Variability and Correlated Noise in the Discharge of Neurons in Motor and Parietal Areas of the Primate Cortex

Lee, Dongsoo; Port, Nicholas; Kruse, Wolfgang; Georgopoulos, Apostolos P.

doi:10.1523/jneurosci.18-03-01161.1998

Cited by 293 publications

(338 citation statements)

References 53 publications

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“…We detected an overall positive correlation, which was to a large degree independent of sensory and motor parameters and variables relating to the animal's performance and motivation, providing an instance of residual noise correlation in the cortex that cannot be accounted by behavioral factors. Correlated noise between neurons recorded from the same electrode was in the same broad range as in other cortical areas of the monkey (Gawne and Richmond 1993;Lee et al 1998;Maynard et al 1999;Zohary et al 1994) as well as the frontal cortex of the rat (Jung et al 2000). It is difficult however to directly compare these values as sensory and motor variations in each trial may have a higher impact in other cortical areas.…”

Section: Trial-to-trial Covariationsmentioning

confidence: 91%

“…Functional classes of neurons have been previously defined based on their firing rate properties (Taira and Georgopoulos 1993), and differences in terms of their correlated discharges have been identified; however, these differences involved the relationship between signal and noise correlation rather than the actual value of noise correlation that we report here (Lee et al 1998). The higher discharge synchronization between FS units that we report in this study is consistent with intracellular recordings suggesting that nearby interneurons form a tight network of electrotonic synapses and synchronize their firing with millisecond precision (Beierlein et al 2000;Gibson et al 1999).…”

Section: Short Scale Synchronizationmentioning

confidence: 92%

“…Responses of adjacent cortical neurons, recorded extracellularly from a single electrode, have been shown to be positively but weakly correlated in that fashion (Gawne and Richmond 1993;Jung et al 2000;Lee et al 1998;Maynard et al 1999;Zohary et al 1994). These concurrent deviations from the neurons' respective mean response rates have been termed correlated noise, and they are thought to represent direct or indirect shared inputs that vary randomly from trial to trial (Bair et al 2001).…”

Section: Introductionmentioning

confidence: 99%

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Correlated Discharges Among Putative Pyramidal Neurons and Interneurons in the Primate Prefrontal Cortex

Constantinidis

Goldman‐Rakic

2002

Journal of Neurophysiology

274

233

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Constantinidis, Christos, and Patricia S. Goldman-Rakic. Correlated discharges among putative pyramidal neurons and interneurons in the primate prefrontal cortex. J Neurophysiol 88: 3487-3497, 2002; 10.1152/jn.00188.2002. Neurophysiological recordings have revealed that the discharges of nearby cortical cells are positively correlated in time scales that range from millisecond synchronization of action potentials to much slower firing rate co-variations, evident in rates averaged over hundreds of milliseconds. The presence of correlated firing can offer insights into the patterns of connectivity between neurons; however, few models of population coding have taken account of the neuronal diversity present in cerebral cortex, notably a distinction between inhibitory and excitatory cells. We addressed this question in the monkey dorsolateral prefrontal cortex by recording neuronal activity from multiple micro-electrodes, typically spaced 0.2-0.3 mm apart. Putative excitatory and inhibitory neurons were distinguished based on their action potential waveform and baseline discharge rate. We tested each pair of simultaneously recorded neurons for presence of significant cross-correlation peaks and measured the correlation of their averaged firing rates in successive trials. When observed, cross-correlation peaks were centered at time 0, indicating synchronous firing consistent with two neurons receiving common input. Discharges in pairs of putative inhibitory interneurons were found to be significantly more strongly correlated than in pairs of putative excitatory cells. The degree of correlated firing was also higher for neurons with similar spatial receptive fields and neurons active in the same epochs of the behavioral task. These factors were important in predicting the strength of both short time scale (Ͻ5 ms) correlations and of trial-to-trial discharge rate covariations. Correlated firing was only marginally accounted for by motor and behavioral variations between trials. Our findings suggest that nearby inhibitory neurons are more tightly synchronized than excitatory ones and account for much of the correlated discharges commonly observed in undifferentiated cortical networks. In contrast, the discharge of pyramidal neurons, the sole projection cells of the cerebral cortex, appears largely independent, suggesting that correlated firing may be a property confined within local circuits and only to a lesser degree propagated to distant cortical areas and modules.

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Section: Trial-to-trial Covariationsmentioning

confidence: 91%

Section: Short Scale Synchronizationmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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Correlated Discharges Among Putative Pyramidal Neurons and Interneurons in the Primate Prefrontal Cortex

Constantinidis

Goldman‐Rakic

2002

Journal of Neurophysiology

274

233

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“…This variability is thought to limit the capacity of individual neurons to transmit information (9). Furthermore, variability is often correlated among neurons, and thus, it cannot be completely removed by averaging the population response (9)(10)(11)(12). Recent experimental studies have examined the secondorder statistics of neural responses across a variety of species, cortical areas, tasks, and stimulus and/or attentional conditions (13)(14)(15)(16)(17).…”

mentioning

confidence: 99%

Stimulus-dependent variability and noise correlations in cortical MT neurons

Ponce‐Alvarez

Thiele

Albright

et al. 2013

Proc. Natl. Acad. Sci. U.S.A.

123

152

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Population codes assume that neural systems represent sensory inputs through the firing rates of populations of differently tuned neurons. However, trial-by-trial variability and noise correlations are known to affect the information capacity of neural codes. Although recent studies have shown that stimulus presentation reduces both variability and rate correlations with respect to their spontaneous level, possibly improving the encoding accuracy, whether these second order statistics are tuned is unknown. If so, second-order statistics could themselves carry information, rather than being invariably detrimental. Here we show that rate variability and noise correlation vary systematically with stimulus direction in directionally selective middle temporal (MT) neurons, leading to characteristic tuning curves. We show that such tuning emerges in a stochastic recurrent network, for a set of connectivity parameters that overlaps with a single-state scenario and multistability. Information theoretic analysis shows that second-order statistics carry information that can improve the accuracy of the population code.C ortical activity is highly variable during spontaneous activity (1-4) and even when tested under constant experimental conditions (5-8). This variability is thought to limit the capacity of individual neurons to transmit information (9). Furthermore, variability is often correlated among neurons, and thus, it cannot be completely removed by averaging the population response (9-12). Recent experimental studies have examined the secondorder statistics of neural responses across a variety of species, cortical areas, tasks, and stimulus and/or attentional conditions (13-17). In particular, it has been shown that the Fano factor (FF)-that is, the ratio between the variance of the spike counts over trials and its mean-is reduced when a stimulus is applied (16), thus improving the encoding of the stimulus. Importantly, both preferred and nonpreferred stimuli reduced the FF. In addition, the evoked noise correlation-that is, the trial-to-trial covariance of stimulus induced activity between two simultaneously recorded neurons-is also reduced upon stimulus presentation (18), after stimulus adaptation (19) or perceptual learning (20), and under attention (14, 21), an effect that could, under certain conditions, lead to more reliable estimates of the mean population activity (22). Hence, there is a growing body of evidence suggesting that the encoding of a signal through cortical activity may be improved by minimizing both trialby-trial variability and noise correlations. However, it remains an open experimental and theoretical question, whether these statistics are themselves tuned to different stimulus features, an aspect that may be overlooked when only analyzing preferred and nonpreferred stimuli.Here, we examined the statistics of responses of area-middle temporal (MT) neurons in awake, fixating primates, to moving gratings and different plaid patterns of different directions, as well as moving gratings of differ...

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“…Even the responses of nearby neurons located within the same functional column, which encode the same stimulus property, exhibit a high degree of heterogeneity (1)(2)(3)(4)(5). In primary visual cortex (V1), for instance, it has been reported that neurons tuned to the same stimulus orientation exhibit a high degree of variability in their strength of orientation selectivity, peak response, and baseline activity (1,2).…”

mentioning

confidence: 99%

Efficient coding in heterogeneous neuronal populations

Chelaru

Dragoi

2008

Proc. Natl. Acad. Sci. U.S.A.

141

148

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A ubiquitous feature of neuronal responses within a cortical area is their high degree of inhomogeneity. Even cells within the same functional column are known to have highly heterogeneous response properties when the same stimulus is presented. Whether the wide diversity of neuronal responses is an epiphenomenon or plays a role for cortical function is unknown. Here, we examined the relationship between the heterogeneity of neuronal responses and population coding. Contrary to our expectation, we found that the high variability of intrinsic response properties of individual cells changes the structure of neuronal correlations to improve the information encoded in the population activity. Thus, the heterogeneity of neuronal responses is in fact beneficial for sensory coding when stimuli are decoded from the population response.computational modeling ͉ information coding ͉ sensory cortex ͉ visual cortex ͉ neuronal populations

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Variability and Correlated Noise in the Discharge of Neurons in Motor and Parietal Areas of the Primate Cortex

Cited by 293 publications

References 53 publications

Correlated Discharges Among Putative Pyramidal Neurons and Interneurons in the Primate Prefrontal Cortex

Correlated Discharges Among Putative Pyramidal Neurons and Interneurons in the Primate Prefrontal Cortex

Stimulus-dependent variability and noise correlations in cortical MT neurons

Efficient coding in heterogeneous neuronal populations

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