3dExtrema has a number of functions that are done by default, but are not what you want to do exactly. Using these additional options below, you should find the maximum location:

% 3dExtrema -volume -mask_file amy_rs+tlrc. -closure -sep_dist 512 func_slim+tlrc'[0]'
++ 3dExtrema: AFNI version=AFNI_2009_12_31_1431 (Sep 29 2010) [64-bit]
++ Authored by: B. Douglas Ward
Reading mask dataset: amy_rs+tlrc.
Number of voxels above mask threshold = 34
Reading input dataset: func_slim+tlrc[0]
Reading input dataset: func_slim+tlrc[0]
Reading volume #0
Number of volumes = 1

Maxima for Volume #0 (Coordinates Order = RAI):
Index Intensity RL[mm] AP[mm] IS[mm] Count Dist[mm]
----- --------- ------ ------ ------ ----- --------
1 7.893 22.00 9.00 -12.00 3

Compare this output to similar results using a couple other AFNI programs, 3dmaxima or 3dclust.

First, some additional preparation of the datasets:

% 3dresample -prefix amy_rs -master func_slim+tlrc. -input 'TT_Daemon::amygdala'
% 3dcalc -a func_slim+tlrc'[0]' -b amy_rs+tlrc. -expr 'a*step(b)' -prefix func_amy


% 3dmaxima -min_dist 512 -input func_amy+tlrc.
---------------------------------------------
RAI mm coordinates:

( 22.00 9.00 -12.00) : val = 7.893089

number of extrema = 1
---------------------------------------------


% 3dclust 0 1 func_amy+tlrc.
++ 3dclust: AFNI version=AFNI_2009_12_31_1431 (Sep 29 2010) [64-bit]
++ Authored by: RW Cox et al
#
#Cluster report for file func_amy+tlrc.
#[Connectivity radius = 1.00 mm Volume threshold = 64.00 ]
#[Single voxel volume = 64.0 (microliters) ]
#[Voxel datum type = short ]
#[Voxel dimensions = 4.000 mm X 4.000 mm X 4.000 mm ]
#[Coordinates Order = RAI ]
#[Fake voxel dimen = 1.000 mm X 1.000 mm X 1.000 mm ]
#Mean and SEM based on Absolute Value of voxel intensities:
#
#Volume CM RL CM AP CM IS minRL maxRL minAP maxAP minIS maxIS Mean SEM Max Int MI RL MI AP MI IS
#------ ----- ----- ----- ----- ----- ----- ----- ----- ----- ------- ------- ------- ----- ----- -----
18 21.8 5.7 -15.5 18.0 30.0 1.0 9.0 -20.0 -8.0 2.0679 0.4451 7.8931 22.0 9.0 -12.0
16 -23.3 5.5 -14.8 -30.0 -18.0 1.0 9.0 -20.0 -8.0 1.7386 0.2269 3.8732 -22.0 5.0 -16.0
#------ ----- ----- ----- ----- ----- ----- ----- ----- ----- ------- ------- ------- ----- ----- -----
# 34 2.5 5.6 -15.2 1.9129 0.2566


Note 3dClust returned the maximum values from two clusters, so that's a little different.