scholarly journals Neuronal Population Activity in Spinal Motor Circuits: Greater Than the Sum of Its Parts

2017 ◽  
Vol 11 ◽  
Author(s):  
Rune W. Berg
Keyword(s):  
Neuronal Population ◽  
Population Activity ◽  
Motor Circuits ◽  
Spinal Motor

scholarly journals Interpreting Neuronal Population Activity by Reconstruction: Unified Framework With Application to Hippocampal Place Cells

1998 ◽  
Vol 79 (2) ◽  
pp. 1017-1044 ◽  
Author(s):  
Kechen Zhang ◽  
Iris Ginzburg ◽  
Bruce L. McNaughton ◽  
Terrence J. Sejnowski
Keyword(s):  
Bayesian Methods ◽  
Neuronal Population ◽  
Place Cells ◽  
The Body ◽  
Unified Framework ◽  
Population Activity ◽  
Reconstruction Methods ◽  
Special Cases ◽  
Physical Variables ◽  
The Brain

Zhang, Kechen, Iris Ginzburg, Bruce L. McNaughton, and Terrence J. Sejnowski. Interpreting neuronal population activity by reconstruction: unified framework with application to hippocampal place cells. J. Neurophysiol. 79: 1017–1044, 1998. Physical variables such as the orientation of a line in the visual field or the location of the body in space are coded as activity levels in populations of neurons. Reconstruction or decoding is an inverse problem in which the physical variables are estimated from observed neural activity. Reconstruction is useful first in quantifying how much information about the physical variables is present in the population and, second, in providing insight into how the brain might use distributed representations in solving related computational problems such as visual object recognition and spatial navigation. Two classes of reconstruction methods, namely, probabilistic or Bayesian methods and basis function methods, are discussed. They include important existing methods as special cases, such as population vector coding, optimal linear estimation, and template matching. As a representative example for the reconstruction problem, different methods were applied to multi-electrode spike train data from hippocampal place cells in freely moving rats. The reconstruction accuracy of the trajectories of the rats was compared for the different methods. Bayesian methods were especially accurate when a continuity constraint was enforced, and the best errors were within a factor of two of the information-theoretic limit on how accurate any reconstruction can be and were comparable with the intrinsic experimental errors in position tracking. In addition, the reconstruction analysis uncovered some interesting aspects of place cell activity, such as the tendency for erratic jumps of the reconstructed trajectory when the animal stopped running. In general, the theoretical values of the minimal achievable reconstruction errors quantify how accurately a physical variable is encoded in the neuronal population in the sense of mean square error, regardless of the method used for reading out the information. One related result is that the theoretical accuracy is independent of the width of the Gaussian tuning function only in two dimensions. Finally, all the reconstruction methods considered in this paper can be implemented by a unified neural network architecture, which the brain feasibly could use to solve related problems.

scholarly journals Optimization of sensory stimulation for neuronal population activity

2010 ◽  
Vol 11 (S1) ◽  
Author(s):  
Noelia Montejo ◽  
Jean-Luc Blanc ◽  
Yann Mahnoun ◽  
Jean-Michel Brezun ◽  
Nicolas Catz ◽  
...  
Keyword(s):  
Sensory Stimulation ◽  
Neuronal Population ◽  
Population Activity

Dense Circuit Reconstruction to Understand Neuronal Computation: Focus on Zebrafish

2021 ◽  
Vol 44 (1) ◽  
Author(s):  
Rainer W. Friedrich ◽  
Adrian A. Wanner
Keyword(s):  
Neuronal Population ◽  
Higher Order ◽  
Order Structure ◽  
Annual Review ◽  
Publication Date ◽  
Population Activity ◽  
Stimulus Features ◽  
Processing And Storage ◽  
Low Dimensional ◽  
Neuronal Computation

The dense reconstruction of neuronal wiring diagrams from volumetric electron microscopy data has the potential to generate fundamentally new insights into mechanisms of information processing and storage in neuronal circuits. Zebrafish provide unique opportunities for dynamical connectomics approaches that combine reconstructions of wiring diagrams with measurements of neuronal population activity and behavior. Such approaches have the power to reveal higher-order structure in wiring diagrams that cannot be detected by sparse sampling of connectivity and that is essential for neuronal computations. In the brain stem, recurrently connected neuronal modules were identified that can account for slow, low-dimensional dynamics in an integrator circuit. In the spinal cord, connectivity specifies functional differences between premotor interneurons. In the olfactory bulb, tuning-dependent connectivity implements a whitening transformation that is based on the selective suppression of responses to overrepresented stimulus features. These findings illustrate the potential of dynamical connectomics in zebrafish to analyze the circuit mechanisms underlying higher-order neuronal computations. Expected final online publication date for the Annual Review of Neuroscience, Volume 44 is July 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Somatosensory cortical neuronal population activity across states of anaesthesia

2002 ◽  
Vol 15 (4) ◽  
pp. 744-752 ◽  
Author(s):  
Irina A. Erchova ◽  
Mikhail A. Lebedev ◽  
Mathew E. Diamond
Keyword(s):  
Neuronal Population ◽  
Population Activity

Activation of 5-HT1A receptors in medullary raphé disrupts sleep and decreases shivering during cooling in the conscious piglet

2008 ◽  
Vol 294 (3) ◽  
pp. R884-R894 ◽  
Author(s):  
J. W. Brown ◽  
E. A. Sirlin ◽  
A. M. Benoit ◽  
J. M. Hoffman ◽  
R. A. Darnall
Keyword(s):  
Rem Sleep ◽  
Peripheral Vasoconstriction ◽  
Motor Circuits ◽  
Spinal Motor ◽  
Brown Adipose ◽  
Cool Environment ◽  
Way 100635 ◽  
Medullary Raphe ◽  
Physiol Regul Integr Comp ◽  
Stimulation Of

Activation of 5-HT1A receptors in the medullary raphé decreases sympathetically mediated brown adipose tissue (BAT) thermogenesis and peripheral vasoconstriction when previously activated with leptin, LPS, prostaglandins, or cooling. It is not known whether shivering is also modulated by medullary raphé 5-HT1A receptors. We previously showed in conscious piglets that activation of 5-HT1A receptors with (±)-8-hydroxy-2-(dipropylamino)-tetralin (8-OH-DPAT) in the paragigantocellularis lateralis (PGCL), a medullary region lateral to the raphé that contains substantial numbers of 5-HT neurons, eliminates rapid eye movement (REM) sleep and decreases shivering in a cold environment, but does not attenuate peripheral vasoconstriction. Hoffman JM, Brown JW, Sirlin EA, Benoit AM, Gill WH, Harris MB, Darnall RA. Am J Physiol Regul Integr Comp Physiol 293: R518–R527, 2007. We hypothesized that, during cooling, activation of 5-HT1A receptors in the medullary raphé would also eliminate REM sleep and, in contrast to activation of 5-HT1A receptors in the PGCL, would attenuate both shivering and peripheral vasoconstriction. In a continuously cool environment, dialysis of 8-OH-DPAT into the medullary raphé resulted in alternating brief periods of non-REM sleep and wakefulness and eliminated REM sleep, as observed when 8-OH-DPAT is dialyzed into the PGCL. Moreover, both shivering and peripheral vasoconstriction were significantly attenuated after 8-OH-DPAT dialysis into the medullary raphé. The effects of 8-OH-DPAT were prevented after dialysis of the selective 5-HT1A receptor antagonist WAY-100635. We conclude that, during cooling, exogenous activation of 5-HT1A receptors in the medullary raphé decreases both shivering and peripheral vasoconstriction. Our data are consistent with the hypothesis that neurons expressing 5-HT1A receptors in the medullary raphé facilitate spinal motor circuits involved in shivering, as well as sympathetic stimulation of other thermoregulatory effector mechanisms.

scholarly journals The Limited Utility of Multiunit Data in Differentiating Neuronal Population Activity

PLoS ONE ◽  
2016 ◽  
Vol 11 (4) ◽  
pp. e0153154 ◽  
Author(s):  
Corey J. Keller ◽  
Christopher Chen ◽  
Fred A. Lado ◽  
Kamran Khodakhah
Keyword(s):  
Neuronal Population ◽  
Population Activity

scholarly journals Optimal Tuning Widths in Population Coding of Periodic Variables

2006 ◽  
Vol 18 (7) ◽  
pp. 1555-1576 ◽  
Author(s):  
Marcelo A. Montemurro ◽  
Stefano Panzeri
Keyword(s):  
Cortical Neurons ◽  
Neuronal Population ◽  
Population Coding ◽  
Model Parameters ◽  
Population Activity ◽  
Sensory Stimuli ◽  
Tuning Curves ◽  
Periodic Stimulus ◽  
Tuning Width ◽  
Stimulus Features

We study the relationship between the accuracy of a large neuronal population in encoding periodic sensory stimuli and the width of the tuning curves of individual neurons in the population. By using general simple models of population activity, we show that when considering one or two periodic stimulus features, a narrow tuning width provides better population encoding accuracy. When encoding more than two periodic stimulus features, the information conveyed by the population is instead maximal for finite values of the tuning width. These optimal values are only weakly dependent on model parameters and are similar to the width of tuning to orientation ormotion direction of real visual cortical neurons. A very large tuning width leads to poor encoding accuracy, whatever the number of stimulus features encoded. Thus, optimal coding of periodic stimuli is different from that of nonperiodic stimuli, which, as shown in previous studies, would require infinitely large tuning widths when coding more than two stimulus features.

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