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[MCWG] Molecular Connectivity Newsletter: April 2026

Molecular Connectivity Working Group Newsletter

April 2026

Greetings from the MCWG!

Thank you to everyone who joined us for March’s MCOS with Penghui Du! Missed it? The recording is available here.

Wishing our community a joyful Easter filled with renewal, inspiration, and continued progress in advancing brain molecular connectivity!


Upcoming MCOS

Date: April 17th, 2026
Time: 13:00 UTC
Registration: Please register here.
Title: Preoperative network activity predicts the response to subthalamic DBS for Parkinson’s disease
Speaker: Dr. Prashin Unadkat

Abstract: Does the brain’s baseline network architecture tell us about an individual’s capacity to respond to neuromodulation? Can we use this to identify which Parkinson’s disease patients will benefit most from deep brain stimulation before they ever reach the operating room? This talk will present our work developing and validating STN StimNet, a treatment-specific metabolic brain network identified in PD patients with implanted subthalamic nucleus (STN) electrodes. Several key questions will be addressed: What distinguishes a treatment-induced network from a disease-related one? What is the electrophysiological basis of this network; specifically, why do STN theta-band oscillations, rather than the pathological beta activity traditionally linked to PD motor impairment, drive StimNet expression? We go on to demonstrate how preoperatively measured network expression with either FDG PET or resting-state fMRI predicts postoperative motor outcomes, and how it compares to the current gold standards for patient selection. Using data from a large cohort of PD patients spanning the clinical spectrum of the disease, we illustrate how these measurements can stratify patients by their likelihood of achieving a clinically meaningful response, while appropriately excluding populations unlikely to benefit, such as those with atypical parkinsonian syndromes. Finally, this predictive framework may have relevance beyond STN-DBS in Parkinson’s disease. The principle that preoperative circuit-level activity shapes an individual’s response to focal neuromodulation could guide patient selection across other DBS targets and may extend to other movement and psychiatric disorders.

Dr. Prashin Unadkat, MBBS, PhD is the Chief Resident in the Department of Neurosurgery at the Zucker School of Medicine at Hofstra/Northwell and an incoming Stereotactic and Functional Neurosurgery fellow at Baylor College of Medicine. His clinical practice focuses on image-guided and neuromodulatory surgical strategies for movement disorders, psychiatric conditions, and epilepsy. His research centers on developing functional and structural brain imaging biomarkers that can predict treatment response and improve surgical planning, with a particular emphasis on network-level analysis of deep brain stimulation effects.


The MCOS promotes rigor in research and resource sharing. We aim to hold MCOS every third Friday of the month, subject to change due to speaker availability. Please stay tuned for MCOS updates and reminders on social media! Thank you!


👩🏻‍🔬 People of MCWG

Each month, we will feature a member of the MCWG and have a brief Q&A!

This month please enjoy our highlight of Prof Dr Daniela Perani, member of the MCWG Steering Committee.

Prof Dr Daniela Perani is an internationally renowned neurologist and neuroscientist, and Professor Emeritus of Neuroscience at the Università Vita-Salute San Raffaele in Milan. She has served as the coordinator of numerous national and international research projects. Her work in the field of cognitive neuroscience has extensively employed neuroimaging techniques to investigate language, memory, and the perception of music. In the clinical domain, she has focused in particular on the neural correlates of neurodegenerative diseases. She has authored more than 400 peer-reviewed publications in international journals, as well as numerous book chapters and books.

Prof Dr Daniela Perani has graciously responded to our feature questionnaire:

What sparked your interest in molecular imaging or led you to focus on research in molecular imaging?

My interest in molecular imaging was sparked early in my career through my work in neuroscience, particularly in the study of brain function and cognitive processes in health and diseases. During my initial training and research activities, I became deeply interested in understanding how complex neurological and cognitive functions—such as language, memory, and neurodegenerative changes—could be linked to underlying biological mechanisms in the living human brain. At that time in the ninety, molecular imaging represented a unique and emerging opportunity to bridge neuroscience and clinical research. My work focused on applying techniques such as MRI and PET to investigate brain anatomy, metabolism and neurotransmitter systems, allowing me to explore both neurological disorders and cognitive processes in vivo. This approach enabled me to connect molecular and functional alterations with clinical symptoms, especially in conditions like dementia and language disorders.  What motivated me most was the possibility of combining advanced imaging technologies with questions about how the brain supports cognition, and how these processes are disrupted in disease. This intersection between molecular mechanisms and neurological and cognitive function has remained a central theme throughout my career.

What is your role in the Molecular Connectivity Working Group, and what have you been contributing to or working on within the group?

Within the Molecular Connectivity Working Group, I currently serve as a member of the Board of Directors, contributing in a senior and advisory capacity. My involvement builds on my earlier work, where I conducted some of the pioneering studies on PET-based molecular connectivity, helping to establish the conceptual and methodological framework that has guided much of the subsequent research in this area. These initial contributions were aimed at demonstrating how molecular imaging, and in particular PET, could be used not only to assess regional brain activity but also to investigate connectivity patterns at a molecular level. This work contributed to opening new directions for understanding brain organization and dysfunction.

In my current role, I remain actively engaged in the group’s activities by providing critical input on ongoing projects, contributing to strategic discussions, and offering guidance on methodological developments. I also support the group through active suggestions and mentorship, helping to ensure scientific rigor and to foster the continued evolution of molecular connectivity research.

In what ways do you imagine molecular connectivity will advance our understanding of brain function?

Molecular connectivity could greatly enhance our understanding of brain function by linking large-scale brain networks to their underlying biochemical processes. Unlike MRI, which captures structural or functional activity indirectly, PET provides insight into metabolism and neurotransmitter systems, bringing us closer to the brain’s biological foundations. However, challenges remain. For example, FDG-PET connectivity is often based on correlations in glucose uptake, whose biological meaning is still unclear — they may reflect true neural interactions, shared inputs, or global effects. Differences between PET and MRI networks further highlight the need for careful multimodal integration. Methodological issues also persist, including sensitivity to noise, variability, and preprocessing choices. These require more robust statistical approaches. The complexity increases with neurotransmitter-based connectivity, where correlations in receptor binding do not necessarily indicate direct functional links. Overall, the key goal is to connect molecular connectivity findings to clear biological interpretations. If these challenges are addressed, it could bridge molecular and systems neuroscience, offering deeper insight into cognition and brain disorders.

What do you think are the most important challenges in current brain connectivity research, or which unsolved/underappreciated issues should the community address?

Brain connectivity research faces several key challenges that must be addressed to achieve true biological insight. A central issue is that connectivity is still mostly inferred from statistical relationships (e.g., correlations) rather than direct neural interactions, making interpretation uncertain—especially in fMRI and PET. Another major challenge is integrating different imaging modalities. MRI and PET capture distinct aspects of brain function (hemodynamic vs. biochemical), but their results often only partially overlap, highlighting the lack of a unified framework. Similarly, molecular and neurotransmitter connectivity can be difficult to interpret, as correlations in receptor binding do not necessarily reflect functional interactions. Neurophysiology (e.g., EEG/ERP) offers an important opportunity by providing fast temporal dynamics that can help link and validate findings across modalities, potentially enabling more mechanistic models of brain function. Methodological limitations also persist, including sensitivity to noise, variability across subjects and sites, and reliance on simplified models. There is a strong need for large, standardized, multimodal datasets. While AI can help analyze complex data, its success depends on high-quality data and biologically meaningful questions—otherwise, it risks producing results that are technically advanced but hard to interpret.

What is your favorite mentoring memory—either a story about a mentor’s impact on you or your impact on a mentee?

I don’t have a “favorite mentoring memory”. In the fields like brain connectivity and molecular neuroscience,  a powerful mentoring memory is when a mentor helps someone move from feeling overwhelmed by complexity to seeing a clear path forward. For example, a student working on brain connectivity at the molecular level might be struggling to integrate vast datasets—gene expression, synaptic markers, and network-level imaging. A good mentor doesn’t just give answers; they help the mentee reframe the problem, connect concepts across scales, and build confidence in handling ambiguity.

What scientist or scientific achievement do you most admire?

First, I want to underline that I admire joy, enthusiasm, and tenacity, as well as the ability to face doubts, support young people in their research, and share results without ever overpowering others.  I admire all the work carried out by Eric Kandel all over his scientific career and his group.


🌟 Molecular Connectivity Working Group – OHBM 2026 Symposium 🌟

Molecular connectivity: Best practices for data analysis
Bordeaux June 19th, 2026 – (In-person or virtually)

Registration: Register Here! Free of Charge!

Program & Speakers:

8:30 – 08:40 Welcome & Introduction by the organizers

08:40 – 09:10 (30 min) Molecular connectivity in the broader context of fMRI and other modalities Bratislav Misic, McGill University (Canada)

09:10 – 9:30 (20 min) Introduction to molecular connectivity and nomenclature in the context of the Delphi studySharna Jamadar, Monash University (Australia)

9:30 – 9:50 (20 min) Overview of commonly used methods for assessment of molecular connectivity with emphasis on technical aspects that require discussionMattia Veronese, University of Padua (Italy)

09:50 – 10:10 (20 min) Preprocessing: Data harmonization, PVC, normalizationMartin Norgaard, University of Copenhagen (Denmark)

10:10 – 10:30 Coffee break

10:30 – 10:50 (20 min) General prerequisites (population heterogeneity, statistical power), minimum number of subjects for inter- and intra-subject estimationArianna Sala, Université de Liège (Belgium)

10:50 – 11:10 (20 min) ROI-level estimation metrics: partial or Pearson correlation, Euclidean SimilarityTommaso Volpi, Yale University (USA)

11:10 – 11:30 (20 min) Voxel-level estimation: SSM-PCA vs. ICA (which method and when? selection of components), seed-based correlationMatthieu Doyen, Université de Lorraine (France)

11:30 – 11:50 (20 min) Best practices for merging molecular, functional information and clinical infoVince Calhoun, GSU, GATech, Emory University (USA)

11:50 – 12:10 (20 min) Statistical robustness (bootstrapping, corrections)Chris Habeck, Columbia University (USA)

12:10 – 13:00 Summary and plan for future steps


👨🏼‍🔬 We are looking for Volunteers – Join us!

The resources committee is currently looking for volunteers for the literature review of studies in molecular connectivity.
If you are interested in joining us, please reach out through: https://molecularconnectivity.com/how-to-join/


🧠 New Studies Spotlight

📝Task-evoked brain network architecture captured by the complementary integration of metabolic and functional connectivity

The goal of this study by Vallini and colleagues was to map the reconfiguration of the whole brain metabolic network in response to increasingly difficult tasks, and to investigate how both functional and metabolic reconfigurations contribute to behavioural performance during the task.

Read the full study in NeuroImage.

Key Findings:

  • A remodulation of the visual and dorsal attention networks was observed on the metabolic networks, with the posterior cingulate cortex having a prominent involvement in network reconfiguration.
  • The default brain network dynamically reorganises its functional connectivity in a task-specific manner, showing stronger associations with task-related regions, regardless of activity changes.
  • The integration of molecular and functional connectivity provided the best explanation for task performance, suggesting that neurometabolic and neurovascular network adaptations provide complementary insights into cognitive brain dynamics.

📝Individual-level metabolic connectivity captures cortical morphology and their coupling strengthens with age

In this study by Facca and colleagues, the integration of FDG PET and structural MRI data were used to investigate how cortical morphology constrains large-scale patterns of metabolic connectivity across the human lifespan.

Read the full study in bioRxiv.

Key Findings:

  • Brain regions sharing similar morphometric profiles also display coherent temporal patterns of glucose utilisation. This relationship likely stems from shared cellular determinants of energy demand, including neuronal and synaptic density, myelination, and glial composition.
  • The alignment found between structural and functional connectivity was moderate, suggesting a degree of structural-metabolic decoupling. This divergence likely reflects a degree of neuroenergetic flexibility, which may be grounded in the different timescales governing these modalities.
  • The coordination of glucose metabolism becomes increasingly governed by cortical morphology over the adult lifespan. The aging brain undergoes a shift towards a more “static” metabolic organisation: as the temporal variability of glucose consumption decreases, its spatial pattern becomes increasingly anchored to the physical neural substrate.

📝Utility of [18F]PI-2620 as universal biomarker for the amyloid/tau/neurodegeneration classification of Alzheimer disease: an exploratory study with dual-phase PET imaging

Franceschi and colleagues aimed at evaluating the efficacy of [18F]PI-2620 as a single biomarker for the A/T/N classification through the identification of spatial covariance patterns using SSM/PCA in early- and late-phase scans of amyloid-positive Alzheimer’s disease patients and amyloid-negative healthy controls.

Read the full study in Neuroradiology.

Key Findings:

  • The identified patterns of tau spatial covariance were in line with previous studies, showing an increased tau loading in limbic, temporoparietal, and lentiform regions, and a decrease in smaller clusters located in the frontoparietal cortices, caudate, and cerebellum. Meanwhile, the early-phase pattern showed decreased perfusion in caudate, thalamus, frontal, temporal, and parietal cortices, and an increase in cerebellar, lentiform, and motor cortical regions, also in line with current literature.
  • The identified tau pattern shared similarities with the amyloid pattern: high uptake in bilateral temporal lobe and strong correlations between subject scores.
  • Pattern expression scores of early- and late-phase [18F]PI-2620 together accurately predicted amyloid status when compared to pattern expression scores derived from amyloid PET scans.

📝 Novel insights into cognitive network alterations in temporal lobe epilepsy: a [18F]SynVesT-1 PET study

Qui and colleagues employed the Kullback-Leibler Divergence Similarity Estimation algorithm to construct individualised brain synaptic connectomes using [18F]SynVesT-1 PET imaging in temporal lobe epilepsy patients. Their main hypothesis was that distributed synaptic connectivity attenuation, rather than focal synaptic loss, mediates cognitive network dysfunction in epilepsy.

Read the full study in Epilepsy & Behaviour.

Key Findings:

  • A significant global reduction in regional connections and decreased connection strength was observed in epilepsy patients compared to controls. The caudate nucleus emerged as a critical hub, with its centrality showing positive associations with both spatial skills and full-scale intelligence quotient.
  • Synaptic vulnerability extended beyond mesiotemporal structures and involved the caudate nucleus, frontal lobe, and posterior cortex in temporal lobe epilepsy patients.
  • The region-specific synaptic connectivity reductions not only correlate with domain-specific cognitive impairment, but also may serve as quantifiable biomarkers for monitoring cognitive decline progression and cognitive treatment response.

Call for announcements, job opportunities, information and news!

The MCWG Outreach Council invites you to submit announcements or information about papers, conferences, presentations or other events or news related to brain and molecular connectivity as well as any positions available or job opportunities that you wish to publicize and share with the community!

Please submit any material for consideration by the final day of each month using this form – thank you!


Who we are

The MCWG is made up of four international and multidisciplinary councils dedicated to promoting molecular connectivity research via dissemination of methods, results, collaboration, and resource sharing (e.g. datasets, tools) within the scientific community. We encourage the neuroscientific community to take an integrative perspective in study of the brain connectome, where various methods including MRI-based techniques, electrophysiological tools, and molecular imaging advance our understanding of the brain. Please find fundamental questions outlined here: “Brain connectomics: time for a molecular imaging perspective?”

Our website can be found here. We also invite you to join the MCWG!


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