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Laboratory
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BNS(607) –
Windows On The Brain

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Fall 2017

 

 

 

Electroencephalogram
(EEG) is a noninvasive powerful tool for neuroscience researches, especially
for the human brain researches. It provides a high temporal resolution. The
event related potential (ERP) technique utilizes advantages of EEG and locks
the EEG signals to an event. Thanks to this properties, the method opens a
window to see how the human brain processes the environment. The spatial
navigation is one of them.

Topographical
N170 (NT170) has been shown that it encodes goal directed spatial
processing. In the virtual T-maze, the subjects navigates to find rewards. No
matter whether they find reward or not, the evoked ERP by the feedback following
right turn occurs 5-10 ms faster than this following left turn. The waveform
shares similar properties with N170 evoked by face recognition tasks in which
the ERP is generated around 170-190 ms, the most strongly at PO8 channel as a
negative deflection1. However, when the spatial
cues are removed, the delay between right and left disappears2. This shows that the signal
is related to the spatial navigation. In addition to this evidence, the source
localization points around parahippocampal region. Hippocampus and
parahippocampus are important structures for coding the location of the body
and the location of objects with respect to each other34. The cells in this region
have been shown to respond by increasing firing rate to landmarks associated to
the navigational goals5. It also shown that the
information is coded by phase of theta oscillation and firing rate in the
hippocampal region6. Time-frequency analysis also
shows that phase resetting, which is associated with the parahippocampal and
hippocampal activity, happens faster when the subject turns right than left2.

People utilize
different properties of the environment while they navigate. Egocentric and
allocentric frames are two of the properties. Egocentric navigation defines the
locating objects with respect to the body and allocentric navigation utilizes
the object and there relative position7. However, egocentric
navigation contributes to allocentric because when someone enters a place (i.e.

room), the space is firstly framed by egocentric perspective. The saccade is
imperative part of the navigation. The objects are mapped with respect to the body.

There is also evidences for gaze centered frame used for the spatial
representation8. In this experiment design,
the subjects fixes their gaze to the center of the screen and no body or body
part or head movement is required.

In these
experiments, the NT170 was presented in egocentric frames which means the
subjects being able to conceptualize the maze have the NT170 whereas the
subjects cannot conceptualize the maze does not evoke NT1702. However, there is an ongoing
debate whether the spatial navigation is egocentric or allocentric7. Thus, this debate raises
intriguing question of whether the NT170 encodes the egocentric or allocentric
navigation.

Methods

7 people
participated the experiment. All 3 males and 4 females were right handed and
aged between 18 and 28 with average of 20.85 and standard deviation of 3.35
. 6 of them were undergrad students in Rutgers University and one was in a
graduate program in Rutgers University. All of them were given consent.

A virtual T maze was used. While the subject was looking through the
stem, he/she made a choice to turn toward right or left alley. At the end of
the alley, reward or no reward was indicated by apple or orange. The walls and
floor of the maze constructed of bricks. The color of bricks in each alley and
stem were slightly different so that the participant can navigate and this was
providing the egocentric frame. The reward and no reward cases were randomized.

The main manipulation was the environment of the maze. The true maze was
introduced with the true background of the right alley consisting of a big
mountain and this of left alley was a small mountain and this was providing the
allocentric frame. However, 20% of the time, the backgrounds were switched so
that the big mountain was presented on the left alley background and the small
mountain on the right alley. The session was starting with introduction the
maze and environment from different perspective, then the trails started with 1000
ms start image which was the stem of maze followed by a double arrow for
informing the participant to make a selection. The

Figure
1
Figure 1 The maze and alleys. a) Broad view of the maze. b) An example of true
right alley with the big mountain and the reward indication. c) An example of
true left alley with the small mountain and the no reward indication. d)
Mismatching background on right alley. e) Mismatching background on left alley

subject was able
to turn the right alley by pressing 9 and the left alley by pressing 1 on the
keyboard. After introducing the selected alley for 500 ms, the reward or no
reward indicator appeared for 1000ms. A blank screen was presented for 1000 ms
to indicate the end of trail. The participants were given a questionnaire to
see if they comprehend the structure of maze so that they were navigating
through the maze.

10-20 montage
system was used. Fp1, Fpz, Fp2, F3, Fz, F4, FC1, FCz, FC2, C3, Cz, C4, P3, Pz,
P4, PO7, Oz, PO8 electrodes were used in the recording. Two mastoid electrodes
were used as reference. Horizontal eye movements were recorded from the
external canthi of right and left eyes. Vertical eye movements were recorded
via suborbit of the right eye and Fp2 electrode so that electroocular artifacts
were rejected and corrected. AFz was the ground electrode. Nasion and inion
were used to align head cap in anterior posterior orientation and preauricular
points were used to center the Cz on the mediolateral axis. The sampling rate
was 1 kHz, and the amplifier had 0.017-67.5 Hz bandpass filter. The electrode
impedances were maintained below 20 k?. Brain Vision Recorder (Brain
Products GmbH, Munich) software was used to record.

Brain Vision
Analyzer (Brain Products GmbH, Munich) software was used to process data. The
data was filtered with 2th order Butterworth bandpass filter with 0.1 and 30 Hz
cutoff frequency. The EEG data was segmented between 200 ms before and 800 ms
after the onset of feedback. EOG interference was corrected by Gratton’s method
and the data rereferenced to average of all electrodes. Baseline correction was
done based on the prestimulus period. Artifacts were rejected if the voltage
step was bigger than 20 µV/ms and the voltage change bigger than 100 µV in each
epoch.

The reward
positivity (RP) was evaluated based on the local minimum between 200 and 400 ms
at the frontal electrodes (FCz)9. N170 happens most
significantly at PO8 electrode and NT170 latency was measured as the time of
minimum peak between 100 and 250 ms and its amplitude was measured as peak
difference of its peak amplitude and the peak amplitude of first positive
deflection between 50 and 150 ms.

Averaged ERPs of
each subjects were used for statistical analyses of latency and amplitude.

t-test was conducted to compare significance of the effect of the each case.

The amplitude analyses for the NT170 were done as difference between N170 and
P1 amplitudes.

 

 

Results

Table 1 The number of trials
in each analysis condition. High frequency trials stands for “true background”
and low frequency for “wrong background”.

Figure
2
Grand average of reward – no reward in true and false background trials at FCz
channel. (Red: Reward in true background; Black: no reward in true background;
Blue: Subtraction of no reward from reward in true background trails; Green:
Reward in false background; Pink: no reward in false background; Yellow:
Subtraction of no reward from reward in false background)

Figure 3
The mean amplitudes and error bars of NT170 at each electrode.

In Figure 2, the average of no-reward cases have a bigger negative
deflection than the reward cases in both true background (TB) and false
background (FB). Although latency of no-reward peak in FB looks delayed than
that in TB, there were not significantly different in paired t-test of
differences waves (p > 0.5). The amplitudes of difference waves also do not
show statistically significant difference (p > 0.05).

Because the
NT170 has the highest value at PO8 channel, this channel is used for the rest
of the NT170 analyses.

Figure 4
The evoked N170 in true and false background trails are pooled at PO8
channel (Blue: Navigators right turn; Pink: Navigators left turn; Green:
Nonnavigators right turn; Brown: Nonnavigators left turn; Black: Grand left
turn; Red: Grand right turn)

In Figure 4, the grand average (all participants are pooled together)
of right turn (red) and grand average of left turn do not show much difference
and they hide the nonnavigators N170. When the nonnavigator participants were
analyzed, the N170 wave becomes very small(Brown and green). Furthermore, when
we pool the TB and FB, the NT170 delay is not so visible in the navigators
group.

Figure
5
Comparison NT170 of navigators in true and distorted background. (Left: Overall
view of the ERP; Right: Narrower time axis)  (Black: Right turn in true background; Blue:
Left turn in true background; Red: Right turn in false background; Green: Left
turn in false background)

When we analyze
the true back ground and the false background trails, the difference between
evoked NT170 becomes significant in navigators group. In Figure 5, blue and
black lines shows the delay of evoked potential when the navigators turned left
in comparison to right turn in true background by blue and black line,
respectively. The NT170 happens around 10 ms faster in the right turn trials
than the left turn. However, when we compare the red and green line
representing right turn and left turn in false background, respectively, the
difference significantly reduces.

The latency
detection for two subjects was not successful. The detected N170 latencies for
them were 103 ms and 109 ms while the P1 latencies were detected as 143 and 143
ms, respectively. So these subjects were excluded from the statistical analysis
of NT170 latency analysis in true background trails.  The peak latencies of N170 for right and left
turn in true background do not statistically differ from each other (p>0.5).

Although, the differences are not significant, the mean and standard deviations
are shown in Figure 6. The latency analysis for left – right turn in false
background does not show significant difference, too (p>0.1). The mean and
standard deviations are shown in Figure 6. 

Figure
6
Mean and standard deviations of N170 latencies of navigators’ right and left
turn in true background (Left) and false background (Right)

The peak
amplitudes of N170 when the navigators turn right and left in true background
do not significantly differ (p>0.5). Likewise, the right-left turn
amplitudes are not significantly different in false background trials
(p>0.1). The means and standard deviations are shown in Figure 7.

Figure
7
Amplitudes of NT170 when the participants turn right or left (Left: True
background, Right: False background)

 

 

Figure
8
Comparison of evoked wave in nonnavigators in true and false background. (Blue:
Right turn in true background; Black: Left turn in true background; Green: Right
turn in false background; Red: Left turn in false background)

In Figure 8, although
the number of nonnavigators is only two, we do not see a similar evoked wave to
that of the navigators. In addition, the left – right turn and true – false background
do not show significant difference.

Discussion

The experiment
showed that the NT170 is related to the navigation and it has the biggest
momentum at channel PO8. The questionnaire at the end of the sessions enable us
to differentiate the participants who realized the structure of virtual T maze
and who could not. This paradigm revealed that the navigation is essential part
of the NT170. The participants failing to recognize the right and left alley of
the maze did not evoked the N170. On the other hand, all the participants had
the reward positivity at channel FCz so they were aware of the reward and
no-reward cases. In other words, they had the goal to receive the reward. As a
necessary of the navigation, the goal is induced to the participants5. This showed us navigation is
essential for NT170.

On top of all,
the NT170 was affected by the alteration of the background of the alleys. Although,
the statistics could not show the difference between the delays of right turn
and left turn in both true background and false background, the grand average
graphs reveal the big change. Because of the small sample size, the variance
between the subjects reduced the power of the analysis. While the N170 peak was
happening around 10 ms earlier in the right turn trails in comparison to the
left turns in the true background trials, this delay obviously reduced when the
backgrounds were switched.

Parahippocampus
plays critical role in the navigation and spatial representation. The source
localization study pointed this region in the virtual T maze navigation2. The region is also shown in
the PET scan that this region and some other regions are active while the
subject explores an environment, if there are objects. However, the other
activated regions are active except the parahippocampal region  in the case of exploring the region without
objects3. This shows that
parahippocampal region is critical for allocentric frame reference. So, the
reduced NT170 delay might be related to the distraction of the theta resetting
in the hippocampal navigational coding by the parahippocampal allocentric frame
coding sent to the hippocampus.

In another
study, the single cell recording in humans shows that even though some
overlaps, the majority of hippocampal cells response to the spatial location of
the subject in a virtual maze and majority of the parahippocampal cells
response to the spatial locations of the landmarks. Thus, the hippocampus might
be combining the visual and spatial location information with allocentric
information form parahippocampus5.

When we consider
the findings from the single cell study and the PET scan study, the
parahippocampus is the main responsible in the coding of allocentric
representation of a space. In our experiment, the navigator subjects were able
to recognize the right and left alley so they were aware of their spatial
locations. In other words, we were not altering their egocentric location in
the maze. Although they were not aware of the change of the mountains in the
background, the reduced NT170 delay showed that it is related to the
allocentric navigation.

Another
advantage of our experimental paradigm is that the participants do not have to
move their gaze to navigate toward the reward. They mainly just focus to the
center of the view field. Therefore, when a reward is presented on the right,
it is not presented on their right field of their view. This also reduces the
interference of egocentric frame reference which is an important paradigm in
the studies of allocentric navigation researches7.

The single cell
and other studies (for review, see 7) show that egocentric and
allocentric frame reference partially overlay in parahippocampus and
hippocampus. As a next step, the experiment can be conducted with more
participants. In order to alter the egocentric reference and see the effect on
NT170, the tiles in the left alley and right alley can be switched in some
trials.

References

1          T. E. Baker and C. B. Holroyd, “Which
way do i go? neural activation in response to feedback and spatial processing
in a virtual t-maze,” Cereb. Cortex, vol. 19, no. 8, pp. 1708–1722,
2009.

2          T. E. Baker and C. B. Holroyd, “The
topographical N170: Electrophysiological evidence of a neural mechanism for
human spatial navigation,” Biol. Psychol., vol. 94, no. 1, pp. 90–105,
2013.

3          E. A. Maguire, C. D. Frith, N.

Burgess, J. G. Donnett, and J. O’Keefe, “Knowing Where Things Are: Parahippocampal
Involvement in Encoding Object Locations in Virtual Large-Scale Space,” J.

Cogn. Neurosci., vol. 10, no. 1, pp. 61–76, 1998.

4          E. A. Maguire, R. S. Frackowiak, and
C. D. Frith, “Learning to find your way: A role for the human hippocampal
formation,” vol. 263, no. 1377, pp. 1745–1750, 1996.

5          A. D. Ekstrom et al., “Cellular
networks underlying human spatial navigation,” Nature, vol. 425, no.

6954, pp. 184–188, 2003.

6          J. O’Keefe and N. Burgess, “Dual phase
and rate coding in hippocampal place cells: Theoretical significance and
relationship to entorhinal grid cells,” Hippocampus, vol. 15, no. 7, pp.

853–866, 2005.

7          F. Filimon, “Are All Spatial Reference
Frames Egocentric? Reinterpreting Evidence for Allocentric, Object-Centered, or
World-Centered Reference Frames,” Front. Hum. Neurosci., vol. 9, no.

December, pp. 1–21, 2015.

8          K. Fiehler, I. Schütz, and D. Y. P.

Henriques, “Gaze-centered spatial updating of reach targets across different
memory delays,” Vision Res., vol. 51, no. 8, pp. 890–897, 2011.

9          W. H. Miltner, C. H. Braun, and M. G.

Coles, “Event-Related Brain Potentials Following Incorrect Feedback in a
Time-Estimation Task,” J. Cogn. Neurosci., vol. 9, no. 6, pp. 788–798,
1997.

 

 

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