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Research on interval timing strongly implicates the cerebellum and the basal ganglia as part of the timing network of the brain. Here we tested the hypothesis that the brain uses differential timing mechanisms and networks--specifically, that the cerebellum subserves the perception of the absolute duration of time intervals, whereas the basal ganglia mediate perception of time intervals relative to a regular beat. In a functional magnetic resonance imaging experiment, we asked human subjects to judge the difference in duration of two successive time intervals as a function of the preceding context of an irregular sequence of clicks (where the task relies on encoding the absolute duration of time intervals) or a regular sequence of clicks (where the regular beat provides an extra cue for relative timing). We found significant activations in an olivocerebellar network comprising the inferior olive, vermis, and deep cerebellar nuclei including the dentate nucleus during absolute, duration-based timing and a striato-thalamo-cortical network comprising the putamen, caudate nucleus, thalamus, supplementary motor area, premotor cortex, and dorsolateral prefrontal cortex during relative, beat-based timing. Our results support two distinct timing mechanisms and underlying subsystems: first, a network comprising the inferior olive and the cerebellum that acts as a precision clock to mediate absolute, duration-based timing, and second, a distinct network for relative, beat-based timing incorporating a striato-thalamo-cortical network.
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... It is 10 therefore of critical importance to first understand how the brain tracks the beat, to 11 then find ways to monitor and support the rehabilitation of dysfunctional timing 12 processes in individuals with those disorders. 13 The human brain's timing system comprises a number of structures that were 14 traditionally associated with motor functions and include the basal ganglia, cerebellum, 15 and parietal, temporal and frontal areas. The activation of this network of structures 16 has been indicated by neuroimaging work [9][10][11], and corroborated by 17 neuropsychological [6,12] and transcranial magnetic stimulation studies [13], two 18 essential methodologies that support a direct test of the criticalness of the given brain 19 structures. ...
... duration-based, 21 implicit or explicit timing. The supplementary motor area and basal ganglia for 22 instance have been repeatedly reported to be more engaged in beat-based timing [14], 23 and that with further sub-specialization in finding vs. keeping the beat for instance [15]. 24 However, findings are not entirely consistent in terms of the specificity of criticalness 25 (e.g. ...
... [20]). More specifically, the timing 31 system has been promoted to feature the entrainment of neural oscillations in the beta 32 range (13)(14)(15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) with the periodicity of the beat in musical rhythms [21]. 33 In attempts to get to the bottom of the structural and functional neural correlates 34 that underlie our entrainment with and "feeling of the beat", previous MEG and EEG 35 work both demonstrated clear effects in oscillatory activity. ...
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We propose here (the informed use) of a customised, data-driven machine-learning pipeline to analyse magnetoencephalography (MEG) in a theoretical source space, with respect to the processing of a regular beat. This hypothesis- and data-driven analysis pipeline allows us to extract the maximally relevant components in MEG source-space, with respect to the oscillatory power in the frequency band of interest and, most importantly, the beat-related modulation of that power. Our pipeline combines Spatio-Spectral Decomposition as a first step to seek activity in the frequency band of interest (SSD, [1]) with a Source Power Co-modulation analysis (SPoC; [2]), which extracts those components that maximally entrain their activity with the given target function, that is here with the periodicity of the beat in the frequency domain (hence, f-SPoC). MEG data (102 magnetometers) from 28 participants passively listening to a 5-min long regular tone sequence with a 400 ms beat period (the “target function” for SPoC) were segmented into epochs of two beat periods each to guarantee a sufficiently long time window. As a comparison pipeline to SSD and f-SpoC, we carried out a state-of-the-art cluster-based permutation analysis (CBPA, [3]). The time-frequency analysis (TFA) of the extracted activity showed clear regular patterns of periodically occurring peaks and troughs across the alpha and beta band (8-20 Hz) in the f-SPoC but not in the CBPA results, and both the depth and the specificity of modulation to the beat frequency yielded a significant advantage. Future applications of this pipeline will address target the relevance to behaviour and inform analogous analyses in the EEG, in order to finally work toward addressing dysfunctions in beat-based timing and their consequences. Author summary When listening to a regular beat, oscillations in the brain have been shown to synchronise with the frequency of that given beat. This phenomenon is called entrainment and has in previous brain-imaging studies been shown in the form of one peak and trough per beat cycle in a range of frequency bands within 15-25 Hz (beta band). Using machine-learning techniques, we designed an analysis pipeline based on Source-Power Co-Modulation (SPoC) that enables us to extract spatial components in MEG recordings that show these synchronisation effects very clearly especially across 8-20 Hz. This approach requires no anatomical knowledge of the individual or even the average brain, it is purely data driven and can be applied in a hypothesis-driven fashion with respect to the “function” that we expect the brain to entrain with and the frequency band within which we expect to see this entrainment. We here apply our customised pipeline using “f-SPoC” to MEG recordings from 28 participants passively listening to a 5-min long tone sequence with a regular 2.5 Hz beat. In comparison to a cluster-based permutation analysis (CBPA) which finds sensors that show statistically significant power modulations across participants, our individually extracted f-SPoC components find a much stronger and clearer pattern of peaks and troughs within one beat cycle. In future work, this pipeline can be implemented to tackle more complex “target functions” like speech and music, and might pave the way toward rhythm-based rehabilitation strategies.
... To form appropriate temporal expectation, our brain usually relies on two dimensions of temporal information, namely the absolute, interval/duration-based timing and the relative, rhythm/beat-based timing (Teki, Grube, Kumar, & Griffiths, 2011). Whereas both interval-based and rhythm-based timings facilitate temporal expectation and usually coexist and complement each other (Nobre & van Ede, 2018), their underlying mechanisms in forming temporal expectation are dissociable (Breska & Ivry, 2018;Teki et al., 2011) and likely lead to multiple functional circuits supporting the interplay between temporal expectation and cognitive resource allocation. ...
... To form appropriate temporal expectation, our brain usually relies on two dimensions of temporal information, namely the absolute, interval/duration-based timing and the relative, rhythm/beat-based timing (Teki, Grube, Kumar, & Griffiths, 2011). Whereas both interval-based and rhythm-based timings facilitate temporal expectation and usually coexist and complement each other (Nobre & van Ede, 2018), their underlying mechanisms in forming temporal expectation are dissociable (Breska & Ivry, 2018;Teki et al., 2011) and likely lead to multiple functional circuits supporting the interplay between temporal expectation and cognitive resource allocation. As is often the case, interval-based and rhythm-based temporal expectations modulate different aspects of behaviors, with the former mainly on the perceptual level and the latter on the motor response level (Morillon, Schroeder, Wyart, & Arnal, 2016). ...
... Such temporal dynamics of LC also coincide well with the refractory response of voluntary attention proposed in a recent dynamic model of temporal attention (Denison, Carrasco, & Heeger, 2021). On the other hand, time perception also recruits various subcortical structures, especially the cerebellum and the basal ganglia (Teki et al., 2011). As goal-directed behaviors are supposed to flexibly prioritize relevant sensory information (Shalev & van Ede, 2021), one may assume that voluntary attentional recovery (Denison et al., 2021), therefore the AB phenomenon, can be modulated by temporal information via those subcortical structures. ...
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The attentional blink (AB) reveals a limitation in conscious processing of sequential targets. Although it is widely held that the AB derives from a structural bottleneck of central capacity, how the central processing is constrained is still unclear. As the AB reflects the dilemma of deploying attentional resources in the time dimension, research on temporal allocation provides an important avenue for understanding the mechanism. Here we reviewed studies regarding the role of temporal expectation in modulating the AB performance primarily based on two temporal processing strategies: interval-based and rhythm-based timings. We showed that both temporal expectations can help to organize limited resources among multiple attentional episodes, thereby mitigating the AB effect. As it turns out, scrutinizing on the AB from a temporal perspective is a promising way to comprehend the mechanisms behind the AB and conscious cognition. We also highlighted some unresolved issues and discussed potential directions for future research.
... Previous rhythm perception studies have, thus far, typically focused on simple stimuli such as trains of clicks or tones [72]. A network comprising basal ganglia, thalamus and cortical (mostly motor-related) areas seems to be critical for the human ability to perform beat-based timing tasks, during which deviations from isochrony are detected [82][83][84]. It is not fully clear whether similar regions are also important for the extraction of rhythm in speech sounds, although some studies support this notion [68,85]. ...
... However, further research will be required to determine whether this, or an alternative "duration-based timing" mechanism is responsible for the present findings. This latter mechanism allows the absolute duration of an interval to be judged without an underlying beat, and seems to rely on a different underlying brain network centred on the cerebellum [82][83][84]. ...
Article
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Auditory rhythms are ubiquitous in music, speech, and other everyday sounds. Yet, it is unclear how perceived rhythms arise from the repeating structure of sounds. For speech, it is unclear whether rhythm is solely derived from acoustic properties (e.g., rapid amplitude changes), or if it is also influenced by the linguistic units (syllables, words, etc.) that listeners extract from intelligible speech. Here, we present three experiments in which participants were asked to detect an irregularity in rhythmically spoken speech sequences. In each experiment, we reduce the number of possible stimulus properties that differ between intelligible and unintelligible speech sounds and show that these acoustically-matched intelligibility conditions nonetheless lead to differences in rhythm perception. In Experiment 1, we replicate a previous study showing that rhythm perception is improved for intelligible (16-channel vocoded) as compared to unintelligible (1-channel vocoded) speech-despite near-identical broadband amplitude modulations. In Experiment 2, we use spectrally-rotated 16-channel speech to show the effect of intelligibility cannot be explained by differences in spectral complexity. In Experiment 3, we compare rhythm perception for sine-wave speech signals when they are heard as non-speech (for naïve listeners), and subsequent to training, when identical sounds are perceived as speech. In all cases, detection of rhythmic regularity is enhanced when participants perceive the stimulus as speech compared to when they do not. Together, these findings demonstrate that intelligibility enhances the perception of timing changes in speech, which is hence linked to processes that extract abstract linguistic units from sound.
... Though the study of timing differences in autism has focused mainly on interval timing, recent evidence has also suggested differences in neural and motor entrainment to rhythmicity (Beker et al., 2021;Vishne et al., 2021). Temporal orienting via rhythmic cueing has been shown to draw on different subcortical neural mechanisms than temporal orienting through learned interval timing: the former is thought to be more dependent on cerebellum, while the latter is thought to draw more on the basal ganglia (Teki et al., 2011). Structural and functional differences associated with both of these areas have been hypothesized to underlie different aspects of autism phenotypes (Blaylock, 2010;Hampson & Blatt, 2015;Subramanian et al., 2017); thus, the study and comparison of intervallic and rhythmic temporal orienting could help to expose subcortical contributions to autism. ...
Article
Individuals with autism spectrum disorder (ASD) may show secondary sensory and cognitive characteristics, including differences in auditory processing, attention, and, according to a prominent hypothesis, the formulation and utilization of predictions. We explored the overlap of audition, attention, and prediction with an online auditory "temporal orienting" task in which participants utilized predictive timing cues (both rhythmic and interval-based) to improve their detection of faint sounds. We compared an autistic (n = 78) with a nonautistic (n = 83) group, controlling for nonverbal IQ, and used signal detection measures and reaction times to evaluate the effect of valid temporally predictive cues. We hypothesized that temporal orienting would be compromised in autism, but this was not supported by the data: the boost in performance induced by predictability was practically identical for the two groups, except for the small subset of the ASD group with co-occurring attention deficit hyperactivity disorder, who received less benefit from interval-based cueing. However, we found that the presence of a rhythm induced a significantly stronger bias toward reporting target detections in the ASD group at large, suggesting weakened response inhibition during rhythmic entrainment.
... These results represent a fundamental, previously unreported difference in rhythmic temporal processing (or at least auditory rhythmic temporal processing) in ASD that manifests in both perceptual and motor timing tasks. A recent meta-analysis shows that most timing functions on the sub-second timescale seem to be intact in autistic adults 19 ; however, none of the reviewed literature looked specifically at rhythmic timing, which is known to draw on different neural mechanisms than interval timing 30 . Since our findings run contrary to the general consensus on sub-second timing in autism and to the results in a previous study, it is important that these results be replicated before they can be taken as authoritative. ...
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Recent results suggest that autistic individuals find it challenging to temporally coordinate their actions with predictable external cues, as indicated, for instance, by lower accuracy in synchronizing finger taps to an auditory metronome compared with their non-autistic peers. However, it is not yet clear whether these difficulties are driven primarily by motor or perceptual impairments. We recruited autistic and non-autistic participants for an online study which tested both finger tapping synchronization and continuation as well as purely perceptual (non-motoric) rhythmic timing. We fractionated each participant’s synchronization results into several individual-specific parameters representing error correction, motor noise, and internal time-keeper noise, and also investigated error-correcting responses to small timing perturbations in metronome timing. Contrary to previous work, we did not find strong evidence for reduced tapping error correction. However, we found compelling evidence for noisier internal rhythmic time-keeping in the synchronization, continuation, and perceptual components of the experiment. These results suggest that noisier rhythmic timing processes underlie some sensorimotor coordination challenges in autism.
... By recording the activity in the dentate nucleus, they noted an increase in the basal firing rate correlated with the succession of stimuli (ramping across hundreds of milliseconds). This evidence could disprove the hypothesis for which the cerebellum is involved exclusively in duration-estimation timing (as opposed to basal ganglia that rely on beat timing) (Teki et al., 2011) or could hint at an influence of the basal ganglia on the cerebellum. ...
Thesis
A growing body of literature is showing an involvement of the cerebellum in managing time predictions and expectations of motor and cognitive events. On the other hand the medial prefrontal cortex (mPFC) is widely considered the area where there is the integration between internal models and cognition. Moreover, mPFC is involved in most of the models for time perception, making it an ideal candidate for handling predictive behaviors. Both tracing experiments and interval timing task highlighted a connection between these two areas. We thus developed a model to investigate the role of the cerebellum in the creation and update of implicit temporal predictions in mPFC of mice. We recorded the extracellular activity in the mPFC (specifically left prelimbic area, PrL) while the head-restrained mice perform the following variable foreperiod task : two cues are presented in a sequence followed by a reward delivered at either a fixed or a variable time point (randomly chosen between two possible delays). At the same time, we photoactivate cerebellar Purkinje cells of L7-Channelrhdopsin2 mice at specific frequencies, above contralateral Crus I. The aim of the optogenetic stimulation is to interfere with neuronal discharge in the mPFC. We confirm the foreperiod effect, already described in the literature, for which responses are faster and more accurate when an interval between a cue and a go signal/reward (foreperiod) is constant. Interestingly we report different behavior of two important prefrontal oscillations: delta (1.5-4Hz) and theta (4-10Hz). They show ramping behavior only when the foreperiod is variable and fixed, respectively. Moreover, cerebellar photostimulation affects these oscillations only if they are ramping. This is probably representative of different neural substrates recruited by the two foreperiod conditions.
... La percepción del ritmo implica dos tipos de percepción del tiempo: el tiempo basado en intervalos -absolutoy el tiempo basado en latidos -relativo- (Grube et al., 2010;Ross et al., 2016;Iversen y Balasubramaniam, 2016). El primero hace referencia a la capacidad de discriminar diferencias entre un intervalo de tiempo, mientras que el segundo hace referencia a la capacidad de establecer intervalos de tiempo en relación con las regularidades subyacentes a ese tempo (Teki et al., 2011). Por tanto, aquella percepción relacionada con la sensación de un ritmo regular -la basada en latidos-, la prominencia del ritmo y la acentuación provocan en la mente del oyente un fuerte componente perceptual debido a las regularidades que presenta la duración del estímulo auditivo (Nozaradan et al., 2011;Honing, 2012;Ravignani et al., 2017). ...
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Las imágenes mentales sonoras son el producto de las copias o reconstrucciones de experiencias perceptivas del pasado o el producto de anticipación de experiencias futuras posibles, pero en ausencia de los estímulos externos apropiados. Sin embargo, en el área musical, no se conoce a ciencia cierta cómo interactúan estas con percepciones visuales externas en la recreación o generación de imágenes mentales auditivas. A lo largo de esta revisión bibliografía se tratará de discernir cómo cada una de las cualidades del sonido infiere o provoca una respuesta en los procesos de pensamiento y proporciona la base semántica para el lenguaje musical.
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The measurement of time in the subsecond scale is critical for many sophisticated behaviors, yet its neural underpinnings are largely unknown. Recent neurophysiological experiments from our laboratory have shown that the neural activity in the medial premotor areas (MPC) of macaques can represent different aspects of temporal processing. During single interval categorization, we found that preSMA encodes a subjective category limit by reaching a peak of activity at a time that divides the set of test intervals into short and long. We also observed neural signals associated with the category selected by the subjects and the reward outcomes of the perceptual decision. On the other hand, we have studied the behavioral and neurophysiological basis of rhythmic timing. First, we have shown in different tapping tasks that macaques are able to produce predictively and accurately intervals that are cued by auditory or visual metronomes or when intervals are produced internally without sensory guidance. In addition, we found that the rhythmic timing mechanism in MPC is governed by different layers of neural clocks. Next, the instantaneous activity of single cells shows ramping activity that encode the elapsed or remaining time for a tapping movement. In addition, we found MPC neurons that build neural sequences, forming dynamic patterns of activation that flexibly cover all the produced interval depending on the tapping tempo. This rhythmic neural clock resets on every interval providing an internal representation of pulse. Furthermore, the MPC cells show mixed selectivity, encoding not only elapsed time, but also the tempo of the tapping and the serial order element in the rhythmic sequence. Hence, MPC can map different task parameters, including the passage of time, using different cell populations. Finally, the projection of the time varying activity of MPC hundreds of cells into a low dimensional state space showed circular neural trajectories whose geometry represent the internal pulse and the tapping tempo. Overall, these findings support the notion that MPC is part of the core timing mechanism for both single interval and rhythmic timing, using neural clocks with different encoding principles, probably to flexibly encode and mix the timing representation with other task parameters.
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Music is increasingly being used as a therapeutic tool in the field of rehabilitation medicine and psychophysiology. One of the main key components of music is its temporal organization. The characteristics of neurocognitive processes during music perception of meter in different tempo variations technique have been studied by using the event-related potentials technique. The study involved 20 volunteers (6 men, the median age of the participants was 23 years). The participants were asked to listen to 4 experimental series that differed in tempo (fast vs. slow) and meter (duple vs. triple). Each series consisted of 625 audio stimuli, 85% of which were organized with a standard metric structure (standard stimulus) and 15% were organized with a modified metric structure (deviant stimulus). The results revealed that the type of metric structure influences the detection of the change in it. The analysis revealed that the N200 wave occurred significantly faster for stimuli with duple meter and fast tempo and was the slowest for stimuli with triple meter and fast pace.
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Important characteristics of the environment can be transduced and represented in the temporal patterning of sensory stimulation. In two experiments, we compared accuracy of temporal processing by different modalities. Experiment 1 examined binary categorization of rate for visual (V) or vibrotactile (T) stimulus pulses presented at either 4 or 6 Hz. Inter-pulse intervals were either constant or variable, perturbed by random Gaussian variates. Subjects categorized the rate of T pulse sequences more accurately than V sequences. In V conditions only, subjects disproportionately tended to mis-categorize 4-Hz pulse rates, for all but the most variable sequences. We hypothesized that this pattern of errors arose because individual V pulses appeared longer in duration, disproportionately causing V sequences to appear fast. We tested this hypothesis in Experiment 2, using simpler stimuli and a two-interval forced choice method. Gap detection thresholds were taken with the same two modalities as in Experiment 1, and also with bimodal (VT) stimuli. As predicted, visual gap thresholds were larger (3×) than tactile thresholds. Additionally, performance with VT stimuli seemed to be nearly completely dominated by their T components. Together, these results suggest considerable, untapped potential for vibrotactile stimulation to convey temporal information like that needed for eyes-free alerting signals.
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The cerebellum is known to project via the thalamus to multiple motor areas of the cerebral cortex. In this study, we examined the extent and anatomical organization of cerebellar input to multiple regions of prefrontal cortex. We first used conventional retrograde tracers to map the origin of thalamic projections to five prefrontal regions: medial area 9 (9m), lateral area 9 (9l), dorsal area 46 (46d), ventral area 46, and lateral area 12. Only areas 46d, 9m, and 9l received substantial input from thalamic regions included within the zone of termination of cerebellar efferents. This suggested that these cortical areas were the target of cerebellar output. We tested this possibility using retrograde transneuronal transport of the McIntyre-B strain of herpes simplex virus type 1 from areas of prefrontal cortex. Neurons labeled by retrograde transneuronal transport of virus were found in the dentate nucleus only after injections into areas 46d, 9m, and 9l. The precise location of labeled neurons in the dentate varied with the prefrontal area injected. In addition, the dentate neurons labeled after virus injections into prefrontal areas were located in regions spatially separate from those labeled after virus injections into motor areas of the cerebral cortex. Our observations indicate that the cerebellum influences several areas of prefrontal cortex via the thalamus. Furthermore, separate output channels exist in the dentate to influence motor and cognitive operations. These results provide an anatomical substrate for the cerebellum to be involved in cognitive functions such as planning, working memory, and rule-based learning.
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This study investigated the effects of different types of neurological deficits on timing functions. The performance of Parkinson, cerebellar, cortical, and peripheral neuropathy patients was compared to age-matched control subjects on two separate measures of timing functions. The first task involved the production of timed intervals in which the subjects attempted to maintain a simple rhythm. The second task measured the subjects' perceptual ability to discriminate between small differences in the duration of two intervals. The primacy of the cerebellum in timing functions was demonstrated by the finding that these were the only patients who showed a deficit in both the production and perception of timing tasks. The cerebellar group was found to have increased variability in performing rhythmic tapping and they were less accurate than the other groups in making perceptual discriminations regarding small differences in duration. Critically, this perceptual deficit appears to be specific to the perception of time since the cerebellar patients were unaffected in a control task measuring the perception of loudness. It is argued that the operation of a timing mechanism can be conceptualized as an isolable component of the motor control system. Furthermore, the results suggest that the domain of the cerebellar timing process is not limited to the motor system, but is employed by other perceptual and cognitive systems when temporally predictive computations are needed.
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Projections from the cerebellar and dorsal column nuclei to the inferior olive of the rhesus monkey were traced with anterograde autoradiographic methods. The cerebellar nuclei give rise to a massive projection which reaches the contralateral inferior olivary complex by way of the descending limb of the superior cerebellar peduncle. Dentato-olivary fibers project exclusively upon the principal olivary nucleus (PO) and observe a strict topography. The dorsal, lateral, and ventral dentate project respectively to the dorsal, lateral, and ventral lamellae of the PO. Within the lamellae, the dentato-olivary fibers are related point for point in the medio-lateral axis. By contrast, the rostro-caudal topography is reversed so that the rostral pole of the dentate projects to the caudal PO and the caudal dentate to the rostral PO. These connections are predominantly crossed but a small ipsilateral component recrosses the midline at the olivary commissure and mirrors the topography on the opposite side. The anterior interpositus projects only to the medial half of the DAO and the posterior interpositus projects only to the rostral two thirds of the MAO. The ipsilateral component is minor in comparison with the contralateral projection, but appears to be more substantial than the ïpsilateral projection to the PO arising from the dentate nucleus. The fastigial nucleus does not project upon the olivary complex. The dorsal column nuclei project topographically upon the contralateral accessory nuclei with the gracile nucleus sending fibers primarily to the lateal half of the DAO and the cuneate nucleus projecting to rostral cell groups of the MAO. The present results when compared with other olivary connections described by previous studies in a veriety of species suggest that regions of the MAO and DAO receiving sensory information from the periphery may lie outside the influence of cerebellar feedback loops.
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Statistical parametric maps are spatially extended statistical processes that are used to test hypotheses about regionally specific effects in neuroimaging data. The most established sorts of statistical parametric maps (e.g., Friston et al. [1991]: J Cereb Blood Flow Metab 11:690–699; Worsley et al. [1992]: J Cereb Blood Flow Metab 12:900–918) are based on linear models, for example ANCOVA, correlation coefficients and t tests. In the sense that these examples are all special cases of the general linear model it should be possible to implement them (and many others) within a unified framework. We present here a general approach that accomodates most forms of experimental layout and ensuing analysis (designed experiments with fixed effects for factors, covariates and interaction of factors). This approach brings together two well established bodies of theory (the general linear model and the theory of Gaussian fields) to provide a complete and simple framework for the analysis of imaging data. The importance of this framework is twofold: (i) Conceptual and mathematical simplicity, in that the same small number of operational equations is used irrespective of the complexity of the experiment or nature of the statistical model and (ii) the generality of the framework provides for great latitude in experimental design and analysis.
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What is the nature of the human timing mechanism for perceptual judgements about short temporal intervals? One possibility is that initial periodic events, such as tones, establish internal beats which continue after the external events and serve as reference points for the perception of subsequent events. A second possibility is that the timer records the intervals produced by events. Later, the stored intervals can be reproduced or compared to other intervals. A study by Schulze (1978) provided evidence favoring beat-based timing. In contrast, our two experiments support an interval theory. The judgements of intervals between tones is not improved when the events are synchronized with internal beats established by the initial intervals. The conflict between the two sets of results may be resolved by the fact that an interval timer can recycle from one interval to the next, thus operating in a beat-like mode. However, a timer of this sort is just as accurate when comparing intervals that are off the beat.
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In two experiments, the performance of listeners with different amounts of musical training (high skill, low skill) was examined in a two-alternative forced choice time-detection task involving simple five-cycle acoustic sequences. In each of a series of trials, all listeners determined which of two pattern cycles contained a small time change. Sequence context was also varied (regular vs. irregular timing). In Experiment 1, in which context was manipulated as a between-subjects variable, high-skill listeners performed significantly better than low-skill listeners only with regular patterns. In Experiment 2, in which context was manipulated as a within-subjects variable, the only significant source of variance was pattern context: All listeners were better at detecting time changes in regular than in irregular patterns. The results are considered in light of several hypotheses, including the expectancy/contrast model (Jones & Boltz, 1989).
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Seven experiments examine the influence of contextual timing manipulations on prospective time judgments. Subjects judged durations of standard vs comparison time intervals in the context of a preceding induction (context) sequence. In some experiments, the rate of the induction sequence was systematically manipulated relative to the range of to-be-judged standard time intervals; in others, the induction sequence was omitted. Time judgments were strongly influenced by the rate of an induction sequence with best performance occurring when the standard time interval ended as expected, given context rate. An expectancy profile, in the form of an inverted U, indicated that time estimation accuracy declined systematically as a standard interval differed from a context rate. A similar expectancy profile emerged when the context rate was based on a harmonic subdivision (one-half) of an expected standard interval. Results are discussed in terms of various stimulus-based models of prospective time judgments, including those which appeal to attentional periodicities and entrainment.