Biology subjects

Siddiqi, S. H.

Publications and source records attributed to Siddiqi, S. H..

13 recordsLinked to original sources

bioRxiv2026

Network Localization of Anxiety as an Early Manifestation of Alzheimer's Disease-related Neurodegeneration

Objective Anxiety is a prominent neuropsychiatric symptom in preclinical Alzheimer's disease (AD), but the neural circuitry linking anxiety and AD remains uncharacterized. We assessed whether anxiety in preclinical AD is independently associated with AD-related neurodegeneration and localizes to a common anxiety network. Methods In cognitively unimpaired (CU) older adults with 3T MRI and amyloid-beta PET (N=1,775), we examined whether an established AD-related atrophy network is associated with anxiety (STAI-6). Then, using Atrophy Network Mapping (ANM), which maps individual cortical atrophy patterns onto a normative functional connectome (N=1000), we derived an anxiety network. We tested its 1) spatial convergence with the AD network and with a causal anxiety network derived from lesion and neuromodulation data, 2) specificity relative to depression, 3) generalizability in samples from independent cohorts with AD and Parkinson's disease (total n=878), and 4) association with longitudinal outcomes. Results In CU older adults, greater AD-network atrophy was associated with higher anxiety, independent of depression, cognition, cortical atrophy, and amyloid burden. Anxiety localized to a network closely resembling the AD network (r=0.74, p=0.04) and the causal anxiety network (r=0.72, p=0.02). This convergence extended across the AD continuum and to the Parkinson's disease cohort and was specific to anxiety relative to depression. Greater anxiety-network atrophy was associated with cognitive decline over 4.6 years. Conclusion Anxiety localizes to a brain circuit resembling the AD-related atrophy network, is consistent across the AD continuum and may extend beyond AD. These findings support anxiety as an independent marker of early AD-related neurodegeneration.

neuroscience↗

bioRxiv2026

Non-invasive Neuromodulation Targeting Approach by Mapping Stimulations and Lesions That Modify Visual Memory

Therapeutic brain stimulation is believed to target specific networks, but targeting approaches for memory remain debated. For other symptoms, neuromodulation targets have been localized by mapping connectivity of lesions and stimulation sites to specific symptoms. This approach has yielded networks for global memory, but it remains unclear whether it applies to specific types of memory. Here, we mapped connectivity of stimulation sites, lesions, and atrophy patterns associated with different memory types. We included 544 individuals across three datasets: transcranial magnetic stimulation (N=262), penetrating head trauma (N=169), and ischemic stroke (N=113). We identified a network preferentially connected to lesions and stimulation sites specifically associated with changes in visual memory. Of note, the direction of this effect was inverted depending on whether lesions or stimulation occurred at younger age or an older age, consistent with prior results. This age effect was replicated in an independent dataset of patients with preclinical Alzheimers disease (N=1240). To examine neuromodulation targets, we computed electrical field models for potential TMS sites that overlap with the networks derived from each stimulation or lesion dataset; the resulting targets intersected with established targets that demonstrated efficacy for treating memory impairment - precuneus, cortical-hippocampal network, and dorsolateral prefrontal cortex - with peak intersection at medial posterior parietal lobe, angular gyrus, and left anterior middle frontal gyrus, respectively. Future head-to-head clinical trials are needed to systematically compare these proposed neuromodulation targets against each other. One Sentence SummaryNeuromodulation targets for visual memory diverge by age at the time of injury or stimulation.

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bioRxiv2026

A network for self-transcendence derived from patients with brain lesions

Self-transcendence, the reorientation of experience away from the self toward others, nature, or broader meaning, is a fundamental dimension of human psychology, yet its causal neural architecture remains poorly understood. Here we applied lesion network mapping to 88 neurosurgical patients with pre- and post-operative assessments of trait self-transcendence to identify the distributed brain network whose disruption alters this capacity. The resulting network showed significant spatial correspondence with the default mode network and, at a finer parcellation level, with frontoparietal control subnetworks. Leave-one-out analyses identified posterior midline regions as the most stable correlates of increased self-transcendence following brain lesions. Independent validation against fMRI meta-analyses of self-referential processing, compassion, and ketamine administration, alongside a neuromodulation target previously shown to modulate the sense of self, converged on a consistent model. These findings provide causal evidence for a network architecture in which posterior midline hubs constrain, and brainstem and anterior midline regions facilitate, self-transcendent experience.

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bioRxiv2026

Impact of Censoring on the Quality of Cortical Parcellations and Personalized TMS Targets

Head motion systematically biases functional connectivity (FC) estimates in resting-state functional MRI (rs-fMRI). A common mitigation strategy is to censor high-motion volumes and discard high-motion runs. However, overly stringent censoring risks discarding signal alongside noise, potentially degrading FC estimates. Here, we test the efficacy of various censoring strategies on individual-specific cortical parcellations and personalized transcranial magnetic stimulation (TMS) target selection. Using precision-fMRI datasets comprising 50 individuals, we define individualized "ground-truth" references from [≥]1 hour of low-motion data per participant. We then simulate 10-min or 20-min rs-fMRI sessions with varying motion levels from the remaining data, yielding final samples of 22 and 19 participants, respectively. Higher motion produces parcellations and TMS targets that deviate further from the ground-truth references. However, at any given motion level, lenient censoring produces higher quality parcellations and personalized TMS targets than strict censoring. The improvement is comparable to doubling scan duration from 20 to 40 min under strict censoring. With personalized connectome-guided TMS, a common dilemma is whether to re-scan patients with only high-motion runs. A mixed-motion session with one low-motion run and one high-motion run may often be considered usable after discarding the high-motion run and strict censoring. We find that lenient censoring of high-motion-only sessions yields TMS targets comparable to - or even better than - those derived from strictly censored mixed-motion sessions. Therefore, within the motion range and parcellation/TMS targeting frameworks evaluated here, patients may not need to be re-scanned solely because all runs exceed strict censoring criteria.

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bioRxiv2026

The methodological foundations of lesion network mapping remain sound

Lesion network mapping (LNM) and related techniques have been used in over 200 studies, primarily to test whether anatomically distributed lesions that cause the same symptom fall within a common brain network. A recent article1 challenges the specificity and validity of this technique, suggesting that lesion network maps primarily reflect intrinsic properties of the normative connectome rather than lesion-symptom relationships. However, the data and procedures in van den Heuvel et al. do not reflect those used in most LNM studies. Further, the main conclusions were based on similarity between maps, but similarity does not imply the absence of meaningful differences. In contrast, LNM provides evidence for meaningful differences using specificity testing. Exemplary analyses of 1090 lesion locations from 34 prior LNM studies do not support van den Heuvels concerns and confirm the lesion-deficit specificity of LNM. While we encourage further methodological investigation, the analyses of van den Heuvel et al. do not invalidate prior LNM findings or future applications.

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bioRxiv2026

Focal brain stimulation sites that modify autonomic arousal map to a convergent brain circuit and potential therapeutic target

Causal modulation of autonomic outflow could yield new therapeutic targets for autonomic hyperactivation. We employed three natural experiments in which different brain regions were targeted using transcranial magnetic stimulation (TMS) (n=139 sites, n=14 individuals), deep brain stimulation (n=392 sites, n=58 individuals), or low-intensity focused ultrasound (n=46 sites, n=23 individuals) with subsequent autonomic measurements. Using a human connectome database (n=1000) as a wiring diagram, we identified a convergent brain circuit that, when focally modulated, transiently reduces autonomic arousal. This circuit significantly resembled previously reported causal circuits for posttraumatic stress disorder (PTSD) and anxiety. In independent datasets, TMS to the autonomic arousal circuit reduced laboratory startle in healthy volunteers (n=28), lesions to this circuit reduced exaggerated startle in PTSD (n=193), and TMS to this circuit reduced anxiety-related autonomic symptoms in patients with clinically significant anxiety (n=30). Thus, the convergent circuit may serve as a potential neuromodulation target for autonomic hyperactivation.

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bioRxiv2025

Proximity to an SGC-DLPFC Individualized Functional Target and outcomes in large rTMS clinical trials for Treatment-Resistant Depression

BackgroundTargeting methods for repetitive transcranial magnetic stimulation (rTMS) in patients with depression now include the use of individual functional scans to target specific functional connectivity (FC) patterns obtained from functional magnetic resonance imaging (fMRI). Potential biomarkers of rTMS response include target FC with the subgenual anterior cingulate cortex (SGC) or the causal depression circuit (CDC), each of which may be candidates for individualized functional targets (iFTs). We assessed the relationship of these two approaches to clinical outcomes in two large rTMS clinical trials. Methods501 subjects with moderate to severe depression underwent 4-6 weeks of daily rTMS to the left dorsolateral prefrontal cortex (DLPFC), targeted using neuronavigation to a common group-based functional target. Resting-state scans acquired at baseline were used to retrospectively compute iFTs using either SGC-DLPFC or CDC-DLPFC FC. The Euclidean distance from the group-based target used in the trial to the centre of gravity of each iFT was computed and correlated with outcomes. ResultsMost subjects iFTs were within 2cm of their group-based target. Proximity to either the SGC- or CDC-iFT was not associated with better outcomes. Sensitivity analyses accounting for treatment target FC, methodology, data quality, or treatment parameters did not change the results. ConclusionsProximity to SGC- or CDC-derived iFTs was not associated with better outcomes in patients who received neuronavigated rTMS to a group-based target. Prospective randomized clinical trials comparing neuronavigated group-based target to neuronavigated iFTs are needed.

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bioRxiv2025

Network-based Near-Scalp Personalized Brain Stimulation Targets

Functional connectivity (FC) is often used to identify personalized targets for transcranial magnetic stimulation (TMS). However, existing methods often overlook individual differences in whole-cortex network organization. Furthermore, in some personalized TMS protocols, lower stimulation intensity is used for targets closer to the scalp, which may improve patient tolerance. Here, we develop an algorithm to simultaneously optimize FC and scalp proximity for target localization. We first use the multi-session hierarchical Bayesian model (MS-HBM) to estimate high-quality individual-specific cortical networks. A tree-based algorithm is then used to select the optimal target. With essentially no parameter to tune, our framework may potentially improve generalizability across populations. We compare our approach to existing "cluster" and "cone" algorithms. In two test-retest datasets of healthy individuals from the United States and Singapore, tree-based MS-HBM reliably identifies personalized TMS targets for depression near the scalp. Tree-based MS-HBM targets compare favorably with cluster and cone targets in terms of reliability, scalp proximity, and FC to the subgenual anterior cingulate cortex (sACC) in new out-of-sample MRI sessions. To demonstrate versatility, the same algorithm identifies personalized anxiety targets without tuning any parameter. In patients with treatment-resistant depression, tree-based MS-HBM targets compare favorably with cluster and cone targets in terms of reliability, scalp proximity, and sACC FC, hypothetically reducing stimulation intensity by 15% and 5% respectively. MS-HBM also exhibits the best (most negative) electric-field hotspot sACC FC and highest reliability in induced electric fields. Overall, tree-based MS-HBM provides a robust, generalizable framework to estimate near-scalp personalized targets across populations.

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bioRxiv2024

Lesions that Cause Psychosis Map to a Common Brain Circuit in the Hippocampus

ImportanceIdentifying anatomy causally involved in psychosis could inform therapeutic neuromodulation targets for schizophrenia. ObjectiveTo assess whether lesions that cause secondary psychosis have functional connections to a common brain circuit. DesignThis case-control study mapped functional connections of published cases of lesions causing secondary psychosis compared with control lesions unassociated with psychosis. SettingThis study was conducted in a computational laboratory. ParticipantsPublished cases of lesion-induced psychosis were analyzed. Included subjects had documented brain lesions associated with new-onset psychotic symptoms without prior history of psychosis. Control cases included 1156 patients with lesions not associated with psychosis. Generalizability across lesional datasets was assessed using an independent cohort of 181 patients with brain lesions who subsequently underwent neurobehavioral testing. ExposuresLesions causing secondary psychosis. Main Outcomes and MeasuresPsychosis or no psychosis. Results153 lesions from published cases were determined to be causal of psychosis (65 [42%] male; mean [SD] age, 50.0 [20.8] years), 42 of which were described as "schizophrenia" or "schizophrenia-like". Lesions that caused secondary psychosis mapped to a common brain circuit defined by functional connectivity to the posterior subiculum of the hippocampus (84% functional overlap, pFWE<5 x 10-5). At a lower statistical threshold (75%> overlap, pFWE<5 x 10-4), this circuit included the ventral tegmental area, retrosplenial cortex, lobule IX and dentate nucleus of the cerebellum, and the mediodorsal and midline nuclei of the thalamus. This circuit was consistent when derived from "schizophrenia-like" cases (spatial r=0.98). We repeated these analyses after excluding lesions intersecting the hippocampus (n=47) and found a consistent functional connectivity profile (spatial r=0.98) with the posterior subiculum remaining the center of connectivity (>75% overlap, pFWE<5x10-5), demonstrating a circuit-level effect. In an independent observational cohort of patients with penetrating head trauma (n=181), lesions associated with symptoms of psychosis exhibited significantly similar connectivity profiles to the lesion-derived psychosis circuit (suspiciousness, p=0.025; unusual thought content, p=0.046). Voxels in the rostromedial prefrontal cortex (rmPFC) are highly correlated with this psychosis circuit (spatial r=0.82), suggesting the rmPFC as a promising TMS target for psychosis. Conclusions and RelevanceLesions that cause secondary psychosis affect a common brain circuit in the hippocampus. These results can help inform therapeutic neuromodulation targeting. Key PointsO_ST_ABSQuestionC_ST_ABSDo lesions that cause psychosis affect a common brain circuit? FindingsThis case-control study found that lesions causing psychosis specifically affected a common functional circuit aligning with the posterior subiculum of the hippocampus. This functional circuit was consistent across different psychotic symptoms, suggesting a shared neural substrate for psychosis. A similar circuit was derived when excluding lesions directly intersecting the hippocampus, indicating a circuit-level effect. MeaningIdentifying a common brain circuit causally involved in psychotic symptoms suggests that the hippocampus may be pivotal in the pathophysiology and treatment targeting of psychotic disorders.

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bioRxiv2023

A neural network for religious fundamentalism derived from patients with brain lesions

Religious fundamentalism, characterized by rigid adherence to a set of beliefs putatively revealing inerrant truths, is ubiquitous across cultures and has a global impact on society. Understanding the psychological and neurobiological processes producing religious fundamentalism may inform a variety of scientific, sociological, and cultural questions. Research indicates that brain damage can alter religious fundamentalism. However, the precise brain regions involved with these changes remain unknown. Here, we analyzed brain lesions associated with varying levels of religious fundamentalism in two large datasets from independent laboratories. Lesions associated with greater fundamentalism were connected to a specific brain network with nodes in the right orbitofrontal, dorsolateral prefrontal, and inferior parietal lobes. This fundamentalism network was strongly right hemisphere lateralized and highly reproducible across the independent datasets (r = 0.82) with cross-validations between datasets. To explore the relationship of this network to lesions previously studied by our group, we tested for similarities to twenty-one lesion-induced conditions. Lesions associated with confabulation and criminal behavior showed a similar connectivity pattern as lesions associated with greater fundamentalism. Moreover, lesions associated with poststroke pain showed a similar connectivity pattern as lesions associated with lower fundamentalism. These findings are consistent with hemispheric specializations in reasoning and lend insight into previously observed epidemiological associations with fundamentalism, such as cognitive rigidity and outgroup hostility.

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bioRxiv2023

Lesion Network Localization of a Stable Personality Trait

ObjectiveTo identify a convergent neuroanatomical substrate for novelty seeking (NS), a stable personality trait, which could serve as a therapeutic target for transcranial magnetic stimulation (TMS). MethodsWe analyzed two independent datasets (total n=136) in which the Temperament and Character Inventory (TCI) was used to document alterations across 7 stable personality traits before and after brain lesions surgically induced by glioma resection. Using lesion network mapping, we examined whether alterations in NS were causally associated with lesions to specific brain networks. We assessed for strength of replication across datasets and specificity against other personality traits. ResultsLesion locations that are linked to NS map to a common brain with its largest cluster in the dorsal cingulate. This map was specific to NS relative to other personality traits and overlapped with prior published neuroimaging findings related to the term "novelty". Utilizing a pre-computed connectome, we also derived a map highlighting potential targets for non-invasive brain stimulation that may alter this stable personality trait. ConclusionsWe derived and cross-validated a brain network that is functionally connected to lesions that are causally responsible for the stable personality trait "novelty seeking". Lesions to this network were associated with changes in NS. This includes a superficial node within the dorsolateral prefrontal cortex that may serve as a promising TMS target to modulate or protect against abnormal NS.

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bioRxiv2021

Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression

BackgroundAt the group level, antidepressant efficacy of rTMS targets is inversely related to their normative connectivity with subgenual anterior cingulate cortex (sgACC). Individualized connectivity may yield better targets, particularly in patients with neuropsychiatric disorders who may have aberrant connectivity. However, sgACC connectivity shows poor test-retest reliability at the individual level. Individualized resting-state network mapping (RSNM) can reliably map inter-individual variability in brain network organization. ObjectiveTo identify individualized RSNM-based rTMS targets that reliably target the sgACC connectivity profile. MethodsWe used RSNM to identify network-based rTMS targets in 10 healthy controls and 13 individuals with traumatic brain injury-associated depression (TBI-D). These "RSNM targets" were compared with consensus structural targets and targets based on individualized anti-correlation with a group-mean-derived sgACC region ("anti-group-mean sgACC targets"). The TBI-D cohort was randomized to receive active (n=9) or sham (n=4) rTMS to RSNM targets. ResultsThe group-mean sgACC connectivity profile was reliably estimated by individualized correlation with default mode network (DMN) and anti-correlation with dorsal attention network (DAN). Individualized RSNM targets were then identified based on DAN anti-correlation and DMN correlation. Counterintuitively, anti-correlation with the group-mean sgACC connectivity profile was stronger and more reliable for RSNM-derived targets than for "anti-group-mean sgACC targets". Improvement in depression after RSNM-targeted rTMS was predicted by target anti-correlation with the portions of sgACC. Active treatment led to increased connectivity within and between several relevant regions. ConclusionsRSNM may enable reliable individualized rTMS targeting, although further research is needed to determine whether this personalized approach can improve clinical outcomes.

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bioRxiv2017

rTMS with individualized resting-state network mapping for neuropsychiatric sequelae of repetitive traumatic brain injury in a retired NFL player

The recent advent of individualized resting-state network mapping (RSNM) has revealed substantial inter-individual variability in anatomical localization of brain networks identified using resting-state functional MRI (rsfMRI). Such variability may be particularly important after repetitive traumatic brain injury (TBI), which is associated with treatment-resistant depression. RSNM enables personalized targeting of repetitive transcranial magnetic stimulation (rTMS), a focal brain stimulation technique that relieves depression when administered over dorsolateral prefrontal cortex.\n\nRSNM was used to identify left/right dorsolateral prefrontal rTMS targets with maximal difference between dorsal attention network and default mode network (DMN) correlations. These targets were spatially distinct from those identified by prior methods. The method was evaluated by administering twenty sessions of left-sided excitatory and right-sided inhibitory rTMS to a retired NFL defensive lineman with progressive treatment-resistant neuropsychiatric disturbances. Treatment led to improvement in Montgomery-Asberg Depression Rating Scale (72%), cognitive testing, and headache scales. In comparison with healthy individuals and subjects with TBI-associated depression, baseline rsfMRI revealed substantially elevated DMN connectivity with medial temporal lobe (MTL). Serial rsfMRI scans showed gradual improvement in MTL-DMN connectivity and stimulation site connectivity with subgenual anterior cingulate cortex. This highlights the possibility of individualized neuromodulation and biomarker-based monitoring for neuropsychiatric sequelae of repetitive TBI.

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