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Regular version of the site
Master 2019/2020

Advanced Neuroimaging

Category 'Best Course for Career Development'
Category 'Best Course for Broadening Horizons and Diversity of Knowledge and Skills'
Category 'Best Course for New Knowledge and Skills'
Area of studies: Psychology
Delivered by: School of Psychology
When: 2 year, 1, 2 module
Mode of studies: Full time
Instructors: Matteo Feurra, Mario Martinez-Saito, Alisia Vorobyova
Master’s programme: Cognitive Sciences and Technologies: From Neuron to Cognition
Language: English
ECTS credits: 4

Course Syllabus

Abstract

EEG (electroencephalography) is the measurement of electrical potential differences across points on the scalp using sensitive equipment. These small potential differences are the result of electrical activity within the brain and are associated with brain function. The coherent activity of cortical pyramidal neurons generates ionic currents, and these give rise to electric field and electric potential variations. The measured voltages are of µV range (microvolt, or one millionth of a Volt) and are typically recorded at multiple scalp sites simultaneously. Although other important techniques exist to study brain function, EEG offers excellent temporal resolution (millisecond scale) and moderate spatial resolution (cm scale) using modern analysis techniques such as cortical mapping. EEG remains unparalleled in ease of use. MEG (magnetoencephalography) is a method of estimation of electrical brain activity via measurement of tiny magnetic fields that accompany changes in electric potential of the cortex. The origin of these changes in general view is same as for EEG, but, since tissues of a head are nominally transparent for magnetic fields, the topography of the signal does not suffer from anisotropy of skull, skin and neural tissue. Therefore, the spatial resolution of modern MEG systems is much better than for EEG still saving time resolution of the last one. On the other hand, tiniest magnetic fields (in range of femtoTesla or 10-15 Tesla) require very precise state-of-art sensors called SQUIDs (superconductive quantum interferometers) placed in liquid helium. This architecture apparently leads to high operational costs and necessary to build a special magnetic shielded camera around the magnetoencephalographic device. To sum up, MEG data processing results in the very precise spatiotemporal mapping of the brain activity in cortical areas that help scientists to construct a detailed picture of the interplay of neuronal populations, especially when complemented with other techniques. Non Invasive Brain Stimulation techniques are able to modulate human cognitive behavior. Among these methods are transcranial electric stimulation and transcranial magnetic stimulation that both come in multiple variants. A property of both types of brain stimulation is that they modulate brain activity and in turn modulate cognitive behavior. They are optimal tools for investigating brain activity in basic research and for neurorehabilitation purposes. It includes TMS, tDCS, tACS. fMRI (functional magnetic resonance imaging) is a neuroimaging technique which allows to visualize a brain activity-related signal across the whole brain with a millimetric resolution. fMRI requires an MRI scanner functioning with a specific protocol that extracts the BOLD (blood oxygen level dependent) signal, Although the BOLD signal hinges on the magnetic properties of blood, it has been shown to be a reliable proxy of time series of brain activity. The major drawback of the BOLD signal, besides being an indirect measure of neural activity, is that it is sluggish, i.e. it has low temporal resolution (~8s) and it is delayed (~6s). However, it is virtually, to this day, the only technique which allows whole brain visualization at a reasonable cost. One of the course’s main foci is on acquisition of the skills in the use of Brain Stimulation and Electroencephalography techniques. Therefore, it will mainly consist of 50% of hands-on learning and 50% of lectures on the related to advanced aspect of neurophysiology theory. At the end of the course we will expect participants to be able to collect, analyze and interpret EEG/MEG, TMS, tDCS, tACS, and fMRI data.
Learning Objectives

Learning Objectives

  • Familiarise with the novel technology and innovations in neuroscience research, its advances and connections to other branches of science.
  • Know advanced aspect of mechanisms that underlay Transcranial Magnetic Stimulation (TMS) and Transcranial Electrical Stimulation (tDCS, tACS, tRNS).
  • Get training to the use of TMS and TES.
  • Know how to apply combined TMS and TES with Electroencephalography (EEG).
  • Get training to measure and analyze EEG.
  • Get training to analyze MEG.
  • Get training to analyze fMRI.
Expected Learning Outcomes

Expected Learning Outcomes

  • • be able to use TMS, in an advanced experimental setting. The student is able to reflect on the methods of activity studied based on cognitive neuroscience approaches. The student is able to independently become acquainted with new methods of cognitive neuroscience.
  • • be able to combine brain stimulation with EEG technique. • be able to work with advanced software / hardware in EEG research. The student is able to reflect on the methods of activity studied based on cognitive neuroscience approaches. The student is able to independently become acquainted with new methods of cognitive neuroscience.
  • • be able to analyze MEG data. • be able to work with advanced software / hardware in MEG research. The student is able to reflect on the methods of activity studied based on cognitive neuroscience approaches. The student is able to independently become acquainted with new methods of cognitive neuroscience.
  • • be able to analyze fMRI data. • be able to work with software in fMRI research. The student is able to reflect on the methods of activity studied based on cognitive neuroscience approaches. The student is able to independently become acquainted with new methods of cognitive neuroscience.
  • • be able to combine brain stimulation with EEG technique. The student is able to reflect on the methods of activity studied based on cognitive neuroscience approaches. The student is able to independently become acquainted with new methods of cognitive neuroscience.
  • • be able to use tDCS, tACS, tRNS in an advanced experimental setting; The student is able to reflect on the methods of activity studied based on cognitive neuroscience approaches. The student is able to independently become acquainted with new methods of cognitive neuroscience.
  • • Combined use of TES with Electroencephalography (EEG). The student is able to reflect on the methods of activity studied based on cognitive neuroscience approaches. The student is able to independently become acquainted with new methods of cognitive neuroscience.
Course Contents

Course Contents

  • Transcranial Magnetic Stimulation (TMS)
    • Advances of TMS • Basic principles of neuronavigation • Motor Evoked Potential and stimulation of the sensorisystem • Motor Threshold by TMS • Patterned repetitive TMS (rTMS) protocols •
  • ELECTROENCEPHALOGRAPHY
    • Introduction to EEG Laboratory • EEG measurement • Capturing electrode locations • Stimulus Presentation Software • Recording Software • EEG Preprocessing methods • Steady State Visual Evoked Potentials • Oddball paradigm
  • MAGNETOENCEPHALOGRAPHY
    • MEG measurement • Head position control • Artifact suppressing and data preprocessing • Event-related fields • Induced activity • Source reconstruction
  • FUNCTIONAL MAGNETIC RESONANCE
    • GLM FRAMEWORK • STATISTICAL INFERENCE • MULTI-LEVEL MODELS • MULTIPLE COMPARISONS PROBLEM: FWER, FDR • SENSITIVITY ANALYSIS • SPM UTILITIES • FUNCTIONAL CONNECTIVITY • EFFECTIVE CONNECTIVITY • MULTIVARIATE DECOMPOSITION METHODS • EFFECTIVE CONNECTIVITY MODELS: SEM, DCM, GRANGER CAUSALITY, BAYESIAN NETWORKS
  • TMS-EEG
    hands-on sessions of simultaneous combination of TMS and EEG
  • Transcranial Electrical Stimulation (TES)
    • Basic principles of tDCS, tACS, tRNS • Combined TMS/EEG • Combined tES/EEG
  • tDCS-EEG
    Online combination of TMS-EEG
Assessment Elements

Assessment Elements

  • non-blocking Participation in lectures and seminars (i.e. discussions)
    Exception is due to medical reasons with presentation of medical certificate.
  • non-blocking Paper presentation
    Talk on the seminar on the topic related to the lectures, 15 minutes each student
  • non-blocking Final Exam (theory)
    If 0.3 *Gtest + 0.3 * Gclass + 0.4 * Gresearch equal 8, 9 or 10, student is eligible to have the grade 8, 9, 10 as a final grade on this course.
  • non-blocking Practice test on TMS, TES and EEG (Gtest)
    Students will be asked to perform an experimental setup and asked questions on the devices. Hands-on test.
Interim Assessment

Interim Assessment

  • Interim assessment (2 module)
    0.7 * Final Exam (theory) + 0.3 * Participation in lectures and seminars (i.e. discussions)
Bibliography

Bibliography

Recommended Core Bibliography

  • Birbaumer, N. (2006). Breaking the silence: brain-computer interfaces (BCI) for communication and motor control. Psychophysiology, 43(6), 517–532. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=mdc&AN=17076808
  • Bortoletto M, Veniero D, Thut G, & Miniussi C. (2015). The contribution of TMS-EEG coregistration in the exploration of the human cortical connectome. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.657C755E
  • Brosnan, M. B., Arvaneh, M., Harty, S., Maguire, T., O’Connell, R., Robertson, I. H., & Dockree, P. M. (2018). Prefrontal Modulation of Visual Processing and Sustained Attention in Aging, a tDCS-EEG Coregistration Approach. Journal Of Cognitive Neuroscience, 30(11), 1630–1645. https://doi.org/10.1162/jocn_a_01307
  • Cappelletti, M., Gessaroli, E., Hithersay, R., Mitolo, M., Didino, D., Kanai, R., … Walsh, V. (2013). Transfer of Cognitive Training across Magnitude Dimensions Achieved with Concurrent Brain Stimulation of the Parietal Lobe. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.A94A504
  • Hari, R., & Salmelin, R. (2012). Magnetoencephalography: From SQUIDs to neuroscience: Neuroimage 20th Anniversary Special Edition. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.7050C50
  • Hauk, O., Wakeman, D. G., & Henson, R. (2011). Comparison of noise-normalized minimum norm estimates for MEG analysis using multiple resolution metrics. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.FA12E48D
  • Jackson, A. F., & Bolger, D. J. (2014). The neurophysiological bases of EEG and EEG measurement: A review for the rest of us. Psychophysiology, 51(11), 1061–1071. https://doi.org/10.1111/psyp.12283
  • John Ashburner, Gareth Barnes, Chun-chuan Chen, Jean Daunizeau, Guillaume Flandin, Karl Friston, … Christophe Phillips. (2014). SPM12 Manual The FIL Methods Group (and honorary members). Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsbas&AN=edsbas.4E7BB4B8
  • Logothetis, N. K., & Wandell, B. A. (2004). Interpreting the Bold Signal. Annual Review of Physiology, 66(1), 735–774. https://doi.org/10.1146/annurev.physiol.66.082602.092845
  • Walsh, V., & Cowey, A. (2000). TIMELINE: Transcranial magnetic stimulation and cognitive neuroscience. Nature Reviews Neuroscience, 1(1), 73–80. https://doi.org/10.1038/35036239

Recommended Additional Bibliography

  • Anna Lisa Mangia, Marco ePirini, & Angelo eCappello. (2014). Transcranial Direct Current Stimulation and Power Spectral Parameters: a tDCS/EEG co-registration study. https://doi.org/10.3389/fnhum.2014.00601/full