scholarly journals The structure of hippocampal CA1 interactions optimizes spatial coding across experience

2021 ◽  
Author(s):  
Michele Nardin ◽  
Jozsef Csicsvari ◽  
Gašper Tkačik ◽  
Cristina Savin
Keyword(s):  
Spatial Information ◽  
Signal To Noise Ratio ◽  
Cell Interactions ◽  
Statistical Estimator ◽  
Spatial Coding ◽  
Efficient Coding ◽  
Maximum Entropy Models ◽  
Hippocampal Ca1 ◽  
Central Brain ◽  
Neural Interactions

Although much is known about how single neurons in the hippocampus represent an animal’s position, how cell-cell interactions contribute to spatial coding remains poorly understood. Using a novel statistical estimator and theoretical modeling, both developed in the framework of maximum entropy models, we reveal highly structured cell-to-cell interactions whose statistics depend on familiar vs. novel environment. In both conditions the circuit interactions optimize the encoding of spatial information, but for regimes that differ in the signal-to-noise ratio of their spatial inputs. Moreover, the topology of the interactions facilitates linear decodability, making the information easy to read out by downstream circuits. These findings suggest that the efficient coding hypothesis is not applicable only to individual neuron properties in the sensory periphery, but also to neural interactions in the central brain.

scholarly journals Combined social and spatial coding in a descending projection from the prefrontal cortex

2017 ◽  
Author(s):  
M. Murugan ◽  
M. Park ◽  
J. Taliaferro ◽  
H.J. Jang ◽  
J. Cox ◽  
...  
Keyword(s):  
Prefrontal Cortex ◽  
Social Behavior ◽  
Spatial Information ◽  
Spatial Association ◽  
Well Being ◽  
Unique Contribution ◽  
Social Investigation ◽  
Spatial Coding ◽  
Socially Motivated ◽  
Spatial Locations

Social interactions are crucial to the survival and well-being of all mammals, including humans. Although the prelimbic cortex (PL, part of medial prefrontal cortex) has been implicated in social behavior, it is not clear which neurons are relevant, nor how they contribute. We found that the PL contains anatomically and molecularly distinct subpopulations of neurons that target 3 downstream regions that have been implicated in social behavior: the nucleus accumbens (NAc), the amygdala, and the ventral tegmental area. Activation of NAc-projecting PL neurons (PL-NAc), but not the other subpopulations, decreased preference for a social target, suggesting an unique contribution of this population to social behavior. To determine what information PL-NAc neurons convey, we recorded selectively from them, and found that individual neurons were active during social investigation, but only in specific spatial locations. Spatially-specific inhibition of these neurons prevented the formation of a social-spatial association at the inhibited location. In contrast, spatially nonspecific inhibition did not affect social behavior. Thus, the unexpected combination of social and spatial information within the PL-NAc population appears to support socially motivated behavior by enabling the formation of social-spatial associations.

scholarly journals Mild Traumatic Brain Injury Decreases Spatial Information Content and Reduces Place Field Stability of Hippocampal CA1 Neurons

2020 ◽  
Vol 37 (2) ◽  
pp. 227-235 ◽  
Author(s):  
John I. Broussard ◽  
John B. Redell ◽  
Jing Zhao ◽  
Mark E. Maynard ◽  
Nobuhide Kobori ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Information Content ◽  
Mild Traumatic Brain Injury ◽  
Spatial Information ◽  
Place Field ◽  
Ca1 Neurons ◽  
Hippocampal Ca1 Neurons ◽  
Hippocampal Ca1

Differences in Spatial Knowledge of Individuals With Blindness When Using Audiotactile Maps, Using Tactile Maps, and Walking

2018 ◽  
Vol 84 (3) ◽  
pp. 330-343 ◽  
Author(s):  
Konstantinos Papadopoulos ◽  
Marialena Barouti ◽  
Eleni Koustriava
Keyword(s):  
Spatial Information ◽  
Visual Impairments ◽  
Cognitive Maps ◽  
Cognitive Map ◽  
Spatial Knowledge ◽  
Spatial Coding ◽  
Direct Experience ◽  
Tactile Maps ◽  
Experimental Trials ◽  
Blind Individuals

To examine how individuals with visual impairments understand space and the way they develop cognitive maps, we studied the differences in cognitive maps resulting from different methods and tools for spatial coding in large geographical spaces. We examined the ability of 21 blind individuals to create cognitive maps of routes in unfamiliar areas using (a) audiotactile maps, (b) tactile maps, and (c) direct experience of movement along the routes. We also compared participants’ cognitive maps created with the use of audiotactile maps, tactile maps, and independent movement along the routes with regard to their precision (i.e., the correctness or incorrectness of spatial information location) and inclusiveness (i.e., the amount of spatial information included correctly in the cognitive map). The results of the experimental trials demonstrated that becoming familiar with an area is easier for blind individuals when they use a tactile aide, such as an audiotactile map, as compared with walking along the route.

Gaussian Noise Filter Using Variable Step Time Matrix of PCNN

2011 ◽  
Vol 48-49 ◽  
pp. 551-554 ◽  
Author(s):  
Yuan Yuan Cheng ◽  
Hai Yan Li ◽  
Qi Xiao ◽  
Yu Feng Zhang ◽  
Xin Ling Shi
Keyword(s):  
Gaussian Noise ◽  
Spatial Information ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Wiener Filter ◽  
Noise Filter ◽  
Variable Step ◽  
Mean Filter ◽  
Reduction Methods ◽  
Novel Method

A novel method was brought forward for the purpose of filtering Gaussian noise effectively by using variable step time matrix of the simplified pulse coupled neural network (PCNN). Firstly, the time matrix of PCNN, related to the grayscale and spatial information of an image, is calculated to identify the noise polluted pixels. Subsequently, a variable step, a long step for strong noise and a short step for weak noise, based on the time matrix is applied to modify the grayscale of noised pixels in a sliding window. And then wiener filter is used to the image to further filter the noise. Experiments show that the proposed filter can remove Gaussian noise effectively than other noise reduction methods such as median filter, mean filter, wiener filter etc, and the filtered image is smooth and the details and edges are sharp. Compared with existing PCNN based Gaussian noise filter, the proposed filter gets higher Peak Signal-to-Noise Ratio (PSNR) and better performance.

scholarly journals Place cells in head-fixed mice navigating a floating real-world environment

2020 ◽  
Author(s):  
Mary Ann Go ◽  
Jake Rogers ◽  
Giuseppe P. Gava ◽  
Catherine Davey ◽  
Seigfred Prado ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Real World ◽  
Spatial Information ◽  
Memory Function ◽  
Place Cells ◽  
Neural Population ◽  
Spatial Coding ◽  
Place Fields ◽  
Freely Moving ◽  
World Environment

ABSTRACTThe hippocampal place cell system in rodents has provided a major paradigm for the scientific investigation of memory function and dysfunction. Place cells have been observed in area CA1 of the hippocampus of both freely moving animals, and of head-fixed animals navigating in virtual reality environments. However, spatial coding in virtual reality preparations has been observed to be impaired. Here we show that the use of a real-world environment system for head-fixed mice, consisting of a track floating on air, provides some advantages over virtual reality systems for the study of spatial memory. We imaged the hippocampus of head-fixed mice injected with the genetically encoded calcium indicator GCaMP6s while they navigated circularly constrained or open environments on the floating platform. We observed consistent place tuning in a substantial fraction of cells with place fields remapping when animals entered a different environment. When animals re-entered the same environment, place fields typically remapped over a time period of multiple days, faster than in freely moving preparations, but comparable with virtual reality. Spatial information rates were within the range observed in freely moving mice. Manifold analysis indicated that spatial information could be extracted from a low-dimensional subspace of the neural population dynamics. This is the first demonstration of place cells in head-fixed mice navigating on an air-lifted real-world platform, validating its use for the study of brain circuits involved in memory and affected by neurodegenerative disorders.

scholarly journals Parallel visual pathways with topographic versus non-topographic organization connect the Drosophila eyes to the central brain

2020 ◽  
Author(s):  
Lorin Timaeus ◽  
Laura Geid ◽  
Gizem Sancer ◽  
Mathias F. Wernet ◽  
Thomas Hummel
Keyword(s):  
Visual Information ◽  
Visual Cues ◽  
Spatial Information ◽  
Central Complex ◽  
Structural Basis ◽  
Projection Neurons ◽  
Central Brain ◽  
Retinotopic Organization ◽  
Dendritic Fields ◽  
Parallel Visual Pathways

SummaryOne hallmark of the visual system is the strict retinotopic organization from the periphery towards the central brain, spanning multiple layers of synaptic integration. Recent Drosophila studies on the computation of distinct visual features have shown that retinotopic representation is often lost beyond the optic lobes, due to convergence of columnar neuron types onto optic glomeruli. Nevertheless, functional imaging revealed a spatially accurate representation of visual cues in the central complex (CX), raising the question how this is implemented on a circuit level. By characterizing the afferents to a specific visual glomerulus, the anterior optic tubercle (AOTU), we discovered a spatial segregation of topographic versus non-topographic projections from molecularly distinct classes of medulla projection neurons (medullo-tubercular, or MeTu neurons). Distinct classes of topographic versus non-topographic MeTus form parallel channels, terminating in separate AOTU domains. Both types then synapse onto separate matching topographic fields of tubercular-bulbar (TuBu) neurons which relay visual information towards the dendritic fields of central complex ring neurons in the bulb neuropil, where distinct bulb sectors correspond to a distinct ring domain in the ellipsoid body. Hence, peripheral topography is maintained due to stereotypic circuitry within each TuBu class, providing the structural basis for spatial representation of visual information in the central complex. Together with previous data showing rough topography of lobula projections to a different AOTU subunit, our results further highlight the AOTUs role as a prominent relay station for spatial information from the retina to the central brain.

scholarly journals Spatio-temporal encoding by quadratic gradients in magnetic resonance imaging

2019 ◽  
Author(s):  
Sina Marhabaie ◽  
Geoffrey Bodenhausen ◽  
Philippe Pelupessy
Keyword(s):  
Spatial Information ◽  
Signal To Noise Ratio ◽  
Magnetic Field Gradient ◽  
Quadratic Function ◽  
Transverse Magnetization ◽  
Chirp Pulse ◽  
Simultaneous Application ◽  
Quadratic Phase ◽  
Temporal Encoding ◽  
Spatio Temporal

Abstract. SPatio-temporal ENcoding (SPEN) MRI is a non-Fourier imaging technique that encodes the spatial information in such a way that there is a one-to-one correspondence between the signal intensity as a function of time and the spin density at the corresponding position. In current spatio-temporal encoding methods imparting a quadratic phase – that is the phase of the transverse magnetization depends as a quadratic function of the spatial coordinates – onto the transverse magnetization is the first crucial step. Usually, this is achieved by simultaneous application of a frequency-swept (chirp) pulse and a linear magnetic field gradient. In this work, we show that it can be advantageous to use quadratic encoding gradients for this purpose. By avoiding chirp pulses one can achieve much smaller specific absorption rates (SARs), and shorter echo times (TEs), while the spatial resolution, the field of view (FOV), and the signal-to-noise ratio (SNR) are the same as in SPEN if one uses similar parameters. In addition, the proposed sequence can readily be used for multi-slice applications.

scholarly journals Spatial Filtering for Enhanced High-Density Surface Electromyographic Examination of Neuromuscular Changes and Its Application to Spinal Cord Injury

2020 ◽  
Author(s):  
Xu Zhang ◽  
Xinhui Li ◽  
Xiao Tang ◽  
Xun Chen ◽  
Xiang Chen ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Spatial Information ◽  
Single Channel ◽  
Signal To Noise Ratio ◽  
Spatial Filtering ◽  
High Density ◽  
Widespread Application ◽  
Cord Injury ◽  
Diagnostic Power

Abstract Background: Spatial filtering of multi-channel signals is considered to be an effective pre-processing approach for improving signal-to-noise ratio. The use of spatial filtering for preprocessing high-density (HD) surface electromyogram (sEMG) helps to extract critical spatial information, but its application to non-invasive examination of neuromuscular changes have not been well investigated.Methods: Aimed at evaluating how spatial filtering can facilitate examination of muscle paralysis, three different spatial filtering methods are presented using principle component analysis (PCA) algorithm, non-negative matrix factorization (NMF) algorithm, and both combination, respectively. Their performance was evaluated in terms of diagnostic power, through HD-sEMG clustering index (CI) analysis of neuromuscular changes in paralyzed muscles following spinal cord injury (SCI).Results: The experimental results showed that: 1) The CI analysis of conventional single-channel sEMG can reveal complex neuromuscular changes in paralyzed muscles following SCI, and its diagnostic power has been confirmed to be characterized by the variance of Z-scores; 2) the diagnostic power was highly dependent on the location of sEMG recording channel. Directly averaging the CI diagnostic indicators over channels just reached a medium level of the diagnostic power; 3) the use of either PCA-based or NMF-based filtering method yielded a greater diagnostic power, and their combination could even enhance the diagnostic power significantly.Conclusions: This study not only presents an essential preprocessing approach for improving diagnostic power of HD-sEMG, but also helps to develop a standard sEMG preprocessing pipeline, thus promoting its widespread application.

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