Dataset Information

Natural motion trajectory enhances the coding of speed in primate extrastriate cortex.

ABSTRACT: The ability to estimate the speed of an object irrespective of size or texture is a crucial function of the visual system. However, previous studies have suggested that the neuronal coding of speed in the middle temporal area (MT, a key cortical area for motion analysis in primates) is ambiguous, with most neurons changing their speed tuning depending on the spatial frequency (SF) of a visual pattern. Here we demonstrate that the ability of MT neurons to encode speed is markedly improved when stimuli follow a trajectory across the visual field, prior to entering their receptive fields. We also show that this effect is much less marked in the primary visual area. These results indicate that MT neurons build up on computations performed at earlier levels of the visual system to provide accurate coding of speed in natural situations, and provide additional evidence that nonlinear pooling underlie motion processing.

SUBMITTER: Davies AJ

PROVIDER: S-EPMC4728434 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Natural motion trajectory enhances the coding of speed in primate extrastriate cortex.

Davies Amanda J AJ Chaplin Tristan A TA Rosa Marcello G P MG Yu Hsin-Hao HH

Scientific reports 20160127

The ability to estimate the speed of an object irrespective of size or texture is a crucial function of the visual system. However, previous studies have suggested that the neuronal coding of speed in the middle temporal area (MT, a key cortical area for motion analysis in primates) is ambiguous, with most neurons changing their speed tuning depending on the spatial frequency (SF) of a visual pattern. Here we demonstrate that the ability of MT neurons to encode speed is markedly improved when st ...[more]

PMID: 26813361

Similar Datasets

Project description:Working memory (WM) provides the stability necessary for high-level cognition. Influential theories typically assume that WM depends on the persistence of stable neural representations, yet increasing evidence suggests that neural states are highly dynamic. Here we apply multivariate pattern analysis to explore the population dynamics in primate lateral prefrontal cortex (PFC) during three variants of the classic memory-guided saccade task (recorded in four animals). We observed the hallmark of dynamic population coding across key phases of a working memory task: sensory processing, memory encoding, and response execution. Throughout both these dynamic epochs and the memory delay period, however, the neural representational geometry remained stable. We identified two characteristics that jointly explain these dynamics: (1) time-varying changes in the subpopulation of neurons coding for task variables (i.e., dynamic subpopulations); and (2) time-varying selectivity within neurons (i.e., dynamic selectivity). These results indicate that even in a very simple memory-guided saccade task, PFC neurons display complex dynamics to support stable representations for WM.SIGNIFICANCE STATEMENT Flexible, intelligent behavior requires the maintenance and manipulation of incoming information over various time spans. For short time spans, this faculty is labeled "working memory" (WM). Dominant models propose that WM is maintained by stable, persistent patterns of neural activity in prefrontal cortex (PFC). However, recent evidence suggests that neural activity in PFC is dynamic, even while the contents of WM remain stably represented. Here, we explored the neural dynamics in PFC during a memory-guided saccade task. We found evidence for dynamic population coding in various task epochs, despite striking stability in the neural representational geometry of WM. Furthermore, we identified two distinct cellular mechanisms that contribute to dynamic population coding.

Project description:Daily life often requires the coordination of our actions with those of another partner. After 50 years (1968-2018) of behavioral neurophysiology of motor control, the neural mechanisms that allow such coordination in primates are unknown. We studied this issue by recording cell activity simultaneously from dorsal premotor cortex (PMd) of two male interacting monkeys trained to coordinate their hand forces to achieve a common goal. We found a population of "joint-action cells" that discharged preferentially when monkeys cooperated in the task. This modulation was predictive in nature, because in most cells neural activity led in time the changes of the "own" and of the "other" behavior. These neurons encoded the joint-performance more accurately than "canonical action-related cells", activated by the action per se, regardless of the individual versus interactive context. A decoding of joint-action was obtained by combining the two brains' activities, using cells with directional properties distinguished from those associated to the "solo" behaviors. Action observation-related activity studied when one monkey observed the consequences of the partner's behavior, i.e., the cursor's motion on the screen, did not sharpen the accuracy of joint-action cells' representation, suggesting that it plays no major role in encoding joint-action. When monkeys performed with a non-interactive partner, such as a computer, joint-action cells' representation of the other (non-cooperative) behavior was significantly degraded. These findings provide evidence of how premotor neurons integrate the time-varying representation of the self-action with that of a co-actor, thus offering a neural substrate for successful visuomotor coordination between individuals.SIGNIFICANCE STATEMENT The neural bases of intersubject motor coordination were studied by recording cell activity simultaneously from the frontal cortex of two interacting monkeys, trained to coordinate their hand forces to achieve a common goal. We found a new class of cells, preferentially active when the monkeys cooperated, rather than when the same action was performed individually. These "joint-action neurons" offered a neural representation of joint-behaviors by far more accurate than that provided by the "canonical action-related cells", modulated by the action per se regardless of the individual/interactive context. A neural representation of joint-performance was obtained by combining the activity recorded from the two brains. Our findings offer the first evidence concerning neural mechanisms subtending interactive visuomotor coordination between co-acting agents.

Dataset Information

Natural motion trajectory enhances the coding of speed in primate extrastriate cortex.

Publications

Natural motion trajectory enhances the coding of speed in primate extrastriate cortex.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure