Cerebral Cortex Advance Access originally published online on April 29, 2008
Cerebral Cortex 2009 19(1):1-12; doi:10.1093/cercor/bhn067
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Feature Article |
The Human Dorsal Action Control System Develops in the Absence of Vision
1 Department of Experimental and Biological Psychology, 2 Department of Neuroradiology, Philipps-University Marburg, D-35032 Marburg, Germany, 3 Department of Biological Psychology and Neuropsychology, University of Hamburg, D-20146 Hamburg, Germany
Address correspondence to Katja Fiehler. Email: fiehler{at}staff.uni-marburg.de.
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Abstract |
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The primate dorsal pathway has been proposed to compute vision for action. Although recent findings suggest that dorsal pathway structures contribute to somatosensory action control as well, it is yet not clear whether or not the development of dorsal pathway functions depends on early visual experience. Using functional magnetic resonance imaging, we investigated the pattern of cortical activation in congenitally blind and matched blindfolded sighted adults while performing kinesthetically guided hand movements. Congenitally blind adults activated similar dorsal pathway structures as sighted controls. Group-specific activations were found in the extrastriate cortex and the auditory cortex for congenitally blind humans and in the precuneus and the presupplementary motor area for sighted humans. Dorsal pathway activity was in addition observed for working memory maintenance of kinesthetic movement information in both groups. Thus, the results suggest that dorsal pathway functions develop in the absence of vision. This favors the idea of a general mechanism of movement control that operates regardless of the sensory input modality. Group differences in cortical activation patterns imply different movement control strategies as a function of visual experience.
Key Words: congenitally blind humans • dorsal stream • haptic • neural plasticity • working memory
Movements are guided by visual, auditory, kinesthetic, and tactile information. To date, it is still an open question where and how these different types of information are integrated for coherent action control. For visual information processing, 2 anatomically and functionally distinct cortical pathways have been proposed: a dorsal pathway, which projects from early visual areas to the posterior parietal cortex and uses vision for space perception, and a ventral pathway, which projects from early visual areas to the inferotemporal cortex and computes vision for object perception (Ungerleider and Mishkin 1982
). That is, the 2 pathways encode "where" and "what" an object is. More recently, the functional role of the dorsal pathway has been reinterpreted by suggesting that it is involved not in spatial processing per se, but in the visual guidance and control of actions, specifically determining "how" to interact with an object (Goodale and Milner 1992). Both pathways project to the prefrontal cortex constituting a frontoparietal network for movement control.
An equivalent pathway model has been proposed for the somatosensory domain stating that somatosensory information is also segregated along 2 pathways subserving action (posterior parietal cortex) and perception (posterior parietal cortex and insula) (Dijkerman and DeHaan 2007). Recently, we tested this theoretical framework by means of functional magnetic resonance imaging (fMRI) using a kinesthetic movement task (Fiehler et al. 2007, 2008). The results demonstrated that kinesthetic information is processed in brain regions of the dorsal pathway, thus, confirming the assumptions of the somatosensory pathway model. Moreover, we extended the originally proposed function of the dorsal pathway in online action control to mnemonic processes related to action control. In accordance with previous findings on visual (Connolly et al. 2003; Curtis 2006) and tactile (Stoeckel et al. 2003; Kaas et al. 2007) action–related working memory, we found dorsal pathway activity associated with working memory maintenance of kinesthetic information. Together, these findings provide converging evidence that the dorsal pathway supports action control not only on the basis of vision but also more generally by integrating all movement-relevant signals. It is, however, an unresolved issue whether visual experience is indispensable to the development of dorsal pathway functions.
Can the dorsal pathway evolve even in the absence of visual information? Congenitally blind humans who lack in visual experience during ontogenesis provide an exceptional opportunity to address this question. Several authors have reported activity in dorsal pathway structures in blind and sighted participants in spatial imagery tasks, that is, tasks requiring space perception (Röder et al. 1997; Vanlierde et al. 2003). However, to our knowledge, brain activity related to action control has not yet been investigated systematically in humans lacking any visual input since birth.
Here, fMRI was applied to decide whether or not the development of dorsal pathway functions that contribute to kinesthetic action control depends on intact vision. We specifically examined if areas of the dorsal pathway are recruited in the blind in the same manner as previously shown in sighted individuals (Fiehler et al. 2008) when hand movements are performed on the basis of kinesthetic information. As early vision alters sensory perception, like kinesthesia (Imbiriba et al. 2006) and touch (Röder et al. 2004), as well as cognitive processing (Cattaneo et al. 2007), we tested congenitally blind humans only.
We found a large activation overlap in areas of the dorsal pathway for congenitally blind and sighted participants during performance and working memory maintenance of kinesthetically guided hand movements. Our results imply that the development of the dorsal action control system is not restricted to visual experience during ontogenesis. Thus, we suggest a multimodal cortical network of movement control that evolves on the basis of visual and nonvisual sensory input signals.
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Participants
Twelve congenitally blind (6 females; mean age 25 years, range 20–38 years) and twelve sighted (8 females; mean age 25 years, range 19–35 years) adults participated. Written informed consent according to procedures approved by the local research ethics committee was obtained from each volunteer. All 12 blind participants were congenitally blind as assessed in an interview and had major retinal damage, and their blindness was not due to a progressive neurological disease. Sighted participants were part of a larger sample whose results had been published by Fiehler et al. (2008) elsewhere. All participants reported no history of medical, neurological, or psychiatric disorders and were free from prescription medication. Participants were matched by age (maximum difference ± 3 years) and years of education (MW ± SD, sighted: 17.3 ± 4.5 years; blind: 17.6 ± 2.7 years). Handedness was assessed by the Edinburgh Handedness Inventory (Oldfield 1971) using the adapted version for the blind volunteers (sighted participants: 12 right handed; congenitally blind participants: 10 right handed, 2 ambidextrous). All participants were blindfolded throughout the scan.
Stimuli and Experimental Setup
During the whole experiment, congenitally blind (CB) and sighted control (SC) participants lay supine in the scanner with their upper arm next to the body and their right forearm flexed to reach the experimental apparatus with the stylus held in the right hand (Fig. 1B left). The stimulus set comprised of 29 different line patterns engraved in small plastic cards (95 x 150 mm; width x height) (Fig. 1B right). There were 2 types of line patterns: one circular and 28 multisegment patterns. Line length was kept constant for all patterns (120 mm). To ensure comparable task complexity, each multisegment pattern was constructed with the same features: 4 segments (1 short, 2 medium, and 1 long segment of 15, 30, and 45 mm length, respectively) connected by one acute (45°), one right (90°), and one obtuse (135°) angle. To ease tracing requirements, the beginning of each line pattern was located at the left side of the card at a constant height of 75 mm and marked by a small plastic pin. Three line pattern cards were attached to a cardholder that was uprightly fixed on a base. The base was attached comfortably to the abdomen of the participants by 2 hook-and-loop strips. The cardholder was adjustable in 3 directions by a 120° turn on its own axis so that 3 line patterns could be successively presented per trial. The cardholder was turned by the experimenter who stood next to the participant while 2 research assistants sorted and attached the cards to a card holder in the previously defined trial order and handed it to the experimenter. Cardholders were exchanged between trials and during the delay epoch.
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Due to the small size of the line patterns participants mainly used finger, hand, and wrist movements while the upper arm remained stationary. In addition, head and shoulder motion was restrained by a Tempur foam head cushion (Tempur Deutschland GmbH, Steinhagen, Germany) and 4 additional arm cushions mounted to the right and left arm.
Experimental Protocol
The performance of kinesthetically guided hand movements was embedded in a delayed-recognition task that reliably activates cortical areas of the dorsal pathway in sighted participants during movement execution without vision (Fiehler et al. 2008). The time course of the delayed-recognition task is depicted in Figure 1A. Each trial started with a variable interval of 0.25 – 1.00 s followed by a tone (ca. 1 s) indicating the beginning of the movement-encoding period which always lasted 14 s. During this period, participants traced 3 line patterns with a stylus in their right hand, one after the other. After movement encoding, a second tone (ca. 1 s) signaled the beginning of the delay period. Participants were instructed to maintain a mental representation of the hand movements across a variable 7.5–8.5 s delay period while the right hand rested on their abdomen. The jitter at the beginning of each trial and of the delay period was randomly varied in 250-ms steps. Following the delay, a third tone (ca. 1 s) signaled the start of the movement recognition period. Participants traced one probe line pattern and finally pressed one of two buttons on a response box with their left hand to indicate whether the last line pattern matched one of the stimulus set items. The presentation of the probe was followed by a variable intertrial interval (ITI) together lasting 7.5–9.5 s depending on the length of the 2 applied jitters. The total trial length was 34 s.
The stimulus sets always consisted of 3 stimuli with either none (set size 0), 1 (set size 1), 2 (set size 2), or 3 (set size 3) multisegment patterns and 3, 2, 1, or 0 circles, respectively (Fig. 1B, right). None of the multisegment patterns was repeated within the same trial. The order of the different stimulus sets was randomized so that participants did not know how many complex line patterns were presented during the movement period. During the movement recognition period, a probe stimulus was presented which was a multisegment pattern in the set size 1, 2, and 3 conditions and either a multisegment or a circular pattern in the set size 0 condition. There were 12 trials per condition and run, and 2 runs per participant, resulting in 96 trials per participant. To guarantee comparable task requirements, 2 filler trials per set size 1, 2, and 3 conditions and runs were inserted with a circle presented as probe. Thus, there was a total of 102 trials per participant. Trials were balanced for the number and position of complex line patterns and the position of the match stimulus within the stimulus set. Furthermore, the number of match/nonmatch motor responses and the direction of the match/nonmatch response buttons were counterbalanced across the experiment.
Prior to fMRI scanning, participants were trained in the experimental procedure outside the scanner while lying in a supine position. The practice session lasted 30–60 min depending on the participants' performance. After training, participants were able to reliably trace the 3 line pattern cards within 14 s, to inhibit any arm movement during the maintenance period and to accurately recognize the movement during the recognition period. Only participants who successfully performed the practice session participated in the fMRI experiment. Performance criteria were a percent correct rate of more than 90% for the set size 0 condition and more than 60 % for the set size 3 condition. Stimuli presented during the practice session were not used during the scanning session.
Functional MRI Acquisition
Imaging was performed on a 1.5 T GE Signa Scanner (GE Medical Systems, Milwaukee, WI) equipped with a standard quadrature bird-cage head coil. A high-resolution 3D set of anatomical images was acquired in the axial orientation for each participant using a T1-weighted spoiled gradient echo sequence (SPGR, field of view [FOV] = 240 x 180 mm2, matrix size 256 x 192, time echo [TE] = 6 ms, time repetition [TR] = 33 ms) covering the whole brain. Functional images were acquired with a T2*-weighted gradient echo-planar imaging (EPI) sequence sensitive to blood oxygenation level–dependent (BOLD) contrasts (TR = 2000 ms; TE = 60 ms; flip angle = 80°; 64 x 64-pixel matrix; voxel size = 3.75 x 3.75 x 5 mm; FOV = 240 x 240 mm2), with each volume consisting of 19 axial slices (inter slice distance = 1 mm).
Data analysis
Behavioral Data
Reaction times and percent correct rates were measured for each experimental condition (task difficulty: set size 0, 1, 2, 3) in both groups of participants (CB and SC). Inverse efficiency scores were calculated by dividing the average reaction time by the proportion correct for each condition (cf., Townsend and Ashby 1993). This procedure eliminates possible speed accuracy trade-offs. For statistical analysis, a repeated-measures analysis of variance (ANOVA) with the within-participant factor task difficulty and the between-participant factor group was computed. Significance level was set at P < 0.001.
Functional MRI Data
The Statistic Parametric Mapping (SPM) package was used for image processing and statistical analyses (SPM2; http://www.fil.ion.ucl.ac.uk/spm; Welcome Department of Imaging Neuroscience, London, UK). The first 4 volumes of each fMRI run were discarded to allow for signal equilibration. Data preprocessing comprised the following steps: images of each participant were corrected for motion artifacts, corrected for slice time acquisition differences using a sinc-interpolation algorithm, spatially normalized to a standard EPI template as defined by the Montreal MNI and spatially smoothed using a 4 mm full width at half maximum (FWHM) Gaussian kernel. The voxel dimensions of each reconstructed scan were 3 x 3 x 3 mm.
A first-level analysis was performed individually for each participant based on the general linear model (GLM). For each participant, BOLD signals increasing with the level of task difficulty (set size 3 > set size 2 > set size 1 > set size 0) were assessed by a parametric analysis, including both correct and incorrect trials. To this end, the predictor of interest (movement encoding) was weighted by the logarithm of 2 (set size 0), 3 (set size 1), 4 (set size 2), and 5 (set size 3) to test which voxels in the brain positively correlate with the four levels of task difficulty (parameter). The resultant logarithmic function provides a better fit to the observed performance data (F = 42.03, P < 0.05; cf., Fig. 1C) than a linear function (F = 10.40, P = 0.08). This parametric variation of movement complexity substantiates the impact of an observed activation pattern: areas exhibiting increased activity in response to an increasing number of the to be encoded stimuli are very likely specifically involved in processing that stimulus (e.g., Druzgal and D'Esposito 2001). In addition to the predictor of interest (movement encoding), the GLM model comprised 5 predictors of no interest for the remaining task periods (movement maintenance and recognition) and for the filler trials of each task period. Regression coefficients for all predictors were estimated using least squares within SPM2 (Friston et al. 1995). Low-frequency signals were suppressed by applying a 1/128 Hz highpass filter.
Following first-level analyses, images of parameter estimates for the contrast of interest (task difficulty during movement encoding) were entered into a second-level one-sample t-test (random effects analysis) for each group separately (within-group analysis). Significance level was set at P < 0.001, uncorrected. To correct for multiple comparisons (type I error), a spatial cluster filter technique (Forman et al. 1995) implemented in AlphaSim was applied to the statistical parametric maps to produce a corrected significance level of P < 0.05. This resulted in a minimum cluster size of 464 mm3 for the SC group and 472 mm3 for the CB group. To identify cortical regions significantly activated in both CB and SC participants, we conducted a conjunction analysis. Significant group differences in the BOLD signal were detected by a two-sample t-test (between-group analysis). The resulting statistical parametric maps were thresholded at P < 0.005, uncorrected, combined with a spatial cluster threshold of 248 mm3 (Forman et al. 1995) to achieve a corrected significance level of P < 0.05.
Analogous to the data analysis of the movement-encoding period, cortical regions involved in working memory maintenance of kinesthetic information were assessed by a parametric analysis that contained the predictor of interest (movement maintenance) weighted by the logarithm of 2 (set size 0), 3 (set size 1), 4 (set size 2), and 5 (set size 3). Thus, an increase in the BOLD signal should reflect increasing memory load. The GLM also comprised 5 predictors of no interest containing the remaining task periods (movement encoding and recognition) and the filler trials of each task period. Given estimates of the temporal smoothness of the hemodynamic response, the covariate modeling of the first seconds of the delay period would be contaminated by hemodynamic activity from the movement-encoding period. To temporally separate the BOLD responses of the movement encoding and the delay period, the first 3 s of the delay period were not entered into the analyses (cf. Postle et al. 2000). Regression coefficients for all predictors were estimated using least squares within SPM2, and low-frequency signals were suppressed by a 1/128 Hz highpass filter. Within- and between-group parametric maps were calculated using random-effects analysis setting the significance level to P < 0.005, uncorrected. To correct for multiple comparisons, the statistical parametric maps were thresholded by a minimum cluster size of 1072 mm3 for the SC group and 896 mm3 for the CB group for the within-group analyses to achieve comparable false-positive probabilities (P < 0.05, corrected; Forman et al. 1995). The cluster threshold (P < 0.05, corrected) for the between-group analyses was 336 mm3.
The areas showing significant changes in BOLD signal were characterized in terms of MNI coordinates (x, y, z), cluster size (number of voxels per cluster), and maximal Z scores. Anatomically distinct brain areas within volumes of interest were classified by means of the Anatomy toolbox for SPM2 (Eickhoff et al. 2005; http://www.fz-juelich.de/inb/inb-3//spm_anatomy_toolbox) that is based on histological processing and cytoarchitectonic analyses of 10 postmortem human brains. The resulting cytoarchitectural areas are probability maps. This means, volumes of interest are defined statistically; as a consequence they are not only restricted to one cortical area only but do also extend into neighboring areas. The probability for a specific volume of interest, however, is always larger than for the neighboring ones. Weighted contrast values were calculated for selected volumes of interest using the MarsBar toolbox for SPM2 (Brett et al. 2002; http://marsbar.sourceforge.net/).
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Results |
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We investigated the pattern of cortical activation in 12 CB and 12 SC participants while performing kinesthetically guided hand movements under 4 levels of task difficulty. Task difficulty was determined by the number of distinct movement sequences per trial (Fig. 1B). Both groups executed the movements with their right hand without any visual feedback. The performance was embedded in a delayed recognition task where participants had to indicate whether a performed hand movement matched one of the 3 previous movements (Fig. 1A). To explore whether the development of the dorsal pathway functions associated with action control depends on vision, we first focus on the results of the movement-encoding period. Then we report the findings of the delay period uncovering the role of the dorsal pathway in kinesthetic working memory maintenance and the impact of early visual experience on that process.
Behavior
Participants' performance was measured in terms of inverse efficiency scores (for a definition, see method section). Performance data were clearly affected by task difficulty (Table 1). The repeated-measures ANOVA with the within-participant factor task difficulty and the between-participant factor group revealed a significant main effect of task difficulty (F3,66 = 125.89, P < 0.0001) indicating decreasing performance with increasing task difficulty (Fig. 1C). Task efficiency of CB and SC participants did not differ (group effect, F1,22 = 0.02, P = 0.88; group x task difficulty interaction, F3,66 = 2.18, P = 0.10).
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Cortical Activation
To determine which brain areas are involved in kinesthetic movement processing, we first focused on the encoding period. A parametric analysis (set size 3 > set size 2 > set size 1 > set size 0) for each group was calculated to reveal brain regions systematically responding to movement difficulty. We then compared the activation patterns of the CB and the SC group in order to identify cortical areas recruited in a similar or different manner for kinesthetic movement control. Secondly, we investigated brain regions involved in working memory maintenance of kinesthetic information. To this end, we calculated an additional parametric analysis (set size 3 > set size 2 > set size 1 > set size 0) to detect cortical areas showing an activation increase with increasing memory load.
Brain Regions Active During Execution of Kinesthetically Guided Hand Movements
CB Group
CB participants strongly activated the postcentral gyrus in both hemispheres, mainly covering area 2 of the primary somatosensory cortex. In contrast to the left hemispheric activation, the right postcentral gyrus activation spread into the secondary somatosensory cortex and the inferiorly adjacent auditory cortex. The widely distributed activation of the postcentral gyrus extended caudally into the anterior part of the intraparietal sulcus, a terminal point of the dorsal pathway. Dorsal pathway activity was additionally found in the left superior parietal lobe. Interestingly, CB participants also recruited a brain region located within the ventral perceptual pathway, the right inferior temporal gyrus (Table 2 and Fig. 2 upper row).
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activation of the SC group). L left; R right.SC Group
SC participants showed a more distributed activation pattern than CB participants. The most prominent activation occurred in the left and right postcentral gyrus, predominantly in area 2 of the primary somatosensory cortex. Similar to the CB group, we found dorsal pathway activation in the anterior portion of the intraparietal sulcus and the superior parietal lobe bilaterally. Kinesthetic movement processing further involved medial and lateral premotor areas in the left and right hemisphere, the right middle occipital gyrus, and the cerebellar vermis (Table 2 and Fig. 2 middle row).
Group Comparison
In the group comparison, we first concentrated on brain areas commonly activated by CB and SC participants by applying a conjunction analysis. This yielded the same cortical regions that were observed in the CB group by the parametric analysis (regions marked with an asterisk in Table 2). Thus, all cortices identified for kinesthetic movement processing in the CB group were also activated in the SC group during this task (Fig. 2 lower row). There was a significant activation overlap in the right inferior temporal gyrus between CB and SC participants but no significant activation in the SC group alone. This can be ascribed to the fact that SC participants activated a similar brain region (x/y/z, 51/–57/–15; P < 0.001, uncorrected), but the corresponding cluster size was marginally smaller than the cluster filter threshold.
Brain areas activated either in the CB or in the SC group were delineated by a two-sample t-test (Table 3). This analysis revealed stronger activation in CB participants than in SC participants in 2 sensory areas, namely, in the left extrastriate cortex (BA18) and in the posterior portion of the auditory cortex along the superior temporal gyrus (BA 22) of the left hemisphere (Fig. 3). The auditory cortex activation was further classified by means of statistical probability maps (Anatomy toolbox for SPM2, http://www.fz-juelich.de/inb/inb-3//spm_anatomy_toolbox). The observed activation cluster belonged to area TE 1.0 (Morosan et al. 2001), a subregion of the auditory cortex (Fig. 3). Note that the accuracy of the anatomical classification is limited by the spatial resolution of the present fMRI data. Stronger activation for SC than CB participants was found in the rostral presupplementary motor area and in the right parieto–occipital fissure extending into the precuneus (Fig. 3).
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Brain Regions Active during Working Memory Maintenance Of Kinesthetically Guided Hand Movements
The results of the maintenance period are summarized in Table 4 and Figure 4. The parametric analysis used to isolate cortical areas responding to memory load revealed significant signal changes for the SC group in the left polar prefrontal cortex (BA 10), the left middorsolateral prefrontal cortex (BA 46), and the anterior intraparietal sulcus bilaterally with the center of gravity in the left hemisphere. In the CB group, activity was also found in the anterior intraparietal sulcus in both hemispheres, only the left activation cluster, however, reached the cluster size threshold whereas the right cluster slightly missed it. Activations in congenitally blind and sighted volunteers significantly overlapped in the left anterior intraparietal sulcus (x/y/z, –48/–48/45; P < 0.05, corrected), especially in human intraparietal area 1 (hIP1; Choi et al. 2006). The left intraparietal activation cluster of the SC group extended more anteriorly compared to the CB group as evidenced by a significantly stronger activation in human intraparietal area 2 (hIP2; Choi et al. 2006) for SC participants.
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Discussion |
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The present study investigated whether dorsal pathway functions develop in the absence of visual experience. We observed that CB humans activated dorsal pathway structures while performing kinesthetically guided hand movements. This dorsal pathway activation substantially overlapped with the activation pattern observed in SC participants. We also found group-specific brain activity: the SC group showed stronger activation than the CB group in the presupplementary motor area and the right precuneus extending into the parieto–occipital fissure, whereas the CB group showed stronger activation than the SC group in the left extrastriate cortex and the left auditory cortex. In both groups, working memory maintenance of kinesthetic information activated areas of the dorsal pathway, in particular the left anterior intraparietal sulcus. In the following, we will first discuss the functional properties of the cortices involved in kinesthetic movement control and will then elaborate the present findings on kinesthetic working memory.
Neural Mechanisms Of Kinesthetic Movement Control
In the present task, complex hand movements were substantially guided by kinesthetic input signals from the hand and fingers. Additionally, tactile feedback from the fingertips holding the stylus were used, although most likely to a small degree. In line with functional imaging studies on tactile object exploration (Stoeckel et al. 2003) and kinesthetic movement control (Fiehler et al. 2008), we observed a large bilateral activation cluster in the primary somatosensory cortex (SI), especially in area 2, in both CB and SC participants. This agrees with previous observations showing that area 2 processes primarily kinesthetic information and, to a lesser extent, complex cutaneous stimuli, for example, surface curvature (Bodegard et al. 2001). As expected, kinesthetically guided movements further activated the superior parietal cortex in both groups. Research in human (Gerardin et al. 2000) and nonhuman (Sakata et al. 1973) primates has demonstrated that the superior parietal cortex implements a more elaborative processing of kinesthetic movement information. In contrast to the primary somatosensory cortex, neurons in the superior parietal cortex respond to multiple joint interactions and integrate both tactile and kinesthetic information. Dense corticocortical connections (Jones and Powell 1969) and similar receptor distributions (Scheperjans et al. 2005) facilitate intense mutual interactions between the primary somatosensory cortex and the superior parietal cortex and their exchange of information. Thus, area 2 and the superior parietal cortex seem to be involved in the processing of kinesthetic and tactile information in the present task.
The superior parietal cortex located within the dorsal pathway is known to be involved in online action control as well. In previous imaging studies, the superior parietal cortex has been observed to be active during hand and finger movements requiring kinesthetic control (Gerardin et al. 2000). Moreover, lesions of posterior parietal areas result in a severe impairment of exploratory hand movements despite intact elementary sensory or motor functions, termed tactile apraxia (Binkofski et al. 2001). In addition, we observed activity in a second dorsal pathway region, the anterior part of the intraparietal sulcus. The anterior intraparietal sulcus has been discussed as an area that transforms sensory input into motor commands and continuously updates the ongoing movement with respect to the aspired movement goal (Desmurget and Grafton 2000). As a consequence, this area allows for a flexible control of actions. Due to strong cortical connections (Rushworth et al. 2006), the information is further transferred to the ventral premotor cortex important for performing of precise hand movements. Congruously, we found motor-related activation in that area.
The localization of the anterior intraparietal sulcus activation for kinesthetic hand movement control in the present task significantly overlapped with brain areas reported for visually guided hand movements (Binkofski et al. 1998; Culham et al. 2003; Frey et al. 2005). Thus, it seems that the anterior intraparietal sulcus controls action on the basis of both kinesthetic and visual information. This is in accordance with the visual (Goodale and Milner 1992) and the somatosensory (Dijkerman and DeHaan 2007) pathway models which both hypothesize that the dorsal action stream terminates in the posterior parietal cortex. Our results together with previous findings suggest a modality-independent function of the dorsal pathway, in particular the anterior intraparietal sulcus, in hand movement control. Future research could further substantiate the assumption of multimodality by directly comparing different input modalities (e.g., visual vs. kinesthetic) used for action guidance under specific task instructions within one experiment.
The key finding of the present study is the substantial overlap of activation of dorsal pathway structures, the anterior intraparietal sulcus and the superior parietal cortex, in CB and SC participants. Because vision is the dominant sense in sighted humans providing the most reliable spatial information, goal-directed actions are most often predominantly visually guided. Therefore, it is plausible to assume that early visual experience is indispensable for the development of parietal systems responsible for movement control. An effect of early vision on multisensory action control has recently been demonstrated by Röder et al. (2004, 2007) in behavioral experiments. They found that spatial reference frames used for auditory action control differed for CB and SC participants. However, their data do not exclude a role of the parietal cortex for action control in the blind. The present fMRI results suggest that movement control is mediated by the dorsal pathway regardless of the sensory input modalities available during development. This is in accordance with recent findings by Garg et al. (2007) who observed activity enhancement in a vision-related cortical region of the dorsal fronto-parietal pathway, the frontal eye fields, in both congenitally blind and sighted participants performing a spatial attention task. The present dorsal pathway activity in congenitally blind adults also supports the argument that activation of the dorsal pathway observed in haptic movement tasks in sighted individuals is not solely caused by visual imagery.
In addition to vision, touch, and kinesthesia, auditory information contribute to movement control as well. Analogous to the "what" and "where" segregation of visual information processing (Ungerleider and Mishkin 1982), a similar functional organization has been proposed for the auditory modality (for evidence in monkeys, see, Romanski et al. 1999; Rauschecker and Tian 2000; for evidence in humans, see, Alain et al. 2001; Clark et al. 2002). There is evidence that sound localization and sound identification are functionally distinct along dorsal and ventral pathways, respectively. Consequently, greatest spatial selectivity was found in the caudal aspects of the superior temporal gyrus, considered as the origin of the dorsal "where" pathway. This area has dense cortical connections to the posterior parietal cortex (Romanski et al. 1999), again in line with its role in spatial processing. Thus, multiple sensory inputs about spatial relations converge in the posterior parietal cortex and are integrated into a coherent space representation used for action guidance. This furthermore implies that the dorsal pathway has access to multimodal information. Evidence for the involvement of the auditory "where" pathway and its parietal projection areas in congenitally blind people would provide further evidence for a modality-independent development of dorsal pathway functions.
Interestingly, in CB participants we found activation in an area of the ventral pathway, in the right inferior temporal gyrus. A similar activation was observed in the SC group but the corresponding cluster size slightly missed the cluster filter threshold. The existence of reliable inferior temporal cortex activity in both groups, was substantiated by a significant activation overlap (x/y/z, 48/–57/–15; P < 0.05, corrected) detected by the conjunction analysis. This activation partly overlapped with the rostral part of the object sensitive area termed lateral occipital complex (LOC; Malach et al. 1995). The functional specialization of LOC in object recognition was confirmed by a lesion study that reported visual form agnosia in a patient with a severe damage in the ventral pathway (James et al. 2003). Recent imaging experiments have demonstrated that a region within LOC (LOtv) is not only involved in visual but also in tactile object recognition (Amedi et al. 2001; Pietrini et al. 2004). Object-related auditory information failed to activate LOtv (Amedi et al. 2002). LOtv responded, however, if shape information was preserved in the auditory signal by using visual-to-auditory sensory substitution soundscapes (Amedi et al. 2007). Apparently, LOtv functions as a multisensory object-selective network that is driven by the presence of shape information. Based on these findings, we assume that ventral pathway activation in CB and SC participants is associated with the encoding and memorizing of the geometrical shape of the movement path in order to successfully perform the delayed-recognition task. While SC participants might have used both visual imagery and haptic input signals to extract shape information, it is evident that CB participants must have relied on haptic input only supporting the role of LOtv in visual and haptic object recognition.
Recruitment of Presupplementary Motor Area and Precuneus in Sighted Humans
Although the dorsal pathway network engaged in the present task was similar in CB and SC participants, we observed brain regions selectively recruited by either the one or the other group as well. In comparison to the CB group, SC participants showed stronger activation in the pre-supplementary motor area (pre-SMA) and in the right precuneus extending into the parieto-occipital fissure. Anatomical studies revealed reciprocal connections between these two areas (Wise et al. 1997). Together with the pre-SMA, the precuneus is part of a neural network functionally specialized for the process of spatially guided behavior (Selemon and Goldman-Rakic 1988). In particular, parieto-occipital regions are supposed to compute egocentric and allocentric spatial coordinates used for body movement control. This finding was supported by a recent study in patients with lesions in the occipito-parietal junction and adjoining precuneus who suffered from optic ataxia (Karnath and Perenin 2005). Moreover, tactile object localization in contrast to tactile object identification was associated with greater activation in the precuneus region (Reed et al. 2005). The pre-SMA is proposed to contribute to this process by implementing higher order aspects of motor control, that is, updating of motor plans and control of complex movement sequences (Picard and Strick 1996). Activity in the pre-SMA systematically varied with movement difficulty, i.e., the complexity in movement transitions was positively correlated with the strength of cortical activation (Harrington et al. 2000). Consistent with this view, we found that three different complex hand movements (Set size 3) compared to three simple circular hand movements (Set size 0) led to an increase in the BOLD signal in the pre-SMA (x/y/z, cluster size, Z score: –6/21/36, 91 voxels, Z = 3.85, P < 0.05, corrected) for the SC but not for the CB participants. A similar result was observed for the occipito-parietal region (x/y/z, cluster size, Z score: 18/–57/21, 21 voxels, Z = 3.86, P < 0.05, corrected). The pre-SMA, in contrast to the occipito-parietal region, also showed a linear increase in activation strength with an increase in movement difficulty in the SC group, favoring its role in sensorimotor control processes.
In addition to their function in active movement guidance, both precuneus and pre-SMA seem to be important for motor imagery (Gerardin et al. 2000). It has been argued that these cortical regions are constituent parts of a distinct neural network of motor imagery engaged in the construction of internal spatial representations for movement control. Activity in this network has been found to increase when demands of locomotor imaging tasks require increasing cognitive and sensory information processing (Malouin et al. 2003).
Following this argument, the higher activation in the pre-SMA and occipito-parietal areas in SC compared to CB participants might be due to higher task-related cognitive and sensorimotor demands. Because of the dominant visual sense, sighted individuals are not as experienced as blind humans in kinesthetic movement control. Therefore, the execution of the present task might have required more effort for the SC group reflected by increased activity in brain regions associated with spatial movement control. Support for this assumption was also provided by a comparable performance level of both groups (see behavioral data) and significantly less training time for CB participants. Alternatively, the group difference might be attributed to the use of different strategies for movement processing as congenitally blind in contrast to sighted humans have been shown to prefer egocentric rather than external allocentric reference frames for motor control (Röder et al. 2007).
Recruitment of the Extrastriate and Auditory Cortex in Congenitally Blind Humans
Kinesthetic movement processing elicited stronger activation in the extrastriate cortex in CB compared to SC participants. This activation of the occipital cortex in the blind is in accordance with previous findings showing activation in striate and extrastriate areas in a variety of non-visual perceptual tasks, for example, tactile discrimination (Sadato et al. 1996, 2004; Cohen et al. 1997) and auditory localization (Weeks et al. 2000; Gougoux et al. 2005), as well as cognitive tasks, for example, speech processing (Röder et al. 2002) and verbal memory (Amedi et al. 2003). The present data add to these reports by demonstrating extrastriate cortex activity in the blind also for kinesthetic information processing used for action guidance.
Visual deafferentation leads to cross-modal cortical reorganization of the occipital cortex (Röder and Rösler 2004; Pascual-Leone et al. 2005). Neural transplantation (Schlaggar and O'Leary 1991) and rewiring studies (Sur and Leamey 2001) suggest that the occipital cortex tissue can process input from non-visual modalities, that is, somatosensory and auditory information. Even transient visual deprivation (five days) in sighted humans can already induce an activation of the primary visual cortex for tactile and auditory processing (Pascual-Leone and Hamilton 2001). Since transcranial magnetic stimulation (TMS) over the occipital cortex seems to interfere with perceptual and cognitive processing of blind people (Cohen et al. 1997; Amedi et al. 2004), it has been argued that this area may take over non-visual functions in the blind. Although, visual cortex activity emerges within a few days after blindfolding and has been found in a great variety of perceptual and cognitive tasks, its functional significance is still not fully understood.
Moreover, CB participants in contrast to SC participants exhibited increased activation in the auditory cortex. Somatosensory input to the auditory cortex has recently been demonstrated in human and non-human primates. Intracranial recordings in monkeys have shown activation in the caudomedial auditory cortex (CM) triggered by repetitive electrical stimulation of the median nerve (Schroeder et al. 2001), by cutaneous stimulation at the head/neck and hand, and by kinesthetic stimulation at the elbow (Fu et al. 2003). The timing and laminar activation for somatosensory and auditory inputs are nearly the same in monkey area CM supporting somatosensory-auditory convergence in this area. Anatomical reconstructions, however, indicated that the somatosensory input region includes but may not be restricted to area CM (Schroeder et al. 2001). Using fMRI, a putative human homologue of area CM has been identified located in a subregion of human auditory cortex along the superior temporal gyrus (Foxe et al. 2002). This area substantially overlaps with the region activated in the present study. Comparable to the monkey data, the subregion of the human auditory cortex responded to both auditory and somatosensory stimuli. The activation strength was larger for multisensory than summed unisensory stimulation suggesting multisensory integration in that convergence zone. This result was confirmed by a recent electrophysiological study that demonstrated early activation of auditory cortical areas (around 100 ms after stimulus onset) in response to vibrotactile stimulation (Caetano and Jousmäki 2006). Thus, multisensory input signals are integrated early in the cortical processing hierarchy, in other words, in brain areas traditionally considered as unisensory. A direct comparison of brain areas contributing to auditory and vibrotactile processing revealed a shared neural substrate in the posterior auditory belt area (Schürmann et al. 2006). These results were interpreted such that vibrotactile stimuli elicit a perception of a sound via tactile sense due to the sound-like temporal patterns in vibration. However, single tactile pulses that resulted in a sensation of a brief touch without any vibration also activated parts of the posterior auditory belt region (Schürmann et al. 2006). Therefore, it is more likely that the posterior auditory belt region represents a multisensory convergence zone that subserves processing of composite audiotactile events.
While in sighted individuals the guidance of hand movements is primarily based on vision, blind people have to rely on kinesthetic, tactile, and auditory information. The greater experience in and stronger reliance of movement control on composite somatosensory and auditory feedback might have led to a stronger excitability of the multisensory convergence zone in the auditory cortex in the blind. Thus, visual deprivation results in both intermodal changes (i.e., visual cortex activation) and compensatory changes in the intact sensory cortices (i.e., auditory cortex activation) due to intramodal plasticity (cf., Röder and Rösler 2004).
Neural Mechanisms of Kinesthetic Working Memory
Consistent with previous findings in tactile working memory (Stoeckel et al. 2003; Kaas et al. 2007), the present study identified the anterior intraparietal sulcus as being responsible for working memory maintenance of kinesthetic information used to guide hand actions. Activity in this region systematically varied with memory load, i.e., the hemodynamic response increased with increasing mnemonic demands. Importantly, we demonstrated that the anterior intraparietal sulcus was not only recruited by sighted but also by congenitally blind participants. This finding further supports the assumption that dorsal pathway functions related to the control of immediate and delayed actions do not depend on early visual input.
Based on the anatomically defined maps by Choi et al. (2006), activation overlapped significantly in both groups in the left posterior portion of the anterior intraparietal sulcus, more precisely, in human intraparietal area 1 (hIP1), but differed in the left anteriorly located human intraparietal area 2 (hIP2). Since, to our knowledge, no studies have examined the distinct functional roles of hIP1 and hIP2 so far, an interpretation of the observed group difference in hIP2 must be speculative and is left for future research.
Kinesthetic working memory is moreover associated with greater activity in prefrontal regions. Research in non-human primates using the tactile flutter discrimination task, which requires the comparison of two frequencies separated by a short delay, suggests that the prefrontal cortex is part of a network involved in tactile working memory (Romo and Salinas 2003). In accordance with the monkey data, prefrontal activity related to tactile working memory has been reported in humans using fMRI (Stoeckel et al. 2003; Kaas et al. 2007) as well. Across different modalities, the prefrontal cortex seems to be involved in mnemonic control processes, whereas the posterior association cortices directly operate on the storage buffer (cf., Postle et al. 1999). Our data extend previous findings on tactile working memory to the kinesthetic modality.
Conclusion
In sum, congenitally blind and sighted humans recruited similar networks of the dorsal action control system for kinesthetic movement processing. This result demonstrates that dorsal pathway functions develop even in the absence of vision. Group differences in cortical activation patterns imply different movement control strategies depending on visual experience during ontogenesis.
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German Research Foundation (Ro 529/18).
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We thank Franz-Josef Visse and Judith Tacke for their help in recruiting blind participants and Annerose Engel for thoughtful discussions about the experimental design. Conflict of Interest: None declared.
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