DR wrote the manuscript. All authors read and approved the final manuscript.

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Williams, J., Ramaswamy, D. & Oulhaj, A. ten Hz flicker improves recognition memory in older people. BMC Neurosci 7, 21 (2006). https://doi.org/ten.1186/1471-2202-seven-21

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Received: 31 Baronial 2005
Accepted: 05 March 2006
Published: 05 March 2006
DOI : https://doi.org/10.1186/1471-2202-7-21

Keywords

Episodic Memory
Learning Stage
Existent Word
Quadratic Trend
Alpha Rhythm