Higher Visual Areas Research Articles

Reward facilitates hemodynamic responses in higher visual areas

Reward facilitates hemodynamic responses in higher visual areas

Effect of retinal phototoxicity induced by blue light exposure on the response properties of neurons of the lateral geniculate nucleus of the rat

Abstract Purpose Exposure to bright blue light causes photochemical damage of rodent’s retina via the apoptotic pathway involved in retinitis pigmentosa and age‐related macular degeneration. This photochemical retinal damage occurs with a several different types of morphology and the severity of retinal damage induced by light has great variation among retinal regions. Rather than a mere decrease of the visual response blue light phototoxicity involves important changes on image processing at the retina. Higher visual areas, such as lateral geniculate nucleus (LGN) must adapt their physiology to the new situation. In the present work we will study the changes, and their temporal course, of the response of LGN neurons provoked by acute exposure to bright blue light. Methods We will stimulate the retina of Wistar rats at 7 different wavelengths and we will record extracellular multiunit activity of these neurons on three different groups: without exposure to bright light (control group), rats exposed to bright (5000 lux) blue light for 72 hours (exposed group) and rats exposed and let a week under control conditions (recovery group). Results Exposed group showed different profiles of the response parameters measured at the different stimulating wavelengths. These profiles were similar between control and recovery groups. Conclusion Data shows that retinal damage induced by blue light has a great impact on LGN physiology and that plasticity changes must occur at this area to adapt to the new situation.

Representation sharpening can explain perceptual priming.

Perceiving and identifying an object is improved by prior exposure to the object. This perceptual priming phenomenon is accompanied by reduced neural activity. But whether suppression of neuronal activity with priming is responsible for the improvement in perception is unclear. To address this problem, we developed a rate-based network model of visual processing. In the model, decreased neural activity following priming was due to stimulus-specific sharpening of representations taking place in the early visual areas. Representation sharpening led to decreased interference of representations in higher visual areas that facilitated selection of one of the competing representations, thereby improving recognition. The model explained a wide range of psychophysical and physiological data observed in priming experiments, including antipriming phenomena, and predicted two functionally distinct stages of visual processing.

Integration of local features into global shapes: monkey and human fMRI studies

Summary the properties of neurons in different visual areas (Hubel and Wiesel, 1968; Felleman and Van Essen, 1991; Van The integration of local image features into global Essen et al., 1992), and in humans, where recent fMRI shapes was investigated in monkeys and humans us- studies provide evidence for functional organization of ing fMRI. An adaptation paradigm was used, in which the visual cortex (Wandell, 1999, for review). The strong stimulus selectivity was deduced by changes in the correlation between the fMRI signal and the underlying course of adaptation of a pattern of randomly oriented neural responses (Logothetis et al., 2001) emphasizes elements. Accordingly, we observed stronger activity the importance of such studies for bridging the gap when orientation changes in the adapting stimulus between the extensive neurophysiological findings in resulted in a collinear contour than a different random monkeys and those reported in combined psychophysipattern. This selectivity to collinear contours was ob- cal and imaging investigations with humans. Our goal served not only in higher visual areas that are impli- was to investigate the visual integration processes in cated in shape processing, but also in early visual both the monkey and the human brain by using the same areas where selectivity depended on the receptive fMRI technique and similar experimental paradigms. field size. These findings suggest that unified shape We tested responses across visual areas to collinear perception in both monkeys and humans involves mul- contours versus random patterns. The collinear patterns tiple visual areas that may integrate local elements to consisted of a number of similarly oriented elements global shapes at different spatial scales. embedded into a background of randomly oriented elements, while the random patterns consisted of a field of randomly oriented elements. Such displays yield the

Modeling neural tuning to border ownership of figures through intracortical interactions in V2

A border between two image regions is normally owned by only one of the regions; determining which one is essential for surface perception and figure-ground segmentation. Border ownership (BOWN) is signalled by some V2 neurons, even though its value depends on information coming from well outside their classical receptive fields (Zhou, Friedman, von der Heydt, J. Neurosci. 20(17):6594–411, 2000). Tuning to BOWN is significantly weaker or even absent in V1, so the tuning in V2 cannot be relayed from V1. Thus the key question arises whether the context-dependent neural tuning to BOWN in V2 is generated by mechanisms within this area, by top-down feedback from higher visual areas, or by a combination of both top-down and local mechanisms. I use a model of V2 to show that this visual area can plausibly generate the ownership signal by itself, without requiring top-down mechanisms or external explicit labels for figures, T junctions or corners. In the model, neurons have spatially local classical receptive fields, are tuned to orientation, and only receive information (from V1) about the location and orientation of borders. Tuning to BOWN arises in the model through finite-range, intra-cortical interactions. The model can account for the physiological observations in Zhou et al 2000 and Qiu and von der Heydt, VSS abstract 115, 2003, including the effect of occlusion, transparency and figures of different sizes, shapes and neighborhood relationships. The model also makes testable predictions, the matches to which can be used to constrain the model parameters further. The model can be extended to include the effects of additional image cues, such as surface luminance and depth, or top down attention, whose influence on BOWN have been observed psychophysically.

Masking interrupts figure-ground signals in V1

In a backward masking paradigm, a target stimulus is rapidly (<100 msec) followed by a second stimulus. This typically results in a dramatic decrease in the visibility of the target stimulus. It has been shown that masking reduces responses in V1. It is not known, however, which process in V1 is affected by the mask. In the past, we have shown that in V1, modulations of neural activity that are specifically related to figure–ground segregation can be recorded. Here, we recorded from awake macaque monkeys, engaged in a task where they had to detect figures from background in a pattern backward masking paradigm. We show that the V1 figure–ground signals are selectively and fully suppressed at target–mask intervals that psychophysically result in the target being invisible. Initial response transients, signalling the features that make up the scene, are not affected. As figure–ground modulations depend on feedback from extrastriate areas, these results suggest that masking selectively interrupts the recurrent interactions between V1 and higher visual areas.

MT neurons do not signal relative disparity

Psychophysical studies have shown that relative disparity, the difference of two absolute disparities, is important in perceptual judgements such as stereoacuity. A recent study showed that a small but significant population of V2 neurons signals relative disparity, whereas V1 neurons do not (Thomas et al. 1999, SFN Abstr.). A logical hypothesis is that higher visual areas may contain more neurons signaling relative disparity. In this study, we tested whether MT neurons signal relative disparity between their classical receptive field (CRF) and surrounding regions. We recorded 40 neurons from 3 awake fixating rhesus monkeys. A bi-partite (center/surround) random-dot stereogram was presented, with the center patch covering the neurons' CRF. Dots in both the center and surround patches moved at the neuron's preferred velocity, and both the center and surround disparities varied from trial to trial. Disparity tuning of responses to the center patch was obtained for each of 3–5 surround disparities, and each tuning curve was fit with a gabor function. If neurons signal relative disparity, the tuning curves should shift by an amount equal to the surround disparity. For each possible pair of surround disparities, we calculated the shift in the peak or trough of the tuning curves relative to the difference in surround disparity (shift ratio). A shift ratio of 1 indicates that the shift was equal to the difference in surround disparity, consistent with relative disparity encoding. A shift ratio of 0 indicates that there was no shift with surround disparity, consistent with absolute disparity encoding. Although the median shift ratio of 0.041 was significantly different from 0 (sign-test, p=0.0005, n=209 shifts), the distribution was tightly clustered around 0, and only 1% (2/209) of shift ratios were larger than 0.5. The results suggest that MT neurons do not signal relative disparity in a center-surround configuration, but rather signal the absolute disparity in their CRF.

Perceptual priming leads to reduction of gamma frequency oscillations

Oscillations of neural activity are ubiquitous in the brain and are critical for normal cognitive function. In the visual system, repetitive presentation of a stimulus results in the reduction of power elicited in the gamma frequency band. However, this reduction does not result in degradation of perception; on the contrary, perception is improved by prior experience with the stimulus. To explain how reduction of gamma frequency oscillations, observed in priming experiments, can lead to improvement in behavior, we assume that visual processing takes place in two distinct stages: representation sharpening in the early visual areas and competitive interaction among representations in the higher visual areas and the prefrontal cortex. Here, we present a network model of spiking neurons that demonstrates how stimulus repetition leads to a decrease in power of the local field potential oscillations in the gamma frequency range in the early layer and also improves network response by reducing the latency to reach a decision in the higher area.

Temporal Sequence of Attentional Modulation in the Lateral Intraparietal Area and Middle Temporal Area during Rapid Covert Shifts of Attention

In the visual system, spatial attention enhances sensory responses to stimuli at attended locations relative to unattended locations. Which brain structures direct the locus of attention, and how is attentional modulation delivered to structures in the visual system? We trained monkeys on an attention-switch task designed to precisely measure the onset of attentional modulation during rapid shifts of spatial attention. Here we show that attentional modulation appears substantially earlier in the lateral intraparietal area (LIP) than in an anatomically connected lower visual area, the middle temporal area. This temporal sequence of attentional latencies demonstrates that endogenous changes of state can occur in higher visual areas before lower visual areas and satisfies a critical prediction of the hypothesis that LIP is a source of top-down attentional signals to early visual cortex.

Neuroplasticity predicts outcome of optic neuritis independent of tissue damage

To determine whether lateral occipital complex (LOC) activation with functional magnetic resonance imaging (fMRI) predicts visual outcome after clinically isolated optic neuritis (ON). To investigate the reasons behind good recovery following ON, despite residual optic nerve demyelination and neuroaxonal damage. Patients with acute ON and healthy volunteers were studied longitudinally over 12 months. Structural MRI, visual evoked potentials (VEPs), and optical coherence tomography (OCT) were used to quantify acute inflammation, demyelination, conduction block, and later to estimate remyelination and neuroaxonal loss over the entire visual pathway. The role of neuroplasticity was investigated using fMRI. Multivariable linear regression analysis was used to study associations between vision, structure, and function. Greater baseline fMRI responses in the LOCs were associated with better visual outcome at 12 months. This was evident on stimulation of either eye (p = 0.007 affected; p = 0.020 fellow eye), and was independent of measures of demyelination and neuroaxonal loss. A negative fMRI response in the LOCs at baseline was associated with a relatively worse visual outcome. No acute electrophysiological or structural measures, in the anterior or posterior visual pathways, were associated with visual outcome. Early neuroplasticity in higher visual areas appears to be an important determinant of recovery from ON, independent of tissue damage in the anterior or posterior visual pathway, including neuroaxonal loss (as measured by MRI, VEP, and OCT) and demyelination (as measured by VEP).

Contrast induced changes in response latency depend on stimulus specificity

Neurones in visual cortex show increasing response latency with decreasing stimulus contrast. Neurophysiological recordings from neurones in inferior temporal cortex (IT) and the superior temporal sulcus (STS), show that the increment in response latency with decreasing stimulus contrast is considerably greater in higher visual areas than that seen in primary visual cortex. This suggests that the majority of the latency change is not retinal or V1 in origin, instead each cortical processing area adds latency at low contrast. I show that, as in earlier visual areas, response latency is more strongly dependent on stimulus contrast than stimulus identity. There is large variation in the extent to which response latency increases with decreasing stimulus contrast. I show that this between cell variability is, at least in part, related to the stimulus specificity of the neurones: the increase in response latency as stimulus contrast decreases is greater for neurones that respond to few stimuli compared to neurones that respond to many stimuli.

Perceptual learning of global pattern motion occurs on the basis of local motion

Enhancement in perceptual learning of a visual stimulus can often be explained either by learning of integrated visual information that is processed in higher visual areas or by learning of component information that is processed in lower visual areas. It is not clear on which visual information perceptual learning is predominantly based. We examined whether perceptual learning of global pattern motion occurs on the basis of local or global motion as a result of performance improvement in detecting contraction (or expansion) in a display in which contracting (or expanding) dots slightly outnumbers expanding (or contracting) dots. We measured the degree of transfer of the learning effect by presenting test stimuli spatially shifted so that the region of the test stimuli partially overlapped the trained region. The results showed that the degree of transfer was entirely dependent on how similar local motion directions in the test stimuli are to those in the trained stimulus in the overlapping area, irrespective of whether a test stimulus contained the same global motion direction as the trained or not. These results indicate that perceptual learning at least in the present setting occurs on the basis of local motion signals.

Basal ganglia and memory retrieval during delayed match-to-sample and non-match-to-sample tasks

Top-down guidance of visual search requires the ability tobias the processing of visual features towards the charac-teristics of the desired object. Whatever form they maytake, these characteristics (that we will call here a templateof the object) have to be transferred from memory to thevisual cortical areas, either from long-term memory orworking memory. High visual areas like the inferotempo-ral cortex, or visuo-mnemonic areas in the medial tempo-ral lobe have been shown to exhibit sustained activitiesduring delayed matching-to-sample (DMS) or delayednon-matching-to-sample (DNMS) tasks, showing theirinvolvement in working memory (WM) processes [1].Particularly, perirhinal cortex (PRh) is involved in objectrecognition, novelty detection and categorization, and itsimpairment leads to severe deficits in DMS and DNMStasks [2].We designed in [3] a computational model of PRh thatwas able to perform multimodal categorization despitepartial object presentation. Its main feature was the incor-poration of dopaminergic modulation of synaptic cur-rents, which allowed the model to exhibit sustainedactivities in clusters of cells representing a given objectunder an optimal level of tonic dopamine (DA) firing. Wealso observed propagation of activity within a cluster,which leads to the interesting property that the visualinformation contained in a cluster can be retrieved troughthe stimulation of a very limited number of cells by tha-lamic afferents. We therefore formulated the hypothesisthat PRh is potential site where visual memory can beretrieved through partial thalamic stimulation in order tobias processing in the ventral stream through feedbackmodulation.Given the fact that PRh receives connections from parts ofthe thalamus that are tonically inhibited by basal ganglia(BG) structures [4], we here suggest that BG can act as con-troller for memory retrieval in PRh, but without any visualdetails about the object to be retrieved. We tested thishypothesis by building a computational model involvingPRh, BG structures, thalamus and a prefrontal cortex(PFC) area that performs static working memory in amanner functionally similar to [5]. We applied this modelto interlaced DMS and DNMS tasks, where one of twoobjects (A or B) is first presented to the system, followedby a task cue indicating whether the system should per-form DMS or DNMS, then both A and B objects. If the sys-tem selects the correct object in PRh, it receives aprobabilistic reward that elicits a phasic DA burst.The model is composed of competing mean firing-rateneurons that interacts through connections havingweights evolve through an homeostatic Hebbian learningrule. Both PRh and PFC areas project on the input struc-ture of BG, the nucleus accumbens (NAcc), which in turnproject to the globus pallidus (GPi) that tonically inhibitsthe thalamus. Selective inhibition of a GPi cell allows itsefferent thalamic cells to exhibit activity and thereforestimulate the corresponding cluster in PRh. The DA cellsslowly learn to predict reward associated to NAcc patterns

Object-based biasing for attentional control of gaze: a comparison of biologically plausible mechanisms

INTRODUCTION In the visual system, attending to important objects in the visual field relies on the transfer of top-down, object-based task information to the spatially organised areas of cortex. How this occurs and the method by which this information can influence the dorsal stream and redirect gaze are not well understood. Current models of the ventral stream mostly focus on the feed-forward mechanisms involved and current feedback models do not seem to address the issue of object-space binding in a comprehensive and plausible manner. METHODS We investigated these questions using the following modeling framework. A bidirectional, ventral stream object recognition hierarchy up to anterior inferior temporal cortex (AIT) from primary visual cortex (V1) and a model of dorsal stream to frontal eye fields (FEF) with our previously developed oculomotor system [1]. Selection is performed in both the object-based mapping of AIT [2] and the spatial mapping of FEF [3] by basal ganglia loops [4]. Modeling of the ventral stream consists of a hierarchy of increasingly spatially invariant cortical areas linked by both feed-forward excitatory and feedback connections. Within each receptive field, there is a competition to represent the strongest and thus most likely representation for that region, which can be biased by the feedback from higher visual areas. Three models of feedback attention mechanism were tested: additive feedback, shunting (multiplicative) feedback and a shunt of feedback by feed-forward. The model was tested using a simple visual world (colored flags) that nevertheless challenged all the main competencies being investigated. Performance was measured by (i) eliciting saccadic behavior in simulated visual search with different numbers of distractors, and (ii) target segmentation in cluttered scenes within a fixed time window. RESULTS In the target segmentation task, the additive feedback model consistently fails to bind the AIT representation of the object to the correct location on the visual field. The shunting model was able to segment 58% of scenes while the gating model was most successful (83%) (Figure 1). We then took the most successful (gating) model and challenged it with a conjunction visual search task. Here, by simulating models trained and naive to the target stimulus, we showed that subsequent learning of a combined representation of an untrained target stimulus can explain the experimentally observed decrease in the slope of reaction time against number of distractors for that target (Figure 2) [5].

The Cortical Site of Visual Suppression by Transcranial Magnetic Stimulation

In visual suppression paradigms, transcranial magnetic stimulation (TMS) applied approximately 90 ms after visual stimulus presentation over occipital visual areas can robustly interfere with visual perception, thereby most likely affecting feedback activity from higher areas (Amassian VE, Cracco RQ, Maccabee PJ, Cracco JB, Rudell A, Eberle L. 1989. Suppression of visual perception by magnetic coil stimulation of human occipital cortex. Electroencephalogr Clin Neurophysiol 74:458-462.). It is speculated that the observed effects might stem primarily from the disruption of V1 activity. This hypothesis, although under debate, argues in favor of a special role of V1 in visual awareness. In this study, we combine TMS, functional magnetic resonance imaging, and calculation of the induced electric field to study the neural correlates of visual suppression. For parafoveal visual stimulation in the lower right half of the visual field, area V2d is shown to be the likely TMS target based on its anatomical location close to the skull surface. Furthermore, isolated stimulation of area V3 also results in robust visual suppression. Notably, V3 stimulation does not directly affect the feedback from higher visual areas that is relayed mainly via V2 to V1. These findings support the view that intact activity patterns in several early visual areas (rather than merely in V1) are likewise important for the perception of the stimulus.

Transcranial flavoprotein fluorescence imaging of mouse cortical activity and plasticity

Endogenous fluorescence signals derived from mitochondria reflect activity-dependent changes in brain metabolism and may be exploited in functional brain imaging. Endogenous flavoprotein fluorescence imaging in mice is especially important because many genetically manipulated strains of mice are available and the transparent skull of mice allows transcranial fluorescence imaging of cortical activities. In the primary sensory areas of mice, cortical activities and experience-dependent plasticity have been investigated using transcranial fluorescence imaging. Furthermore, differential imaging, based on stimulus specificity of cortical areas, distinguished activities in higher visual areas around the primary visual cortex from those in primary visual cortex. The combination of transcranial fluorescence imaging with the suppression of cortical activities using photobleaching of flavoproteins is expected to aid in elucidating the roles of sensory cortices including higher areas in mice.

Selecting and perceiving multiple visual objects

To explain how multiple visual objects are attended and perceived, we propose that our visual system first selects a fixed number of about four objects from a crowded scene based on their spatial information (object individuation) and then encode their details (object identification). We describe the involvement of the inferior intra-parietal sulcus (IPS) in object individuation and the superior IPS and higher visual areas in object identification. Our neural object-file theory synthesizes and extends existing ideas in visual cognition and is supported by behavioral and neuroimaging results. It provides a better understanding of the role of the different parietal areas in encoding visual objects and can explain various forms of capacity-limited processing in visual cognition such as working memory.

Uncertainty reveals surround modulation of shape

Noisy estimations of shape can be partially resolved by incorporating relevant information from the context. The effect of surround stimuli on shape perception becomes clear in illusions of shape contrast and assimilation. In this study, we answer the question how a surround-induced bias depends on the reliability of shape signals. This way, we assess the processes by which an observer incorporates relevant data from the context into the shape estimate. We selectively added visual noise to the center and surround and compared a bias in shape perception with a control condition where no noise was added. In the conditions where shape and surround stimuli were well defined, we found a shape-contrast bias. When the surround stimuli were degraded, this contrast bias decreased. Most interestingly, when the central shape was degraded, an assimilation bias was observed. This bias was larger when the entire stimulus was degraded compared to when only the central shape was degraded. This suggests that shape contrast is the result of inference processes relying on local representations in early visual areas whereas assimilation is related to inference processes by global representations in higher visual areas.

Texture-surround suppression of contour-shape coding in human vision

Contextual influences on neurons in the primary visual cortex have largely been studied using simple visual stimuli and their functional role is still poorly understood. Using a novel visual after-effect of perceived shape we show psychophysically that the coding of a contour's shape is inhibited by nearby parallel, but not orthogonal texture orientations. This suggests that neurons in the visual cortex that are suppressed by parallel orientations feed their outputs into higher visual areas that are involved in the processing of contour shape and in the recognition of objects.

Bayesian reconstruction of perceptual experiences from human brain activity

Event Abstract Back to Event Bayesian reconstruction of perceptual experiences from human brain activity Sensory systems transform stimulus energy measured at the peripheral transducers into explicit representations of various abstract features. These transformations can be viewed as (nonlinear) mappings between the stimuli and brain activity measurements [1]. Most work in sensory neuroscience has focused on development of quantitative encoding models posed in terms of nonlinear mechanisms that filter the stimuli in order to produce appropriate responses. Recent interest in brain-machine interfaces has pushed development of decoding models that aim to classify, identify or reconstruct the stimulus directly from measured brain activity. These models work in the opposite direction, transforming responses into stimuli features. Most decoding models use non-parametric algorithms such as SVM, and are not based on explicit encoding models. We have pioneered an alternative approach in which the decoding algorithm is inferred from one or more explicit encoding models. In a study published last year [2] we showed that this approach can be used to extract far more information from functional MRI measurements than was generally believed possible. In more recent work along these lines, we have developed a new Bayesian decoding model that can reconstruct natural images seen by an observer from measured brain activity. The decoder combines three elements: a structural encoding model that characterizes signals from early visual areas; a semantic encoding model that characterizes signals from higher visual areas; and appropriate priors that incorporate statistical information about the structure and semantics of natural scenes. By combining all these elements the decoder produces reconstructions that accurately reflect the distribution, structure and semantic category of the objects contained in the original image. These results help clarify how distinct representations in different parts of the brain can be combined to provided a coherent reconstruction of the visual world; they also highlight a potentially important role for prior knowledge in visual perception. Our Bayesian decoding model can be generalized directly to permit reconstruction of other perceptual dimensions, such as color and motion. It might also be possible to use this framework to reconstruct subjective perceptual processes such as visual imagery and dreaming. More generally, these results suggest that Bayesian decoding algorithms could form the basis of powerful new brain-reading technologies and brain-computer interfaces. Acknowledgements. The functional MRI scans were conducted with the support of the staff at the Brain Imaging Center at UC Berkeley and at the Veterans Administration in Martinez, CA. This research was supported by the National Eye Institute and by UC Berkeley intramural funds.