The Effect of Binaural Beats on Synchronization to a ... - CCRMA

The  Effect  of  Binaural  Beats  on   Synchronization  to  a  Pacing  Stimulus   Final  Project  for  Music  251  

Roy  Fejgin   CCRMA,  Stanford  University  

Introduction Background Tapping  experiments  have  been  widely  used  to  study  sensorimotor  synchronization  (SMS)  in  humans.  The  topic  is  of   interest  since  several  important  functions  are  involved,  such  as  mental  timekeeping,  acting  in  response  to  a  stimulus,   and  the  coordination  of  the  auditory,  visual  and  motor  systems  [1].    Moreover,  SMS  is  essential  to  activities  such  as   music  playing  and  dancing,  allowing  the  performer  to  stay  in  sync  with  other  performers.  The  task  often  used  in  SMS   experiments  is  tapping  to  a  periodic  beat  (a  “pacing  stimulus”).  Tapping  seems  to  be  a  good  choice  since  it  is  simple,  and   involves  contact  with  a  surface,  which  mimics  the  interaction  with  instruments  such  as  keyboards  and  percussion.   Binaural  beats  have  been  the  topic  of  study  since  the  early  20th  century.  The  phenomenon  occurs  when  two  tones  are   presented  to  a  subject,  one  to  each  ear.  If  the  tones  are  at  neighboring  frequencies  (with  a  difference  of  up  to  about  35   Hz),  the  subject  perceives  a  beating  effect  –  periodic  variation  of  loudness  -­‐  at  the  frequency  of  the  difference  between   the  tone  frequencies  [3].  For  example,  if  one  tone  is  at  440  Hz  and  the  other  at  447  Hz,  beating  is  perceived  at  7  Hz.  It   should  be  stressed  that  beating  is  perceived  even  though  there  is  no  beating  in  actual  stimuli  signals  (unlike  regular   acoustic  beating).     Binaural  beats  have  generated  much  interest  due  to  some  evidence  they  can  entrain  brainwaves.  That  is,  exposure  to   binaural  beat  stimulation  causes  an  increase  in  EEG  brainwave  activity  at  the  beating  frequency.  Brainwave  activity  at   particular  frequency  bands  is  correlated  with  specific  states  of  consciousness.  For  example,  the  Theta  band  (4-­‐8Hz)  is   with  drowsiness  or  deep  meditation;  Beta  activity  (13-­‐30Hz)  is  associated  with  waking  state  and  active  concentration.   Therefore,  there  is  reason  to  believe  through  the  mechanism  of  entrainment  we  can  use  binaural  beats  to  alter  one’s   state  of  consciousness.  

Problem Statement The  purpose  of  this  experiment  is  to  explore  the  effect  of  binaural  beats  on  tapping  performance.  To  the  best  of  my   knowledge,  previous  tapping  experiments  have  been  carried  out  without  regard  for  the  subject’s  state  of  consciousness.   Assuming  binaural  beats  can  indeed  alter  one’s  state  of  consciousness,  we  can  use  them  to  test  tapping  at  various   states.  

In  this  experiment,  performance  on  two  types  of  tapping  tasks  was  measured.  The  first  was  paced  tapping,  meaning   tapping  along  with  a  pacing  stimulus.  The  second  –  unpaced  tapping  –  involves  first  acquiring  a  tempo  using  paced   tapping,  then  continuing  to  tap  without  the  pacing  stimulus.  For  both  tasks,  the  key  parameter  measured  was  tap  error,   which  was  defined  as  the  difference  between  the  beat  time  and  the  subject’s  actual  tap  time.  Statistical  measures  such   as  the  mean  tap  error  and  standard  deviation  were  then  computed  from  the  tap  error.   The  hypothesis  was  that  subjects  would  exhibit  different  tapping  performance  depending  on  the  frequency  of  the   binaural  beats  to  which  they  were  exposed.  

Method Stimuli and Task Each  subject  performed  three  rounds  of  a  task,  each  round  time  at  a  different  binaural  beat  frequency.  A  round   consisted  of  three  sections.  First,  binaural  beats  mixed  with  white  noise  were  played  for  130  seconds.  Next,  with  the   beats  and  noise  continuing,  a  pacing  stimulus  was  introduced  and  the  subject  requested  to  tap  to  it  (“paced  tapping”).   This  went  on  for  40  seconds.  Finally,  the  pacing  stimulus  was  removed  and  the  subject  was  requested  to  continue   tapping  (“unpaced  tapping”).  That  section  was  5  seconds  long.  The  audio  signal  was  then  stopped  for  a  few  seconds   while  the  operator  adjusted  the  beat  frequency,  and  then  the  next  round  was  performed.   The  binaural  beats  were  generated  using  two  tones.  The  tone  presented  to  the  left  ear  was  always  at  440  Hz.  The  tone   presented  to  the  right  ear  was  at  higher  by  either  0  Hz,  6  Hz  (later  5  Hz,  see  the  section  ‘experiment  versions’),  or  17  Hz.   The  first  round  was  always  at  0  Hz,  that  is,  the  tones  presented  to  both  ears  were  at  the  same  frequency  and  thus   generated  no  binaural  beating.  This  was  done  in  order  to  get  a  baseline  for  the  subject’s  performance  before  being   exposed  to  any  binaural  beats.  The  order  of  the  beat  frequencies  in  the  remaining  rounds  was  randomized.   The  noise  that  was  mixed  with  the  binaural  beats  was  white  noise,  low-­‐pass  filtered  with  a  cutoff  frequency  of  2000  Hz.   The  purpose  of  the  noise  was  twofold.  First,  it  was  meant  to  make  the  binaural  beats  more  pleasant  to  listen  to.  Second,   the  presence  of  the  noise  made  it  harder  for  the  subject  to  become  aware  of  the  beating  -­‐  or  lack  of  beating  during  the  0   Hz  round,  allowing  an  effective  control  round.   The  pacing  stimulus  was  a  beep  presented  once  per  second  (1  Hz).  The  beep  was  a  100  ms  tone  at  777  Hz.  The  main   consideration  in  selecting  that  frequency  was  to  ensure  that  the  pacing  stimulus  would  be  easily  audible  in  the  presence   of  the  noise  and  binaural  tones.  It  was  selected  by  trial  and  error.  It  was  easy  to  hear  because  it  is  neither  close  to  the   frequencies  of  the  binaural  tones,  nor  a  multiple  of  those  frequencies.   The  subject  tapped  on  to  the  pads  of  a  MIDI  controller.  The  MIDI  events  were  sent  to  a  computer  running  ChucK,  where   their  timestamps  were  recorded.  The  ChucK  program  calculated  the  tap  error  by  subtracting  the  tap  timestamp  from  the   stimulus  timestamp,  and  then  compensating  for  system  latencies.  The  following  sections  go  into  detail  regarding  the   experimental  setup.          

Setup and Software

  Figure  1:  Experiment  Setup  

  The  setup  consisted  of  a  Macintosh  laptop  running  ChucK,  a  MIDI  controller,  a  microphone  placed  near  the  MIDI   controller,  and  a  pair  of  headphones.   The  MIDI  controller  employed  was  an  M-­‐Audio  Axiom  25,  which  has  pads  as  inputs.  The  pads  turned  out  to  be  a   convenient  and  accurate  interface  for  capturing  the  taps,  since  they  are  designed  for  percussion.  The  taps  generated   MIDI  events  that  were  sent  over  a  USB  interface  to  the  laptop.    A  microphone  was  placed  on  the  tapping  surface  and  connected  to  the  laptop’s  analog  input.  On  the  laptop,  the  ChucK   program  redirected  the  microphone  input  back  out  to  the  headphones.  The  purpose  of  the  microphone  was  to  give  the   subject  auditory  feedback  for  their  taps.  It  would  have  otherwise  been  difficult  for  the  subject  to  hear  their  taps  in  the   presence  of  the  loud  sound  (noise,  binaural  beats,  and  pacing  stimulus)  generated  by  the  headphones.   The  laptop  ran  a  ChucK  program  written  for  this  experiment.  The  program  executes  a  complete  round  (binaural  beats  -­‐>   paced  tapping  -­‐>  unpaced  tapping)  without  need  for  user  intervention.  Between  rounds,  the  operator  saves  the  test   results,  select  the  next  beat  frequency,  and  restarts  the  test.     When  MIDI  tapping  events  are  received,  the  program  records  their  timestamp.  At  the  end  of  a  round,  the  program   processes  all  tap  events  and  associates  each  event  with  the  closest  pacing  stimulus  (or,  in  the  cased  of  unpaced  tapping,   with  the  time  when  the  pacing  would  have  occurred).  When  a  pacing  stimulus  is  associated  with  more  than  one  tap,  the   program  discards  the  taps  as  invalid.  Finally,  the  program  calculates  some  statistics,  for  example:  the  mean  and  STD  of   tap  errors  during  the  paced  section,  and  the  same  for  the  unpaced  section.  

System Latency and Jitter The  tap  timing  error,  the  key  parameter  measured  in  the  experiment,  was  defined  as  the  difference  between  the  pacing   beat  time  and  the  tap  time.  In  practice,  however,  it  is  not  straightforward  to  measure  this  time  difference  due  to   multiple  unknown  (and  variable)  delays  present  in  the  system.  Among  these  are:  delay  caused  by  the  buffering  of  output   audio  samples  in  the  OS;  delay  introduced  by  the  USB  interface;  MIDI  event  processing  latency;  other  events  occurring  in   the  system  such  as  network  interface  IO,  activity  in  other  processes,  etc.   In  order  to  estimate  the  overall  latency  and  latency  jitter  in  the  system,  the  following  technique  was  employed.  A   simplified  version  of  the  ChucK  program  used  in  the  experiment  was  created.  The  simplified  program  generated  a  few   beeps  and  recorded  the  timestamps  of  the  input  MIDI  events.  In  addition,  a  microphone  was  placed  where  it  could   capture  both  the  sound  of  the  stimulus  and  sound  the  subject’s  finger  hitting  the  pad.  On  the  laptop,  the  audio  from  the   microphone  was  recorded  to  a  .wav  file.   The  resulting  waveform  was  then  visually  examined  in  an  audio  editing  program.  By  measuring  the  distance  between   peaks  in  the  waveform,  an  accurate  stimulus-­‐response  delay  was  determined,  free  of  any  error  introduced  by  system   delays.  Comparing  the  measured  delay  to  the  stimulus-­‐response  delay  observed  by  the  ChucK  program  allowed   calculating  the  system  latency.   The  above  procedure  was  repeated  five  times.  The  observed  system  latencies  were  all  the  range  of  11  to  15  ms.  A  value   of  13  ms  was  selected  as  the  system  latency  estimate.  When  running  the  actual  experiment,  13  ms  were  subtracted   from  all  tap  timestamps  in  order  to  compensate  for  the  system  latency.  

Experiment Versions After  testing  the  first  eleven  subjects  and  looking  at  the  preliminary  results,  it  was  clear  that  the  results  were  not  as   expected.  The  expectation,  based  on  the  three  people  tested  before  the  pilot,  had  been  that  average  tap  errors  and   STDs  would  be  lower  for  the  higher  beat  frequency.  However,  the  error    with  6  Hz  beats  was  -­‐42  ms  when  averaged   across  all  taps  and  all  subjects,  as  compared  to  -­‐44  ms  for  17  Hz  beats.    Given  the  large  variations  in  tap  errors  among   subjects  and  the  small  data  set,  this  difference  did  not  appear  to  be  significant.   At  this  point  I  re-­‐examined  the  experiment  in  search  of  problems.  I  decided  to  make  two  adjustments:  change  the  lower   beat  frequency  from  6  to  5  Hz,  and  reduce  the  level  of  the  filtered  noise  in  the  mix.  Five  more  subjects  were  tested  with   the  new  parameters.   The  first  change  was  made  in  an  attempt  to  ensure  that  the  binaural  beat  was  at  a  frequency  that  would  not  periodically   align  with  the  tap  frequency  of  1  Hz.  In  retrospect,  I  do  not  believe  that  the  change  from  6  to  5  Hz  ensures  that.  See  the   following  sections  for  further  examination  of  the  topic.   The  second  change,  lowering  of  the  noise  level,  was  made  in  an  attempt  to  ensure  that  the  binaural  beats  are  not   masked  by  the  noise  to  such  and  extent  that  their  effect  is  lost.   In  the  sections  below,  the  first  set  of  parameters  is  referred  to  as  version  1  (v1)  and  the  second  as  version  2  (v2).    

Results and Analysis

Median  of  Average  Tap  Error  (ms)  

Paced Tapping

Mean  Tap  Error,  Paced,   Median  Across  All  Subjects   (v1+v2)   0.00  

Binaural  Beat  Frequency   0  Hz  (no  beafng)  

5  or  6  Hz  

17  Hz  

-­‐20.00   -­‐40.00   -­‐60.00  

-­‐34.85  

-­‐39.96  

-­‐49.70  

  Figure    2:  Median  of  all  subjects’  mean  tap  error,  paced  case.  

In  the  paced  tapping  task,  the  mean  tap  error  was  computed  for  each  subject.  Figure  2  shows  the  median  of  all  subjects’   mean  tap  error.  We  see  that  the  tap  error  magnitude  with  a  17  Hz  binaural  beat  frequency  was  larger  than  the  tap  error   with  at  lower  beat  frequencies  (5  and  6  Hz).  However,  this  result  should  not  be  interpreted  as  conclusive  evidence  that   tapping  accuracy  is  improved  with  low-­‐frequency  binaural  beat  stimulation.  Figure  3  helps  understand  why.  It  shows  the   individual  subjects’  results.  We  can  see  that  five  subjects  performed  better  with  6  Hz,  four  performed  better  with  17  Hz,   and  one  performed  similarly  with  both  beat  frequencies.  Thus  there  is  no  clear  trend  of  better  performance  with  any  of   the  frequencies.  For  version  2,  the  results  are  more  consistent:  out  of  five  subjects,  four  performed  better  with  5  Hz   stimulation.  However,  given  the  small  sample  size  in  version  2  and  the  large  variability  of  the  tap  errors,  we  should  be   cautious  in  drawing  any  conclusions  from  the  last  result.   Surprisingly,  the  greatest  difference  found  was  between  the  tap  error  without  any  binaural  beats  (0  Hz  -­‐  baseline)  and   either  of  the  tests  with  binaural  beats.  This  finding  does  is  not  in  agreement  with  the  hypothesis:  we  would  expect  the   baseline  result  to  be  somewhere  in  between  the  results  for  the  two  other  tests,  reflecting  the  random  state  of  mental   activity  with  which  subjects  entered  the  experiment.  I  suggest  two  possible  explanations  for  this  finding.   First,  it  is  possible  that  the  binaural  beats  were  actually  acting  as  an  additional  pacing  stimulus  (and  thus  making  tapping   easier),  since  they  complete  an  integral  number  of  periods  for  every  beat  of  the  pacing  stimulus.  The  change  from  6  to  5   Hz  between  version  1  and  version  2  did  not  fix  that  problem.  A  better  solution  would  be  to  use  a  fractional  frequency  for   the  binaural  beats,  such  as  5.1  Hz.  A  fractional  frequency  would  ensure  that  the  binaural  beats  do  not  complete  an   integral  number  of  periods  every  1  second  (the  rate  of  the  pacing  stimulus).  As  a  result,  the  phase  relationship  between   the  binaural  beat  and  the  pacing  stimulus  would  be  constantly  changing,  so  the  binaural  beat  would  no  longer   contribute  to  pacing.   Another  possible  explanation  for  the  better  tapping  accuracy  with  binaural  beats  is  that  perhaps,  on  average,  the   subjects  entered  the  experiment  at  high  levels  of  concentration,  with  considerable  brainwave  activity  at  frequencies  

above  17  Hz.  If  that  were  indeed  the  case,  it  would  explain  the  results  since  both  binaural  beat  stimulations  would  work   in  the  same  direction  of  reducing  the  dominant  brainwave  frequencies.  It  is  worth  noting  that  most  subjects  had  been   studying  immediately  before  taking  part  in  the  experiment,  so  high  levels  of  concentration  would  not  be  surprising.  

 

 

Figure  3:  Mean  Tap  Error  By  Subject  

 

Unpaced tapping Though  not  the  intended  focus  of  this  study,  an  interesting  find  was  a  consistent  difference  between  paced  and  unpaced   tapping  performance.  In  paced  tapping,  all  subjects  showed  a  negative  mean  tap  error.  That  is,  on  average  they  all   tapped  before  the  beat  time.  In  unpaced  tapping,  on  the  other  hand,  some  subjects  tapped  before  the  beat  time  (on   average)  while  others  after  it,  but  in  general  they  tended  to  tap  later  than  during  paced  tapping:  in  25  of  31  (81%)  of  all   rounds  executed  with  binaural  tapping  the  mean  tap  error  was  smaller  (more  negative)  for  paced  tapping.  When   including  the  baseline  round  (no  binaural  beat)  the  percentage  drops  to  64%.     Figure  4  demonstrates  these  results  for  the  17  Hz  case.  

 

  Figure  4:  Mean  Tap  Error:  Paced  versus  Unpaced  

Other Observations It  is  interesting  to  note  that  both  the  two  most  accurate  tappers  play  percussion  instruments.  

 

   

Conclusions The  experiment  did  not  find  conclusive  evidence  for  an  effect  of  binaural  beats  on  tapping  performance.  However,  I   would  like  to  point  out  some  limitations  of  the  current  paradigm,  and  suggest  ways  in  which  the  question  could  be   further  explored.   First,  this  experiment  was  constrained  by  the  limited  availability  of  subject  test  time.  Since  all  subjects  were  volunteers   and  were  not  compensated,  the  experiment  had  to  be  short.  As  a  result,  an  entrainment  time  of  only  two  minutes  was   used.  Previous  research  on  binaural  beats  employed  much  longer  entrainment  duration  (such  as  20  minutes,  see  for   example  [4]).  Extending  the  entrainment  time  would  important  in  order  to  ensure  entrainment  is  actually  taking  place.   Along  the  same  line,  monitoring  the  subject’s  EEG  would  be  very  useful.  Direct  evidence  of  the  level  of  entrainment   would  enhance  our  confidence  in  the  results.  Also,  it  would  allow  us  to  discern  which  subjects  are  susceptible  to   entrainment,  and  which  are  not.  Naturally,  the  latter  subjects  should  not  be  considered  when  evaluating  the  effect  of   entrainment  on  tapping  accuracy.   Lastly,  the  relationship  between  the  binaural  beat  frequency  and  the  pacing  stimulus  frequency  should  be  given  more   attention.  As  described  in  the  results  section,  use  of  a  fractional  binaural  beat  frequency  with  an  integral  pacing   frequency  could  help  minimize  the  contribution  of  the  binaural  beats  to  pacing.    

Acknowledgement I  would  like  to  thank  Nori  Jacoby  for  suggesting  the  latency  measurement  technique;  Jonathan  Berger  and  Jieun  Oh  for   their  helpful  suggestions  regarding  the  experiment  design;  Xiang  Zhang  for  letting  me  use  his  MIDI  controller  in  the   experiment  setup;  Sean  Colvin  for  suggesting  to  explore  the  relationship  between  the  pacing  and  beat  frequencies;  and   classmates  and  other  people  at  CCRMA  for  voluntarily  participating  in  the  experiment.  

References [1] Patel, A. D., Iversen, J. R., Chen, Y., & Repp, B. H. (2005). The influence of metricality and modality on synchronization with a beat. Experimental Brain Research, 163, 226-238. [2] Repp, B. H. (2005). Sensorimotor synchronization: A review of the tapping literature. Psychonomic Bulletin & Review, 12(6), 969992. [3] Licklider, J. C. R., Webster, J. C., Hedlun, J. M. On the frequency limits of binaural beats. Journal of the Acoustical Society of America., 1950, 22, 468-473. [4] Russel, H., Turow, G. “Rhythmic sensory stimulation of the brain: The possible use of inexpensive sensory stimulation technologies to improve IQ test scored and behavior.” The Rhytmic Brain: Music, Ritual and Healing. Ed. Jonathan Berger and Gabe Turow. (forthcoming).