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Search Results: 1 - 10 of 168961 matches for " Mathew E. Diamond "
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Information carried by population spike times in the whisker sensory cortex can be decoded without knowledge of stimulus time
Stefano Panzeri,Mathew E. Diamond
Frontiers in Synaptic Neuroscience , 2010, DOI: 10.3389/fnsyn.2010.00017
Abstract: Computational analyses have revealed that precisely timed spikes emitted by somatosensory cortical neuronal populations encode basic stimulus features in the rat’s whisker sensory system. Efficient spike time based decoding schemes both for the spatial location of a stimulus and for the kinetic features of complex whisker movements have been defined. To date, these decoding schemes have been based upon spike times referenced to an external temporal frame – the time of the stimulus itself. Such schemes are limited by the requirement of precise knowledge of the stimulus time signal, and it is not clear whether stimulus times are known to rats making sensory judgments. Here, we first review studies of the information obtained from spike timing referenced to the stimulus time. Then we explore new methods for extracting spike train information independently of any external temporal reference frame. These proposed methods are based on the detection of stimulus-dependent differences in the firing time within a neuronal population. We apply them to a data set using single-whisker stimulation in anesthetized rats and find that stimulus site can be decoded based on the millisecond-range relative differences in spike times even without knowledge of stimulus time. If spike counts alone are measured over tens or hundreds of milliseconds rather than milliseconds, such decoders are much less effective. These results suggest that decoding schemes based on millisecond-precise spike times are likely to subserve robust and information-rich transmission of information in the somatosensory system.
Neuronal Encoding of Texture in the Whisker Sensory Pathway
Ehsan Arabzadeh,Erik Zorzin,Mathew E. Diamond
PLOS Biology , 2012, DOI: 10.1371/journal.pbio.0030017
Abstract: A major challenge of sensory systems neuroscience is to quantify brain activity underlying perceptual experiences and to explain this activity as the outcome of elemental neuronal response properties. Rats make extremely fine discriminations of texture by “whisking” their vibrissae across an object's surface, yet the neuronal coding underlying texture sensations remains unknown. Measuring whisker vibrations during active whisking across surfaces, we found that each texture results in a unique “kinetic signature” defined by the temporal profile of whisker velocity. We presented these texture-induced vibrations as stimuli while recording responses of first-order sensory neurons and neurons in the whisker area of cerebral cortex. Each texture is encoded by a distinctive, temporally precise firing pattern. To look for the neuronal coding properties that give rise to texture-specific firing patterns, we delivered horizontal and vertical whisker movements that varied randomly in time (“white noise”) and found that the response probabilities of first-order neurons and cortical neurons vary systematically according to whisker speed and direction. We applied the velocity-tuned spike probabilities derived from white noise to the sequence of velocity features in the texture to construct a simulated texture response. The close match between the simulated and real responses indicates that texture coding originates in the selectivity of neurons to elemental kinetic events.
Neuronal Encoding of Texture in the Whisker Sensory Pathway
Ehsan Arabzadeh ,Erik Zorzin,Mathew E Diamond
PLOS Biology , 2005, DOI: 10.1371/journal.pbio.0030017
Abstract: A major challenge of sensory systems neuroscience is to quantify brain activity underlying perceptual experiences and to explain this activity as the outcome of elemental neuronal response properties. Rats make extremely fine discriminations of texture by “whisking” their vibrissae across an object's surface, yet the neuronal coding underlying texture sensations remains unknown. Measuring whisker vibrations during active whisking across surfaces, we found that each texture results in a unique “kinetic signature” defined by the temporal profile of whisker velocity. We presented these texture-induced vibrations as stimuli while recording responses of first-order sensory neurons and neurons in the whisker area of cerebral cortex. Each texture is encoded by a distinctive, temporally precise firing pattern. To look for the neuronal coding properties that give rise to texture-specific firing patterns, we delivered horizontal and vertical whisker movements that varied randomly in time (“white noise”) and found that the response probabilities of first-order neurons and cortical neurons vary systematically according to whisker speed and direction. We applied the velocity-tuned spike probabilities derived from white noise to the sequence of velocity features in the texture to construct a simulated texture response. The close match between the simulated and real responses indicates that texture coding originates in the selectivity of neurons to elemental kinetic events.
Learning not to feel: reshaping the resolution of tactile perception
Mohsen Omrani,Armin Lak,Mathew E. Diamond
Frontiers in Systems Neuroscience , 2013, DOI: 10.3389/fnsys.2013.00029
Abstract: We asked whether biased feedback during training could cause human subjects to lose perceptual acuity in a vibrotactile frequency discrimination task. Prior to training, we determined each subject's vibration frequency discrimination capacity on one fingertip, the Just Noticeable Difference (JND). Subjects then received 850 trials in which they performed a same/different judgment on two vibrations presented to that fingertip. They gained points whenever their judgment matched the computer-generated feedback on that trial. Feedback, however, was biased: the probability per trial of “same” feedback was drawn from a normal distribution with standard deviation twice as wide as the subject's JND. After training, the JND was significantly widened: stimulus pairs previously perceived as different were now perceived as the same. The widening of the JND extended to the untrained hand, indicating that the decrease in resolution originated in non-topographic brain regions. In sum, the acuity of subjects' sensory-perceptual systems shifted in order to match the feedback received during training.
Redundancy and synergy arising from correlations in large ensembles
Michele Bezzi,Mathew E. Diamond,Alessandro Treves
Quantitative Biology , 2000,
Abstract: Multielectrode arrays allow recording of the activity of many single neurons, from which correlations can be calculated. The functional roles of correlations can be revealed by the measures of the information conveyed by neuronal activity; a simple formula has been shown to discriminate the information transmitted by individual spikes from the positive or negative contributions due to correlations (Panzeri et al, Proc. Roy. Soc. B., {266}: 1001--1012 (1999)). The formula quantifies the corrections to the single-unit instantaneous information rate which result from correlations in spike emission between pairs of neurons. Positive corrections imply synergy, while negative corrections indicate redundancy. Here, this analysis, previously applied to recordings from small ensembles, is developed further by considering a model of a large ensemble, in which correlations among the signal and noise components of neuronal firing are small in absolute value and entirely random in origin. Even such small random correlations are shown to lead to large possible synergy or redundancy, whenever the time window for extracting information from neuronal firing extends to the order of the mean interspike interval. In addition, a sample of recordings from rat barrel cortex illustrates the mean time window at which such `corrections' dominate when correlations are, as often in the real brain, neither random nor small. The presence of this kind of correlations for a large ensemble of cells restricts further the time of validity of the expansion, unless what is decodable by the receiver is also taken into account.
Whisker-Mediated Texture Discrimination
Mathew E. Diamond,Moritz von Heimendahl,Ehsan Arabzadeh
PLOS Biology , 2012, DOI: 10.1371/journal.pbio.0060220
Abstract:
Hippocampal Representation of Touch-Guided Behavior in Rats: Persistent and Independent Traces of Stimulus and Reward Location
Pavel M. Itskov,Ekaterina Vinnik,Mathew E. Diamond
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0016462
Abstract: Understanding the mechanisms by which sensory experiences are stored remains a compelling challenge for neuroscience. Previous work has described how the activity of neurons in the sensory cortex allows rats to discriminate the physical features of an object contacted with their whiskers. But to date there is no evidence about how neurons represent the behavioural significance of tactile stimuli, or how they are encoded in memory. To investigate these issues, we recorded single-unit firing and local field potentials from the CA1 region of hippocampus while rats performed a task in which tactile stimuli specified reward location. On each trial the rat touched a textured plate with its whiskers, and then turned towards the Left or Right water spout. Two textures were associated with each reward location. To determine the influence of the rat's position on sensory coding, we placed it on a second platform in the same room where it performed the identical texture discrimination task. Over 25 percent of the sampled neurons encoded texture identity – their firing differed for two stimuli associated with the same reward location – and over 50 percent of neurons encoded the reward location with which the stimuli were associated. The neuronal population carried texture and reward location signals continuously, from the moment of stimulus contact until the end of reward collection. The set of neurons discriminating between one texture pair was found to be independent of, and partially overlapping, the set of neurons encoding the discrimination between a different texture pair. In a given neuron, the presence of a tactile signal was uncorrelated with the presence, magnitude, or timing of reward location signals. These experiments indicate that neurons in CA1 form a texture representation independently of the action the stimulus is associated with and retain the stimulus representation through reward collection.
Whisker-Mediated Texture Discrimination
Mathew E Diamond ,Moritz von Heimendahl,Ehsan Arabzadeh
PLOS Biology , 2008, DOI: 10.1371/journal.pbio.0060220
Abstract:
Auditory stimuli elicit hippocampal neuronal responses during sleep
Ekaterina Vinnik,Sergey Antopolskiy,Pavel M. Itskov,Mathew E. Diamond
Frontiers in Systems Neuroscience , 2012, DOI: 10.3389/fnsys.2012.00049
Abstract: To investigate how hippocampal neurons code behaviorally salient stimuli, we recorded from neurons in the CA1 region of hippocampus in rats while they learned to associate the presence of sound with water reward. Rats learned to alternate between two reward ports at which, in 50% of the trials, sound stimuli were presented followed by water reward after a 3-s delay. Sound at the water port predicted subsequent reward delivery in 100% of the trials and the absence of sound predicted reward omission. During this task, 40% of recorded neurons fired differently according to which of the two reward ports the rat was visiting. A smaller fraction of neurons demonstrated onset response to sound/nosepoke (19%) and reward delivery (24%). When the sounds were played during passive wakefulness, 8% of neurons responded with short latency onset responses; 25% of neurons responded to sounds when they were played during sleep. During sleep the short-latency responses in hippocampus are intermingled with long lasting responses which in the current experiment could last for 1–2 s. Based on the current findings and the results of previous experiments we described the existence of two types of hippocampal neuronal responses to sounds: sound-onset responses with very short latency and longer-lasting sound-specific responses that are likely to be present when the animal is actively engaged in the task.
Factors Affecting Frequency Discrimination of Vibrotactile Stimuli: Implications for Cortical Encoding
Justin A. Harris, Ehsan Arabzadeh, Adrienne L. Fairhall, Claire Benito, Mathew E. Diamond
PLOS ONE , 2006, DOI: 10.1371/journal.pone.0000100
Abstract: Background Measuring perceptual judgments about stimuli while manipulating their physical characteristics can uncover the neural algorithms underlying sensory processing. We carried out psychophysical experiments to examine how humans discriminate vibrotactile stimuli. Methodology/Principal Findings Subjects compared the frequencies of two sinusoidal vibrations applied sequentially to one fingertip. Performance was reduced when (1) the root mean square velocity (or energy) of the vibrations was equated by adjusting their amplitudes, and (2) the vibrations were noisy (their temporal structure was irregular). These effects were super-additive when subjects compared noisy vibrations that had equal velocity, indicating that frequency judgments became more dependent on the vibrations' temporal structure when differential information about velocity was eliminated. To investigate which areas of the somatosensory system use information about velocity and temporal structure, we required subjects to compare vibrations applied sequentially to opposite hands. This paradigm exploits the fact that tactile input to neurons at early levels (e.g., the primary somatosensory cortex, SI) is largely confined to the contralateral side of the body, so these neurons are less able to contribute to vibration comparisons between hands. The subjects' performance was still sensitive to differences in vibration velocity, but became less sensitive to noise. Conclusions/Significance We conclude that vibration frequency is represented in different ways by different mechanisms distributed across multiple cortical regions. Which mechanisms support the “readout” of frequency varies according to the information present in the vibration. Overall, the present findings are consistent with a model in which information about vibration velocity is coded in regions beyond SI. While adaptive processes within SI also contribute to the representation of frequency, this adaptation is influenced by the temporal regularity of the vibration.
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