Structural and Functional Connectivity Predict the Effects of Direct Brain Stimulation on Memory

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Abstract

Intracranial stimulation can enhance episodic memory in humans; however, the behavioral effects vary substantially across individuals and stimulation sites. Here, we investigated whether the network embedding of a stimulation target, defined by MRI-based normative structural and functional connectivity, accounts for variability in stimulation-linked memory enhancement. We analyzed data from 50 adults with medically refractory epilepsy who underwent intracranial EEG monitoring and completed a verbal delayed free-recall task during stimulation of left temporal cortex sites across 61 sessions (39 closed-loop; 22 random). On average, closed-loop stimulation delivered during classifier-detected low-encoding states increased recall rates, whereas random stimulation produced no reliable benefit. Diffusion tractography from a normative database showed that sites yielding greater memory enhancement were characterized by stronger structural coupling to a distributed fronto-temporo-parietal network. Greater structure-function congruence with a normative verbal-encoding activation network predicted larger closed-loop memory benefit (Spearman ρ = 0.58, P < 0.0001). Functional connectivity exhibited overlapping trends but did not yield robust regional associations after permutation correction. Multivariate Partial Least Squares Structural Equation Modeling further identified stimulation mode, baseline memory, and a structural profile factor as independent predictors of memory enhancement, with no independent contribution of functional connectivity. These findings indicate that reliable stimulation-driven memory improvement depends not only on the timing of stimulation, but also on whether the stimulated target is structurally embedded within an encoding-relevant network scaffold. Significance statement Memory enhancement through direct brain stimulation holds substantial clinical promise, yet inconsistent outcomes have limited its therapeutic translation. This study shows that the effectiveness of closed-loop brain stimulation for memory improvement is determined by the structural network architecture of the stimulation target. Sites more deeply embedded within white-matter pathways connecting a distributed verbal encoding network yield the greatest mnemonic benefits when stimulation is delivered adaptively during poor encoding states. These findings establish a principled, network-based rationale for precision-guided neuromodulation: optimizing both the target’s structural embedding and the timing of stimulation delivery are necessary and complementary conditions for reliable, individualized memory enhancement.
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Abstract Intracranial stimulation can enhance episodic memory in humans; however, the behavioral effects vary substantially across individuals and stimulation sites. Here, we investigated whether the network embedding of a stimulation target, defined by MRI-based normative structural and functional connectivity, accounts for variability in stimulation-linked memory enhancement. We analyzed data from 50 adults with medically refractory epilepsy who underwent intracranial EEG monitoring and completed a verbal delayed free-recall task during stimulation of left temporal cortex sites across 61 sessions (39 closed-loop; 22 random). On average, closed-loop stimulation delivered during classifier-detected low-encoding states increased recall rates, whereas random stimulation produced no reliable benefit. Diffusion tractography from a normative database showed that sites yielding greater memory enhancement were characterized by stronger structural coupling to a distributed fronto-temporo-parietal network. Greater structure-function congruence with a normative verbal-encoding activation network predicted larger closed-loop memory benefit (Spearman ρ = 0.58, P < 0.0001). Functional connectivity exhibited overlapping trends but did not yield robust regional associations after permutation correction. Multivariate Partial Least Squares Structural Equation Modeling further identified stimulation mode, baseline memory, and a structural profile factor as independent predictors of memory enhancement, with no independent contribution of functional connectivity. These findings indicate that reliable stimulation-driven memory improvement depends not only on the timing of stimulation, but also on whether the stimulated target is structurally embedded within an encoding-relevant network scaffold. Significance statement Memory enhancement through direct brain stimulation holds substantial clinical promise, yet inconsistent outcomes have limited its therapeutic translation. This study shows that the effectiveness of closed-loop brain stimulation for memory improvement is determined by the structural network architecture of the stimulation target. Sites more deeply embedded within white-matter pathways connecting a distributed verbal encoding network yield the greatest mnemonic benefits when stimulation is delivered adaptively during poor encoding states. These findings establish a principled, network-based rationale for precision-guided neuromodulation: optimizing both the target’s structural embedding and the timing of stimulation delivery are necessary and complementary conditions for reliable, individualized memory enhancement. Competing Interest Statement The authors have declared no competing interest.

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europepmc
last seen: 2026-05-20T01:45:00.602351+00:00
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License: CC-BY-4.0