Nina Dolfen; Serena Reverberi; Hans Op de Beeck; Bradley R. King; Genevieve Albouy

Table 3.

Results linear regressions

	HC	Block 1				Block 2
Stepwise	Predictors	B	Beta	t	p_fdr	B	Beta	t	p_fdr
	RK	0.276	1,91	1.084	0.33	0.267	0.185	1.029	0.364
	RP					0.062	0.066	0.367	1
	Model	R²	F	ΔR²		R²	F	ΔR²
		0.037	1.175	0.037		0.042	0.638	0.004
	Caudate	Block 1				Block 2
Stepwise	Predictors	B	Beta	t	p_fdr	B	Beta	t	p_fdr
	RK					−0.443	−0.325	−2.002	0.126
	RP	0.337	0.322	1.892	0.095	0.424	0.327	0.2.011	0.074
	Model	R²	F	ΔR²		R²	F	ΔR²
		0.104	3.58	0.104		0.209	3.968	0.105
	Putamen	Block 1				Block 2
Stepwise	Predictors	B	Beta	t	p_fdr	B	Beta	t	p_fdr
	RK					−0.091	−0.063	−0.352	0.848
	RP	0.448	0.359	2.144	0.07	0.474	0.380	2.11	0.075
	Model	R²	F	ΔR²		R²	F	ΔR²
		0.129	4.595	0.129		0.133	2.295	0.004
	aSPL	Block 1				Block 2
Stepwise	Predictors	B	Beta	t	p_fdr	B	Beta	t	p_fdr
	RK					0.045	0.027	0.149	0.882
	RP	0.043	0.033	0.183	0.856	0.043	0.033	0.181	0.858
	Model	R²	F	ΔR²		R²	F	ΔR²
		0.001	0.034	0.001		0.043	0.027	0.042
	M1	Block 1				Block 2
Stepwise	Predictors	B	Beta	t	p_fdr	B	Beta	t	p_fdr
	RK	0.565	0.496	2.637	0.021	0.517	0.455	2.973	0.021
	RP					0.976	0.266	1.741	0.162
	Model	R2	F	ΔR²		R2	F	ΔR²
		0.246	10.126	0.246*		0.562	6.911	0.069
Simple	Predictors	B	Beta	t	p_fdr
	RP	1.236	0.337	1.995	0.19
	Model	R²	F	ΔR²		Df 1	Df 2
		0.114	3.979	0.114		1	31
	PMC	Block 1				Block 2
Stepwise	Predictors	B	Beta	t	p_fdr	B	Beta	t	p_fdr
	RK	0.647	0.573	3.89	0.003	0.662	0.587	4.156	0.007
	RP					0.359	0.276	1.954	0.21
	Model	R²	F	ΔR²		R²	F	ΔR²
		0.328	15.126	0.328*		0.635	10.159	0.076
Simple	Predictors	B	Beta	t	p_{fdr r}
	RP	0.320	0.246	1.413	0.168
	Model	R²	F	ΔR²		Df 1	Df 2
		0.061	1.998	0.061		1	31
	SMA	Block 1				Block 2
Stepwise	Predictors	B	Beta	t	p_fdr	B	Beta	t	p_fdr
	RK	0.540	0.419	2.57	0.035	0.516	0.400	2.66	0.028
	RP					0.556	383	2.55	0.112
	Model	R²	F	ΔR²		R²	F	ΔR²
		0.176	6.62	0.176*		0.323	7.145	0.147
Simple	Predictors	B	Beta	t	p_fdr
		0.585	0.403	2.455	0.14
	Model	R²	F	ΔR²		Df 1	Df 2
		0.163	6.026	0.163		1	31

Notes. Dependent variable, delta similarity in the SEQ condition. Predictors, delta similarity in the RK and/or RP matrix. An F test was used to assess whether the change in explained variance (ΔR²) from the prior step is significant (*p_FDR ≤ 0.05, corrected for 7 tests). Block 1, df1 = 1; df2 = 31; Block 2, df1 = 2; df2 = 30. Stepwise regression was followed by simple regressions when only one out of two predictors was included in the final model. N = 33.

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The Hippocampus Represents Information about Movements in Their Temporal Position in a Learned Motor Sequence

The Journal of NeuroscienceSociety for Neuroscience

The Hippocampus Represents Information about Movements in Their Temporal Position in a Learned Motor Sequence

The Journal of Neuroscience Society for Neuroscience