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Streams of Consciousness

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Streams of ConsciousnessAlumit IshaiWhen investigating the neural correlates of conscious-ness, neuroscientists distinguish between ‘‘consciousstate’’ (being awake as opposed to asleep or in a coma),which is regulated by brainstem and thalamic nuclei, and‘‘conscious representation’’ (awareness of specific phe-nomenal experience). The advent of functional brainimaging techniques, especially fMRI, enables the non-invasive inquiries of the mechanisms underlying con-scious experience, particularly in the visual system. Todate, most experimental paradigms designed to studyconsciousness contrast the response during consciousvisual experience with the response during unconsciousvisual experience (the so-called blindsight phenomen-on), or record patterns of brain activation during binoc-ular rivalry, perception of bistable figures, and visualmental imagery. The current data suggest that activity inhigh-level areas of the ventral visual pathway, but not inV1, are necessary for conscious visual experience. More-over, visual awareness requires parietal and prefrontalregions (for a recent review, see Rees, Kreiman, & Koch,2002). The neural correlates of conscious vision, there-fore, parallel the distributed cortical networks that mod-ulate visual attention and visual imagery. As mostresearchers confuse ‘‘awareness’’ with ‘‘consciousness,’’the reported differential activity during consciousness iscurrently indistinguishable from that of other highercognitive functions.In his article, ‘‘Functional fMRI and the Study ofHuman Consciousness,’’ Dan Lloyd uniquely combinesa conceptual analysis of consciousness with neuroscien-tific methods, in order to characterize the neural man-ifestations of consciousness (Lloyd, 2002). Lloyd adoptsHusserl’s criteria, according to which the phenome-nology of consciousness is based on three essentialprinciples: intentionality (the external world as it isexperienced and not as it is); superposition (sensoryand nonsensory properties are present in perception);and temporality (all objects share perception ofpresent, past, and anticipated future). If indeed theseaspects of consciousness are implemented in the brain,the empirical evidence should include temporal flux(with passing time, the multivariate differences betweenimages should increase) and superposition (imagessharing task or stimulus conditions should be similar).Lloyd’s methodological approach includes three con-straints. First, time points in a scan series are consid-ered individually, because temporality implies thatconsciousness at each point in time is distinct fromthe preceding and the proceeding points. Second,subjects are considered individually, because intersub-ject averaging could eliminate individual expression ofconsciousness. Finally, brain states are considered glob-ally, seeking distributed patterns of activation thatencompass large cortical areas, rather than assuminglocalized responses.To test his predictions, Lloyd reanalyzes four data sets(Hazeltine, Poldrack, & Gabrieli, 2000; Ishai, Ungerleider,Martin, & Haxby, 2000; Mechelli, Friston, & Price, 2000;Postle, Berger, Taich, & D’Esposito, 2000) provided byThe fMRI Data Center. The studies, published in theDecember 2000 issue of the Journal of Cognitive Neuro-science, included a variety of cognitive tasks (targettracking, passive viewing, delayed matching, reading,and spatial working memory), stimuli (faces, objects,words, pseudowords, 2-D arrays of squares, coloredcircles), and motor responses (button presses and sac-cades). Needless to say, none of the original studies wasdesigned for or aimed at underpinning the neural mech-anisms of ‘‘neurophenomenology.’’ Nevertheless, Lloydpreprocesses and reanalyzes the raw data to test hispredictions about the general structures of conscious-ness, which by their nature are task and stimulus inde-pendent. Using multivariate distance analysis andartificial neural networks, he shows a time–distanceeffect (i.e., as the time series progressed, the distancebetween images increased) and that the past and futurebrain states, retention and protention, respectively, areembedded in present brain states. As time passes, sug-gests Lloyd, the brain is changing ‘‘globally, incremen-tally, and monotonically.’’Previous fMRI studies of consciousness compared onestate of awareness with another, assumed localization,and ignored the temporal flux. Lloyd’s original approachproposes methodological and conceptual advantages.Traditionally, fMRI data analysis focused on two param-eters, namely the spatial extent of the activation and theamplitude of the response within an activated region.The data are usually displayed as statistical maps indicat-ing the location and size of significant activation, andgraphs or histograms showing the percent fMRI signalchange. Given the spatial and temporal resolution of thetechnique, extracting temporal information about the‘‘tripartite temporality’’ (i.e., the experienced present ofNational Institutes of HealthD 2002 Massachusetts Institute of Technology Journal of Cognitive Neuroscience 14:6, pp. 832–833an object is influenced by the past and the future) isproblematic. The hemodynamic function presents aserious challenge, as each time point is contaminatedby the immediately preceding response. Lloyd’s correc-tion—that is, excluding 10 seconds before and after eachtime point—is thus necessary. Moreover, he trains arti-ficial neural networks to reconstruct the temporal in-formation encoded in each time point. In all subjects,the neural networks succeeded in recovering informa-tion about the preceding volume (retention) and thefollowing volume (protention). Lloyd assumes distrib-uted patterns of activation (Ishai, Ungerleider, Martin,Schouten, & Haxby, 1999; Ishai et al., 2000); however,his current analysis does not include spatial localization.Further investigation is therefore required to determinewhich brain regions mediate the temporal manifesta-tions of consciousness.Lloyd’s finding that performance is better when thenetwork recovered information about the past than thefuture was perhaps not surprising, due to the asymmetrybetween the known immediate past and the unknownfuture. One could assume, however, that ‘‘top–down’’effects such as expectation, anticipation, and attentionshould modulate ‘‘future’’ patterns of activation. Forexample, Kastner, Pinsk, De Weerd, Desimone, &


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