1,721,164 research outputs found
Analytical estimates of limited sampling biases in different information measures
No full textMeasuring the information carried by neuronal activity is made difficult, particularly when recording from mammalian cells, by the limited amount of data usually available, which results in a systematic error. While empirical ad hoc procedures have been used to correct for such error, we have recently proposed a direct procedure consisting of the analytical calculation of the average error, its estimation (up to subleading terms) from the data, and its subtraction from raw information measures to yield unbiased measures. We calculate here the leading correction terms for both the average transmitted information and the conditional information and, since usually one must first regularize the data, we specify the expressions appropriate to different regularizations. Computer simulations indicate a broad range of validity of the analytical results, suggest the effectiveness of regularizing by simple binning and illustrate the advantage of this over the previously used 'bootstrap' procedure
Methods for inferring neural circuit interactions and neuromodulation from local field potential and electroencephalogram measures
No full textElectrical recordings of neural mass activity, such as local field potentials (LFPs) and electroencephalograms (EEGs), have been instrumental in studying brain function. However, these aggregate signals lack cellular resolution and thus are not easy to be interpreted directly in terms of parameters of neural microcircuits. Developing tools for a reliable estimation of key neural parameters from these signals, such as the interaction between excitation and inhibition or the level of neuromodulation, is important for both neuroscientific and clinical applications. Over the years, we have developed tools based on neural network modeling and computational analysis of empirical data to estimate neural parameters from aggregate neural signals. This review article gives an overview of the main computational tools that we have developed and employed to invert LFPs and EEGs in terms of circuit-level neural phenomena, and outlines future challenges and directions for future research
Erratum: Deciphering the spike train of a sensory neuron: Counts and temporal patterns in the rat whisker pathway (Journal of Neuroscience (September 6, 2006) (9216-9226))
No full textNeural coding: Looking up and down the visual thalamus
No full text: Integrating sensory and postural information is essential for perception and behavior. A new study shows that information about whether mice are looking up or down is combined with visual information in the primary visual thalamus, an early sensory stage of visual processing
Information carried by population spike times in the whisker sensory cortex can be decoded without knowledge of stimulus time
Full text linkComputational 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
How well can we estimate the information carried in neuronal responses from limited samples?
Full text linkIt is difficult to extract the information carried by neuronal responses about a set of stimuli because limited data samples result in biased estimates. Recently two improved procedures have been developed to calculate information from experimental results: a binning-and-correcting procedure and a neural network procedure. We have used data produced from a model of the spatiotemporal receptive fields of parvocellular and magnocellular lateral geniculate neurons to study the performance of these methods as a function of the number of trials used. Both procedures yield accurate results for one-dimensional neuronal codes. They can also be used to produce a reasonable estimate of the extra information in a three-dimensional code, in this instance, within 0.05-0.1 bit of the asymptotically calculated value - about 10% of the total transmitted information. We believe that this performance is much more accurate than previous procedures
Coding of Movement Intentions
No full textMovement intentions are planning signals of the brain that convey goals of upcoming movements. They emerge from sensory information that has entered the brain through various perceptual channels, or from internal states of the brain. Most often, motor intentions originate neither from purely external nor from entirely internal signals, but they are elicited from a combination of both
The role of individual spikes and spike patterns in population coding of stimulus location in rat somatosensory cortex
No full textThis report addresses the nature of population coding in sensory cortex by applying information theoretic analysis to data recorded simultaneously from neuron pairs located in primary somatosensory cortex of anaesthetised rats. We studied how cortical spike trains code for the location of a whisker stimulus on the rat's snout. We found that substantially more information was conveyed by 10 ms precision spike timing compared with that conveyed by the number of spikes counted over a 40 ms response interval. Most of this information was accounted for by the timing of individual spikes. In particular, it was the first post-stimulus spikes that were crucial. Spike patterns within individual cells played a smaller role; spike patterns across cells were negligible. This pattern of results was robust both to the exact nature of the stimulus set and to the precision at which spikes were binned. © 2002 Elsevier Science Ireland Ltd. All rights reserved
Complementary contributions of spike timing and spike rate to perceptual decisions in rat S1 and S2 cortex
No full textWhen a neuron responds to a sensory stimulus, two fundamental codes [1-6] may transmit the information specifying stimulus identity--spike rate (the total number of spikes in the sequence, normalized by time) and spike timing (the detailed millisecond-scale temporal structure of the response). To assess the functional significance of these codes, we recorded neuronal responses in primary (S1) and secondary (S2) somatosensory cortex of five rats as they used their whiskers to identify textured surfaces. From the spike trains evoked during whisker contact with the texture, we computed the information that rate and timing codes carried about texture identity and about the rat's choice. S1 and S2 spike timing carried more information about stimulus and about choice than spike rates; the conjunction of rate and timing carried more information than either code alone. Moreover, on trials when our spike-timing-decoding algorithm extracted faithful texture information, the rat was more likely to choose correctly; when our spike-timing-decoding algorithm extracted misleading texture information, the rat was more likely to err. For spike rate information, the relationship between faithfulness of the message and correct choice was significant but weaker. These results indicate that spike timing makes crucial contributions to tactile perception, complementing and surpassing those made by rate. The language by which somatosensory cortical neurons transmit information, and the readout mechanism used to produce behavior, appears to rely on multiplexed signals from spike rate and timing
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