Tango of control: The interplay between proactive and reactive control.

Cognitive control has been theorized operating through two distinct mechanisms, proactive and reactive control, as posited by the dual mechanism of control model. Despite its potential to explain cognitive control variability, the supporting evidence for this model remains inconclusive. Prior studies frequently employed the Stroop task to assess this model, manipulating the proportion congruency (PC) at the list-wide and/or item-specific levels to target proactive and reactive control, respectively. However, these manipulations have been questioned as they may invoke low-level associative learning instead of control-driven mechanisms. Although solutions have been proposed to address these concerns, they still have limitations and impracticalities. In pursuit of a clearer understanding of this issue, we manipulated proactive and reactive control simultaneously to more directly investigate their separability. We conducted two experiments using a peripheral and a perifoveal spatial Stroop task version, respectively, and we adopted state-of-the-art methodologies, leveraging trial-level multilevel modeling analytical approaches, to effectively estimate the Stroop effect and its control-related modulations while controlling for confounding factors. Notably, we manipulated both list-wide and item-specific PCs at the trial level, allowing for a fine-grained analysis. Our results provide compelling evidence for the existence of a list-wide, PC-dependent proactive control mechanism, influencing Stroop performance independently of reactive control and confounding factors. Additionally, an item-specific PC-dependent reactive control effect was found to influence Stroop performance only in interaction with proactive control. These findings contribute to a better understanding of the interplay between proactive and reactive control mechanisms, shedding light on the intricate nature of cognitive control. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Topological features of functional brain networks and subclinical impulsivity: an investigation in younger and older adults.

Impulsive traits (i.e., the tendency to act without forethought regardless of negative outcomes) are frequently found in healthy populations. When exposed to risk factors, individuals may develop debilitating disorders of impulse control (addiction, substance abuse, gambling) characterized by behavioral and cognitive deficits, eventually leading to huge socioeconomic costs. With the far-reaching aim of preventing the onset of impulsive disorders, it is relevant to investigate the topological organization of functional brain networks associated with impulsivity in sub-clinical populations. Taking advantage of the open-source LEMON dataset, we investigated the topological features of resting-state functional brain networks associated with impulsivity in younger (n = 146, age: 20-35) and older (n = 61, age: 59-77) individuals, using a graph-theoretical approach. Specifically, we computed indices of segregation and integration at the level of specific circuits and nodes known to be involved in impulsivity (frontal, limbic, and striatal networks). In younger individuals, results revealed that impulsivity was associated with a more widespread, less clustered and less efficient functional organization, at all levels of analyses and in all selected networks. Conversely, impulsivity in older individuals was associated with reduced integration and increased segregation of striatal regions. Speculatively, such alterations of functional brain networks might underlie behavioral and cognitive abnormalities associated with impulsivity, a working hypothesis worth being tested in future research. Lastly, differences between younger and older individuals might reflect the implementation of age-specific adaptive strategies, possibly accounting for observed differences in behavioral manifestations. Potential interpretations, limitations and implications are discussed.

Facial emotion recognition in individuals with mild cognitive impairment: An exploratory study.

Understanding facial emotions is fundamental to interact in social environments and modify behavior accordingly. Neurodegenerative processes can progressively transform affective responses and affect social competence. This exploratory study examined the neurocognitive correlates of face recognition, in individuals with two mild cognitive impairment (MCI) etiologies (prodromal to dementia - MCI, or consequent to Parkinson's disease - PD-MCI). Performance on the identification and memorization of neutral and emotional facial expressions was assessed in 31 individuals with MCI, 26 with PD-MCI, and 30 healthy controls (HC). Individuals with MCI exhibited selective impairment in recognizing faces expressing fear, along with difficulties in remembering both neutral and emotional faces. Conversely, individuals with PD-MCI showed no differences compared with the HC in either emotion recognition or memory. In MCI, no significant association emerged between the memory for facial expressions and cognitive difficulties. In PD-MCI, regression analyses showed significant associations with higher-level cognitive functions in the emotional memory task, suggesting the presence of compensatory mechanisms. In a subset of participants, voxel-based morphometry revealed that the performance on emotional tasks correlated with regional changes in gray matter volume. The performance in the matching of negative expressions was predicted by volumetric changes in brain areas engaged in face and emotional processing, in particular increased volume in thalamic nuclei and atrophy in the right parietal cortex. Future studies should leverage on neuroimaging data to determine whether differences in emotional recognition are mediated by pathology-specific atrophic patterns.

A comparison between different variants of the spatial Stroop task: The influence of analytic flexibility on Stroop effect estimates and reliability.

The spatial Stroop task measures the ability to resolve interference between relevant and irrelevant spatial information. We recently proposed a four-choice spatial Stroop task that ensures methodological advantages over the original color-word verbal Stroop task, requiring participants to indicate the direction of an arrow while ignoring its position in one of the screen corners. However, its peripheral spatial arrangement might represent a methodological weakness and could introduce experimental confounds. Thus, aiming at improving our "Peripheral" spatial Stroop, we designed and made available five novel spatial Stroop tasks (Perifoveal, Navon, Figure-Ground, Flanker, and Saliency), wherein the stimuli appeared at the center of the screen. In a within-subjects online study, we compared the six versions to identify which task produced the largest but also the most reliable and robust Stroop effect. Indeed, although internal reliability is frequently overlooked, its estimate is fundamental, also in light of the recently proposed reliability paradox. Data analyses were performed using both the classical general linear model analytical approach and two multilevel modelling approaches (linear mixed models and random coefficient analysis), which specifically served for more accurately estimating the Stroop effect by explaining intra-subject, trial-by-trial variability. We then assessed our results based on their robustness to such analytic flexibility. Overall, our results indicate that the Perifoveal spatial Stroop is the best alternative task for its statistical properties and methodological advantages. Interestingly, our results also indicate that the Peripheral and Perifoveal Stroop effects were not only the largest, but also those with highest and most robust internal reliability.

lmeEEG: Mass linear mixed-effects modeling of EEG data with crossed random effects.

BACKGROUND: Mixed-effects models are the current standard for the analysis of behavioral studies in psycholinguistics and related fields, given their ability to simultaneously model crossed random effects for subjects and items. However, they are hardly applied in neuroimaging and psychophysiology, where the use of mass univariate analyses in combination with permutation testing would be too computationally demanding to be practicable with mixed models. NEW METHOD: Here, we propose and validate an analytical strategy that enables the use of linear mixed models (LMM) with crossed random intercepts in mass univariate analyses of EEG data (lmeEEG). It avoids the unfeasible computational costs that would arise from massive permutation testing with LMM using a simple solution: removing random-effects contributions from EEG data and performing mass univariate linear analysis and permutations on the obtained marginal EEG. RESULTS: lmeEEG showed excellent performance properties in terms of power and false positive rate. COMPARISON WITH EXISTING METHODS: lmeEEG overcomes the computational costs of standard available approaches (our method was indeed more than 300 times faster). CONCLUSIONS: lmeEEG allows researchers to use mixed models with EEG mass univariate analyses. Thanks to the possibility offered by the method described here, we anticipate that LMM will become increasingly important in neuroscience. Data and codes are available at osf.io/kw87a. The codes and a tutorial are also available at github.com/antovis86/lmeEEG.

On the relationship between emotions and cognitive control: Evidence from an observational study on emotional priming Stroop task.

Evidence is discordant regarding how emotional processing and cognitive control interact to shape behavior. This observational study sought to examine this interaction by looking at the distinction between proactive and reactive modes of control and how they relate to emotional processing. Seventy-four healthy participants performed an emotional priming Stroop task. On each trial, target stimuli of a spatial Stroop task were preceded by sad or neutral facial expressions, providing two emotional conditions. To manipulate the requirement of both proactive and reactive control, the proportion of congruent trials (PC) was varied at the list-wide (LWPC) and item-specific (ISPC) levels, respectively. We found that sad priming led to behavioral costs only in trials with low proactive and reactive cognitive control demands. Our findings suggest that emotional processing affects cognitive processes other than cognitive control in the Stroop task. Moreover, both proactive and reactive control modes seem effective in overcoming emotional interference of priming stimuli.

Neural Differences in Relation to Risk Preferences during Reward Processing: An Event-Related Potential Study.

Inter-individual variability in risk preferences can be reflected in reward processing differences, making people risk-seekers or risk-averse. However, the neural correlates of reward processing in individuals with risk preferences remain unknown. Consequently, this event-related potential (ERP) study examined and compared electrophysiological correlates associated with different stages of reward processing in risk-seeking and risk-averse groups. Individuals scoring in the bottom and top 20% on the Balloon Analogue Risk Task (BART) were deemed risk-averse and risk-seeking, respectively. Participants engaged in a gambling task while their electroencephalogram (EEG) was recorded. Risk-seekers tended to choose high-risk options significantly more frequently than low-risk options, whereas risk-averse individuals chose low-risk options significantly more frequently than high-risk ones. All participants selected the low-risk alternative more slowly than the high-risk option. During the anticipation stage, the low-risk option elicited a relatively attenuated stimulus-preceding negativity (SPN) response from risk-seekers compared to risk-averse participants. During the outcome stage, feedback-related negativity (FRN) increased in risk-seekers responding to greater losses but not in risk-averse participants. These results indicate that ERP components can detect differences in reward processing during risky situations. In addition, these results suggest that motivation and cognitive control, along with their associated neural processes, may play a central role in differences in reward-based behavior between the two groups.

The Stroop legacy: A cautionary tale on methodological issues and a proposed spatial solution.

The Stroop task is a seminal paradigm in experimental psychology, so much that various variants of the classical color-word version have been proposed. Here we offer a methodological review of them to emphasize the importance of designing methodologically rigorous Stroop tasks. This is not an end by itself, but it is fundamental to achieve adequate measurement validity, which is currently hindered by methodological heterogeneity and limitations. Among the several Stroop task variants in the literature, our methodological overview shows that the spatial Stroop task is not only a potentially methodologically adequate variant, which can thus assure measuring the Stroop effect with the required validity, but it might even allow researchers to overcome some of the methodological limitations of the classical paradigm due to its use of verbal stimuli. We thus focused on the spatial Stroop tasks in the literature to verify whether they really exploit such inherent potentiality. However, we show that this was generally not the case because only a few of them (1) are purely spatial, (2) ensure both all the three types of conflicts/facilitations (at the stimulus, response, and task levels) and the dimensional overlaps considered fundamental for yielding a complete Stroop effect according to the multiple loci account and Kornblum's theory, respectively, and (3) controlled for low-level binding and priming effects that could bias the estimated Stroop effect. Based on these methodological considerations, we present some examples of spatial Stroop tasks that, in our view, satisfy such requirements and, thus, ensure producing complete Stroop effects.

White matter tract disconnection in Gerstmann's syndrome: Insights from a single case study.

It has been suggested that Gerstmann's syndrome is the result of subcortical disconnection rather than emerging from damage of a multifunctional brain region within the parietal lobe. However, patterns of white matter tract disconnection following parietal damage have been barely investigated. This single case study allows characterising Gerstmann's syndrome in terms of disconnected networks. We report the case of a left parietal patient affected by Gerstmann's tetrad: agraphia, acalculia, left/right orientation problems, and finger agnosia. Lesion mapping, atlas-based estimation of probability of disconnection, and DTI-based tractography revealed that the lesion was mainly located in the superior parietal lobule, and it caused disruption of both intraparietal tracts passing through the inferior parietal lobule (e.g., tracts connecting the angular, supramarginal, postcentral gyri, and the superior parietal lobule) and fronto-parietal long tracts (e.g., the superior longitudinal fasciculus). The lesion site appears to be located more superiorly as compared to the cerebral regions shown active by other studies during tasks impaired in the syndrome, and it reached the subcortical area potentially critical in the emergence of the syndrome, as hypothesised in previous studies. Importantly, the reconstruction of tracts connecting regions within the parietal lobe indicates that this critical subcortical area is mainly crossed by white matter tracts connecting the angular gyrus and the superior parietal lobule. Taken together, these findings suggest that this case study might be considered as empirical evidence of Gerstmann's tetrad caused by disconnection of intraparietal white matter tracts.

P3-like signatures of temporal predictions: a computational EEG study.

Many cognitive processes, ranging from perception to action, depend on the ability to predict the timing of forthcoming events. Yet, how the brain uses predictive models in the temporal domain is still an unsolved question. In previous work, we began to explore the neural correlates of temporal predictions by using a computational approach in which an ideal Bayesian observer learned the temporal probabilities of target onsets in a simple reaction time task. Because the task was specifically designed to disambiguate updating of predictive models and surprise, changes in temporal probabilities were explicitly cued. However, in the real world, we are usually incidentally exposed to changes in the statistics of the environment. Here, we thus aimed to further investigate the electroencephalographic (EEG) correlates of Bayesian belief updating and surprise associated with incidental learning of temporal probabilities. In line with our previous EEG study, results showed distinct P3-like modulations for updating and surprise. While surprise was indexed by an early fronto-central P3-like modulation, updating was associated with a later and more posterior P3 modulation. Moreover, updating was associated with a P2-like potential at centro-parietal electrodes, likely capturing integration processes between prior beliefs and likelihood of the observed event. These findings support previous evidence of trial-by-trial variability of P3 amplitudes as an index of dissociable inferential processes. Coupled with our previous findings, the present study strongly bolsters the view of the P3 as a key brain signature of temporal Bayesian inference. Data and scripts are shared on OSF: osf.io/sdy8j/.

Subjective experience of time in dementia with Lewy bodies during COVID-19 lockdown.

Dementia with Lewy bodies (DLB) is a neurodegenerative disease characterized by cognitive, behavioral and motor symptoms and has a more challenging clinical management and poorer prognosis compared to other forms of dementia. The experience of lockdown leads to negative psychological outcomes for fragile people such as elderly with dementia, particularly for DLB, causing a worsening of cognitive and neuropsychiatric symptoms. Since an individual's feeling of time passage is strongly related to their cognitive and emotional state, it is conceivable to expect alterations of this construct in people with DLB during such a difficult period. We therefore assessed the subjective experience of the passage of time for present and past time intervals (Subjective Time Questionnaire, STQ) during the lockdown due to coronavirus disease (COVID-19) in 22 patients with DLB (17 of which were re-tested in a post-lockdown period) and compared their experience with that of 14 caregivers with similar age. Patients showed a significantly slower perception of present and past time spent under lockdown restrictions. We argue that these alterations might be related to the distinctive features of DLB and their exacerbation recorded by the patients' caregivers during the period of lockdown, though our results show that the patients' experience of time passage in a post-lockdown period remained similarly slow. Overall, we show an impairment of the subjective perception of time passage in DLB tested during the COVID-19 lockdown. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-021-01811-7.

Effect of group-based vs individualized stimulation site selection on reliability of network-targeted TMS.

BACKGROUND: Transcranial magnetic stimulation (TMS) is a widely used technique for the noninvasive assessment and manipulation of brain activity and behavior. Although extensively used for research and clinical purposes, recent studies have questioned the reliability of TMS findings because of the high inter-individual variability that has been observed. OBJECTIVE: In this study, we compared the efficacy and reliability of different targeting scenarios on the TMS-evoked response. METHODS: 24 subjects underwent a single pulse stimulation protocol over two parietal nodes belonging to the Dorsal Attention (DAN) and Default Mode (DMN) Networks respectively. Across visits, the stimulated target for both networks was chosen either based on group-derived networks' maps or personalized network topography based on individual anatomy and functional profile. All stimulation visits were conducted twice, one month apart, during concomitant electroencephalography recording. RESULTS: At the network level, we did not observe significant differences in the TMS-evoked response between targeting conditions. However, reliable patterns of activity were observed- for both networks tested- following the individualized targeting approach. When the same analyses were carried out at the electrode space level, evidence of reliable patterns was observed following the individualized stimulation of the DAN, but not of the DMN. CONCLUSIONS: Our findings suggest that individualization of stimulation sites might ensure reliability of the evoked TMS-response across visits. Furthermore, individualized stimulation sites appear to be of foremost importance in highly variable, high order task-positive networks, such as the DAN.

Maximizing brain networks engagement via individualized connectome-wide target search.

BACKGROUND: In recent years, the possibility to noninvasively interact with the human brain has led to unprecedented diagnostic and therapeutic opportunities. However, the vast majority of approved interventions and approaches still rely on anatomical landmarks and rarely on the individual structure of networks in the brain, drastically reducing the potential efficacy of neuromodulation. OBJECTIVE: Here we implemented a target search algorithm leveraging on mathematical tools from Network Control Theory (NCT) and whole brain connectomics analysis. By means of computational simulations, we aimed to identify the optimal stimulation target(s)- at the individual brain level- capable of reaching maximal engagement of the stimulated networks' nodes. RESULTS: At the model level, in silico predictions suggest that stimulation of NCT-derived cerebral sites might induce significantly higher network engagement, compared to traditionally employed neuromodulation sites, demonstrating NCT to be a useful tool in guiding brain stimulation. Indeed, NCT allows us to computationally model different stimulation scenarios tailored on the individual structural connectivity profiles and initial brain states. CONCLUSIONS: The use of NCT to computationally predict TMS pulse propagation suggests that individualized targeting is crucial for more successful network engagement. Future studies will be needed to verify such prediction in real stimulation scenarios.

Presurgical predictors of early cognitive outcome after brain tumor resection in glioma patients.

Gliomas are commonly characterized by neurocognitive deficits that strongly impact patients' and caregivers' quality of life. Surgical resection is the mainstay of therapy, and it can also cause cognitive impairment. An important clinical problem is whether patients who undergo surgery will show post-surgical cognitive impairment above and beyond that present before surgery. The relevant rognostic factors are largely unknown. This study aims to quantify the cognitive impairment in glioma patients 1-week after surgery and to compare different pre-surgical information (i.e., cognitive performance, tumor volume, grading, and lesion topography) towards predicting early post-surgical cognitive outcome. We retrospectively recruited a sample of N = 47 patients affected by high-grade and low-grade glioma undergoing brain surgery for tumor resection. Cognitive performance was assessed before and immediately after (∼1 week) surgery with an extensive neurocognitive battery. Multivariate linear regression models highlighted the combination of predictors that best explained post-surgical cognitive impairment. The impact of surgery on cognitive functioning was relatively small (i.e., 85% of test scores across the whole sample indicated no decline), and pre-operative cognitive performance was the main predictor of early post-surgical cognitive outcome above and beyond information from tumor topography and volume. In fact, structural lesion information did not significantly improve the accuracy of prediction made from cognitive data before surgery. Our findings suggest that post-surgery neurocognitive deficits are only partially explained by preoperative brain damage. The present results suggest the possibility to make reliable, individualized, and clinically relevant predictions from relatively easy-to-obtain information.

Depressive symptoms and cognitive control: the role of affective interference.

Depressive symptoms are characterised by reduced cognitive control. However, whether depressive symptoms are linked to difficulty in exerting cognitive control in general or over emotional content specifically remains unclear. To better differentiate between affective interference or general cognitive control difficulties in people with depressive symptoms, we employed a non emotional (cold) and an emotional (hot) version of a task-switching paradigm in a nonclinical sample of young adults (N = 82) with varying levels of depressive symptoms. Depressive symptoms were linked to greater difficulties in exerting cognitive control in complex situations (mixed-task blocks) compared to simple and semiautomatic situations (single-task blocks) in both task versions. Moreover, greater depressive symptoms were associated with longer latencies in the emotional version of the task across all trial types. Thus, the emotion-specific effect was not modulated by the degree of cognitive control required to perform the task. In sum, depressive symptoms were characterised by a general difficulty to exert cognitive control in both emotional and non emotional contexts and by greater difficulty in even simple attentional processing of emotional material. This study granted novel insights on the extent of cognitive control difficulties in emotional and non emotional contexts for people with depressive symptoms.

Transcranial magnetic stimulation treatment in Alzheimer's disease: a meta-analysis of its efficacy as a function of protocol characteristics and degree of personalization.

Alzheimer's disease (AD) represents the most common type of neurodegenerative disorder. Although our knowledge on the causes of AD remains limited and no curative treatments are available, several interventions have been proposed in trying to improve patients' symptomatology. Among those, transcranial magnetic stimulation (TMS) has been shown a promising, safe and noninvasive intervention to improve global cognitive functioning. Nevertheless, we currently lack agreement between research studies on the optimal stimulation protocol yielding the highest efficacy in these patients. To answer this query, we conducted a systematic literature search in PubMed, PsycINFO and Scopus databases and meta-analysis of studies published in the last 10 years (2010-2021) according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Differently from prior published meta-analytic work, we investigated whether protocols that considered participants-specific neuroimaging scans for the selection of individualized stimulation targets held more successful outcomes compared to those relying on a generalized targeting selection criteria. We then compared the effect sizes of subsets of studies based on additional protocol characteristics (frequency, duration of intervention, number of stimulation sites, use of concomitant cognitive training and patients' educational level). Our results confirm TMS efficacy in improving global cognitive functioning in mild-to-moderate AD patients, but also highlight the flaws of current protocols characteristics, including a possible lack of sufficient personalization in stimulation protocols.

High-density EEG sleep correlates of cognitive and affective impairment at 12-month follow-up after COVID-19.

OBJECTIVE: To disentangle the pathophysiology of cognitive/affective impairment in Coronavirus Disease-2019 (COVID-19), we studied long-term cognitive and affective sequelae and sleep high-density electroencephalography (EEG) at 12-month follow-up in people with a previous hospital admission for acute COVID-19. METHODS: People discharged from an intensive care unit (ICU) and a sub-intensive ward (nonICU) between March and May 2020 were contacted between March and June 2021. Participants underwent cognitive, psychological, and sleep assessment. High-density EEG recording was acquired during a nap. Slow and fast spindles density/amplitude/frequency and source reconstruction in brain gray matter were extracted. The relationship between psychological and cognitive findings was explored with Pearson correlation. RESULTS: We enrolled 33 participants ( 17 nonICU) and 12 controls. We observed a lower Physical Quality of Life index, higher post-traumatic stress disorder (PTSD) score, and a worse executive function performance in nonICU participants. Higher PTSD and Beck Depression Inventory scores correlated with lower executive performance. The same group showed a reorganization of spindle cortical generators. CONCLUSIONS: Our results show executive and psycho-affective deficits and spindle alterations in COVID-19 survivors - especially in nonICU participants - after 12 months from discharge. SIGNIFICANCE: These findings may be suggestive of a crucial contribution of stress experienced during hospital admission on long-term cognitive functioning.

Impaired cognitive control in patients with brain tumors.

Though the assessment of cognitive functions is proven to be a reliable prognostic indicator in patients with brain tumors, some of these functions, such as cognitive control, are still rarely investigated. The objective of this study was to examine proactive and reactive control functions in patients with focal brain tumors and to identify lesioned brain areas more at "risk" for developing impairment of these functions. To this end, a group of twenty-two patients, candidate to surgery, were tested with an AX-CPT task and a Stroop task, along with a clinical neuropsychological assessment, and their performance was compared to that of a well-matched healthy control group. Although overall accuracy and response times were similar for patients and control groups, the patient group failed more on the BX trials of the AX-CPT task and on the incongruent trials of the Stroop task, specifically. Behavioral results were associated with the damaged brain areas, mostly distributed in right frontal regions, by means of a lesion-symptom mapping multivariate approach. This analysis showed that a white matter cluster in the right prefrontal area was associated with lower d'-context values on the AX-CPT, which reflected the fact that these patients rely more on later information (reactive processes) to respond to unexpected and conflicting stimuli, than on earlier contextual cues (proactive processes). Taken together, these results suggest that patients with brain tumors present an imbalance between proactive and reactive control strategies in high interfering conditions, in association with right prefrontal white matter lesions.

Fronto-parietal homotopy in resting-state functional connectivity predicts task-switching performance.

Homotopic functional connectivity reflects the degree of synchrony in spontaneous activity between homologous voxels in the two hemispheres. Previous studies have associated increased brain homotopy and decreased white matter integrity with performance decrements on different cognitive tasks across the life-span. Here, we correlated functional homotopy, both at the whole-brain level and specifically in fronto-parietal network nodes, with task-switching performance in young adults. Cue-to-target intervals (CTI: 300 vs. 1200 ms) were manipulated on a trial-by-trial basis to modulate cognitive demands and strategic control. We found that mixing costs, a measure of task-set maintenance and monitoring, were significantly correlated to homotopy in different nodes of the fronto-parietal network depending on CTI. In particular, mixing costs for short CTI trials were smaller with lower homotopy in the superior frontal gyrus, whereas mixing costs for long CTI trials were smaller with lower homotopy in the supramarginal gyrus. These results were specific to the fronto-parietal network, as similar voxel-wise analyses within a control language network did not yield significant correlations with behavior. These findings extend previous literature on the relationship between homotopy and cognitive performance to task-switching, and show a dissociable role of homotopy in different fronto-parietal nodes depending on task demands.