- Open Access
Atypical multisensory integration in Niemann-Pick type C disease – towards potential biomarkers
© Andrade et al.; licensee BioMed Central Ltd. 2014
- Received: 17 March 2014
- Accepted: 16 September 2014
- Published: 20 September 2014
Niemann-Pick type C (NPC) is an autosomal recessive disease in which cholesterol and glycosphingolipids accumulate in lysosomes due to aberrant cell-transport mechanisms. It is characterized by progressive and ultimately terminal neurological disease, but both pre-clinical studies and direct human trials are underway to test the safety and efficacy of cholesterol clearing compounds, with good success already observed in animal models. Key to assessing the effectiveness of interventions in patients, however, is the development of objective neurobiological outcome measures. Multisensory integration mechanisms present as an excellent candidate since they necessarily rely on the fidelity of long-range neural connections between the respective sensory cortices (e.g. the auditory and visual systems).
A simple way to test integrity of the multisensory system is to ask whether individuals respond faster to the occurrence of a bisensory event than they do to the occurrence of either of the unisensory constituents alone. Here, we presented simple auditory, visual, and audio-visual stimuli in random sequence. Participants responded as fast as possible with a button push. One 11-year-old and two 14-year-old boys with NPC participated in the experiment and their results were compared to those of 35 age-matched neurotypical boys.
Reaction times (RTs) to the stimuli when presented simultaneously were significantly faster than when they were presented alone in the neurotypical children, a facilitation that could not be accounted for by probability summation, as evidenced by violation of the so-called ‘race’ model. In stark contrast, the NPC boys showed no such speeding, despite the fact that their unisensory RTs fell within the distribution of RTs observed in the neurotypicals.
These results uncover a previously undescribed deficit in multisensory integrative abilities in NPC, with implications for ongoing treatment of the clinical symptoms of these children. They also suggest that multisensory processes may represent a good candidate biomarker against which to test the efficacy of therapeutic interventions.
- Race model
- Lysosomal disease
- Rare disease
- Sensory processing
- Sensory integration
Niemann-Pick type C (NPC) disease is a rare progressive lysosomal storage disorder caused by mutations in either the NPC1 or NPC2 gene, with about 95% of cases attributable to the former ,. Individuals with NPC cannot properly metabolize cholesterol and other lipids which accumulate in the brain and in visceral organs (e.g. liver and spleen), ultimately causing cell dysfunction and organ system failure. Although NPC1 and NPC2 proteins are expressed ubiquitously, brain tissue is the most severely affected, resulting in widespread intraneuronal storage of cholesterol and glycosphingolipids that ultimately results in massive neurodegeneration -. While appearing relatively typical during the early stages of the disease, over time NPC children develop vertical gaze palsy, motor system impairment, learning difficulties and clumsiness, as well as seizures -. Documented changes in brain include ectopic dendrite growth, altered synaptic connectivity affecting cortical pyramidal neurons, axonal degeneration, myelin loss, gliosis and the formation of neurofibrillary tangles similar to Alzheimer's disease ,. Neuronal death is prominent in some brain regions such as the cerebellum where Purkinje cells selectively die, undoubtedly contributing to the clinically-evident motor system dysfunction ,,. Effective treatments are limited, although promising clinical trials are underway based on results in animal models of NPC ,,.
Key to advancing new treatments for this and related lysosomal diseases with neural involvement is the development of objective biomarkers of neurological function against which the efficacy of new drugs can be tested in human patients. Our work and that of others has demonstrated the essential role that multisensory integration (MSI) plays in typical perception and cognition -. Because inputs from the various senses (e.g., the auditory, visual and somatosensory systems) initially arrive into widely separated regions of the neocortex, MSI must involve ongoing communication between relatively far-flung cortical regions, although it may well be initiated even earlier in the hierarchy within nuclei of the thalamus . In this sense, probing multisensory functioning provides an excellent assay of inter-regional communication, and the fidelity of the multisensory system must at least in part be a function of the integrity of long-range neural connectivity. For this reason we expected measures of MSI to provide a sensitive metric of neural dysfunction in NPC disease. What's more, MSI processes show a prolonged period of neuroplasticity, with continued development of these abilities seen into the late teenage years ,. As such, measures of MSI may provide useful biomarkers against which to test the impact of treatment on brain function.
A straightforward way to measure multisensory integration is to compare reaction times (RT) to unisensory and multisensory events during a simple speeded response task. It has been firmly established that adults react more quickly to multisensory than unisensory inputs ,-. For such behavioral facilitation to be unequivocally attributed to multisensory integration, this speeding up must exceed what is predicted due to the mere presence of a redundant signal (i.e. two inputs). That is, when two stimulus copies are presented simultaneously, even if both were to be processed entirely independently in the brain, one would still expect to see a speeding up of responses since there is increased likelihood that either of the two stimuli will yield a fast reaction-time relative to just one input. This is often referred to as the Redundant Signals Effect (RSE), and its presence does not, of itself, necessarily point to integration effects. The so-called “race model” is applied to test for the presence of true multisensory effects, by assessing whether responses to multisensory inputs are faster than the fastest possible responses produced by the unisensory conditions -. This is achieved by comparing the probabilities of making fast responses during multisensory events to those during unisensory events. The race model is said to be violated whenever the cumulative probability (CP) of a response at a given latency for the multisensory condition is greater than the sum of the CPs from each of the unisensory conditions. When the race model is violated, it is taken to be a strong indication that the inputs from the two different senses are interacting (in a non-additive way) to produce the speeding of the responses. Work from our laboratory suggests that this metric of MSI RT-speeding follows a developmental trajectory, with little evidence for behavioral enhancement before age 9, but that near full maturity is reached by age 16 ,. Moreover, in these developmental studies, behavioral performance was shown to benefit from MSI at the single participant level for 95% of neurotypical participants aged 11-16, and 100% of participants aged 13-16. This relatively protracted developmental trajectory of MSI behavioral facilitation is consistently seen across laboratories ,. Here we used this behavioral approach to assay multisensory function in three boys with NPC -- two adolescents (14 years, 7 months & 14 years, 5 months old) and one younger boy (11 years, 1 month) -- comparing their performance to that of 16 neurotypical adolescent boys aged 13-15, and 19 neurotypical boys aged 10-13, respectively.
Two adolescent boys with NPC (14 years, 7 months & 14 years, 5 months of age respectively) and one 11 year old boy with NPC (11 years, 1 month) participated in the study. NPC was clinically diagnosed by metabolic specialists and confirmed via genetic testing. Participants were administered the Wechsler Abbreviated Scales of Intelligence (WASI-II) The WASI-II is a short and reliable measure of intelligence that assesses general intellectual functioning. All four subtests were used: Vocabulary, Block Design, Similarities, and Matrix Reasoning. Vocabulary measures the individual’s expressive vocabulary, verbal knowledge, and fund of information. Block Design measures spatial visualization, visual-motor coordination, and abstract conceptualization. The Similarities subtest measures verbal concept formation, abstract verbal reasoning ability, and general intellectual ability. Matrix Reasoning measures non-verbal fluid reasoning and general intellectual ability. Scores are reported as a Verbal Comprehension Index (VCI), a Perceptual Reasoning Index (PRI), and a Full Scale Intelligence Quotient (FSIQ), which represents performance on all 4 subtests.
Wechsler Abbreviated Scale of Intelligence scores
Wechsler Abbreviated Scale of Intelligence (WASI-II)
NPC Participant 1
NPC Participant 2
NPC Participant 3
FULL SCALE IQ (FSIQ)
Verbal Comprehension Index (VCI)
Perceptual Reasoning Index (PRI)
NPC Participant 1
Participant 1 is a 14 year 8 month old adolescent boy, who was evaluated 3 months after his participation in our behavioral study. He was diagnosed with NPC in 2005 and is currently on the following medications: Zavesca (miglustat), Depakote (divalproex sodium), Keppra (levetiracetam), and Coumadin (warfarin). He has a history of seizures onsetting at age 14. Parental reports indicate clumsiness and unclear speech, which were also observed in the lab. The participant currently receives occupational and speech therapy. He is home-schooled due to the frequency of his seizures. A routine hearing screen performed at the lab revealed mild high frequency hearing loss (i.e. 4,000 Hz tones were not detected at <60 dB & 2,000 Hz tones were not detected at <45 dB). A routine vision screen (Snellen chart) revealed 20/20 and 20/30 visual acuity, in the right and left eyes respectively.
Overall intellectual functioning, as measured by the Full Scale IQ on the WASI-II, was estimated in the mild to moderately impaired range (FSIQ = 76). His Verbal Comprehension Index score fell in the mildly impaired range (VCI = 82) and was somewhat higher than his Perceptual Reasoning Index score which fell in the mild to moderately impaired range (PRI = 74); however this difference was not statistically significant. The examiner noted that on several trials of the Block Design subtests of the PRI, the participant was able to reproduce the modeled design, however with a 90° rotation. The examiner noted that the participant performed much better when verbal items called for short succinct answers. This likely contributed to his higher Similarities score, as several of the relationships probed by the subtest can be addressed with one word explanations, as compared to the Vocabulary subtest which requires a more lengthy, developed explanation. Further, the examiner notes that speech was effortful and may have affected performance, with the current scores underestimating the participant’s true abilities. The examiner also noted that the participant appeared fatigued and yawned frequently towards the end of the testing session.
NPC Participant 2
Participant 2 is a 14 year 10 month old adolescent boy, who was evaluated 3 months after his participation in our behavioral study. He was diagnosed with NPC in 2005; this patient has a I1061T and M1142T mutation on exons 21 and 22. He is currently on the following medications: Trileptal (oxcarbazepine) and Zavesca (miglustat). He has a history of seizures with the last seizure occurring 10 months prior to testing. The participant currently receives occupational therapy, speech therapy, and has a 1:1 aide at school. A routine hearing screen performed at the lab revealed mild high frequency hearing loss (i.e. 4,000 Hz tones were not detected at <60 dB). A routine vision screen (Snellen chart) revealed 20/60 visual acuity in both eyes.
Overall intellectual functioning, as measured by the Full Scale IQ on the WASI-II, was estimated in the moderately impaired range (FSIQ = 62). His Verbal Comprehension Index score was in the mild to moderately impaired range (VCI = 69) and somewhat higher than his Perceptual Reasoning Index score which fell in the moderately to severely impaired range (PRI = 58); however, this difference was not statistically significant. The examiner observed that the participant had motor difficulties when manipulating the blocks used in one of the PRI subtests (Block Design). Poor articulation was noted at times, but this was not believed to have interfered with testing.
NPC Participant 3
Participant 3 is an 11 year 1 month old boy, who was evaluated on the same day as his participation in our behavioral study. He was diagnosed with NPC in 2013. He is currently on the following medications: Keppra (levetiracetam) and Zavesca (miglustat). He has a history of seizures, including a 4 day hospitalization due to seizure-like activity. He has suffered a concussion that did not render him unconscious. The participant currently receives occupational therapy and academic help with reading and math in a specialized classroom setting at school. Normal hearing was confirmed through a routine hearing screen performed at the lab. A routine vision screen (Snellen chart) revealed 20/50 and 20/30 visual acuity, in the right and left eyes respectively.
Overall intellectual functioning, as measured by the Full Scale IQ on the WASI-II, was estimated in the moderately impaired range (FSIQ = 63). His Verbal Comprehension Index score fell in the mild to moderately impaired range (VCI = 72) and was significantly higher than his Perceptual Reasoning Index score which fell in the moderately to severely impaired range (PRI = 56). The examiner noted that the participant had much difficulty with Block Design subtest of the PRI, often asking whether the designs presented to him were ‘even possible’. On the Matrix Reasoning subtest of the PRI, the participant could not correctly answer any of items at or beyond the starting point for his age and testing here was quickly discontinued. The examiner notes that the participant was pleasant, friendly, and cooperative testing session.
Thirty-five neurotypical boys also participated in this study. Sixteen adolescent boys aged 13-15 served as an age-matched control group for the two older patients. Nineteen boys aged 10-12 served as an age-matched control group for the younger patient. Participants were screened for neurological and psychiatric disorders, as well as other major medical conditions. These data were partially reported in a pair of previous studies ,. Participants were also administered the WASI-II and Full Scale IQ (FSIQ), Verbal Comprehension Index (VCI), and Perceptual Reasoning Index (PRI) scores were obtained, which for these groups were in the average or high average range (Older group mean (standard deviation - SD): FSIQ = 113 (12), VCI = 104 (14), PRI = 110 (12); Younger group: FSIQ = 113 (14), VCI = 108 (12), PRI = 113 (13)). Audiometric evaluation confirmed that all participants had within-normal-limits hearing thresholds. All participants had normal or corrected-to-normal vision.
Before entering into the study, informed written consent was obtained from the children's parents, and verbal or written assent was obtained from children. All procedures were approved by the Institutional Review Board at The Albert Einstein College of Medicine and were in accordance with the tenets for the responsible conduct of human research laid out in the Declaration of Helsinki.
Paradigm & task
A 1000-Hz tone (duration 60 ms; 75 dB SPL; rise/fall time 5 ms) was presented from a single Hartman Multimedia JBL Duet speaker located centrally atop the computer monitor from which the visual stimulus was presented.
A red disc with a diameter of 3.2 cm (subtending 1.5° in diameter at a viewing distance of 122 cm) appearing on a black background was presented on a Liquid Crystal Display (LCD) monitor (Dell Ultrasharp 1704FTP, 60Hz refresh rate) for 60 ms. The disc was located 0.4 cm superior to central fixation along the vertical meridian (0.9° at a viewing distance of 122 cm). A small cross marked the point of central fixation on the monitor.
Auditory and visual simultaneous
The “auditory-alone” and “visual-alone” conditions described above were presented simultaneously. The auditory and visual stimuli were presented in close spatial proximity, with the speaker placed atop the monitor in vertical alignment with the visual stimulus.
Participants were seated in a dimly lit, sound-attenuated electrically shielded room (Industrial Acoustics Company, Bronx, New York) 122 cm from the monitor. They were given a response pad (Logitech Wingman Precision) and instructed to press a button with their right thumb as quickly as possible when they saw the red circle, heard the tone, or saw the circle and heard the tone together. The same response key was used for all 3 stimulus types. Presentation software (Neurobehavioral Systems, Inc., Albany CA) was used for stimulus delivery. This software ensures precise timing of stimulus presentation and is commonly used in neuroscience, psychophysics, and psychological experiments. It takes into account the refresh rate of the computer monitor when presenting visual stimuli. In this experiment, stimulus delivery in the multisensory condition was triggered by the onset of the visual stimulus. All 3 stimulus types were presented with equal probability and in random order in blocks of 100 trials. Inter-stimulus-interval (ISI) varied randomly between 1000 and 3000 (ms) according to a uniform (square wave) distribution. Participants completed a minimum of 8 blocks, with most completing 10. Breaks were encouraged between blocks to help maintain concentration and reduce restlessness or fatigue (these methods are also presented in detail in Brandwein et al , and Molholm et al ).
Interrogating the race model
To test the race model, we first calculated the cumulative probability of reaction times across the three stimulus types (audio-alone, visual-alone, and audio-visual) for each of the participants. The range of RTs accepted was determined at the individual participant level with the slowest and fastest 2.5% of trials excluded. Using a 95% cutoff to define the time window for acceptable trials rather than an absolute cutoff value allowed us to more accurately capture the range of RTs for each participant, an important factor in calculating the race model (described below). The RT distribution was then divided into quantiles from the 5th to the 100th percentile in increments of 5%. For any RT latency, t, the race model holds when this CP value is less than or equal to the sum of the CP from each of the unisensory conditions. Conversely, the race-model is said to be violated if the CP for any audiovisual RT latency is larger than that predicted by the race model (the sum of the unisensory CPs) at any quantile. Violations were expected to occur in the first third of the distribution (i.e. the quantiles containing the fastest RTs at the lower end of the RT range) because this is when interactions between visual and auditory inputs would result in the fulfillment of a response criterion before either input alone could satisfy the same criterion . At the individual level, a participant was said to have shown race model violation if the CP of his RT to the audiovisual stimulus was larger than that predicted by the race model at any quantile within the first third of the distribution. In order to more easily interpret results from the race model test, a Miller inequality value can be computed, both at the individual and group levels, by subtracting the CP predicted by the race model from the CP of the multisensory condition. Any positive “Miller values” indicate race model violation and RT speeding that cannot be accounted for by probability summation or by the ‘redundant signals effect’.
Behavioral performance - reaction times & hit rates
NPC Participant 1
NPC Participant 2
NPC Participant 3
Older neurotypicals (13-15 years old; N = 16)
Younger neurotypicals (10-12 years old; N = 19)
NPC Participant 1
NPC Participant 2
NPC Participant 3
Older neurotypicals (13-15 years old; N = 16)
Younger neurotypicals (10-12 years old; N = 19)
A repeated measures ANOVA revealed a significant effect of stimulus type on RTs for both the older F(2,30) = 12.1, p < .001 and younger F(2,36) = 91.4, p < .001 neurotypical groups. Follow-up protected t-tests confirm a speeding up of RTs for the multisensory condition for the older neurotypical group (Audio vs. AV - t(15) = 3.4, p < .01; Visual vs. AV - t(15) = 5.0, p <. 01; Audio vs. Visual - t(15) = -.31, p = .76) and for the younger neurotypical group (Audio vs. AV - t(18) = 10.4, p < .01, Visual vs. AV- t(18) = 12.4, p < .01). Additionally, the younger group had significantly faster RTs to the auditory condition as compared to the visual condition, t(18) = -3.1, p < .01.
If motor difficulties alone were to account for the larger variance in RTs and lower hit rates in the NPC participants, one would expect these to occur at the same probability across all three experimental conditions, which is not the case in this sample. Deficits in motor response do not account for the differential effect noted in 2 of the patients across the unisensory and multisensory conditions. The two NPC adolescents had faster RTs and a higher percentage of hits in the multisensory conditions compared to the unisensory. To probe the nature of this speeding up and assess whether the patients may be benefitting from an integrative process, we applied a test for multisensory integration effects (i.e. testing the race model). In this test a within-individual analysis is employed, thus accommodating the between group differences already noted.
Multisensory integration effects - race model
To our knowledge, this is the first study to examine multisensory processes in NPC. The observed lack of race model violation in NPC suggests compromised connectivity between auditory and visual areas of the brain, possibly at both sub-cortical and cortical levels. It is likely that these inter-sensory connections develop very early in life, strengthen across childhood, and stabilize during adolescence ,,,.Understanding when exactly during the progression of NPC that MSI becomes compromised will require further investigation and will be crucial to maximizing the clinical usefulness of this measure in the NPC population. Two possible scenarios are that; 1) MSI-induced behavioral facilitation never quite reaches “healthy” levels in these individuals or 2) that like many of the other symptoms exhibited in this population, NPC patients experience a degradation of MSI function with progression of the disease state. In either case, this metric of MSI presents a behavioral marker against which to measure improved neurocognitive function due to experimental treatment interventions.
In terms of everyday functioning, an obvious question is what impact deficits in multisensory processing will have on the abilities of NPC children to effectively navigate their environment. For example, effective MSI leads to improved speech perception when a listener has the benefit of watching the facial articulations of a speaker, especially if the fidelity of the auditory input is affected by noisy background environmental conditions ,,,,. Thus, one implication is that these children may find communication more difficult in challenging multi-speaker scenarios, not uncommon in classrooms or other social settings. MSI is also vital to more basic functions, such as maintaining balance through visuo-vestibular and visual-somatosensory integration  and in speeded orienting to reliable multisensory events, whether it be for object identification or cueing initiation of approach/avoidance behaviors ,-,. A more comprehensive understanding of the multisensory integration abilities of these children is clearly called for, and it will be of significant interest to assess the underlying neurophysiology in turn ,.
Another obvious outcome of the current study is that the NPC children show basic motor deficits. While it is true that there are neurotypical participants who are as slow to respond to unisensory inputs, and others who show similarly high variance in RTs, no neurotypical children show the poor response rates we see in the NPC children. Simply put, the NPC children are slow, variable and inaccurate and this triumvirate of issues clearly points to fundamental sensory-motor issues. That said, we do not believe that the MSI deficits observed here are primarily due to these issues, since these issues apply equally to all the experimental conditions (both unisensory and multisensory; also see Additional file 1). As the race model analysis is conducted at the individual participant level, where the cumulative probability distributions are calculated for each participant and within-subject RTs are compared to determine the multisensory benefit, general motor delays are accounted for. It could reasonably be asked, though, whether simple tests of motor speed, variance and accuracy might not prove equally useful biomarkers for NPC. However, it bears re-emphasizing that while the NPC children do show these issues, their performance levels do not fall completely outside the normal distribution for these measures, whereas for the measures of multisensory integration, they clearly do.
It is worth pointing out that these children with NPC are, at some basic level, benefitting from multisensory stimulation, even if not in an integrative manner. The fact that mean RTs and hits are improved in some cases, even in the absence of significant multisensory integration, when patients are exposed to stimulation in two sensory streams is promising, especially in terms of sensory training. This may have implications for the development of assistive technologies used for communication, particularly during the more progressed phases of the disease.
A natural question that arises is whether the multisensory deficit we observe in NPC can be meaningfully impacted through intervention. The landscape is actually quite promising in this regard since several studies now point to multisensory and unisensory gain with repeated training. These studies show that training can lead to improvement in MSI-dependent tasks such as speech-perception , that training can narrow the time window during which two sensory inputs are seen as “synchronous” and thus integrated , and that MSI networks can be engaged and enhanced in training activities where abstract stimuli are paired, such as specific sounds with abstract shapes, or musical tones with symbols ,. Work in animal models also supports the notion that sensory integration abilities can be impacted through practice with training-induced multisensory enhancement noted in both behavior and activity patterns at the single cell level in the superior colliculus, in both juvenile  and adult cats .
An obvious limitation of the current work is the relatively small cohort of three patients with NPC that we were able to test. Ideally, one would like to have greater numbers. However, the disease prevalence rate for NPC is estimated at 1-in-120,000 ,,, so recruitment of larger populations is extremely challenging. It is worth emphasizing that the atypical multisensory integration pattern noted here is highly consistent across the 3 NPC patients in our sample and the findings are strengthened by comparison of these 3 patients to large existing datasets of neurotypical age-matched children. In all 3 cases, the performance metrics of the NPC patients fall completely outside the “normative” curve for MSI development.
This study uncovered clear multisensory deficits in three patients with NPC. The simple-to-acquire measures of multisensory response speed described here may prove to be useful endpoints against which to track disease progression and to assess the efficacy of therapeutic interventions. Specific environmental accommodations should be considered to address the potential impact of deteriorating multisensory mechanisms in these children.
GA, SM, SUW and JJF conceived the study. GA and ABB coordinated data collection. JSB and GA conducted the primary data analyses. GA wrote the initial draft of the paper and all authors provided multiple rounds of input during the editorial process. The senior author, JJF, attests that all authors had full access to the data and that each author saw and approved the final submitted version of this manuscript.
We extend our deep appreciation to the families involved in this research for their time, patience, and care. The Human Clinical Phenotyping Core, where the children in this study were clinically evaluated, is a facility of the Rose F. Kennedy Intellectual and Developmental Disabilities Research Center (IDDRC) which is funded through a center grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD P30 HD071593). Ongoing support of the Cognitive Neurophysiology Laboratory is provided through a grant from the Sheryl and Daniel R. Tishman Charitable Foundation. Support for this work was provided in part by the Support of Accelerated Research of NPC Disease foundation (SOAR-NPC). We thank Greg Peters and Emmett Foxe for assistance with data collection and Drs. Juliana Bates and Zonya Mitchell for help with clinical testing.
- Vanier MT, Duthel S, Rodriguez-Lafrasse C, Pentchev P, Carstea ED: Genetic heterogeneity in Niemann-Pick C disease: a study using somatic cell hybridization and linkage analysis. Am J Hum Genet. 1996, 58: 118-125.PubMedPubMed CentralGoogle Scholar
- Vanier MT, Suzuki K: Recent advances in elucidating Niemann-Pick C disease. Brain Pathol. 1998, 8: 163-174. 10.1111/j.1750-3639.1998.tb00143.x.View ArticlePubMedGoogle Scholar
- Vanier MT: Biochemical studies in Niemann-Pick disease. I. Major sphingolipids of liver and spleen. Biochim Biophys Acta. 1983, 750: 178-184. 10.1016/0005-2760(83)90218-7.View ArticlePubMedGoogle Scholar
- Vanier MT: Lipid changes in Niemann-Pick disease type C brain: personal experience and review of the literature. Neurochem Res. 1999, 24: 481-489. 10.1023/A:1022575511354.View ArticlePubMedGoogle Scholar
- Zervas M, Dobrenis K, Walkley SU: Neurons in Niemann-Pick disease type C accumulate gangliosides as well as unesterified cholesterol and undergo dendritic and axonal alterations. J Neuropathol Exp Neurol. 2001, 60: 49-64.View ArticlePubMedGoogle Scholar
- Mengel E, Klunemann HH, Lourenco CM, Hendriksz CJ, Sedel F, Walterfang M, Kolb SA: Niemann-Pick disease type C symptomatology: an expert-based clinical description. Orphanet J Rare Dis. 2013, 8: 166-10.1186/1750-1172-8-166.View ArticlePubMedPubMed CentralGoogle Scholar
- Garver WS, Francis GA, Jelinek D, Shepherd G, Flynn J, Castro G, Vockley CW, Coppock DL, Pettit KM, Heidenreich RA, Meany FJ: The National Niemann-Pick C1 disease database: report of clinical features and health problems. Am J Med Genet A. 2007, 143A: 1204-1211. 10.1002/ajmg.a.31735.View ArticlePubMedGoogle Scholar
- Patterson MC, Hendriksz CJ, Walterfang M, Sedel F, Vanier MT, Wijburg F: Recommendations for the diagnosis and management of Niemann-Pick disease type C: an update. Mol Genet Metab. 2012, 106: 330-344. 10.1016/j.ymgme.2012.03.012.View ArticlePubMedGoogle Scholar
- Wraith JE, Baumgartner MR, Bembi B, Covanis A, Levade T, Mengel E, Pineda M, Sedel F, Topcu M, Vanier MT, Widner H, Wijburg FA, Patterson MC: Recommendations on the diagnosis and management of Niemann-Pick disease type C. Mol Genet Metab. 2009, 98: 152-165. 10.1016/j.ymgme.2009.06.008.View ArticlePubMedGoogle Scholar
- Walkley SU, Suzuki K: Consequences of NPC1 and NPC2 loss of function in mammalian neurons. Biochim Biophys Acta. 2004, 1685: 48-62. 10.1016/j.bbalip.2004.08.011.View ArticlePubMedGoogle Scholar
- Liu B, Turley SD, Burns DK, Miller AM, Repa JJ, Dietschy JM: Reversal of defective lysosomal transport in NPC disease ameliorates liver dysfunction and neurodegeneration in the npc1-/- mouse. Proc Natl Acad Sci U S A. 2009, 106: 2377-2382. 10.1073/pnas.0810895106.View ArticlePubMedPubMed CentralGoogle Scholar
- Sarna JR, Larouche M, Marzban H, Sillitoe RV, Rancourt DE, Hawkes R: Patterned Purkinje cell degeneration in mouse models of Niemann-Pick type C disease. J Comp Neurol. 2003, 456: 279-291. 10.1002/cne.10522.View ArticlePubMedGoogle Scholar
- Aqul A, Liu B, Ramirez CM, Pieper AA, Estill SJ, Burns DK, Liu B, Repa JJ, Turley SD, Dietschy JM: Unesterified cholesterol accumulation in late endosomes/lysosomes causes neurodegeneration and is prevented by driving cholesterol export from this compartment. J Neurosci. 2011, 31: 9404-9413. 10.1523/JNEUROSCI.1317-11.2011.View ArticlePubMedPubMed CentralGoogle Scholar
- Davidson CD, Ali NF, Micsenyi MC, Stephney G, Renault S, Dobrenis K, Ory DS, Vanier MT, Walkley SU: Chronic cyclodextrin treatment of murine Niemann-Pick C disease ameliorates neuronal cholesterol and glycosphingolipid storage and disease progression. PLoS One. 2009, 4: e6951-10.1371/journal.pone.0006951.View ArticlePubMedPubMed CentralGoogle Scholar
- Bair WN, Kiemel T, Jeka JJ, Clark JE: Development of multisensory reweighting for posture control in children. Exp Brain Res. 2007, 183: 435-446. 10.1007/s00221-007-1057-2.View ArticlePubMedPubMed CentralGoogle Scholar
- Foxe JJ: Multisensory integration: frequency tuning of audio-tactile integration. Curr Biol. 2009, 19: R373-R375. 10.1016/j.cub.2009.03.029.View ArticlePubMedGoogle Scholar
- Foxe JJ, Molholm S, Del Bene VA, Frey HP, Russo NN, Blanco DB, Saint-Amour D, Ross L: Severe multisensory speech integration deficits in high-functioning school-aged children with Autism Spectrum Disorder (ASD) and their resolution during early adolescence.Cereb Cortex 2013, [Epub ahead of print].,Google Scholar
- Foxe JJ, Schroeder CE: The case for feedforward multisensory convergence during early cortical processing. Neuroreport. 2005, 16: 419-423. 10.1097/00001756-200504040-00001.View ArticlePubMedGoogle Scholar
- Molholm S, Martinez A, Shpaner M, Foxe JJ: Object-based attention is multisensory: co-activation of an object's representations in ignored sensory modalities. Eur J Neurosci. 2007, 26: 499-509. 10.1111/j.1460-9568.2007.05668.x.View ArticlePubMedGoogle Scholar
- Molholm S, Ritter W, Javitt DC, Foxe JJ: Multisensory visual-auditory object recognition in humans: a high-density electrical mapping study. Cereb Cortex. 2004, 14: 452-465. 10.1093/cercor/bhh007.View ArticlePubMedGoogle Scholar
- Molholm S, Ritter W, Murray MM, Javitt DC, Schroeder CE, Foxe JJ: Multisensory auditory-visual interactions during early sensory processing in humans: a high-density electrical mapping study. Brain Res Cogn Brain Res. 2002, 14: 115-128. 10.1016/S0926-6410(02)00066-6.View ArticlePubMedGoogle Scholar
- Ross LA, Molholm S, Blanco D, Gomez-Ramirez M, Saint-Amour D, Foxe JJ: The development of multisensory speech perception continues into the late childhood years. Eur J Neurosci. 2011, 33: 2329-2337. 10.1111/j.1460-9568.2011.07685.x.View ArticlePubMedPubMed CentralGoogle Scholar
- Ross LA, Saint-Amour D, Leavitt VM, Javitt DC, Foxe JJ: Do you see what I am saying? Exploring visual enhancement of speech comprehension in noisy environment. Cereb Cortex. 2007, 17: 1147-1153. 10.1093/cercor/bhl024.View ArticlePubMedGoogle Scholar
- Stein BE, Meredith MA: Multisensory integration. Neural and behavioral solutions for dealing with stimuli from different sensory modalities. Ann N Y Acad Sci. 1990, 608: 51-65. 10.1111/j.1749-6632.1990.tb48891.x. discussion 65-70View ArticlePubMedGoogle Scholar
- Cappe C, Rouiller EM, Barone P: Cortical and Thalamic Pathways for Multisensory and Sensorimotor Interplay. The Neural Bases of Multisensory Processes. Edited by: Murray MM, Wallace MT. 2012, CRC Press, Boca Raton (FL)Google Scholar
- Brandwein AB, Foxe JJ, Russo NN, Altschuler TS, Gomes H, Molholm S: The development of audiovisual multisensory integration across childhood and early adolescence: a high-density electrical mapping study. Cereb Cortex. 2011, 21: 1042-1055. 10.1093/cercor/bhq170.View ArticlePubMedPubMed CentralGoogle Scholar
- Harrington LK, Peck CK: Spatial disparity affects visual-auditory interactions in human sensorimotor processing. Exp Brain Res. 1998, 122: 247-252. 10.1007/s002210050512.View ArticlePubMedGoogle Scholar
- Hughes HC, Reuter-Lorenz PA, Nozawa G, Fendrich R: Visual-auditory interactions in sensorimotor processing: saccades versus manual responses. J Exp Psychol Hum Percept Perform. 1994, 20: 131-153. 10.1037/0096-15126.96.36.199.View ArticlePubMedGoogle Scholar
- Maravita A, Bolognini N, Bricolo E, Marzi CA, Savazzi S: Is audiovisual integration subserved by the superior colliculus in humans?. Neuroreport. 2008, 19: 271-275. 10.1097/WNR.0b013e3282f4f04e.View ArticlePubMedGoogle Scholar
- Murray MM, Molholm S, Michel CM, Heslenfeld DJ, Ritter W, Javitt DC, Schroeder CE, Foxe JJ: Grabbing your ear: rapid auditory-somatosensory multisensory interactions in low-level sensory cortices are not constrained by stimulus alignment. Cereb Cortex. 2005, 15: 963-974. 10.1093/cercor/bhh197.View ArticlePubMedGoogle Scholar
- Miller J: Divided attention: evidence for coactivation with redundant signals. Cogn Psychol. 1982, 14: 247-279. 10.1016/0010-0285(82)90010-X.View ArticlePubMedGoogle Scholar
- Miller J: Timecourse of coactivation in bimodal divided attention. Percept Psychophys. 1986, 40: 331-343. 10.3758/BF03203025.View ArticlePubMedGoogle Scholar
- Ulrich R, Miller J, Schroter H: Testing the race model inequality: an algorithm and computer programs. Behav Res Methods. 2007, 39: 291-302. 10.3758/BF03193160.View ArticlePubMedGoogle Scholar
- Brandwein AB, Foxe JJ, Butler JS, Russo NN, Altschuler TS, Gomes H, Molholm S: The development of multisensory integration in high-functioning autism: high-density electrical mapping and psychophysical measures reveal impairments in the processing of audiovisual inputs. Cereb Cortex. 2013, 23: 1329-1341. 10.1093/cercor/bhs109.View ArticlePubMedPubMed CentralGoogle Scholar
- Gori M, Del Viva M, Sandini G, Burr DC: Young children do not integrate visual and haptic form information. Curr Biol. 2008, 18: 694-698. 10.1016/j.cub.2008.04.036.View ArticlePubMedGoogle Scholar
- Nardini M, Jones P, Bedford R, Braddick O: Development of cue integration in human navigation. Curr Biol. 2008, 18: 689-693. 10.1016/j.cub.2008.04.021.View ArticlePubMedGoogle Scholar
- Otto TU, Mamassian P: Noise and correlations in parallel perceptual decision making. Curr Biol. 2012, 22: 1391-1396. 10.1016/j.cub.2012.05.031.View ArticlePubMedGoogle Scholar
- Brebner JT, Welford AT: Introduction: an Historical Background Sketch. 1980, Academic, New YorkGoogle Scholar
- Fieandt K v, Huhtala A, Kullberg P, Saarl K: Personal Tempo and Phenomenal Time at Different Age Levels. 1956Google Scholar
- Galton F: On instruments for (1) testing perception of differences of tint and for (2) determining reaction time. J Anthropol Inst. 1899, 19: 27-29.Google Scholar
- Jevas S, Yan JH: The effect of aging on cognitive function: A preliminary quantitative review. Res Q Exerc Sport. 2001, 72: A49-A49.Google Scholar
- Welford AT: Motor performance. 1977, New York, Van Nostrand ReinholdGoogle Scholar
- Welford AT: Choice reaction time: Basic concepts. 1980, New York, Academic PressGoogle Scholar
- Welford AT: Reaction time, speed of performance, and age. Ann N Y Acad Sci. 1988, 515: 1-17. 10.1111/j.1749-6632.1988.tb32958.x.View ArticlePubMedGoogle Scholar
- Barutchu A, Crewther DP, Crewther SG: The race that precedes coactivation: development of multisensory facilitation in children. Dev Sci. 2009, 12: 464-473. 10.1111/j.1467-7687.2008.00782.x.View ArticlePubMedGoogle Scholar
- Nardini M, Begus K, Mareschal D: Multisensory uncertainty reduction for hand localization in children and adults. J Exp Psychol Hum Percept Perform. 2013, 39: 773-787. 10.1037/a0030719.View ArticlePubMedGoogle Scholar
- Wallace MT, Carriere BN, Perrault TJ, Vaughan JW, Stein BE: The development of cortical multisensory integration. J Neurosci. 2006, 26: 11844-11849. 10.1523/JNEUROSCI.3295-06.2006.View ArticlePubMedGoogle Scholar
- Wallace MT, Stein BE: Early experience determines how the senses will interact. J Neurophysiol. 2007, 97: 921-926. 10.1152/jn.00497.2006.View ArticlePubMedGoogle Scholar
- Ma WJ, Zhou X, Ross LA, Foxe JJ, Parra LC: Lip-reading aids word recognition most in moderate noise: a Bayesian explanation using high-dimensional feature space. PLoS One. 2009, 4: e4638-10.1371/journal.pone.0004638.View ArticlePubMedPubMed CentralGoogle Scholar
- Saint-Amour D, De Sanctis P, Molholm S, Ritter W, Foxe JJ: Seeing voices: High-density electrical mapping and source-analysis of the multisensory mismatch negativity evoked during the McGurk illusion. Neuropsychologia. 2007, 45: 587-597. 10.1016/j.neuropsychologia.2006.03.036.View ArticlePubMedPubMed CentralGoogle Scholar
- Foxe JJ, Morocz IA, Murray MM, Higgins BA, Javitt DC, Schroeder CE: Multisensory auditory-somatosensory interactions in early cortical processing revealed by high-density electrical mapping. Brain Res Cogn Brain Res. 2000, 10: 77-83. 10.1016/S0926-6410(00)00024-0.View ArticlePubMedGoogle Scholar
- Foxe JJ, Wylie GR, Martinez A, Schroeder CE, Javitt DC, Guilfoyle D, Ritter W, Murray MM: Auditory-somatosensory multisensory processing in auditory association cortex: an fMRI study. J Neurophysiol. 2002, 88: 540-543.PubMedGoogle Scholar
- Bernstein LE, Auer ET, Eberhardt SP, Jiang J: Auditory Perceptual Learning for Speech Perception Can be Enhanced by Audiovisual Training. Front Neurosci. 2013, 7: 34-10.3389/fnins.2013.00034.View ArticlePubMedPubMed CentralGoogle Scholar
- Powers AR, Hevey MA, Wallace MT: Neural correlates of multisensory perceptual learning. J Neurosci. 2012, 32: 6263-6274. 10.1523/JNEUROSCI.6138-11.2012.View ArticlePubMedPubMed CentralGoogle Scholar
- Butler AJ, James KH: Active learning of novel sound-producing objects: motor reactivation and enhancement of visuo-motor connectivity. J Cogn Neurosci. 2013, 25: 203-218. 10.1162/jocn_a_00284.View ArticlePubMedGoogle Scholar
- Paraskevopoulos E, Kuchenbuch A, Herholz SC, Pantev C: Multisensory integration during short-term music reading training enhances both uni- and multisensory cortical processing. J Cogn Neurosci. 2014, 26: 2224-2238. 10.1162/jocn_a_00620.View ArticlePubMedGoogle Scholar
- Stein BE, Rowland BA: Organization and plasticity in multisensory integration: early and late experience affects its governing principles. Prog Brain Res. 2011, 191: 145-163. 10.1016/B978-0-444-53752-2.00007-2.View ArticlePubMedPubMed CentralGoogle Scholar
- Yu L, Rowland BA, Xu J, Stein BE: Multisensory plasticity in adulthood: cross-modal experience enhances neuronal excitability and exposes silent inputs. J Neurophysiol. 2013, 109: 464-474. 10.1152/jn.00739.2012.View ArticlePubMedPubMed CentralGoogle Scholar
- Vanier MT: Niemann-Pick disease type C. Orphanet J Rare Dis. 2010, 5: 16-10.1186/1750-1172-5-16.View ArticlePubMedPubMed CentralGoogle Scholar
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