Individualized fMRI connectivity defines signatures of antidepressant and placebo responses in major depression.

Though sertraline is commonly prescribed in patients with major depressive disorder (MDD), its superiority over placebo is only marginal. This is in part due to the neurobiological heterogeneity of the individuals. Characterizing individual-unique functional architecture of the brain may help better dissect the heterogeneity, thereby defining treatment-predictive signatures to guide personalized medication. In this study, we investigate whether individualized brain functional connectivity (FC) can define more predictable signatures of antidepressant and placebo treatment in MDD. The data used in the present work were collected by the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study. Patients (N = 296) were randomly assigned to antidepressant sertraline or placebo double-blind treatment for 8 weeks. The whole-brain FC networks were constructed from pre-treatment resting-state functional magnetic resonance imaging (rs-fMRI). Then, FC was individualized by removing the common components extracted from the raw baseline FC to train regression-based connectivity predictive models. With individualized FC features, the established prediction models successfully identified signatures that explained 22% variance for the sertraline group and 31% variance for the placebo group in predicting HAMD17 change. Compared with the raw FC-based models, the individualized FC-defined signatures significantly improved the prediction performance, as confirmed by cross-validation. For sertraline treatment, predictive FC metrics were predominantly located in the left middle temporal cortex and right insula. For placebo, predictive FC metrics were primarily located in the bilateral cingulate cortex and left superior temporal cortex. Our findings demonstrated that through the removal of common FC components, individualization of FC metrics enhanced the prediction performance compared to raw FC. Associated with previous MDD clinical studies, our identified predictive biomarkers provided new insights into the neuropathology of antidepressant and placebo treatment.

Neurophysiological Measures of Proactive and Reactive Control in Negative Template Use.

In a visual search task, knowing features of distractors in advance leads to a more efficient visual search. Although previous studies suggested that the benefits of these negative cues rely on attentional control, it is unclear whether proactive or reactive control is involved. In this study, we analyzed the EEG data of participants performing a visual search task (n = 14). Participants searched for a shape-defined target after receiving a positive cue (target color), negative cue (distractor color), or neutral cue (non-informative). To examine proactive control, we measured EEG after the cue onset but before visual search. Our time-frequency analysis revealed a higher power of theta oscillations over frontoparietal regions after the negative cues compared with the positive and neutral cues, as well as higher theta phase synchronization within the prefrontal region, demonstrating negative cues rely more heavily on proactive control compared with other cue types. To examine reactive control, we measured EEG after the search onset. We found a lateralization of posterior alpha power toward the target side in both positive and negative cues conditions, with a later lateralization observed after negative cues. Interestingly, we observed a significant relationship between the increase of proactive theta power after negative cues and the decrease of reactive alpha power after the search. This suggests the coordination of proactive and reactive mechanisms lead to the most efficient search.

Flexibility in Attentional Control: Multiple Sources and Suppression.

In daily life, it is critical that we are able to direct our visual attention to information that is important for our tasks while avoiding distracting information. To control our attention, we engage "attentional templates" that reconfigure how incoming visual signals are processed in our brains. But what are these attentional templates and how do they work? Much of our understanding of the nature of attentional templates has been driven by the proposed mechanism linking attentional templates and working memory from the biased competition model [1] (Desimone and Duncan, 1995). Over the past 20 years, research inspired by this proposal has vastly increased our understanding of attentional control. This work has highlighted flexibility in attentional control, with multiple sources of control and flexible enhancement or suppression based on task demands.

How visual working memory contents influence priming of visual attention.

Recent evidence shows that when the contents of visual working memory overlap with targets and distractors in a pop-out search task, intertrial priming is inhibited (Kristjánsson, Sævarsson & Driver, Psychon Bull Rev 20(3):514-521, 2013, Experiment 2, Psychonomic Bulletin and Review). This may reflect an interesting interaction between implicit short-term memory-thought to underlie intertrial priming-and explicit visual working memory. Evidence from a non-pop-out search task suggests that it may specifically be holding distractors in visual working memory that disrupts intertrial priming (Cunningham & Egeth, Psychol Sci 27(4):476-485, 2016, Experiment 2, Psychological Science). We examined whether the inhibition of priming depends on whether feature values in visual working memory overlap with targets or distractors in the pop-out search, and we found that the inhibition of priming resulted from holding distractors in visual working memory. These results are consistent with separate mechanisms of target and distractor effects in intertrial priming, and support the notion that the impact of implicit short-term memory and explicit visual working memory can interact when each provides conflicting attentional signals.

The Control of Single-color and Multiple-color Visual Search by Attentional Templates in Working Memory and in Long-term Memory.

The question whether target selection in visual search can be effectively controlled by simultaneous attentional templates for multiple features is still under dispute. We investigated whether multiple-color attentional guidance is possible when target colors remain constant and can thus be represented in long-term memory but not when they change frequently and have to be held in working memory. Participants searched for one, two, or three possible target colors that were specified by cue displays at the start of each trial. In constant-color blocks, the same colors remained task-relevant throughout. In variable-color blocks, target colors changed between trials. The contralateral delay activity (CDA) to cue displays increased in amplitude as a function of color memory load in variable-color blocks, which indicates that cued target colors were held in working memory. In constant-color blocks, the CDA was much smaller, suggesting that color representations were primarily stored in long-term memory. N2pc components to targets were measured as a marker of attentional target selection. Target N2pcs were attenuated and delayed during multiple-color search, demonstrating less efficient attentional deployment to color-defined target objects relative to single-color search. Importantly, these costs were the same in constant-color and variable-color blocks. These results demonstrate that attentional guidance by multiple-feature as compared with single-feature templates is less efficient both when target features remain constant and can be represented in long-term memory and when they change across trials and therefore have to be maintained in working memory.

The effects of self-focus on attentional biases in social anxiety:An ERP study.

Cognitive theories of social anxiety disorder suggest that biased attention plays a key role in maintaining symptoms. These biases include self-focus and attention to socially threatening stimuli in the environment. The goal of this study was to utilize ERPs that are elicited by a change detection task to examine biases in selective attention (i.e., N2pc) and working memory maintenance (i.e., contralateral delay activity; CDA). Additionally, the effect of self-focus was examined using false heart rate feedback. In support of the manipulation, self-focus cues resulted in greater self-reported self-consciousness and task interference, enhanced anterior P2 amplitude and reduced SPN amplitude. Moreover, P2 amplitude for self-focus cues was correlated with reduced task performance for socially anxious subjects only. The difference in P2 amplitude between self-focus and standard cues was correlated with social anxiety independent of depression. As hypothesized, socially anxious participants (n = 20) showed early selection and maintenance of disgust faces relative to neutral faces as indicated by the N2pc and CDA components. Nonanxious controls (n = 22) did not show these biases. During self-focus cues, controls showed marginal evidence of biased selection for disgust faces, whereas socially anxious subjects showed no bias in this condition. Controls showed an ipsilateral delay activity after being cued to attend to one hemifield. Overall, this study supports early and persistent attentional bias for social threat in socially anxious individuals. Furthermore, self-focus may disrupt these biases. These findings and supplementary data are discussed in light of cognitive models of social anxiety disorder, recent empirical findings, and treatment.

Why are some individuals better at using negative attentional templates to suppress distractors? Exploration of interindividual differences in cognitive control efficiency.

Negative templates are based on foreknowledge of distractor features and can lead to more efficient visual search at the group level. However, large individual differences exist in the size of benefits induced by negative cues. The cognitive factors underlying these interindividual differences remain unknown. Previous research has suggested higher engagement of proactive control for negative templates compared to positive templates. We thus hypothesized that interindividual differences in proactive control efficiency may explain the large variability in negative cue benefits. A large data set made up of data from two previously published studies was reanalyzed (N = 139), with eye movements recorded in 36 participants. Individual proactive control efficiency was measured through reaction time (RT) variability. Participants with higher proactive control efficiency exhibited larger benefits after negative cues across two critical measures: Individuals with higher proactive control showed larger RT benefits following negative compared to neutral cues; similarly, individuals with higher proactive control exhibited lower first saccades to cued distractor items. No such relationship was observed for positive cues. Our results confirmed the existence of large interindividual differences in the benefits induced by negative attentional templates. Critically, we show that proactive control drives these interindividual differences in negative template use. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Distinct mechanisms of attentional suppression: exploration of trait factors underlying cued- and learned-suppression.

Attention allows us to focus on relevant information while ignoring distractions. Effective suppression of distracting information is crucial for efficient visual search. Recent studies have developed two paradigms to investigate attentional suppression: cued-suppression which is based on top-down control, and learned-suppression which is based on selection history. While both types of suppression reportedly engage proactive control, it remains unclear whether they rely on shared mechanisms. This study aimed to determine the relationship between cued- and learned-suppression. In a within-subjects design, 54 participants performed a cued-suppression task where pre-cues indicated upcoming target or distractor colors, and a learned-suppression task where a salient color distractor was present or absent. No significant correlation emerged between performance in the two tasks, suggesting distinct suppression mechanisms. Cued-suppression correlated with visual working memory capacity, indicating reliance on explicit control. In contrast, learned-suppression correlated with everyday distractibility, suggesting implicit control based on regularities. These results provide evidence for heterogeneous proactive control mechanisms underlying cued- and learned-suppression. While both engage inhibition, cued-suppression relies on deliberate top-down control modulated by working memory, whereas learned-suppression involves implicit suppression shaped by selection history and distractibility traits.

Similar Quality of Visual Working Memory Representations between Negative and Positive Attentional Templates.

Visual working memory (VWM) plays an important role during visual search, with some theories suggesting an equivalence between working memory representations and guidance from attentional templates. However, recent work has shown that participants can also use 'negative templates', the foreknowledge of distractor-features stored in VWM, to guide attention away from distractors during visual search. These negative templates must also be represented in working memory, but the question remains whether the quality of the working memory representations underlying negative and positive templates are similar, in spite of their opposite impacts on attention. In this study, participants (N = 33) engaged in a visual search task for a shape-defined target after receiving a positive cue (target color), negative cue (distractor color) or neutral cue (non-informative). In 20% of the trials, a color-wheel probe was presented instead of a search array to measure the quality of the cue representation stored in VWM. Our results revealed that participants were more likely to guess in response to neutral cues than negative cues. Yet, the comparison between positive and negative cues showed no significant differences. However, we found no difference in memory precision for the three cue types. More interestingly, the more the VWM quality is boosted by the negative cue, the greater the ability to guide attention away from distractors. Such a pattern of results might map to recent evidence of between-individuals differences in utilization of negative cues. These findings highlight the distinction between attentional templates and simple maintenance in working memory.

Symptom dimensions of resting-state electroencephalographic functional connectivity in autism.

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by social and communication deficits (SCDs), restricted and repetitive behaviors (RRBs) and fixated interests. Despite its prevalence, development of effective therapy for ASD is hindered by its symptomatic and neurophysiological heterogeneities. To comprehensively explore these heterogeneities, we developed a new analytical framework combining contrastive learning and sparse canonical correlation analysis that identifies symptom-linked resting-state electroencephalographic connectivity dimensions within 392 ASD samples. We present two dimensions with multivariate connectivity basis exhibiting significant correlations with SCD and RRB, confirm their robustness through cross-validation and demonstrate their conceptual generalizability using an independent dataset (n = 222). Specifically, the right inferior parietal lobe is the core region for RRB, while connectivity between the left angular gyrus and the right middle temporal gyrus show key contribution to SCD. These findings provide a promising avenue to parse ASD heterogeneity with high clinical translatability, paving the way for ASD treatment development and precision medicine.

Dementia Subtypes Defined Through Neuropsychiatric Symptom-Associated Brain Connectivity Patterns.

Importance: Understanding the heterogeneity of neuropsychiatric symptoms (NPSs) and associated brain abnormalities is essential for effective management and treatment of dementia. Objective: To identify dementia subtypes with distinct functional connectivity associated with neuropsychiatric subsyndromes. Design, Setting, and Participants: Using data from the Open Access Series of Imaging Studies-3 (OASIS-3; recruitment began in 2005) and Alzheimer Disease Neuroimaging Initiative (ADNI; recruitment began in 2004) databases, this cross-sectional study analyzed resting-state functional magnetic resonance imaging (fMRI) scans, clinical assessments, and neuropsychological measures of participants aged 42 to 95 years. The fMRI data were processed from July 2022 to February 2024, with secondary analysis conducted from August 2022 to March 2024. Participants without medical conditions or medical contraindications for MRI were recruited. Main Outcomes and Measures: A multivariate sparse canonical correlation analysis was conducted to identify functional connectivity-informed NPS subsyndromes, including behavioral and anxiety subsyndromes. Subsequently, a clustering analysis was performed on obtained latent connectivity profiles to reveal neurophysiological subtypes, and differences in abnormal connectivity and phenotypic profiles between subtypes were examined. Results: Among 1098 participants in OASIS-3, 177 individuals who had fMRI and at least 1 NPS at baseline were included (78 female [44.1%]; median [IQR] age, 72 [67-78] years) as a discovery dataset. There were 2 neuropsychiatric subsyndromes identified: behavioral (r = 0.22; P = .002; P for permutation = .007) and anxiety (r = 0.19; P = .01; P for permutation = .006) subsyndromes from connectivity NPS-associated latent features. The behavioral subsyndrome was characterized by connections predominantly involving the default mode (within-network contribution by summed correlation coefficients = 54) and somatomotor (within-network contribution = 58) networks and NPSs involving nighttime behavior disturbance (R = -0.29; P < .001), agitation (R = -0.28; P = .001), and apathy (R = -0.23; P = .007). The anxiety subsyndrome mainly consisted of connections involving the visual network (within-network contribution = 53) and anxiety-related NPSs (R = 0.36; P < .001). By clustering individuals along these 2 subsyndrome-associated connectivity latent features, 3 subtypes were found (subtype 1: 45 participants; subtype 2: 43 participants; subtype 3: 66 participants). Patients with dementia of subtype 3 exhibited similar brain connectivity and cognitive behavior patterns to those of healthy individuals. However, patients with dementia of subtypes 1 and 2 had different dysfunctional connectivity profiles involving the frontoparietal control network (FPC) and somatomotor network (the difference by summed z values was 230 within the SMN and 173 between the SMN and FPC for subtype 1 and 473 between the SMN and visual network for subtype 2) compared with those of healthy individuals. These dysfunctional connectivity patterns were associated with differences in baseline dementia severity (eg, the median [IQR] of the total score of NPSs was 2 [2-7] for subtype 3 vs 6 [3-8] for subtype 1; P = .04 and 5.5 [3-11] for subtype 2; P = .03) and longitudinal progression of cognitive impairment and behavioral dysfunction (eg, the overall interaction association between time and subtypes to orientation was F = 4.88; P = .008; using the time × subtype 3 interaction item as the reference level: ß = 0.05; t = 2.6 for time × subtype 2; P = .01). These findings were further validated using a replication dataset of 193 participants (127 female [65.8%]; median [IQR] age, 74 [69-77] years) consisting of 154 newly released participants from OASIS-3 and 39 participants from ADNI. Conclusions and Relevance: These findings may provide a novel framework to disentangle the neuropsychiatric and brain functional heterogeneity of dementia, offering a promising avenue to improve clinical management and facilitate the timely development of targeted interventions for patients with dementia.

Individual deviations from normative electroencephalographic connectivity predict antidepressant response.

BACKGROUND: Antidepressant medications yield unsatisfactory treatment outcomes in patients with major depressive disorder (MDD) with modest advantages over the placebo, partly due to the elusive mechanisms of antidepressant responses and unexplained heterogeneity in patient's response to treatment. Here we develop a novel normative modeling framework to quantify individual deviations in psychopathological dimensions that offers a promising avenue for the personalized treatment for psychiatric disorders. METHODS: We built a normative model with resting-state electroencephalography (EEG) connectivity data from healthy controls of three independent cohorts. We characterized the individual deviation of MDD patients from the healthy norms, based on which we trained sparse predictive models for treatment responses of MDD patients (102 sertraline-medicated and 119 placebo-medicated). Hamilton depression rating scale (HAMD-17) was assessed at both baseline and after the eight-week antidepressant treatment. RESULTS: We successfully predicted treatment outcomes for patients receiving sertraline (r = 0.43, p < 0.001) and placebo (r = 0.33, p < 0.001). We also showed that the normative modeling framework successfully distinguished subclinical and diagnostic variabilities among subjects. From the predictive models, we identified key connectivity signatures in resting-state EEG for antidepressant treatment, suggesting differences in neural circuit involvement between sertraline and placebo responses. CONCLUSIONS: Our findings and highly generalizable framework advance the neurobiological understanding in the potential pathways of antidepressant responses, enabling more targeted and effective personalized MDD treatment. TRIAL REGISTRATION: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC), NCT#01407094.

Discriminative functional connectivity signature of cocaine use disorder links to rTMS treatment response.

Cocaine use disorder (CUD) is prevalent, and repetitive transcranial magnetic stimulation (rTMS) shows promise in reducing cravings. However, the association between a consistent CUD-specific functional connectivity signature and treatment response remains unclear. Here we identify a validated functional connectivity signature from functional magnetic resonance imaging to discriminate CUD, with successful independent replication. We found increased connectivity within the visual and dorsal attention networks and between the frontoparietal control and ventral attention networks, alongside reduced connectivity between the default mode and limbic networks in patients with CUD. These connections were associated with drug use history and cognitive impairments. Using data from a randomized clinical trial, we also established the prognostic value of these functional connectivities for rTMS treatment outcomes in CUD, especially involving the frontoparietal control and default mode networks. Our findings reveal insights into the neurobiological mechanisms of CUD and link functional connectivity biomarkers with rTMS treatment response, offering potential targets for future therapeutic development.

Optimizing Antidepressant Efficacy: Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response.

Major depressive disorder (MDD) is a common and often severe condition that profoundly diminishes quality of life for individuals across ages and demographic groups. Unfortunately, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates in a substantial number of patients. The development of effective therapies for MDD is hindered by the insufficiently understood heterogeneity within the disorder and its elusive underlying mechanisms. To address these challenges, we present a target-oriented multimodal fusion framework that robustly predicts antidepressant response by integrating structural and functional connectivity data (sertraline: R2 = 0.31; placebo: R2 = 0.22). Through the model, we identify multimodal neuroimaging biomarkers of antidepressant response and observe that sertraline and placebo show distinct predictive patterns. We further decompose the overall predictive patterns into constitutive network constellations with generalizable structural-functional co-variation, which exhibit treatment-specific association with personality traits and behavioral/cognitive task performance. Our innovative and interpretable multimodal framework provides novel insights into the intricate neuropsychopharmacology of antidepressant treatment and paves the way for advances in precision medicine and development of more targeted antidepressant therapeutics.

Terms of debate: Consensus definitions to guide the scientific discourse on visual distraction.

Hypothesis-driven research rests on clearly articulated scientific theories. The building blocks for communicating these theories are scientific terms. Obviously, communication - and thus, scientific progress - is hampered if the meaning of these terms varies idiosyncratically across (sub)fields and even across individual researchers within the same subfield. We have formed an international group of experts representing various theoretical stances with the goal to homogenize the use of the terms that are most relevant to fundamental research on visual distraction in visual search. Our discussions revealed striking heterogeneity and we had to invest much time and effort to increase our mutual understanding of each other's use of central terms, which turned out to be strongly related to our respective theoretical positions. We present the outcomes of these discussions in a glossary and provide some context in several essays. Specifically, we explicate how central terms are used in the distraction literature and consensually sharpen their definitions in order to enable communication across theoretical standpoints. Where applicable, we also explain how the respective constructs can be measured. We believe that this novel type of adversarial collaboration can serve as a model for other fields of psychological research that strive to build a solid groundwork for theorizing and communicating by establishing a common language. For the field of visual distraction, the present paper should facilitate communication across theoretical standpoints and may serve as an introduction and reference text for newcomers.

Where do we store the memory representations that guide attention?

During the last decade one of the most contentious and heavily studied topics in the attention literature has been the role that working memory representations play in controlling perceptual selection. The hypothesis has been advanced that to have attention select a certain perceptual input from the environment, we only need to represent that item in working memory. Here we summarize the work indicating that the relationship between what representations are maintained in working memory and what perceptual inputs are selected is not so simple. First, it appears that attentional selection is also determined by high-level task goals that mediate the relationship between working memory storage and attentional selection. Second, much of the recent work from our laboratory has focused on the role of long-term memory in controlling attentional selection. We review recent evidence supporting the proposal that working memory representations are critical during the initial configuration of attentional control settings, but that after those settings are established long-term memory representations play an important role in controlling which perceptual inputs are selected by mechanisms of attention.

Negative and positive templates: Two forms of cued attentional control.

Our ability to control our attention to focus on goal-relevant information is critical for functioning in daily life. In addition to the typical attentional control driven by target enhancement described in most theories of attention, recent research has focused on our ability to use information about distractions maintained in working memory to direct our attention away from known distractors. Using these negative templates can improve the efficiency of attention, much in the same way as enhancing information matching search targets. However, these effects only occur for specific tasks or in specific circumstances. In this review, I will focus on our emerging understanding of the relationship between distractor ignoring from negative templates and target enhancement from positive templates. I will also highlight key remaining questions for further study.

Assessing recoding accounts of negative attentional templates using behavior and eye tracking.

Can we use attentional control to ignore known distractor features? Providing cues before a visual search trial about an upcoming distractor color (negative cue) can lead to reaction time benefits compared with no cue trials. This suggests top-down control may use negative templates to actively suppress distractor features, a notion that challenges the mechanisms of top-down control provided in many theories of attention. However, there is currently mixed support for this mechanism in the literature. Alternative explanations have been proposed, which do not require suppression within top-down control but instead involve recoding the negative cue into a positive template based on color or spatial layouts. In three experiments, we contrasted the predictions of active suppression and the recoding strategies. Across experiments, we found consistent evidence against a color recoding account. We also found evidence of accuracy, reaction time, and eye movement benefits when location recoding was not possible. These results suggest that prior benefits from negative cues cannot be explained exclusively by spatial or color recoding. The results indicate that active suppression likely plays a role in the attentional benefits following negative cues. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Explicit attentional goals unlock implicit spatial statistical learning.

People can quickly learn spatial distributions of targets and direct attention to likely regions of targets. These implicitly learned spatial biases have been shown to be persistent, transferring to other similar visual search tasks. However, a persistent attentional bias is incompatible with frequently changing goals in our typical daily environment. We propose a flexible goal-specific probability cueing mechanism to address this discrepancy. We examined whether participants could learn and utilize target-specific spatial priority maps across five experiments (each N = 24). In Experiment 1, participants were faster to find the target at the target-specific high-probability location, in line with a goal-specific probability cueing effect. This demonstrated that separate spatial priorities derived from statistical learning can be flexibly activated based on the current goal. In Experiment 2, we ensured the results were not driven solely by intertrial priming. In Experiment 3, we ensured the results were driven by early attentional guidance effects. In Experiment 4, we extended our findings to a complex spatial distribution including four locations, supporting a sophisticated representation of target likelihood in the activated spatial priority maps. Finally, in Experiment 5, we confirmed that the effect was driven by the activation of an attentional template and not associative learning between the target cue and a spatial location. Our findings demonstrate a previously unrecognized mechanism for flexibility within statistical learning. The goal-specific probability cueing effect relies on coordination of feature-based and location-based attention, utilizing information that crosses traditional boundaries between top-down control and selection history. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Defining Dementia Subtypes Through Neuropsychiatric Symptom-Linked Brain Connectivity Patterns.

BACKGROUND: Dementia is highly heterogeneous, with pronounced individual differences in neuropsychiatric symptoms (NPS) and neuroimaging findings. Understanding the heterogeneity of NPS and associated brain abnormalities is essential for effective management and treatment of dementia. METHODS: Using large-scale neuroimaging data from the Open Access Series of Imaging Studies (OASIS-3), we conducted a multivariate sparse canonical correlation analysis to identify functional connectivity-informed symptom dimensions. Subsequently, we performed a clustering analysis on the obtained latent connectivity profiles to reveal neurophysiological subtypes and examined differences in abnormal connectivity and phenotypic profiles between subtypes. RESULTS: We identified two reliable neuropsychiatric subsyndromes - behavioral and anxiety in the connectivity-NPS linked latent space. The behavioral subsyndrome was characterized by the connections predominantly involving the default mode and somatomotor networks and neuropsychiatric symptoms involving nighttime behavior disturbance, agitation, and apathy. The anxiety subsyndrome was mainly contributed by connections involving the visual network and the anxiety neuropsychiatric symptom. By clustering individuals along these two subsyndromes-linked connectivity latent features, we uncovered three subtypes encompassing both dementia patients and healthy controls. Dementia in one subtype exhibited similar brain connectivity and cognitive-behavior patterns to healthy individuals. However, dementia in the other two subtypes showed different dysfunctional connectivity profiles involving the default mode, frontoparietal control, somatomotor, and ventral attention networks, compared to healthy individuals. These dysfunctional connectivity patterns were associated with differences in baseline dementia severity and longitudinal progression of cognitive impairment and behavioral dysfunction. CONCLUSIONS: Our findings shed valuable insights into disentangling the neuropsychiatric and brain functional heterogeneity of dementia, offering a promising avenue to improve clinical management and facilitate the development of timely and targeted interventions for dementia patients.