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Antonenko, D.

Publications and source records attributed to Antonenko, D..

13 recordsLinked to original sources

Brain Regions Involved in Object-Location Memory Across the Human Lifespan: A Systematic Review and Activation Likelihood Estimation Meta-Analysis of Task-Based fMRI

BackgroundThe ability to remember object locations in real life is a fundamental cognitive process that supports goal-directed behavior and is particularly vulnerable to aging and neurodegenerative disease. Despite a growing body of functional magnetic resonance imaging (fMRI) research on object-location memory (OLM), the neural substrates of establishing and retrieving location information are largely unknown. ObjectiveThis systematic review and coordinate-based meta-analysis aimed to identify brain regions consistently activated during OLM in healthy adults, primarily for encoding and - on an exploratory basis - for retrieval, and to characterize age-related differences in OLM-related neural activity. MethodsA systematic search was conducted across three databases (PubMed, PsycInfo, Cochrane Library) up to February 2026. Studies employing task-based fMRI during the encoding and retrieval of object-location associations in healthy adults were eligible. Age-related differences in OLM-related brain activity were examined via narrative synthesis. An activation likelihood estimation (ALE) meta-analysis was performed on studies reporting stereotactic peak coordinates. The review was pre-registered on PROSPERO (CRD420251023695). ResultsTwenty-one studies comprising 637 participants were included in the systematic review, with 12 studies being eligible for the encoding ALE meta-analysis. The retrieval ALE meta-analysis was not possible due to the limited number of included studies and reported foci. The systematic review indicated that OLM encoding consistently recruited bilateral fusiform gyri and parahippocampal cortices, with additional engagement of parietal and prefrontal regions across individual studies, whereas OLM retrieval recruited mainly the hippocampus and precuneus. The coordinate-based ALE meta-analysis revealed two significant clusters of activation during OLM encoding: a left-lateralized cluster encompassing the fusiform gyrus, parahippocampal gyrus, and inferior temporal gyrus (peak MNI: -28, -38, -16), and a right-hemisphere cluster spanning the parahippocampal gyrus and fusiform gyrus (peak MNI: 30, -46, -16). Age-related differences, based on a small number of studies with direct age comparison, pointed toward reduced activity in posterior cortical regions coupled with increased activity in prefrontal and midline regions. Additionally, younger adults showed greater hippocampal activation for successful than unsuccessful spatial retrieval, whereas older adults showed the opposite pattern. ConclusionThe systematic review and meta-analysis identify the fusiform gyri and parahippocampal cortices as the most reliably activated regions during OLM encoding, locating OLM formation primarily within the ventral visual-to-medial-temporal processing stream. Retrieval additionally engaged the hippocampus and precuneus, consistent with their established roles in episodic memory. Age-related differences included reduced posterior cortical encoding activity in older adults, a reversal of the hippocampal activation pattern during retrieval, and weaker suppression of midline regions during task performance. The identified encoding pathway may inform targeted network-level interventions such as non-invasive brain stimulation to counteract cognitive decline in aging and neurodegenerative disease. Highlights- First systematic review and coordinate-based meta-analysis of task-based fMRI during encoding and retrieval of object-location memories (OLMs). - Activation likelihood estimation (ALE) identified bilateral fusiform gyrus and parahippocampus as the most consistent encoding regions, supporting a ventral-dominant input pathway. - Hippocampus and precuneus were the most consistent OLM retrieval regions, suggesting an encoding-retrieval dissociation. - Age-related encoding differences centered on reduced fusiform and parahippocampal subsequent-memory effects, with an altered anterior-hippocampal response in older adults.

neuroscience↗

Multicenter reliability of electric field simulations: Evidence from a traveling-subjects study

Multicenter neuroimaging studies face challenges from scanner-related measurement biases that can obscure biological effects. Traveling-subject (TS) designs allow direct quantification of such biases by scanning the same participants across multiple sites. While reliability of structural, functional, and diffusion MRI has been established, the reliability of electric field simulations for transcranial brain stimulation has not been examined. We assessed inter-scanner and scan-rescan reliability of simulated electric field magnitudes in 10 participants scanned twice on each of five 3T Siemens scanners, using SimNIBS v4.1 to simulate focal tDCS across seven cortical and cerebellar targets. ICC values indicated good to excellent inter-scanner (0.86-0.97) and scan-rescan (0.94-0.98) reliability, with between-scanner variance not exceeding measurement error. Intra-individual segmentation variability substantially explained within-person differences in field magnitudes, whereas image quality did not predict segmentation variability. These results demonstrate that individualized electric field simulations are robust to scanner-related variation, supporting their use in multicenter brain stimulation research.

neuroscience↗

Temporo-Occipital and Medial Temporal Networks Underlying Object-Location Learning

Object-location memory (OLM), a fundamental component of spatial memory, is essential for everyday functioning yet declines with aging and neurodegenerative disorders. Functional neuroimaging studies have consistently implicated medial temporal lobe (MTL) structures, including the hippocampus and parahippocampal gyrus, as well as medial and lateral temporo-occipital regions, in object-location associative learning. However, the neural mechanisms and functional network interactions supporting OLM acquisition remain largely unknown. To address this gap, we examined twenty healthy adults (18-45 years) performing an object-location learning task during functional MRI. As a first main finding, task-related functional connectivity analyses revealed enhanced coupling between MTL structures, ventral visual regions, and temporo-occipital cortices during OLM learning. Secondly, stronger connectivity within this network was associated with higher learning accuracy, highlighting the behavioral relevance of coordinated cortical-MTL interactions. Thirdly, these connectivity patterns were not static but evolved across learning stages: interregional coupling was strongest during early learning and progressively attenuated as performance stabilized, suggesting sharpening and increased efficiency of network interactions with learning. Together, our results provide mechanistic insight into OLM acquisition at the functional network level and offer an evidence-based framework for identifying target networks to enhance spatial memory through non-invasive brain stimulation.

neuroscience↗

Harmonizing the stimulation dose of focal tDCS across target sites

Non-invasive brain stimulation is an established tool for modulating neural activity that holds promise for advancing both cognitive neuroscience and clinical interventions. Focal transcranial direct current stimulation (tDCS), using center-surround electrode montages, enables more region-specific targeting. Although computational models can simulate individual electric fields, no existing approach enables the prospective individualization of electrode placement while standardizing the dose across targeted brain regions. In the current preparatory methodological study, we present a modeling-based framework that harmonizes the electric field strength between different target regions at the group level, but preserves inter-individual variability. This enables systematic examination of dose-response relationships and their regional differences. Positioning of the center-surround electrode montages is individualized to ensure focusing of the electric field on the target regions. We started by defining brain targets for eight cognitive and motor functions using MRI data from 43 participants. Using field simulations, we then estimated a group-average field strength in the target regions that had led to behavioral and physiological effects in prior tDCS studies (resulting in 0.2 V/m). The radii of the center-surround montages were optimized for each target region to achieve the intended field strength while maximizing focality. Validation in an independent sample (n=53) confirmed that the intended target field strength is achieved on average for new participants. The described computational tools are made available as open-source software, allowing other researchers to apply our individualization framework with parameters (target regions and target field strengths) tailored to their specific research questions; and are currently being implemented in a multi-center study involving approximately 1,000 datasets.

neuroscience↗

Multimodal Imaging-Based Targeting Approach for Network-Level Brain Stimulation

BackgroundNeural network effects of transcranial direct current stimulation (tDCS) are poorly understood. Here, we introduce an empirically informed, multimodal functional magnetic resonance imaging (fMRI) based framework suited for guiding stimulation target selection and hypothesis-based data analysis in focal tDCS-fMRI studies. MethodsWe illustrate our approach using data of 37 healthy individuals (19 females; mean {+/-} SD age = 25.8 {+/-} 5.9) recruited from a multicenter tDCS-fMRI study. Participants completed resting-state (RS- and task-fMRI (object-location memory, OLM, or associative picture-pseudoword learning, APPL, experiments) with placebo tDCS. Seed-based RS data analysis identified the functional networks originating from project-specific target regions for focal tDCS (right occipito-temporal cortex, rOTC; left ventral IFG, lvIFG) and also established their test-retest reliability using intraclass correlation coefficients (ICC). Dice coefficients analyzed the overlap between the seeded RS- and task-evoked networks. This aimed to identify task-active regions potentially affected by downstream neural network effects from the target regions. ResultsSeed-based analyses identified two highly reliable ventral visual-limbic (rOTC) and language-related networks (lvIFG), with >72-77% of voxels showing good-to-excellent TRR (ICC [≥] 0.75). Only a subset of voxels identified by the RS analyses overlapped with activity elicited by the experimental paradigms (ranging from 7.5-55%), with larger correspondence for the OLM task (Dice OLM: 0.249-0.349; APPL 0.065-0.106). Therefore, the degree of potential tDCS network effects varied substantially depending on the target region, the extent of its functional network and task-specific activity patterns. Degree of correspondence was further mediated by the selected contrasts-of-interest in the task-based analyses, with more conservative control conditions resulting in reduced overlap. ConclusionWe established a principled, multimodal fMRI framework bridging a critical gap in neuromodulation research. By integrating reliable intrinsic connectivity maps with task-evoked activity patterns, we provide a method to prospectively identify network-level targets for focal brain stimulation and to generate hypotheses for data analyses in tDCS-fMRI studies. This approach paves the way for investigating modulation of specific functional networks, shifting the rationale from stimulating an isolated brain region to strategically targeting key nodes within a predefined functional pathway.

neuroscience↗

Deep learning to overcome human error and bias in electrode position extraction in tDCS-fMRI studies

Combining transcranial direct current stimulation (tDCS) with fMRI enables investigation of stimulation effects, while structural MRI verifies electrode positioning, critical for focal montages where minor misplacements reduce target current dose. Currently, no fully automated methods exist for precise electrode extraction from MRI. We developed an Attention U-Net-based deep learning approach to automate electrode detection in focal tDCS-fMRI studies, using structural pointwise-encoding time reduction with radial acquisition (PETRA) MRI scans from a multicenter trial (N = 392 images; 1,568 electrodes, https://www.memoslap.de/en/home/). Performance was compared to manual and semi-automated methods for a 3x1 montage (three cathodes around a central anode). The network achieved robust segmentation (Dice Score = 0.76, Hausdorff distance = 36.76 mm), identifying all electrodes in 95% of cases (323/340). These metrics compared network-segmented electrodes to highly accurate, manually segmented electrodes, which are also called "ground truth". Linear mixed-effects models on 52 "ground truth" images showed deep learning outperformed manual and semi-automated methods, aligning best with ground truth. Fully/semi-automated methods comparison of 290 images showed highest agreement (ICC = 0.990, bias = 1.3 mm), while manual extraction exhibited larger biases (-5.77 to -7.06 mm) and systematic errors. The automated approach overcomes manual limitations by improving precision, eliminating human variability and bias, and enabling scalability for large studies. It sets a new standard for electrode verification in focal tDCS, particularly for studies requiring precise localization. The model is open-source, with future refinements discussed

neuroscience↗

Occipital tACS does not modulate manual performance but fixation variability under visuo-proprioceptive conflict

The modulation of oscillations at alpha and beta frequency ranges recorded over sensory cortices has been linked to the top-down weighting of sensory information relative to (competing) information from other modalities. Here, using a virtual reality-based hand-target matching task under visuo-proprioceptive conflict, we tested whether alpha-/beta-tACS over the occipital cortex would improve action performance when conflicting visual movement feedback needed to be ignored in favor of proprioception. Participants had to match a target rhythm with either their unseen real hand (RH) grasping movements, or with the movements of a virtual hand (VH) that displayed their actual movements after a constant time delay. Visual movement feedback was, consequently, either task-relevant (VH task) or a distractor (RH task). In a cross-over, double-blind, within-subject design, we applied either low-intensity (2 mA peak-to-peak) transcranial alternating current stimulation (tACS) at 10 Hz ("alpha") or 20 Hz ("beta"), or sham, over the occipital cortex during this task. Neither alpha- nor beta-tACS significantly affected hand-target matching performance, but fixation variability in the RH condition significantly decreased during beta-tACS relative to sham stimulation. Thus, despite not directly modulating manual performance, occipital beta-tACS could have facilitated ignoring the mismatching (distracting) visual movement feedback when needed.

animal behavior and cognition↗

Functionally Relevant and Reliable Brain Stimulation Targets for Enhancement of Novel Word-Learning

Linking word-forms and their meanings is central to language learning. Transcranial direct current stimulation (tDCS), has shown potential to enhance this process, but with variable effects. This study aimed to (1) identify reliable and functionally relevant tDCS target brain regions to enhance novel-word learning and (2) assess test-retest reliability (TRR) of behavioral and imaging outcomes. Twenty healthy individuals completed two functional magnetic resonance imaging (fMRI) sessions using parallel task versions. Participants learned picture-pseudoword associations across six learning blocks. Behavioral learning was analyzed using linear-mixed-models. Whole-brain and region-of-interest (ROI) analyses examined learning-related activity changes and their behavioral relevance. TRR was assessed using intraclass correlation coefficients (ICCs). Participants successfully acquired the novel-word forms, indexed by increased accuracy and faster latency across stages. Behavioral outcomes showed good-to-excellent TRR. The task elicited robust language-learning related activity and activity changes across stages were correlated with learning success. Task-related activity was variable, but voxels within significant clusters ([~]81%) and most ROIs showed moderate-to-excellent consistency. Power analyses confirmed a sufficient sample size for detecting the reported ICCs. Current modeling suggested that focal-tDCS can induce neurophysiologically relevant electrical field strength in the identified target regions. Hence, we identified accessible, reliable and functionally relevant cortical targets for enhancing novel-word learning. TRR results support the usefulness of the paradigm for future concurrent tDCS-fMRI research. Our study also outlines a general path towards optimization of brain stimulation studies by implementing an empirically informed approach for selecting reliable and relevant target regions and implementation of reliable experimental and imaging paradigms.

neuroscience↗

Brain oscillatory processes related to sequence memory in healthy older adults

Sequence memory is subject to age-related decline, but the underlying processes are not yet fully understood. We analyzed electroencephalography (EEG) in 21 healthy older (60-80 years) and 26 young participants (20-30 years) and compared time-frequency spectra and theta-gamma phase-amplitude-coupling (PAC) during encoding of the order of visually presented items. In older adults, desynchronization in theta (4-8 Hz) and synchronization in gamma (30-45 Hz) power did not distinguish between subsequently correctly and incorrectly remembered trials, while there was a subsequent memory effect for young adults. Theta-gamma PAC was modulated by item position within a sequence for older but not young adults. Specifically, position within a sequence was coded by higher gamma amplitude for successive theta phases for later correctly remembered trials. Thus, deficient differentiation in theta desynchronization and gamma oscillations during sequence encoding in older adults may reflect neurophysiological correlates of age-related memory decline. Furthermore, our results indicate that sequences are coded by theta-gamma PAC in older adults, but that this mechanism might lose precision in aging.

neuroscience↗

Towards optimization of oscillatory stimulation during sleep

BackgroundOscillatory rhythms during sleep such as slow oscillations (SO) and spindles, and most importantly their coupling, are thought to underlie processes of memory consolidation. External slow oscillatory transcranial direct current stimulation (so-tDCS) with a frequency of 0.75 Hz has been shown to improve this coupling and memory consolidation, however, effects varied quite markedly between individuals, studies, and species. Here, we aimed to determine how precisely the frequency of stimulation has to match the naturally occurring SO frequency in individuals to optimally improve SO-spindle coupling. Moreover, we systematically tested stimulation durations necessary to induce changes. MethodsWe addressed these questions by comparing so-tDCS with individualized frequency to standardized frequency of 0.75 Hz in a within-subject design with 28 older participants during napping while systematically varying stimulation train durations between 30 s, 2 min, and 5 min. ResultsStimulation trains as short as 30 s were sufficient to modulate the coupling between SOs and spindle activity. Contrary to our expectations, so-tDCS with standardized frequency indicated stronger aftereffects with regard to SO-spindle coupling compared to individualized frequency. Angle and variance of spindle maxima occurrence during the SO cycle were similarly modulated. ConclusionIn sum, short stimulation trains were sufficient to induce significant changes in sleep physiology allowing for more trains of stimulation, which provides methodological advantages and possibly even larger behavioral effects in future studies. With regard to individualized stimulation frequency, further options of optimization need to be investigated, such as closed-loop stimulation to calibrate stimulation frequency to the SO frequency at time of stimulation onset. Significance statementApplication of slow oscillatory transcranial direct current stimulation during sleep has been shown to enhance specific memory-relevant sleep parameters and memory performance after sleep, albeit with a high degree of variability. Here, we systematically explored two major stimulation parameters possibly accounting for this variability in humans: frequency and duration of stimulation. We found, contrary to our expectations, standardized frequency stimulation with 0.75 Hz being superior to individualized frequency stimulation in enhancing specific sleep parameters. Moreover short stimulation trains of 30 seconds were as effective as 5 min in modulating aftereffects. These are encouraging findings, implying methodological advantages as larger quantity of aftereffects data can be obtained within the same time window, which may also lead to enhanced behavioral stimulation effects.

neuroscience↗

Interrelations between delta waves, spindles and slow oscillations in human NREM sleep and their functional role in memory

Certain neurophysiological characteristics of sleep, in particular slow oscillations (SO), sleep spindles, and their temporal coupling, have been well characterized and associated with human memory formation. Delta waves, which are somewhat higher in frequency and lower in amplitude compared to SO, have only recently been found to play a critical role in memory processing of rodents, through a competitive interplay between SO-spindle and delta-spindle coupling. However, human studies that comprehensively address delta waves, their interactions with spindles and SOs as well as their functional role for memory are still lacking. Electroencephalographic data were acquired across three naps of 33 healthy older human participants (17 female) to investigate delta-spindle coupling and the interplay between delta and SO-related activity. Additionally, we determined intra-individual stability of coupling measures and their potential link to the ability to form novel memories. Our results revealed weaker delta-spindle compared to SO-spindle coupling. Contrary to our initial hypothesis, we found that increased delta activity was accompanied by stronger SO-spindle coupling. Moreover, we identified the ratio between SO- and delta-nested spindles as the sleep parameter that predicted ability to form novel memories best. Our study suggests that SOs, delta waves and sleep spindles should be jointly considered when aiming to link sleep physiology and memory formation in aging. Significance statementInterrelations between delta waves, slow oscillations and sleep spindles have recently been causally linked to the balance between consolidation and forgetting in rats using optogenetics. In humans, SO-spindle coupling has been intensively investigated, but delta waves and their interaction with spindles were only studied jointly as SWA. Here we delineate the coupling of delta waves to spindles, investigate interactions of delta- and SO-related activity and investigate their role for the ability to form novel memories in healthy older individuals. Our results show differences as well as dependencies between SO- and delta-related activities including spindle coupling. Further, our results indicate that the ratio of SO- to delta-nested spindles might be the most informative sleep parameter for memory formation of older adults.

neuroscience↗

Beneficial effects of cerebellar tDCS on motor learning are associated with altered putamen-cerebellar connectivity: a simultaneous tDCS-fMRI study

Non-invasive transcranial stimulation of cerebellum and primary motor cortex (M1) has been shown to enhance motor learning. However, the mechanisms by which stimulation improves learning remain largely unknown. Here, we sought to shed light on the neural correlates of transcranial direct current stimulation (tDCS) during motor learning by simultaneously recording functional magnetic resonance imaging (fMRI). We found that right cerebellar tDCS, but not left M1 tDCS, led to enhanced sequence learning in the serial reaction time task. Performance was also improved following cerebellar tDCS compared to sham in a sequence production task, reflecting superior training effects persisting into the post-training period. These behavioral effects were accompanied by increased learning-specific activity in right M1, left cerebellum lobule VI, left inferior frontal gyrus and right inferior parietal lobule during cerebellar tDCS compared to sham. Despite the lack of group-level changes comparing left M1 tDCS to sham, activity increase in right M1, supplementary motor area, and bilateral superior frontal cortex, under M1 tDCS, was associated with better sequence performance. This suggests that lack of group effects in M1 tDCS relate to inter-individual variability in learning-related activation patterns. We further investigated how tDCS modulates effective connectivity in the cortico-striato-cerebellar learning network. Using dynamic causal modelling, we found altered connectivity patterns during both M1 and cerebellar tDCS when compared to sham. Specifically, during cerebellar tDCS, negative modulation of a connection from putamen to cerebellum was decreased for sequence learning only, effectively leading to decreased inhibition of the cerebellum. These results show specific effects of cerebellar tDCS on functional activity and connectivity in the motor learning network and may facilitate the optimization of motor rehabilitation involving cerebellar non-invasive stimulation.

neuroscience↗

SimNIBS 2.1: A Comprehensive Pipeline for Individualized Electric Field Modelling for Transcranial Brain Stimulation

Numerical simulation of the electric fields induced by Non-Invasive Brain Stimulation (NIBS), using realistic anatomical head models has gained interest in recent years for understanding the NIBS effects in individual subjects. Although automated tools for generating the head models and performing the electric field simulations have become available, individualized modelling is still not standard practice in NIBS studies. This is likely partly explained by the lack of robustness and usability of the previously available software tools, and partly by the still developing understanding of the link between physiological effects and electric field distributions in the brain. To facilitate individualized modelling in NIBS, we have introduced the SimNIBS (Simulation of NIBS) software package, providing easy-to-use automated tools for electric field modelling. In this article, we give an overview of the modelling pipeline in SimNIBS 2.1, with step-by-step examples of how to run a simulation. Furthermore, we demonstrate a set of scripts for extracting average electric fields for a group of subjects, and finally demonstrate the accuracy of automated placement of standard electrode montages on the head model. SimNIBS 2.1 is freely available at www.simnibs.org.

bioengineering↗