Biology subjects

Piastra, M. C.

Publications and source records attributed to Piastra, M. C..

3 recordsLinked to original sources

bioRxiv2026

Cortical E-fields of deep brain stimulation in Parkinson's disease patients exceed typical E-field magnitudes of transcranial electrical stimulation

BackgroundDeep brain stimulation (DBS) is an established and effective intervention for Parkinsons disease. Although the exact mechanisms of action are still unclear, both therapeutic benefits and side effects are solely attributed to neuromodulation via strong electric fields (E-fields) in the surgical target. Nevertheless, DBS generates E-fields that extend beyond the stimulation site and can be detected throughout the brain. Recent evidence from transcranial electrical stimulation studies shows that weak cortical E-fields even below 1 V/m can have a neuromodulatory effect, raising the question of a physiological relevance of weak cortical fields of DBS. However, the strength of cortical E-fields of DBS is currently unknown. ObjectiveUsing a novel framework, we aimed to quantify the whole-brain E-field distribution in patients with Parkinsons disease receiving therapeutic DBS of the subthalamic nucleus (STN-DBS). MethodsIn this work, we developed a pipeline to simulate DBS E-field distributions throughout the brain, based on the existing open-source toolboxes Lead-DBS and SimNIBS. We constructed patient-specific whole-head models including electrode leads for 25 patients with Parkinsons disease receiving subthalamic DBS, and simulated E-fields using the patients clinical stimulation settings for 49 hemispheres. ResultsWe found that median peak E-field magnitudes exceeded 0.3 V/m in all cortical regions and were greater than 1 V/m in the orbital gyrus, superior temporal gyrus, fusiform gyrus, parahippocampal gyrus, insular gyrus, cingulate gyrus. Most prominently, the orbital and insular gyri showed peak magnitudes ranging from 0.81 to 8.61 V/m and 0.90 to 8.01 V/m. ConclusionsOur results indicate that the E-fields of STN-DBS reach cortical peak magnitudes that exceed typically reported values of transcranial electrical stimulation. This opens the possibility that weak E-fields of DBS could have a direct neuromodulatory effect in wider regions of the brain, for example in cortical regions.

neuroscience↗

bioRxiv2025

Variable E-field properties of dual-site tACS

BackgroundDual-site transcranial alternating current stimulation (ds-tACS) enables the modulation of interregional functional connectivity by introducing a phase lag between the stimulating currents. However, overlapping electric fields (E-fields), particularly in closely spaced cortical targets like the primary motor cortices (M1s), may unintentionally alter E-field characteristics and confound the interpretation of functional connectivity modulation. ObjectiveWe aimed to systematically evaluate how different phase lags affect key E-field characteristics when using high-definition ds-tACS, particularly when targeting the M1s. We sought to determine which montage configuration best preserved stable E-field characteristics and investigated whether indi-vidualised montage selection could enhance control over E-field consistency. MethodsWe used individualised finite-element method simulations based on MRI-derived head models to quantify the effects of different phase lags on E-field characteristics. E-field magnitude, normal component, spatial distribution, directionality, and effective stimulation area were assessed for nine montages and eight phase lags. ResultsAll E-field properties, including E-field peak magnitude, peak magnitude of the normal component, redistribution, difference to optimal directionality, and effective area of stimulation, were modulated significantly across differ-ent phase lags for all tested montages. Furthermore, we found substantial inter-individual variability in all E-field properties. Individual selection of montages improved critical properties, particularly the E-field directionality. ConclusionsIn contrast to common assumptions, variations in the phase lag can significantly affect key E-field properties of high-definition ds-tACS. Therefore, we recommend considering modulations of the E-field characteristics when comparing physiological or behavioural effects of ds-tACS at different phase lags. Moreover, given the high inter-individual variability, we suggest the individualisation of montages to the most relevant E-field property. HighlightsO_LIDual-site tACS is often used to modulate functional connectivity. C_LIO_LIChanges in E-field characteristics with varying phase lags are undesirable. C_LIO_LIWe used FEM models to quantify these changes across arbitrary phase lags. C_LIO_LIE-field characteristics of all montages varied significantly with the phase lag. C_LIO_LIIndividualised montage selection was able to improve critical characteristics. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/668900v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1c666baorg.highwire.dtl.DTLVardef@8257e4org.highwire.dtl.DTLVardef@1584d7corg.highwire.dtl.DTLVardef@472447_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

The impact of CSF-filled cavities on scalp EEG and its implications

Previous studies have found EEG amplitude and scalp topography differences between neurotypical and neurological/neurosurgical groups, being interpreted at the cognitive level. However, these comparisons are invariably accompanied by anatomical changes. Critical to EEG are the so-called volume currents, which are affected by the spatial distribution of the different tissues in the head. We investigated the effect of CSF-filled cavities on simulated EEG scalp data. We simulated EEG scalp potentials for known sources using different volume conduction models: a reference model (i.e., unlesioned brain) and models with realistic CSF-filled cavities gradually increasing in size. We used this approach for a single source close or far from the CSF-lesion cavity, and for a scenario with a distributed configuration of sources (i.e., a "cognitive ERP effect"). Magnitude and topography error between the reference and lesion models were quantified. For the single-source simulation close to the lesion, the CSF-filled lesion modulated signal amplitude with more than 17% magnitude error, and topography with more than 9% topographical error. Negligible modulation was found for the single source far from the lesion. For the multi-source simulations of the cognitive effect, the CSF-filled lesion modulated signal amplitude with more than 6% magnitude error, and topography with more than 16% topography error in a non-monotonic fashion. In conclusion, the impact of a CSF-filled cavity cannot be neglected for scalp-level EEG data. Especially when group-level comparisons are made, any scalp-level attenuated, aberrant, or absent effects are difficult to interpret without considering the confounding effect of CSF. Impact statementPrevious studies have found EEG amplitude and scalp topography differences between neurotypical and neurological/neurosurgical groups (whose brain damage leads to the presence of a CSF-filled cavity), being interpreted at the cognitive level. Via simulations of scalp-level EEG patterns, we show that attenuated, aberrant, or absent effects in these comparisons are difficult to interpret without considering the confounding effect of CSF. FundingThis study was partly supported by grants from the Netherlands Organization for Scientific Research (Nederlandse Organisatie voor Wetenschappelijk Onderzoek [NWO]) to V. P. (451-17-003 and VI.Vidi.201.081) and to the Language in Interaction Consortium (024-001-006). CRediTVP: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Project administration, Visualization, Writing - original draft, Writing - review & editing RO: Conceptualization, Methodology, Software, Writing - review & editing JMS: Conceptualization, Methodology, Software, Writing - review & editing MCP: Conceptualization, Investigation, Methodology, Visualization, Writing - review & editing

neuroscience↗