FOCUS (FunctiOnal neuroimaging and Complex neUral Systems)

Componenti

Brischetto Costa Tommaso (Coordinatore)
Cauda Franco (Coordinatore)
Sergio Duca (Componente)
Mario Ferraro (Componente)
Jordi Manuello (Dottorando)
Donato Liloia (Studente)

Contatti

Settore ERC

LS5_2 - Glial cells and neuronal-glial communication

LS5_7 - Sensory systems, sensation and perception, including pain

LS5_8 - Neural basis of behaviour

SH4_4 - Neuropsychology

Attività

L’obiettivo di ricerca del laboratorio è quello di indagare la connettività cerebrale e la patoconnettomica per mezzo di tecniche di risonanza magnetica funzionale e tecniche computazionali.

I principali campi di indagine sono:

Le Neuroimmagini funzionali sono un insieme di metodiche che si prefiggono di indagare il funzionamento in vivo del cervello umano ed animale.
Mediante le neuroimmagini funzionali è possibile indagare il rapporto tra funzionamento cerebrale e comportamento, studiare le basi fisiologiche delle funzioni psicologiche, nonché processi mentali come percezione, attenzione, memoria, apprendimento ed emozioni. Tali metodiche sono inoltre efficaci nello studio della patofisiologia e l'evoluzione delle patologie cerebrali con possibili ed interessanti risvolti di trattamento.
Le metodiche principalmente usate dal nostro gruppo sono la Risonanza Magnetica Funzionale (fMRI), la Tomografia ad Emissione di Positroni (PET) e l'elettroencefalografia (EEG).

Le tecniche di connettività neurale si prefiggono di studiare come le varie aree del cervello si connettono ed interagiscono tra loro. E' così possibile definire una mappa anatomica o funzionale ed eventualmente comprendere elementi di causalità tra le attività delle varie aree cerebrali indagate. La scala di tali mappe può variare dal livello neuronale fino al livello di macro-aree cerebrali, tipico delle tecniche di neuroimmagine funzionale come l'fMRI o l'EEG.
La connettività neurale può essere usata sia come metodo di indagine per il funzionamento di base del cervello, l'associazione tra funzioni cerebrali e comportamento osservato, sia per comprendere e valutare l'insorgenza e l'evoluzione delle patologie cerebrali.

La patoconnettomica si occupa di mettere in relazione le alterazioni della connettività con la patologia cerebrale e di scoprire le modalità di propagazione del danno cerebrale da un’area ad un'altra.

I sistemi neurali complessi, sono un settore scientifico che si prefigge di modellizzare, descrivere ed integrare, mediante l'utilizzo di opportune tecniche matematiche, i risultati ottenuti attraverso metodiche di neuroimaging, di genetica e di anatomia.
Le tecniche di studio dei sistemi complessi neurali possono permettere una migliore comprensione del funzionamento e della patofisiologia cerebrale, della vulnerabilità al danno delle reti neurali e descrivere il funzionamento del cervello in termini di networks.

Il rsfMRI è un metodo di imaging cerebrale funzionale che può essere utilizzato per valutare le interazioni regionali che si verificano quando un soggetto non sta eseguendo un compito esplicito. Questa attività cerebrale a riposo può essere osservata attraverso i cambiamenti nel flusso sanguigno che possono essere misurati in modo particolarmente efficiente utilizzando la risonanza magnetica funzionale. Poiché l'attività cerebrale è presente anche in assenza di un compito richiesto dall'esterno, ogni regione del cervello avrà fluttuazioni spontanee nel segnale fMRI. L'approccio rsfMRI è utile per esplorare organizzazione funzionale del cervello e di esaminare le sue alterazioni.

La statistica bayesiana è una statistica alternativa alla statistica ortodossa che si basa esclusivamente sulla teoria della probabilità. Queste tecniche permetto di ottenere delle informazioni sul cervello migliori o non visibili con le tecniche statistiche tradizionali ed inoltre permette di costruire modelli di funzionamento del cervello utili alla modellazione delle reti neurali.

Il dolore è un'esperienza complessa, esso comprende aspetti sia emozionali che sensoriali. Quando il dolore persiste al di là dell'esperienza acuta o perdura dopo la fase di guarigione, esso perde la sua funzione evolutiva e cronicizza, diventando quindi disfunzionale. Il dolore cronico costituisce un grave peso sociale, che interferisce con la qualità di vita delle persone.
Il gruppo si occupa dello studio del dolore acuto e cronico, utilizzando in combinazione diverse strumentazioni (come la risonanza magnetica funzionale, l'elettroencefalografia e i potenziali evento correlati, la stimolazione magnetica transcranica, la conduttanza cutanea, la pupillometria) e approcci sperimentali (studi lesionali, di psicofisica e di neuroimmagine).
L'obiettivo ultimo è quello di comprendere meglio i meccanismi di risposta del cervello agli stimoli nocivi e dolorosi, in condizioni sane e patologiche, e le possibilità che esistono di modulare l'intensità di tali risposte.

Comprensione della relazione tra connettività normotipica e sviluppo spazio-temporale dei pattern di alterazione patologica.

Sviluppo di metodi computazionali avanzati.

Andrew Bagshaw; School of Psychology, University of Birmingham, UK.
Andrea Eugenio Cavanna; Michael Trimble Neuropsychiatry Research Group, University of Birmingham and BSMHFT, Birmingham. Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology and University College London, UK.
Peter T. Fox; Director of Research Imaging Institute Malcolm Jones Professor and Vice Chair for Research and Research Education, Department of Radiology Professor, Departments of Neurology, Psychiatry, and Physiology University of Texas Health Science Center at San Antonio, USA.
Patrick Péruch; Centre de Recherche en Neurosciences Cognitives CNRS, Cedex, FR.
Carlo Adolfo Porro; Dipartimento Scienze Biomediche, Università di Modena, IT.
Alessandro Vercelli; Neuroscience Institute of the Cavalieri Ottolenghi Foundation, Orbassano , IT
Lucina Q. Uddin; Psychiatry and Behavioral Science, Stanford School of Medicine.
A. Vania Apkarian; Professor of Physiology, Surgery, Anesthesia, Cognitive Brain Mapping Group & Neuroscience Institute. Northwestern University Medical School Chicago, Illinois
Rainer Goebel; Department of Cognitive Neuroscience Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD Maastricht, The Netherlands
Roberto Keller; Psichiatra, Centro Autismo adulti, ASL TO2, Torino.
Irvin Rock; Berkley University, California.
Mayra Manzano and Rosario Torres; La Habana University, Neuroscience Center Cuba.
Ryuta Kawashima; Tohoku University, Japan.
Javeria Hashmi; Dalhousie Medical School, Canada.
Bratislav Misic; McGill University, Canada.
PnInsula; CIMCYC, Università di Granada, Spagna.

Il gruppo afferisce al CCS-fMRI e tramite un accordo di collaborazione con l'Ospedale Koelliker ha accesso ad una serie di attrezzature e studi presso l'ospedale Koelliker:

1 Scanner per risonanza magnetica Philips 3.0 Tesla attrezzato con sequenze per analisi neurofunzionale e tensore di diffusione.

1 Stimolatore Nordic Neurolab per stimolazione visiva, uditiva e tattile attrezzato per rilevazioni di eye tracking compatibile fMRI.

1. ECG e Capnografo fMRI compatibile.

1 set di stimolatori "Pinprick"

5 Workstation per analisi fMRI

Software di analisi dati (BrainVoyager, Matlab, SPSS, Eprime, Photoshop, Wavelab, SPM, Sigview, Labwiew.

Dischi di backup, stampanti ed attrezzatura informatica varia.

1 Studio per analisi dati e riunioni

1 Sala riunioni

Il Prof. Tommaso Brischetto Costa ed il Prof. Franco Cauda sono responsabili anche del Laboratorio di neuroimaging sito in Via Verdi 10 al Dipartimento di Psicologia che viene utilizzato dal gruppo di ricerca. Il laboratorio consiste di Due Mac Pro ed una Workstation Linux con le seguenti caratteristiche:

DELL PowerEdge T620

2 PROCESSORI Intel® Xeon® processor E5-2600
128Gb RAM
HD SAS 300Gb
HD SSD 400GB SAS Value SLC 6Gb/s 2,5"
HD SATA 4TB 7.2K RPM SATA 3GBPS 3.5”
GPU NVIDIA TESLA K20

Focus Group is a Research laboratory of the Department of Psychology of the University of Turin

The research objective of the laboratory is to investigate brain connectivity and pathoconnectomics by means of functional magnetic resonance techniques and computational techniques.

The main fields of investigation are:

neuroimaging is a set of methods that aim to investigate the in vivo functioning of the human and animal brain.
By means of functional neuroimaging it is possible to investigate the relationship between brain functioning and behavior, to study the physiological basis of psychological functions, as well as mental processes such as perception , attention , memory , learning and emotions . These methods are also effective in the study of the pathophysiology and the evolution of brain pathologies with possible and interesting treatment implications.
The methods mainly used by our group are Functional Magnetic Resonance Imaging (fMRI), Positron Emission Tomography (PET) and electroencephalography (EEG).

connectivity Neural connectivity techniques aim to study how the various areas of the brain connect and interact with each other. It is thus possible to define an anatomical or functional map and possibly include elements of causality between the activities of the various brain areas investigated. The scale of these maps can vary from the neuronal level to the level of cerebral macro-areas, typical of functional neuroimaging techniques such as fMRI or EEG.
Neural connectivity can be used both as an investigation method for the basic functioning of the brain, the association between brain functions and observed behavior, and to understand and evaluate the onset and evolution of brain pathologies.

Pathoconnectomics deals with relating the alterations of the connectivity with the cerebral pathology and with discovering the modalities of propagation of the cerebral damage from one area to another.

Complex neural systems are a scientific sector that aims to model, describe and integrate, through the use of appropriate mathematical techniques, the results obtained through neuroimaging, genetics and anatomy methods.
The techniques of studying complex neural systems can allow a better understanding of the functioning and pathophysiology of the brain, of the vulnerability to damage of neural networks and to describe the functioning of the brain in terms of networks.

rsfMRI is a functional brain imaging method that can be used to assess regional interactions that occur when a subject is not performing an explicit task. This resting brain activity can be observed through changes in blood flow which can be measured particularly efficiently using functional magnetic resonance imaging . Since brain activity is present even in the absence of an externally requested task, each region of the brain will have spontaneous fluctuations in the fMRI signal. The rsfMRI approach is useful for exploring functional organization of the brain and examining its alterations.

Bayesian statistics is an alternative statistic to orthodox statistics which is based solely on probability theory. These techniques make it possible to obtain information on the brain that is better or not visible with traditional statistical techniques and also allows the construction of brain functioning models useful for modeling neural networks.

Pain is a complex experience, it includes both emotional and sensory aspects. When pain persists beyond the acute experience or persists after the healing phase, it loses its evolutionary function and becomes chronic, thus becoming dysfunctional. Chronic pain is a serious social burden, which interferes with people's quality of life.
The group deals with the study of acute and chronic pain, using a combination of different instruments (such as functional magnetic resonance, electroencephalography and related event potentials, transcranial magnetic stimulation, skin conductance, pupillometry) and experimental approaches (lesion studies , psychophysics and neuroimaging).
The ultimate goal is to better understand the response mechanisms of the brain to harmful and painful stimuli, in healthy and pathological conditions, and the possibilities that exist to modulate the intensity of these responses .

neuroimaging ; analysis of connectivity in the healthy brain and affected by neuropsychiatric pathology; Bayesian statistics.

Understanding of the relationship between normotypic connectivity and spatio-temporal development of pathological alteration patterns.

Development of advanced computational methods.

Andrew Bagshaw; School of Psychology, University of Birmingham, UK.
Andrea Eugenio Cavanna; Michael Trimble Neuropsychiatry Research Group, University of Birmingham and BSMHFT, Birmingham. Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology and University College London, UK.
Peter T. Fox; Director of Research Imaging Institute Malcolm Jones Professor and Vice Chair for Research and Research Education, Department of Radiology Professor, Departments of Neurology, Psychiatry, and Physiology University of Texas Health Science Center at San Antonio, USA.
Patrick Péruch; Centre de Recherche en Neurosciences Cognitives CNRS, Cedex, FR.
Carlo Adolfo Porro; Dipartimento Scienze Biomediche, Università di Modena, IT.
Alessandro Vercelli; Neuroscience Institute of the Cavalieri Ottolenghi Foundation, Orbassano , IT
Lucina Q. Uddin; Psychiatry and Behavioral Science, Stanford School of Medicine.
A. Vania Apkarian; Professor of Physiology, Surgery, Anesthesia, Cognitive Brain Mapping Group & Neuroscience Institute. Northwestern University Medical School Chicago, Illinois
Rainer Goebel; Department of Cognitive Neuroscience Faculty of Psychology and Neuroscience, Maastricht University, 6200 MD Maastricht, The Netherlands
Roberto Keller; Psichiatra, Centro Autismo adulti, ASL TO2, Torino.
Irvin Rock; Berkley University, California.
Mayra Manzano and Rosario Torres; La Habana University, Neuroscience Center Cuba.
Ryuta Kawashima; Tohoku University, Japan.
Javeria Hashmi ; Dalhousie Medical School, Canada.
Bratislav Misic ; McGill University, Canada.
PnInsula ; CIMCYC, University of Granada, Spain.

The group belongs to the CCS-fMRI and through a collaboration agreement with the Koelliker Hospital has access to a series of equipment and studies at the Koelliker hospital:

1 Philips 3.0 Tesla magnetic resonance scanner equipped with sequences for neurofunctional analysis and diffusion tensor.
Nordic Stimulator Neurolab for visual, auditory and tactile stimulation equipped for fMRI compatible eye tracking detections.
ECG and Capnograph fMRI compatible.
1 set of " Pinprick " stimulators
5 Workstation for fMRI analysis
Data analysis software ( BrainVoyager , Matlab, SPSS, Eprime , Photoshop, Wavelab , SPM, Sigview , Labwiew .
Backup disks, printers and various computer equipment.
1 Studio for data analysis and meetings
1 meeting room

Prof. Tommaso Brischetto Costa and Prof. Franco Cauda are also responsible for the neuroimaging laboratory located in Via Verdi 10 in the Department of Psychology which is used by the research group. The lab consists of Two Mac Pros and one Linux Workstation with the following features:

DELL PowerEdge T620

2 PROCESSORS Intel® Xeon® processor E5-2600
128Gb RAMHD SAS 300GbHD SSD 400GB SAS Value SLC 6Gb/s 2.5"HD SATA 4TB 7.2K RPM SATA 3GBPS 3.5”GPU NVIDIA TESLA K20

Prodotti della ricerca

1: Cauda F., Geda E., Sacco K., D'Agata F., Duca S., Geminiani G., Keller R. (2011) Grey matter abnormality in autism spectrum disorder: an activation likelihood estimation meta-analysis study. J Neurol Neurosurg Psychiatry,82(12), 1304-13. doi: 10.1136/jnnp.2010.239111.

2: Baudino B., D'Agata F., Caroppo P., Castellano G., Cauda S., Manfredi M., Geda E., Castelli L., Mortara P., Orsi L., Cauda F., Sacco K., Ardito R.B., Pinessi L., Geminiani G., Torta R., Bisi G. (2012) The chemotherapy long-term effect on cognitive functions and brain metabolism in lymphoma patients. Q J Nucl Med Mol Imaging., 56(6):559-68.

3: Isoardo G., Stella M., Cocito D., Risso D., Migliaretti G., Cauda F., Palmitessa A., Faccani G., Ciaramitaro P. (2012) Neuropathic pain in post-burn hypertrophic scars: a psychophysical and neurophysiological study. Muscle Nerve., 45(6):883-90. doi: 10.1002/mus.23259.

4: Caglio M., Latini-Corazzini L., D'Agata F., Cauda F., Sacco K., Monteverdi S., Zettin M., Duca S., Geminiani G. (2012) Virtual navigation for memory rehabilitation in a traumatic brain injured patient..
Neurocase, 18(2):123-31. doi:10.1080/13554794.2011.568499.

5: Sacco K., Cauda F., D'Agata F., Duca S., Zettin M., Virgilio R., Nascimbeni A., Belforte G., Eula G., Gastaldi L., Appendino S., Geminiani G. (2011) A combined robotic and cognitive training for locomotor rehabilitation: evidences of cerebral functional reorganization in two chronic traumatic brain injured patients.
Front Hum Neurosci. ;5:146. doi: 10.3389/fnhum.2011.00146.

6: Amanzio M., Benedetti F., Porro C.A., Palermo S., Cauda F. (2013) Activation likelihood estimation meta-analysis of brain correlates of placebo analgesia in human experimental pain.
Hum Brain Mapp.,34(3), 738-52. doi: 10.1002/hbm.21471.

7: D'Agata F., Costa T., Caroppo P., Baudino B., Cauda F., Manfredi M., Geminiani G., Mortara P., Pinessi L., Castellano G., Bisi G. (2013) Multivariate analysis of brain metabolism reveals chemotherapy effects on prefrontal cerebellar system when related to dorsal attention network. EJNMMI Res. 2013 Apr 4;3(1):22. doi:10.1186/2191-219X-3-22..

8: D'Agata F., Caroppo P., Boghi A., Coriasco M., Caglio M., Baudino B., Sacco K., Cauda F., Geda E., Bergui M., Geminiani G., Bradac G.B., Orsi L., Mortara P. (2011) Linking coordinative and executive dysfunctions to atrophy in spinocerebellar ataxia 2 patients.
Brain Struct Funct., 216(3), 275-88. doi: 10.1007/s00429-011-0310-4.

9: Torta D.M., Cauda F.. (2011) Different functions in the cingulate cortex, a meta-analytic connectivity modeling study.
Neuroimage., 56(4), 2157-72. doi: 10.1016/j.neuroimage.2011.03.066..

10: Amanzio M., Torta D.M., Sacco K., Cauda F., D'Agata F., Duca S., Leotta D., Palermo S., Geminiani G.C.(2011) Unawareness of deficits in Alzheimer's disease: role of the cingulate cortex.
Brain., 134(Pt 4):1061-76. doi: 10.1093/brain/awr020.

11: Spena G., Nava A., Cassini F., Pepoli A., Bruno M., D'Agata F., Cauda F., Sacco K., Duca S., Barletta L., Versari P.(2010) Preoperative and intraoperative brain mapping for the resection of eloquent-area tumors. A prospective analysis of methodology, correlation, and usefulness based on clinical outcomes.
Acta Neurochir .152(11), 1835-46. doi: 10.1007/s00701-010-0764-9.

12: Latini-Corazzini L., Nesa M.P., Ceccaldi M., Guedj E., Thinus-Blanc C, Cauda F., Dagata F., Péruch P. (20109 Route and survey processing of topographical memory during navigation.
Psychol Res. ,74(6):545-59. doi: 10.1007/s00426-010-0276-5.

13: Caglio M., Latini-Corazzini L., D'Agata F., Cauda F., Sacco K., Monteverdi S., Zettin M., Duca S., Geminiani G. (2009) Video game play changes spatial and verbal memory rehabilitation of a single case with traumatic brain injury.
Cogn Process., 10 Suppl 2:S195-7. doi: 10.1007/s10339-009-0295-6.

14: Tamietto M., Cauda F., Corazzini L.L., Savazzi S., Marzi C.A., Goebel R., Weiskrantz L., de Gelder B. (2010) Collicular vision guides nonconscious behavior.
J Cogn Neurosci. , 22(5):888-902. doi: 10.1162/jocn.2009.21225.

15: Pia L., Corazzini L.L., Folegatti A., Gindri P., Cauda F.. Mental number line disruption in a right-neglect patient after a left-hemisphere stroke.(2009)
Brain Cogn.,69(1):81-8. doi: 10.1016/j.bandc.2008.05.007

16: Sacco K., Cauda F., Cerliani L., Mate D., Duca S., Geminiani G.C.(2006) Motor imagery of walking following training in locomotor attention. The effect of "the tango lesson".
Neuroimage,,32(3):1441-9.

17: Torta D.M., Castelli L., Latini-Corazzini L., Banche A., Lopiano L., Geminiani G.(2010) Dissociation between time reproduction of actions and of intervals in patients with Parkinson's disease.
J Neurol. ,257(8):1356-61. doi:10.1007/s00415-010-5532-5..

18: Cistaro A., Quartuccio N., Vesco S., Pagani M., Fania P., Donati L., Nobili F.M., Duca S., Carrara G., Valentini M.C.(2012). Positron emission tomography.
Ophthalmology. ,119(7):1496-7.e1. doi: 10.1016/j.ophtha.2012.02.047.

19: Tettamanti M., Rognoni E., Cafiero R., Costa T., Galati D., Perani D. (2012). Distinct pathways of neural coupling for different basic emotions.. Neuroimage, 59, 1804-1817, doi:10.1016/j.neuroimage.2011.08.018

20: Brischetto Costa T., Crini M.- (2011). Basic emotions: Differences in time sequence and functional imaging with low resolution brain electrical tomography (LORETA).

21: Belforte G. Eula G. Appendino S. Cauda F.. Sacco K.. (2010)
MR compatible device for active and passive foot movements
International Journal of Mechanics and Control, 11, 1.

22: Manuello J., Nani A., Cauda F., “Attention, Salience, and Self-Awareness: The Role of Insula in Meditation”. In book: Island of Reil (Insula) in the Human Brain. Springer Nature, editor: Mehmet Turgut et al. (2018)

23: Manuello J., Nani A., Cauda F., “Consciousness and Meditation: Two Partially Overlapping Networks”. In book: Consciousness: Social Perspectives, Psychological Approaches And Current Research. NOVA publishers, editor: Lloyd Alvarado. (2016)

24: Manuello J., Vercelli U., Nani A., Costa T., Cauda F. (2016) "Mindfulness meditation and consciousness: An integrative neuroscientific perspective". Consciousness and Cognition, 40, 67-78

25: Nani A., Manuello J., Mancuso L., Liloia D., Costa T., Cauda F. (2019) “The neural correlates of consciousness and attention: Two sister processes of the brain”. Frontiers in Neuroscience https://doi.org/10.3389/fnins.2019.01169

26: Nani A., Manuello J., Liloia D., Duca S., Costa T., Cauda F. (2019) “The Neural Correlates of Time: A Meta-analysis of Neuroimaging Studies”. Journal of Cognitive Neuroscience https://doi.org/10.1162/jocn_a_01459

27: Ficco L., Mancuso L., Manuello J., Teneggi A., Liloia D., Duca S., Costa T., Kovacs G., Cauda F. (2021) “Disentangling predictive processing in the brain: a meta-analytic study in favour of a predictive network”. Scientific Reports https://doi.org/10.1038/s41598-021-95603-5

28: Mancuso L., Cavuoti-Cabanillas S., Liloia D., Manuello J., Buzi G., Cauda F., Costa T. (2022) “Tasks activating the Default Mode Network map multiple functional systems”. Brain Structure and Function https://doi.org/10.1007/s00429-022-02467-0

1: Cauda F., Torta D.M., Sacco K., D'Agata F., Geda E., Duca S., Geminiani G., Vercelli A.(2013) Functional anatomy of cortical areas characterized by Von Economo neurons.Brain Struct Funct.,218(1), 1-20.

2 Torta D.M., Cauda F. Different functions in the cingulate cortex, a meta-analytic connectivity modeling study.(2011)
Neuroimage, 56(4), 2157-72.doi: 10.1016/j.neuroimage.2011.03.066

3: Cauda F., Cavanna A.E., D'Agata F., Sacco K., Duca S., Geminiani G.C.(2011) Functional connectivity and coactivation of the nucleus accumbens: a combined functional connectivity and structure-based meta-analysis.
J Cogn Neurosci., 23(10), 2864-77. doi: 10.1162/jocn.2011.21624

4 Cauda F., Giminiani G, D'Agata D., Duca S.,Sacco K..(2011) Discovering the somatotopic organization of the motor areas of the medial wall using low-frequency BOLD fluctuations.
Hum Brain Mapp., 32(10), 1566-79. doi:10.1002/hbm.21132.

5: Sacco K., Cauda F., D'Agata F., Mate D, Duca S., Geminiani G..(2009) Reorganization and enhanced functional connectivity of motor areas in repetitive ankle movements after training in locomotor attention.
Brain Res. ,1297:124-34. doi:10.1016/j.brainres.2009.08.049

6: Mancuso L., Costa T., Nani A., Manuello J., Liloia D., Gelmini G., Panero M., Duca S., Cauda F. (2019) The homotopic connectivity of the functional brain: a meta-analytic approach. Scientific Reports https://doi.org/10.1038/s41598-019-40188-3

7: Bonelli C., Mancuso L., Manuello J., Liloia D., Costa T., Cauda F. (2022) Sex differences in Brain Homotopic Co-activations: a meta-analytic study. Brain Structure and Function https://doi.org/10.1007/s00429-022-02572-0

8: Manuello J., Verdejo-Romàn J., Torres Espìnola F., Escudero-Marín M., Catena A., Cauda F., Campoy C. (2022) Influence of gestational diabetes and pre-gestational maternal BMI on the brain of six years old offspring. Pediatric Neurology doi.org/10.1016/j.pediatrneurol.2022.05.005

9: Manuello J., Costa T., Cauda F., Liloia D. (2022) Six actions to improve detection of critical features for neuroimaging coordinate-based meta-analysis preparation. Neuroscience & Biobehavioral Reviews https://doi.org/10.1016/j.neubiorev.2022.104659

1: Premi E, Cauda F, Gasparotti R, Diano M, Archetti S, Padovani A, Borroni B. Multimodal FMRI resting-state functional connectivity in granulin mutations: the case of fronto-parietal dementia. PLoS One. 2014 Sep 4;9(9):e106500. doi: 10.1371/journal.pone.0106500. eCollection 2014. PubMed PMID: 25188321; PubMed Central PMCID: PMC4154688.

2: Cauda F, Palermo S, Costa T, Torta R, Duca S, Vercelli U, Geminiani G, Torta DM. Gray matter alterations in chronic pain: A network-oriented meta-analytic approach. Neuroimage Clin. 2014 Apr 16;4:676-86. doi: 10.1016/j.nicl.2014.04.007. eCollection 2014. PubMed PMID: 24936419; PubMed Central PMCID: PMC4053643.

3: Cauda F, Costa T, Palermo S, D'Agata F, Diano M, Bianco F, Duca S, Keller R. Concordance of white matter and gray matter abnormalities in autism spectrum disorders: a voxel-based meta-analysis study. Hum Brain Mapp. 2014 May;35(5):2073-98. doi: 10.1002/hbm.22313. Epub 2013 Jul 26. PubMed PMID:23894001.

4: Cauda F, Geda E, Sacco K, D'Agata F, Duca S, Geminiani G, Keller R. Grey matter abnormality in autism spectrum disorder: an activation likelihood estimation meta-analysis study. J Neurol Neurosurg Psychiatry. 2011 Dec;82(12):1304-13. doi: 10.1136/jnnp.2010.239111. Epub 2011 Jun 21. PubMed PMID: 21693631.

5: D'Agata F, Caroppo P, Boghi A, Coriasco M, Caglio M, Baudino B, Sacco K, Cauda F, Geda E, Bergui M, Geminiani G, Bradac GB, Orsi L, Mortara P. Linking coordinative and executive dysfunctions to atrophy in spinocerebellar ataxia 2 patients. Brain Struct Funct. 2011 Sep;216(3):275-88. doi:10.1007/s00429-011-0310-4. Epub 2011 Apr 2. PubMed PMID: 21461742.

6: Amanzio M, Torta DM, Sacco K, Cauda F, D'Agata F, Duca S, Leotta D, Palermo S, Geminiani GC. Unawareness of deficits in Alzheimer's disease: role of the cingulate cortex. Brain. 2011 Apr;134(Pt 4):1061-76. doi: 10.1093/brain/awr020. Epub 2011 Mar 7. PubMed PMID: 21385751.

7: Cauda F, D'Agata F, Sacco K, Duca S, Cocito D, Paolasso I, Isoardo G, Geminiani G. Altered resting state attentional networks in diabetic neuropathic pain. J Neurol Neurosurg Psychiatry. 2010 Jul;81(7):806-11. doi: 10.1136/jnnp.2009.188631. Epub 2009 Dec 1. PubMed PMID: 19955113.

8: Cauda F, Sacco K, D'Agata F, Duca S, Cocito D, Geminiani G, Migliorati F, Isoardo G.
Low-frequency BOLD fluctuations demonstrate altered thalamocortical connectivity in diabetic neuropathic pain. BMC Neurosci. 2009 Nov 26;10:138. doi: 10.1186/1471-2202-10-138. PubMed PMID: 19941658; PubMed Central PMCID: PMC2789078.

9: Cauda F, Micon BM, Sacco K, Duca S, D'Agata F, Geminiani G, Canavero S. Disrupted intrinsic functional connectivity in the vegetative state. J Neurol Neurosurg Psychiatry. 2009 Apr;80(4):429-31. doi: 10.1136/jnnp.2007.142349. PubMed PMID: 19289479.

10: Cauda F, Sacco K, Duca S, Cocito D, D'Agata F, Geminiani GC, Canavero S. Altered resting state in diabetic neuropathic pain. PLoS One. 2009;4(2):e4542.doi: 10.1371/journal.pone.0004542. Epub 2009 Feb 20. PubMed PMID: 19229326; PubMed Central PMCID: PMC2638013.

11: Manuello J., Nani A., Premi E., Borroni B., Costa T., Tatu K., Liloia D., Duca S., Cauda F. (2018) "The Pathoconnectivity Profile of Alzheimer's Disease: A Morphometric Coalteration Network Analysis". Front. Neurol. 8:739. doi: 10.3389/fneur.2017.00739

12: Liloia D., Cauda F., Nani A., Manuello J., Duca S., Fox P.T., Costa T. (2018) Low entropy maps as patterns of the pathological alteration specificity of brain regions: A meta-analysis dataset. Data in Brief https://doi.org/10.1016/j.dib.2018.10.142

13: Cauda F., Nani A., Manuello J., Premi E., Palermo S., Tatu K., Duca S., Fox P.T., Costa T. (2018) Brain structural alterations are distributed following functional, anatomic and genetic connectivity. Brain. https://doi.org/10.1093/brain/awy252

14: Cauda F., Nani A., Costa T., Palermo S., Tatu K., Manuello J., Duca S., Fox P.T., Keller R. (2018) "The morphometric co-atrophy networking of schizophrenia, autistic and obsessive spectrum disorders". Hum Brain Mapp. 00: 131. https://doi.org/10.1002/hbm.23952

15: Cauda F., Nani A., Manuello J., Liloia D., Tatu K., Vercelli U., Duca S., Fox P.T., Costa T. (2019) The alteration landscape of the cerebral cortex". NeuroImage. 184: 359-371 doi:10.1016/j.neuroimage.2018.09.036

16: Cauda F., Mancuso L., Nani A., Ficco L., Premi E., Manuello J., Liloia D., Gelmini G., Duca S., Costa T. (2020) Hubs of long‐distance co‐alteration characterize brain pathology. Human Brain Mapping https://doi.org/10.1002/hbm.25093

17: Mancuso L., Fornito A., Costa T., Ficco L., Liloia D., Manuello J., Duca S., Cauda F. (2020) A meta-analytic approach to mapping co-occurrent grey matter volume increases and decreases in psychiatric disorders NeuroImage doi.org/10.1016/j.neuroimage.2020.117220

18: Liloia D., Mancuso L., Uddin L.Q., Costa T., Nani A., Keller R., Manuello J., Duca S., Cauda F. (2021) Gray Matter Abnormalities Follow Non-Random Patterns of Co-Alteration in Autism: Meta-Connectomic Evidence. NeuroImage:Clinical https://doi.org/10.1016/j.nicl.2021.102583

19: Liloia D., Brasso C., Cauda F., Mancuso L., Manuello J., Costa T., Duca S., Rocca P. (2021) Updating and Characterizing Neuroanatomical Markers in High-Risk Subjects, Recently Diagnosed and Chronic Patients with Schizophrenia: A Revised Coordinate-Based Meta-Analysis. Neuroscience & Biobehavioral Reviews https://doi.org/10.1016/j.neubiorev.2021.01.010

20:Nani A., Manuello J., Mancuso L., Liloia D., Costa T., Vercelli A., Duca S., Cauda F. (2021) The pathoconnectivity network analysis of the insular cortex: A morphometric fingerprinting NeuroImage doi.org/10.1016/j.neuroimage.2020.117481

21: Cauda F., Nani A., Liloia D., Gelmini G., Mancuso L., Manuello J., Panero M., Duca S., Zang Y., Costa T. (2021) Interhemispheric co‑alteration of brain homotopic regions. Brain Structure and Function https://doi.org/10.1007/s00429-021-02318-4

22: Liloia D., Cauda F., Uddin L.Q., Manuello J., Mancuso L., Keller R., Nani A., Costa T. (2022) Revealing the Selectivity of Neuroanatomical Alteration in Autism Spectrum Disorder via Reverse Inference. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging https://doi.org/10.1016/j.bpsc.2022.01.007

23: Manuello J., Mancuso L., Liloia D., Cauda F., Duca T., Costa T. (2022) A co-alteration parceling of the cingulate cortex. Brain Structure and Function https://doi.org/10.1007/s00429-022-02473-2

24: Liloia D., Crocetta A., Cauda F., Duca S., Costa T., Manuello J. (2022) Seeking Overlapping Neuroanatomical Alterations between Dyslexia and Attention-Deficit/Hyperactivity Disorder: A Meta-Analytic Replication Study. Brain Sciences https://doi.org/10.3390/brainsci12101367

25: Camasio A., Panzeri E., Mancuso L., Costa T., Manuello J., Ferraro M., Duca S., Cauda F., Liloia D. (in press) Linking neuroanatomical abnormalities in autism spectrum disorder with gene expression of candidate ASD genes: a meta-analytic and network-oriented approach PLOS One

1 Cauda F., Vercelli A. How many clusters in the insular cortex? (2012) Cereb Cortex.

2: Cauda F., Costa T., Torta D.M., Sacco K., D'Agata F., Duca S., Geminiani G., Fox P.T., Vercelli A. (2012). Meta-analytic clustering of the insular cortex: characterizing the meta-analytic connectivity of the insula when involved in active tasks.
Neuroimage, 62(1), 343-55. doi: 10.1016/j.neuroimage.2012.04.01

3: Costa T., Boccignone G., Ferraro M.(2012) Gaussian mixture model of heart rate variability.
PLoS One., 7(5):e37731. doi: 10.1371/journal.pone.0037731

4: Costa T., Ferraro M.(1993) A neural model of discrete and continuous modes of visual discrimination. Spat Vis. 1993;7(3):243-55

5: Costa T., Galati D., Rognoni E. (2009). The Hurst exponent of cardiac response to positive and negative emotional film stimuli using wavelet. Autonomic Nuroscience: Basic & Clinical, 151,. 183-185.

6: Costa T., Rognoni E., Crini M., Galati D. (2008). Phase Synchronization at different frequency bands induced by the emotional film stimuli of happiness, sadness and fear. In Yuanzhu Ling( Eds). Research Topics on Brain Mapping. (pp 87-111), NEW YORK, :Nova Science

7: Costa T., Rognoni E., Galati D. (2006). EEG phase synchronization during emotional response to positive and negative film stimuli. Neuroscience Letters, 406,. 159-164.

1:Cauda F., D'Agata F., Sacco K., Duca S., Geminiani G., Vercelli A.(2011) Functional connectivity of the insula in the resting brain.
Neuroimage., 55(1), 8-23. doi: 10.1016/j.neuroimage.2010.11.049.

2: Cauda F., Geminiani G., D'Agata F., Sacco K., Duca S., Bagshaw A.P., Cavanna A.E.(2010)
Functional connectivity of the posteromedial cortex. PLoS One., 5(9). doi:pii: e13107. 10.1371/journal.pone.0013107.

3: Cauda F., Geminiani G., D'Agata F., Duca S., Sacco K..(2011)
Discovering the somatotopic organization of the motor areas of the medial wall using low-frequency BOLD fluctuations.
Hum Brain Mapp., 32(10), 1566-79. doi: 10.1002/hbm.21132.

4: A Cauda F., Torta D.M., Sacco K., D'Agata F., Geda E., Duca S., Geminiani G., Vercelli A.(2013) Funcional anatomy of cortical areas characterized by Von Economo neurons.
Brain Struct Funct.,218(1), 1-20.

1 Cauda F., Costa T., Diano M, Sacco K., Duca S., Geminiani G., Torta D.M.. (2013) Massive Modulation of brain areas after mechanical pain stimulation: a time-resolved fMRI study
Cerebral Cortex. May (Accepted)

2:Torta D.M., Diano M, Costa T., Gallace A., Geminiani G., Cauda F. (Accepted) Crossing the line of pain: investigating the neural basis of crossed-hands analgesia Journal of Pain

3: Sambo C.F., Torta D.M., Gallace A., Liang M., Moseley G.L., Iannetti G.D. (2013). The temporal order judgement of tactile and nociceptive stimuli is impaired by crossing the hands over the body midline.
Pain., 154(2):242-7. doi: 10.1016/j.pain.2012.10.010

4: Legrain V., Mancini F., Sambo C.F., Torta D.M., Ronga I., Valentini E.(2012) Cognitive aspects of nociception and pain: bridging neurophysiology with cognitive psychology.
Neurophysiol Clin., 42(5):325-36. doi:10.1016/j.neucli.2012.06.003.

5: Torta D.M., Liang M., Valentini E., Mouraux A., Iannetti G.D.(2012) Dishabituation of laser-evoked EEG responses: dissecting the effect of certain and uncertain changes in stimulus spatial location. Exp Brain Res , 218(3):361-72. doi:10.1007/s00221-012-3019-6.

6: Gallace A., Torta D.M., Moseley G.L., Iannetti G.D.(2011) The analgesic effect of crossing the arms.
Pain., 152(6):1418-23. doi: 10.1016/j.pain.2011.02.029

7: Valentini E., Torta D.M., Mouraux A., Iannetti G.D. Dishabituation of laser-evoked EEG responses: dissecting the effect of certain and uncertain changes in stimulus modality.(2011)
J Cogn Neurosci., 23(10):2822-37. doi: 10.1162/jocn.2011.21609.

8: Cauda F., Torta D.M., Sacco K., Geda E., D'Agata F., Costa T., Duca S., Geminiani G.,Amanzio M..(2012) Shared "core" areas between the pain and other task-related networks.
PLoS One., 7(8), e41929. doi: 10.1371/journal.pone.0041929

9: Isoardo G., Stella M., Cocito D., Risso D., Migliaretti G., Cauda F., Palmitessa A., Faccani G., Ciaramitaro P. (2012). Neuropathic pain in post-burn hypertrophic scars: a psychophysical and neurophysiological study. Muscle Nerve., 45(6):883-90.doi: 10.1002/mus.23259.

10 Amanzio M., Benedetti F., Porro C.A., Palermo S., Cauda F.. (2013) Activation likelihood estimation meta-analysis of brain correlates of placebo analgesia in human experimental pain.
Hum Brain Mapp.,34(3), 738-52. doi: 10.1002/hbm.21471.

11: Cauda F., D'Agata F., Sacco K., Duca S., Cocito D., Paolasso I., Isoardo G.,Geminiani G.. (2010) Altered resting state attentional networks in diabetic neuropathic pain.
J Neurol Neurosurg Psychiatry., 81(7), 806-11. doi:10.1136/jnnp.2009.188631.

12: Cauda F., Sacco K., D'Agata F., Duca S., Cocito D, Geminiani G., Migliorati F, Isoardo G. (2009) Low-frequency BOLD fluctuations demonstrate altered thalamocortical connectivity in diabetic neuropathic pain. BMC Neurosci. 26;10:138. doi:10.1186/1471-2202-10-138.

13: Cauda F., Sacco K., Duca S., Cocito D, D'Agata F., Geminiani G.C, Canavero S. (2009) Altered resting state in diabetic neuropathic pain.
PLoS One., 4(2):e4542. doi: 10.1371/journal.pone.0004542.

1: Costa T., Liloia D., Ferraro M., Manuello J., Plausible reasoning in neuroscience”. In book: Handbook of Abductive Cognition. Springer Nature, editor: Lorenzo Magnani. (Expected by the end of 2022)

2: Cauda F., Nani A., Liloia D., Manuello J., Premi E., Duca S., Fox P.T., Costa T. (2020) “Finding specificity in structural brain alterations through Bayesian reverse inference”. Human Brain Mapping doi: 10.1002/hbm.25105

3: Costa T., Manuello J., Ferraro M., Liloia D., Nani A., Fox P.T., Lancaster J., Cauda F. (2021) “BACON: A tool for reverse inference in brain activation and alteration”. Human Brain Mapping https://doi.org/10.1002/hbm.25452

4: Costa T., Manuello J., Cauda F., Liloia D. (in press) Retrospective Bayesian evidence of null effect in two decades of Alzheimer’s disease clinical trials Journal of Alzheimer’s Disease

5: Costa T., Cauda F. (2022) A Bayesian Reanalysis of the Phase III Aducanumab (ADU) Trial. Journal of Alzheimer’s disease DOI: 10.3233/JAD-220132