1Electroencephalography & Event-related potentials (EEG & ERP) علی یونسیپژوهشکده علوم شناختیاردیبهشت 91
2مصرف کننده شیشه (متآمفتامین) مصرف کننده قبلی شیشهفرد سالم
3خلاصه مقدمه ای بر نوار مغزی و سیگنال ناشی از محرک منشا فعالیت الکتریکی مغزریتمهای مغزیحالات مغزکاربردهای EEGکاربردهای شناختییادگیریحافظهتوجهتفسیر رویاکاربردهای بالینیتشنجاختلالات حافظهپایشپایش تشنجپایش در طول بیهوشیپایش در حین عمل اندارترکتومی
4تفسیرهای عملکردی کاربردهای شناختی ERP BCI ورودیهای حسی خروجیهای حرکتی توجهیادگیریکاربردهای بالینی ERPSchizophreniaMood disordersAlcohol dependence and substance abuseDementiaTraumatic brain injuryNormal developmentChildhood disordersADHDLearning Disordersتحقیقات در حال انجامسوء مصرف شیشهخواب
5Research and Application Psychological ResearchNeurological ResearchMedical ResearchEducational Research and ApplicationTherapeutic ApplicationOccupational Application
14How do EEGs work?This activity may be detectable to electrodes on the scalp.Conventional electrode caps from EGI, Neuroscan, and Electro-Cap.
15برتریهای نسبی به دیگر روشها Hardware costs are significantly lower than those of all other techniquesEEG sensors can be used in more places than fMRI, SPECT, PET, MRS, or MEG,EEG has higher temporal resolution - milliseconds, rather than seconds - it can, in fact, take as many as 2000 samples per second (Only MEG rivals these speeds)EEG is relatively tolerant of subject movementEEG is silentEEG does not aggravate claustrophobiaEEG does not involve exposure to high-intensity (>1 Tesla) magnetic fieldsERP studies can be conducted with relatively simple paradigms, compared with block-design of fMRI studiesExtremely uninvasive
16نقصان نسبت به دیگر روشها Significantly lower spatial resolution. fMRI, for example, can directly display areas of the brain that are active, while EEG requires intense interpretation just to hypothesize what areas are activated by a particular response.EEG determines neural activity that occurs below the upper layers of the brain (the cortex) very poorly. Unlike PET and MRS, cannot identify specific locations in the brain at which various neurotransmitters, drugs, etc. can be found.Often takes a long time to connect a subject to EEG, as it requires precise placement of dozens of electrodes around the head and the use of various gels, saline solutions, and/or pastes to keep them in place.Signal-to-noise ratio is very poor, so sophisticated data analysis and relatively large numbers of subjects are needed to extract useful information from EEG
17چند نکته حیاتیa given electrode on the scalp does not record solely the neuronal activity directly underlying it. Rather, every electrode picks up signals from different sources that can eventually be quite distalFluctuation of the voltage at the reference electrode will lead to changes of the potential at the active electrode even if the voltage at that point was actually stable. There is no point that is electrically silent and could be considered as true zero potential.
29Different types of brain waves in normal EEG RhythmFrequency(Hz)Amplitude(uV)Recording& LocationAlpha(α)8 – 1350 – 100Adults, rest, eyes closed.Occipital regionBeta(β)20Adult, mental activityFrontal regionTheta(θ)5 – 7Above 50Children, drowsy adult, emotional distressOccipitalDelta(δ)2 – 4Children in sleepD T A B
33EEG recording in man Eyes opened condition. Examples of different waves.
34The cocktail party problem - find Z x1z1x2z2AxNXT=AZTzNZTXT
35Source Separation Algorithm Blind Source SeparationBlind Source Separation deals with the « separation » of a mixture of sources, with a little prior information about the mixing process and the sources signalsx = AsŜ = WxEnvironmentx1Ŝ 1S1S2SNSource Separation AlgorithmWx2Ŝ2............xNŜNSourcesSensorsObservations
36Nyquist TheoremThe highest frequency which can be accurately represented is one- half of the sampling rate.The sampling rate here is below the Nyquist frequency, so the result of sampling is nothing like the input:aliasing.For practical purposes the sampling rate should be 10 higher than the highest frequency in the signal.
38First PC lies along the axis of maximum variance. Second PC is constrained to be orthogonal to first.
39Are there basis functions that better describe the variance in the data? What if we relaxed the orthogonality constraint and used a different measure of independence (not variance)?IC1 and IC2 are the independent components that ICA finds in the data – projecting the data onto these axes will give you back the two sinusoids.
40LORETAOne such method is known as "LORETA", which provides an estimate of the current distribution throughout the entire 3- dimensional space within the brain.An example of a LORETA solution, mapped onto a normalized brain space, is provided below.SPAN Harry Howard - Tulane University04/06/11
41Brain Wave Activity Delta – sleep state (1-3 Hz) Theta – between sleep and awake (4-7 Hz)Alpha – relaxed state (8-12 Hz)Low Beta – focused concentration (SMR-Sensory Motor Rhythms) (12-15 Hz)Mid-range Beta – alert state (15-18 Hz)High Beta – very alert, vigilant (Above 18)Gamma – Hyper vigilant (Above 40)
43Default-mode brainThe default network is a network of brain regions that are active when the individual is not focused on the outside world and the brain is at wakeful rest.Working memory tasks differentially deactivate the PCC.signal increase and spatial decrease in the PCC and a signal decrease but spatial increase in the ACC with increasing working memory load
44Oscillations and the control of information processing (1) Oscillations: Timing and spatial organization of information processes. Oscillations provide mechanisms that allow the emergence of spatially and temporally organized firing patterns in neural networks.(2) Slow frequency oscillations: Conscious control of information processing. Slow frequency oscillations in the theta and alpha range (of about 4 – 13.5 Hz) are associated with the top-down control of two large processing systems, a working memory system and a a complex knowledge system, allowing semantic orientation in a constantly changing environment.Theta and alpha oscillations exhibit a variety of different synchronization processes (e.g., amplitude increase, phase coupling, event-related phase reorganization) that reflect different types of control processes and different aspects of the timing of cognitive processes.
45Example of an evoked, ‘traveling’ theta wave, one subject, negative polarity is in blue FzTheta-waves single subject “B“Cz-1.5pop -1p+1Pz-1.0Oz-0.5µV0.00.51.0change in direction1.55006007008009001000110012001300ms poststim
46برانگیختگی ناشی از محرک کاربردهاترجمه سیگنال به یک حرکتاستفاده از مغز به عنوان یک پردازشگر سریعبررسی عملکرد حسی و شناختی فرد
47Alzheimer’s disease and mild cognitive impairment Semantic classification task: low frequency functional connectivity between anterior (MPFC) and posterior (PCC/retrosplenial cortex) regions : negatively associated with ageeyes-closed resting state in Alzheimer patients (N=24; 9 males; mean age 76.3 years) and non-demented subjects with subjective memory complaints (N=19; 9 males)The mean level of EEG synchronization was lower in Alzheimer patients in the upper alpha (10–13 Hz) and beta (13–30 Hz) band.
48Schizophrenialow-frequency and alpha-band power abnormalities (perhaps thalamic and frontal lobe dysfunction)augmented low-frequency power :more negative symptomslarger third ventricleslarger frontal horns of the lateral ventriclesincreased cortical sulci widthsgreater ocular motor dysfunction
49Autism In the θ (3–6 Hz) frequency range 8–10 Hz: within left hemisphere frontal and temporal regions8–10 Hz:globally reduced coherence within frontal regions and between frontal and all other scalp regions.The ASD : greater relative power between 3 and 6 Hz and 13–17 Hz and significantly less relative power between 9 and 10 Hz.
50خصوصیات نورونی برانگیختگی ناشی از محرک P3 یکی از بخشهای خاص این سیگنال برانگیخته است:میزان توجهسختی پردازش تصویرسن فردبرانگیختگیبدون محرک هدفبرانگیختگی با محرک هدف
51The mismatch negativity (MMN) MMN can be recorded in infants and young children
55بیماریهایی که در آنها تغییرات درERP گزارش شده است Mood disordersAlcohol dependence and substance abuseDementiaآلزایمرTraumatic brain injuryNormal developmentChildhood disordersADHDLearning Disordersمولتیپل اسکلروزیسپارکینسون
56Comareappearance of the MMN is a valid predictor of recovery from coma.Based onsix N100 studies (N = 548 patients)five MMN studies (N = 470)six P300 studies (N = 313)the N100, MMN, or P300, when present, significantly predicted awakening, P300 and MMN being significantly better predictors than N100.
57Schizophreniareduced P300 amplitude in patients with schizophrenia (first reported 35 years ago)The patients with schizophrenia showed smaller MMN amplitude60 patients53 unaffected family members44 healthy controls
58Mood disorders deviant P300 is less consistent in mood disorders patient subtypes or to the severity of depressionBipolar disorder show more consistent P300 deviations (both latency and amplitude)
59Alcohol dependence the P300 amplitude reduction degree of reduction in P300 in alcoholics was highly correlated with the number of alcohol-dependent individuals in the family
60Dementia between subcortical and cortical dementias P300 latency distinguish dementia from depression-associated pseudodementiaDiscrimination between patients with early Alzheimer’s disease and healthy individuals
61Traumatic brain injury Reduction in the amplitude of visual P300 in survivors of traumatic brain injury in approximately half of the studiesMost frequent effect of traumatic brain injury: reduction in the amplitude of auditory P300
63Developmental changes in ERPs three-stimulus oddball (frequent standard, rare target, rare nontarget novel) frontal P3a amplitude elicited by rare novel stimuli tends to increase between the ages of 8 and 20 years.For routine initial examination, the passive oddball may be the most useful task across a wide age range
64Attention-deficit/hyperactivity disorder small P300 amplitudes with normal latencya decrement in P300 at posterior electrode sites in conjunction with an augmentation at frontal sites
65Other disorders of childhood central auditory processing difficulties : failed to generate ERPs or substantially increased latencies and smaller amplitudesIn 11-year-old children with oppositional-defiant disorder: smaller P300 amplitudes to both cues and targets in a CPT
66High-risk childrenVisual mental rotation task: P300 amplitude was smaller for young boys at high- compared to lowrisk for alcoholism (similar to individuals with alcohol dependence)Lower P300 amplitudes also were observed in the pre-adolescent sons of alcoholic men
67Dyslexiathe magnitude of the MMN reduction is correlated with the severity of dyslexiaMMN can also be employed to assess the effectiveness of dyslexia rehabilitation programs
75EEGLAB documentation EEGLAB Home Page http://sccn.ucsd.edu/eeglab/ EEGLAB Tutorial IndexWorkshop Home Page- 200 pages of tutorial (including “how to” for plugins) WEB or PDF
76کاربردهای بالقوه برانگیختگی ناشی از محرک در مطالعات اعتیاد: نتیجه گیریکاربردهای بالقوه برانگیختگی ناشی از محرک در مطالعات اعتیاد:تشخیص اعتیاد؟تشخیص نوع ماده/مواد مصرفی؟تشخیص مدت زمان مصرف و دوز مصرفی؟پایش درمان اعتیاد؟سیستمهای بازخورد عصبی و زیستی؟