As we interact with the external world, we judge magnitudes from sensory information. The estimation of magnitudes has been characterized in primates, yet it is largely unexplored in non-primate species. Here we use time interval reproduction to study rodent behavior and its neural correlates in the context of magnitude estimation. We show that gerbils display primate-like magnitude estimation characteristics in time reproduction. Most prominently their behavioral responses show a systematic overestimation of small stimuli and an underestimation of large stimuli, often referred to as regression effect. We investigated the underlying neural mechanisms by recording from medial prefrontal cortex and show that the majority of neurons respond either during the measurement or the reproduction of a time interval. Cells that are active during both phases display distinct response patterns. We categorize the neural responses into multiple types and demonstrate that only populations with mixed responses can encode the bias of the regression effect. These results help unveil the organizing neural principles of time reproduction and perhaps magnitude estimation in general.
Large parts of our knowledge about the physiology of the hippocampus in the intact brain are derived from studies in rats and mice. While many of those findings fit well to the limited data available from humans and primates, there are also marked differences, for example in hippocampal oscillation frequencies and in the persistence of theta oscillations. To test whether the distinct sensory specializations of the visual and auditory system of primates play a key role in explaining these differences, we recorded basic hippocampal physiological properties in Mongolian gerbils, a rodent species with high visual acuity and good low-frequency hearing, similar to humans. We found that gerbils show only minor differences to rats regarding hippocampal place field activity, theta properties (frequency, persistence, phase precession, theta compression), and sharp wave ripple events. The only major difference between rats and gerbils was a considerably higher degree of head direction selectivity of gerbil place fields, which may be explained by their visual system being able to better resolve distant cues. Thus, differences in sensory specializations between rodent species only affect hippocampal circuit dynamics to a minor extent, which implies that differences to other mammalian lineages, such as bats and primates, cannot be solely explained by specialization in the auditory or visual system.
As we interact with the external world, we judge magnitudes from sensory information. The estimation of magnitudes has been characterized in primates, yet it is largely unexplored in non-primate species. Here, we show that gerbils that solve a time-interval reproduction task display primate-like magnitude estimation characteristics, most prominently a systematic overestimation of small stimuli and an underestimation of large stimuli, often referred to as regression effect. We investigated the underlying neural mechanisms by recording from medial prefrontal cortex and show that the majority of neurons respond either during the measurement or the reproduction of a time-interval. Cells that are active during both phases display distinct response patterns. We categorize the neural responses into multiple types and demonstrate that only populations with mixed responses can encode the bias of the regression effect. These results reveal the organizing neural principles of an important higher cognitive function.Animals including humans estimate the magnitude of physical stimuli, integrate path length and keep track of duration to gather behaviorally relevant information from their environment. Although such estimates may ultimately be used for binary actions, like discriminating items or events and making decisions, the estimation itself is done on a continuum of values. Behavioral analyses over the past century established specific biases in magnitude estimation [e.g. reviewed in 1] such as the regression effect, i.e. the overestimation of small and the underestimation of large stimuli across a range of values. Recently, this bias regained attention as it may be the result of an error minimization strategy [2][3][4].Despite a long history of behavioral research on magnitude estimation, its neural basis is not well understood. It is an ongoing debate whether a dedicated or distributed 1
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