Assessment of the caudate nucleus and its relation to route learning in both congenital and late blind individuals
© Voss et al.; licensee BioMed Central Ltd. 2013
Received: 20 December 2012
Accepted: 18 September 2013
Published: 4 October 2013
In the absence of visual input, the question arises as to how complex spatial abilities develop and how the brain adapts to the absence of this modality. As such, the aim of the current study was to investigate the relationship between visual status and an important brain structure with a well established role in spatial cognition and navigation, the caudate nucleus. We conducted a volumetric analysis of the caudate nucleus in congenitally and late blind individuals, as well as in matched sighted control subjects.
No differences in the volume of the structure were found either between congenitally blind (CB) and matched sighted controls or between late blind (LB) and matched sighted controls. Moreover, contrary to what was expected, no significant correlation was found between caudate volume and performance in a spatial navigation task. Finally, consistent with previously published reports, the volume of the caudate nucleus was found to be negatively correlated with age in the sighted; however such correlations were not significant in the blind groups.
Although there were no group differences, the absence of an age-volume correlation in the blind suggests that visual deprivation may still have an effect on the developmental changes that occur in the caudate nucleus.
Spatial cognition and the ability to properly navigate in one’s environment are believed to result from the contribution of several subcortical structures such as the hippocampus (HC) and the caudate nucleus (CN). This is well documented in rats, for instance, as place learning involves two different memory systems subserved by the HC and the dorsal striatum (particularly the caudate nucleus) [1–3]. In the early phases of learning, the HC is involved in the rapid acquisition of spatial information, allowing for rats to reach a target from any starting position . The dorsal striatum is involved in a slower learning process  that relies on rewarded stimulus–response (S-R) behaviour [3, 5], i.e. gradually learning particular body turns in response to stimuli, which allow the rats to reach a target location from one starting point . A similar segregation has been observed in humans. Functional Magnetic Resonance Imaging (fMRI) studies have shown that tasks requiring spatial representations preferentially activate the HC, while tasks not requiring a particular `spatial strategy activate mainly the CN [7, 8]. Moreover, gray matter density in these structures is found to correlate with specific navigational strategies ; subjects who were qualified as “spatial learners” had significantly more grey matter in the HC and less in the CN compared to “response learners”.
Given the importance of vision and visual cues for spatial navigation and wayfinding, the absence of the visual modality raises questions on not only the ability to navigate in one’s environment without vision but also on the anatomical and functional consequences to the brain structures involved in such learning. Despite the absence of visual inputs, blind individuals are nonetheless able to properly orient themselves and navigate in space [10, 11]. To date, three studies have examined the effects of visual loss on the structural integrity of the HC [11–13]. While initial results may have seemed at odds with each other, with Fortin et al.  finding an increase in volume in the anterior portion of the HC and Chebat et al.  finding a decrease in volume in the posterior portion, a subsequent study by Lepore et al.  actually confirmed both sets of findings, suggesting that following blindness there is a shift of the neuronal population towards the anterior portions of the hippocampus compared to sighted individuals. Importantly, however, little is known about the consequences of visual loss on the structural anatomy of the CN. Interestingly, in our previous study , where both blind and sighted subjects were asked to learn new paths in a human-size labyrinth (i.e. route learning task), most subjects anecdotally reported using a ‘response learners’ strategy where they attempted to sequentially recall the series of right and left turns that were required to properly follow the taught route. Indeed, previous work has not only shown the blind to possess superior serial memory for sequences , but that they also construct mental representations of paths via serial memorization of segmented inputs from each location along the path . Moreover, crucial to our hypothesis formulation, recent data has in fact shown that route learning abilities in young and older adults are positively correlated to CN volume . Therefore, given the above mentioned findings, we hypothesized here that blind individuals would not only possess larger CN relative to their sighted counterparts, but also that the volume would be significantly related to previously obtained behavioral measures in the blind . To address this, using the MRI scans previously obtained in the aforementioned hippocampus volumetric study , we performed volume measurements of the CN in congenitally blind, late blind and matched sighted controls. We furthermore wanted to assess whether known associations with the caudate volume would also hold true in blindness. For instance, in normally-sighted individuals, the caudate volume is known to decrease with age [17, 18], and there are conflicting reports on how the caudate and hippocampal volumes covary with one another [9, 19, 20]. The latter investigation is especially pertinent to the present study, given the previously established relationship between hippocampal volume and route learning performance.
Subject demographic information
Causes of blindness
Leber’s congenital amaurosis
Leber’s congenital amaurosis
Leber’s congenital amaurosis
Medical accident (retina damage)
Congenital cataracts and glaucoma
Glaucoma and aniridia
Image acquisition and analysis
For each participant, MR images were previously acquired (see ) on a Siemens 1.5 Tesla Magnetom Vision MRI scanner (Siemens, Erlangen, Germany) at the Notre-Dame Hospital (CHUM). All images were acquired in high resolution (1 × 1 × 1 mm, T1-weighted 3D) with a sagittally oriented echo sequence (TR: 1100; TE:4.38; flip angle of 15; 256 × 256 matrix and FOV:250).
Following the manual corrections, the reliability of the measurements was ascertained by obtaining estimates of both the intra-rater reliability and inter-rater reliability. The intra-rater intra-class reliability coefficients were 0.971 (left CN) and 0.988 (right CN), and were obtained by the original rater (PV) re-measuring the CN volume in four randomly selected MRI scans, with at least two months elapsing between consecutive measurements. The inter-rater intra-class reliability coefficients were 0.926 (left CN) and 0.942 (right CN), and were obtained by two raters (PV and MF) measuring caudate volumes independently in eight randomly selected MRI scans.
Behavioral route learning task
The task is described in greater detail Fortin et al. . Briefly, the route learning task was performed as follows: subjects were asked to memorize a traveled route within a human-size labyrinth, guided by an experimenter, and then had to follow the same path alone on five subsequent trials while trying to make as few errors as possible; when mistakes were made, subjects were instructed to stop and were repositioned by the experimenter in the correct direction. Sighted subjects performed the task blindfolded. Four different routes were tested of increasing difficulty: with six, eight, ten and twelve decision points to memorize.
We correlated caudate volumetric measurements with several other measures to address aforementioned hypotheses. Both sighted control groups were pooled together, as there is no a priori reason to not consider them along a continuum of individuals with normal sensory experience. Regression analyses involving the blind groups were performed with both groups pooled together, as well as separately since both groups have differential experience with the visual modality.
We first ascertained whether or not caudate volume would be predictive of performance on a spatial navigation task. The task is briefly explained above, and entailed the learning of 4 different routes of increasing difficulty within a human size labyrinth. Previously, the size of the right hippocampus was shown to be predictive of performance. For a more detailed description of the task and of the findings, please see Fortin et al. . As previously done, we chose to use the performance of each subject (number of errors) on the most difficult route as regressors in correlational analyses with caudate volume. However, contrary to what was observed with the hippocampus, no such correlation between performance and caudate volume was observed when correlating both measures across all participants [lCN (r = 0.011; p = 0.955); rCN (r = −0.144; p = 0.447)].
We also investigated the relationship between the total caudate volume and the total hippocampal volume previously measured in the same subjects (Fortin et al., ). We found no significant correlation between the volumes of both structures in any of the groups [CB (r = −0.263; p = 0.529), LB (r = 0.078; p = 0.869), Sighted (r = 0.242; p = 0.385)].
The primary goals of the present study were: 1) to address whether or not the CN volume is affected in blindness, 2) to ascertain if it plays a role in the superior wayfinding abilities of blind individuals. Importantly, we also investigated the role played by the age of blindness onset on the CN (by separately comparing CB and LB to groups of sighted controls). Lastly, we also investigated whether blindness would alter associations the caudate volume has with hippocampal volume (disputed) and age.
Effect of blindness
The CN volume was not significantly different in the CB compared to matched sighted controls (SCB). However, while Figure 2 seems to indicate that the CN is larger in the LB compared to the SLB, this difference did not reach statistical significance, possibly due to the small subject sample and high variability. The latter contrast also revealed a significant effect of hemisphere, with the right caudate being larger than the left for each group. This hemispheric asymmetry is consistent with previous research showing that the right caudate tends to be larger than the left caudate, irrespective of gender and laterality [28, 29]. It is however unclear to us why this asymmetry was not found for the CB-SCB contrast. Since our LB and SLB groups are older, perhaps the CN asymmetry is exacerbated with aging. Such a hypothesis is however speculative and remains to be further explored.
We also chose to compare the CN measurements with those of previously obtained hippocampal measurements  in an attempt to address inconsistencies in the literature. Here we show that both measures are uncorrelated in all groups. This is in marked contrast to two separate lines of findings. The first stems from a previously mentioned study investigating the neural correlates of spatial navigation and showed that the size of both structures are negatively correlated with one another . This inverse correlation is consistent with the authors’ findings of the hippocampus being larger in ‘spatial’ learners and of the CN being larger in ‘response’ learners. The second line of evidence stems from work investigating the effect of aging on cortical and subcortical structures, which has shown the volume of both the hippocampus and the CN to correlate with one another [19, 20]. However in the latter studies, the correlation coefficients were modest (ranging between 0.24 and 0.4) and likely reached statistical significance due to the large sample sizes (> 65). Interestingly, the correlation found here in the sighted was also of 0.24 (though with a much smaller sample size), indicating a certain level of agreement between both datasets. It remains nonetheless difficult to reconcile our findings with those of Bohbot et al. , where a negative correlation was found. Consequently, the currently available data does not paint a very clear picture of the relationship between caudate and hippocampal volume. As such, further investigation will be required to elucidate the nature of the volumetric relationship, should one actually exist.
The present finding of an age-related decline of caudate volume in the sighted subjects was expected and is consistent with previous reports [17, 18]. Surprisingly however, no such relationship was found in the blind. Furthermore, the strength of the age – caudate volume relationship was shown to be significantly different between the blind and the sighted for the right caudate, suggesting that blindness does perhaps affect the caudate volume in a more subtle manner than anticipated. The absence of a significant relationship in the blind appears to, at least partly, result from the fact that the CN volume in the older LB individuals isn’t reduced compared to the CB (see Figure 2). It would therefore appear that the loss of sight after puberty alters the normal developmental time-course of the age-related decline in caudate volume. The absence of an age-volume relationship in the blind could also possibly result from differential visual inputs into the tail of the CN via corticostriatal connections with extrastriate visual areas [30, 31].
Taken together, the present findings indicate that the CN is not a beneficiary of compensatory plastic changes in blind individuals, as is the hippocampus [11, 13] and visually-deafferented cortical areas. Indeed, there are numerous published reports showing that occipital brain function (see ) and occipital neuroanatomical changes  appear to underlie superior abilities in a wide-range of non-visual perceptual and cognitive domains. The present null finding might be due to the CN’s heterogeneous functionality which is largely motor-learning related, and for which there is little evidence of measured enhancements in the blind population. In contrast, the hippocampus’ primary functions are related to memory and spatial encoding, both for which the blind have been shown to develop superior abilities in [10, 11, 32]. The visually deafferented occipital cortex however, appears to underlie a variety of enhanced perceptual and cognitive skills in the blind. As such, given that route learning is but one of many functions subtended by the CN, it is possible that it is insufficient to drive substantial compensatory changes following visual deprivation.
Relation to task performance
Given the nature of the spatial navigation task, where a prominent strategy for success was to sequentially recall the series of right and left, we had hypothesized that the CN would be a likely structure to be called upon, and that its volume would be predictive of performance as previous studies have shown . Unexpectedly however, the CN volume was not at all predictive of performance. This finding was of course unexpected given the nature of the task and the known association between the type of task used and grey matter volume in the CN. Importantly though, it is worth pointing out that volume does not always correlate with performance in spatial navigation tasks, but rather correlates with strategies as previously underlined . This was highlighted in a recent study where the hippocampal volume was found to correlate only with the use of spatial memory strategies, and not with performance on a navigation task . Consequently, the absence of a correlation might simply reflect the use of differential strategies across our subject sample when performing the route learning task. However, without quantitative data on the strategies used by the participants, it is unfortunately difficult to explain the lack of a correlation with more certainty. Future work should take care in assessing the strategies used by the participants to address these unanswered questions.
The present data suggest that compensatory plasticity in blindness does not extend to sub-cortical structures in the striatum, as the CN was found to be equal in volume between sighted and blind subjects (although a statistically non-significant increase was observed in the LB relative to sighted controls), and did not correlate with performance on of the route learning task. Evidently, further investigations are required in order to better understand the role visual deprivation plays in shaping the neuroanatomy of the CN, and how this interplays with route learning abilities.
We thank all the participants who took part in this study. This study was supported by grants from the Canadian Institutes of Health Research (CIHR) awarded to FL. PV was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC).
- O’Keefe J, Nadel L: The hippocampus as a cognitive Map. 1978, Oxford: ClarendonGoogle Scholar
- McDonald RJ, White NM: Parallel information processing in the water-maze: evidence for independent memory systems involving dorsal striatum and hippocampus. Behav Neural Biol. 1994, 109: 579-593.View ArticleGoogle Scholar
- White NM, McDonald RJ: Multiple parallel memory systems in the brain of the rat. Neurobiol Learn Mem. 2002, 77: 125-184. 10.1006/nlme.2001.4008.View ArticlePubMedGoogle Scholar
- Packard MG, McGaugh JL: Inactivation of hippocampus or caudate nucleus with lidocaine differentially affects expression of place and response learning. Neurobiol Learn Mem. 1996, 65: 65-72. 10.1006/nlme.1996.0007.View ArticlePubMedGoogle Scholar
- Packard MG, Knowlton BJ: Learning and memory functions of the basal ganglia. Annu Rev Neurosci. 2002, 25: 563-593. 10.1146/annurev.neuro.25.112701.142937.View ArticlePubMedGoogle Scholar
- Eichenbaum H, Stewart C, Morris HG: Hippocampal representation in place learning. J Neurosci. 1990, 10: 3531-3542.PubMedGoogle Scholar
- Hartley T, Maguire EA, Spiers HJ, Burgess N: The well-worn route and the path less travelled: distinct neural bases of route following and wayfinding in humans. Neuron. 2003, 37: 877-888. 10.1016/S0896-6273(03)00095-3.View ArticlePubMedGoogle Scholar
- Iaria G, Petrides M, Dagher A, Pike B, Bohbot VD: Cognitive strategies dependent on the hippocampus and caudate nucleus in human navigation: variability and change with practice. J Neurosci. 2003, 23: 5945-5952.PubMedGoogle Scholar
- Bohbot VD, Lerch J, Thorndycraft B, Iaria G, Zijdenbos AP: Gray matter differences correlate with spontaneous strategies in a human virtual navigation task. J Neurosci. 2007, 27: 10078-10083. 10.1523/JNEUROSCI.1763-07.2007.View ArticlePubMedGoogle Scholar
- Tinti C, Adenzato M, Tamietto M, Cornoldi C: Visual experience is not necessary for efficient survey spatial cognition: evidence from blindness. Q J Exp Psychol. 2006, 59: 1306-1328. 10.1080/17470210500214275.View ArticleGoogle Scholar
- Fortin M, Voss P, Lord C, Lassonde M, Pruessner J, Saint-Amour D, Rainville C, Lepore F: Wayfinding in the blind: larger hippocampal volume and supranormal spatial navigation. Brain. 2008, 131: 2995-3005. 10.1093/brain/awn250.View ArticlePubMedGoogle Scholar
- Chebat DR, Chen JK, Schneider F, Ptito A, Kupers R, Ptito M: Alterations in right posterior hippocampus in early blind individuals. NeuroReport. 2007, 18: 329-333. 10.1097/WNR.0b013e32802b70f8.View ArticlePubMedGoogle Scholar
- Lepore N, Shi Y, Lepore F, Fortin M, Voss P, Chou Y, Lord C, Lassonde M, Dinov I, Toga AW, Thompson PM: Patterns of hippocampal shape and volume changes in blind subjects. Neuroimage. 2009, 46: 949-957. 10.1016/j.neuroimage.2009.01.071.PubMed CentralView ArticlePubMedGoogle Scholar
- Raz N, Striem E, Pundak G, Orlov T, Zohary E: Superior serial memory in the blind: a case of cognitive compensatory adjustment. Curr Biol. 2007, 17: 1129-1133. 10.1016/j.cub.2007.05.060.View ArticlePubMedGoogle Scholar
- Iverson JM: How to get to the cafeteria: gesture and speech in blind and sighted children’s spatial descriptions. Dev Psychol. 1999, 35: 1131-1142.View ArticleGoogle Scholar
- Head D, Isom M: Age effects on wayfinding and route learning skills. Behav Brain Res. 2010, 209: 49-58. 10.1016/j.bbr.2010.01.012.View ArticlePubMedGoogle Scholar
- Hasan KM, Halphen C, Kamali A, Nelson FM, Wolinsky JS, Narayana PA: Caudate nuclei volume, diffusion tensor metrics, and T(2) relaxation in healthy adults and relapsing-remitting multiple sclerosis patients: implications for understanding gray matter degeneration. J Magn Reson Imaging. 2009, 29: 70-77. 10.1002/jmri.21648.PubMed CentralView ArticlePubMedGoogle Scholar
- Walhovd KB, Fjell AM, Reinvang I, Lundervold A, Dale AM, Eilertsen DE, Quinn BT, Salat D, Makris N, Fischl B: Effects of age on volumes of cortex, white matter and subcortical structures. Neurobiol Aging. 2005, 26: 1260-1270.Google Scholar
- Raz N, Williamson A, Gunning-Dixon F, Head D, Acker JD: Neuroanatomical and cognitive correlates of adult age differences in acquisition of a perceptual-motor skill. Microsc Res Tech. 2000, 51: 85-93. 10.1002/1097-0029(20001001)51:1<85::AID-JEMT9>3.0.CO;2-0.View ArticlePubMedGoogle Scholar
- Raz N, Lindenberger U, Rodrigue KM, Kennedy KM, Head D, Williamson A, Dahle C, Gerstorf D, Acker JD: Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cereb Cortex. 2005, 15: 1676-1689. 10.1093/cercor/bhi044.View ArticlePubMedGoogle Scholar
- Oldfield RC: The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia. 1971, 9: 97-113. 10.1016/0028-3932(71)90067-4.View ArticlePubMedGoogle Scholar
- Sled JG, Zijdenbos AP, Evans AC: A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging. 1998, 17: 87-97. 10.1109/42.668698.View ArticlePubMedGoogle Scholar
- Collins DL, Neelin P, Peters TM, Evans AC: Automatic 3D intersubject registration of MR volumetric data in standardized talairach space. J Comput Assist Tomogr. 1994, 18: 192-205. 10.1097/00004728-199403000-00005.View ArticlePubMedGoogle Scholar
- Collins DL, Zijdenbos AP, Kollokian V, Sled JG, Kabani NJ, Holmes CJ, et al: Design and construction of a realistic digital brain phantom. IEEE Trans Med Imaging. 1998, 17: 463-468. 10.1109/42.712135.View ArticlePubMedGoogle Scholar
- Collins DL, Evans AC: ANIMAL: Validation and applications of nonlinear registration-based segmentation. Intern J Pattern Recognit Artif Intell. 1997, 11: 1271-1294. 10.1142/S0218001497000597.View ArticleGoogle Scholar
- Pruessner JC, Li LM, Serles W, Pruessner M, Collins DL, Kabani N, Lupien S, Evans AC: Volumetry of hippocampus and amygdala with high-resolution MRI and threedimensional analysis software: minimizing the discrepancies between laboratories. Cereb Cortex. 2000, 10: 433-442. 10.1093/cercor/10.4.433.View ArticlePubMedGoogle Scholar
- Pruessner JC, Collins DL, Pruessner M, Evans AC: Age and gender predict volume decline in the anterior and posterior hippocampus in early adulthood. J Neurosci. 2001, 21: 194-200.PubMedGoogle Scholar
- Ifthikharuddin SF, Shrier DA, Numaguchi Y, Tang X, Ning R, Shibata DK, Kurlan R: MR volumetric analysis of the human basal ganglia: normative data. Acad Radiol. 2000, 7: 627-634. 10.1016/S1076-6332(00)80579-6.View ArticlePubMedGoogle Scholar
- Peterson BS, Riddle MA, Cohen DJ, Katz LD, Smith JC, Leckman JF: Human basal ganglia volume asymmetries on magnetic resonance images. Magn Reson Imaging. 1993, 11: 493-498. 10.1016/0730-725X(93)90468-S.View ArticlePubMedGoogle Scholar
- Selemon LD, Goldman-Rakic PS: Longitudinal topography and interdigitation of corticostriatal projections in the rhesus monkey. J Neurosci. 1985, 5: 776-794.PubMedGoogle Scholar
- Yeterian EH, Pandya DN: Corticostriatal connections of extrastriate visual areas in rhesus monkeys. J Compar Neurol. 1995, 352: 436-457. 10.1002/cne.903520309.View ArticleGoogle Scholar
- Voss P, Collignon O, Lassonde M, Lepore F: Adaptation to sensory loss. WIREs Cog Sci. 2010, 1: 308-328. 10.1002/wcs.13.View ArticleGoogle Scholar
- Voss P, Zatorre R: Occipital cortical thickness predicts performance on pitch and musical tasks in blind individuals. Cereb Cortex. 2012, 22: 2455-2465. 10.1093/cercor/bhr311.View ArticlePubMedGoogle Scholar
- Konishi K, Bohbot VD: Spatial navigation strategies correlate with gray matter in the hippocampus of healthy older adults tested in a virtual maze. Front Aging Neurosci. 2013, 5: 1-8.PubMed CentralView ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.