Sources of noise during accumulation of evidence in unrestrained and voluntarily head-restrained rats

Scott, Bruce R.; Constantinople, Christine M.; Erlich, Jeffrey C; Tank, David W.; Brody, Carlos D.

doi:10.7554/elife.11308

Cited by 81 publications

(163 citation statements)

References 41 publications

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“…This is of possible broader interest, for example, in linking to rodent work (Erlich et al, 2015, Scott et al, 2015, Morcos and Harvey 2016, Pinto et al, 2017, Odoemene et al, 2017, Licata et al, 2017). …”

Section: Discussionmentioning

confidence: 99%

“…In other instances, however, “late weighting” has been observed, where choices were primarily influenced by sensory evidence presented in late stimulus epochs (Tsetsos et al, 2012; Cheadle et al, 2014; Bronfman et al, 2016; Carland et al, 2016). In rodents, a mixture of either early or flat weighting profiles has been reported (Erlich et al, 2015; Scott et al, 2015; Pinto et al, 2017; Licata et al, 2017). …”

Section: Introductionmentioning

confidence: 99%

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Strategic and Dynamic Temporal Weighting for Perceptual Decisions in Humans and Macaques

Levi

Yates

Huk

et al. 2018

eNeuro

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Perceptual decision-making is often modeled as the accumulation of sensory evidence over time. Recent studies using psychophysical reverse correlation have shown that even though the sensory evidence is stationary over time, subjects may exhibit a time-varying weighting strategy, weighting some stimulus epochs more heavily than others. While previous work has explained time-varying weighting as a consequence of static decision mechanisms (e.g., decision bound or leak), here we show that time-varying weighting can reflect strategic adaptation to stimulus statistics, and thus can readily take a number of forms. We characterized the temporal weighting strategies of humans and macaques performing a motion discrimination task in which the amount of information carried by the motion stimulus was manipulated over time. Both species could adapt their temporal weighting strategy to match the time-varying statistics of the sensory stimulus. When early stimulus epochs had higher mean motion strength than late, subjects adopted a pronounced early weighting strategy, where early information was weighted more heavily in guiding perceptual decisions. When the mean motion strength was greater in later stimulus epochs, in contrast, subjects shifted to a marked late weighting strategy. These results demonstrate that perceptual decisions involve a temporally flexible weighting process in both humans and monkeys, and introduce a paradigm with which to manipulate sensory weighting in decision-making tasks.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Strategic and Dynamic Temporal Weighting for Perceptual Decisions in Humans and Macaques

Levi

Yates

Huk

et al. 2018

eNeuro

View full text Add to dashboard Cite

show abstract

“…Studies have used visually stimuli in the upper visual field which require approach behaviors (Harvey, Collman, Dombeck, & Tank, 2009; Scott, Constantinople, Erlich, Tank, & Brody, 2015). Conversely, other studies have employed stimuli which occur in the lower visual field, and which require avoidance behaviors (Ho et al, 2015; Manita et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

Segregated fronto‐cortical and midbrain connections in the mouse and their relation to approach and avoidance orienting behaviors

Savage

McQuade

Thiele

2017

J of Comparative Neurology

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The orchestration of orienting behaviors requires the interaction of many cortical and subcortical areas, for example the superior colliculus (SC), as well as prefrontal areas responsible for top–down control. Orienting involves different behaviors, such as approach and avoidance. In the rat, these behaviors are at least partially mapped onto different SC subdomains, the lateral (SCl) and medial (SCm), respectively. To delineate the circuitry involved in the two types of orienting behavior in mice, we injected retrograde tracer into the intermediate and deep layers of the SCm and SCl, and thereby determined the main input structures to these subdomains. Overall the SCm receives larger numbers of afferents compared to the SCl. The prefrontal cingulate area (Cg), visual, oculomotor, and auditory areas provide strong input to the SCm, while prefrontal motor area 2 (M2), and somatosensory areas provide strong input to the SCl. The prefrontal areas Cg and M2 in turn connect to different cortical and subcortical areas, as determined by anterograde tract tracing. Even though connectivity pattern often overlap, our labeling approaches identified segregated neural circuits involving SCm, Cg, secondary visual cortices, auditory areas, and the dysgranular retrospenial cortex likely to be involved in avoidance behaviors. Conversely, SCl, M2, somatosensory cortex, and the granular retrospenial cortex comprise a network likely involved in approach/appetitive behaviors.

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“…A key advance has been the widespread adoption of head-fixation methods, first developed in the primate neurophysiology community (Wurtz, 1969) and then adapted the use in rodents (Dombeck et a., 2007) (see also Kleinfeld and Griesbeck (2005) and references therein). Both mice (Murphy et al, 2016) and rats (Scott et al, 2013; Scott et al, 2015) can be trained to voluntarily engage in head fixation, indicating that head fixation is not an aversive experience.…”

Section: Introductionmentioning

confidence: 99%

Time to wake up: Studying neurovascular coupling and brain-wide circuit function in the un-anesthetized animal

et al. 2017

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Functional magnetic resonance imaging (fMRI) has allowed the noninvasive study of task-based and resting-state brain dynamics in humans by inferring neural activity from blood-oxygenation-level dependent (BOLD) signal changes. An accurate interpretation of the hemodynamic changes that underlie fMRI signals depends on the understanding of the quantitative relationship between changes in neural activity and changes in cerebral blood flow, oxygenation and volume. While there has been extensive study of neurovascular coupling in anesthetized animal models, anesthesia causes large disruptions of brain metabolism, neural responsiveness and cardiovascular function. Here, we review work showing that neurovascular coupling and brain circuit function in the awake animal are profoundly different from those in the anesthetized state. We argue that the time is right to study neurovascular coupling and brain circuit function in the awake animal to bridge the physiological mechanisms that underlie animal and human neuroimaging signals, and to interpret them in light of underlying neural mechanisms. Lastly, we discuss recent experimental innovations that have enabled the study of neurovascular coupling and brain-wide circuit function in un-anesthetized and behaving animal models.

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Sources of noise during accumulation of evidence in unrestrained and voluntarily head-restrained rats

Cited by 81 publications

References 41 publications

Strategic and Dynamic Temporal Weighting for Perceptual Decisions in Humans and Macaques

Strategic and Dynamic Temporal Weighting for Perceptual Decisions in Humans and Macaques

Segregated fronto‐cortical and midbrain connections in the mouse and their relation to approach and avoidance orienting behaviors

Time to wake up: Studying neurovascular coupling and brain-wide circuit function in the un-anesthetized animal

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