Discovering and visualizing patterns in EEG data

pre-printBrain activity data is often collected through the use of electroen-cephalography (EEG). In this data acquisition modality, the electric fields generated by neurons are measured at the scalp. Although this technology is capable of measuring activity from a group of neurons, recent efforts provide evidence that these small neuronal collections communicate with other, distant assemblies in the brain's cortex. These collaborative neural assemblies are often found by examining the EEG record to find shared activity patterns. In this paper, we present a system that focuses on extracting and visualizing potential neural activity patterns directly from EEG data. Using our system, neuroscientists may investigate the spectral dynamics of signals generated by individual electrodes or groups of sensors. Additionally, users may interactively generate queries which are processed to reveal which areas of the brain may exhibit common activation patterns across time and frequency. The utility of this system is highlighted in a case study in which it is used to analyze EEG data collected during a working memory experiment

Mapping working memory retrieval in space and in time:A combined electroencephalography and electrocorticography approach

In this study, we investigated the time course and neural correlates of the retrieval process underlying visual working memory. We made use of a rare dataset in which the same task was recorded using both scalp electroencephalography (EEG) and Electrocorticography (ECoG), respectively. This allowed us to examine with great spatial and temporal detail how the retrieval process works, and in particular how the medial temporal lobe (MTL) is involved. In each trial, participants judged whether a probe face had been among a set of recently studied faces. With a method that combines hidden semi-Markov models and multivariate pattern analysis, the neural signal was decomposed into a sequence of latent cognitive stages with information about their durations on a trial-by-trial basis. Analyzed separately, EEG and ECoG data yielded converging results on discovered stages and their interpretation, which reflected 1) a brief pre-attention stage, 2) encoding the stimulus, 3) retrieving the studied set, and 4) making a decision. Combining these stages with the high spatial resolution of ECoG suggested that activity in the temporal cortex reflected item familiarity in the retrieval stage; and that once retrieval is complete, there is active maintenance of the studied face set in the decision stage in the MTL. During this same period, the frontal cortex guides the decision by means of theta coupling with the MTL. These observations generalize previous findings on the role of MTL theta from long-term memory tasks to short-term memory tasks

EEG Cortical Neuroimaging during Human Full-Body Movement.

Studying how the human brain functions during full-body movement can increase our understanding of how to diagnose and treat neurological disorders. High-density electroencephalography (EEG) can record brain activity during body movement due to its portability and excellent time resolution. However, EEG is prone to movement artifact, and traditional EEG methods have poor spatial resolution. Combining EEG with independent component analysis (ICA) and inverse source modeling can improve spatial resolution. In my first study, I used EEG and ICA to investigate the biomechanical and neural interplay of performing a complicated cognitive task at different walking speeds. Young, healthy subjects stepped significantly wider when walking with the cognitive task compared to walking alone, but walking speed did not affect cognitive performance (i.e. reaction time and correct responses). EEG results mirrored cognitive performance, in that there were similar event-related desynchronizations in the somatosensory association cortex around encoding at all speeds. For my second study, I addressed the problem of movement artifact in EEG. I created an interface that blocked true electrocortical signals while recording only movement artifact. I quantified the spectral changes in the movement artifact EEG, tested various methods of removing the artifact, and compared their efficacies. Artifact spectral power varied across individuals, electrode locations, and walking speed. None of the cleaning methods removed all artifact. For my third study, I examined cortical spectral power fluctuations and effective connectivity during active and viewed full-body exercise with different combinations of arm and leg effort. Larger spectral fluctuations occurred in the cortex during rhythmic arm exercise compared to rhythmic leg exercise, which suggests that rhythmic arm movement is more cortically driven. The strength and direction of information flow was very similar between the active and viewed exercise conditions, with the right motor cortex being the hub of information flow. These studies provide insight into how the human brain functions during full-body movement and may have applications for rehabilitation after a brain injury or in brain monitoring for improving cognitive performance.PhDBiomedical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116622/1/jekline_1.pd

Applying Acoustical and Musicological Analysis to Detect Brain Responses to Realistic Music: A Case Study

Music information retrieval (MIR) methods offer interesting possibilities for automatically identifying time points in music recordings that relate to specific brain responses. However, how the acoustical features and the novelty of the music structure affect the brain response is not yet clear. In the present study, we tested a new method for automatically identifying time points of brain responses based on MIR analysis. We utilized an existing database including brain recordings of 48 healthy listeners measured with electroencephalography (EEG) and magnetoencephalography (MEG). While we succeeded in capturing brain responses related to acoustical changes in the modern tango piece Adios Nonino, we obtained less reliable brain responses with a metal rock piece and a modern symphony orchestra musical composition. However, brain responses might also relate to the novelty of the music structure. Hence, we added a manual musicological analysis of novelty in the musical structure to the computational acoustic analysis, obtaining strong brain responses even to the rock and modern pieces. Although no standardized method yet exists, these preliminary results suggest that analysis of novelty in music is an important aid to MIR analysis for investigating brain responses to realistic music.Peer reviewe

Dynamic Changes in Brain Functional Connectivity during Concurrent Dual-Task Performance

This study investigated the spatial, spectral, temporal and functional proprieties of functional brain connections involved in the concurrent execution of unrelated visual perception and working memory tasks. Electroencephalography data was analysed using a novel data-driven approach assessing source coherence at the whole-brain level. Three connections in the beta-band (18–24 Hz) and one in the gamma-band (30–40 Hz) were modulated by dual-task performance. Beta-coherence increased within two dorsofrontal-occipital connections in dual-task conditions compared to the single-task condition, with the highest coherence seen during low working memory load trials. In contrast, beta-coherence in a prefrontal-occipital functional connection and gamma-coherence in an inferior frontal-occipitoparietal connection was not affected by the addition of the second task and only showed elevated coherence under high working memory load. Analysis of coherence as a function of time suggested that the dorsofrontal-occipital beta-connections were relevant to working memory maintenance, while the prefrontal-occipital beta-connection and the inferior frontal-occipitoparietal gamma-connection were involved in top-down control of concurrent visual processing. The fact that increased coherence in the gamma-connection, from low to high working memory load, was negatively correlated with faster reaction time on the perception task supports this interpretation. Together, these results demonstrate that dual-task demands trigger non-linear changes in functional interactions between frontal-executive and occipitoparietal-perceptual cortices

The role of multi-scale phase synchronization and cross-frequency interactions in cognitive integration

Neuronal processing is distributed into anatomically distinct, largely specialized, neuronal populations. These populations undergo rhythmic fluctuations in excitability, which are commonly known as neuronal oscillations. Electrophysiological studies of neuronal activity have shown that phase synchronization of oscillations within frequencies characterizes both resting state and task execution and that its strength is correlated with task performance. Therefore phase-synchronization within frequencies is thought to support communication between oscillating neuronal populations and thereby integration and coordination of anatomically distributed processing in cognitive functions. However, it has remained open if and how phase synchronization is associated with directional flow of information. Furthermore, oscillations and synchronization are observed concurrently in multiple frequencies, which are thought to underlie distinct computational functions. Little is known how oscillations and synchronized networks of different frequencies in the human brain are integrated and enable unified cognitive function and experience. In the first study of this thesis, we developed a measure of directed connectivity in networks of coupled oscillators, called Phase Transfer Entropy (Phase TE) and tested if Phase TE could detect directional flow in simulated data in the presence of noise and signal mixing. Results showed that Phase TE indeed reliably detected information flow under these conditions and was computationally efficient. In the other three studies, we investigated if two different forms of inter-areal cross-frequency coupling (CFC), namely cross-frequency phase synchrony (CFS) and phase-amplitude coupling (PAC), could support integration and coordination of neuronal processing distributed across frequency bands in the human brain. In the second study, we analyzed source-reconstructed magneto- and electroencephalographic (M/EEG) data to investigate whether inter-areal CFS could be observed between within-frequency synchronized networks and thereby support the coordination of spectrally distributed processing in visual working memory (VWM). The results showed that CFS was increased during VWM maintenance among theta to gamma frequency bands and the strength of CFS networks predicted individual VWM capacity. Spectral patterns of CFS were found to be different from PAC, indicating complementary roles for both mechanisms. In the third study, we analyzed source-reconstructed M/EEG data to investigate whether inter-areal CFS and PAC could be observed during two multi-object visual tracking tasks and thereby support visual attention. PAC was found to be significantly correlated with object load in both tasks, and CFS in one task. Further, patterns of CFS and PAC differed significantly between subjects with high and low capacity for visual attention. In the fourth study, we analyzed intracerebral stereo-electroencephalographic data (SEEG) and source-reconstructed MEG data to investigate whether CFS and PAC are present also in resting state. Further, in order to address concerns about observations of CFC being spurious and caused by non-sinusoidal or non-zero mean signal waveforms, we introduced a new approach to identify true inter-areal CFC connections and discard potentially spurious ones. We observed both inter-areal CFS and PAC, and showed that a significant part of connections was unambiguously true and non-spurious. Spatial profiles differed between CFS and PAC, but were consistent across datasets. Together, the results from studies II-IV provide evidence that inter-areal CFS and PAC, in complementary ways, connect frequency-specific phase-synchronized networks that involve functionally specialized regions across the cortex to support complex functions such as VWM and attention, and also characterize the resting state. Inter-areal CFC thus may be crucial for the coordination and integration of spectrally distributed processing and the emergence of introspectively coherent cognitive function.Keskeinen kysymys aivotutkimuksessa on, kuinka ajattelu ja kognitio syntyvät ihmisaivojen 10^15 hermosolussa. Informaation käsittely aivoissa tapahtuu suurissa hermosolupopulaatioissa, jotka ovat toiminnallisesti erikoistuneita ja anatomisesti eroteltuja eri aivoalueille. Niiden aktivaatiorakenteiden jaksollisia muutoksia kutsutaan aivorytmeiksi eli oskillaatioiksi. Hermosolupopulaatioiden välistä viestintää edesauttaa niiden toiminnan samantahtisuus eli synkronoituminen. Sähköfysiologisissa tutkimuksissa on havaittu aivorytmien synkronoituvan sekä lepomittausten että tehtävien suorituksen aikana siten että tämä synkronoituminen ennustaa kognitiivissa tehtävissä suoriutumista. Oskillaatioiden vaihesynkronia ei kuitenkaan kerro niiden välisen vuorovaikutuksen suunnasta. Tämän lisäksi oskillaatioita ja niiden välistä synkroniaa havaitaan yhtäaikaisesti lukuisilla eri taajuuksilla, joiden ajatellaan olevan vastuussa erillisistä laskennallisista ja kognitiivisista toiminnoista. Toistaiseksi on kuitenkin jäänyt kartoittamatta, miten informaation käsittely eri taajuuksilla yhdistetään yhtenäisiksi kognitiivisiksi toiminnoiksi, ja havaitaanko myös eri taajuisten oskillaatioverkkojen välillä synkroniaa. Väitöskirjan ensimmäisessä osatyössä on kehitetty uusi tapata mitata oskillaattoriverkkojen vuorovaikutusten suuntia, jonka toimivuus todennettiin simuloimalla synkronoituneita hermosolupopulaatioita. Väitöskirjan muissa osatöissä on tutkittu havaitaanko ihmisaivoissa eri taajuisten oskillaatioiden välistä synkronoitumista. Erityisesti tutkittiin kahta erilaista synkronian muotoa, joista ensimmäinen (’cross- frequency phase synchrony’,CFS) mittaa kahden oskillaation välistä vaihesuhdetta ja toinen (’phase-amplitude coupling’, PAC) vaiheen ja amplitudin suhdetta. Väitöskirjan toisessa osassa tutkittiin, selittääkö CFS koehenkilöiden suoriutumista näkötyömuistitehtävässä. Tutkimukseen osallistuneilta koehenkilöiltä mitattiin aivosähkökäyrä (EEG) ja aivomagneettikäyrä (MEG), joiden avulla selvitettiin havaitaanko aivoalueiden välistä synkroniaa (CFS). Tutkimustulokset osoittivat, että koehenkilöiden CFS oli korkeampi näkötyömuistitehtävän mielessä pitämisen aikana theta-taajuuksista gamma-taajuuksiin asti ja että CFS-verkkojen vahvuus ennusti yksilöllistä työmuistikapasiteettia. Kolmannessa tutkimuksessa analysoitiin MEG- ja EEG-aivokuvantamislaitteita käyttäen onko aivoalueiden välillä CFS:ä ja PAC:a kahdessa näkötarkkaavaisuustehtävässä. PAC lisääntyi tilastollisesti merkitsevästi tehtävän vaikeuden mukaan kummassakin tehtävässä, kun taas CFS lisääntyi yhdessä tehtävässä. Lisäksi CFS ja PAC taajuusparit olivat erilaisia hyvin suoriutuvien koehenkilöiden sekä heikosti suoriutuvien koehenkilöiden välillä. Neljännessä tutkimuksessa tutkittiin havaitaanko CFS:ä ja PAC:a aivojen lepotilassa. Aivokuoren aktiivisuutta mitattiin MEG:llä sekä epilepsiapotilailta aivoihin kirurgisesti asetetuilla elektrodeilla. CFS:ä sekä PAC:a havaittiin kummallakin menetelmällä. Lisäksi kehitimme menetelmän joka vähentää väärien havaintojen todennäköisyyttä ja lisää aitojen CFS ja PAC yhteyksien havaitsemista. Tulokset osoittavat, että merkittävä osuus yhteyksistä aivoalueiden välillä on aitoja. CFS- ja PAC-profiilit erosivat toisistaan, mutta olivat samanlaisia eri menetelmillä tutkittaessa. Yhdistettynä tulokset tutkimuksista II–IV viittaavat siihen, että CFS ja PAC yhdistävät eri taajuuksille ja aivoalueille hajautettua informaation käsittelyä. CFS:sää ja PAC:ia havaittiin aivojen lepotilassa mutta myös tarkkaavaisuus- ja näkötyömuistitehtävän aikana. CFS ja PAC saattavat mahdollistaa eri taajuisten aivorytmien ja hajautettujen prosessien koordinaation ja yhdistämisen

For whom the bell tolls : periodic reactivation of sensory cortex in the gamma band as a substrate of visual working memory maintenance

Peer reviewedPublisher PD

Sensorimotor Modulations by Cognitive Processes During Accurate Speech Discrimination: An EEG Investigation of Dorsal Stream Processing

Internal models mediate the transmission of information between anterior and posterior regions of the dorsal stream in support of speech perception, though it remains unclear how this mechanism responds to cognitive processes in service of task demands. The purpose of the current study was to identify the influences of attention and working memory on sensorimotor activity across the dorsal stream during speech discrimination, with set size and signal clarity employed to modulate stimulus predictability and the time course of increased task demands, respectively. Independent Component Analysis of 64–channel EEG data identified bilateral sensorimotor mu and auditory alpha components from a cohort of 42 participants, indexing activity from anterior (mu) and posterior (auditory) aspects of the dorsal stream. Time frequency (ERSP) analysis evaluated task-related changes in focal activation patterns with phase coherence measures employed to track patterns of information flow across the dorsal stream. ERSP decomposition of mu clusters revealed event-related desynchronization (ERD) in beta and alpha bands, which were interpreted as evidence of forward (beta) and inverse (alpha) internal modeling across the time course of perception events. Stronger pre-stimulus mu alpha ERD in small set discrimination tasks was interpreted as more efficient attentional allocation due to the reduced sensory search space enabled by predictable stimuli. Mu-alpha and mu-beta ERD in peri- and post-stimulus periods were interpreted within the framework of Analysis by Synthesis as evidence of working memory activity for stimulus processing and maintenance, with weaker activity in degraded conditions suggesting that covert rehearsal mechanisms are sensitive to the quality of the stimulus being retained in working memory. Similar ERSP patterns across conditions despite the differences in stimulus predictability and clarity, suggest that subjects may have adapted to tasks. In light of this, future studies of sensorimotor processing should consider the ecological validity of the tasks employed, as well as the larger cognitive environment in which tasks are performed. The absence of interpretable patterns of mu-auditory coherence modulation across the time course of speech discrimination highlights the need for more sensitive analyses to probe dorsal stream connectivity

Serial representation of items during working memory maintenance at letter-selective cortical sites

A key component of working memory is the ability to remember multiple items simultaneously. To understand how the human brain maintains multiple items in memory, we examined direct brain recordings of neural oscillations from neurosurgical patients as they performed a working memory task. We analyzed the data to identify the neural representations of individual memory items by identifying recording sites with broadband gamma activity that varied according to the identity of the letter a subject viewed. Next, we tested a previously proposed model of working memory, which had hypothesized that the neural representations of individual memory items sequentially occurred at different phases of the theta/alpha cycle. Consistent with this model, the phase of the theta/alpha oscillation when stimulus-related gamma activity occurred during maintenance reflected the order of list presentation. These results suggest that working memory is organized by a cortical phase code coordinated by coupled theta/alpha and gamma oscillations and, more broadly, provide support for the serial representation of items in working memory