2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 1 Development of Complex Curricula for Molecular Bionics and Infobionics Programs within a consortial* framework** Consortium leader PETER PAZMANY CATHOLIC UNIVERSITY Consortium members SEMMELWEIS UNIVERSITY, DIALOG CAMPUS PUBLISHER The Project has been realised with the support of the European Union and has been co-financed by the European Social Fund *** **Molekuláris bionika és Infobionika Szakok tananyagának komplex fejlesztése konzorciumi keretben ***A projekt az Európai Unió támogatásával, az Európai Szociális Alap társfinanszírozásával valósul meg. PETER PAZMANY CATHOLIC UNIVERSITY SEMMELWEIS UNIVERSITY sote_logo.jpg dk_fejlec.gif INFOBLOKK 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 2 Peter Pazmany Catholic University Faculty of Information Technology BIOMEDICAL IMAGING fMRI–NeuroscienceApplications www.itk.ppke.hu (Orvosbiológiai képalkotás) (fMRI alkalmazása a kutatásban) ÉVA BANKÓ, ISTVÁN KÓBOR, ZOLTÁN VIDNYÁNSZKY Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 3 www.itk.ppke.hu Important Tool to Investigate Brain Function • Sensory Processing– early level – higher-order • Neural Plasticity– short-term plasticity – long-term cortical reorganization – developmental plasticity • Cognitive Function– attentional network – decision making – memory Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 4 www.itk.ppke.hu Sensory Processing Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 5 Retinotopical Mapping Aim is to separate early and mid-level visual areas Visual areas in the brain are defined by – Physiology – Cellular architecture – Connections to other areas – Topographical representationof the world www.itk.ppke.hu Neuralrepresentationofthestimulusintheprimaryvisualcortexofamacaquemonkey(Tootelletal.1988,JNeurosci). Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 6 www.itk.ppke.hu Visual field representation in human primary visual cortex (V1) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 7 Protocol for Retinotopy • Phase reversing checkerboard stimulus for strong excitation • Aim is to probe the entire visual field:– Rotating wedge to get information about visual field quadrants – Contracting-expanding ring to get informationabout eccentricity www.itk.ppke.hu polar_stimuli ecc_stimuli CW/CCW rotating wedge Contracting/expanding ring Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 8 www.itk.ppke.hu Defining visual areas on flattened cortex Phase map – Phasereversaldelineates areas Eccentricity map – Tells about fovealand peripheralrepresentation of each area dorsal ventral medial lateral lateral medial Left hemisphere Right hemisphere UVM LHM RHM LVM UVM LHM RHM LVM Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 9 www.itk.ppke.hu Retinotopy Demo Flattened right hemisphere, cut through the calcarine sulcus polar_lag0-6 LVF B B M M U U occipital pole ventral-dorsal uppermiddlebottom visual field Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 10 www.itk.ppke.hu • As a result the voxels are assigned to areas,so the activation pattern of each area in a specific experimental design can be studied separately. • Topographic mapping can also be done in somatosensory and auditory cortices. 2hemishpere Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 11 www.itk.ppke.hu Category-specific higher-order cortical areas Therearetwovisualprocessingstreamsexistinginthecortexforprocessingdifferentvisualpercepts: • Ventral(“what”)pathway–enablesthevisualidentificationofobjects– maininputfrom“slowanddetailed”parvosystemofLGN – ends in object-selective inferior temporal cortex • Dorsal (“where”) pathway–spatial perception, visual location of objects– main input from “quick and dirty” magno system of LGN – ends in posterior parietal cortex, comprises motion selective area MT+ (Mischkin& Ungerleider1983, Trends Neurosci) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 12 www.itk.ppke.hu Functional Localizers • Higher-ordercorticalareaslackingtopographicalorganizationbutbeingcategory-specificcanstillbedeterminedbasedonfunctionalcontrasts– E.g. Face-localizer: probingthe selectivity of object-selectiveinferotemporal cortex using the contrast of non-sense objects and faces LO: Lateral Occipital Complex OFA: Occipital Face Area FFA: Fusiform Face Area (Kovács et al.2008, Neuroimage) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 13 www.itk.ppke.hu Face processing network Haxby Mainly the posterior part of STS (pSTS) i.e. Fusiform Face Area, strongly right lateralized Activation due to presentation of faces w/ both emotionaland neutral expressions Activation due to presentation of faces w/ emotionalexpressions (Haxby et al, 2000, Trends Cog Sci) (Grill-Spector et al, 2004, Nature Neurosci) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 14 www.itk.ppke.hu – hMT+ (V5) localizer: probing the motion-selectivity of the dorsal visual pathway • specialized in the processing of visual motion information: its response to coherent motion is higher than to incoherent motion • block design: coherently and incoherentlymoving dotsare presented in interleavedorder + + + + > LOCALIZE Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 15 www.itk.ppke.hu Localizers as means of studying homology between species It was shown that both face-selective patches in macaque cortex (Tsao et al. 2003, Nat Neurosci; Pinsk et al. 2005, PNAS) correspond to existing structures in humans. (Rajimehr et al., 2009, PNAS) MacaqueHuman PTFP: Post. Temp. Face PatchFFA: Fusiform Face Area ATFP: Ant. Temp. Face Patch © 2009 The National Academy of Sciences 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 16 Studying the Auditory System • Sparse fMRI:– To explore central auditory function may be compromised by the intense bursts of stray acoustic noise produced by the scanner whenever the magnetic resonance signal is read out – Sparse imaging includes a delay between each fMRI volume, so stimuli can be presented while scanner is silent. 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 16 www.itk.ppke.hu Time (sec) 0 10 Continuous Time (sec) 0 10 Sparse Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 17 Sparse fMRI: – Typically, sparse design like a block design –each acquisition measures effect of single stimuli. – Stimuli must be presented ~5sec prior to acquisition. – Sparse designs have less power than continuous designs, and it is difficult to estimate latency of BOLD response. – Due to T1 effects, Sparse designs can still have good power. 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 www.itk.ppke.hu Time (sec) 0 10 BOLD Biomedical Imaging: fMRI –NeuroscienceApplications Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 18 www.itk.ppke.hu Continuous fMRI: The functional neuroanatomy of target detection •WhenperformingbothauditoryandvisualoddballtasksignificantincreasesinfMRIsignalfortargetversusnon-targetconditionswereobservedinthesupramarginalgyrus,frontaloperculumandinsularcortexbilaterally,andinfurthercircumscribedparietalandfrontalregionscorrespondingtotheP300component. •Theeffectswereconsistentovervariousstimulationandresponsemodalitiesandcanberegardedasspecificfortargetdetectioninboththeauditoryandthevisualmodality.TheseresultsthereforecontributetotheunderstandingofthetargetdetectionnetworkinhumancerebralcortexandimposeconstraintsonattemptsatlocalizingtheneuronalP300generator (Linden et al. 1999, Cereb Cortex) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 19 www.itk.ppke.hu Sparse fMRI: Voice-selective areas in human auditory cortex •Voice-selectiveregionscanbefoundbilaterallyalongtheupperbankofthesuperiortemporalsulcus(STS):•greater neuronal activity when subjects listened passively to vocal sounds, than to non-vocal environmental sounds •high degree of selectivity (central STS)–responding significantly more to vocal sounds than to matched control stimuli, including scrambled voices and amplitude-modulated noise •Thevoice-selectiveareasintheSTSmayrepresentthecounterpartoftheface-selectiveareasinhumanvisualcortex. (Belin et al. 2000, Nature) STS 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 20 tactile2.jpg 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 20 www.itk.ppke.hu tactile1.jpg •Somatosensory cortex: increased BOLD signal to baseline in the case of externally-produced tactile stimulation, while reduced BOLD signal compared to baseline in the case of self-produced tactile stimulation › mediated by the cerebellum Somatosensory stimulation: self-produced or external? •Significantly decreased activity in right anterior cerebellar cortex associated with the interaction between the effects of self-generated movement and tactile stimulation(external input) (Blakemore et al., 1998, Nature Neurosci) Biomedical Imaging: fMRI –NeuroscienceApplications Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 21 www.itk.ppke.hu Neuronal Plasticity Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 22 www.itk.ppke.hu Plasticity Underlying Long-term Learning Long-termpracticeonsequenceperformance(motorskilllearning) •Inacomplexfingermovingparadigmaftertrainingimprovedratesofperformanceinducedincreasedactivationoftheprimarysensorimotorcortex,whichdidnotgeneralizetothecontralateralhand. (Karni et al. 1998, PNAS) Time (weeks) Performance Rate (sequences/30s) © 1998 The National Academy of Sciences Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 23 www.itk.ppke.hu Enhancement of relevant information during perceptual learning •Perceptuallearningisdefinedasperformanceorsensitivityincreaseinasensoryfeatureasaresultofrepetitivetrainingorexposuretothefeatureandisregardedasmanifestationofsensoryplasticity. •Visualtexturediscriminationinduceslong-lastingbehavioralimprovementrestrictedtothetrainedeyeandtrainedlocationinvisualfield.Within-subjectcomparisonsbetweentrainedanduntrainedeye for targets presented withinthe same quadrant revealed higher activity in a corres-ponding retinotopic area of visual cortex. ›learning leads to enhanced perceptual and neural responses for the learned relevant stimulus (Schwarzet al.,2002, PNAS) © 2002 The National Academy of Sciences Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 24 www.itk.ppke.hu Learning to suppress irrelevant stimuli •Beforetraining:nodifferencebetweenthefMRIresponsesevokedbythetask-relevantandtask-irrelevantmotiondirections •Aftertraining:task-irrelevantdirection(i.e.distractorstimulus)evokedsignificantlysmallerfMRIresponsesthantask-relevantdirection ›learningleadstosuppressedperceptualandneuralresponsesfortask-irrelevantinformation,whichcompeteswiththeprocessingofthetask-relevantinformationduringtraining (Gál et al.,2009, E J Neurosci) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 25 www.itk.ppke.hu Studying Long-Term Cortical Reorganization • in congenitally and early blind people retinotopic visual cortex is activated when reading Braille, as opposed to late blind people who show much less activation (Burton 2003, J Neurosci) © 2003 Society for Neuroscience Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 26 www.itk.ppke.hu •Visual cortex activation in verbal tasks in blind people also correlates with verbal memory performance Fig 2 full size Fig 7 full size (Amedi et al, 2003, Nature Neurosci) 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 27 www.itk.ppke.hu Cross-modal plasticity in congenitally deaf: • Auditorycortexactivatesforsimplevisualstimuli(movingdotpattern)inearlydeafsubjects,demonstratingthatearlydeafnessresultsintheprocessingofvisualstimuliinprimaryauditorycortex. 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 27 (Finneyet al. 2001, Nature Neurosci) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 28 www.itk.ppke.hu •Bothbilateralinferiorprefrontalregions(includingBroca’sarea)andbilateralsuperiortemporalregions(includingWernicke’sarea)wereactivatedbyviewingsignlanguage(BSL)incongenitallydeafsigners.DeafnativesignersalsodemonstratedgreateractivationintheleftsuperiortemporalgyrusinresponsetoBSLthanhearingnativesigners(A),whichsuggeststhatlefttemporalauditoryregionsmaybeprivilegedforprocessingheardspeecheveninhearingnativesigners.However,intheabsenceofauditoryinputthisregioncanberecruitedforvisual processing. 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 28 (MacSweeneyet al. 2002, Brain) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 29 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 29 www.itk.ppke.hu Studying Developmental Plasticity Dyslexia, a developmental disorder • Functional neuroimaging studies have revealed differences in brain function and connectivity that are characteristic of dyslexia, e.g.– children and adults with dyslexia exhibit reduced or absent activation in the left temporo-parietal cortex – left temporo-parietal region supports the cross-modal relation of auditory and visual processes during reading – atypical activations in left middle and superior temporal gyri associated with receptive language, and left occipito-temporal regions associated with visual analysis of letters and words Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 30 Brain Plasticity Associated with Treatment Duringphonologicalprocessingthereisamarkedfrontal(redcircles)andtemporo-parietal(bluecircles)hypoactivationindyslexicreaderscomparedtotypicallydevelopingreaders,whichbecamemoreactiveafterremediation. (Templeet al., 2003, PNAS) 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 30 www.itk.ppke.hu dyslexic_child.jpg © 2003 The National Academy of Sciences Biomedical Imaging: fMRI –NeuroscienceApplications Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 31 www.itk.ppke.hu Cognitive Functions Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 32 www.itk.ppke.hu Studying the Organization of Attention System Attentionsystems: •Dorsalgoal-directedattentionalnetwork(blue)isinvolvedinpreparingandapplyinggoal-directed(top-down)selectionforstimuliandresponses.(rightwardbias) •Ventralstimulus-drivenattentionalnetwork(orange)isnotinvolvedintop-downselection.Instead,thissystemisspecializedforthedetectionofbehaviourallyrelevantstimuli,particularlywhentheyaresalientorunexpected.(reorientingdeficit) (Corbetta and Shulman, 2002, Nature Rev Neurosci) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 33 www.itk.ppke.hu Basis of Attentional Selection: Location (Matrínez et al., 1999, Nature Neurosci) Spatial attentional selection: Whensubjectsarecuedtoshifttheirattentionbetweentwolocationsofthevisualfield,striateandextrastriatecortexresponsesmodulatewiththealternationoftheattentionalcue:responsesaregreaterwhenthesubjectsattendtothestimuliinthecontralateralhemifield. Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 34 www.itk.ppke.hu Basis of Attentional Selection: Features (Saenz et al., 2002, Nature Neurosci) Globalattentionalselection:attentiontoastimulusfeature(colorordirectionofmotion)increasedtheresponseofcorticalvisualareasnotonlytothestimuliattheattendedlocationbutalsotoaspatiallydistant,ignoredstimulusthatsharedthesamefeature. attended side Motion Color Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 35 www.itk.ppke.hu Basis of Attentional Selection: Objects Withstimuliconsistingofafacetransparentlysuperimposedonahouse,withonemovingandtheotherstationaryorviceversa,attendingtothemovingobjectresultedinhigheractivationnotonlyinmotionprocessingareaMTbutalsointhecorticalareaselectiveforthemovingobject.Thisprovidesphysiologicalevidencethatwholeobjectsareselectedevenwhenonlyonevisualattributeisrelevant,insteadoflocationsorfeaturebeingtheunitsofattentionalselection. (O’Craven et al., 1999, Nature) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 36 •Perceptualdecisionmakingistheactofchoosingoneoptionorcourseofactionfromasetofalternativesonthebasisofavailablesensoryevidence.Thecorticalareasinvolvedi)representsensoryevidenceii)accumulateandcomparesensoryevidencetocomputeadecisionvariableiii)monitorperformancedetectingerrorstosignalforadjustmentofdecisionstrategies. www.itk.ppke.hu Stimulus (Heekeren et al. 2008, Nature Rev Neurosci) Studying Areas Involved in Decision Making Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 37 •Value-baseddecisionmakingistheactofchoosingfromseveralalternativesonthebasisofasubjectivevaluethattheindividualplacesonthem. www.itk.ppke.hu (Rangel et al. 2008, Nature Rev Neurosci) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 38 www.itk.ppke.hu Sensory evidence representation in perceptual decision making •Forthepreferredcategory,bothface-(FFA)andhouse-selectiveregions(PPA)respondedmoretosuprathresholdthantoperi-thresholdimageswhereastheoppositewastrueforthenon-preferredcategory,indicatingthatface-andhouse-selectiveregionsininferotemporalcortexrepresentedthesensoryevidenceforthetworespectivecategories. (Heekerenet al., 2004, Nature) FFA PPA Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 39 www.itk.ppke.hu Facets of value-based desision makinguncovered by fMRI: Value representation •Orbitofrontal cortex(OFC) –primary involved in representing the reinforcement value of objects and value expectations •Anterior Cingulate cortex(ACC) –primary involved in representing the reinforcement value of actions (Rushworth et al., 2007, Trends Cog Sci) OFC ACC Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 40 www.itk.ppke.hu Reference-dependent value computation •Orbitofrontal cortex(OFC) and Dorsal Striatum–track parameters such as expected value indicating the computation of reference-independent value. •Ventral Striatum–indexes the degree to which stated prices are distorted with respect to a reference point (framing effect). (De Martinoet al. 2009, J Neurosci) © 2009 Society for Neuroscience Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 41 www.itk.ppke.hu Role of emotions in decision making •Orbitofrontal cortex(OFC) –has higher activation in the case of rational decisions. •Amygdala–has higher activation in the case of irrational decisions (loss-aversion). (De Martinoet al. 2006, Science) Amyg y=-2R OFC x=-4z=-10 R Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 42 www.itk.ppke.hu Studying the Structures Associated with Memory Long-term memory systems: • Declarative (explicit) memory affords the capacity for conscious recollections about facts and events– subtypes: semantic memory; episodic memory – structures involved are medial-temporal lobe, prefrontal cortex, diencephalon and basal forebrain • Non-declarative (implicit) memory, a heterogeneous collection of nonconscious abilities that includes the learning of skills and habits, priming and some forms of classical conditioning. Short-term memory: • Working memory Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 43 www.itk.ppke.hu • Encodingandretrievaldifferenceswerefoundwithinthe:– medialtemporallobes(MTLs):encoding(ESA)inducedgreateractivityintheanteriorhippocampus,whileretrieval(RSA)wasassociatedwithgreateractivityintheposteriorparahippocampalcortex/hippocampus(encoding-retrievalgradientalongthelongitudinalMTLaxis). – prefrontalcortex(PFC):encodinginducedgreateractivityinventrolateralPFC,whileretrievalwasassociatedwithgreateractivityindorsolateralandanteriorPFC. • Onlythelefthippocampuswasassociatedwithrelationalmemoryingeneral(i.e.,forbothsemanticandperceptualencodingandretrieval) (Princeet al., 2005, J Neurosci) Encoding and retrieval of semantic and perceptual associations © 2005 Society for Neuroscience Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 44 www.itk.ppke.hu Working memory for emotional expressions • Althoughinitialprocessingofemotionandidentityisaccomplishedinanatomicallysegregatedtemporalandoccipitalregions,activemaintenanceofbothfacialemotionsandidentityisassociatedwithasustaineddelay-periodactivityinorbitofrontalcortex(OFC),amygdalaandhippocampus. (LoPrestiet al., 2008, J Neurosci) memory condition control condition © 2008 Society for Neuroscience Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 45 www.itk.ppke.hu WorkingmemoryforemotionalexpressionsII • Short-termencodingandretrievaloffacialexpressionsdependontheactivationlevelofrightpSTS,whichpredominantlyprocesseschangeablefacialfeaturessuchasfacialexpressions • Correlation only existed if expression wasattended and disappeared when identity wasrelevant Attend to emotion > attend to identity AllSubs avgRun_Emo_STS_groupROI_BVQX_cikk (Bankó et al., 2009, J Vision) 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 46 © 2008 The National Academy of Sciences www.itk.ppke.hu 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 46 (Fair et al. 2008, PNAS ) Resting State fMRI–Default Network • Defaultnetwork:areasthatconsistentlyexhibitdecreasesfrombaselineactivity,duringawidevarietyofgoal-directedbehaviors.Thesedecreasessuggesttheexistenceofanorganized,baselinedefaultmodeofbrainfunctionthatissuspendedduringspecificgoal-directedbehaviors.However,itsspecificfunctionisdebated. • Imagingcanbedifficult,sincethereisnostandardwayofmeasuringthebraininitsrestingstate(i.e.whatisrestingstate?). Biomedical Imaging: fMRI –NeuroscienceApplications Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 47 www.itk.ppke.hu Other Applications Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 48 www.itk.ppke.hu “Mindreading” –Decoding Cortical Activity •EnsemblefMRIsignalsinearlyvisualareascanreliablypredictonindividualtrialswhichofeightstimulusorientationsthesubjectwasseeing. •Feature-basedattentionstronglybiasedensembleactivitytowardstheattendedorientation ›fMRIactivitypatternsinearlyvisualareas,includingprimaryvisualcortex(V1),containdetailedorientationinformationthatcanreliablypredictsubjectiveperception. (Kamitani and Tong, 2005, Nature Neurosci) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 49 www.itk.ppke.hu “Mindreading” –Decoding Cortical Activity II RepresentationofBehavioralChoiceforMotioninHumanVisualCortex •Multivoxelpatternanalysis(MVPA)enablestodiscriminatewith60-70%accuracybetweenleftwardandrightwardmotioninthecaseof100%motioncoherenceinallareasregardlessofitsmotionselectivity.HoweveronlymotionsensitiveareahMT+wasabletodiscriminatebetweenperceiveddirectionofmotion(ambiguosstimulus)makingthisareathecandidatewhichtheconsciousexperienceisbasedon. (Serences and Boynton, 2007, J Neurosci) © 2007 Society for Neuroscience Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 50 www.itk.ppke.hu “Mindreading” –Perception w/o awareness fMRIisausefultootoinvestigateperceptionwithoutawareness,becausetheneurallocusofanyactivationthatoccuroutsideofawarenessprovidessomeinformationaboutthenatureoftheinformationrepresented: •Thepresentationoffearfulfacesmaskedwithneutralfaceselicitsastrongeramygdalaresponsethanwhenhappyfacesarepresentedbeforeneutralfaces,eventhoughsubjectsfailedtoseeanyexpressivefaces. ›amygdalarespondstononconsciousstimuli (Whalen et al. 1998, J Neurosci) © 1998 Society for Neuroscience 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 51 TÁMOP –4.1.2-08/2/A/KMR-2009-0006 51 www.itk.ppke.hu Voluntary Regulation of Brain Activity Real-time fMRI (rtfMRI):evidence show that voluntary regulation of brain activity can be achieved by training led by on-line (direct or indirect) feedback of BOLD signal Delayed: • Adjustingmotor behavior in order to expand activation in the motor and somatosensory cortex (Yoo and Jolesz 2002 Neuroreport) • Effects related to the visual presentation of facial expressions could not be separated from the effects of the feedbackfrom amygdala–hippocampal area (Posse et al 2003 NeuroImage) Quasi-realtime• Regulation of anterior cingulate and anterior insular cortex (Weiskopf et al 2003 Neuroimage, Caria et al. 2007,NeuroImage) 2010.10.23 Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 52 C:\Program Files (x86)\Microsoft Office\MEDIA\CAGCAT10\j0302953.jpg C:\Users\viktor\AppData\Local\Microsoft\Windows\Temporary Internet Files\Content.IE5\MZRIX1P8\MP900403159[1].jpg TÁMOP –4.1.2-08/2/A/KMR-2009-0006 52 www.itk.ppke.hu Prospective clinical/industrial consequences of rtfMRI: Pain perception reduced via rtfMRI training based on rostral anterior cingulate cortex (rACC) activity (deCharms et al. 2005, PNAS) Controlling reward/decision making system: e.g. treatment of addictive behaviour (smoking, drug abuse etc.) 2010.10.23 C:\Users\viktor\AppData\Local\Microsoft\Windows\Temporary Internet Files\Content.IE5\MZRIX1P8\MC900239159[1].wmf C:\Users\viktor\AppData\Local\Microsoft\Windows\Temporary Internet Files\Content.IE5\4WC4H1TL\MC900282528[1].wmf Biomedical Imaging: fMRI –NeuroscienceApplications Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 53 www.itk.ppke.hu Combined Methodologies Combining the two methodologies can be used to address questions for which neither method would be appropriate alone! Pros and Cons of Imaging(fMRI/PET) • high spatial resolution •sluggish and temporally blurred: temporal scale is on the order of seconds Pros and Cons of Electrophysiology(EEG/MEG) • limited spatial resolution •excellent millisecond order temporal resolution, which enables studying sequential processing steps as they take place in the brain Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 54 www.itk.ppke.hu Theoretical considerations To confidentially correlate haemodynamic and electrophysiologically based measurements of neural activity one must have: – common sensory frame (identical stimuli) – common biological reference (identical subjects) – common experimental frame (identical paradigms) – appropriate spatial frame (individual dipole modeling of ERP scalp topography i.e source localization) › to establish an approximate location of the ERP-generating dipole of interest, which has strong correspondence with the foci of haemodynamic activity Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 55 www.itk.ppke.hu Source localization • aim is to infer the underlying source location from the obtained scalp potential maps … however, any field potential vector could be consistent with an infinite number of possible dipoles • there is noway to know which one is correct… we can only guess which is better then the other one, but only out of those solutions considered ›source localization is an ill-defined problem and requires imaging Forward problem Inverse problem No unique mathematical solution Can be calculated given some constraints about volume conduction Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 56 www.itk.ppke.hu fMRI-guided source localization Source model Forward model Data Inverse solution Anatomy Registration fMRI contrast Difference between model and data is reflected in residual variance (RV) Helps to solve the uncertainty of the inverse solution Seeding Establishes anatomical correspondence Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 57 www.itk.ppke.hu Procedure • a model-fitting procedure for estimating intracranial sources underlying ERPs (not for ongoing EEG –too many sources) • Estimation: define a source model › calculate the corresponding potential map (forward model) › compare the fit of the forward model to the actual data: if model fits (the residual variance between model and data is low), then data is consistent with these sources; yet there is no unique solution • Imaging helps:– to confine sources to anatomically plausible places after registration with 3D anatomy• helps to know the exact locations of electrodes relative to the individuals’ brain • how to: define fiducial positions in MRI slices to match up EEG/MEG and MRI coordinate systems • result is an individual head model Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 58 www.itk.ppke.hu •Imaging helps:– to seed from fMRIactivations• Orientation and temporal evolution computed from EEG/MEG • Inaccuracy of localization not critical for regional source Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 59 www.itk.ppke.hu •Imaging helps:– Best results are obtained if measuring EEG/fMRIconcurrently• However,simultaneousEEG/fMRIregistrationintroducesfMRIacquisitionartefacts,whichneedtobeeliminated(bigchallenge:theartefactcanbemorethantwoordersofmagnitudehigherthanthephysiologicalEEGsignal) • PossiblesolutionisusinginterleavedEEG-fMRIprotocolsordoingsequentialEEGandfMRIsessions Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 60 www.itk.ppke.hu Linear superposition of source activities at scalp DataSource modelSource waveforms R L = × P100 N170 RV: Discrepancy betweendata and model Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 61 www.itk.ppke.hu Mathematically speaking… • Decompose the reference-free data of ERPs UE×ninto a a set of sources SS×nand a set of attenuation coefficients cS×E, so that UE×n= cS×Ex SS×n E: number of channels + reference channel n: number of timepointsS: number of sources • Decomposition results in:– an electroanatomical time-independent matrix cthat reflects that anatomical substrates do not move around in the head – a time-variant dipole source potential matrix Sthat represents the change in activity of each source over time Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 62 www.itk.ppke.hu The attenuation matrix cis determined by: • the geometry between the source and the electrodes (the head model) • the nature of the conductance of the three-layer head model (Brain, Skull, Scalp);– the skull is less conductive than the layers on either side this results in a spatial smearing of potentials as they cross the skull Solutions are constrained by: • the geometry of the head • the volume conduction of the dipoles • the anatomical constraints dictated by the user (e.g., inside the head, symmetrical, not in the ventricles, etc...) Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 63 www.itk.ppke.hu Application –MR guided localization By using MR guided source localization the authors were able to decompose the processing stages of working memory retrieval (Bledowski et al., 2006, JNeurosci) © 2006 Society for Neuroscience Biomedical Imaging: fMRI –NeuroscienceApplications 2011.10.04.. TÁMOP –4.1.2-08/2/A/KMR-2009-0006 64 www.itk.ppke.hu Possible problems of combined methodologies • Coregistration of EEG electrodes with MRI ~ 5 mm • Inaccuracy of head model (even for realistic model!) ~ 10 mm • Coregistration of MRI and fMRI (distortions) ~ 5 mm • Location of center of gravity of neuronal activityversus BOLD effect, e. g. influence of venous signal ~ 10 mm › fMRI clusters provide only rough localization of neuronal activation.Systematic differences (~ 15 mm) between EEG and fMRI are likely. However, source waveform topography is rather insensitive to small variationsin source location.