Cerebral Cortex Advance Access originally published online on December 7, 2005
Cerebral Cortex 2006 16(10):1522-1528; doi:10.1093/cercor/bhj089
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Integration of Local Features to a Global Percept by Neural Coupling
NeuroImage Nord, Department of Systems Neuroscience, University Medical Center Hamburg Eppendorf, Martinistrasse 52, 20246 Hamburg, Germany
Address correspondence to Dr Michael Rose, NeuroImage Nord, Department of Systems Neuroscience, University Medical Center Hamburg Eppendorf, Martinistrasse 52, D-20246 Hamburg, Germany. Email: rose{at}uke.uni-hamburg.de.
 |
Abstract |
|---|
 Top Abstract IntroductionMethodsResultsDiscussionReferences |
|---|
The integration of different visual attributes into the percept of a single global shape is a central aspect of object processing. In hierarchically organized stimuli with local and global levels, the attentional focus largely determines which level is processed. Here we tested the hypothesis that object processing during attention to the global aspect of the stimulus is characterized by an increased neural coupling between visual areas reflecting the integration of local features. In the present experiment, we used global letters that were constructed by smaller local letters, and a cue signaled which spatial level should be identified. On the local level, only 1 relevant letter was presented laterally in 1 visual hemifield. In contrast, the global letter extended into both hemifields, and the integration of information from both hemispheres was necessary to identify the global stimulus. Therefore, we expected an increased functional coupling between hemispheres during global processing. This hypothesis was investigated using electroencephalographic recordings and an analysis of phase locking and coherence. The results show that stimulus-locked neural coupling within the gamma band (30–40 Hz) across hemispheres in visual cortex increased for global processing after stimulus presentation and could therefore reflect the integration of local visual information.
Key Words: attention • binding • EEG • gamma band • perception
|
Introduction |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Many real world objects are constructed by a hierarchical structure of features. A simple example is the forest consisting of trees and the tree consisting of leaves. With a closer look, many common objects like houses, faces, or pictures exhibit different levels of visual features. Usually, the human observer is able to control the level at which visual information is consciously perceived, that is, the processing is mainly determined by the subject's attentional set (Kinchla and others 1983
).
There is accumulating evidence that the analysis of global and local features in the ventral visual pathway is augmented by attentional modulation. Visuospatial attention seems to be retinotopically specific at least in early visual areas (Tootell and others 1998; Martinez and others 1999). In accord with these results, it was demonstrated that global and local attention is established within the visual cortex by amplification effects within the cortical area where the particular feature of the stimulus is represented (Sasaki and others 2001). Attention to the global (i.e., larger) aspect of a stimulus enhanced activity in more peripheral areas of the visual cortex, whereas attention directed to a local, that is, centrally presented, feature resulted in an enhancement of activation in foveal representations.
An important aspect that has not yet been examined is the fact that local information is distributed over multiple small early visual representations (Kourtzi and others 2003) and that information from these areas has to be integrated to generate the percept of the global shape. In cases where the global shape spans both the visual hemifields, one might expect "binding" of areas representing local object features to a global percept. This binding might be accomplished through neural coupling between bilateral visual areas.
Coupling of electrical brain activity in the gamma band (around 40 Hz) has been proposed as a basic mechanism underlying transient functional coupling of neural assemblies (von der Malsburg 1994). Many studies in the visual system of cats (Eckhorn and others 1988; Gray and others 1989; Engel and others 1991) and monkeys (Bressler and others 1993; Kreiter and Singer 1996; Fries and others 2001) have lent support to this hypothesis. Thus, binding by neural coherence is a possible mechanism underlying the integration of visual information during global attention.
Early and intermediate areas of the visual cortex have a strong preference for the contralateral visual hemifield (Palmer 1999). Thus, the perception of the global shape of a stimulus that comprises visual tokens presented in both hemifields is only possible if visual information from the hemispheres is integrated. In the present experiment, we tested the hypothesis that the functional coupling between visual cortices of both hemispheres is relevant for the integration of distributed information as is the case when attending to the global stimulus. Functional coupling was investigated by scalp electroencephalogram (EEG) recordings, which were analyzed in the time–frequency domain. Parameters for neural coupling were estimated within the gamma band using coherence (interrelation between 2 signals based on amplitudes and phases) and phase locking (consistency between the phases of 2 signals). In addition, we were interested in the temporal characteristics of neural coupling. Importantly, coupling could be present already before stimulus onset as a result of attention in the absence of a stimulus, or coupling could arise later, at the time of stimulus presentation, indicating an interaction of attentional and perceptual processes. The former would indicate that coupling is a stimulus-independent effect linked to attentional processing, whereas the latter scenario would indicate that coupling is linked to object processing possibly augmented by attention.
To test the hypothesis that neural coupling between visual cortices is larger for global than for local attention, we employed hierarchical stimuli in which the global shape of a letter is constructed from smaller letters (Navon 1977). Crucially, the design was adjusted to avoid the usual benefit of global information that results in relative prolonged response latencies in the local task (Navon 1977). This effect is most likely due to the increased difficulty that could affect neural binding. Therefore, we manipulated the difficulty of the global identification by increasing the distance between the local letters (i.e., increasing sparseness) and by using a very short presentation time. If interhemispheric binding is relevant for the extraction of the global shape, then an increase in the difficulty of the global task could result in an increase of the neural coupling. To additionally test the hypothesis, that task difficulty affects the neural coupling or the timing of this coupling, we rotated the global stimuli in half of the trials by 90°. We expected that the identification of rotated global letters is more difficult than recognizing upright letters and consequently an increased functional coupling for the rotated global letters.
|
Methods |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Volunteers and Stimuli
Thirteen healthy, right-handed volunteers with normal or corrected to normal vision participated in the experiment (mean age 32 years, range 24–40, 5 females). The study was approved by the local ethics committee. Stimuli were presented by a personal computer that ensured synchronization with the EEG recording unit using the software "Presentation" (http://www.neuro-bs.com). A liquid crystal display monitor with a constant refresh rate of 60 Hz was used for stimulus presentation with a viewing distance of 60 cm.
The letters "E" and "S" were used for the global and the local features of the stimuli, respectively. The global letter subtended 9.2° (horizontal) by 10.9° (vertical) with the geometric center located at fixation. The local letter subtended 1.2° by 1.7° of visual angle. The distance between the local stimuli was adjusted in behavioral pilot studies to avoid the usual reaction time (RT) benefit of the global task. Half of the stimuli (n = 250) were congruent, that is, the global and local letters were identical. To avoid that the participants attend only to 1 level, the other half of stimuli consisted of noncongruent stimuli, with different letters at the global and local level. Therefore, the participants could not develop the strategy to only encode the global letter, knowing that the local letter is always identical. To ensure that each participant processed the same local information at identical lateral locations, only 2 relevant local letters were presented at fixed positions left and right within the global letter. The remaining irrelevant letters forming the global stimuli were "X" (see Fig. 1). We further manipulated the global stimuli by rotating the global letters in 50% of the trials by 90° to examine the effect of task difficulty. This resulted in a 2 x 2 factorial design (global/local attention and upright/rotated global shape).
|
Procedure
Each target dimension (global, local left, local right) was cued by arrows 800–1200 ms before the target (cue duration was 200 ms). Throughout the trials, volunteers had to fixate at a central letter X (fixation). This fixation was only interrupted by the cue. Using the letter X as fixation was important because this central letter was always the central part of the target stimulus, that is, for the target presentation the central X was simply left on the screen. Target letter presentation time was 1 frame (i.e., 16.7 ms), and the intertrial interval was randomly chosen from an interval of 3000–5000 ms. Participants had to indicate the target letter by pressing 1 of the 2 buttons with the index or middle finger of the right hand. All stimuli appeared in a pseudorandom order, which was rearranged for each participant. Four sessions with 125 trials each were presented with a short break between the sessions resulting in a duration of about 1 h for the whole experiment.
EEG Recordings and Analysis
EEG was recorded from 17 channels (BrainVision System amplifier), impedance < 5 k
, low cutoff of 0.03 Hz, high cutoff of 250 Hz, 500-Hz sampling rate referred to the electrode at FCz. Vertical electrooculogram and horizontal electrooculogram (HEOG) were recorded from above versus below the left eye and from the outer canthi of the eyes, respectively.
Data Analysis
Because we did not expect a difference in the interhemispheric coupling between congruent and noncongruent stimuli, data were pooled across both conditions. Data segments of 1200 ms were extracted from 200 ms before to 1000 ms after target presentation. Epochs with artifacts caused by blinks or eye movements (vertical and horizontal), amplifier saturation, and fast amplitude shifts (>100 µV within 2 ms) were excluded from further analysis. The epochs were decomposed using a wavelet-based time–frequency analysis (Tallon-Baudry and others 2001) (C. Torrence and G. Compo, http://paos.colorado.edu/research/wavelets). For each trial, the signal was convolved with complex Morlet's wavelets (wave number = 6), with f0 ranging from 1 to 50 Hz in 0.5 Hz steps. The wavelet basis was normalized to have a total energy of 1 at all scales (frequencies). The coherence and phase-locking spectra were calculated across the time series and were Z-transformed (Jarvis and Mitra 2001). Coherence was computed using the cross-spectral density (xp) of channel k and channel m and the power spectral densities pk and pm in the time (t)–frequency (f) domain:
 |
; Gruber and Muller 2005) as
 |
To assess neural coupling between hemisphere, phase locking and coherence from occipital and parietal electrode pairs were estimated (O1–O2, P7–P8, P3–P4). As a control, within-hemisphere phase locking and coherence was computed for the electrode pairs P7–O1 and P8–O2. For a better comparison of intra- versus interhemispheric coupling (Fig. 3), the difference (D) between global and local processing was Z-transformed for each electrode pair using the frequency-specific mean (µf) and standard deviation (
f) of a baseline –300 to 0 ms before stimulus onset:
 |
|
|
Results |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Behavioral data indicated a comparable level of difficulty in the global and local conditions. RTs and accuracy data were analyzed using an analysis of variance (ANOVA) for repeated measures (factors global/local attention and upright/rotated global shape). Mean RTs for correct trials showed no difference for the factor global/local attention (mean RT global: 634 ms, mean RT local: 610 ms, F1,12 = 4.1, not significant [n.s.]), no difference for the factor shape (F1,12 = 0.2, n.s.), and no reliable interaction attention x shape (F1,12 = 0.7, n.s.). The level of accuracy (90% correct global, 89% correct local) also did not vary systematically across conditions (factor global/local attention: F1,12 = 0.4, n.s.; factor upright/rotated shape: F1,12 = 1.1, n.s.; attention x shape F1,12 = 0.1, n.s.).
During the global attention condition, both parameters of functional coupling showed an increase in the gamma band between occipital electrode pairs from the left and right hemispheres. As can be seen in Figure 2A,B, this effect was maximal between 30 and 40 Hz and was limited to a distinct time period around 400 ms. Therefore, we compared mean phase locking and coherence between 30 and 40 Hz from 350 to 450 ms using an ANOVA for repeated measures (3 factors: electrode pair [O1–O2, P3–P4, P7–P8], global/local attention, and upright/rotated global shape). The results confirmed the increased phase locking for the global attention condition (F1,12 = 8.9, P < 0.05) and no significant difference for the attention effect between electrode pair (electrode pair x attention: F2,24 = 0.6, n.s.). The maximal difference was observed at electrode pair P7–P8. The rotation of the global letter did not result in a reliable modulation of neural coupling (main effect shape: F1,12 = 3.9, n.s.; interaction rotation x attention: F1,12 = 1.1, n.s.). The increase of coherency for the global attention condition confirmed the phase-locking statistics showing more coupling for the global condition (F1,12 = 8.44, P < 0.05). Comparing coherence and phase locking for each electrode pair separately, only the electrode pair P7–P8 shows a significant modulation by the global/local attention (F1,12 = 5.9, P < 0.05; O1–O2: F1,12 = 0.2, n.s.; P3–P4: F1,12 = 0.04, n.s.).
|
To test for the specificity of our result, we addressed the question of whether coupling is restricted to across- but not within-hemisphere electrodes. We restricted the following analysis to phase locking because coherence may be affected by possible amplitude differences, whereas phase locking is independent from the amplitudes (Varela and others 2001
). We therefore conducted an ANOVA with factors hemisphere (within vs. across), electrode pair (2 pairs across [O1–O2, P7–P8] vs. 2 pairs within [P7–O1, P8–O2]), global shape (upright/rotated), and attention (global/local). Crucially, the interaction between attention and hemisphere was significant (F1,12 = 9.7, P < 0.05), indicating an increased phase locking for global attention that was larger across than within hemispheres (Fig. 3). To assess a possible lateralization effect of global and local attention that may affect the coupling, we estimated the spectral densities for electrodes P7, P8, O1, O2, P3, and P4 separately for global, local left, and local right conditions between 300 and 600 ms after stimulus. Within the gamma band (30–40 Hz), the corresponding ANOVA (factors location, attention, electrode, upright/rotated global shape) revealed no difference between the attentional states (F2,24 = 0.23, n.s.). To control for eye movements, we estimated the mean activity of the HEOG channel between 0 and 600 ms. The corresponding ANOVA (factors attention and shape) revealed no difference in eye movements between conditions (attention: F1,12 = 0.07, n.s.; shape: F1,12 = 0.34, n.s.).
|
Discussion |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Binding by synchrony was hypothesized to play a critical role in the formation of neural ensembles necessary for top–down modulation of information processing (Engel and others 2001
). This notion is strongly supported by our data showing that EEG coupling in the gamma band is related to the spatial scale of attentional processing during the perception of hierarchically organized stimuli. Importantly, volunteers were viewing physically identical stimuli, but the amount of integration of spatially distributed features changed. The different states of integration were accompanied by circumscribed changes of neural coupling within the gamma band.
The local attention conditions were used as reference that was identical in all experimental settings but differs only with respect to the amount of feature integration. The behavioral data provided evidence for a comparable level of task difficulty of the local and global attention condition. Therefore, it is unlikely that the interhemispheric coupling is affected by differences in the attentional effort. Due to the fact that the local stimulus was presented lateral in one visual hemifield, the letter could be identified without information from the other visual hemisphere. In contrast, the global letter extended into both hemifields, and therefore, information from both hemispheres had to be integrated. In comparison with the local baseline, phase locking and coherence within the gamma band increased between hemispheres when participants attended to the global contour of the stimulus. Phase-locking values—a measure of the coupling of 2 signals independent of the amplitudes—increased between the occipital parts of both hemispheres for the global attention condition in comparison with the local attention condition. This finding suggests that an increased level of information exchange between the visual hemispheres may be the basis of the perceptual integration of the local features to a global shape. This interpretation is supported by neuroanatomical data showing a strong interconnection of visual areas via the corpus callosum (Hubel and Wiesel 1967; Payne 1994) and experiments with animals showing the relevance of the corpus callosum for coupling effects of the gamma band between the hemispheres (Engel and others 1991). Furthermore, it was demonstrated that EEG coherence measures in the gamma band can be used to detect these corticocortical callosal functional connections during visual processing (Kiper and others 1999; Knyazeva and others 1999; Rose and Büchel, 2005). Although our results are in accord with direct coupling between visual areas of both hemispheres, we cannot rule out the possibility that coupling between hemispheres is established due to a common input to both hemispheres from a third brain area.
The relevance of neural coupling of high-frequency components has been demonstrated for visual search (Tallon-Baudry and others 1997) and object recognition (Tallon-Baudry and others 1999). Long-range coupling effects within the gamma band were further reported for visuomotor integration during associative learning, thus confirming the role of neural binding in the coordination of neural activity in distributed networks (Miltner and others 1999). Only recently, the role of gamma band coherence between cortex and spinal motor neurons (as indexed by electromyography) in the preparation of a selected movement was demonstrated and proposed as a mechanism for RT benefits by attention (Schoffelen and others 2005). It was suggested that coherence in the gamma band reflects the formation of Hebbian cell assemblies (Hebb 1949) required for the binding of brain areas (Miltner and others 1999; Engel and Singer 2001). Our results provide further evidence for the importance of neural coupling and indicate that the role of between-area binding may be the integration of features processed in spatially separated neural assemblies on the basis of attentional selection.
The involvement of gamma band activity in selective attention has already been demonstrated in several experiments (for review, see Fell and others 2003). It was demonstrated for visual (Gruber and others 1999; Muller and others 2000; Struber and others 2000) and acoustic stimuli (Tiitinen and others 1993; Debener and others 2003). Intracranial recording in trained monkeys showed that neural binding increased as a consequence of attention (Fries and others 2001; Taylor and others 2005). The coupling of neurons may also be the underlying mechanism for the enhancement and suppression effects observed for distant areas within the visual cortex evoked by spatial attention (Tootell and others 1998).
The unified percept of a global shape involves multiple visual areas that are assumed to process different aspects at different spatial scales depending on the receptive field size of the neurons within each area (Kourtzi and others 2003). The areas involved in this distributed processing scheme include early visual areas (e.g., V1, V2) as well as "higher" areas (e.g., lateral occipital complex [LOC]), and recurrent mechanisms of feedback interactions are assumed to mediate the extraction of the global shape (Lamme and others 1998; Kourtzi and others 2003). In analogy to the finding that long-range connections are used to mediate contour integration (Gilbert and Wiesel 1989; Malach and others 1993), there is increasing evidence that object features represented by spatially distinct neural assemblies are dynamically linked to a coherent percept by coherent activity in the gamma range (Engel and Singer 2001). However, it should be noted that there are other results that did not support a role of neural synchrony for the binding of visual features for single-neuron activity within one area like V1 or V5 (Lamme and Spekreijse 1998; Thiele and Stoner 2003; Roelfsema and others 2004).
The peak of the gamma band coupling for the global processing was observed at electrode pair P7–P8. Although the spatial resolution of the EEG did not allow a precise localization of the effect, it is in accord with the assumption that the binding of higher visual areas is relevant for the integration of local features to a global contour. The known role of the LOC in object processing could be in line with the proposed function of shape extraction by integration of local stimuli (Malach and others 1995; Kourtzi and Kanwisher 2000).
The involvement of the observed gamma band coupling in object processing is supported by the temporal characteristics of phase locking. A reliable difference between the conditions was restricted to a distinct time period about 400 ms after stimulus onset. Before stimulus appearance, no systematic modulation of phase locking was observed. If neural coupling did reflect a preparatory attentional state, then a tonic increase in phase locking should have emerged before stimulus onset. The transient increase of phase locking 400 ms after stimulus presentation in the global attention condition supports the notion that this coupling is related to attentional-based object processing. The latency of the effect further suggests a "later" stage of object processing like object identification, which is in accord with other studies showing gamma band activity during object representation (Tallon-Baudry and Bertrand 1999) or audiovisual integration (Kaiser and others 2005) starting around 300 ms after stimulus onset. Even very shortly presented stimuli like the letters used in the present study were represented and processed over a longer time range indicated, for example, in EEG studies on subliminal priming (Jaskowski and others 2003).
In contrast to our expectations, the behavioral measures did not show a reliable difference between rotated and upright global letters, indicating that the rotation of the global stimuli did not results in an increased difficulty of the task. The fact that EEG coherence and phase locking were also not different for the attention to global rotated and global upright letters is thus not surprising. Therefore, the relation of gamma band activity and task difficulty in global attention task has to be addressed in a new study that convincingly demonstrates task difficulty effects through differences in RTs.
There is an ongoing debate about the control mechanism that is involved in shifting the attentional focus from the global level to the local level and vice versa. Clinical data and some imaging studies suggest a relative hemispheric specialization for global and local attention with a predominance of the right hemisphere for global and the left hemisphere for local attentional selection (Delis and others 1986; Robertson and others 1988; Fink and others 1997; Yamaguchi and others 2000). However, other imaging studies did not confirm these hemispheric differences and concluded that the processing within the visual cortex is not asymmetric and that possible lateralization effects may occur at later stages of processing within the parietal cortex (Kotchoubey and others 1997; Heinze and others 1998; Sasaki and others 2001; Kourtzi and others 2003). Our analysis of the spectral densities showed no lateralization effect for the gamma band and no differences in the amplitudes of induced gamma activity between local and global processing. Therefore, the increased coupling between the hemispheres for the global processing was not influenced by modulations of gamma band lateralization effects or absolute power.
In conclusion, our findings suggest that the integration of distributed local features to the global aspect of a centrally presented stimulus results in an increase in interhemispheric coupling. Thus, our results are in accord with the assumption that neural coupling within the gamma band reflects the mechanism of information exchange of different neural populations and is dynamically modulated by the selected level of integration.
|
Acknowledgments |
|---|
This work was supported by the Volkswagen-Stiftung, Deutsche Forschungsgemeinschaft and the Bundesministerium fur Bildung und Forschung.
|
References |
|---|
|
TopAbstractIntroductionMethodsResultsDiscussionReferences |
|---|
Bressler SL, Coppola R, Nakamura R. 1993. Episodic multiregional cortical coherence at multiple frequencies during visual task performance. Nature 366:153–156.[CrossRef][Medline]
Debener S, Herrmann CS, Kranczioch C, Gembris D, Engel AK. 2003. Top-down attentional processing enhances auditory evoked gamma band activity. Neuroreport 14:683–686.[CrossRef][ISI][Medline]
Delis DC, Robertson LC, Efron R. 1986. Hemispheric specialization of memory for visual hierarchical stimuli. Neuropsychologia 24:205–214.[CrossRef][ISI][Medline]
Eckhorn R, Bauer R, Jordan W, Brosch M, Kruse W, Munk M, Reitboeck HJ. 1988. Coherent oscillations: a mechanism of feature linking in the visual cortex? Multiple electrode and correlation analyses in the cat. Biol Cybern 60:121–130.[CrossRef][ISI][Medline]
Engel AK, Fries P, Singer W. 2001. Dynamic predictions: oscillations and synchrony in top-down processing. Nat Rev Neurosci 2:704–716.[CrossRef][ISI][Medline]
Engel AK, Konig P, Kreiter AK, Singer W. 1991. Interhemispheric synchronization of oscillatory neuronal responses in cat visual cortex. Science 252:1177–1179.[CrossRef][ISI][Medline]
Engel AK, Singer W. 2001. Temporal binding and the neural correlates of sensory awareness. Trends Cogn Sci 5:16–25.[CrossRef][ISI][Medline]
Fell J, Fernandez G, Klaver P, Elger CE, Fries P. 2003. Is synchronized neuronal gamma activity relevant for selective attention? Brain Res Brain Res Rev 42:265–272.[CrossRef][Medline]
Fink GR, Halligan PW, Marshall JC, Frith CD, Frackowiak RS, Dolan RJ. 1997. Neural mechanisms involved in the processing of global and local aspects of hierarchically organized visual stimuli. Brain 120(Pt 10):1779–1791.
Fries P, Reynolds JH, Rorie AE, Desimone R. 2001. Modulation of oscillatory neuronal synchronization by selective visual attention. Science 291:1560–1563.
Gilbert CD, Wiesel TN. 1989. Columnar specificity of intrinsic horizontal and corticocortical connections in cat visual cortex. J Neurosci 9:2432–2442.[Abstract]
Gray CM, Konig P, Engel AK, Singer W. 1989. Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties. Nature 338:334–337.[CrossRef][Medline]
Gruber T, Muller MM. 2005. Oscillatory brain activity dissociates between associative stimulus content in a repetition priming task in the human EEG. Cereb Cortex 15:109–116.
Gruber T, Muller MM, Keil A, Elbert T. 1999. Selective visual-spatial attention alters induced gamma band responses in the human EEG. Clin Neurophysiol 110:2074–2085.[CrossRef][ISI][Medline]
Hebb DO. 1949. The organization of behavior. New York: Wiley.
Heinze HJ, Hinrichs H, Scholz M, Burchert W, Mangun GR. 1998. Neural mechanisms of global and local processing: a combined PET and ERP study. J Cogn Neurosci 10:485–498.[Abstract]
Hubel DH, Wiesel TN. 1967. Cortical and callosal connections concerned with the vertical meridian of visual fields in the cat. J Neurophysiol 30:1561–1573.
Jarvis MR, Mitra PP. 2001. Sampling properties of the spectrum and coherency of sequences of action potentials. Neural Comput 13:717–749.
Jaskowski P, Skalska B, Verleger R. 2003. How the self controls its "automatic pilot" when processing subliminal information. J Cogn Neurosci 15:911–920.
Kaiser J, Hertrich I, Ackermann H, Mathiak K, Lutzenberger W. 2005. Hearing lips: gamma-band activity during audiovisual speech perception. Cereb Cortex 15:646–653.
Kinchla RA, Solis-Macias V, Hoffman J. 1983. Attending to different levels of structure in a visual image. Percept Psychophys 33:1–10.[ISI][Medline]
Kiper DC, Knyazeva MG, Tettoni L, Innocenti GM. 1999. Visual stimulus-dependent changes in interhemispheric EEG coherence in ferrets. J Neurophysiol 82:3082–3094.
Knyazeva MG, Kiper DC, Vildavski VY, Despland PA, Maeder-Ingvar M, Innocenti GM. 1999. Visual stimulus-dependent changes in interhemispheric EEG coherence in humans. J Neurophysiol 82:3095–3107.
Kotchoubey B, Wascher E, Verleger R. 1997. Shifting attention between global features and small details: an event-related potential study. Biol Psychol 46:25–50.[CrossRef][ISI][Medline]
Kourtzi Z, Kanwisher N. 2000. Cortical regions involved in perceiving object shape. J Neurosci 20:3310–3318.
Kourtzi Z, Tolias AS, Altmann CF, Augath M, Logothetis NK. 2003. Integration of local features into global shapes: monkey and human FMRI studies. Neuron 37:333–346.[CrossRef][ISI][Medline]
Kreiter AK, Singer W. 1996. Stimulus-dependent synchronization of neuronal responses in the visual cortex of the awake macaque monkey. J Neurosci 16:2381–2396.
Lamme VA, Spekreijse H. 1998. Neuronal synchrony does not represent texture segregation. Nature 396:362–366.[CrossRef][Medline]
Lamme VA, Super H, Spekreijse H. 1998. Feedforward, horizontal, and feedback processing in the visual cortex. Curr Opin Neurobiol 8:529–535.[CrossRef][ISI][Medline]
Malach R, Amir Y, Harel M, Grinvald A. 1993. Relationship between intrinsic connections and functional architecture revealed by optical imaging and in vivo targeted biocytin injections in primate striate cortex. Proc Natl Acad Sci USA 90:10469–10473.
Malach R, Reppas JB, Benson RR, Kwong KK, Jiang H, Kennedy WA, Ledden PJ, Brady TJ, Rosen BR, Tootell RB. 1995. Object-related activity revealed by functional magnetic resonance imaging in human occipital cortex. Proc Natl Acad Sci USA 92:8135–8139.
Martinez A, Anllo-Vento L, Sereno MI, Frank LR, Buxton RB, Dubowitz DJ, Wong EC, Hinrichs H, Heinze HJ, Hillyard SA. 1999. Involvement of striate and extrastriate visual cortical areas in spatial attention. Nat Neurosci 2:364–369.[CrossRef][ISI][Medline]
Miltner WH, Braun C, Arnold M, Witte H, Taub E. 1999. Coherence of gamma-band EEG activity as a basis for associative learning. Nature 397:434–436.[CrossRef][Medline]
Muller MM, Gruber T, Keil A. 2000. Modulation of induced gamma band activity in the human EEG by attention and visual information processing. Int J Psychophysiol 38:283–299.[CrossRef][ISI][Medline]
Navon D. 1977. Forest before trees: the precedence of global features in visual perception. Cogn Psychol 9:353–383.[CrossRef][ISI]
Palmer SE. 1999. Vision science. Cambridge, MA: MIT press.
Payne BR. 1994. Neuronal interactions in cat visual cortex mediated by the corpus callosum. Behav Brain Res 64:55–64.[CrossRef][ISI][Medline]
Robertson LC, Lamb MR, Knight RT. 1988. Effects of lesions of temporal-parietal junction on perceptual and attentional processing in humans. J Neurosci 8:3757–3769.[Abstract]
Roelfsema PR, Lamme VA, Spekreijse H. 2004. Synchrony and covariation of firing rates in the primary visual cortex during contour grouping. Nat Neurosci 7:982–991.[CrossRef][ISI][Medline]
Rose M, Büchel C. 2005 Neural coupling binds visual tokens to moving stimuli. J Neurosci 25:10101–10104.
Sasaki Y, Hadjikhani N, Fischl B, Liu AK, Marrett S, Dale AM, Tootell RB. 2001. Local and global attention are mapped retinotopically in human occipital cortex. Proc Natl Acad Sci USA 98:2077–2082.
Schoffelen JM, Oostenveld R, Fries P. 2005. Neuronal coherence as a mechanism of effective corticospinal interaction. Science 308:111–113.
Struber D, Basar-Eroglu C, Hoff E, Stadler M. 2000. Reversal-rate dependent differences in the EEG gamma-band during multistable visual perception. Int J Psychophysiol 38:243–252.[CrossRef][ISI][Medline]
Tallon-Baudry C, Bertrand O. 1999. Oscillatory gamma activity in humans and its role in object representation. Trends Cogn Sci 3:151–162.[CrossRef][ISI][Medline]
Tallon-Baudry C, Bertrand O, Delpuech C, Permier J. 1997. Oscillatory gamma-band (30–70 Hz) activity induced by a visual search task in humans. J Neurosci 17:722–734.
Tallon-Baudry C, Bertrand O, Fischer C. 2001. Oscillatory synchrony between human extrastriate areas during visual short-term memory maintenance. J Neurosci 21:RC177.
Taylor K, Mandon S, Freiwald WA, Kreiter AK. 2005. Coherent oscillatory activity in monkey area v4 predicts successful allocation of attention. Cereb Cortex 15:1424–1437.
Thiele A, Stoner G. 2003. Neuronal synchrony does not correlate with motion coherence in cortical area MT. Nature 421:366–370.[CrossRef][Medline]
Tiitinen H, Sinkkonen J, Reinikainen K, Alho K, Lavikainen J, Naatanen R. 1993. Selective attention enhances the auditory 40-Hz transient response in humans. Nature 364:59–60.[CrossRef][Medline]
Tootell RB, Hadjikhani N, Hall EK, Marrett S, Vanduffel W, Vaughan JT, Dale AM. 1998. The retinotopy of visual spatial attention. Neuron 21:1409–1422.[CrossRef][ISI][Medline]
Varela F, Lachaux JP, Rodriguez E, Martinerie J. 2001. The brainweb: phase synchronization and large-scale integration. Nat Rev Neurosci 2:229–239.[CrossRef][ISI][Medline]
von der Malsburg C. 1994. The correlation theory of brain function. In: Domany E, van Hemmen JL and Schulten K, editors. Models of neural networks II. Berlin: Springer. p 95–119.
Yamaguchi S, Yamagata S, Kobayashi S. 2000. Cerebral asymmetry of the "top-down" allocation of attention to global and local features. J Neurosci 20:RC72.
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  V. A. Makarov, K. E. Schmidt, N. P. Castellanos, L. Lopez-Aguado, and G. M. Innocenti Stimulus-Dependent Interaction between the Visual Areas 17 and 18 of the 2 Hemispheres of the Ferret (Mustela putorius) Cereb Cortex, August 1, 2008; 18(8): 1951 - 1960. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. M. Doesburg, A. B. Roggeveen, K. Kitajo, and L. M. Ward Large-Scale Gamma-Band Phase Synchronization and Selective Attention Cereb Cortex, February 1, 2008; 18(2): 386 - 396. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||