scholarly journals Lognormal firing rate distribution reveals prominent fluctuation-driven regime in spinal motor networks

2016 ◽  
Author(s):  
Peter C. Petersen ◽  
Rune W. Berg
Keyword(s):  
Neuronal Population ◽  
Output Curve ◽  
Dynamical Regime ◽  
Rhythmic Movements ◽  
Firing Rates ◽  
Motor Behaviors ◽  
Spinal Motor ◽  
Rich Diversity ◽  
The Mean ◽  
Lumbar Spinal

ABSTRACTWhen spinal circuits generate rhythmic movements it is important that the neuronal activity remains within stable bounds to avoid saturation and to preserve responsiveness. In what dynamical regime does the neuronal population operate in order to achieve this? Here, we simultaneously record from hundreds of neurons in lumbar spinal circuits and establish the neuronal fraction that operates within either a ‘mean-driven’ or a ‘fluctuation–driven’ regime during generation of multiple motor behaviors. We find a rich diversity of firing rates across the neuronal population as reflected in a lognormal distribution and demonstrate that half of the neurons spend at least 50% of the time in the ‘fluctuation–driven’ regime regardless of behavior. Since neurons in this regime have a ‘supralinear’ input–output curve, which enhances sensitivity, whereas the mean–driven regime reduces sensitivity, this fraction may reflect a fine trade–off between stability and sensitivity in order to maintain flexibility across motor behaviors.

scholarly journals Lognormal firing rate distribution reveals prominent fluctuation–driven regime in spinal motor networks

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Peter C Petersen ◽  
Rune W Berg
Keyword(s):  
Neuronal Population ◽  
Output Curve ◽  
Input Output ◽  
Rhythmic Movements ◽  
Trade Off ◽  
Firing Rates ◽  
Spinal Motor ◽  
Rich Diversity ◽  
The Mean ◽  
Lumbar Spinal

When spinal circuits generate rhythmic movements it is important that the neuronal activity remains within stable bounds to avoid saturation and to preserve responsiveness. Here, we simultaneously record from hundreds of neurons in lumbar spinal circuits of turtles and establish the neuronal fraction that operates within either a ‘mean-driven’ or a ‘fluctuation–driven’ regime. Fluctuation-driven neurons have a ‘supralinear’ input-output curve, which enhances sensitivity, whereas the mean-driven regime reduces sensitivity. We find a rich diversity of firing rates across the neuronal population as reflected in a lognormal distribution and demonstrate that half of the neurons spend at least 50 % of the time in the ‘fluctuation–driven’ regime regardless of behavior. Because of the disparity in input–output properties for these two regimes, this fraction may reflect a fine trade–off between stability and sensitivity in order to maintain flexibility across behaviors.

scholarly journals What, if anything, is the true neurophysiological significance of “rotational dynamics”?

2019 ◽  
Author(s):  
Mikhail A. Lebedev ◽  
Alexei Ossadtchi ◽  
Nil Adell Mill ◽  
Núria Armengol Urpí ◽  
Maria R. Cervera ◽  
...  
Keyword(s):  
Neuronal Population ◽  
Rotational Dynamics ◽  
Neuronal Responses ◽  
Linear Transformations ◽  
Experimental Conditions ◽  
Temporal Shift ◽  
Firing Rates ◽  
Motor Behaviors ◽  
Neuronal Populations ◽  
Neuronal Mechanisms

AbstractBack in 2012, Churchland and his colleagues proposed that “rotational dynamics”, uncovered through linear transformations of multidimensional neuronal data, represent a fundamental type of neuronal population processing in a variety of organisms, from the isolated leech central nervous system to the primate motor cortex. Here, we evaluated this claim using Churchland’s own data and simple simulations of neuronal responses. We observed that rotational patterns occurred in neuronal populations when (1) there was a temporal shift in peak firing rates exhibited by individual neurons, and (2) the temporal sequence of peak rates remained consistent across different experimental conditions. Provided that such a temporal order of peak firing rates existed, rotational patterns could be easily obtained using a rather arbitrary computer simulation of neural activity; modeling of any realistic properties of motor cortical responses was not needed. Additionally, arbitrary traces, such as Lissajous curves, could be easily obtained from Churchland’s data with multiple linear regression. While these observations suggest that temporal sequences of neuronal responses could be visualized as rotations with various methods, we express doubt about Churchland et al.’s exaggerated assessment that such rotations are related to “an unexpected yet surprisingly simple structure in the population response”, which “explains many of the confusing features of individual neural responses.” Instead, we argue that their approach provides little, if any, insight on the underlying neuronal mechanisms employed by neuronal ensembles to encode motor behaviors in any species.

scholarly journals Analysis of neuronal ensemble activity reveals the pitfalls and shortcomings of rotation dynamics

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Mikhail A. Lebedev ◽  
Alexei Ossadtchi ◽  
Nil Adell Mill ◽  
Núria Armengol Urpí ◽  
Maria R. Cervera ◽  
...  
Keyword(s):  
Neuronal Population ◽  
Neuronal Responses ◽  
Linear Transformations ◽  
Experimental Conditions ◽  
Firing Rates ◽  
Motor Behaviors ◽  
Neuronal Ensembles ◽  
Neuronal Populations ◽  
Activity Modeling ◽  
Neuronal Mechanisms

AbstractBack in 2012, Churchland and his colleagues proposed that “rotational dynamics”, uncovered through linear transformations of multidimensional neuronal data, represent a fundamental type of neuronal population processing in a variety of organisms, from the isolated leech central nervous system to the primate motor cortex. Here, we evaluated this claim using Churchland’s own data and simple simulations of neuronal responses. We observed that rotational patterns occurred in neuronal populations when (1) there was a temporal sequence in peak firing rates exhibited by individual neurons, and (2) this sequence remained consistent across different experimental conditions. Provided that such a temporal order of peak firing rates existed, rotational patterns could be easily obtained using a rather arbitrary computer simulation of neural activity; modeling of any realistic properties of motor cortical responses was not needed. Additionally, arbitrary traces, such as Lissajous curves, could be easily obtained from Churchland’s data with multiple linear regression. While these observations suggest that temporal sequences of neuronal responses could be visualized as rotations with various methods, we express doubt about Churchland et al.’s bold assessment that such rotations are related to “an unexpected yet surprisingly simple structure in the population response”, which “explains many of the confusing features of individual neural responses”. Instead, we argue that their approach provides little, if any, insight on the underlying neuronal mechanisms employed by neuronal ensembles to encode motor behaviors in any species.

scholarly journals A deep convolutional visual encoding model of neuronal responses in the LGN

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Eslam Mounier ◽  
Bassem Abdullah ◽  
Hani Mahdi ◽  
Seif Eldawlatly
Keyword(s):  
Firing Rate ◽  
Visual Information ◽  
Visual Stimulation ◽  
Neuronal Population ◽  
Neuronal Firing ◽  
Electrode Arrays ◽  
Deep Convolutional Neural Networks ◽  
Firing Rates ◽  
Spatiotemporal Representation

AbstractThe Lateral Geniculate Nucleus (LGN) represents one of the major processing sites along the visual pathway. Despite its crucial role in processing visual information and its utility as one target for recently developed visual prostheses, it is much less studied compared to the retina and the visual cortex. In this paper, we introduce a deep learning encoder to predict LGN neuronal firing in response to different visual stimulation patterns. The encoder comprises a deep Convolutional Neural Network (CNN) that incorporates visual stimulus spatiotemporal representation in addition to LGN neuronal firing history to predict the response of LGN neurons. Extracellular activity was recorded in vivo using multi-electrode arrays from single units in the LGN in 12 anesthetized rats with a total neuronal population of 150 units. Neural activity was recorded in response to single-pixel, checkerboard and geometrical shapes visual stimulation patterns. Extracted firing rates and the corresponding stimulation patterns were used to train the model. The performance of the model was assessed using different testing data sets and different firing rate windows. An overall mean correlation coefficient between the actual and the predicted firing rates of 0.57 and 0.7 was achieved for the 10 ms and the 50 ms firing rate windows, respectively. Results demonstrate that the model is robust to variability in the spatiotemporal properties of the recorded neurons outperforming other examined models including the state-of-the-art Generalized Linear Model (GLM). The results indicate the potential of deep convolutional neural networks as viable models of LGN firing.

OBESITY AND SELF-REPORTED OUTCOME AFTER MINIMALLY INVASIVE LUMBAR SPINAL FUSION SURGERY

Neurosurgery ◽  
2008 ◽  
Vol 63 (5) ◽  
pp. 956-960 ◽  
Author(s):  
David S. Rosen ◽  
Sherise D. Ferguson ◽  
Alfred T. Ogden ◽  
Dezheng Huo ◽  
Richard G. Fessler
Keyword(s):  
Minimally Invasive ◽  
Linear Models ◽  
Short Form ◽  
Length Of Hospital Stay ◽  
Fusion Surgery ◽  
Body Habitus ◽  
Short Form 36 ◽  
Spinal Fusion Surgery ◽  
The Mean ◽  
Lumbar Spinal

Abstract OBJECTIVE Many patients undergoing lumbar spine fusion are overweight or obese. The relationship between body habitus and outcome after lumbar spine fusion surgery is not well defined. METHODS We analyzed a prospectively maintained database of self-reported pain and quality of life measures, including Visual Analog Scale pain score, Short Form 36, and Oswestry Disability Index. We selected patients undergoing minimally invasive transforaminal lumbar interbody fusion between September 2002 and June 2006 at a single institution. We used linear regression models and mixed-effects linear models to examine the relationships between body habitus and self-reported outcomes. RESULTS The analysis identified 110 patients meeting the study criteria, with a median follow-up period of 14.8 months. The mean age was 56 years, mean height was 169 cm, and mean weight was 82.2 kg. The mean body mass index (BMI) was 28.7 kg/m2; 31% of patients were overweight (BMI, 25–29.9), and 32% of patients were obese (BMI, >30). Linear regression analysis did not identify a correlation between weight or BMI and pre- and postsurgery changes in any of the outcome measures. The significant findings observed in the mixed-effects linear models were that the changing patterns of Short Form 36 Body Pain subscale and Short Form 36 Vitality subscale varied significantly by category of BMI (P = 0.01 and P = 0.002, respectively), but not significantly if continuous BMI was used (P = 0.53 and P = 0.46, respectively). BMI correlated marginally with estimated blood loss (P = 0.08), but not operative time, length of hospital stay, or complications. CONCLUSION Among this cohort of minimally invasive lumbar fusion patients, body habitus measured by BMI, weight, or height did not have a significant relationship with most self-reported outcome measures, operative time, length of hospital stay, or complications. Obesity should not be considered a contraindication to minimally invasive lumbar spinal fusion surgery.

Minimally invasive anteroposterior combined surgery using lateral lumbar interbody fusion without corpectomy for treatment of lumbar spinal canal stenosis associated with osteoporotic vertebral collapse

2021 ◽  
pp. 1-9
Author(s):  
Kentaro Fukuda ◽  
Hiroyuki Katoh ◽  
Yuichiro Takahashi ◽  
Kazuya Kitamura ◽  
Daiki Ikeda
Keyword(s):  
Interbody Fusion ◽  
Combined Surgery ◽  
Vertebral Collapse ◽  
Short Segment ◽  
Canal Stenosis ◽  
The Mean ◽  
Osteoporotic Vertebral Collapse ◽  
Anterior Support ◽  
Lumbar Spinal

OBJECTIVE Various reconstructive surgical procedures have been described for lumbar spinal canal stenosis (LSCS) with osteoporotic vertebral collapse (OVC); however, the optimal surgery remains controversial. In this study, the authors aimed to report the clinical and radiographic outcomes of their novel, less invasive, short-segment anteroposterior combined surgery (APCS) that utilized oblique lateral interbody fusion (OLIF) and posterior fusion without corpectomy to achieve decompression and reconstruction of anterior support in patients with LSCS-OVC. METHODS In this retrospective study, 20 patients with LSCS-OVC (mean age 79.6 years) underwent APCS and received follow-up for a mean of 38.6 months. All patients were unable to walk without support owing to severe low-back and leg pain. Cleft formations in the fractured vertebrae were identified on CT. APCS was performed on the basis of a novel classification of OVC into three types. In type A fractures with a collapsed rostral endplate, combined monosegment OLIF and posterior spinal fusion (PSF) were performed between the collapsed and rostral adjacent vertebrae. In type B fractures with a collapsed caudal endplate, combined monosegment OLIF and PSF were performed between the collapsed and caudal adjacent vertebrae. In type C fractures with severe collapse of both the rostral and caudal endplates, bisegment OLIF and PSF were performed between the rostral and caudal adjacent vertebrae, and pedicle screws were also inserted into the collapsed vertebra. Preoperative and postoperative clinical and radiographical status were reviewed. RESULTS The mean number of fusion segments was 1.6. Walking ability improved in all patients, and the mean Japanese Orthopaedic Association score for recovery rate was 65.7%. At 1 year postoperatively, the mean preoperative Oswestry Disability Index of 65.6% had significantly improved to 21.1%. The mean local lordotic angle, which was −5.9° preoperatively, was corrected to 10.5° with surgery and was maintained at 7.7° at the final follow-up. The mean corrective angle was 16.4°, and the mean correction loss was 2.8°. CONCLUSIONS The authors have proposed using minimally invasive, short-segment APCS with OLIF, tailored to the morphology of the collapsed vertebra, to treat LSCS-OVC. APCS achieves neural decompression, reconstruction of anterior support, and correction of local alignment.

Physiology and Morphology of Shared and Specialized Spinal Interneurons for Locomotion and Scratching

2008 ◽  
Vol 99 (6) ◽  
pp. 2887-2901 ◽  
Author(s):  
Ari Berkowitz
Keyword(s):  
Direct Evidence ◽  
Ventral Horn ◽  
Morphological Properties ◽  
Rhythmic Movements ◽  
Potential Oscillations ◽  
Spinal Interneurons ◽  
Firing Rates ◽  
Motor Outputs ◽  
Membrane Potential Oscillations

Distinct types of rhythmic movements that use the same muscles are typically generated largely by shared multifunctional neurons in invertebrates, but less is known for vertebrates. Evidence suggests that locomotion and scratching are produced partly by shared spinal cord interneuronal circuity, although direct evidence with intracellular recording has been lacking. Here, spinal interneurons were recorded intracellularly during fictive swimming and fictive scratching in vivo and filled with Neurobiotin. Some interneurons that were rhythmically activated during both swimming and scratching had axon terminal arborizations in the ventral horn of the hindlimb enlargement, indicating their likely contribution to hindlimb motor outputs during both behaviors. We previously described a morphological group of spinal interneurons (“transverse interneurons” or T neurons) that were rhythmically activated during all forms of fictive scratching at higher peak firing rates and with larger membrane potential oscillations than scratch-activated spinal interneurons with different dendritic orientations. The current study demonstrates that T neurons are activated during both swimming and scratching and thus are components of the shared circuitry. Many spinal interneurons activated during fictive scratching are also activated during fictive swimming (scratch/swim neurons), but others are suppressed during swimming (scratch-specialized neurons). The current study demonstrates that some scratch-specialized neurons receive strong and long-lasting hyperpolarizing inhibition during fictive swimming and are also morphologically distinct from T neurons. Thus this study indicates that locomotion and scratching are produced by a combination of shared and dedicated interneurons whose physiological and morphological properties are beginning to be revealed.

Bursts and recurrences of bursts in the spike trains of spontaneously active striate cortex neurons

1985 ◽  
Vol 53 (4) ◽  
pp. 926-939 ◽  
Author(s):  
C. R. Legendy ◽  
M. Salcman
Keyword(s):  
Standard Deviation ◽  
Spike Train ◽  
Striate Cortex ◽  
Quantitative Measure ◽  
Spike Trains ◽  
Spike Rate ◽  
Occurrence Rate ◽  
Implanted Electrodes ◽  
Firing Rates ◽  
The Mean

Simultaneous recordings were made from small collections (2-7) of spontaneously active single units in the striate cortex of unanesthetized cats, by means of chronically implanted electrodes. The recorded spike trains were computer scanned for bursts of spikes, and the bursts were catalogued and studied. The firing rates of the neurons ranged from 0.16 to 32 spikes/s; the mean was 8.9 spikes/s, the standard deviation 7.0 spikes/s. Bursts of spikes were assigned a quantitative measure, termed Poisson surprise (S), defined as the negative logarithm of their probability in a random (Poisson) spike train. Only bursts having S greater than 10, corresponding to an occurrence rate of about 0.01 bursts/1,000 spikes in a random spike train, were considered to be of interest. Bursts having S greater than 10 occurred at a rate of about 5-15 bursts/1,000 spikes, or about 1-5 bursts/min. The rate slightly increased with spike rate; averaging about 2 bursts/min for neurons having 3 spikes/s and about 4.5 bursts/min for neurons having 30 spikes/s. About 21% of the recorded units emitted significantly fewer bursts than the rest (below 1 burst/1,000 spikes). The percentage of these neurons was independent of spike rate. The spike rate during bursts was found to be about 3-6 times the average spike rate; about the same for longer as for shorter bursts. Bursts typically contained 10-50 spikes and lasted 0.5-2.0 s. When the number of spikes in the successively emitted bursts was listed, it was found that in some neurons these numbers were not distributed at random but were clustered around one or more preferred values. In this sense, bursts occasionally "recurred" a few times in a few minutes. The finding suggests that neurons are highly reliable. When bursts of two or more simultaneously recorded neurons were compared, the bursts often appeared to be temporally close, especially between pairs of neurons recorded by the same electrode; but bursts seldom started and ended simultaneously on two channels. Recurring bursts emitted by one neuron were occasionally accompanied by time-locked recurring bursts by other neurons.

scholarly journals Variance: A Possible Coding Mechanism for Gustatory Sensilla on the Labellum of the Fleshfly Sarcophaga Bullata

1990 ◽  
Vol 150 (1) ◽  
pp. 19-36
Author(s):  
B. K. MITCHELL ◽  
J. J.B. SMITH ◽  
P. J. ALBERT ◽  
A. T. WHITEHEAD
Keyword(s):  
Complex Stimulus ◽  
Three Solutions ◽  
Firing Rates ◽  
Sarcophaga Bullata ◽  
Medium Length ◽  
Electrophysiological Responses ◽  
Taste Sensilla ◽  
The Mean ◽  
Behavioural Tests ◽  
Gustatory Sensilla

In behavioural tests, 2-day-old female Sarcophaga bullata consumed more liver or fish powder in solution than 100 mmol l−1 sucrose. We investigated the chemosensory basis of this discrimination by recording electrophysiological responses of 177 medium-length labellar taste sensilla from 10 different flies to two applications of each of these three solutions. Responses from three chemosensory cells were evident in most records. Cell 1 produced a mean response of 37.6 impulses s−1, and similar responses to all three stimuli. It was the most active of the three cells. Cell 2 produced a significantly greater response to fish than to liver or sucrose in one of the two stimulus applications. Cell 3, the least active, responded with twice the firing rate to fish than to liver or sucrose. However, the mean firing rates did not provide information that could account for the observed behavioural discrimination. The only difference in the electrophysiological responses to the three stimuli which correlated with the behavioural discrimination was the variance of the response of cell 1, which was much higher to sucrose than to either fish or liver. We propose that variance itself could provide the necessary information to allow the fly's nervous system to distinguish between a ‘simple’ stimulus such as sucrose and a ‘complex’ stimulus such as fish or liver.

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