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Maggi S, Hock RM, O'Neill M, Buckley M, Moran PM, Bast T, Sami M, Humphries MD. Tracking subjects' strategies in behavioural choice experiments at trial resolution. eLife 2024; 13:e86491. [PMID: 38426402 PMCID: PMC10959529 DOI: 10.7554/elife.86491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Accepted: 02/23/2024] [Indexed: 03/02/2024] Open
Abstract
Investigating how, when, and what subjects learn during decision-making tasks requires tracking their choice strategies on a trial-by-trial basis. Here, we present a simple but effective probabilistic approach to tracking choice strategies at trial resolution using Bayesian evidence accumulation. We show this approach identifies both successful learning and the exploratory strategies used in decision tasks performed by humans, non-human primates, rats, and synthetic agents. Both when subjects learn and when rules change the exploratory strategies of win-stay and lose-shift, often considered complementary, are consistently used independently. Indeed, we find the use of lose-shift is strong evidence that subjects have latently learnt the salient features of a new rewarded rule. Our approach can be extended to any discrete choice strategy, and its low computational cost is ideally suited for real-time analysis and closed-loop control.
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Affiliation(s)
- Silvia Maggi
- School of Psychology, University of NottinghamNottinghamUnited Kingdom
| | - Rebecca M Hock
- School of Psychology, University of NottinghamNottinghamUnited Kingdom
| | - Martin O'Neill
- School of Psychology, University of NottinghamNottinghamUnited Kingdom
- Department of Health & Nutritional Sciences, Atlantic Technological UniversitySligoIreland
| | - Mark Buckley
- Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
| | - Paula M Moran
- School of Psychology, University of NottinghamNottinghamUnited Kingdom
- Department of Neuroscience, University of NottinghamNottinghamUnited Kingdom
| | - Tobias Bast
- School of Psychology, University of NottinghamNottinghamUnited Kingdom
- Department of Neuroscience, University of NottinghamNottinghamUnited Kingdom
| | - Musa Sami
- Institute of Mental Health, University of NottinghamNottinghamUnited Kingdom
| | - Mark D Humphries
- School of Psychology, University of NottinghamNottinghamUnited Kingdom
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2
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Do J, Jung MW, Lee D. Automating licking bias correction in a two-choice delayed match-to-sample task to accelerate learning. Sci Rep 2023; 13:22768. [PMID: 38123637 PMCID: PMC10733387 DOI: 10.1038/s41598-023-49862-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 12/12/2023] [Indexed: 12/23/2023] Open
Abstract
Animals often display choice bias, or a preference for one option over the others, which can significantly impede learning new tasks. Delayed match-to-sample (DMS) tasks with two-alternative choices of lickports on the left and right have been widely used to study sensory processing, working memory, and associative memory in head-fixed animals. However, extensive training time, primarily due to the animals' biased licking responses, limits their practical utility. Here, we present the implementation of an automated side bias correction system in an olfactory DMS task, where the lickport positions and the ratio of left- and right-rewarded trials are dynamically adjusted to counterbalance mouse's biased licking responses during training. The correction algorithm moves the preferred lickport farther away from the mouse's mouth and the non-preferred lickport closer, while also increasing the proportion of non-preferred side trials when biased licking occurs. We found that adjusting lickport distances and the proportions of left- versus right-rewarded trials effectively reduces the mouse's side bias. Further analyses reveal that these adjustments also correlate with subsequent improvements in behavioral performance. Our findings suggest that the automated side bias correction system is a valuable tool for enhancing the applicability of behavioral tasks involving two-alternative lickport choices.
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Affiliation(s)
- Jongrok Do
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea
| | - Min Whan Jung
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Republic of Korea.
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, 34141, Republic of Korea.
| | - Doyun Lee
- Center for Cognition and Sociality, Institute for Basic Science, Daejeon, 34126, Republic of Korea.
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3
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Ding Y, Vlasov Y. Pre-neuronal processing of haptic sensory cues via dispersive high-frequency vibrational modes. Sci Rep 2023; 13:14370. [PMID: 37658126 PMCID: PMC10474056 DOI: 10.1038/s41598-023-40675-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 08/16/2023] [Indexed: 09/03/2023] Open
Abstract
Sense of touch is one of the major perception channels. Neural coding of object textures conveyed by rodents' whiskers has been a model to study early stages of haptic information uptake. While high-precision spike timing has been observed during whisker sweeping across textured surfaces, the exact nature of whisker micromotions that spikes encode remains elusive. Here, we discovered that a single micro-collision of a whisker with surface features generates vibrational eigenmodes spanning frequencies up to 10 kHz. While propagating along the whisker, these high-frequency modes can carry up to 80% of shockwave energy, exhibit 100× smaller damping ratio, and arrive at the follicle 10× faster than low frequency components. The mechano-transduction of these energy bursts into time-sequenced population spike trains may generate temporally unique "bar code" with ultra-high information capacity. This hypothesis of pre-neuronal processing of haptic signals based on dispersive temporal separation of the vibrational modal frequencies can shed light on neural coding of haptic signals in many whisker-like sensory organs across the animal world as well as in texture perception in primate's glabrous skin.
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Affiliation(s)
- Yu Ding
- Department of Physics, University of Illinois Urbana Champaign, 208 North Wright Street, Urbana, IL, 61801, USA
| | - Yurii Vlasov
- Department of Physics, University of Illinois Urbana Champaign, 208 North Wright Street, Urbana, IL, 61801, USA.
- Department of BioEngineering, University of Illinois Urbana Champaign, 208 North Wright Street, Urbana, IL, 61801, USA.
- Carle Illinois College of Medicine, University of Illinois Urbana Champaign, 208 North Wright Street, Urbana, IL, 61801, USA.
- Department of Electrical and Computer Engineering, University of Illinois Urbana Champaign, 208 North Wright Street, Urbana, IL, 61801, USA.
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4
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Campagner D, Vale R, Tan YL, Iordanidou P, Pavón Arocas O, Claudi F, Stempel AV, Keshavarzi S, Petersen RS, Margrie TW, Branco T. A cortico-collicular circuit for orienting to shelter during escape. Nature 2023; 613:111-119. [PMID: 36544025 PMCID: PMC7614651 DOI: 10.1038/s41586-022-05553-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Accepted: 11/10/2022] [Indexed: 12/24/2022]
Abstract
When faced with predatory threats, escape towards shelter is an adaptive action that offers long-term protection against the attacker. Animals rely on knowledge of safe locations in the environment to instinctively execute rapid shelter-directed escape actions1,2. Although previous work has identified neural mechanisms of escape initiation3,4, it is not known how the escape circuit incorporates spatial information to execute rapid flights along the most efficient route to shelter. Here we show that the mouse retrosplenial cortex (RSP) and superior colliculus (SC) form a circuit that encodes the shelter-direction vector and is specifically required for accurately orienting to shelter during escape. Shelter direction is encoded in RSP and SC neurons in egocentric coordinates and SC shelter-direction tuning depends on RSP activity. Inactivation of the RSP-SC pathway disrupts the orientation to shelter and causes escapes away from the optimal shelter-directed route, but does not lead to generic deficits in orientation or spatial navigation. We find that the RSP and SC are monosynaptically connected and form a feedforward lateral inhibition microcircuit that strongly drives the inhibitory collicular network because of higher RSP input convergence and synaptic integration efficiency in inhibitory SC neurons. This results in broad shelter-direction tuning in inhibitory SC neurons and sharply tuned excitatory SC neurons. These findings are recapitulated by a biologically constrained spiking network model in which RSP input to the local SC recurrent ring architecture generates a circular shelter-direction map. We propose that this RSP-SC circuit might be specialized for generating collicular representations of memorized spatial goals that are readily accessible to the motor system during escape, or more broadly, during navigation when the goal must be reached as fast as possible.
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Affiliation(s)
- Dario Campagner
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
- UCL Gatsby Computational Neuroscience Unit, London, UK
| | - Ruben Vale
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
- MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Yu Lin Tan
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
| | | | - Oriol Pavón Arocas
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
| | - Federico Claudi
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
| | - A Vanessa Stempel
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
| | | | | | - Troy W Margrie
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK
| | - Tiago Branco
- UCL Sainsbury Wellcome Centre for Neural Circuits and Behaviour, London, UK.
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5
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Abstract
Identical physical inputs do not always evoke identical percepts. To investigate the role of stimulus history in tactile perception, we designed a task in which rats had to judge each vibrissal vibration, in a long series, as strong or weak depending on its mean speed. After a low-speed stimulus (trial n - 1), rats were more likely to report the next stimulus (trial n) as strong, and after a high-speed stimulus, they were more likely to report the next stimulus as weak, a repulsive effect that did not depend on choice or reward on trial n - 1. This effect could be tracked over several preceding trials (i.e., n - 2 and earlier) and was characterized by an exponential decay function, reflecting a trial-by-trial incorporation of sensory history. Surprisingly, the influence of trial n - 1 strengthened as the time interval between n - 1 and n grew. Human subjects receiving fingertip vibrations showed these same key findings. We are able to account for the repulsive stimulus history effect, and its detailed time scale, through a single-parameter model, wherein each new stimulus gradually updates the subject's decision criterion. This model points to mechanisms underlying how the past affects the ongoing subjective experience.
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Rodgers CC, Nogueira R, Pil BC, Greeman EA, Park JM, Hong YK, Fusi S, Bruno RM. Sensorimotor strategies and neuronal representations for shape discrimination. Neuron 2021; 109:2308-2325.e10. [PMID: 34133944 PMCID: PMC8298290 DOI: 10.1016/j.neuron.2021.05.019] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 01/28/2021] [Accepted: 05/14/2021] [Indexed: 10/21/2022]
Abstract
Humans and other animals can identify objects by active touch, requiring the coordination of exploratory motion and tactile sensation. Both the motor strategies and neural representations employed could depend on the subject's goals. We developed a shape discrimination task that challenged head-fixed mice to discriminate concave from convex shapes. Behavioral decoding revealed that mice did this by comparing contacts across whiskers. In contrast, a separate group of mice performing a shape detection task simply summed up contacts over whiskers. We recorded populations of neurons in the barrel cortex, which processes whisker input, and found that individual neurons across the cortical layers encoded touch, whisker motion, and task-related signals. Sensory representations were task-specific: during shape discrimination, but not detection, neurons responded most to behaviorally relevant whiskers, overriding somatotopy. Thus, sensory cortex employs task-specific representations compatible with behaviorally relevant computations.
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Affiliation(s)
- Chris C Rodgers
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA.
| | - Ramon Nogueira
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
| | - B Christina Pil
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA
| | - Esther A Greeman
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA
| | - Jung M Park
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA
| | - Y Kate Hong
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA
| | - Stefano Fusi
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA; Center for Theoretical Neuroscience, Columbia University, New York, NY 10027, USA
| | - Randy M Bruno
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA; Kavli Institute for Brain Science, Columbia University, New York, NY 10027, USA.
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7
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Body-generated hydrodynamic flows influence male–male contests and female mate choice in a freshwater fish. Anim Behav 2020. [DOI: 10.1016/j.anbehav.2020.09.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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8
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Chéreau R, Bawa T, Fodoulian L, Carleton A, Pagès S, Holtmaat A. Dynamic perceptual feature selectivity in primary somatosensory cortex upon reversal learning. Nat Commun 2020; 11:3245. [PMID: 32591523 PMCID: PMC7319990 DOI: 10.1038/s41467-020-17005-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 06/05/2020] [Indexed: 11/09/2022] Open
Abstract
Neurons in primary sensory cortex encode a variety of stimulus features upon perceptual learning. However, it is unclear whether the acquired stimulus selectivity remains stable when the same input is perceived in a different context. Here, we monitor the activity of individual neurons in the mouse primary somatosensory cortex during reward-based texture discrimination. We track their stimulus selectivity before and after changing reward contingencies, which allows us to identify various classes of neurons. We find neurons that stably represented a texture or the upcoming behavioral choice, but the majority is dynamic. Among those, a subpopulation of neurons regains texture selectivity contingent on the associated reward value. These value-sensitive neurons forecast the onset of learning by displaying a distinct and transient increase in activity, depending on past behavioral experience. Thus, stimulus selectivity of excitatory neurons during perceptual learning is dynamic and largely relies on behavioral contingencies, even in primary sensory cortex. Do cortical neurons stably represent stimulus features in different contexts? Here, using calcium imaging, the authors show that texture selectivity of individual neurons is dynamic during reversal learning. For a subclass this is contingent on the associated reward and forecasts the onset of learning.
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Affiliation(s)
- Ronan Chéreau
- Department of Basic Neurosciences and the Center for Neuroscience, CMU, University of Geneva, Rue Michel Servet 1, 1211, Geneva, Switzerland
| | - Tanika Bawa
- Department of Basic Neurosciences and the Center for Neuroscience, CMU, University of Geneva, Rue Michel Servet 1, 1211, Geneva, Switzerland.,Lemanic Neuroscience Doctoral School, University of Geneva, Geneva, Switzerland
| | - Leon Fodoulian
- Department of Basic Neurosciences and the Center for Neuroscience, CMU, University of Geneva, Rue Michel Servet 1, 1211, Geneva, Switzerland.,Lemanic Neuroscience Doctoral School, University of Geneva, Geneva, Switzerland
| | - Alan Carleton
- Department of Basic Neurosciences and the Center for Neuroscience, CMU, University of Geneva, Rue Michel Servet 1, 1211, Geneva, Switzerland
| | - Stéphane Pagès
- Department of Basic Neurosciences and the Center for Neuroscience, CMU, University of Geneva, Rue Michel Servet 1, 1211, Geneva, Switzerland
| | - Anthony Holtmaat
- Department of Basic Neurosciences and the Center for Neuroscience, CMU, University of Geneva, Rue Michel Servet 1, 1211, Geneva, Switzerland.
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Petersen RS, Colins Rodriguez A, Evans MH, Campagner D, Loft MSE. A system for tracking whisker kinematics and whisker shape in three dimensions. PLoS Comput Biol 2020; 16:e1007402. [PMID: 31978043 PMCID: PMC7028309 DOI: 10.1371/journal.pcbi.1007402] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 02/18/2020] [Accepted: 12/05/2019] [Indexed: 11/18/2022] Open
Abstract
Quantification of behaviour is essential for biology. Since the whisker system is a popular model, it is important to have methods for measuring whisker movements from behaving animals. Here, we developed a high-speed imaging system that measures whisker movements simultaneously from two vantage points. We developed a whisker tracker algorithm that automatically reconstructs 3D whisker information directly from the ‘stereo’ video data. The tracker is controlled via a Graphical User Interface that also allows user-friendly curation. The algorithm tracks whiskers, by fitting a 3D Bezier curve to the basal section of each target whisker. By using prior knowledge of natural whisker motion and natural whisker shape to constrain the fits and by minimising the number of fitted parameters, the algorithm is able to track multiple whiskers in parallel with low error rate. We used the output of the tracker to produce a 3D description of each tracked whisker, including its 3D orientation and 3D shape, as well as bending-related mechanical force. In conclusion, we present a non-invasive, automatic system to track whiskers in 3D from high-speed video, creating the opportunity for comprehensive 3D analysis of sensorimotor behaviour and its neural basis. The great ethologist Niko Tinbergen described a crucial challenge in biology to measure the “total movements made by the intact animal”[1]. Advances in high-speed video and machine analysis of such data have made it possible to make profound advances. Here, we target the whisker system. The whisker system is a major experimental model in neurobiology and, since the whiskers are readily imageable, the system is ideally suited to machine vision. Rats and mice explore their environment by sweeping their whiskers to and fro. It is important to measure whisker movements in 3D, since whiskers move in 3D and since the mechanical forces that act on them are 3D. However, the computational problem of automatically tracking whiskers in 3D from video has generally been regarded as prohibitively difficult. Our innovation here is to extract 3D information about whiskers using a two-camera, high-speed imaging system and to develop computational methods to reconstruct 3D whisker state from the imaging data. Our hope is that this study will facilitate comprehensive, 3D analysis of whisker behaviour and, more generally, contribute new insight into brain mechanisms of perception and behaviour.
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Affiliation(s)
- Rasmus S. Petersen
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, United Kingdom
- * E-mail:
| | - Andrea Colins Rodriguez
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, United Kingdom
| | - Mathew H. Evans
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, United Kingdom
| | - Dario Campagner
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, United Kingdom
| | - Michaela S. E. Loft
- Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, United Kingdom
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Deutsch D, Schneidman E, Ahissar E. Generalization of Object Localization From Whiskers to Other Body Parts in Freely Moving Rats. Front Integr Neurosci 2019; 13:64. [PMID: 31736724 PMCID: PMC6839537 DOI: 10.3389/fnint.2019.00064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 10/16/2019] [Indexed: 11/13/2022] Open
Abstract
Rats can be trained to associate relative spatial locations of objects with the spatial location of rewards. Here we ask whether rats can localize static silent objects with other body parts in the dark, and if so with what resolution. We addressed these questions in trained rats, whose interactions with the objects were tracked at high-resolution before and after whisker trimming. We found that rats can use other body parts, such as trunk and ears, to localize objects. Localization resolution with non-whisking body parts (henceforth, ‘body’) was poorer than that obtained with whiskers, even when left with a single whisker at each side. Part of the superiority of whiskers was obtained via the use of multiple contacts. Transfer from whisker to body localization occurred within one session, provided that body contacts with the objects occurred before whisker trimming, or in the next session otherwise. This transfer occurred whether temporal cues were used for discrimination or when discrimination was based on spatial cues alone. Rats’ decision in each trial was based on the sensory cues acquired in that trial and on decisions and reward locations in previous trials. When sensory cues were acquired by body contacts, rat decisions relied more on the reward location in previous trials. Overall, the results suggest that rats can generalize the idea of relative object location across different body parts, while preferring to rely on whiskers-based localization, which occurs earlier and conveys higher resolution.
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Affiliation(s)
- David Deutsch
- Department of Neurobiology, The Weizmann Institute of Science, Rehovot, Israel
| | - Elad Schneidman
- Department of Neurobiology, The Weizmann Institute of Science, Rehovot, Israel
| | - Ehud Ahissar
- Department of Neurobiology, The Weizmann Institute of Science, Rehovot, Israel
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The Sensorimotor Basis of Whisker-Guided Anteroposterior Object Localization in Head-Fixed Mice. Curr Biol 2019; 29:3029-3040.e4. [PMID: 31474537 PMCID: PMC6771421 DOI: 10.1016/j.cub.2019.07.068] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 06/26/2019] [Accepted: 07/23/2019] [Indexed: 11/22/2022]
Abstract
Active tactile perception combines directed motion with sensory signals to generate mental representations of objects in space. Competing models exist for how mice use these signals to determine the precise location of objects along their face. We tested six of these models using behavioral manipulations and statistical learning in head-fixed mice. Trained mice used a whisker to locate a pole in a continuous range of locations along the anteroposterior axis. Mice discriminated locations to ≤0.5 mm (<2°) resolution. Their motor program was noisy, adaptive to touch, and directed to the rewarded range. This exploration produced several sets of sensorimotor features that could discriminate location. Integration of two features, touch count and whisking midpoint at touch, was the simplest model that explained behavior best. These results show how mice locate objects at hyperacute resolution using a learned motor strategy and minimal set of mentally accessible sensorimotor features.
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