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High-dimensional geometry of population responses in visual cortex [article]

Carsen Stringer, Marius Pachitariu, Nicholas Steinmetz, Matteo Carandini, Kenneth D Harris
2018 bioRxiv   pre-print
Here, we analyzed the correlation structure of natural image coding, in large visual cortical populations recorded from awake mice.  ...  A neuronal population encodes information most efficiently when its activity is uncorrelated and high-dimensional, and most robustly when its activity is correlated and lower-dimensional.  ...  perpetuity. was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.  ... 
doi:10.1101/374090 fatcat:rmeaoobfgvf35mm44xkfg54cem

Neural population geometry: An approach for understanding biological and artificial neural networks [article]

SueYeon Chung, L. F. Abbott
2021 arXiv   pre-print
One approach to addressing this challenge is to utilize mathematical and computational tools to analyze the geometry of these high-dimensional representations, i.e., neural population geometry.  ...  Together, these findings illustrate an exciting trend at the intersection of machine learning, neuroscience, and geometry, in which neural population geometry provides a useful population-level mechanistic  ...  Indeed, the challenges in interpreting high-dimensional ANNs, containing millions of parameters, and neural populations are shared [25] .  ... 
arXiv:2104.07059v2 fatcat:i3huichzs5eehcb7ij6rthkl2e

A Model of Representational Spaces in Human Cortex

J. Swaroop Guntupalli, Michael Hanke, Yaroslav O. Halchenko, Andrew C. Connolly, Peter J. Ramadge, James V. Haxby
2016 Cerebral Cortex  
Here, we present a linear model of shared representational spaces in human cortex that captures fine-scale distinctions among population responses with response-tuning basis functions that are common across  ...  Current models of the functional architecture of human cortex emphasize areas that capture coarse-scale features of cortical topography but provide no account for population responses that encode information  ...  Neural representational spaces in human cortex are high-dimensional.  ... 
doi:10.1093/cercor/bhw068 pmid:26980615 pmcid:PMC4869822 fatcat:sy6zffnqyrds7gbels7go23nhm

Modality general and modality specific coding of hedonic valence

V Miskovic, AK Anderson
2018 Current Opinion in Behavioral Sciences  
between how things look, sound, feel, taste and smell good or bad to us, offering a higher dimensional space of evaluative discriminations.  ...  Here we raise the possibility that, in addition to these well established gain control effects, sensory systems might also have a more direct role in representing the pleasantness component of perception  ...  Alongside these sensory properties, population coding of self-reported hedonics was reflected in distributed swaths of cortex.  ... 
doi:10.1016/j.cobeha.2017.12.012 pmid:29967806 pmcid:PMC6024250 fatcat:t3ofpmjd5vf5bh2olh2n4mvjli

Hyperalignment: Modeling shared information encoded in idiosyncratic cortical topographies

James V Haxby, J Swaroop Guntupalli, Samuel A Nastase, Ma Feilong
2020 eLife  
Hyperalignment captures shared information by projecting pattern vectors for neural responses and connectivities into a common, high-dimensional information space, rather than by aligning topographies  ...  Individual transformation matrices project information from individual anatomical spaces into the common model information space, preserving the geometry of pairwise dissimilarities between pattern vectors  ...  in functional architecture in a high-dimensional information space.  ... 
doi:10.7554/elife.56601 pmid:32484439 fatcat:dbikkgynz5fx3hpxyjdmal5bn4

Ramp-shaped neural tuning supports graded population-level representation of the object-to-scene continuum [article]

Jeongho Park, Emilie Josephs, Talia Konkle
2022 bioRxiv   pre-print
Thus, our results together suggest that depicted spatial scale is coded parametrically in large-scale population codes across the entire ventral occipito-temporal cortex.  ...  Instead, we observed large swaths of cortex with opposing ramp-shaped profiles, with highest responses to one end of the object-to-scene continuum or the other, and a small region showing a weak tuning  ...  The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.  ... 
doi:10.1101/2022.01.06.475244 fatcat:rcdnb6mskjcqzotplyp2lyqdaa

Large-scale neuroanatomical visualization using a manifold embedding approach

Shantanu H. Joshi, Ian Bowman, John Darrell Van Horn
2010 2010 IEEE Symposium on Visual Analytics Science and Technology  
We present a unified framework for data processing, mining and interactive visualization of largescale neuroanatomical databases.  ...  Our workflow implements predefined metrics for clustering and classification, and data projection schemes to aid in visualization.  ...  There are numerous techniques to project high dimensional data into lower dimensional spaces for analysis or visualization.  ... 
doi:10.1109/vast.2010.5652532 pmid:21318096 pmcid:PMC3037590 dblp:conf/ieeevast/JoshiBH10 fatcat:4m2fc7lfrnbdnbwkezjwilyviu

Decoding Neural Representational Spaces Using Multivariate Pattern Analysis

James V. Haxby, Andrew C. Connolly, J. Swaroop Guntupalli
2014 Annual Review of Neuroscience  
in patterns of brain activity.  ...  This article reviews these advances and integrates neural decoding methods into a common framework organized around the concept of high-dimensional representational spaces. 435 Annu. Rev.  ...  All the neural decoding and encoding methods can be understood in terms of analyzing or manipulating the geometry of the response vectors in a high-dimensional space.  ... 
doi:10.1146/annurev-neuro-062012-170325 pmid:25002277 fatcat:ah6sfup2mrct7bkg2kel37z3w4

Perceptual Spaces: Mathematical Structures to Neural Mechanisms

Q. Zaidi, J. Victor, J. McDermott, M. Geffen, S. Bensmaia, T. A. Cleland
2013 Journal of Neuroscience  
The diversity of the neural architecture in these different sensory systems provides an opportunity to compare their different solutions to common problems: the need for dimensionality reduction, strategies  ...  A central goal of neuroscience is to understand how populations of neurons build and manipulate representations of percepts that provide useful information about the environment.  ...  High-dimensional computational architecture of odor representations In olfaction, the dimensionality and geometry of similarity for representational processing are unusually configured, and this has important  ... 
doi:10.1523/jneurosci.3343-13.2013 pmid:24198350 pmcid:PMC3818541 fatcat:g7o4kys47nfgxmmy6a5hsmyxdq

Representational geometry: integrating cognition, computation, and the brain

Nikolaus Kriegeskorte, Rogier A. Kievit
2013 Trends in Cognitive Sciences  
A visually perceived object, for example, will correspond to a point in the representational space of a given visual area.  ...  Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented.  ...  The space in which the dots are placed is the space of representational patterns (illustrated as two-dimensional, but high-dimensional in reality).  ... 
doi:10.1016/j.tics.2013.06.007 pmid:23876494 pmcid:PMC3730178 fatcat:c2swzal2pzhdljj2rliiqwzo2e

Geometry of orientation preference map determines nonclassical receptive field properties [chapter]

U. Ernst, K. Pawelzik, F. Wolf, T. Geisel
1997 Lecture Notes in Computer Science  
Our model includes the long-range lateral connections linking cell populations of similar orientation preference, and the dynamics of local microcircuits which introduce a di erential interaction whose  ...  We demonstrate that the geometry of an orientation preference map determines the positions of cells sensitive for orientation contrasts, and we propose a simple statistical method to check the predictions  ...  At the same time, this framework may o er a test if the mechanisms revealed in the simulations are consistent with the biological nature of nonclassical receptive elds.  ... 
doi:10.1007/bfb0020161 fatcat:nzmytv53dfbjvok4hgdyc75om4

Object manifold geometry across the mouse cortical visual hierarchy [article]

Emmanouil Froudarakis, Uri Cohen, Maria Diamantaki, Edgar Y. Walker, Jacob Reimer, Philipp Berens, Haim Sompolinsky, Andreas S. Tolias
2020 bioRxiv   pre-print
We simultaneously recorded the responses of thousands of neurons to measure the information about object identity available across the visual cortex and found that lateral visual areas LM, LI and AL carry  ...  However, the associated changes in the geometry of object manifolds along the cortex remain unknown. Using home cage training we showed that mice are capable of invariant object recognition.  ...  However, the associated changes in the geometry of the object manifold along the visual cortex remain unknown for any species.  ... 
doi:10.1101/2020.08.20.258798 fatcat:edhr63d4pja4do53bcz25ptnti

Object vision to hand action in macaque parietal, premotor, and motor cortices

Stefan Schaffelhofer, Hansjörg Scherberger
2016 eLife  
We visualize these non-discrete premotor signals that drive the primary motor cortex M1 to reflect the movement of the grasping hand.  ...  The parietal area AIP operated primarily in a visual mode.  ...  ., seeds in sawdust). Monkeys had visual and auditory contact to other monkeys. They were fed on a diet of enriched biscuits and fruits.  ... 
doi:10.7554/elife.15278 pmid:27458796 pmcid:PMC4961460 fatcat:jwkvz7n5ofaw5am3bk2tifz7eu

Why neurons mix: high dimensionality for higher cognition

Stefano Fusi, Earl K Miller, Mattia Rigotti
2016 Current Opinion in Neurobiology  
This form of mixed selectivity plays an important computational role which is related to the dimensionality of the neural representations: high-dimensional representations with mixed selectivity allow  ...  In contrast, neural representations based on highly specialized neurons are low dimensional and they preclude a linear readout from generating several responses that depend on multiple task-relevant variables  ...  visual percept of neurons famously reported in inferotemporal (IT) cortex [31] .  ... 
doi:10.1016/j.conb.2016.01.010 pmid:26851755 fatcat:dk6cq44lgreyfhoeljplm7k5bq

Population Coding of Visual Space: Modeling

Sidney R. Lehky, Anne B. Sereno
2011 Frontiers in Computational Neuroscience  
These responses were analyzed using multidimensional scaling to extract the representation of global space implicit in population activity.  ...  that in some cases the neural representation of space may be dimensionally isomorphic with 3D physical space.  ...  to the original high-dimensional neural response data.  ... 
doi:10.3389/fncom.2010.00155 pmid:21344012 pmcid:PMC3034232 fatcat:gpxh6zgnzvc5zgmydmncirbdmy
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