Neural Basis Of Visual Perception Research Articles

Connectivity reveals homology between the visual systems of the human and macaque brains.

The visual systems of humans and nonhuman primates share many similarities in both anatomical and functional organization. Understanding the homology and differences between the two systems can provide important insights into the neural basis of visual perception and cognition. This research aims to investigate the homology between human and macaque visual systems based on connectivity, using diffusion tensor imaging and resting-state functional magnetic resonance imaging to construct structural and functional connectivity fingerprints of the visual systems in humans and macaques, and quantitatively analyze the connectivity patterns. By integrating multimodal magnetic resonance imaging, this research explored the homology and differences between the two systems. The results showed that 9 brain regions in the macaque visual system formed highly homologous mapping relationships with 11 brain regions in the human visual system, and the related brain regions between the two species showed highly structure homologous, with their functional organization being essentially conserved across species. Finally, this research generated a homology information map of the visual system for humans and macaques, providing a new perspective for subsequent cross-species analysis.

Neural basis of visual perception and reasoning ability in Alzheimer's disease: correlation between Raven's Colored Progressive Matrices test and 123 I-IMP SPECT imaging results.

Impairment of visual perception frequently occurs in Alzheimer's disease (AD) and can cause severe constraints in daily activities. The nonverbal Raven's Colored Progressive Matrices (RCPM) test consists of sets A, AB, and B and is easily performed in a short time to evaluate both visual perception and reasoning ability. The purpose of this study was to evaluate the neural basis of visual perception and reasoning ability in patients with AD using RCPM and single-photon emission computed tomography (SPECT). Fifty patients who fulfilled the National Institute on Aging/Alzheimer's Association criteria for probable AD dementia were examined with RCPM and SPECT. All SPECTs were performed using N-isopropyl-p-[123 I]-iodoamphetamine. A multiple regression model was used to perform multivariate analyses of the relationships between regional cerebral blood flow (rCBF) and RCPM scores. There was a significant positive correlation between RCPM total score and rCBF in the inferior parietal lobes bilaterally, the right inferior temporal gyrus, and the right middle frontal gyrus. Set A was positively correlated with rCBF in the right temporal and right parietal lobes. Set AB was positively correlated with rCBF in the right temporal, right parietal, and right frontal lobes. Set B was positively correlated with rCBF in the right parietal and right frontal lobes. Our findings suggest that deteriorations of specific brain regions are associated with dysfunction of visual perception and reasoning ability in AD. RCPM is another informative assessment scale of cognition for use in patients with AD. Copyright © 2016 John Wiley & Sons, Ltd.

Neuronal Representation of Ultraviolet Visual Stimuli in Mouse Primary Visual Cortex.

The mouse has become an important model for understanding the neural basis of visual perception. Although it has long been known that mouse lens transmits ultraviolet (UV) light and mouse opsins have absorption in the UV band, little is known about how UV visual information is processed in the mouse brain. Using a custom UV stimulation system and in vivo calcium imaging, we characterized the feature selectivity of layer 2/3 neurons in mouse primary visual cortex (V1). In adult mice, a comparable percentage of the neuronal population responds to UV and visible stimuli, with similar pattern selectivity and receptive field properties. In young mice, the orientation selectivity for UV stimuli increased steadily during development, but not direction selectivity. Our results suggest that, by expanding the spectral window through which the mouse can acquire visual information, UV sensitivity provides an important component for mouse vision.

Unraveling the principles of auditory cortical processing: can we learn from the visual system?

Studies of auditory cortex are often driven by the assumption, derived from our better understanding of visual cortex, that basic physical properties of sounds are represented there before being used by higher-level areas for determining sound-source identity and location. However, we only have a limited appreciation of what the cortex adds to the extensive subcortical processing of auditory information, which can account for many perceptual abilities. This is partly because of the approaches that have dominated the study of auditory cortical processing to date, and future progress will unquestionably profit from the adoption of methods that have provided valuable insights into the neural basis of visual perception. At the same time, we propose that there are unique operating principles employed by the auditory cortex that relate largely to the simultaneous and sequential processing of previously derived features and that therefore need to be studied and understood in their own right.

Extraction of Bistable-Percept-Related Features From Local Field Potential by Integration of Local Regression and Common Spatial Patterns

Bistable perception arises when an ambiguous stimulus under continuous view is perceived as an alternation of two mutually exclusive states. Such a stimulus provides a unique opportunity for understanding the neural basis of visual perception because it dissociates the perception from the visual input. In this paper, we focus on extracting the percept-related features from the local field potential (LFP) in monkey visual cortex for decoding its bistable structure-from-motion (SFM) perception. Our proposed feature extraction approach consists of two stages. First, we estimate and remove from each LFP trial the nonpercept-related stimulus-evoked activity via a local regression method called the locally weighted scatterplot smoothing because of the dissociation between the perception and the stimulus in our experimental paradigm. Second, we use the common spatial patterns approach to design spatial filters based on the residue signals of multiple channels to extract the percept-related features. We exploit a support vector machine (SVM) classifier on the extracted features to decode the reported perception on a single-trial basis. We apply the proposed approach to the multichannel intracortical LFP data collected from the middle temporal (MT) visual cortex in a macaque monkey performing an SFM task. We demonstrate that our approach is effective in extracting the discriminative features of the percept-related activity from LFP and achieves excellent decoding performance. We also find that the enhanced gamma band synchronization and reduced alpha and beta band desynchronization may be the underpinnings of the percept-related activity.

Relaxation-Based Feature Selection for Single-Trial Decoding of Bistable Perception

Bistable perception refers to the phenomenon of spontaneously alternating percepts while viewing the same stimulus continuously. Bistable stimuli allow dissociation between stimuli and perception, and thus, provide a unique opportunity for understanding the neural basis of visual perception. In this paper, we focus on a relaxation (RELAX) based algorithm to select features from the multitaper spectral estimates of the multichannel intracortical local field potential (LFP), simultaneously collected from the middle temporal visual cortex of a macaque monkey, for decoding its bistable structure-from-motion (SFM) perception. We demonstrate that RELAX surpasses the conventional sequential forward selection (SFS) by offering the flexibility of modifying selected features. We propose a redundancy reduction preprocessing technique to significantly reduce the computational load for both SFS and RELAX. We exploit the support vector machines classifier based on the selected features for single-trial decoding the reported perception. Our results demonstrate the excellent performance of the RELAX feature selection algorithm. Furthermore, we find that the features in the gamma frequency band (30-100 Hz) of LFP are most relevant to bistable SFM perception. This finding is novel in awake monkey studies and suggests that gamma oscillations carry the most discriminative information for bistable perception of SFM stimuli.

Decoding a bistable percept with integrated time–frequency representation of single-trial local field potential

Bistable perception emerges when a stimulus under continuous view is perceived as the alternation of two mutually exclusive states. Such a stimulus provides a unique opportunity for understanding the neural basis of visual perception because it dissociates the perception from the visual input. In this paper we analyze the dynamic activity of local field potential (LFP), simultaneously collected from multiple channels in the middle temporal (MT) visual cortex of a macaque monkey, for decoding its bistable structure-from-motion (SFM) perception. Based on the observation that the discriminative information of neuronal population activity evolves and accumulates over time, we propose to select features from the integrated time–frequency representation of LFP using a relaxation (RELAX) algorithm and a sequential forward selection (SFS) algorithm with maximizing the Mahalanobis distance as the criterion function. The integrated-spectrogram based feature selection is much more robust and can achieve significantly better features than the instantaneous-spectrogram based feature selection. We exploit the support vector machines (SVM) classifier and the linear discriminant analysis (LDA) classifier based on the selected features to decode the reported perception on a single trial basis. Our results demonstrate the excellent performance of the integrated-spectrogram based feature selection and suggest that the features in the gamma frequency band (30–100 Hz) of LFP within specific temporal windows carry the most discriminative information for decoding bistable perception. The proposed integrated-spectrogram based feature selection approach may have potential for a myriad of applications involving multivariable time series such as brain–computer interfaces (BCI).

Single-Trial Decoding of Bistable Perception Based on Sparse Nonnegative Tensor Decomposition

The study of the neuronal correlates of the spontaneous alternation in perception elicited by bistable visual stimuli is promising for understanding the mechanism of neural information processing and the neural basis of visual perception and perceptual decision-making. In this paper, we develop a sparse nonnegative tensor factorization-(NTF)-based method to extract features from the local field potential (LFP), collected from the middle temporal (MT) visual cortex in a macaque monkey, for decoding its bistable structure-from-motion (SFM) perception. We apply the feature extraction approach to the multichannel time-frequency representation of the intracortical LFP data. The advantages of the sparse NTF-based feature extraction approach lies in its capability to yield components common across the space, time, and frequency domains yet discriminative across different conditions without prior knowledge of the discriminating frequency bands and temporal windows for a specific subject. We employ the support vector machines (SVMs) classifier based on the features of the NTF components for single-trial decoding the reported perception. Our results suggest that although other bands also have certain discriminability, the gamma band feature carries the most discriminative information for bistable perception, and that imposing the sparseness constraints on the nonnegative tensor factorization improves extraction of this feature.

Optimal spatio-temporal pooling of neural responses in area MT

Bistable visual stimuli such as Rubin's vase/face or the Necker cube refer to the phenomena of spontaneously alternating percepts while viewing the same visual image. The uncoupling between the stimulus and percept offers a means for understanding neural basis of visual perception. Here we asked whether pooling the responses of a large population of MT neurons over time and space could improve the predictability of perceptual decisions during ambiguous visual stimulation. Two well trained rhesus monkeys indicated the perceived direction of rotation of bistable structure-from-motion (SFM) stimuli by pushing one of two levers. During this task, multi-channel intracortical recordings including single-unit activity (SUA), multi-unit activity (MUA), and local field potentials (LFP) were collected from area MT. We sorted the neural data according to the monkeys' behavioral choices and employed statistical algorithms to classify brain states (i.e., the subjective interpretation of a bistable stimulus). Classification was performed with linear discriminant analysis with leave-one-out cross-validation. We found that SUA, MUA and LFP all had a rather modest capability of predicting the monkeys' perceptual report when considered in isolation. We developed dynamic models for spatio-temporal integration of distributed neural signals. We found that the discriminative information of neuronal population activity accumulates over time and the combination of simultaneously collected data greatly improved the prediction accuracy of each of the signals. The accuracy and statistical power of determining the monkeys' perception increased with the number of channels as well as with the types of neural signals used for analysis. Our results demonstrate that simultaneous collection of multiple neural responses in area MT can improve the determination of perceptual states.

Den visuelle perceptions flerhed

Pedersen, A.D. (2004). A multiple systems approach to visual perception. Nordisk Psykologi, 56 (1) 19–39. This article present arguments that the neural basis of visual perception is best understood as distributed in several autonomous sensorimotor systems and that the brain does not bind the different aspects of the perceived into a coherent percept. The distributed visual systems make it possible for the organism to engage itself in different activities which require distal visual control over multiple environmental facets with biological and psychological significance for the organism. The article draws its arguments from animal lesion studies, clinical neuropsychology and empirically based theories of “where”, “what” and “how” systems. It is argued that the phenomenological experience that the perception is unified, is not due to something intrinsic in the organism or the organisms brain, but that it is related to the fact that organisms live in a unified world, a universe, where discrete objects exist.

Neural Mechanisms of Visual Perception

It is more than half a century ago since Keffer H Hartline published his classical receptive fields studies of single optic nerve fibres in the frog. World War II intervened and the full impact of his work did not become apparent until the early fifties, when Horace Barlow extended Hartline's analysis in the frog and Stephen W Kuffler showed the on-centre and off-centre type ganglion cells in the cat retina. The next advances were made in the late fifties when Jerome Lettvin and Humberto Maturana described cells in the frog tectum with very complex response properties and when David Hubel and I discovered that cells in the cat striate cortex were sensitive to orientation of contours and binocular stimulation. Vision research has gone a long distance since that time—nonetheless we have just begun the long journey towards a detailed mechanistic understanding of the neural basis of visual perception. In this lecture I discuss the processing of visual information at the level of the striate cortex in the cat and monkey, and describe technical advances that have greatly facilitated the analysis of the neural mechanisms of visual perception.

From enzymes to visual perception: a bridge too far?

The primate visual cortex is a quilt of different areas, each having characteristic anatomical and functional features. The interpretation of the organization of these areas and their function in perception has been a subject of intense debate. New impetus has been given to this debate through the serendipitous discovery that the metabolic enzyme, cytochrome oxidase, is distributed in precise patterns within some areas. This discovery led to the hypothesis that the enzyme is a marker of separate routes of processing through the cortical visual areas. If true, this would be a remarkable development in our understanding of the neural basis of visual perception. It thus seems a timely moment at which to analyse the genesis of this hypothesis and its experimental support.

Analogous neural models for tactual and visual learning

Recent evidence concerning the neural basis of visual perception and learning has led to the development of a sequential neural model in which the striate, prestriate, inferior temporal, and ventromedial frontotemporal areas are viewed as successive links in a neocortical-limbic pathway mediating visual-affective associations [17, 20, 21]. In this paper an analogous model is proposed for touch, with the primary and secondary sensory areas (SI and SII) serving as the successive somatosensory links to the ventromedial limbic region. The model helps to account for some otherwise puzzling data reviewed here pertaining to (a) hierarchical organization in tactual perception, (b) localization of the tactual memory trace, and (c) sensory-limbic interaction in tactual learning. The pivotal link in this model is the secondary sensory area (SII), which is assigned a role in somesthesis similar to that attributed to the inferior temporal area in vision. Evidence from a variety of sources is introduced to support the parallel.