| Type | Journal Article |
|---|---|
| Author | Alexander G. Huth |
| Author | Shinji Nishimoto |
| Author | An T. Vu |
| Author | Jack L. Gallant |
| URL | https://linkinghub.elsevier.com/retrieve/pii/S0896627312009348 |
| Volume | 76 |
| Issue | 6 |
| Pages | 1210-1224 |
| Publication | Neuron |
| ISSN | 08966273 |
| Date | 12/2012 |
| DOI | 10.1016/j.neuron.2012.10.014 |
| Accessed | 3/2/2019, 4:23:03 PM |
| Library Catalog | Crossref |
| Language | en |
| Abstract | Humans can see and name thousands of distinct object and action categories, so it is unlikely that each category is represented in a distinct brain area. A more efficient scheme would be to represent categories as locations in a continuous semantic space mapped smoothly across the cortical surface. To search for such a space, we used fMRI to measure human brain activity evoked by natural movies. We then used voxelwise models to examine the cortical representation of 1,705 object and action categories. The first few dimensions of the underlying semantic space were recovered from the fit models by principal components analysis. Projection of the recovered semantic space onto cortical flat maps shows that semantic selectivity is organized into smooth gradients that cover much of visual and nonvisual cortex. Furthermore, both the recovered semantic space and the cortical organization of the space are shared across different individuals. |
| Date Added | 3/2/2019, 4:23:03 PM |
| Modified | 3/2/2019, 4:23:03 PM |
| Type | Journal Article |
|---|---|
| Author | Pieter R. Roelfsema |
| Author | Floris P. de Lange |
| URL | http://www.annualreviews.org/doi/10.1146/annurev-vision-111815-114443 |
| Volume | 2 |
| Issue | 1 |
| Pages | 131-151 |
| Publication | Annual Review of Vision Science |
| ISSN | 2374-4642, 2374-4650 |
| Date | 2016-10-14 |
| DOI | 10.1146/annurev-vision-111815-114443 |
| Accessed | 3/2/2019, 4:32:50 PM |
| Library Catalog | Crossref |
| Language | en |
| Abstract | Neurons in early visual cortical areas not only represent incoming visual information but are also engaged by higher level cognitive processes, including attention, working memory, imagery, and decision-making. Are these cognitive effects an epiphenomenon or are they functionally relevant for these mental operations? We review evidence supporting the hypothesis that the modulation of activity in early visual areas has a causal role in cognition. The modulatory influences allow the early visual cortex to act as a multiscale cognitive blackboard for read and write operations by higher visual areas, which can thereby efficiently exchange information. This blackboard architecture explains how the activity of neurons in the early visual cortex contributes to scene segmentation and working memory, and relates to the subject’s inferences about the visual world. The architecture also has distinct advantages for the processing of visual routines that rely on a number of sequentially executed processing steps. |
| Date Added | 3/2/2019, 4:32:50 PM |
| Modified | 3/2/2019, 4:32:50 PM |
| Type | Journal Article |
|---|---|
| Author | Winrich A. Freiwald |
| Author | Doris Y. Tsao |
| URL | http://science.sciencemag.org/content/330/6005/845 |
| Rights | Copyright © 2010, American Association for the Advancement of Science |
| Volume | 330 |
| Issue | 6005 |
| Pages | 845-851 |
| Publication | Science |
| ISSN | 0036-8075, 1095-9203 |
| Date | 2010/11/05 |
| DOI | 10.1126/science.1194908 |
| Accessed | 3/2/2019, 4:28:18 PM |
| Library Catalog | science.sciencemag.org.revproxy.brown.edu |
| Language | en |
| Abstract | Tuned for Faces The temporal lobe of macaques' brains contains six patches of face-selective cortex. This observation has prompted systems neuroscientists to ask, why so many and what do they do? Freiwald and Tsao (p. 845; see the Perspective by Connor) targeted four of these regions for single-unit recordings and found that the different face-selective patches in macaques have independent functions. The areas where earliest processing occurred were most sharply tuned for individual views and least sharply tuned for identity. The mid-level area was more sharply tuned for identity, and the highest processing stage was strongly tuned for identity in a strikingly view-invariant way. These results yield fundamental insights into the computational process of object recognition, the functional organization of the brain, and how representations are transformed through processing hierarchies. Primates can recognize faces across a range of viewing conditions. Representations of individual identity should thus exist that are invariant to accidental image transformations like view direction. We targeted the recently discovered face-processing network of the macaque monkey that consists of six interconnected face-selective regions and recorded from the two middle patches (ML, middle lateral, and MF, middle fundus) and two anterior patches (AL, anterior lateral, and AM, anterior medial). We found that the anatomical position of a face patch was associated with a unique functional identity: Face patches differed qualitatively in how they represented identity across head orientations. Neurons in ML and MF were view-specific; neurons in AL were tuned to identity mirror-symetrically across views, thus achieving partial view invariance; and neurons in AM, the most anterior face patch, achieved almost full view invariance. Recognition of faces from different viewpoints involves several distinct stages of neural processing. Recognition of faces from different viewpoints involves several distinct stages of neural processing. |
| Date Added | 3/2/2019, 4:28:18 PM |
| Modified | 3/2/2019, 4:28:18 PM |
| Type | Journal Article |
|---|---|
| Author | Siyu Zhang |
| Author | Min Xu |
| Author | Tsukasa Kamigaki |
| Author | Johnny Phong Hoang Do |
| Author | Wei-Cheng Chang |
| Author | Sean Jenvay |
| Author | Kazunari Miyamichi |
| Author | Liqun Luo |
| Author | Yang Dan |
| URL | http://science.sciencemag.org/content/345/6197/660 |
| Rights | Copyright © 2014, American Association for the Advancement of Science |
| Volume | 345 |
| Issue | 6197 |
| Pages | 660-665 |
| Publication | Science |
| ISSN | 0036-8075, 1095-9203 |
| Date | 2014/08/08 |
| Extra | PMID: 25104383 |
| DOI | 10.1126/science.1254126 |
| Accessed | 3/2/2019, 4:33:39 PM |
| Library Catalog | science.sciencemag.org.revproxy.brown.edu |
| Language | en |
| Abstract | You only see what you want to see We often focus on a particular item out of a thousand objects in a visual scene. This ability is called selective attention. Selective attention enhances the responses of sensory nerve cells to whatever is being observed and dampens responses to any distractions. Zhang et al. identified a region of the mouse forebrain that modulates responses in the visual cortex. This modulation improved the mouse's performance in a visual task. Science, this issue p. 660 Top-down modulation of sensory processing allows the animal to select inputs most relevant to current tasks. We found that the cingulate (Cg) region of the mouse frontal cortex powerfully influences sensory processing in the primary visual cortex (V1) through long-range projections that activate local γ-aminobutyric acid–ergic (GABAergic) circuits. Optogenetic activation of Cg neurons enhanced V1 neuron responses and improved visual discrimination. Focal activation of Cg axons in V1 caused a response increase at the activation site but a decrease at nearby locations (center-surround modulation). Whereas somatostatin-positive GABAergic interneurons contributed preferentially to surround suppression, vasoactive intestinal peptide-positive interneurons were crucial for center facilitation. Long-range corticocortical projections thus act through local microcircuits to exert spatially specific top-down modulation of sensory processing. Projections from the frontal cortex control stimulus processing in the visual system in mice. Projections from the frontal cortex control stimulus processing in the visual system in mice. |
| Date Added | 3/2/2019, 4:33:39 PM |
| Modified | 3/2/2019, 4:33:39 PM |
| Type | Journal Article |
|---|---|
| Author | Takayuki Sato |
| Author | Go Uchida |
| Author | Mark D. Lescroart |
| Author | Jun Kitazono |
| Author | Masato Okada |
| Author | Manabu Tanifuji |
| URL | http://www.jneurosci.org/content/33/42/16642 |
| Rights | Copyright © 2013 the authors 0270-6474/13/3316642-15$15.00/0 |
| Volume | 33 |
| Issue | 42 |
| Pages | 16642-16656 |
| Publication | Journal of Neuroscience |
| ISSN | 0270-6474, 1529-2401 |
| Date | 2013/10/16 |
| Extra | PMID: 24133267 |
| Journal Abbr | J. Neurosci. |
| DOI | 10.1523/JNEUROSCI.5557-12.2013 |
| Accessed | 3/2/2019, 4:29:02 PM |
| Library Catalog | www.jneurosci.org.revproxy.brown.edu |
| Language | en |
| Abstract | There are two dominant models for the functional organization of brain regions underlying object recognition. One model postulates category-specific modules while the other proposes a distributed representation of objects with generic visual features. Functional imaging techniques relying on metabolic signals, such as fMRI and optical intrinsic signal imaging (OISI), have been used to support both models, but due to the indirect nature of the measurements in these techniques, the existing data for one model cannot be used to support the other model. Here, we used large-scale multielectrode recordings over a large surface of anterior inferior temporal (IT) cortex, and densely mapped stimulus-evoked neuronal responses. We found that IT cortex is subdivided into distinct domains characterized by similar patterns of responses to the objects in our stimulus set. Each domain spanned several millimeters on the cortex. Some of these domains represented faces (“face” domains) or monkey bodies (“monkey-body” domains). We also identified domains with low responsiveness to faces (“anti-face” domains). Meanwhile, the recording sites within domains that displayed category selectivity showed heterogeneous tuning profiles to different exemplars within each category. This local heterogeneity was consistent with the stimulus-evoked feature columns revealed by OISI. Taken together, our study revealed that regions with common functional properties (domains) consist of a finer functional structure (columns) in anterior IT cortex. The “domains” and previously proposed “patches” are rather like “mosaics” where a whole mosaic is characterized by overall similarity in stimulus responses and pieces of the mosaic correspond to feature columns. |
| Date Added | 3/2/2019, 4:29:02 PM |
| Modified | 3/2/2019, 4:29:02 PM |
| Type | Journal Article |
|---|---|
| Author | D. L. K. Yamins |
| Author | H. Hong |
| Author | C. F. Cadieu |
| Author | E. A. Solomon |
| Author | D. Seibert |
| Author | J. J. DiCarlo |
| URL | http://www.pnas.org/cgi/doi/10.1073/pnas.1403112111 |
| Volume | 111 |
| Issue | 23 |
| Pages | 8619-8624 |
| Publication | Proceedings of the National Academy of Sciences |
| ISSN | 0027-8424, 1091-6490 |
| Date | 2014-06-10 |
| DOI | 10.1073/pnas.1403112111 |
| Accessed | 3/2/2019, 4:25:33 PM |
| Library Catalog | Crossref |
| Language | en |
| Date Added | 3/2/2019, 4:25:33 PM |
| Modified | 3/2/2019, 4:25:33 PM |
| Type | Journal Article |
|---|---|
| Author | Nikolaus Kriegeskorte |
| URL | http://journal.frontiersin.org/article/10.3389/neuro.06.004.2008/abstract |
| Publication | Frontiers in Systems Neuroscience |
| ISSN | 16625137 |
| Date | 2008 |
| DOI | 10.3389/neuro.06.004.2008 |
| Accessed | 3/2/2019, 4:24:25 PM |
| Library Catalog | Crossref |
| Language | en |
| Abstract | A fundamental challenge for systems neuroscience is to quantitatively relate its three major branches of research: brain-activity measurement, behavioral measurement, and computational modeling. Using measured brain-activity patterns to evaluate computational network models is complicated by the need to define the correspondency between the units of the model and the channels of the brain-activity data, e.g., single-cell recordings or voxels from functional magnetic resonance imaging (fMRI). Similar correspondency problems complicate relating activity patterns between different modalities of brain-activity measurement (e.g., fMRI and invasive or scalp electrophysiology), and between subjects and species. In order to bridge these divides, we suggest abstracting from the activity patterns themselves and computing representational dissimilarity matrices (RDMs), which characterize the information carried by a given representation in a brain or model. Building on a rich psychological and mathematical literature on similarity analysis, we propose a new experimental and data-analytical framework called representational similarity analysis (RSA), in which multi-channel measures of neural activity are quantitatively related to each other and to computational theory and behavior by comparing RDMs. We demonstrate RSA by relating representations of visual objects as measured with fMRI in early visual cortex and the fusiform face area to computational models spanning a wide range of complexities.The RDMs are simultaneously related via second-level application of multidimensional scaling and tested using randomization and bootstrap techniques. We discuss the broad potential of RSA, including novel approaches to experimental design, and argue that these ideas, which have deep roots in psychology and neuroscience, will allow the integrated quantitative analysis of data from all three branches, thus contributing to a more unified systems neuroscience. |
| Date Added | 3/2/2019, 4:24:25 PM |
| Modified | 3/2/2019, 4:24:25 PM |
| Type | Journal Article |
|---|---|
| Author | Takashi Owaki |
| Author | Michel Vidal-Naquet |
| Author | Yunjun Nam |
| Author | Go Uchida |
| Author | Takayuki Sato |
| Author | Hideyuki Câteau |
| Author | Shimon Ullman |
| Author | Manabu Tanifuji |
| URL | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0201192 |
| Volume | 13 |
| Issue | 9 |
| Pages | e0201192 |
| Publication | PLOS ONE |
| ISSN | 1932-6203 |
| Date | Sep 20, 2018 |
| Journal Abbr | PLOS ONE |
| DOI | 10.1371/journal.pone.0201192 |
| Accessed | 3/2/2019, 4:27:02 PM |
| Library Catalog | PLoS Journals |
| Language | en |
| Abstract | Despite a large body of research on response properties of neurons in the inferior temporal (IT) cortex, studies to date have not yet produced quantitative feature descriptions that can predict responses to arbitrary objects. This deficit in the research prevents a thorough understanding of object representation in the IT cortex. Here we propose a fragment-based approach for finding quantitative feature descriptions of face neurons in the IT cortex. The development of the proposed method was driven by the assumption that it is possible to recover features from a set of natural image fragments if the set is sufficiently large. To find the feature from the set, we compared object responses predicted from each fragment and responses of neurons to these objects, and search for the fragment that revealed the highest correlation with neural object responses. Prediction of object responses of each fragment was made by normalizing Euclidian distance between the fragment and each object to 0 to 1 such that the smaller distance gives the higher value. The distance was calculated at the space where images were transformed to a local orientation space by a Gabor filter and a local max operation. The method allowed us to find features with a correlation coefficient between predicted and neural responses of 0.68 on average (number of object stimuli, 104) from among 560,000 feature candidates, reliably explaining differential responses among faces as well as a general preference for faces over to non-face objects. Furthermore, predicted responses of the resulting features to novel object images were significantly correlated with neural responses to these images. Identification of features comprising specific, moderately complex combinations of local orientations and colors enabled us to predict responses to upright and inverted faces, which provided a possible mechanism of face inversion effects. (292/300). |
| Date Added | 3/2/2019, 4:27:02 PM |
| Modified | 3/2/2019, 4:27:02 PM |