In sum, our results demonstrate that the reading problems experienced by children with dyslexia are not a consequence of visual magnocellular dysfunction. While visual magnocellular weakness does manifest in dyslexia, it is not the cause of the reading problem. Second, the weaknesses in the magnocellular visual system, indexed in this

study by the amount of activity in area V5/MT during the perception of visual motion, do not represent a symptom of dyslexia. They are not, Bortezomib ic50 as previous models assumed, part of a common etiology with different behavioral manifestations and thereby an integral part of the pathophysiology of dyslexia. Rather, they are a secondary consequence of reading experience itself. We suggest that phonological deficits, by restricting the amount and quality of reading in dyslexics, limit the opportunity for reading to induce changes in the visual magnocellular system (by mechanisms that remain to be determined). As such, reading itself can be thought of as an environmental influence that bears on functional and anatomical aspects of the brain and, in the case of reading disability, these changes are not invoked to the same degree as they are in typical MDV3100 research buy readers. In the context of the observed differences at the level of the LGN, larger neurons in the controls relative to the dyslexic at postmortem could be due to extensive versus limited experience with reading over

a lifetime. The same explanation holds to account for the differences between dyslexics and age-matched controls in behavioral studies

of magnocellular function and brain imaging studies of V5/MT. Together, our results represent not only an important advancement in understanding the etiology of developmental dyslexia, but also offer a reinterpretation of the existing data on visual magnocellular dysfunction in dyslexia. They also contribute to an important growing body of work that explains how experience, in this case for reading, alters the functional organization of the brain. Subjects participating in all three experiments were native English speakers with no history of neurological or psychiatric disorder, and all Ketanserin had normal or corrected-to-normal visual acuity. Written informed consent was obtained from the subjects themselves or from the subjects’ parents (in the case of pediatric participants), and all procedures were approved by the Georgetown University Institutional Review Board. All subjects completed a battery of behavioral tests to evaluate intelligence and proficiency on reading and reading-related skills, including the Wechsler Abbreviated Scale of Intelligence Verbal and Performance tests (IQ), Woodcock-Johnson III (WJ-III) Word Identification (WID, single real word reading), and Woodcock-Johnson Word Attack (WA, single pseudoword reading). Subjects in Experiment 3 also completed the Lindamood Auditory Conceptualization Test (LAC-3, phonemic awareness).

Although the reported effects of attention and rivalry have been variable when Hydroxychloroquine mouse measure physiologically in V1 (e.g., Tong et al., 2006; Reynolds and Chelazzi, 2004), this could be due to a variety of factors including variability in the properties of the stimuli used, such as stimulus contrast and size, which under the normalization framework, predict variable levels of modulation. Ultimately, however,

psychophysical methods can only go so far in pinpointing the neural locus of such effects, and further work in neuroimaging and electrophysiology may shed further light on where in the visual processing hierarchy attention modulates the neural events Selleckchem 5FU underlying visual competition. In summary, our results support a normalization model for visual competition, in which attention plays a crucial role in regulating the neural contrast

response. Attention has long been known to affect rivalry, with some studies reporting that attention modulates the temporal dynamics of binocular rivalry (Paffen and Alais, 2011; Mitchell et al., 2004), and others reporting that rivalry does not occur in the absence of attention in certain early visuocortical areas (Lee et al., 2007; Zhang et al., 2011; Watanabe et al., 2011). While these studies suggest that attention can modulate rivalry, our results and model reveal that these two processes are even more intricately intertwined: visual awareness during dominance

phases of rivalry dictates what receives attention and what does not, which in turn interacts with normalization to determine the gain of the neural response. Four observers participated in the study. All 3-mercaptopyruvate sulfurtransferase had normal or corrected-to-normal vision and gave written consent in compliance with the protocol approved by the Institutional Review Board at Vanderbilt University. Stimuli were generated on a Macintosh running Matlab and the Psychophysics Toolbox (Brainard, 1997; Pelli, 1997). Observers viewed the display in a darkened room on a gamma-corrected CRT (21” Sony MultiScan; refresh rate: 100 Hz). Observers’ heads were stabilized with a chin and forehead rest, 96 cm from the display. The display was viewed through a mirror stereoscope that presented the left half of the display exclusively to the left eye and the right half of the display exclusively to the right eye. Throughout the experiment, each eye viewed a fixation point (0.14° × 0.14°), along with circular fusion frames (9° × 9°) to help stabilized binocular eye alignment (Figure 1). In each trial, stimuli were presented dichoptically, with both eyes viewing orthogonally oriented filtered noise patches.

, 2011; Gandy and DeKosky, 2013; Malenka and Malinow, 2011; Vaillend et al., 2002). Ultimately, the value of Shank mutant mice will depend critically on the ability to use human patients to validate their predictive utility. Recently, whole genome sequencing technology has successfully identified a list of candidate genes in ASD ( Bi et al., 2012; Chahrour et al., 2012; Iossifov et al., 2012; Neale et al., 2012; O’Roak et al., 2011; Sanders et al.,

2012), and this list will likely expand in the future. Because of the rarity of sequence variants across selleckchem the population, it has been challenge to establish a causal role for specific variants in human disease. Functional studies are thus a critical component to determine the pathogenicity of specific genetic variants. The lesson learned from modeling SHANK mutations in mice will almost certainly be valuable to modeling other ASD candidate genes in the future. We thank Juliet www.selleckchem.com/products/PD-0332991.html Hernandez, Benjamin Philpot, Dan Smith, Julia Sommer, and William Wetsel for critical review of the manuscript. We thank Xiaoming Wang and Alexandra Bey for help preparing tables and comments. Work in the lab of Y.-h.J. is supported by Autism Speaks, Phelan-McDermid

Syndrome Foundation, and NIH grants 5K12-HD0043494-08 and R01MH098114-01. Work in the lab of M.D.E. is supported by Pfizer, Inc., and M.D.E. is an employee and shareholder of Pfizer, Inc. “
“The mammalian neocortex plays an important role in higher brain function including cognition, sensory perception, associative learning, and goal-directed motor control. The neocortex is organized in such a way that it is both highly specialized, with defined areas dedicated to specific functions and/or sensory modalities, and highly integrative, with each area receiving converging inputs from Resminostat different thalamic nuclei, other cortical areas, and several neuromodulatory systems. All these inputs are integrated in local neocortical microcircuits, generally considered to be composed of six layers of interconnected excitatory and inhibitory neurons. Early investigations of neocortical

function revealed similar receptive field properties of neurons aligned perpendicular to the brain surface in radial cortical columns (Mountcastle, 1957; Hubel and Wiesel, 1962; Simons, 1978). In primary sensory cortical areas, sensory inputs relayed by the thalamus mainly impact the “granular” layer 4 (L4), which in turn signals to the whole cortical column (although it is important to note that there is also significant direct thalamic input to other layers). The deep infragranular layer 5 (L5) and layer 6 (L6) are the main source of cortical outputs to subcortical structures (such as thalamus, striatum, and brainstem), and layers 2 and 3 (L2/3) contribute an important source of projections to other cortical areas.

Spine

volumes, densities, and turnover rates were analyzed in 3D using custom software. Because spine addition rates can vary between cultures and experimental buy LY294002 days, spine addition rates are reported as a percent of matched controls (calculated using all spines gained in the three posttreatment time points). Absolute spine addition and loss rates for all experiments are documented in Table S1. We prepared 1,000× stocks by dissolving MG132 (A.G. Scientific) and KN-93 (Tocris) in DMSO and bicuculline (Tocris), lactacystin (EMD Biochemicals), myristoylated PKI 14–22 amide (Tocris), Rp-cAMPS (Tocris), and CPP (Sigma) in water. Vehicle controls were matched in identity and volume to that in which the inhibitor was dissolved. When two drugs were applied, the vehicle consisted of the sum of the vehicles for both drugs. Slices were imaged at 30°C in magnesium-free ACSF containing 5 mM MNI-caged-glutamate. Image stacks were acquired immediately before and after the uncaging stimulus, which consisted of 50 pulses (720 nm, ∼12 mW at the sample) of 4 ms duration delivered at 5 Hz by parking

the beam at a point ∼0.5 μm from the edge of a secondary or tertiary apical dendrite. No more than four uncaging trials were performed on the same neuron. The success rate of de novo spine outgrowth was determined by two blind evaluators. Comparison of success rate across conditions was made by Fisher’s click here exact test. Error bars represent standard error of the mean and significance was set at p = 0.05 (two-tailed t test, unless otherwise noted). All statistics were calculated across cells. ∗p < 0.05 and ∗∗p <

0.001. We thank Judy Callis, Aldrin Gomes, and Jim Trimmer for advice and reagents; Lauren Boudewyn, Julie Heiner, and Sarah Mikula for help with experiments and analysis; and Elva Diaz, Jim Trimmer, and Georgia Woods for critical reading of the manuscript. This work was supported by a Burroughs Wellcome Career Award in the Biomedical Sciences (K.Z.), an NSF CAREER Award (0845285 K.Z. and H.V.R.), and the NIH (T32GM007377 A.M.H.; MARC-GM083894 H.V.R.; NS062736 K.Z., A.M.H., Bay 11-7085 and H.V.R.; NS054732 G.N.P.; AG017502 J.W.H. and I.S.S.). H.V.R. was a participant in the BUSP Program (supported by NIH-IMSD GM056765, HHMI 52005892). “
“Huntington’s disease (HD) is an autosomal dominant neurodegenerative disease caused by a CAG expansion in exon 1 of the huntingtin gene (Huntington’s Disease Collaborative Research Group, 1993). This mutation translates into an elongated glutamine tract in the N terminus of the huntingtin protein. Patients with HD display progressive movement dysfunction, including hyperkinetic involuntary movements, chorea, and dystonia, as well as cognitive impairments. Presently, there is no effective treatment for HD. The majority of potential therapies now under development are aimed at ameliorating symptoms of one of several proposed molecular consequences of mutant huntingtin, i.e.

, 1998). Therefore, it is possible that extracellular concentrations of endogenous DBI peptides in discrete areas such as nRT are at a lower level that is more likely to exert PAM rather than NAM effects. In contrast to the stark nRT versus VB differences in physiological PAM effects of DBI, immunoreactivity to DBI was observed in both nRT Metabolism inhibitor and VB (Figure 5). In this regard, it is important to note that DBI is also known as ACBP and the Dbi/Acbp gene is thought to ubiquitously serve housekeeping functions ( Knudsen et al., 1993), generating

an intracellular protein critically involved in facilitating intracellular transport of Acyl-CoA. We hypothesize that the nRT versus

VB differences in the electrophysiological findings likely represent nucleus-specific differences in the extracellular release and processing of DBI. In the current studies, we used a viral strategy to examine whether Dbi gene products are necessary and sufficient to produce endozepine actions in nRT. Although it is possible that viral introduction of DBI into a system in this way induces changes in its modulatory effects, it is unlikely that this explains the PAM actions observed here, as a recent report using similar viral vectors to express DBI and ODN Dabrafenib nmr in the SVZ exclusively observed NAM effects ( Alfonso et al., 2012). The mechanism(s) underlying these differences remain to be determined, though one possible explanation is differential intra- or extracellular processing of DBI, the nature of which is specific to certain areas or cell types. It is certainly

conceivable that some DBI fragments exert PAM effects, whereas others are NAMs. In addition, preliminary evidence suggests that exogenous application of DBI does not alter sIPSCs in VB (C.A.C. and however J.R.H., unpublished data), in contrast to the robust potentiation of uncaging responses when VB sniffer patches are placed in nRT. This further supports a working model in which nRT-specific processing of Dbi gene products underlies the PAM actions. Strikingly, endogenous BZ-mimicking potentiation was observed in nRT, but not in adjacent VB thalamus. This raises the question of why such effects would be specifically localized to nRT, and not VB. Perhaps selection pressure led to evolution of an adaptive specific subcircuit modulation in nRT that reduces the possibility of seizure occurrence. Synaptic inhibition in nRT exerts a prominent desynchronizing effect to reduce the propensity for oscillatory activity (von Krosigk et al., 1993; Huntsman et al., 1999; Schofield et al., 2009), and potentiation of synaptic inhibition by BZs further suppresses oscillations (Huguenard and Prince, 1994a; Sohal and Huguenard, 2003; Sohal et al., 2003).

By deleting GluN2A or GluN2B during early postnatal development, a period of rapid synaptogenesis, we found that

both subunits negatively regulate synaptic AMPAR expression, but by distinct means. We show that, similar to GluN1 deletion (Adesnik et al., 2008), deletion of GluN2B increases the number of functional synapses, suggesting a basal role for GluN2B-containing NMDARs in GDC-0199 maintaining silent synapses in early development. Conversely, deletion of GluN2A increases synaptic strength without affecting the number of unitary connections. These results suggest that when significant bursts of activity drive the synaptic insertion of AMPARs and the recruitment of GluN2A-containing receptors, GluN2A functions to dampen further synapse potentiation. The hippocampal

CA3-to-CA1 synapse is a model excitatory synapse that has been used to delineate the mechanisms of synaptic plasticity. Using conditional KO alleles for GluN2A (Grin2afl/fl; see Figure S1A available online) and GluN2B (Grin2bfl/fl) ( Akashi et al., 2009), we eliminated the target gene in a small subset of hippocampal neurons by transcranial stereotactic injection of P0-P1 mice with a recombinant adeno-associated Sunitinib research buy virus expressing a Cre-GFP fusion protein (rAAV1-Cre-GFP) ( Kaspar et al., 2002). Figure 1A shows a typical acute slice made from a P18 mouse after P0 injection demonstrating sparse infection of CA1 pyramidal neurons. It has long been suspected ADP ribosylation factor from in situ hybridization, single-cell reverse-transcriptase polymerase chain reaction, and pharmacologic studies that hippocampal CA1 pyramidal neurons express primarily GluN2A and

GluN2B subunits (Garaschuk et al., 1996, Watanabe et al., 1992 and Zhong et al., 1995). By cross-breeding the Grin2afl/fl (ΔGluN2A) and Grin2bfl/fl (ΔGluN2B) mice, we generated Grin2afl/flGrin2bfl/fl (ΔGluN2AΔGluN2B) mice and simultaneous whole-cell recording from a Cre-expressing cell (green trace in inset), and a control cell in the presence of NBQX revealed a complete loss of NMDAR-EPSCs ( Figure 1B, inset). We followed the time course of subunit depletion by measuring the ratio of NMDAR-EPSCs from Cre-expressing cells to control cells after P0 injection, and demonstrated a gradual decrease in NMDAR-EPSCs and complete loss consistently by P15 ( Figure 1B), similar to the rate of loss of NMDAR-EPSCs in Grin1fl/fl mice (ΔGluN1). These data indicate that, in addition to obligatory GluN1 subunits, synaptic NMDA receptors in CA1 pyramidal neurons contain only GluN2A and GluN2B. Since the NMDA-EPSCs were entirely gone by P15 in the double conditional KO mice, we performed all subsequent analyses of ΔGluN2A and ΔGluN2B mice after P17 unless indicated.

2c and GCaMP2.0, whereas there was no significant difference between the basal fluorescence of GCaMP2.0

and GCaMP2.2c ( Figures S1B and S1C). In addition, we found that fluorescence intensity CH5424802 concentration changes elicited by 100 μM ATP are ∼1.9-fold (1.9 ± 0.1, n = 56) and ∼3.2-fold (3.2 ± 0.3, n = 61) higher in cells expressing GCaMP2.2c and GCaMP3 than in cells expressing GCaMP2.0, respectively ( Figure S1D). The studies above indicate that GCaMP2.2c has a low basal fluorescence with a modest fluorescence change in response to stimulation, whereas GCaMP3 shows higher basal fluorescence and a more robust change in fluorescence after stimulation. Because GCaMP (and any GECI) binds calcium, there is a risk of neuronal toxicity associated with calcium binding and expression level. To increase the chances of finding lines with both strong signal and low toxicity, we generated both GCaMP2.2c and GCaMP3 transgenic lines. To generate GCaMP transgenic mice, we used the RG7204 clinical trial well-characterized Thy1 promoter to express GCaMPs in neurons. We generated eight founder lines of GCaMP2.2c and six founder lines of GCaMP3. Our previous studies have shown that the Thy1 promoter predominantly drives transgene expression in projection neurons in the CNS. Due to strong transgenic position-effect variegation, a Thy1-driven

transgene is often stochastically and differentially expressed in subsets of neurons in different transgenic lines ( Feng et al., 2000; Young et al., 2008). Consistent with these findings, we found that all founder lines differed in levels and patterns of expression. For further characterization, we focused on Thy1-GCaMP2.2c SB-3CT line 8 and Thy1-GCaMP3 line 6 because these lines had the

highest levels of transgene expression. Both lines of mice are born at the expected Mendelian rate and are healthy with no apparent histological or behavioral abnormality. GCaMP2.2c and GCaMP3 expression in these lines was widespread in the CNS including cortex, hippocampus, thalamus, cerebellum, superior colliculus, amygdala, brain stem, retina, and spinal cord ( Figures 1A, 1B, and 2; Figure S2). However, some notable differences in expression between the two lines were observed. For example, although both lines have expression in layer V neurons of the cortex, expression in layer II/III is more widespread in the Thy1-GCaMP3 line ( Figures 1B, 1Bb1, and 1Bb2) compared to the Thy1-GCaMP2.2c line ( Figures S2B, S2Bb1, and S2Bb2). In addition, Thy1-GCaMP3 mice, but not Thy1-GCaMP2.2c mice, showed high expression in olfactory bulb ( Figures 1A and 2). At the single cell level, both GCaMP2.2c and GCaMP3 were homogeneously distributed in the cytoplasm without nuclear localization ( Figures 1B, 1Bb1, and 1Bb2; Figures S2B, S2Bb1, and S2Bb2). We further examined the effect of long-term GCaMP expression in both GCaMP transgenic lines.

The largest differences in firing rate were present immediately following the target onset. Third, the same proportions of neurons were coherently active immediately following target onset and during the late-delay epoch despite the difference in firing rates between these epochs. Fourth, although coherent activity can be detected more easily when the firing rate is higher (Zeitler et al., 2006), the number of false positives resulting from the statistical testing procedure we use does not vary with firing rate in the

absence of coherent activity (see Supplemental Information; see also [Maris et al., 2007]). Finally, we recalculated SFC after decimating the firing rate of the significantly coherent units by 50% to match the firing rate of those units not coherent with the local fields. We found that, after decimation, 29/34 (85%) remained significantly coherent with LFP. Consequently, although there was a difference between the firing rate of coherent and Ruxolitinib research buy selleck chemicals llc not coherent cells, the difference in firing rate we report here was not due to

a confounding influence of firing rate on coherence. To determine whether coherent and not coherent spiking predicted RT, we performed an ANOVA to determine whether individual neurons showed significant differences in firing rate between the fast and slow RT trials. We found that before a reach and saccade, 21% of coherent cells have significant (p < 0.05) differences in firing rate between fast and slow unless RRT groups and 9% have significant differences between fast and slow SRT groups. Of these recordings, 70% showed a decrease in firing rate with faster RTs and the remaining 30% showed an increase in firing rate. We also found that only 3% of coherently active cells are significantly selective for SRT during the saccade alone task, which is within the expected proportion of false positives

(5%). Finally, and most importantly, when cells are not coherently active, fewer than 5% of cells show significantly selective differences in firing rate for the fast and slow reaction times for all combinations of task and RT type (reach and saccade, RRT: 4%; reach and saccade, SRT 0%; saccade alone, SRT 4%). To quantify the extent to which populations of cells with coherent and not coherent spiking predicted RT, we used a decoding algorithm to predict the RT from each cell population (Figure 5C; see Experimental Procedures). Unlike the LFP analysis, which was done using fixed proportions of fast and slow trials, the population decoding algorithm required that we use a fixed number of trials in each group. We analyzed the fastest or slowest 25 trials (SRT or RRT) in the preferred direction. Ideally, more trials would be available to perform a multiple neuron decoding analysis but this was the largest number of trials available in the database of neuronal recordings for which there was no overlap between the RTs for the fast and slow groups.

, 2010a). Therefore, we expressed CNIH-2 in slice cultures made from γ-8 KO mice and found that CNIH-2 not only rescued the amplitude of the AMPAR-mEPSCs (Figure 7A) but also markedly slowed mEPSC responses, such that the kinetics were considerably slower than what is seen in wild-type neurons or when CNIH-2 is overexpressed in wild-type neurons (Figure 7B). These data are compelling VX-770 for several reasons. One, they show that CNIH-2 effects on AMPAR kinetics are similar in HEK cells and in neurons lacking γ-8. Two, they emphasize the critical role that γ-8 has in determining the effects of CNIH-2/-3 on AMPAR kinetics. And three, they demonstrate that CNIH proteins are able to associate with

synaptic AMPARs. Although we maintain that the primary role for CNIH proteins is in the selective trafficking of GluA1A2 heteromers to synapses, the presence of CNIH

protein on the surface of neurons (Figure 5G) and the ability of CNIH-2 to influence gating properties of synaptic AMPARs in the absence of γ-8 (Figure 7B) are consistent with a selective and likely inert association of CNIH protein with GluA1 subunits of native synaptic GluA1A2 heteromers in the presence of γ-8. In this study, we used a variety of approaches, including the generation of conditional KO mice for CNIH-2 and CNIH-3, to determine the role of cornichon proteins in the regulation of neuronal AMPARs. By deleting CNIHs from neurons, we reveal a critical role for these HSP inhibitor proteins in regulating AMPAR-mediated synaptic transmission because there is a profound loss of AMPAR currents in KO neurons. We have demonstrated that under native conditions, CNIH is saturating, and the KD or KO of CNIHs is essential

for studying their roles in neurons. Furthermore, we find an unanticipated subunit specificity, in that CNIH-2/-3 preferentially interact with and functionally regulate GluA1-containing AMPARs. Strikingly, CNIH-2/-3 KO neurons phenocopy GluA1 KO neurons with respect to their current amplitudes, kinetics, and synaptic plasticity. All of our findings are most consistent with a model in which the primary role of CNIH-2/-3 in CA1 pyramidal neurons is the selective trafficking of GluA1-containing receptors to synapses. Figure 8 summarizes the proposed interactions between γ-8 and CNIH with surface AMPAR subunits. This model is based primarily on data in which γ-8 and CNIH are expressed aminophylline with the various AMPAR subunits in HEK cells but, as we discuss below, is strongly supported by our data from CA1 pyramidal neurons. We propose based on the IKA/IGlu ratio, a sensitive assay for TARP stoichiometry (Shi et al., 2009), that all AMPAR subunit combinations presented in Figure 8 contain four γ-8 as shown in HEK cells for AMPAR homomers (Figures 6Aii and S7) and in neurons for AMPAR heteromers (Figures 1I and S4C). The rest of this discussion concerns the number of CNIH proteins associated with the various AMPAR subunit combinations.

Flexibility tests included active range of motion (ROM) measurements for the

trunk and hip joints, as well as a sit-and-reach test. ROM measurements for trunk flexion, extension, rotation, and hip extension were based on Norkin and White.19 Trunk flexion and extension ROM were assessed by measuring the distance between C7 and S1 while standing in neutral position (neutral length). To locate C7 and S1, the examiner palpated the vertebrae and marked them with a pen. The participant forward flexed as far as possible with the pelvis stabilized. The length between C7 and S1 was remeasured, ALK inhibitor and the difference in lengths (neutral and flexed) was recorded as the trunk flexion ROM. Similarly, for trunk extension, the participant extended as far as possible with the pelvis stabilized. The distance between C7 and S1 was remeasured and the length difference from neutral position was the trunk extension ROM. To measure trunk rotation, the participant sat on a chair with their feet on the floor and their trunk and head in neutral position. The participant rotated their trunk and head as far as possible in both directions. A 30-cm plastic goniometer was positioned HIF inhibitor review so the fulcrum was above the center of the participant’s head. The stationary arm was parallel to the imaginary

line between the iliac crests, and the movement arm aligned with an imaginary line between the acromial processes of the shoulders. Active hip extension was measured with the participant in the prone position, knees extended,

and pelvis stabilized. The fulcrum of the 30-cm plastic goniometer was Ergoloid positioned over the greater trochanter, while the stabilizing arm was aligned with the lateral midline of the pelvis. Following maximal active hip extension, the movement arm was aligned with the lateral midline of the femur. Active hip internal and external rotation ROMs were measured using the method described by Ellison et al.20 The participant was positioned in the prone position with their hip positioned in neutral position and knee flexed at 90°. The non-testing leg was placed at 30° of hip abduction with the knee extended and pelvis stabilized. The 30-cm plastic goniometer was positioned with the stabilizing arm aligned vertically, while the movement arm was aligned along the shaft of the tibia. The sit-and-reach test was performed using the protocol listed in the American College of Sports Medicine (ACSM) Guidelines.21 The participants sat with their shoes on and the feet resting against a sit-and-reach box. The examiner extended and stabilized their knees. They positioned one hand on top of the other with palms down. They were requested to lean as far as possible along the measurement scale without flexing their knees. The furthest distance reached along the scale was recorded to the nearest 0.5 cm. The average of two trials was documented.