Interval time coding by neurons in the presupplementary and supplementary motor areas

Mita, Akihisa; Mushiake, Hajime; Shima, Keisetsu; Matsuzaka, Yoshiya; Tanji, Jun

doi:10.1038/nn.2272

Cited by 272 publications

(267 citation statements)

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“…Importantly, results from macaque studies show that activity in lateral intraparietal area (LIP), the macaque homologue of IPS (Grefkes and Fink, 2005), accords with predictions of the diffusion model and covaries with behavior (Roitman and Shadlen, 2002), consistent with previous macaque work demonstrating a link between LIP activity and response selection (reviewed in Andersen et al, 1997). In contrast, recordings in the macaque homologues of MT+ and SMA implicate them in either sensory (Gold and Shadlen, 2007) or motor (Mita et al, 2009) tasks, respectively. These results suggest that IPS may participate in sensorimotor transformations in humans.…”

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confidence: 78%

The neural representation of sensorimotor transformations in a human perceptual decision making network

Erickson

Kayser

2013

NeuroImage

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Humans can quickly engage a neural network to transform complex visual stimuli into a motor response. Activity from a key region within this network, the intraparietal sulcus (IPS), has been associated with evidence accumulation and motor planning, thus implicating it in sensorimotor transformations. If such transformations occur within a brain region, a key and untested prediction is that neural activity reflecting both the parametric amount of evidence available and the timing of motor planning can be independently manipulated. To investigate these ideas, we constructed a dot motion discrimination task in which information about response modality (what to use) and response mapping (how to use it) was provided independently either before or after presentation of a dot motion coherence stimulus whose strength varied across trials. Consistent with our hypothesis, activity within IPS covaried with dot motion coherence during the stimulus phase, and as information necessary for the response was delayed, the peak of IPS activity shifted to the response phase. In contrast, areas such as the motion-sensitive region MT+ and the supplementary motor area demonstrated activity limited to the stimulus and response phases of the task, respectively. These results show that activity in IPS correlates with temporally dissociable representations consistent with both evidence accumulation and motor planning, and suggest that IPS is a core component for sensorimotor transformations within the perceptual decision-making network.© 2013 Elsevier Inc. All rights reserved. IntroductionThe ability to link sensation with action is integral to even the most fundamental of decisions. In humans, a number of studies have identified a frontoparietal network involved in processes during perceptual decisions, including sensory processing, attentional control, evidence accumulation, and motor planning (Heekeren et al., 2008; Kayser et al., 2010a,b;Liu and Pleskac, 2011;Ploran et al., 2007Ploran et al., , 2011Rowe et al., 2010;Ho et al., 2009;Tosoni et al., 2008). Previously we demonstrated that for subjects performing a dot motion discrimination task, this network displays a blood oxygen level-dependent (BOLD) response that varies inversely with motion coherence (Kayser et al., 2010a). Consistent with previous and subsequent findings (e.g., Hebart et al., 2012;Ho et al., 2009;Kayser et al., 2010b), this negative parametric effect matched predictions of a proportional-rate diffusion model for evidence accumulation to a threshold (Palmer et al., 2005;Ratcliff and McKoon, 2008), and linked human brain activity with a computational model of the transformation from stimulus to response.Although this parametric effect is necessary, it is not sufficient to define regions that support such sensorimotor transformations. Human studies, for example, show that areas such as the motion-sensitive region MT+, supplementary motor area (SMA), and intraparietal sulcus (IPS) all display this parametric effect. Importantly, results from macaque studies show that ...

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confidence: 78%

The neural representation of sensorimotor transformations in a human perceptual decision making network

Erickson

Kayser

2013

NeuroImage

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“…Timing-related signals have been observed in neuronal activity in a variety of brain regions, including PFC (7,(29)(30)(31)(32), lateral intraparietal area (LIP) (33,34), presupplementary and supplementary motor areas (35), basal ganglia (32, 36, 37), cerebellum (3), and thalamus (38). In monkeys performing the time-discrimination task, the LIP neuronal activity ramps up or down at slow and fast speeds in long and short timing tasks, respectively (33), consistent with temporal scaling.…”

Section: Discussionmentioning

confidence: 99%

Representation of interval timing by temporally scalable firing patterns in rat prefrontal cortex

Zhang

Dan

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

141

128

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Perception of time interval on the order of seconds is an essential component of cognition, but the underlying neural mechanism remains largely unknown. In rats trained to estimate time intervals, we found that many neurons in the medial prefrontal cortex (PFC) exhibited sustained spiking activity with diverse temporal profiles of firing-rate modulation during the time-estimation period. Interestingly, in tasks involving different intervals, each neuron exhibited firing-rate modulation with the same profile that was temporally scaled by a factor linearly proportional to the instructed intervals. The behavioral variability across trials within each task also correlated with the intertrial variability of the temporal scaling factor. Local cooling of the medial PFC, which affects neural circuit dynamics, significantly delayed behavioral responses. Thus, PFC neuronal activity contributes to time perception, and temporally scalable firing-rate modulation may reflect a general mechanism for neural representation of interval timing. P erception of time on the order of seconds (interval timing) is crucial for a variety of behaviors (1-4). In interval timingrelated tasks, the animal must keep track of the elapsed time from a previous event and decide when to anticipate a future event or to execute motor actions. Whereas timing perception in shorter timescale (e.g., motor timing) is controlled by automatic timing system in the cerebellum (5, 6), interval timing is thought to involve prefrontal and parietal cortices (7), which are associated with attention and working memory (8). However, how timing information is represented in the neural activity in these cortical areas is unclear. To understand how the brain performs time estimation, it would be particularly useful to examine changes in the pattern of neuronal activity when the animal estimates different time intervals. We thus designed a behavioral task in which the rat was required to estimate two time intervals in the same behavioral session, and multiple single-unit recording was performed concurrently to examine how the task timing was represented by activities of medial prefrontal cortex (mPFC) neurons. Finally, local brain cooling was applied to explore whether mPFC neural network dynamics play causal role in the animal's perception of time intervals on the order of seconds. ResultsAdult rats were trained to perform the time-estimation task ( Fig. 1A and Movie S1), with two instructed durations (1.5 and 2.5 s) in alternating blocks of trials. Each trial was initiated when the rat poked the nose into the waiting port. After a random delay (drawn from a uniform distribution within 0.5-1.5 s), a sound stimulus was presented to indicate the instructed duration of either 1.5 s (pure tone) or 2.5 s (white noise). During "instructive trials," the sound was presented for the instructed duration, and the rat was rewarded only if it exited from the waiting port within a ∼1-s window (Materials and Methods) at the sound termination. The "exit time" is defined as the time be...

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“…In addition, many neurons in the pre-SMA, but rarely in the SMA, were "time-selective," meaning that they encoded the instruction given in the task (Mita et al 2009). The authors suggested that pre-SMA was therefore involved in retrieving information to structure the forthcoming motor behavior.…”

Section: Is Timing a General Function Of The Medial Frontal Cortex?mentioning

confidence: 99%

A Neural Representation of Sequential States Within an Instructed Task

Campos

Breznen

Andersen

2010

Journal of Neurophysiology

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Campos M, Breznen B, Andersen RA. A neural representation of sequential states within an instructed task. J Neurophysiol 104: 2831-2849, 2010. First published August 25, 2010 doi:10.1152/jn.01124.2009. In the study of the neural basis of sensorimotor transformations, it has become clear that the brain does not always wait to sense external events and afterward select the appropriate responses. If there are predictable regularities in the environment, the brain begins to anticipate the timing of instructional cues and the signals to execute a response, revealing an internal representation of the sequential behavioral states of the task being performed. To investigate neural mechanisms that could represent the sequential states of a task, we recorded neural activity from two oculomotor structures implicated in behavioral timing-the supplementary eye fields (SEF) and the lateral intraparietal area (LIP)-while rhesus monkeys performed a memory-guided saccade task. The neurons of the SEF were found to collectively encode the progression of the task with individual neurons predicting and/or detecting states or transitions between states. LIP neurons, while also encoding information about the current temporal interval, were limited with respect to SEF neurons in two ways. First, LIP neurons tended to be active when the monkey was planning a saccade but not in the precue or intertrial intervals, whereas SEF neurons tended to have activity modulation in all intervals. Second, the LIP neurons were more likely to be spatially tuned than SEF neurons. SEF neurons also show anticipatory activity. The state-selective and anticipatory responses of SEF neurons support two complementary models of behavioral timing, state dependent and accumulator models, and suggest that each model describes a contribution SEF makes to timing at different temporal resolutions.

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Interval time coding by neurons in the presupplementary and supplementary motor areas

Cited by 272 publications

References 48 publications

The neural representation of sensorimotor transformations in a human perceptual decision making network

The neural representation of sensorimotor transformations in a human perceptual decision making network

Representation of interval timing by temporally scalable firing patterns in rat prefrontal cortex

A Neural Representation of Sequential States Within an Instructed Task

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