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ISSN 1664-8714 ISBN 978-2-88919-541-1 DOI 10.3389/978-2-88919-541-1 About Frontiers Frontiers is more than just an open-access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers Journal Series The Frontiers Journal Series is a multi-tier and interdisciplinary set of open-access, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. 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What are Frontiers Research Topics? Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: researchtopics@frontiersin.org 2 June 2015 | The Cognitive Thalamus Frontiers in Systems Neuroscience Topic Editors: Yuri B. Saalmann, University of Wisconsin-Madison, USA Sabine Kastner, Princeton University, USA THE COGNITIVE THALAMUS Cognitive processing is commonly conceptualized as being restricted to the cerebral cortex. Accordingly, electrophysiology, neuroimaging and lesion studies involving human and animal subjects have almost exclusively focused on defining roles for cerebral cortical areas in cognition. Roles for the thalamus in cognition have been largely ignored despite the fact that the extensive connectivity between the thalamus and cerebral cortex gives rise to a closely coupled thalamo-cortical system. However, in recent years, growing interest in the thalamus as much more than a passive sensory structure, as well as methodological advances such as high-resolution functional magnetic resonance imaging of the thalamus and improved electrode targeting to subregions of thalamic nuclei using electrical stimulation and diffusion tensor imaging, have fostered research into thalamic contributions to cognition. Evidence suggests that behavioral context modulates processing in primary sensory, or first-order, thalamic nuclei (for example, the lateral geniculate and ventral posterior nuclei), Overlay plot of thalamic lesions in patient sample. Lesion volumes of all 14 patients are plotted on axial sections of a MNI brain template with numbers denoting z-coordinates in MNI space. Different colors denote the number of overlapping lesions per voxel, ranging from 1 to a maximum of 5 individual lesion volumes. Image display follows radiological convention with right hemisphere (R) shown on left side of picture. L, Left; R, Right hemisphere. (Figure 1 (A) from Ostendorf et al., 2013, Front. Syst. Neurosci., doi: 10.3389/fnsys.2013.00010). 3 June 2015 | The Cognitive Thalamus Frontiers in Systems Neuroscience allowing attentional filtering of incoming sensory information at an early stage of brain processing. Behavioral context appears to more strongly influence higher-order thalamic nuclei (for example, the pulvinar and mediodorsal nucleus), which receive major input from the cortex rather than the sensory periphery. Such higher-order thalamic nuclei have been shown to regulate information transmission in frontal and higher-order sensory cortex according to cognitive demands. This Research Topic aims to bring together neuroscientists who study different parts of the thalamus, particularly thalamic nuclei other than the primary sensory relays, and highlight the thalamic contributions to attention, memory, reward processing, decision-making, and language. By doing so, an emphasis is also placed on neural mechanisms common to many, if not all, of these cognitive operations, such as thalamo-cortical interactions and modulatory influences from sources in the brainstem and basal ganglia. The overall view that emerges is that the thalamus is a vital node in brain networks supporting cognition. Citation: Saalmann, Y. B., Kastner, S., eds. (2015). The Cognitive Thalamus. Lausanne: Frontiers Media. doi: 10.3389/978-2-88919-541-1 4 June 2015 | The Cognitive Thalamus Frontiers in Systems Neuroscience Table of Contents 05 The cognitive thalamus Yuri B. Saalmann and Sabine Kastner 07 A role of the human thalamus in predicting the perceptual consequences of eye movements Florian Ostendorf, Daniela Liebermann and Christoph J. Ploner 19 Cognitive control of movement via the cerebellar-recipient thalamus Vincent Prevosto and Marc A. Sommer 27 Functional roles of the thalamus for language capacities Fabian Klostermann, Lea K. Krugel and Felicitas Ehlen 35 Neural signal for counteracting pre-action bias in the centromedian thalamic nucleus Takafumi Minamimoto, Yukiko Hori, Ko Yamanaka and Minoru Kimura 46 The role of the anterior, mediodorsal, and parafascicular thalamus in instrumental conditioning Laura A. Bradfield, Genevra Hart and Bernard W. Balleine 61 The anterior thalamus provides a subcortical circuit supporting memory and spatial navigation Maciej M. Jankowski, Kim C. Ronnqvist, Marian Tsanov, Seralynne D. Vann, Nicholas F. Wright Jonathan T. Erichsen, John P. Aggleton and Shane M. O’Mara 73 ABL1 in thalamus is associated with safety but not fear learning Mouna R. Habib, Dan A. Ganea, Ira K. Katz and Raphael Lamprecht 81 What does the mediodorsal thalamus do? Anna S. Mitchell and Subhojit Chakraborty 100 Mediodorsal thalamus and cognition in non-human primates Mark G. Baxter 105 Thalamic mediodorsal nucleus and its participation in spatial working memory processes: comparison with the prefrontal cortex Shintaro Funahashi 118 Intralaminar and medial thalamic influence on cortical synchrony, information transmission and cognition Yuri B. Saalmann EDITORIAL published: 17 March 2015 doi: 10.3389/fnsys.2015.00039 Frontiers in Systems Neuroscience | www.frontiersin.org March 2015 | Volume 9 | Article 39 Edited and reviewed by: Maria V. Sanchez-Vives, Institució Catalana de Recerca i Estudis Avançats, Institut de Investigacions Biomèdiques August Pi i Sunyer, Spain *Correspondence: Yuri B. Saalmann, saalmann@wisc.edu Received: 24 January 2015 Accepted: 26 February 2015 Published: 17 March 2015 Citation: Saalmann YB and Kastner S (2015) The cognitive thalamus. Front. Syst. Neurosci. 9:39. doi: 10.3389/fnsys.2015.00039 The cognitive thalamus Yuri B. Saalmann 1 * and Sabine Kastner 2 1 Department of Psychology, University of Wisconsin – Madison, Madison, WI, USA, 2 Department of Psychology and Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA Keywords: mediodorsal thalamus, anterior thalamus, intralaminar thalamus, thalamocortical interactions, pulvinar The thalamus, once viewed as passively relaying sensory information to the cerebral cortex, is becoming increasingly acknowledged as actively regulating the information transmitted to corti- cal areas. There are a number of reasons for this change. First, evidence suggests that first-order thalamic areas, like the lateral geniculate nucleus, ventral division of the medial geniculate nucleus, and the ventral posterior nuclei, can modulate neural processing along the sensory pathways to the cortex according to behavioral context (O’Connor et al., 2002; McAlonan et al., 2008). Second, much of the thalamus receives relatively little input from the sensory periphery, instead receiving its major driving input from the cortex. This higher-order thalamus forms pathways between cor- tical areas, which can strongly influence cortical activity (Theyel et al., 2010; Purushothaman et al., 2012; Saalmann et al., 2012). Third, lesions to higher-order thalamic areas, such as the pulvinar and mediodorsal nucleus, can produce severe attention and memory deficits (Saalmann and Kastner, 2011; Baxter, 2013; Bradfield et al., 2013; Jankowski et al., 2013; Mitchell and Chakraborty, 2013), suggesting an important role for the thalamus in cognition. In this Research Topic, we bring together neuroscientists who study different parts of the thala- mus, particularly the higher-order thalamic nuclei, to highlight thalamic contributions to learning (Bradfield et al., 2013; Habib et al., 2013), memory processes (Baxter, 2013; Funahashi, 2013; Jankowski et al., 2013; Mitchell and Chakraborty, 2013; Saalmann, 2014), set-shifting (Bradfield et al., 2013; Minamimoto et al., 2014; Saalmann, 2014), language (Klostermann et al., 2013), as well as movement monitoring and control (Ostendorf et al., 2013; Prevosto and Sommer, 2013; Minami- moto et al., 2014). These studies incorporate a range of methods, from molecular to systems-level approaches, and connect rodent, non-human primate and human data, for a better understanding of human cognition. The first three articles focus on movement monitoring and motor control. Based on lesion data from clinical subjects, Ostendorf et al. (2013) show that the central thalamus makes an important contribution to predicting the perceptual consequences of eye movements. Focusing on cerebello- cortical pathways incorporating the central and ventral lateral thalamus, Prevosto and Sommer (2013) review evidence for thalamic modulation of movement processing based on cognitive requirements. Encompassing a number of thalamic nuclei, including the pulvinar, mediodorsal and ventral intermediate nuclei, Klostermann et al. (2013) discuss contributions of the thalamus and basal ganglia to language perception and production. The Research Topic continues on the theme of behavioral flexibility. Minamimoto et al. (2014) show that that the macaque centromedian nucleus, in the intralaminar thalamus, plays a role in counteracting behavioral biases, which contributes to flexible behavior via interactions with the basal ganglia. Bradfield et al. (2013) review evidence from rodent studies that another intralaminar thalamic nucleus, the parafascicular thalamus, also contributes to behavioral flex- ibility, whereas the mediodorsal thalamic nucleus plays a key role in acquiring goal-directed behavior. Next, the focus shifts to memory processes. Jankowski et al. (2013) review contributions of the anterior thalamus, and its interactions with the hippocampus and cortex, to memory processing and spatial navigation in rodents. This includes evidence for oscillatory activity at theta frequencies 5 | Saalmann and Kastner The cognitive thalamus in the anterior thalamus. Habib et al. (2013) investigate memory processes in the auditory thalamus, showing differ- ential molecular events underlying safety learning and fear conditioning. Finally, there are four reviews highlighting different functions of the large mediodorsal thalamic nucleus and its interactions with the prefrontal cortex in primates. Mitchell and Chakraborty (2013) discuss the effects of lesions of the mediodorsal thalamus, supporting its role in memory and other cognitive processes. Bax- ter (2013) argues that the mediodorsal thalamus regulates plastic- ity within prefrontal cortex as well as the flexibility of prefrontal- dependent operations. Funahashi (2013) reviews contributions of the mediodorsal thalamus to spatial working memory, includ- ing how interaction between the thalamus and prefrontal cor- tex can enable sensory-to-motor transformations of maintained information. To conclude, Saalmann (2014) proposes that the mediodorsal thalamus regulates synchrony between neurons in prefrontal cortex and, consequently, their information exchange according to cognitive control demands. This Research Topic highlights the key contributions of the thalamus to neural processing in cortico-cortical, hippocampo-cortical, cortico-striatal and cerebello-cortical path- ways. Although the underlying mechanisms of thalamic influ- ence on these pathways remain to be clarified, there is growing evidence that the thalamus plays a key role in dynamically rout- ing information across the brain (Saalmann et al., 2012; Xu and Sudhof, 2013). Such a role may involve flexibly synchronizing ensembles of neurons, thereby configuring brain networks for the current behavioral context. Taken together, the articles in this Research Topic show that thalamic interactions with cortical and subcortical areas are integral to behavioral flexibility, memory processes and cognition in general. References Baxter, M. G. (2013). Mediodorsal thalamus and cognition in non- human primates. Front. Syst. Neurosci 7:38. doi: 10.3389/fnsys.2013. 00038 Bradfield, L. A., Hart, G., and Balleine, B. W. (2013). The role of the anterior, mediodorsal, and parafascicular thalamus in instrumental conditioning. Front. Syst. Neurosci . 7:51. doi: 10.3389/fnsys.2013.00051 Funahashi, S. (2013). Thalamic mediodorsal nucleus and its participation in spatial working memory processes: comparison with the prefrontal cortex. Front. Syst. Neurosci . 7:36. doi: 10.3389/fnsys.2013.00036 Habib, M. R., Ganea, D. A., Katz, I. K., and Lamprecht, R. (2013). ABL1 in tha- lamus is associated with safety but not fear learning. Front. Syst. Neurosci . 7:5. doi: 10.3389/fnsys.2013.00005 Jankowski, M. M., Ronnqvist, K. C., Tsanov, M., Vann, S. D., Wright, N. F., Erich- sen, J. T., et al. (2013). The anterior thalamus provides a subcortical circuit supporting memory and spatial navigation. Front. Syst. Neurosci . 7:45. doi: 10.3389/fnsys.2013.00045 Klostermann, F., Krugel, L. K., and Ehlen, F. (2013). Functional roles of the thalamus for language capacities. Front. Syst. Neurosci 7:32. doi: 10.3389/fnsys.2013.00032 McAlonan, K., Cavanaugh, J., and Wurtz, R. H. (2008). Guarding the gate- way to cortex with attention in visual thalamus. Nature 456, 391–394. doi: 10.1038/nature07382 Minamimoto, T., Hori, Y., Yamanaka, K., and Kimura, M. (2014). Neural signal for counteracting pre-action bias in the centromedian thalamic nucleus. Front. Syst. Neurosci. 8:3. doi: 10.3389/fnsys.2014.00003 Mitchell, A. S., and Chakraborty, S. (2013). What does the mediodor- sal thalamus do? Front. Syst. Neurosci 7:37. doi: 10.3389/fnsys.2013. 00037 O’Connor, D. H., Fukui, M. M., Pinsk, M. A., and Kastner, S. (2002). Attention modulates responses in the human lateral geniculate nucleus. Nat. Neurosci. 5, 1203–1209. doi: 10.1038/nn957 Ostendorf, F., Liebermann, D., and Ploner, C. J. (2013). A role of the human thala- mus in predicting the perceptual consequences of eye movements. Front. Syst. Neurosci . 7:10. doi: 10.3389/fnsys.2013.00010 Prevosto, V., and Sommer, M. A. (2013). Cognitive control of movement via the cerebellar-recipient thalamus. Front. Syst. Neurosci 7:56. doi: 10.3389/fnsys.2013.00056 Purushothaman, G., Marion, R., Li, K., and Casagrande, V. A. (2012). Gating and control of primary visual cortex by pulvinar. Nat. Neurosci. 15, 905–912. doi: 10.1038/nn.3106 Saalmann, Y. B. (2014). Intralaminar and medial thalamic influence on cortical synchrony, information transmission and cognition. Front. Syst. Neurosci. 8:83. doi: 10.3389/fnsys.2014.00083 Saalmann, Y. B., and Kastner, S. (2011). Cognitive and perceptual functions of the visual thalamus. Neuron 71, 209–223. doi: 10.1016/j.neuron.2011.06.027 Saalmann, Y. B., Pinsk, M. A., Wang, L., Li, X., and Kastner, S. (2012). The pulvinar regulates information transmission between cortical areas based on attention demands. Science 337, 753–756. doi: 10.1126/science.1223082 Theyel, B. B., Llano, D. A., and Sherman, S. M. (2010). The corticothalamocortical circuit drives higher-order cortex in the mouse . Nat. Neurosci. 13, 84–88. doi: 10.1038/nn.2449 Xu, W., and Sudhof, T. C. (2013). A neural circuit for memory specificity and generalization. Science 339, 1290–1295. doi: 10.1126/science.1229534 Conflict of Interest Statement: The authors declare that the research was con- ducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Copyright © 2015 Saalmann and Kastner. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this jour- nal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Frontiers in Systems Neuroscience | www.frontiersin.org March 2015 | Volume 9 | Article 39 6 | ORIGINAL RESEARCH ARTICLE published: 23 April 2013 doi: 10.3389/fnsys.2013.00010 A role of the human thalamus in predicting the perceptual consequences of eye movements Florian Ostendorf 1,2 *, Daniela Liebermann 1 and Christoph J. Ploner 1 1 Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany 2 Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Berlin, Germany Edited by: Yuri B. Saalmann, Princeton University, USA Reviewed by: Klaus-Peter Hoffmann, Ruhr-University Bochum, Germany Werner Schneider, Bielefeld University, Germany Arvid Herwig, Bielefeld University, Germany *Correspondence: Florian Ostendorf, Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Luisenstr. 56, 10117 Berlin, Germany. e-mail: florian.ostendorf@charite.de Internal monitoring of oculomotor commands may help to anticipate and keep track of changes in perceptual input imposed by our eye movements. Neurophysiological studies in non-human primates identified corollary discharge (CD) signals of oculomotor commands that are conveyed via thalamus to frontal cortices. We tested whether disruption of these monitoring pathways on the thalamic level impairs the perceptual matching of visual input before and after an eye movement in human subjects. Fourteen patients with focal thalamic stroke and 20 healthy control subjects performed a task requiring a perceptual judgment across eye movements. Subjects reported the apparent displacement of a target cue that jumped unpredictably in sync with a saccadic eye movement. In a critical condition of this task, six patients exhibited clearly asymmetric perceptual performance for rightward vs. leftward saccade direction. Furthermore, perceptual judgments in seven patients systematically depended on oculomotor targeting errors, with self-generated targeting errors erroneously attributed to external stimulus jumps. Voxel-based lesion-symptom mapping identified an area in right central thalamus as critical for the perceptual matching of visual space across eye movements. Our findings suggest that trans-thalamic CD transmission decisively contributes to a correct prediction of the perceptual consequences of oculomotor actions. Keywords: efference copy, corollary discharge, visual stability, prediction, thalamus, human, lesion, sensorimotor INTRODUCTION Active perceptual exploration helps animals and humans to sam- ple relevant aspects of the external world, but constantly changes sensory input. These self-generated changes in sensory input (so-called reafference) would severely impair coherent percepts when not properly distinguished from environmental changes. Forward models have been proposed as a candidate mechanism to anticipate the perceptual consequences of actions by an inter- nal monitoring of corresponding motor commands (Wolpert and Miall, 1996). The existence of such internal monitoring sig- nals had been proposed for a long time as an efficient means to disambiguate self-induced displacements of perceptual input from external changes in the outside world (Purkynˇ e, 1825; Von Helmholtz, 1866). Important experimental support for internal monitoring processes was obtained by Von Holst and Mittelstaedt (1950) and Sperry (1950) who coined the hypothetical under- lying signal “efference copy” or “corollary discharge” (CD), respectively. Recently, single-unit recordings in non-human primates iden- tified a CD pathway that conveys oculomotor monitoring infor- mation from brainstem structures to the frontal eye field (FEF) via central portions of the thalamus (Sommer and Wurtz, 2002). Additional experimental evidence suggests that information car- ried through this pathway bears direct functional relevance for visuomotor behavior: transient inactivation of this pathway on the thalamic level impaired oculomotor behavior in a task that required internal monitoring of saccade metrics (Sommer and Wurtz, 2002). Similar findings have been observed in patients with focal thalamic stroke (Gaymard et al., 1994; Bellebaum et al., 2005), suggesting that trans-thalamic CD is critical for accu- rate generation of rapid oculomotor sequences. These findings do however not directly address the question whether trans- thalamic CD signals are also involved in anticipating the percep- tual changes imposed by saccades and whether CD signals may thus ultimately aid perceptual stability across eye movements. Recently, we aimed to address this question in a single patient with a focal ischemic lesion of the right central tha- lamus (Ostendorf et al., 2010). The behavioral assessment of CD function in this patient seemed warranted because of the close anatomical overlap of his focal lesion with the homolo- gous thalamic site in the monkey brain at which CD signals had been recorded (Sommer and Wurtz, 2002, 2004). We used a simple visuomotor task to assess a possible deficit in the per- ceptual matching of space across eye movements: subjects were instructed to report the apparent direction of an unpredictable target displacement that happened in temporal contingency with a saccadic eye movement to this target stimulus. Attenuation of motion perception during saccades (Burr et al., 1982) limits the usefulness of intrasaccadic motion cues to guide this percep- tual decision. Hence, surprisingly large object displacements can escape conscious detection when they take place during saccadic eye movements, a phenomenon called saccadic suppression of displacement (SSD; Bridgeman et al., 1975). However, small mod- ifications of the original task can lead to dramatic performance Frontiers in Systems Neuroscience www.frontiersin.org April 2013 | Volume 7 | Article 10 | SYSTEMS NEUROSCIENCE 7 Ostendorf et al. Human thalamus and corollary discharge improvements in healthy subjects (Deubel and Schneider, 1994; Deubel et al., 1996): a short blanking of the target reverses SSD to high perceptual sensitivity for displacement detection that can even exceed performance under steady fixation (Deubel et al., 1996). Thus, a faithful representation of target position is appar- ently retained across eye movements and can, at least under certain conditions, be combined with accurate and precise ocu- lomotor monitoring information to effectively guide perceptual judgments. Compared to age-matched control subjects, we observed a lateralized deficit for this task variant in the patient, manifest- ing as inaccurate matching of locations across eye movements (Ostendorf et al., 2010). He showed a systematic bias of per- ceptual reports toward apparent backward displacements that was consistent with an internal underestimation of eye move- ment amplitudes. Side and sign of this perceptual deficit were identical to additional impairments observed for the genera- tion of rapid saccade sequences, pointing toward a common disruption of internal monitoring underlying both behavioral deficits. Moreover, the putative deficit in eye movement mon- itoring led to a systematic dependency of perceptual decisions on saccadic errors in the patient (Ostendorf et al., 2010). While normal subjects can reliably predict trial-to-trial variations in eye movement targeting and anticipate the associated percep- tual mismatches (Collins et al., 2009), he systematically misat- tributed self-induced visual errors to external stimulus changes (Ostendorf et al., 2010). Taken together, behavioral deficits in this patient were consistent with an incomplete and noisy CD signal, leading to uncertain and hypometric estimates of executed eye movements. Here, we aim to address specificity and generalizability (Robertson et al., 1993) of our previous findings by probing perceptual performance in a larger sample of 14 patients who sustained focal thalamic lesions from ischemic stroke in differ- ent portions of the thalamus. As in our case study (Ostendorf et al., 2010), we used the original intrasaccadic displacement task in which SSD is expected to appear (Bridgeman et al., 1975) and the task variant proposed by Deubel et al. (1996) in which high perceptual sensitivity in normal subjects has been demon- strated repeatedly (Deubel et al., 1996; Collins et al., 2009). We compared perceptual performance in the patient group with a sample of control subjects in these two task variants. We capital- ized on intra-individual differences between task conditions and saccade directions (Bellebaum et al., 2005) to identify deficits in the trans-saccadic matching of visual space in individual patients. Beyond standard groupwise comparisons, the acquisition of high- resolution imaging data at the time of behavioral testing allowed us to perform voxel-based lesion-symptom mapping (Rorden and Karnath, 2004) in order to identify thalamic regions critical for task performance. METHODS SUBJECTS Fourteen patients with focal lesions of the thalamus [mean age ± standard deviation (SD), 40 6 ± 9 1 years; five females] partici- pated in this study. Patients were recruited from the Department of Neurology, Charité - Universitätsmedizin Berlin, Germany and were part of a patient cohort that had participated in a recent neuropsychological study (Liebermann et al., 2013). Twenty healthy subjects (38 8 ± 7 8 years; eight females) served as controls. Handedness was assessed by Edinburgh-Handedness- Inventory (Oldfield, 1971) with a laterality quotient of ≥ 40 and ≤ 40 denoting right and left-handedness, respectively. In the patient group, 13 subjects were right-handed, one left-handed and none ambidextrous (mean laterality quotient ± SD, 64 2 ± 36 2). 17 control subjects were right-handed, two left-handed, and one ambidextrous (mean laterality quotient ± SD, 68 3 ± 55 1). Average years of education ( ± SD) were 14.3 ( ± 2.8) in patients and 16.1 ( ± 2.3) in control subjects. No significant differences emerged for these demographic measures between patients and the control subjects. Control subjects had no his- tory of neurological or psychiatric disorders and all but one were naive with respect to the purpose of the study. Informed consent was obtained from all subjects before participation in the study, which was approved by the local Ethics Committee (Charité - Universitätsmedizin Berlin, Campus Mitte, Germany). Apart from a slight right-sided hemiparesis accompanied by prickling paresthesia in one patient (P11), neurological examina- tion was normal in all patients at the time of testing (see Table 1 for initial symptoms of individual patients). IMAGING AND LESION RECONSTRUCTION Imaging and lesion reconstruction was identical to Liebermann et al. (2013). In brief, structural imaging was performed on a clinical whole-body scanner (Magnetom Vision, Siemens) at 1.5 T. For reconstruction of lesions, a three-dimensional dataset was acquired, using a magnetization prepared rapid acquisition gradient-echo imaging sequence (MPRAGE, isotropic resolution 1 mm). To screen for additional extra- and intrathalamic lesions at the time of testing, axial images of the whole brain and coronal images of the thalamic region were acquired using a T2-weighted turbo inversion recovery magnitude sequence (whole brain and thalamus, voxel-size 0 91 × 0 9 × 5 mm and 0 95 × 0 9 × 2 mm, respectively). High-resolution imaging revealed no further lesions except for single lacunar lesions in four patients [left cerebel- lum, lobule VI (patient P6) and lobule VIIIb (patient P3), right cerebellum, lobule VI (patient P5), and genu of corpus callo- sum (patient P8)]. In addition, the thalamic lesion of one patient extended slightly into the right hypothalamus (patient P13). Individual brain scans were spatially normalized using MATLAB (The MathWorks, Natick, MA, USA) and the Statistical Parametric Mapping package (SPM5, Wellcome Department of Imaging Neuroscience, London, http://www fil ion ucl ac uk/ spm). Individual MRI data sets were normalized to a T1 Montreal Neurological Institute (MNI) template provided with SPM by using the unified segmentation and normalization function. This method has recently been demonstrated to provide reliable nor- malization of focally lesioned brains to template images (Crinion et al., 2007), although cost function masking might still be recommended for larger lesions (Andersen et al., 2010). For identification of affected thalamic nuclei in individual patients, lesions were co-registered to an atlas of the human thala- mus (Morel, 2007). Coronal reconstructions from MRI data sets were evaluated against corresponding atlas plates. Relative Frontiers in Systems Neuroscience www.frontiersin.org April 2013 | Volume 7 | Article 10 | 8 Ostendorf et al. Human thalamus and corollary discharge Table 1 | Demographic and lesion characteristics of patients. Patient Age Sex Years of education IQ TSL (months) Lesion side Lesion vol. (cm 3 ) Initial symptoms 1 51 F 9 94 22 R 0 13 Left hemiparesis and hypesthesia 2 45 M 13 130 0.25 L 0 06 Right hyp-/paresthesia 3 40 M 18 n/a 12 L 0 07 Right hemiparesis, diplopia 4 45 M 18 118 1 L 0 03 Anomic aphasia, dizziness 5 36 M 13 124 29 B (R > L) 0.03 Diplopia, anomic aphasia 6 43 F 13 n/a 12 B (L > R) 0.36 Vigilance disturbance, aphasia 7 31 M 13 112 8 R 0 12 Left hemiparesis and paresthesia, headache 8 53 M 12 100 1 R 2 35 Left hemiparesis, ataxia, vigilance disturbance, dizziness 9 25 F 13 101 0.5 R 0 21 Headache, nausea 10 37 M 13 118 10 R 0 2 Left hemiparesis, amnesia 11 57 F 13 118 60 L 0 15 Right hemiparesis and paresthesia* 12 39 M 18 130 11 R 0 26 Diplopia, dysarthria, vertigo 13 32 F 18 124 2 L 0 2 Right hemiparesis, diplopia, vertigo 14 34 M 16 118 45 B (R > L) 1.13 Right hemiparesis, diplopia, dysarthria, loss of consciousness Asterisk indicates persistent symptom (only patient P11). Abbreviations: Lesion vol., lesion volume; TSL, time since lesion. lesion extent for a given thalamic nucleus was rated in three increments (less than 1/3, between 1/3 and 2/3, more than 2/3 of nucleus volume affected, see Figure 1B ). Lesion over- lap and subtraction plots (Rorden and Karnath, 2004) were generated on a group level for further lesion-to-symptom map- ping. For this analysis, lesions were manually traced in normal- ized three-dimensional space with MRIcron software (version as of December 2012, www mccauslandcenter sc edu/mricro/ mricron/index html). Estimation of lesion volume and lesion overlap and subtraction analyses (Rorden and Karnath, 2004) were conducted with resulting volumes of interest (VOIs) in MRIcron. For further statistical analysis we used non-parametric voxel-based lesion-symptom mapping as implemented in NPM, which is part of the MRIcron software package. Only voxels that were lesioned in at least 2 patients were included in this analysis. EXPERIMENTAL SET-UP AND TASK The intrasaccadic displacement task was identical to Ostendorf et al. (2010). Stimuli were presented on a 22-in. CRT-monitor (screen resolution, 1024 × 768 pixels; refresh rate, 110 Hz) at a viewing distance of 50 cm. Subjects’ heads were stabilized by a head- and chinrest. Eye movements were recorded with high- speed video-oculography (Sensomotoric Instruments; sampling rate, 500 Hz) of the right eye. Experiments were carried out in an otherwise darkened room. Subjects completed the experiments in multiple test sessions on different days. All stimuli were white (luminance, 56.5 Cd/m 2 ) and presented on a homogenous gray background (luminance, 13.1 Cd/m 2 ). Trials started with presentation of a fixation cross (extent, 0.5 ◦ ) at 6 or 8 ◦ left or right from screen center (see Figure 2 for task schematic). After a variable foreperiod (1600–2400 ms), the fixation cross was switched off and a target cue (diame- ter, 0.5 ◦ ) was presented at the other screen side at 6 or 8 ◦ eccentricity, respectively. Subjects were instructed to perform a saccadic eye movement toward this target, which was switched off during saccade execution and reappeared either directly (STEP condition) or after a temporal gap of 250 ms (BLANK condi- tion) at an unpredictable position. Target displacement for a given trial was adapted by three independent, randomly inter- leaved staircases with a constant step size of 3 ◦ in the STEP task (BLANK task, 1.5 ◦ ). Specifically, when the subject indi- cated a target displacement to the left for a given displacement level, the next displacement level for a given staircase would be shifted by 3 ◦ (BLANK task, 1.5 ◦ ) to the right, i.e., stair- cases followed a one-up, one-down logic. Staircases started at a displacement level of 7 ◦ (GAP task, 3.5 ◦ ) right- and leftward and 0 ◦ (no displacement) with respect to initial target position. Interleaved displacement levels for the three staircases enabled sampling the point of subjective target constancy with a res- olution of 1 ◦ (BLANK task, 0.5 ◦ ) while collecting a sufficient number of trials at higher confidence levels. In both conditions, subjects reported the apparent jump direction by pressing one of two manual response keys. Response registration was limited to maximally 5 s and the target was switched off when a key press was recorded or maximum response time had elapsed. The screen was then blanked for 1600 ms and a next trial started. Saccade direction was fixed within five to six blocks of 24 trials each. DATA ANALYSIS Eye movement data were low-pass filtered, visualized, and ana- lyzed in Matlab by using the ILAB toolbox (Gitelman, 2002) and self-written routines. Saccade onset and offset were determined by a fixed velocity criterion (threshold, 30 ◦ /s). Start and end posi- tions were determined as fixation periods preceding saccade onset and following saccade end. We ensured that intrasaccadic tar- get displacements occurred during the first half of the saccadic eye movement [mean delay after saccade onset ( ± SD), 19 ( ± 4) ms; see lower right panel in Figure 2 ]. Cumulative gaussians were Frontiers in Systems Neuroscience www.frontiersin.org April 2013 | Volume 7 | Article 10 | 9 Ostendorf et al. Human thalamus and corollary discharge FIGURE 1 | (A) Overlay plot of thalamic lesions in patient sample. Lesion volumes of all 14 patients are plotted on axial sections of a MNI brain template with numbers denoting z-coordinates in MNI space. Different colors denote the number of overlapping lesions per voxel, ranging from 1 to a maximum of 5 individual lesion volumes. Image display follows radiological convention with right hemisphere (R) shown on left side of picture. L, Left; R, Right hemisphere. (B) Affected thalamic nuclei, as determined by co-registration of individual MRI to an established atlas of the human thalamus (Morel, 2007). Relative lesion extent for a given nucleus is displayed in three increments: White, not affected, light gray, less than 1/3 of total volume affected, dark gray, between 1/3 and 2/3 affected, black, more than 2/3 affected. Patients are labeled by ascending numbers. Abbreviations: AV, anteroventral nucleus; VA, ventral anterior nucleus; Mtt, mamillothalamic tract; MD, mediodorsal nucleus; CeM, central medial nucleus; CL, central lateral nucleus; CM, centromedian nucleus; Pf, parafascicular nucleus; VL, ventral lateral nucleus; VM, ventral medial nucleus; VP , ventral posterior nucleus; Pul, pulvinar; R, reticular nucleus. fitted to the perceptual response data in Matlab by using psig- nifit, a toolbox that implements the maximum-likelihood method described by Wichmann and Hill (2001). From psychometric functions, we determined the point of subjective target station- arity (PSS) as a measure of bias in perceptual reports and the standard deviation of the fitted cumulative gaussian as a mea- sure of just-noticeable difference (JND). For easier comparison of perceptual performance between conditions and subjects, we converted the psychometric function to percent correct (discard- ing trials with null displacement) and averaged resulting values for corresponding negative and positive displacement levels. We determined a perceptual threshold as the absolute displacement needed to achieve correct responses in 75% of trials (Ostendorf et al.,