Visual backward masking: Modeling spatial and temporal aspects

In modeling visual backward masking, the focus has been on temporal effects. More specifically, an explanation has been sought as to why strongest masking can occur when the mask is delayed with respect to the target. Although interesting effects of the spatial layout of the mask have been found, only a few attempts have been made to model these phenomena. Here, we elaborate a structurally simple model which employs lateral excitation and inhibition together with different neural time scales to explain many spatial and temporal aspects of backward masking. We argue that for better understanding of visual masking, it is vitally important to consider the interplay of spatial and temporal factors together in one single model

Visual backward masking: Modeling spatial and temporal aspects

In modeling visual backward masking, the focus has been on temporal effects. More specifically, an explanation has been sought as to why strongest masking can occur when the mask is delayed with respect to the target. Although interesting effects of the spatial layout of the mask have been found, only a few attempts have been made to model these phenomena. Here, we elaborate a structurally simple model which employs lateral excitation and inhibition together with different neural time scales to explain many spatial and temporal aspects of backward masking. We argue that for better understanding of visual masking, it is vitally important to consider the interplay of spatial and temporal factors together in one single model

A population gain control model of spatiotemporal responses in the visual cortex

textThe mammalian brain is a complex computing system that contains billions of neurons and trillions of connections. Is there a general principle that governs the processing in such large neural populations? This dissertation attempts to address this question using computational modeling and quantitative analysis of direct physiological measurements of large neural populations in the monkey primary visual cortex (V1). First, the complete spatiotemporal dynamics of V1 responses over the entire region that is activated by small stationary stimuli are characterized quantitatively. The dynamics of the responses are found to be systematic but complex. Importantly, they are inconsistent with many popular computational models of neural processing. Second, a simple population gain control (PGC) model that can account for these complex response properties is proposed for the small stationary stimuli. The PGC model is then used to predict the responses to stimuli composed of two elements and stimuli that move at a constant speed. The predictions of the model are consistent with the measured responses in V1 for both stimuli. PGC is the first model that can account for the complete spatiotemporal dynamics of V1 population responses for different types of stimuli, suggesting that gain control is a general mechanism of neural processing.Computer Science

Spatial processing of conspecific signals in weakly electric fish: from sensory image to neural population coding

In this dissertation, I examine how an animal’s nervous system encodes spatially realistic conspecific signals in their environment and how the encoding mechanisms support behavioral sensitivity. I begin by modeling changes in the electrosensory signals exchanged by weakly electric fish in a social context. During this behavior, I estimate how the spatial structure of conspecific stimuli influences sensory responses at the electroreceptive periphery. I then quantify how space is represented in the hindbrain, specifically in the primary sensory area called the electrosensory lateral line lobe. I show that behavioral sensitivity is influenced by the heterogeneous properties of the pyramidal cell population. I further demonstrate that this heterogeneity serves to start segregating spatial and temporal information early in the sensory pathway. Lastly, I characterize the accuracy of spatial coding in this network and predict the role of network elements, such as correlated noise and feedback, in shaping the spatial information. My research provides a comprehensive understanding of spatial coding in the first stages of sensory processing in this system and allows us to better understand how network dynamics shape coding accuracy

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Neural assemblies as core elements for modeling neural networks in the brain

How does the brain process and memorize information? We all know that the neuron (also known as nerve cell) is the processing unit in the brain. But how do neurons work together in networks? The connectivity structure of neural networks plays an important role in information processing. Therefore, it is worthwhile to investigate modeling of neural networks. Experiments extract different kinds of datasets (ranging from pair-wise connectivity to membrane potential of individual neurons) and provide an understanding of neuronal activity. However, due to technical limitations of experiments, and complexity and variety of neural architectures, the experimental datasets do not yield a model of neural networks on their own. Roughly speaking, the experimental datasets are not enough for modeling neural networks. Therefore, in addition to these datasets, we have to utilize assumptions, hand-tuned features, parameter tuning and heuristic methods for modeling networks. In this thesis, we present different models of neural networks that are able to produce several behaviors observed in mammalian brain and cell cultures, e.g., up-state/down-state oscillations, different stimulus-evoked responses of cortical layers, activity propagation with tunable speed and several activity patterns of mice barrel cortex. An element which is embedded in all of these models is a network feature called neural assembly. A neural assembly is a group (also called population) of neurons with dense recurrent connectivity and strong internal synaptic weights. We study the dynamics of neural assemblies using analytical approaches and computer simulations. We show that network models containing assemblies exhibit dynamics similar to activity observed in the brain

Distilling the neural correlates of conscious somatosensory perception

The ability to consciously perceive the world profoundly defines our lives as human beings. Somehow, our brains process information in a way that allows us to become aware of the images, sounds, touches, smells, and tastes surrounding us. Yet our understanding of the neurobiological processes that generate perceptual awareness is very limited. One of the most contested questions in the neuroscientific study of conscious perception is whether awareness arises from the activity of early sensory brain regions, or instead requires later processing in widespread supramodal networks. It has been suggested that the conflicting evidence supporting these two perspectives may be the result of methodological confounds in classical experimental tasks. In order to infer participants’ perceptual awareness in these tasks, they need to report the contents of their perception. This means that the neural signals underlying the emergence of perceptual awareness often cannot be dissociated from pre- and postperceptual processes. Consequently, some of the previously observed effects may not be correlates of awareness after all but instead may have resulted from task requirements. In this thesis, I investigate this possibility in the somatosensory modality. To scrutinise the task dependence of the neural correlates of somatosensory awareness, I developed an experimental paradigm that controls for the most common experimental confounds. In a somatosensory-visual matching task, participants were required to detect electrical target stimuli at ten different intensity levels. Instead of reporting their perception directly, they compared their somatosensory percepts to simultaneously presented visual cues that signalled stimulus presence or absence and then reported a match or mismatch accordingly. As a result, target detection was decorrelated from working memory and reports, the behavioural relevance of detected and undetected stimuli was equated, the influence of attentional processes was mitigated, and perceptual uncertainty was varied in a controlled manner. Results from a functional magnetic resonance imaging (fMRI) study and an electroencephalography (EEG) study showed that, when controlled for task demands, the neural correlates of somatosensory awareness were restricted to relatively early activity (~150 ms) in secondary somatosensory regions. In contrast, late activity (>300 ms) indicative of processing in frontoparietal networks occurred irrespective of stimulus awareness, and activity in anterior insular, anterior cingulate, and supplementary motor cortex was associated with processing perceptual uncertainty and reports. These results add novel evidence to the early-local vs. late-global debate and favour the view that perceptual awareness emerges at the level of modality-specific sensory cortices.Die Fähigkeit zur bewussten Wahrnehmung bestimmt maßgeblich unser Selbstbild als Menschen. Unser Gehirn verarbeitet Informationen auf eine Weise, die es uns ermöglicht, uns der Bilder, Töne, Berührungen, Gerüche und Geschmäcker, die uns umgeben, bewusst zu werden. Unser Verständnis davon, wie neurobiologische Prozesse diese bewusste Wahrnehmung erzeugen, ist jedoch noch sehr begrenzt. Eine der umstrittensten Fragen in der neurowissenschaftlichen Erforschung des perzeptuellen Bewusstseins besteht darin, ob die bewusste Wahrnehmung aus der Aktivität früher sensorischer Hirnregionen entsteht, oder aber die spätere Prozessierung in ausgedehnten supramodalen Netzwerken erfordert. Eine mögliche Erklärung für die widersprüchlichen Ergebnisse, die diesen beiden Perspektiven zugrunde liegen, wird in methodologischen Störfaktoren vermutet, die in klassischen experimentellen Paradigmen auftreten können. Um auf die Wahrnehmung der Versuchspersonen schließen zu können, müssen diese den Inhalt ihrer Wahrnehmung berichten. Das führt dazu, dass neuronale Korrelate bewusster Wahrnehmung häufig nicht sauber von prä- und postperzeptuellen Prozessen getrennt werden können. Folglich könnten einige der zuvor beobachteten Effekte, anstatt tatsächlich bewusste Wahrnehmung widerzuspiegeln, aus den Anforderungen experimenteller Paradigmen entstanden sein. In dieser Arbeit untersuche ich diese Möglichkeit in der somatosensorischen Modalität. Um zu überprüfen, inwiefern neuronale Korrelate bewusster somatosensorischer Wahrnehmung von den Anforderungen experimenteller Aufgaben abhängen, habe ich ein Paradigma entwickelt, dass die häufigsten experimentellen Störfaktoren kontrolliert. In einer somatosensorisch-visuellen Vergleichsaufgabe mussten die Versuchspersonen elektrische Zielreize in zehn verschiedenen Intensitätsstufen detektieren. Anstatt diese jedoch direkt zu berichten, sollten sie ihre somatosensorischen Perzepte mit gleichzeitig präsentierten visuellen Symbolen vergleichen, die entweder Reizanwesenheit oder -abwesenheit signalisierten. Entsprechend wurde dann eine Übereinstimmung oder Nichtübereinstimmung berichtet. Dadurch wurde die Reizwahrnehmung von Arbeitsgedächtnis und Berichterstattung dekorreliert, die Verhaltensrelevanz detektierter und nicht detektierter Reize gleichgesetzt, der Einfluss von Aufmerksamkeitsprozessen reduziert und die mit der Detektion verbundene Unsicherheit auf kontrollierte Weise variiert. Die Ergebnisse aus einer funktionellen Magnetresonanztomographie (fMRT)-Studie und einer Elektroenzephalographie (EEG)-Studie zeigen, dass die neuronalen Korrelate bewusster somatosensorischer Wahrnehmung auf relativ frühe Aktivität (~150 ms) in sekundären somatosensorischen Regionen beschränkt sind, wenn experimentelle Störfaktoren kontrolliert werden. Im Gegensatz dazu trat späte Aktivität (>300 ms), die auf die Verarbeitung in frontoparietalen Netzwerken hindeutet, unabhängig von der Reizwahrnehmung auf, und Aktivität im anterioren insulären, anterioren cingulären und supplementär-motorischen Kortex war mit der Verarbeitung von Detektionsunsicherheit und der Berichterstattung verbunden. Diese Ergebnisse liefern neue Erkenntnisse zur Debatte um die Relevanz früher, lokaler vs. später, globaler Hirnaktivität und unterstützen die Ansicht, dass perzeptuelles Bewusstsein in modalitätsspezifischen sensorischen Kortizes entsteht

From Face Perception to Individual Recognition: The Missing Link

Recognizing other individuals is a key social aspect of our everyday lives. To recognize a familiar individual, we must establish a link between sensory inputs and a representation of that individual held in memory. In primates, faces play a particularly important role on the sensory side of this process, which is reflected in an extensive network of face-selective areas along the inferior temporal lobe. However, where and how memory is re-activated during face perception remains unclear. Using functional magnetic resonance imaging (fMRI), we measured whole brain activity in macaques while they were watching pictures of other monkey faces that were either long-term acquaintances, visually familiar, or totally unfamiliar. In comparison to unfamiliar faces, the entire face-processing network showed increased activity in response to familiar faces of long-time personal acquaintances. In contrast, faces that were only visually familiar elicited less activity than totally unfamiliar faces in most face-selective areas. The face-processing network thus distinguished personally familiar faces from visually familiar faces. Personally familiar faces also prompted the activation of two previously unknown face-selective areas in the temporal lobe. One area was located in the perirhinal cortex (PR), which has been associated with declarative memory, and the other area was embedded in the temporal pole (TP), a region previously associated with social knowledge. These two novel face areas showed a non-linear response as blurred faces became gradually visible, rapidly becoming active when the faces of personal acquaintances became recognizable. Thus, mimicking the perception of a face approaching us, this paradigm revealed a neural correlate of the ‘aha!’ recognition moment in face areas TP and PR. As a first step towards advancing our understanding of the neuronal processing of individual recognition, our fMRI experiments identified two novel face areas specifically involved in recognizing familiar faces. However, the hemodynamic response cannot directly assess neurophysiological properties. Using fMRI-guided electrophysiology, we investigated the responses of neurons within the novel face area TP in awake monkeys, and we provided the first systematic evidence of cells selective for familiar faces. A high fraction of neurons in face area TP were selective for familiar monkey faces, and unfamiliar faces that were physically similar failed to elicit the same neural responses. Importantly, neurons in face area AM, which is thought to compute facial identity at the top of the face perception hierarchy, were not modulated by familiarity. Within TP, neurons also responded to monkey bodies, and to monkey vocalizations. Maximum activity was elicited by the joint observation of faces and bodies, and audiovisual interactions were evident in some TP neurons. Together, these results reveal neuronal processes underlying memory re-activation during face perception and generate hypotheses for testing how individual recognition is achieved through different modalities, thus advancing our understanding into how unique representations of familiar individuals are developed at the neural level

Visual Cortex

The neurosciences have experienced tremendous and wonderful progress in many areas, and the spectrum encompassing the neurosciences is expansive. Suffice it to mention a few classical fields: electrophysiology, genetics, physics, computer sciences, and more recently, social and marketing neurosciences. Of course, this large growth resulted in the production of many books. Perhaps the visual system and the visual cortex were in the vanguard because most animals do not produce their own light and offer thus the invaluable advantage of allowing investigators to conduct experiments in full control of the stimulus. In addition, the fascinating evolution of scientific techniques, the immense productivity of recent research, and the ensuing literature make it virtually impossible to publish in a single volume all worthwhile work accomplished throughout the scientific world. The days when a single individual, as Diderot, could undertake the production of an encyclopedia are gone forever. Indeed most approaches to studying the nervous system are valid and neuroscientists produce an almost astronomical number of interesting data accompanied by extremely worthy hypotheses which in turn generate new ventures in search of brain functions. Yet, it is fully justified to make an encore and to publish a book dedicated to visual cortex and beyond. Many reasons validate a book assembling chapters written by active researchers. Each has the opportunity to bind together data and explore original ideas whose fate will not fall into the hands of uncompromising reviewers of traditional journals. This book focuses on the cerebral cortex with a large emphasis on vision. Yet it offers the reader diverse approaches employed to investigate the brain, for instance, computer simulation, cellular responses, or rivalry between various targets and goal directed actions. This volume thus covers a large spectrum of research even though it is impossible to include all topics in the extremely diverse field of neurosciences