Attention and Interhemispheric Transfer: A Behavioral and f MRI Study B. Weber1, V. Treyer1, N. Oberholzer1, T. Jaermann2, P. Boesiger2, P. Brugger1, M. Regard1, A. Buck1, S. Savazzi3, and C. A. Marzi3
Abstract & When both detections and responses to visual stimuli are performed within one and the same hemisphere, manual reaction times (RTs) are faster than when the two operations are carried out in different hemispheres. A widely accepted explanation for this difference is that it reflects the time lost in callosal transmission. Interhemispheric transfer time can be estimated by subtracting RTs for uncrossed from RTs for crossed responses (crossed uncrossed difference, or CUD). In the present study, we wanted to ascertain the role of spatial attention in affecting the CUD and to chart the brain areas whose activity is related to these attentional effects on interhemispheric transfer. To accomplish this, we varied the proportion of crossed and uncrossed trials in different blocks. With this paradigm subjects are likely to focus attention either on the hemifield contralateral to the responding hand (blocks with 80% crossed trials) or on the ipsilateral hemifield (blocks
INTRODUCTION Since Poffenberger’s seminal article published in 1912 (Poffenberger, 1912), many studies have been carried out to estimate the time needed for interhemispheric transfer (IT) of visuomotor information with this simple behavioral method (for reviews, see Zaidel & Iacoboni, 2003a; Marzi, 1999; Marzi, Bisiacchi, & Nicoletti, 1991). The Poffenberger paradigm consists of a simple reaction time (RT) task in which visual stimuli are tachistoscopically presented to the right or left hemifield. Response is performed by pressing a key with either the hand ipsilateral or contralateral to the stimulated hemifield. Poffenberger was the first to show that crossed visuomotor responses are on average slower than uncrossed responses. In normal subjects, this so-called crossed uncrossed difference (CUD) is around 4 msec, a value that corresponds to estimates of callosal conduction time obtained with transcranial magnetic stimulation (Hanajima et al., 2001). As expected, the CUD is drastically increased in split-brain patients and in patients with agenesis of the corpus callosum (for reviews, see Iaco-
1 University Hospital Zurich, 2 University and Federal Institute of Technology, Zurich, Switzerland, 3Universita’ di Verona, Italy
D 2005 Massachusetts Institute of Technology
with 80% uncrossed trials). We found an inverse correlation between the proportion of crossed trials in a block and the CUD and this effect can be attributed to spatial attention. As to the imaging results, we found that in the crossed minus uncrossed subtraction, an operation that highlights the neural processes underlying interhemispheric transfer, there was an activation of the genu of the corpus callosum as well as of a series of cortical areas. In a further commonality analysis, we assessed those areas which were activated specifically during focusing of attention onto one hemifield either contra- or ipsilateral to the responding hand. We found an activation of a number of cortical and subcortical areas, notably, parietal area BA 7 and the superior colliculi. We believe that the main thrust of the present study is to have teased apart areas important in interhemispheric transmission from those involved in spatial attention. &
boni & Zaidel, 2003; Lassonde, Sauerwein, & Lepore, 2003; Berlucchi, Aglioti, Marzi, & Tassinari, 1995; Marzi, Bisiacchi, et al., 1991). The effect of the lack of the callosum is consistent with the hypothesis that in normal subjects it is the longer callosal route that is responsible for the slower RT in the crossed conditions. This ‘‘structural’’ hypothesis is challenged by a ‘‘dynamic’’ view according to which the CUD can be explained by a stronger activation of the directly stimulated hemisphere with a resultant more forceful activation of the ipsilateral motor cortex, hence, a faster RT (Kinsbourne, 2003). Another open question is the effect of attention on the CUD; some attempts have been made to assess the effect of attentional manipulations on the CUD but the emerging overall picture is unclear (for a review, see Zaidel & Iacoboni, 2003b). In their meta-analysis, Marzi, Bisiacchi, et al. (1991) found no difference between the CUD as estimated with a blocked paradigm in which blocks of trials were either crossed or uncrossed versus a randomized paradigm in which the hemifield of stimulus appearance with respect to the responding hand was unpredictable. At first sight, this might appear as evidence against an attentional modulation of the CUD, however, one might reason that in both conditions the
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attentional bias toward one or the other hemifield is in fact minimized, albeit for different reasons. In the blocked paradigm, the hemifield of stimulus appearance is totally predictable and thus likely to get the maximum attentional deployment, be it ipsilateral or contralateral with respect to the responding hand. In the randomized paradigm, the hemifield of stimulus presentation is unpredictable and the subject’s attention is thought to be spread over the whole visual field with no obvious reason to be biased toward one side. Therefore, neither of the above paradigms can provide a definitive answer to the question of whether attentional biases have an effect on the CUD. To address this issue, we developed a simple modification of the classical Poffenberger paradigm in which the ratio of crossed versus uncrossed stimulus–response combinations was varied across different trial blocks. In one condition 80% of trials were crossed, in another 80% of trials were uncrossed, and in a third condition 50% of trials were crossed and 50% uncrossed. In the 80% crossed condition, subjects are likely to focus their attention onto the hemifield contralateral to the responding hand, and the CUD should decrease. In contrast, in the 80% uncrossed condition they are likely to focus their attention onto the ipsilateral hemifield leading to an increase in the CUD. Finally, the 50% condition is a neutral condition in which the CUD should represent an estimate of IT free from attentional biases. During behavioral performance we used functional magnetic resonance imaging (fMRI) to assess which cortical areas and what parts of the corpus callosum are selectively involved in IT trying to disentangle transmission from attention effects.
RESULTS Behavior RTs were statistically analyzed using a four-way analysis of variance (ANOVA) with three within-subject factors (hand, visual hemifield, crossed–uncrossed condition) and one between-subjects factor (group: performance of the task inside the scanner vs. outside the scanner; see Methods). The only significant main effect was group [F(1,28) = 5.67, p < .05] with subjects performing in the scanner responding on average more slowly than those outside (273.7 vs. 238.0 msec). The Hand Visual field interaction, which is an index of the CUD, was significant [F(1,28) = 8.59, p < .05] with the crossed conditions slower than the uncrossed conditions (257.3 vs. 254.6 msec) and a CUD of 2.7 msec. It is important to point out that the CUD was not reliably different in the two groups of subjects (see Table 1 for the data of the two groups); this means that performing in the scanner slowed down overall RT but did not affect the CUD. The important finding was the significance of the
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Table 1. Mean CUD in the Three Crossing Conditions for the Two Groups of Subjects 80% crossed
50%–50%
80% uncrossed
Outside
0.509
2.446
6.143
Inside
4.508
6.289
6.861
second-order Hand Visual field Condition interaction [F(2,56) = 4.04, p < .05] with subjects showing a smaller and inverted CUD in the predominantly crossed condition ( 2.5 msec) with respect to the neutral (4.4 msec) and the predominantly uncrossed condition (6.5 msec) (see Figure 1). Functional Imaging Main Effect of Hand and Hemifield Table 2 shows the cerebral areas that yielded a significant BOLD effect following contrasts related to hand and visual hemifield. The subtraction left minus right hand showed a significant activation of the right precentral gyrus (BA 4), insular cortex, putamen, and cingulate cortex (BA 24), as well as the left cerebellar cortex. Likewise, the subtraction right minus left hand yielded a reliable BOLD effect in the left precentral gyrus (BA 4), putamen, thalamus, cingulate cortex, and right cerebellum. The subtraction left visual field minus right visual field showed an effect in the right lingual gyrus (BA 18) and the middle temporal gyrus (BA 21/37). The opposite contrast yielded an effect in the left lingual gyrus (BA 18) and middle occipital gyrus (BA 19). These effects confirmed that, as expected, stimulus detection and manual response concerned contralateral visual and motor areas, respectively. It is interesting to point out that the areas revealed by the subtractions related to hand and hemifield are in keeping with those highlighted by similar subtractions in Tettamanti et al.’s (2002) study. An intriguing observation is that our brief and lateralized stimuli consistently showed an effect in BA 18 and 19 rather than 17. Crossed minus Uncrossed and Uncrossed minus Crossed Subtractions One important characteristic of our paradigm was that in the mainly crossed or uncrossed conditions, the side of stimulus presentation was predictable (80% probability) and therefore the optimal strategy of the subjects was to attend either to the hemifield contralateral or ipsilateral with respect to the performing hand depending upon the type of block. Only in the 50% crossed condition would the optimal strategy be to distribute attention evenly across the entire visual field. Therefore, in the present paradigm, callosal load and attentional factors were intermixed. One way to disentangle the two factors
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genu of the corpus callosum. Table 3 indicates that several other areas yielded an effect with a lower Z score (see Discussion). It is important to note that this subtraction revealed an effect in the corpus callosum as well as in other white matter areas.
Uncrossed minus Crossed Subtraction
Figure 1. The CUD as a function of the different proportion of crossed hand–hemifield combinations.
is to compare areas activated in the two opposite subtractions concerned with crossing conditions. The crossed minus uncrossed subtraction should yield those areas that are selectively involved in IT. In contrast, the inverse uncrossed minus crossed subtraction should yield only areas involved in intrahemispheric processing. Crossed minus Uncrossed Subtraction From Table 3 and Figure 2A, one can gather that there were three areas showing a BOLD effect with a Z score above 3 and p < .001 (uncorrected), namely, the gray and white matter of the right cuneus (BA 31/19), the white matter of the right frontal lobe, and the right
Two cortical areas yielded a BOLD effect with Z > 3 and p < .001 (uncorrected), namely, the right cingulate gyrus (BA 24) and the left superior temporal gyrus (BA 38). Importantly, this subtraction did not yield any callosal effect (see Table 4 and Figure 2B). As was the case in the preceding subtraction, some other areas also showed a reliable effect albeit at a lower Z score (see Discussion).
Attention-related Analysis To select out the BOLD effects more directly related to attention, we carried out an analysis by contrasting the two conditions in which the participants’ attention is focused onto one side (i.e., the 80% crossed and the 80% uncrossed conditions), with the condition in which attention is diffuse to the whole field (i.e., the 50% condition). Table 5a shows the areas yielding a BOLD effect at Z > 3, both in the 80% crossed minus 50% and in the 80% uncrossed minus 50% analysis. These areas include
Table 2. Subtractions Related to Hemifield and Hand Brain Area Contrast LH–RH
RH–LH
LVF–RVF
Anatomical
BA
MNI Coordinates [x y z]
Z
p
Right precentral gyrus
4
40
20
44
5.02
< .001
Right insular cortex/putamen
–
30
0
0
3.79
< .001
Left cerebellar cortex
–
22
70
16
3.39
< .001
Right cingulate cortex
24
10
0
40
3.39
< .001
Right cerebellar cortex
–
8
58
20
5.11
< .001
Left precentral gyrus
4
38
16
56
4.83
< .001
Left putamen
–
26
6
4
3.38
< .001
Left thalamus
–
14
20
0
3.85
< .001
Left cingulate cortex
24
4
4
44
3.69
< .001
Right lingual gyrus
18
20
80
20
5.07
< .001
21/37
48
64
0
4.00
< .001
Left lingual gyrus
18
30
66
16
4.37
< .001
Left middle occipital gyrus
19
46
76
0
3.75
< .001
Right middle temporal gyrus RVF–LVF
Statistics
Abbreviations: LH = left hand; RH = right hand; LVF = left visual field; RVF = right visual field; BA = Brodmann’s area; MNI = Montreal Neurological Institute (spatial normalization template used in SPM99). p < .001 (uncorrected).
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Table 3. Crossed
Uncrossed Subtraction Brain Area
Statistics
Anatomical
BA
MNI Coordinates [x y z]
Z
p
Right precuneus/cuneus/wm
31/19
18
54
24
3.70
< .001
Right frontal wm/corpus callosum
9
20
16
32
3.39
< .001
Right genu of corpus callosum
–
10
26
4
3.32
< .001
Left precentral gyrus
6
14
18
72
2.85
< .01
Right superior frontal gyrus
9/10
20
56
20
2.38
< .01
Right inferior frontal gyrus
47
62
18
4
2.26
< .05
Right superior parietal lobule
7
20
54
68
2.23
< .05
Right middle frontal gyrus
6
18
4
64
2.21
< .05
Left middle temporal gyrus
21
52
48
4
2.13
< .05
Right globus pallidum
–
20
12
0
2.10
< .05
Left cingulate gyrus
24
10
4
44
2.10
< .05
Right superior frontal gyrus
8
18
46
48
2.04
< .05
Right middle occipital gyrus
18
32
78
16
2.03
< .05
Abbreviations: BA = Brodmann’s area; MNI = Montreal Neurological Institute (spatial normalization template used in SPM99); wm = white matter. Areas activated at a Z score higher than 3 and p < .001 (uncorrected) are in bold.
the cerebellar culmen; subcortical centers, notably the superior colliculi and the putamen; and BA 7, 8, 39, and 40. These are areas that show an effect during attention to one hemifield whether contra- or ipsilateral to the responding hand. Table 5b shows areas with a common BOLD effect in the 50% condition minus the two 80% (crossed and uncrossed) conditions. Reliable effects were found in BA 6, 8/9, 10, in the parahippocampal gyrus, and in the head of the caudate.
DISCUSSION Behavioral Results The aim of the present work was to study the pathways subserving IT of visuomotor information and the influence of spatial attention. This was done by using a modified Poffenberger paradigm in which the ratio of crossed/uncrossed trials varied in different blocks. The novel behavioral finding was that the CUD was inversely correlated with the proportion of crossed trials, with negative values in the condition in which 80% of trials were crossed and positive values in the reverse condition. It is important to point out that in the 50% crossed–uncrossed condition, the CUD was positive, thus confirming previous results showing that this measure is a consistent and valid indication of IT (Zaidel & Iacoboni 2003a, 2003b; Iacoboni & Zaidel, 2000; Marzi, Bisiacchi, et al., 1991). The negative association between CUD and proportion of crossed trials is clearly the result
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of attentional factors that add to the callosal transfer effect. It is well known (Tassinari, Aglioti, Chelazzi, Marzi, & Berlucchi, 1987; Posner, 1980) that when subjects expect a stimulus from a given hemifield they tend to covertly allocate spatial attention to that hemifield. Attending to the hemifield ipsilateral to the performing hand speeds up RT in the uncrossed conditions and the CUD increases. In contrast, attending to the contralateral hemifield speeds up RT in the crossed conditions and the CUD decreases. Finally, the neutral condition is an unbiased measure of the CUD free from attentional effects. The result of an attentional influence on the CUD does not diminish the value of this measure in measuring IT time; however, it reinforces the idea that to be a valid measure of IT time, the Poffenberger paradigm must be kept free from lateral attentional biases. Imaging Results As mentioned above, the aim of the present study was to tease apart areas that are involved in the IT of visuomotor signals from those involved in spatial attentional biases. An important means to assess the areas more specifically involved in IT was represented by the crossed minus uncrossed subtraction that revealed a reliable BOLD effect in the callosal genu and in various cortical areas, such as BA 31 and 19 in the cuneus and BA 9 in the frontal lobe. These effects are very likely to involve areas that are more active during
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Figure 2. fMRI activations for the comparison crossed minus uncrossed (A) and uncrossed minus crossed (B) superimposed on a coronal slice of a spatially normalized T1-weighted anatomical mean image. The corresponding stereotactic y-coordinates (mm) are given for each slice. (A) Areas passing Z > 3 ( p < .001) are localized in the white and gray matter of the right cuneus (x = 18, y = 54, z = 24), the white matter of the frontal lobe (x = 20, y = 16, z = 32), and the right genu of the corpus callosum (x = 10, y = 26, z = 4). (B) Areas passing Z > 3 ( p < .001) were found in the right cingulate cortex (x = 4, y = 8, z = 28) and the left superior temporal gyrus (x = 52, y = 16, z = 16).
inter- than during intrahemispheric stimulus processing. In keeping with this notion, the effect found in the genu confirms Tettamanti et al.’s (2002) results obtained using fMRI and a Poffenberger paradigm with blocked conditions of crossed or uncrossed trials. As mentioned above, in addition to the callosum, a number of other areas showed a BOLD effect during the crossed conditions and this reinforces the idea of multiple sites of IT (see below). Importantly, among those areas (Table 3), is the right superior parietal lobule (BA 7) whose activation has been found to show a high correlation with the CUD in a recent eventrelated fMRI study (Iacoboni & Zaidel, 2004). This area was also found to be selectively involved in IT both in Marzi, Perani, et al.’s (1999) PET study and in Tettamanti et al.’s fMRI study. Furthermore, BA 7 has shown a significant effect in the commonality analysis carried out in the present experiment (see Table 5a and below for a discussion of its possible attentional role). Importantly, it has been recently reported that a lesion of the right parietal cortex results in an impairment of IT in the Poffenberger paradigm (Marzi, Bongiovanni, Miniussi, & Smania, 2003). The parietal cortex has numerous callosal connections and is endowed with visuospatial and premotor properties, therefore, its involvement in IT of visuomotor information is far from surprising. An involvement of BA 7 in the transfer conditions fits in well with recent results by Peru, Beltramello, Moro, Sattibaldi, and Berlucchi (2003) who found a marked and persistent prolongation of the CUD in the Poffenberger paradigm following a lesion of the posterior body of the corpus callosum in a patient with closed head injury. This part of the corpus callosum is thought to contain fibers intercon-
necting, among others, posterior parietal areas such as BA 7 (de Lacoste, Kirkpatrick, & Ross, 1985). Another area showing a reliable effect in the crossed condition was the left precentral gyrus (BA 6) conceivably belonging to the supplementary motor area (SMA). This area has long been considered as playing a special role in the internal generation of complex movements (Picard & Strick, 2001). However, recent functional imaging studies in humans as well as in monkeys have shown that the SMA is activated during simple voluntary movements in response to visual stimuli (Picard & Strick, 2003). Our present results suggest that this area may be involved in IT of visuomotor information in the Poffenberger paradigm. A similar possibility applies to prefrontal areas such as BA 9/10, which showed a selective involvement in the crossed conditions. In contrast to the crossed minus uncrossed, the reverse subtraction uncrossed minus crossed yielded an activation of the cingulate gyrus (BA 24) and of the superior temporal gyrus (BA 38) at Z > 3. These activations index areas that are more active during intrarather than interhemispheric processing as witnessed by the observation that in this subtraction there was no callosal activation. The cingulate gyrus has been implicated in creating an attentional set (Banich et al., 2000) and is involved in premotor operations (Paus, 2001) and therefore its activation comes as no surprise. By the same token, the right superior temporal cortex has been invoked to play an important role in spatial awareness as witnessed by the effects of its lesion in neglect patients (Karnath, Ferber, & Himmelbach, 2001). The nature of the involvement of the left superior temporal cortex found in the present study deserves further scrutiny.
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Table 4. Uncrossed
Crossed Substraction Brain Area
Statistics
Anatomical
BA
MNI Coordinates [x y z]
Z
p
Right cingulate gyrus
24
4
8
28
3.37
< .001
Left superior temporal gyrus
38
52
16
16
3.25
< .001
Right inferior frontal gyrus
47
38
24
16
2.92
< .01
Left cerebellum
–
4
82
20
2.79
< .01
Right thalamus
–
4
2
8
2.76
< .01
Left cerebellum culmen
–
6
60
4
2.76
< .01
Right middle frontal gyrus
8
40
56
16
2.75
< .01
Left inferior frontal gyrus
44
46
38
8
2.57
< .01
Right postcentral gyrus
2
56
28
52
2.36
< .01
Left middle frontal gyrus
9
40
26
44
2.26
< .05
Right inferior parietal lobule
40
38
44
56
2.17
< .05
Left globus pallidum
–
20
4
8
2.15
< .05
Right middle frontal gyrus/wm
–
44
22
24
2.11
< .05
Left supramarginal gyrus
40
58
50
36
2.06
< .05
Abbreviations: BA = Brodmann’s area; MNI = Montreal Neurological Institute (spatial normalization template used in SPM99); wm = white matter. Area activated at a Z score higher than 3 and p < .001 (uncorrected) are in bold.
Finally, the commonality analysis has provided information on those areas that are specifically involved in attentional focusing to one hemifield either contra- or ipsilateral to the responding hand. It is important to point out that among these areas were subcortical centers such as the superior colliculi and the putamen, in addition to BA 7, 8, 39, and 40, and the cerebellum. Particularly important, in our opinion, is the collicular effect that confirms in humans recent results obtained at the single cell level in the monkey (Ignashchenkova, Dicke, Haarmeier, & Thier, 2004). The authors postulate the existence of collicular neurons specifically involved in covert attentional orienting. By the same token, the involvement of BA 8 relates well to recent experiments in the monkey showing that a substantial increase in the deployment of covert spatial attention could be obtained by microstimulation of FEF sites (Moore & Fallah, 2004). As to the other activated areas, the putamen has been also implicated in attention-demanding tasks and there is abundant evidence, as mentioned above, of an important attentional role of BA 7 (see Coull, Walsh, Frith, & Nobre, 2003). Finally, both BA 39 and BA 40 have been shown to play a role in attentional tasks (Feinstein, Goldin, Stein, Brown, & Paulus, 2002) and an attentional role not necessarily dependent on motor factors has been attributed to the cerebellum (Gottwald, Mihajlovic, Wilde, & Mehdorn, 2003). In sum, all areas activated in the commonality analysis share a role in attention.
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More problematic is the discussion of the results of the inverse commonality analysis (Table 5b) which depicts areas selectively involved the 50% crossed– uncrossed condition in comparison to the areas involved in the 80% crossed and 80% uncrossed conditions. A tentative explanation of the pattern of areas showing an effect in this condition is that they are part of a system subserving vigilance and sustained attention in general. This might certainly be the case of the parahippocampal gyrus as shown by the study of Lawrence, Ross, Hoffmann, Garavan, and Stein (2003). A role in executive functions has been attributed recently to BA 6, 9, and 10 (Sylvester et al., 2003) and an involvement of the caudate in attentional performance has been documented (Sowell et al., 2003). Finally, as mentioned above, BA 8 is undoubtedly an area involved in overt and covert visual attentional shifts (Moore & Fallah, 2004). In sum, again, all activated areas play a role in some aspects of vigilance and sustained attention. Site of Callosal Transfer If one accepts the assumption that the CUD is related to IT, an important question concerns the callosal area responsible. The evidence gathered so far is controversial: A host of neuropsychological (Berlucchi et al., 1995), electrophysiological (Thut et al., 1999; Rugg, Lines, & Milner, 1984; Milner & Lines, 1982) as well as functional neuroimaging (Tettamanti et al., 2002; Marzi,
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Table 5. Commonality Analysis a. Commonalities [80 crossed
50 crossed] and [20 crossed
Anatomical
50 crossed]
BA
Right/left cerebellum culmen
MNI Coordinates [x y z]
Z80
50
Z20
50
4
54
20
5.14
3.32
39
38
76
24
3.35
4.07
8
30
22
56
2.52
4.50
28
12
12
2.59
4.40
Midbrain
4
8
12
3.46
3.28
Superior colliculi
2
34
12
3.22
3.42
40
38
40
40
3.08
3.01
7
10
62
64
2.70
3.36
Right middle temporal gyrus Right middle frontal gyrus Right putamen
Left inferior parietal lobule Right precuneus/superior parietal lobule b. Commonalities [50 crossed
80 crossed] and [50 crossed
20 crossed]
Brain Area Anatomical Right middle frontal gyrus
Statistics
BA
MNI Coordinates [x y z]
Z50
80
Z50
20
6
6
6
72
2.50
4.05
Right superior frontal gyrus (wm)
10
12
60
4
2.54
3.81
Left middle frontal gyrus
8/9
6
48
40
3.08
2.79
Left parahippocampal gyrus (wm)
30
24
24
2.24
3.58
Left head of caudate
10
14
0
3.20
2.46
30
58
0
2.92
2.14
Left superior frontal gyrus
10
Abbreviations: BA = Brodmann’s area; MNI = Montreal Neurological Institute (spatial normalization template used in SPM99); wm = white matter. Area activated at p < .03 in both contrasts, namely, commonalities p < .001 (.032).
Perani, et al., 1999) data suggest that visuomotor IT occurs mainly at a premotor level. On the other hand, there are studies showing that the CUD is normal in subjects with anterior callosal lesions, but markedly increased in those with posterior callosal lesions (Corballis, Corballis, & Fabri, 2004; Peru et al., 2003; Iacoboni, Ptito, Weekes, & Zaidel, 2000; Reuter-Lorenz, Nozawa, Gazzaniga, & Hughes, 1995). Finally, a recent study by Tomaiuolo, Nocentini, Grammaldo, and Caltagirone (2001) assessed the CUD in a patient who had a lesion of the corpus callosum that spared the splenium and rostrum and found that this patient performed similarly to completely callosotomized patients with an overall CUD of 25.5 msec. This suggests that neither the rostrum nor the splenium of the corpus callosum are sufficient for a normal CUD. In light of the above controversy, one is tempted to conclude that IT occurs at several sites in a horse-race fashion (Iacoboni & Zaidel, 1995, 2004; Thut et al., 1999; Bisiacchi et al., 1994; Clarke & Zaidel, 1989) and that the ‘‘winning site’’ depends on several variables. One might also speculate that the functional meaning of IT at various callosal sites is different: The posterior areas might transfer sensory-based information, whereas
the functional meaning of callosal transmission at a premotor level might be twofold: either to transfer visuomotor information on a trial-by-trial basis as hypothesized originally by Poffenberger or to prepare both hemispheres to manually respond to lateralized visual stimuli with a tonic callosal activation. In keeping with the latter possibility, Stancak, Lucking, and KristevaFeige (2000) found a positive correlation between the size of anterior callosal portions and the amplitude of the premovement electroencephalographic potential recorded ipsilaterally to the responding hand (Stancak, Lucking, et al., 2000). In another recent imaging study, Stancak, Cohen, Seidler, Duong, and Kim (2003) found that the size of the anterior portion and trunk of the corpus callosum correlated with the activity of the SMA and cingulate cortical areas during temporally complex bimanual movements. In the present study, not only the anterior callosum but also the SMA and the cingulate cortex were activated during IT. It is possible that, as mentioned above, IT occurs at several sites in a horserace fashion as suggested by the various cortical areas that are activated during IT but that a direct callosal activation is visible with fMRI only at anterior sites because of the presence of many small unmyelinated
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fibers that may more easily yield BOLD signals than myelinated fibers (see below).
The Problem of White Matter Activation The present study, together with its predecessor (Tettamanti et al., 2002), suggests that white matter fMRI activation has a functional basis that can provide important clues on cerebral connectivity. It is known that central nerve fibers require glucose to produce and propagate action potentials (Aiello & Bach-y-Rita, 2000; Fern, Davis, Waxman, & Ransom, 1998) and that their glucose metabolism drops significantly from the awake to the anesthetized state (e.g., Sokoloff et al., 1977). Using quantitative FDG-autoradiography in the rat, a strong correlation has been found between the applied frequency of intracortical electrostimulation and glucose consumption in the stimulated and contralateral homotopic cortex as well as in the connecting fibers of the corpus callosum (Weber, Fouad, Burger, & Buck, 2002). Thus, it can be assumed that changes in metabolism and possibly of blood flow reflect changes in electrical fiber activity. To our knowledge, white matter BOLD signal changes have never been explicitly investigated. Logothetis, Pauls, Augath, Trinath, and Oeltermann (2001) demonstrated that the BOLD signal is more closely related to the neuron’s input (as measured by local field potentials) than to its output (as measured by action potentials). Because white matter tracts only convey action potentials, the electrophysiological basis of changes in oxygenation, blood flow, and glucose metabolism in fibers still needs to be established. The blood supply in white matter seems equally well correlated to blood flow as in the cortex as demonstrated by Klein, Kuschinsky, Schrock, and Vetterlein (1986), who measured the relationship between blood flow, glucose metabolism, and capillary density in the rat. In animals (Innocenti, 1986) and humans (Aboitiz, Scheibel, Fisher, & Zaidel, 1992a, 1992b), the adult corpus callosum consists of unmyelinated and myelinated fibers. The ratio between these fiber types is not known precisely and results vary from study to study; however, there are indications that the anterior part of the callosum has a high density of small fibers, some of which are unmyelinated (Aboitiz et al., 1992a). Because the bulk of the brain’s energy demand is due to maintaining the ion gradients across membranes by active sodium/potassium pumps (Mata et al., 1980), one would assume that unmyelinated fibers require more energy than myelinated fibers and this would fit with Tettamanti et al.’s (2002) and with the present observations of a selective activation of the anterior portion of the callosum. However, the relationship between the presence of myelin and metabolism is still unclear (Aiello & Bach-y-Rita, 2000), partly because the concentration of sodium channels at the nodes of Ranvier in myelinated axons is very high.
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It is important to note that the signal changes observed in white matter are considerably smaller than those in cortical gray matter. Small changes in fiber activity might not therefore be detectable using noninvasive imaging methods. Thus, it is for further research to ascertain whether the monitoring of fiber activity with noninvasive techniques will prove useful to supplement analyses of connectivity that usually involve correlational approaches (Buchel & Friston, 1997; McIntosh & Gonzalez Lima, 1994; Horwitz, Soncrant, & Haxby, 1992).
METHODS Subjects Ten healthy right-handed subjects (6 men, 4 women) participated in the fMRI experiment (mean age 24.9 ± 2.0 years). An additional group of 20 (mean age 30.5 ± 5.9 years; 10 men) healthy right-handed subjects took part in the separate behavioral experiment which was conducted to make sure that performing the Poffenberger paradigm inside the scanner yielded similar results as outside. Behavioral Paradigm Inside the Scanner Visual stimuli were projected onto a semi-opaque screen using a projector connected to a PC. The refresh rate was 60 Hz at a resolution of 1024 768 pixels. Stimuli consisted of small white squares (18 18 visual angle) on a black background and were presented for 50 msec at an eccentricity of 78 along the horizontal meridian. The interstimulus interval was 1400 ± 400 msec. Subjects were asked to fixate a cross in the center of the screen and to press a button (fORP, MR-compatible response pad) with the index finger as quickly as possible after the onset of a stimulus. The experiment consisted of 7 conditions with a duration of 33 sec each: (1) 20% of the stimuli were presented in the right visual field, 80% in the left, subjects were instructed to respond with their right hand; (2) 50% of the stimuli were presented in the right visual field, 50% in the left, right-hand response; (3) 80% of the stimuli were presented in the right visual field, 20% in the left, right-hand response; (4, 5, 6) same as 1, 2, and 3, but subjects were instructed to respond with the left hand; (7) subjects were asked to fixate the cross in the center of the screen but no stimuli were presented, nor was a manual response required. Instructions on which hand to use were written on the screen for 2 sec at the beginning of each block. Each condition consisted of 20 stimuli and was repeated 4 times in a pseudorandom fashion, avoiding two similar consecutive conditions. Conditions 1 and 6 included a total of 80% crossed combinations, Conditions 2 and 5 included 50% crossed
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combinations, and Conditions 3 and 4 included 20% crossed combinations. Condition 7 was also repeated 4 times. The sequence of right–left hemifield presentations within a condition was randomized with the constraint of the planned percent of crossed and uncrossed trials. Outside the Scanner Subjects sat in front of the monitor of a laptop computer with their head restrained. The stimulation parameters were identical to those used in the fMRI experiment. The subjects’ CUD was measured using the above described paradigm as well as using a more classical design in which they were instructed to respond with either their right or left index finger to a set of 200 stimuli presented in two separate blocks using the right or left hand on a given block and with randomized hemifield presentations. The order of the three conditions, namely, one similar to that employed inside the scanner with different proportion of crossed–uncrossed combinations, one with left-hand blocked trials, and one with right-hand blocked trials, was balanced across subjects. In both conditions of testing (inside or outside the scanner), RTs shorter or longer than two standard deviations from the mean were discarded. Functional Imaging Imaging was performed using a 3-T Intera whole body system (Philips Medical Systems, Best, the Netherlands) equipped with 30 mT/m, 150 mT/m/msec gradient coils and an eight-element receive head coil array (MRI Devices, Waukesha, USA). Functional T2*-weighted images were obtained using a parallel SENSE acquisition (flip angle 828, TE 35 msec, 96 96 matrix, reconstructed as 128 128). Twenty-five axial slices were acquired every 3 sec with an in-plane resolution of 2.25 mm and a slice thickness of 4 mm. The subject’s head was restrained with Velcro straps and foam pads. A colocalized anatomical T1-weighted image was acquired after the experiments using a spin-echo sequence (352 282 matrix, reconstructed as 512 512). Image Processing and Statistical Analysis Image processing and statistical analysis were performed using SPM99 (Friston et al., 1995). All functional images were aligned to the first volume and a mean image was computed on the basis of all realigned images. This mean image was spatially normalized into stereotactic space using an EPI template. The normalized data were smoothed with an 8-mm isotropic gaussian kernel. Group statistics. Data analyses were performed by modeling the seven conditions as stimulus functions (box car function convolved with a hemodynamic re-
sponse function) applying the general linear model. Global differences in the signal were cancelled out using proportional scaling. Contrast images of each subject were then entered in a secondary level random effect analysis. The following comparisons were analyzed: (A) Hand effects: right hand minus left hand (i.e., Conditions 1/2/3 4/5/6) and vice-versa. (B) Visual field effects: right visual field minus left visual field (i.e., Conditions 1/4 3/6) and vice-versa. (C) Transfer/attention effects: 80% crossed minus 80 % uncrossed (i.e., Conditions 1/6 3/4) and vice-versa. The inverse contrasts of A, B, and C yield identical activation patterns except for the reversal in sign. (D) Attention effects: 80% crossed minus 50% crossed (Conditions 1/6 2/5) and 80% uncrossed minus 50% crossed (Conditions 3/4 2/5). On the group level, the two resulting activation patterns ( p < .03) were then searched for coactivated areas. This was conducted by transforming the contrast images to binary images and adding them. Common activations are indicated by values of 2. The same was done for the opposite contrasts (Conditions 2/5 1/6 and 2/5 3/4).
Acknowledgments We thank H. A. Buchtel for his precious help in improving the English and M. Funk for the help with the behavioral pilot experiments. Reprint requests should be sent to Carlo A. Marzi, Dipartimento di Scienze Neurologiche e della Visione, Sezione di Fisiologia, Universita’ di Verona, 8 Strada Le Grazie, 37134 Verona, Italy, or via e-mail:
[email protected]. The data reported in this experiment have been deposited in the fMRI Data Center (www.fmridc.org). The accession number is 2-2004-117HP.
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