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High-dimensional geometry of population responses in visual cortex
[article]
2018
bioRxiv
pre-print
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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 was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.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]
2021
arXiv
pre-print
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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
2016
Cerebral Cortex
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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
2018
Current Opinion in Behavioral Sciences
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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
2020
eLife
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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]
2022
bioRxiv
pre-print
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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
2010
2010 IEEE Symposium on Visual Analytics Science and Technology
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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
2014
Annual Review of Neuroscience
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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
2013
Journal of Neuroscience
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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
2013
Trends in Cognitive Sciences
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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]
1997
Lecture Notes in Computer Science
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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]
2020
bioRxiv
pre-print
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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
2016
eLife
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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
2016
Current Opinion in Neurobiology
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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
2011
Frontiers in Computational Neuroscience
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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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