Research ReportFractional anisotropy correlates with auditory simple reaction time performance
Introduction
Since the beginning of the 20th century, simple reaction time tasks (SRT) have provided insights into neurophysiologic and psychological functions of humans (Poffenberger, 1912). For a long time, SRTs are known to be influenced by a variety of extrinsic and intrinsic factors, e.g., caffeine, alcohol, arousal, physical activity, stimulus duration, stimulus intensity, warning signal, daytime, fatigue, age or IQ (see e.g., Welford, 1980, Luce, 1986, Taimela, 1991). In all SRT test paradigms, interindividual variability is reported and still not fully understood, even though strong correlations to both co-variables level of intelligence (Choudhury and Gorman, 1999) and age (Fozard et al., 1994) have been shown. For the intraindividual variance of SRT, a number of hypotheses and computer models exist (Reed, 1998, Miller and Ulrich, 2003), whereas for interindividual variability, an evident corresponding model is still under debate. Yet, it has been proposed that interindividual differences in reaction time (RT) may be due to white matter (WM) differences; especially with respect to myelination (Reed et al., 2004), since the interdependence between myelination and nerve conduction speed is well established (Jack et al., 1983).
Despite these findings, a direct proof for the interrelation of interindividual RT differences and myelination is still missing. Therefore, identification of neural correlates of differences in interindividual RT would provide important information for the understanding of the performance in neural processing speed and behavioral measures. Until recently, no method for the evaluation of such neuromorphologic microstructural WM properties was available in vivo. A turning point in the last decade has been the establishment of diffusion tensor imaging (DTI) (Basser et al., 1994, Le Bihan et al., 1993, Pierpaoli et al., 1996), which is even sensitive for WM abnormalities in clinical routine (Nguyen et al., 2005). Using DTI, the diffusion anisotropy can be mapped voxel by voxel. Thereby, direction of maximum diffusivity is assumed to coincide with the WM fiber tract orientation (Moseley et al., 1991). Fractional anisotropy (FA), which is based on the standard deviation of the three eigenvalues of the diffusion tensor (see Le Bihan, 2003 for a technical review), has been shown to be of clinical relevance in a wide range of various conditions including schizophrenia (Hoptman et al., 2004), sensory neural hearing loss (Chang et al., 2004), multiple sclerosis (Filippi et al., 2001) and others.
Only few reports on the correlation between FA and RT performance measures exist. Madden et al. (2004) reported a moderate correlation in young adults between FA and RT in the splenium of the corpus callosum (r = − 0.54) by using a visual target detection oddball task. Tuch et al. (2005) demonstrated correlations between visual choice reaction tasks and FA in the visual projection and association pathways of healthy young adults. In the latter study, significant correlations were found in the right thalamus, right medial precuneus and left superior temporal WM, but not in the posterior internal capsule representing motor pathways nor in the interhemispheric connections, as represented by the corpus callosum.
Analyzing the time flow of aSRT processing (from stimulus to response) leads to a subdivision into different sections. Some of these sections are included in established neurophysiological test paradigms (Table 1). A comparison of aSRT results with average brainstem acoustic evoked potentials (BEAP), auditory middle latency response (AMLR) and corticomotor latency (CmL) measures in healthy subjects (see Table 1) shows that the involved brain areas are not very likely to account for the main part of latency across individuals in aSRT. Therefore, the complex structures involved during central processing time still remain as crucial influencing factors on interindividual aSRT differences. In imaging studies analyzing SRT responses, a single neuroanatomic substrate for motor preparation, independent of the movement information context was suggested (Deiber et al., 1996). In this PET study, which investigated visual RT tasks, different conditions of motor preparation were associated with increased regional cortical blood flow in a common set of cerebral regions, including contralateral frontal cortex, contralateral parietal association cortex, ipsilateral cerebellum, contralateral basal ganglia and thalamus.
The aim of the present study was to investigate whether variation across individuals in white matter FA of human brain structures was associated with auditory simple RT measures. We suppose a DTI detectable brain area or network along aSRT signal processing structures with crucial influence on human stimulus–response measures. To reduce the influence of complex covariables on RT (e.g., decision making, attention) due to task demanded central processing, we implemented a SRT paradigm. We calculated FA maps in 19 healthy young right handed adults and conducted a whole-head voxel based morphometry (VBM) analysis of fractional anisotropy in the human brain with corresponding interindividual aSRT measures.
Section snippets
Results
Measured aSRT of the different test modalities is summarized in Table 2 as mean values over all subjects and are in agreement with previous findings (Elias et al., 2000). No significant intersubject correlation (p < 0.01) for the different RT measures was found for gender, body height, age or handedness (as represented by Oldfield value).
The whole-head VBM analysis of fractional anisotropy vs. aSRT measures of all subjects revealed a strong positive correlation within right cerebellar structures
Discussion
In this study, we demonstrated correlations of FA with aSRT measures by using a VBM whole head analysis of FA data. Strong positive correlation of RT-mean with FA was found in the right central cerebellar WM, dorso-cranial of the dentate nucleus underneath lobule VI (Fig. 1). Previous research reported connections of the close-by area of the dentate to the representation of the hand in M1 of monkeys (Dum and Strick, 2003). Our findings are in agreement with previous cerebellar imaging studies
Participants
Out of 22 primarily enrolled healthy students, two subjects had to be excluded due to technical problems in image processing and another one because of deficient hearing thresholds. The presented results are based on data acquired from the 19 remaining subjects who were included in the final analysis (9 male, 10 female), all right handed and 23 years of age (mean age 23.1 ± 0.6 years). The participants completed a German version of the Oldfield questionnaire of handedness (Oldfield, 1971) with
Acknowledgments
This work was supported by a programme grant (TP 1.8) of the Interdisciplinary Centre for Clinical Research (IZKF) of the Friedrich-Schiller-University Jena (to J.R.R. & J.H.)/TMWFK (B 307-04004) and the Bundesministerium für Bildung und Forschung (BMBF) (Core-Unit MRT-Methodik, 01ZZ0405). D.G. acknowledges support from the IZKF Jena program for a research stipend.
References (61)
- et al.
Voxel-based morphometry—the methods
NeuroImage
(2000) - et al.
Why voxel-based morphometry should be used
NeuroImage
(2001) - et al.
MR diffusion tensor spectroscopy and imaging
Biophys. J.
(1994) - et al.
Cerebral asymmetry and the effects of sex and handedness on brain structure: a voxel-based morphometric analysis of 465 normal adult human brains
NeuroImage
(2001) - et al.
Parallel neural networks for learning sequential procedures
Trends Neurosci.
(1999) - et al.
Correlations between reaction time and cerebral blood flow during motor preparation
NeuroImage
(2000) - et al.
Mechanisms of neural conditioning
Int. Rev. Neurobiol.
(2001) - et al.
Diffusion tensor imaging of adult age differences in cerebral white matter: relation to response time
NeuroImage
(2004) - et al.
Simple reaction time and statistical facilitation: a parallel grains model
Cogn. Psychol.
(2003) The assessment and analysis of handedness: the Edinburgh inventory
Neurosypchologia
(1971)
Causes of intraindividual variability in reaction times: a neuropsychologically orientated review and a new suggestion
Pers. Individ. Differ.
Sex difference in brain nerve conduction velocity in normal humans
Neuropsychologia
Distributional assumptions in voxel-based morphometry
NeuroImage
Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water
NeuroImage
Effects of cooling the dentate nucleus of the cerebellum on hand movement of the monkey
Brain Res.
Localization of human supratemporal auditory areas from intracerebral auditory evoked potentials using distributed source models
NeuroImage
Inferring microstructural features and the physiological state of tissues from diffusion-weighted images
NMR Biomed.
Extensive piano practicing has regionally specific effects on white matter development
Nat. Neurosci.
Diffusion anisotropy in subcortical white matter and cortical grey matter: changes with aging and the role of CSF-suppression
J. Magn. Reson. Imaging
White matter asymmetry in the human brain: a diffusion tensor MRI study
Cereb. Cortex
Brainstem auditory evoked potential abnormalities in vascular malformations of the posterior fossa
J. Neurol.
Auditory neural pathways evaluation on sensoryneural hearing loss using diffusion tensor imaging
NeuroReport
Intracranial auditory pathways: anatomy correlated with evoked response data
J. Comput. Assist. Tomogr.
The relationship between reaction time and psychometric intelligence in a rural Guatemalan adolescent population
Int. J. Psychol.
Prediction and preparation, fundamental functions of the cerebellum
Learn. Memory
Why voxel based morphometric analysis should be used with great caution when characterizing group differences
NeuroImage
Cerebral structures participating in motor preparation in humans: a positron emission tomography study
J. Neurophysiol.
Clinical applications of diffusion tensor imaging
J. Magn. Reson. Imaging
Experience-dependent changes in cerebellar contribution to motor sequence learning
PNAS
An unfolded map of the cerebellar dentate nucleus and its projections to the cerebral cortex
J. Neurophysiol.
Cited by (16)
Connectome-based models can predict processing speed in older adults
2020, NeuroImageCitation Excerpt :A previous rs-fMRI study revealed that a faster PS was associated with stronger functional connectivity between the left primary motor cortex and the right precentral and postcentral gyrus (Koenig et al., 2014), suggesting that connectivity strength within the motor network was positively correlated with PS performance. Furthermore, structural MRI studies found converging evidence that PS depends on processes subserved by the frontal regions and cerebellum (Böhr et al., 2007; Eckert et al., 2010; Kennedy and Raz, 2009). Task-related (Forn et al., 2009; Gawryluk et al., 2014; for review, see Silva et al., 2018) and task-demand-related activations (Forn et al., 2013) have been reported in the frontal, parietal, occipital and temporal lobes and the cerebellum.
Determining the optimal window size of office buildings considering the workers' task performance and the building's energy consumption
2020, Building and EnvironmentCitation Excerpt :The subjects were to push the spacebar as fast as they could by responding to the sound at a certain volume and pitch. The average reaction time of the subjects (the average time between the time the sound was played and the time it took the subjects to push the spacebar) was set as the evaluation index (refer to Fig. 5(a)) [35,36]. Auditory backward digit span test: This test enables the evaluation of the subjects' short-term memory ability, which is included in the executive function.
Vision of the body improves inter-hemispheric integration of tactile-motor responses
2017, Acta PsychologicaCitation Excerpt :The most likely anatomical pathway to mediate this effect is considered to be the corpus callosum (CC) (Berlucchi, Aglioti, Marzi, & Tassinari, 1995; Marzi, Bisiacchi, & Nicoletti, 1991; Poffenberger, 1912). Although most studies using this paradigm have investigated the CUD effect in the visual domain (Bashore, 1981; Chaumillon, Blouin, & Guillaume, 2014; Jeeves, 1969; Pellicano, Barna, Nicoletti, Rubichi, & Marzi, 2013), several studies have found that the same effect also holds for other sensory modalities such as audition (Böhr et al., 2007; Elias, Bulman-Fleming, & McManus, 2000) and touch (Kaluzny, Palmeri, & Wiesendanger, 1994; Moscovitch & Smith, 1979; Muram & Carmon, 1972; Schieppati, Musazzi, Nardone, & Seveso, 1984; Tamè & Longo, 2015; Tassinari & Campara, 1996). Recently we used this paradigm to show that interhemispheric integration of the tactile and motor responses varies as a function of the specific body part stimulated (Tamè & Longo, 2015).
Early life trauma is associated with altered white matter integrity and affective control
2016, Journal of Psychiatric ResearchCitation Excerpt :However, some other groups have found that the relationship between FA and performance is not always inversed. In a later study, results showed that FA in areas of the cerebellar white matter correlated positively with auditory reaction time in young healthy adults (Bohr et al., 2007). In a sample of children diagnosed with Williams syndrome, Hoeft et al. (Hoeft et al., 2007) showed that worse performance on a visuo-spatial task was associated with greater FA.
DTI reveals structural differences in white matter tracts between bilingual and monolingual children
2012, Brain ResearchCitation Excerpt :In the lIFOF, FA differed significantly between simultaneous bilinguals and sequential and monolingual subjects, while in the AC-OL tract only the difference between simultaneous bilinguals and monolinguals remained significant. Previous research has shown that differences in mean FA values could, in principle, correspond to variations in the number of axons, axon density, size of axons and degree of myelination, and that FA values correlate with information transmission properties (auditory reaction time (Böhr et al., 2007), cognitive processing speed (Turken et al., 2008), information processing speed (Penke et al., 2010; Segura et al., 2009, 2010)). Based on existing studies and the specificities of language processing, we aimed our investigation of FA at four bundles of fibers among several bundles associating with language processing and communication.