Table 5.
Summary Tables for Multiple Regression Analyses
PredictorsRepeatedManipulatedNovel
βtsrβtsrβtsr
(A) Multiple regression analyses with brain region volumes as predictors for the proportion of fixations directed to the critical object ROI in each test condition
CA1 −.567 −1.869 −.325 −500 −1.847 −.287 −.439 −1.465 −.252
Subiculum .478 1.725 .300 .381 1.542 .240 .303 1.106 .190
DG/CA23 .016 0.063 .011 −.131 −0.591 −.092 .096 0.391 .067
PRC .321 1.420 .247 .133 0.661 .103 .336 1.502 .259
alERC .252 1.264 .220 .464* 2.607 .405 .420* 2.131 .367
pmERC −.239 −0.940 −.164 .074 0.328 .051 −.163 −0.647 −.112
PHC .460* 2.114 .368 .484* 2.497 .388 .098 0.456 .079
F(7, 22) = 1.566, p = .198 F(7, 22) = 2.775, p = .031 F(7, 22) = 1.672, p = .168
R2 = .333, Radj2 = .120 R2 = .469, Radj2 = .300 R2 = .347, Radj2 = .140

(B) Multiple regression analyses with brain region volumes as predictors for the proportion of fixations directed to the empty ROI in each test condition
CA1 −.266 −0.838 −.153 .112 0.347 .064 −.140 −0.415 −.080
Subiculum .110 0.380 .069 .171 0.580 .108 −.028 −0.091 −.018
DG/CA23 .338 1.299 .237 .184 0.694 .129 .431 1.560 .302
PRC −.372 −1.573 −.287 −.247 −1.027 −.191 −.299 −1.189 −.230
alERC .405 1.942 .354 .302 1.419 .263 −.062 −0.279 −.054
pmERC −.031 −0.117 −.021 .095 0.352 .065 .027 0.096 .019
PHC −.223 −0.981 −.179 −.307 −1.327 −.246 −.173 −0.716 −.139
F(7, 22) = 1.161, p = .364 F(7, 22) = 1.006, p = .454 F(7, 22) = 0.663, p = .700
R2 = .270, Radj2 = .037 R2 = .242, Radj2 = .001 R2 = .174, Radj2 = −.089

(C) Multiple regression analyses with brain region volumes as predictors for the test/study ratio in each test condition
CA1 −.354 −1.174 −.203 −.177 −0.534 −.102 −.246 −0.781 −.141
Subiculum −.113 −0.410 −.071 .527 1.739 .331 .348 1.211 .219
DG/CA23 .317 1.282 .222 −.347 −1.276 −.243 .274 1.062 .192
PRC −.193 −0.859 −.149 .181 0.731 .139 .385 1.639 .296
alERC −.276 −1.392 −.241 .050 0.230 .044 .083 0.403 .073
pmERC .025 0.099 .017 −.412 −1.486 −.283 −.429 −1.629 −.295
PHC −.146 −.673 −.117 .223 0.940 .179 −.051 −0.227 −.041
F(7, 22) = 1.616, p = .183 F(7, 22) = 0.801, p = .595 F(7, 22) = 1.227, p = .330
R2 = .340, Radj2 = .129 R2 = .203, Radj2 = −.050 R2 = .281, Radj2 = .052

PredictorsalERC PHC
βtsrβtsr
(D) Multiple regression analyses with MoCA, age and viewing to the critical object ROI in the manipulated condition (object-in-place memory) as predictors for alERC and PHC volume
MoCA .358* 2.148 .347   .132 0.741 .127
Age .052 0.312 .050   −.258 −1.452 −.250
Proportion of fixations to critical object ROI .438* 2.711 .438   .355* 2.062 .355
F(3, 26) = 4.115, p = .016   F(3, 26) = 2.598, p = .074
R2 = .322, Radj2 = .244   R2 = .231, Radj2 = .142
PredictorsRepeatedManipulatedNovel
βtsrβtsrβtsr
(A) Multiple regression analyses with brain region volumes as predictors for the proportion of fixations directed to the critical object ROI in each test condition
CA1 −.567 −1.869 −.325 −500 −1.847 −.287 −.439 −1.465 −.252
Subiculum .478 1.725 .300 .381 1.542 .240 .303 1.106 .190
DG/CA23 .016 0.063 .011 −.131 −0.591 −.092 .096 0.391 .067
PRC .321 1.420 .247 .133 0.661 .103 .336 1.502 .259
alERC .252 1.264 .220 .464* 2.607 .405 .420* 2.131 .367
pmERC −.239 −0.940 −.164 .074 0.328 .051 −.163 −0.647 −.112
PHC .460* 2.114 .368 .484* 2.497 .388 .098 0.456 .079
F(7, 22) = 1.566, p = .198 F(7, 22) = 2.775, p = .031 F(7, 22) = 1.672, p = .168
R2 = .333, Radj2 = .120 R2 = .469, Radj2 = .300 R2 = .347, Radj2 = .140

(B) Multiple regression analyses with brain region volumes as predictors for the proportion of fixations directed to the empty ROI in each test condition
CA1 −.266 −0.838 −.153 .112 0.347 .064 −.140 −0.415 −.080
Subiculum .110 0.380 .069 .171 0.580 .108 −.028 −0.091 −.018
DG/CA23 .338 1.299 .237 .184 0.694 .129 .431 1.560 .302
PRC −.372 −1.573 −.287 −.247 −1.027 −.191 −.299 −1.189 −.230
alERC .405 1.942 .354 .302 1.419 .263 −.062 −0.279 −.054
pmERC −.031 −0.117 −.021 .095 0.352 .065 .027 0.096 .019
PHC −.223 −0.981 −.179 −.307 −1.327 −.246 −.173 −0.716 −.139
F(7, 22) = 1.161, p = .364 F(7, 22) = 1.006, p = .454 F(7, 22) = 0.663, p = .700
R2 = .270, Radj2 = .037 R2 = .242, Radj2 = .001 R2 = .174, Radj2 = −.089

(C) Multiple regression analyses with brain region volumes as predictors for the test/study ratio in each test condition
CA1 −.354 −1.174 −.203 −.177 −0.534 −.102 −.246 −0.781 −.141
Subiculum −.113 −0.410 −.071 .527 1.739 .331 .348 1.211 .219
DG/CA23 .317 1.282 .222 −.347 −1.276 −.243 .274 1.062 .192
PRC −.193 −0.859 −.149 .181 0.731 .139 .385 1.639 .296
alERC −.276 −1.392 −.241 .050 0.230 .044 .083 0.403 .073
pmERC .025 0.099 .017 −.412 −1.486 −.283 −.429 −1.629 −.295
PHC −.146 −.673 −.117 .223 0.940 .179 −.051 −0.227 −.041
F(7, 22) = 1.616, p = .183 F(7, 22) = 0.801, p = .595 F(7, 22) = 1.227, p = .330
R2 = .340, Radj2 = .129 R2 = .203, Radj2 = −.050 R2 = .281, Radj2 = .052

PredictorsalERC PHC
βtsrβtsr
(D) Multiple regression analyses with MoCA, age and viewing to the critical object ROI in the manipulated condition (object-in-place memory) as predictors for alERC and PHC volume
MoCA .358* 2.148 .347   .132 0.741 .127
Age .052 0.312 .050   −.258 −1.452 −.250
Proportion of fixations to critical object ROI .438* 2.711 .438   .355* 2.062 .355
F(3, 26) = 4.115, p = .016   F(3, 26) = 2.598, p = .074
R2 = .322, Radj2 = .244   R2 = .231, Radj2 = .142

In all three tables, multiple regression models were run separately for trials in each test condition. Each model is shown in its own column. p < .1, *p < .05, **p < .01 (reflect tests for significance of each predictor). Boldface indicates significant predictors in significant multiple regression models.

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