A representation of the hazard rate of elapsed time in macaque area LIP

Anatomical studies indicate that area F5 in the macaque ventral premotor cortex consists of three different sectors. One of these is F5a in the posterior bank of the inferior arcuate sulcus, but no functional characterization of F5a at the single-cell level exists. We investigated the neuronal selectivity for three-dimensional (3D) shape and grasping activity in F5a. In contrast to neighboring regions F5p and 45B, the great majority of F5a neurons showed selectivity for disparity-defined curved surfaces, and most neurons preserved this selectivity across positions in depth, indicating higher-order disparity selectivity. Thus, as predicted by monkey fMRI data, F5a neurons showed robust 3D-shape selectivity in the absence of a motor response. To investigate the relationship between disparity selectivity and grasping activity, we recorded from 3D-shape-selective F5a neurons during a visually guided grasping task and during grasping in the dark. F5a neurons encoding the depth profile of curved surfaces frequently responded during grasping of real-world objects in the light, but not in the dark, whereas nearby neurons were also active in the dark. The presence of 3D-shape-selective and "visual-dominant" neurons demonstrates that the F5a sector is distinct from neighboring regions of ventral premotor cortex, in line with recent anatomical connectivity studies.

Section: Population Analysis Of Grasping Activity In F5amentioning

confidence: 87%

Selectivity for Three-Dimensional Shape and Grasping-Related Activity in the Macaque Ventral Premotor Cortex

Theys

Pani²,

Loon

et al. 2012

“…The hazard functions obtained from the f ON densities will be referred to as the "f ON hazard rates." It has been suggested that hazard rates are estimated and used to guide behavior (Ghose and Maunsell, 2002;Janssen and Shadlen, 2005;Oswal et al, 2007). The latency of anticipatory pursuit movements could be considered as the outcome of this process.…”

Section: Hazard Ratementioning

confidence: 99%

“…In a visual detection task, it has been shown that the hazard rate could be used to guide the allocation of attention in the time domain (Ghose and Maunsell, 2002). Moreover, it has been shown that a subjective estimate of the hazard rate could describe the behavioral consequence of the anticipation of a "go" signal in a saccade task and could be represented in the LIP (lateral intraparietal area) of the macaque monkey (Janssen and Shadlen, 2005).…”

Section: Introductionmentioning

confidence: 99%

How Do Primates Anticipate Uncertain Future Events?

Hemptinne

Nozaradan²,

Duvivier³

et al. 2007

The timing of an upcoming event depends on two factors: its temporal position, proximal or distal with respect to the present moment, and the unavoidable stochastic variability around this temporal position. We searched for a general mechanism that could describe how these two factors influence the anticipation of an upcoming event in an oculomotor task. Monkeys were trained to pursue a moving target with their eyes. During a delay period inserted before target motion onset, anticipatory pursuit responses were frequently observed. We found that anticipatory movements were altered by the temporal position of the target. Increasing the timing uncertainty associated with the stimulus resulted in an increase in the width of the latency distribution of anticipatory pursuit. These results show that monkeys relied on an estimation of the changing probability of target motion onset as time elapsed during the delay to decide when to initiate an anticipatory smooth eye movement.

“…Neurons in lateral intraparietal area (LIP) seem to represent the passage of time relative to a remembered standard duration (Leon and Shadlen, 2003). Janssen and Shadlen (2005) recorded the activity of LIP neurons while monkeys made saccades to peripheral targets after a variable delay period. The timing of the "Go" signal (dimming of the fixation point) was a random value whose probability distribution was fixed throughout a block of trials.…”

Section: Neural Bases and Modelsmentioning

confidence: 99%

“…By now, many studies indicate that we can use temporal information flexibly and across multiple sensory modalities to orient at-tention selectively to specific intervals (Griffin et al, 2001;Lange et al, 2003;Correa et al, 2004). Positron emission tomography and fMRI studies have shown that control of temporal orienting in speeded-response tasks involves brain areas that participate in spatial orienting of attention as well as areas that participate in motor control (Coull and Nobre, 1998;Coull et al, 2000), including posterior parietal cortex, in which cellular correlates of temporal predictability have been identified (Janssen and Shadlen, 2005). Despite the sizeable overlap of brain areas participating in temporal and spatial orienting, the neural mechanisms involved in anticipating and modulating stimulus processing when each type of orienting occurs in isolation can differ substantially (Nobre, 2004).…”

Section: Neural Bases and Modelsmentioning

confidence: 99%

Time and the Brain: How Subjective Time Relates to Neural Time

Eagleman¹,

Tse²,

Buonomano³

et al. 2005

159

103

Most of the actions our brains perform on a daily basis, such as perceiving, speaking, and driving a car, require timing on the scale of tens to hundreds of milliseconds. New discoveries in psychophysics, electrophysiology, imaging, and computational modeling are contributing to an emerging picture of how the brain processes, learns, and perceives time.Key words: brain; time; behavior; perception; psychophysics; illusion; causality Brains have a difficult problem to solve. Signals from different modalities are processed at different speeds in distant neural regions, but to be useful to the organism as a whole, these signals must become aligned in time and correctly tagged to outside events (Eagleman, 2005b). Understanding the timing of events, such as a motor act followed by a sensory consequence, is critical for moving, speaking, determining causality, and decoding the barrage of temporal patterns at our sensory receptors.Despite its importance to behavior and perception, the neural bases of time perception remain shrouded in mystery. Scattered confederacies of investigators have been interested in time for decades, but only in the past few years has a concerted effort been applied to old problems. Now, experimental psychology is striving to understand how animals perceive and encode temporal intervals, whereas physiology, functional magnetic resonance imaging (fMRI), and EEG unmask how neurons and brain regions underlie temporal computations. In this review, we sketch parts of an emerging picture and highlight remaining confusions about time in the brain. Some of the overarching questions are as follows: How do brains encode and decode information that streams in through time? How are signals entering various brain regions at varied times coordinated with one another? What is the temporal precision with which perception represents the outside world? How are intervals, durations, and sequences coded in the brain? What factors (causality, attention, adrenaline, or eye movements) influence temporal judgments and why? Does the brain constantly recalibrate its time perception? In this minisymposium, we illustrate different experimental approaches that attempt to shine light on these questions and others. PsychophysicsMuch of what we know about time in the brain comes from psychophysical experiments. One class of studies involves ways in which time perception distorts: for example, during brief, dangerous events, such as car accidents and robberies, many people report that events pass in slow motion as if time slowed down. Recent studies have been able to quantify distorted time judgments during rapid eye movements (Eagleman, 2005a;Morrone et al., 2005) or after adaptation to flickering or moving stimuli (Johnston et al., 2005;Kanai and Verstraten, 2005).Although such examples are probably related to very low-level processes, other investigators have reported time distortions they believe are related to attentional shifts (Tse et al., 2004). For example, Tse and colleagues have shown that, when many stimuli are show...