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This is talk 10 of 31 at the Conference on Brain Network Dynamics held at the University of California at Berkeley on January 26-27, 2007. Speaker is David A. Leopold, Unit on Cognitive Neurophysiology and Imaging, National Institute of Mental Health, Bethesda, MD. http://intramural.nimh.nih.gov/research/pi/pi_leopold_d.html . Abstract: The role of the striate cortex (area V1) in shaping our perception of visual patterns and scenes is of fundamental importance in understanding how we see. Visual illusions where a salient stimulus can be temporarily rendered invisible have provided a paradigm by which neuroscientists can isolate neural processes directly involved in perception. This approach has been applied to study electrophysiological activity in monkeys, as well as fMRI activation patterns in humans. Interestingly, the different types of studies have provided divergent results regarding the role of V1 in perceptual processing. Human neuroimaging (fMRI) studies have repeatedly shown that during perceptual suppression there is a marked decrease in the BOLD response in V1. In contrast, single unit studies in monkeys have reported the near absence of such suppression in the firing of individual V1 neurons. Here I will present new data in which we directly compare neurophysiological and fMRI responses during perceptual suppression in monkey area V1. By monitoring the two signals in a variety of conditions within the very same monkeys, we found that the single-unit and BOLD activation specifically ceased to be correlated during periods of perceptual suppression. Slow changes in some bands of the local field potential reflected perception, but only over short time scales. I will discuss how the spatiotemporal pattern of neural events in V1 might contribute to shaping the BOLD response, and will argue that the fMRI signal provides a complementary, rather than incorrect, perspective on neural processing within a cortical area.

Seminar given by Nick Priebe of the University of Texas at Austin to the Redwood Center for Theoretical Neuroscience at UC Berkeley on May 14, 2008. Abstract: Two views of cortical computation have been proposed to account for the selectivity of sensory neurons. In one view, excitatory afferent input provides a rough sketch of the world, which is then refined and sharpened by lateral or feedback inhibition. In the alternative view, excitatory afferent input is sufficient, on its own, to account for sensory selectivity. The debate between these perspectives has in large part been driven by the very real paradox presented by two divergent lines of evidence. On the one hand, many receptive field properties found in visual cortex, such as cross-orientation suppression and contrast-invariant orientation tuning, appear to require lateral inhibition. On the other hand, intracellular recordings have failed to find consistent evidence for lateral inhibition. I will discuss which of these two viewpoints is most appropriate to describe one feature of cortical simple cells, namely, contrast-invariant orientation tuning. A purely linear feed-forward model, incorporating only excitatory input from the thalamus, predicts that the width of orientation tuning in simple cells should broaden with contrast, breaking contrast invariance. Lateral inhibition, in the form of cross-orientation inhibition, is one mechanism that could restore contrast invariance by antagonizing feed-forward excitation at non-preferred orientations. I will demonstrate instead that the predicted broadening is suppressed by three independent mechanisms, none of which appears to require inhibition. First, many simple cells receive only some of their excitatory input from geniculate relay cells, the remainder originating from other cortical neurons with similar preferred orientations. Second, contrast-dependent changes in the trial-to-trial variability of responses lead to contrast-dependent changes in the transformation between membrane potential and spike rate. Third, membrane potential responses of simple cells saturate at lower contrasts than are predicted by a feed-forward model. Thus, the function of lateral inhibition in refining orientation selectivity is accomplished instead by a number of simple, well-defined nonlinearities of visual neurons.

This article is from Neural Systems & Circuits , volume 1 . Abstract Background: The statistical structure of the visual world offers many useful clues for understanding how biological visual systems may understand natural scenes. One particularly important early process in visual object recognition is that of grouping together edges which belong to the same contour. The layout of edges in natural scenes have strong statistical structure. One such statistical property is that edges tend to lie on a common circle, and this 'co-circularity' can predict human performance at contour grouping. We therefore tested the hypothesis that long-range excitatory lateral connections in the primary visual cortex, which are believed to be involved in contour grouping, display a similar co-circular structure. Results: By analyzing data from tree shrews, where information on both lateral connectivity and the overall structure of the orientation map was available, we found a surprising diversity in the relevant statistical structure of the connections. In particular, the extent to which co-circularity was displayed varied significantly. Conclusions: Overall, these data suggest the intriguing possibility that V1 may contain both co-circular and anti-cocircular connections.

This article is from Neural Systems & Circuits , volume 1 . Abstract Background: The statistical structure of the visual world offers many useful clues for understanding how biological visual systems may understand natural scenes. One particularly important early process in visual object recognition is that of grouping together edges which belong to the same contour. The layout of edges in natural scenes have strong statistical structure. One such statistical property is that edges tend to lie on a common circle, and this 'co-circularity' can predict human performance at contour grouping. We therefore tested the hypothesis that long-range excitatory lateral connections in the primary visual cortex, which are believed to be involved in contour grouping, display a similar co-circular structure. Results: By analyzing data from tree shrews, where information on both lateral connectivity and the overall structure of the orientation map was available, we found a surprising diversity in the relevant statistical structure of the connections. In particular, the extent to which co-circularity was displayed varied significantly. Conclusions: Overall, these data suggest the intriguing possibility that V1 may contain both co-circular and anti-cocircular connections.

This article is from Frontiers in Human Neuroscience , volume 8 . Abstract Working memory (WM) is central to human cognition as it allows information to be kept online over brief periods of time and facilitates its usage in cognitive operations (Luck and Vogel, 2013). How this information maintenance actually is implemented is still a matter of debate. Several independent theories of WM, derived, respectively, from behavioral studies and neural considerations, advance the idea that items in WM decay over time and must be periodically reactivated. In this proposal, we show how recent data from intracranial EEG and attention research naturally leads to a simple model of such reactivation in the case of sensory memories. Specifically, in our model the amplitude of high-frequency activity (>50 Hz, in the gamma-band) underlies the representation of items in high-level visual areas. This activity decreases to noise-levels within 500 ms, unless it is reactivated. We propose that top-down attention, which targets multiple sensory items in a cyclical or rhythmic fashion at around 6–10 Hz, reactivates these decaying gamma-band representations. Therefore, working memory capacity is essentially the number of representations that can simultaneously be kept active by a rhythmically sampling attentional spotlight given the known decay rate. Since attention samples at 6–10 Hz, the predicted WM capacity is 3–5 items, in agreement with empirical findings.

This article is from Frontiers in Neuroanatomy , volume 8 . Abstract Calretinin is a calcium-binding protein often used as a marker for a subset of inhibitory interneurons in the mammalian neocortex. We studied the labeled cells in offspring from a cross of a Cre-dependent reporter line with the CR-ires-Cre mice, which express Cre-recombinase in the same pattern as calretinin. We found that in the mature visual cortex, only a minority of the cells that have expressed calretinin and Cre-recombinase during their lifetime is GABAergic and only about 20% are immunoreactive for calretinin. The reason behind this is that calretinin is transiently expressed in many cortical pyramidal neurons during development. To determine whether neurons that express or have expressed calretinin share any distinct functional characteristics, we recorded their visual response properties using GCaMP6s calcium imaging. The average orientation selectivity, size tuning, and temporal and spatial frequency tuning of this group of cells, however, match the response profile of the general neuronal population, revealing the lack of functional specialization for the features studied.

As of 2020 the role of glutathione as a novel neurotransmitter or neuromodulator remains tantalizingly undetermined. See: Multiple Roles of Glutathione in the Nervous System by Christopher Shaw in: Glutathione in the Nervous System edited by Christopher Shaw, 1998 [https://books.google.ca/books?id=7SZhDwAAQBAJ], and Glutathione and Signal Transduction in the Mammalian CNS by Janaky et al., J. Neurochem. 1999 Sep;73(3):889-902.  [Note on name change: In 1994 Stephen Arthur legally changed his name from Stephen Arthur Bowlsby, which is the name cited by Shaw (thesis and Soc. Neurosci. Abstracts 12:75, 1991).] https://en.wikipedia.org/wiki/Glutathione#Potential_neurotransmitters

This article is from PLoS Biology , volume 12 . Abstract Light and electron microscopy of the primary visual cortex of mice indicates that pyramidal neurons connect preferentially to inhibitory neurons.

This article is from PLoS Biology , volume 12 . Abstract Light and electron microscopy of the primary visual cortex of mice indicates that pyramidal neurons connect preferentially to inhibitory neurons.

In recent years, researchers have proposed that the same neural regions responsible for processing sensory information are also recruited to actively store it for short durations (Curtis & D’Esposito, 2003; D’Esposito, 2007; D’Esposito & Postle, 2015; Postle, 2006), a framework known as the sensory recruitment hypothesis (Serences et al., 2009). Supporting evidence comes from multivoxel pattern analysis (MVPA) studies, which have successfully decoded stimulus-specific visual features from activity in the visual cortex, including orientation (Harrison & Tong, 2009; Ester et al., 2015; Pratte & Tong, 2014), colour (Serences et al., 2009), static patterns (Christophel et al., 2012), and motion characteristics like speed and direction (Emrich et al., 2013; Riggall & Postle, 2012). Similar decoding has also been achieved for more complex visual features, such as flow-field motion (Christophel & Haynes, 2014) and saccade goals (Rahmati et al., 2018). These studies support a distributed model of working memory, where sensory areas maintain low-level representations, while associative regions are responsible for higher-order, abstract information (Christophel et al., 2017; Rademaker et al. 2019; Iamshchinina et al. 2021). While these studies demonstrate the role of sensory regions in visual working memory (vWM), they typically rely on simple, non-semantic stimuli to ensure experimental control. However, this approach limits ecological validity. Recent research has shown that vWM performance benefits from visual long-term memory (vLTM), with factors like meaning, familiarity, and expertise enhancing vWM (Brady & Störmer, 2022; Jackson & Raymond, 2008; Xie & Zhang, 2018). These findings suggest that pre-existing vLTM traces play a critical role in the encoding and maintenance of vWM. Yet, studying vWM and vLTM together remains challenging due to the lack of suitable stimuli. Simple visual features used in vWM tasks are not ideal for vLTM studies, while naturalistic images often lack experimental control. This study aims to clarify how pre-existing vLTM traces influence the relationship between vWM and sensory representations. Recent advances in generative neural networks have made it possible to create synthetic, naturalistic images with controlled perceptual variability (Goetschalckx et al., 2021; Son et al., 2022). Using stable diffusion, we developed a custom stimulus set of high-quality, naturalistic images that vary along a perceptual scale while maintaining consistent semantic content (Pettini et al., 2024). To investigate the interaction between vWM and vLTM, we conducted a two-session fMRI experiment. In the first session, participants performed a delayed match-to-sample task. They memorised a complex, naturalistic target image, memorized it for an 8-second delay and then were required to identify it when presented together with a distractor. Task difficulty (easy, medium, hard) was manipulated by varying the level of perceptual similarity between the target and distractor. Repeated and non-repeated targets are included to examine the influence of pre-existing vLTM traces on vWM. Importantly, target and distractor images differ perceptually but retain the same semantic meaning, making them well-suited for a working memory task with naturalistic stimuli. In the second session, participants view the same images while performing a simple orthogonal fixation task. This session provides independent sensory encoding data for the subsequent MVPA analysis. By linking perceptual and memory-related activity, this study addresses how vLTM influences vWM processes in the early visual cortex (V1, V2, V3).

In recent years, researchers have proposed that the same neural regions responsible for processing sensory information are also recruited to actively store it for short durations (Curtis & D’Esposito, 2003; D’Esposito, 2007; D’Esposito & Postle, 2015; Postle, 2006), a framework known as the sensory recruitment hypothesis (Serences et al., 2009). Supporting evidence comes from multivoxel pattern analysis (MVPA) studies, which have successfully decoded stimulus-specific visual features from activity in the visual cortex, including orientation (Harrison & Tong, 2009; Ester et al., 2015; Pratte & Tong, 2014), colour (Serences et al., 2009), static patterns (Christophel et al., 2012), and motion characteristics like speed and direction (Emrich et al., 2013; Riggall & Postle, 2012). Similar decoding has also been achieved for more complex visual features, such as flow-field motion (Christophel & Haynes, 2014) and saccade goals (Rahmati et al., 2018). These studies support a distributed model of working memory, where sensory areas maintain low-level representations, while associative regions are responsible for higher-order, abstract information (Christophel et al., 2017; Rademaker et al. 2019; Iamshchinina et al. 2021). While these studies demonstrate the role of sensory regions in visual working memory (vWM), they typically rely on simple, non-semantic stimuli to ensure experimental control. However, this approach limits ecological validity. Recent research has shown that vWM performance benefits from visual long-term memory (vLTM), with factors like meaning, familiarity, and expertise enhancing vWM (Brady & Störmer, 2022; Jackson & Raymond, 2008; Xie & Zhang, 2018). These findings suggest that pre-existing vLTM traces play a critical role in the encoding and maintenance of vWM. Yet, studying vWM and vLTM together remains challenging due to the lack of suitable stimuli. Simple visual features used in vWM tasks are not ideal for vLTM studies, while naturalistic images often lack experimental control. This study aims to clarify how pre-existing vLTM traces influence the relationship between vWM and sensory representations. Recent advances in generative neural networks have made it possible to create synthetic, naturalistic images with controlled perceptual variability (Goetschalckx et al., 2021; Son et al., 2022). Using stable diffusion, we developed a custom stimulus set of high-quality, naturalistic images that vary along a perceptual scale while maintaining consistent semantic content (Pettini et al., 2024). To investigate the interaction between vWM and vLTM, we conducted a two-session fMRI experiment. In the first session, participants performed a delayed match-to-sample task. They memorised a complex, naturalistic target image, memorized it for an 8-second delay and then were required to identify it when presented together with a distractor. Task difficulty (easy, medium, hard) was manipulated by varying the level of perceptual similarity between the target and distractor. Repeated and non-repeated targets are included to examine the influence of pre-existing vLTM traces on vWM. Importantly, target and distractor images differ perceptually but retain the same semantic meaning, making them well-suited for a working memory task with naturalistic stimuli. In the second session, participants view the same images while performing a simple orthogonal fixation task. This session provides independent sensory encoding data for the subsequent MVPA analysis. By linking perceptual and memory-related activity, this study addresses how vLTM influences vWM processes in the early visual cortex (V1, V2, V3).

In recent years, researchers have proposed that the same neural regions responsible for processing sensory information are also recruited to actively store it for short durations (Curtis & D’Esposito, 2003; D’Esposito, 2007; D’Esposito & Postle, 2015; Postle, 2006), a framework known as the sensory recruitment hypothesis (Serences et al., 2009). Supporting evidence comes from multivoxel pattern analysis (MVPA) studies, which have successfully decoded stimulus-specific visual features from activity in the visual cortex, including orientation (Harrison & Tong, 2009; Ester et al., 2015; Pratte & Tong, 2014), colour (Serences et al., 2009), static patterns (Christophel et al., 2012), and motion characteristics like speed and direction (Emrich et al., 2013; Riggall & Postle, 2012). Similar decoding has also been achieved for more complex visual features, such as flow-field motion (Christophel & Haynes, 2014) and saccade goals (Rahmati et al., 2018). These studies support a distributed model of working memory, where sensory areas maintain low-level representations, while associative regions are responsible for higher-order, abstract information (Christophel et al., 2017; Rademaker et al. 2019; Iamshchinina et al. 2021). While these studies demonstrate the role of sensory regions in visual working memory (vWM), they typically rely on simple, non-semantic stimuli to ensure experimental control. However, this approach limits ecological validity. Recent research has shown that vWM performance benefits from visual long-term memory (vLTM), with factors like meaning, familiarity, and expertise enhancing vWM (Brady & Störmer, 2022; Jackson & Raymond, 2008; Xie & Zhang, 2018). These findings suggest that pre-existing vLTM traces play a critical role in the encoding and maintenance of vWM. Yet, studying vWM and vLTM together remains challenging due to the lack of suitable stimuli. Simple visual features used in vWM tasks are not ideal for vLTM studies, while naturalistic images often lack experimental control. This study aims to clarify how pre-existing vLTM traces influence the relationship between vWM and sensory representations. Recent advances in generative neural networks have made it possible to create synthetic, naturalistic images with controlled perceptual variability (Goetschalckx et al., 2021; Son et al., 2022). Using stable diffusion, we developed a custom stimulus set of high-quality, naturalistic images that vary along a perceptual scale while maintaining consistent semantic content (Pettini et al., 2024). To investigate the interaction between vWM and vLTM, we conducted a two-session fMRI experiment. In the first session, participants performed a delayed match-to-sample task. They memorised a complex, naturalistic target image, memorized it for an 8-second delay and then were required to identify it when presented together with a distractor. Task difficulty (easy, medium, hard) was manipulated by varying the level of perceptual similarity between the target and distractor. Repeated and non-repeated targets are included to examine the influence of pre-existing vLTM traces on vWM. Importantly, target and distractor images differ perceptually but retain the same semantic meaning, making them well-suited for a working memory task with naturalistic stimuli. In the second session, participants view the same images while performing a simple orthogonal fixation task. This session provides independent sensory encoding data for the subsequent MVPA analysis. By linking perceptual and memory-related activity, this study addresses how vLTM influences vWM processes in the early visual cortex (V1, V2, V3).

Development of stimulus selectivity in primary sensory cortex of higher vertebrates is considered in a general mathematical framework. A synaptic evolution scheme of a new kind is proposed in which incoming patterns rather than converging afferents compete. The change in efficacy of a given synapse depends not only on instantaneous pre and postsynaptic activities but also on a slowly varying time-averaged value of the postsynaptic activity. Assuming an appropriate nonlinear form for this dependence, development of selectivity is obtained under quite general conditions on the sensory environment. One does not require nonlinearity of the neuron's integrative power nor does one need to assume any particular form for intracortical circuitry. This is illustrated in simple cases, e.g. when the environment consists of only two different stimuli presented alternately in a random manner. The following formal statement then holds: the state of the system converges with probability 1 to points of maximum selectivity in the state space. We next consider the problem of early development of orientation selectivity and binocular interaction in primary visual cortex. Giving the environment an appropriate form, we obtain orientation tuning curves and ocular dominance comparable to what is observed in normally reared adult cats or monkeys. Simulations with binocular input and various types of normal or altered environments show good agreement with relevant experimental data.

The Exact Histological Localisation of the Visual Area of the Human Cerebral Cortex. Bolton, J Philosophical Transactions of the Royal Society of London. Series B, Containing Papers of a Biological Character (1896-1934). 1900-01-01. 193:165–222

The Exact Histological Localisation of the Visual Area of the Human Cerebral Cortex. Bolton, J Philosophical Transactions of the Royal Society of London. Series B, Containing Papers of a Biological Character (1896-1934). 1900-01-01. 193:165–222

This article is from PLoS ONE , volume 9 . Abstract The mammalian striatum receives inputs from many cortical areas, but the existence of a direct axonal projection from the primary visual cortex (V1) is controversial. In this study we use anterograde and retrograde tracing techniques to demonstrate that V1 directly innervates a topographically defined longitudinal strip of dorsomedial striatum in mice. We find that this projection forms functional excitatory synapses with direct and indirect pathway striatal projection neurons (SPNs) and engages feed-forward inhibition onto these cells. Importantly, stimulation of V1 afferents is sufficient to evoke phasic firing in SPNs. These findings therefore identify a striatal region that is functionally innervated by V1 and suggest that early visual processing may play an important role in striatal-based behaviors.

This article is from PLoS ONE , volume 9 . Abstract The mammalian striatum receives inputs from many cortical areas, but the existence of a direct axonal projection from the primary visual cortex (V1) is controversial. In this study we use anterograde and retrograde tracing techniques to demonstrate that V1 directly innervates a topographically defined longitudinal strip of dorsomedial striatum in mice. We find that this projection forms functional excitatory synapses with direct and indirect pathway striatal projection neurons (SPNs) and engages feed-forward inhibition onto these cells. Importantly, stimulation of V1 afferents is sufficient to evoke phasic firing in SPNs. These findings therefore identify a striatal region that is functionally innervated by V1 and suggest that early visual processing may play an important role in striatal-based behaviors.

Model weights / tensorflow checkpoints for Max F. Burg et al. (2021): Learning Divisive Normalization in Primary Visual Cortex CC0 Waiver

Model weights / tensorflow checkpoints for Max F. Burg et al. (2021): Learning Divisive Normalization in Primary Visual Cortex CC0 Waiver

We propose a theory for ocular dominance (OD) patterns in mammalian primary visual cortex. This theory is based on the premise that OD pattern is an adaptation to minimize the length of intra-cortical wiring. Thus we can understand the existing OD patterns by solving a wire length minimization problem. We divide all the neurons into two classes: left-eye dominated and right-eye dominated. We find that segregation of neurons into monocular regions reduces wire length if the number of connections with the neurons of the same class differs from that with the other class. The shape of the regions depends on the relative fraction of neurons in the two classes. If the numbers are close we find that the optimal OD pattern consists of interdigitating stripes. If one class is less numerous than the other, the optimal OD pattern consists of patches of the first class neurons in the sea of the other class neurons. We predict the transition from stripes to patches when the fraction of neurons dominated by the ipsilateral eye is about 40%. This prediction agrees with the data in macaque and Cebus monkeys. This theory can be applied to other binary cortical systems.

We propose a theory for ocular dominance (OD) patterns in mammalian primary visual cortex. This theory is based on the premise that OD pattern is an adaptation to minimize the length of intra-cortical wiring. Thus we can understand the existing OD patterns by solving a wire length minimization problem. We divide all the neurons into two classes: left-eye dominated and right-eye dominated. We find that segregation of neurons into monocular regions reduces wire length if the number of connections with the neurons of the same class differs from that with the other class. The shape of the regions depends on the relative fraction of neurons in the two classes. If the numbers are close we find that the optimal OD pattern consists of interdigitating stripes. If one class is less numerous than the other, the optimal OD pattern consists of patches of the first class neurons in the sea of the other class neurons. We predict the transition from stripes to patches when the fraction of neurons dominated by the ipsilateral eye is about 40%. This prediction agrees with the data in macaque and Cebus monkeys. This theory can be applied to other binary cortical systems.

In this study we aim at investigating age-related differences in feedback signals in the human brain. We will examine to what extent concurrent contextual information and time-distant mnemonic information can be detected in the feedback signals that arrive at non-stimulated areas of the early visual cortex of younger and older adults. We predict that time-distant mnemonic information, in comparison to concurrent information, contributes less to feedback signals in older than in younger adults. This would be due to age-related differences in reinstating differentiated neural representations of episodic information. We will also test to what extent such patterns in feedback signals are related to neural dedifferentiation in feedforward signals, which is a commonly reported finding in the aging literature.

We compare several ConvNets with different depth and regularization techniques with multi-unit macaque IT cortex recordings and assess the impact of the same on representational similarity with the primate visual cortex. We find that with increasing depth and validation performance, ConvNet features are closer to cortical IT representations.

We compare several ConvNets with different depth and regularization techniques with multi-unit macaque IT cortex recordings and assess the impact of the same on representational similarity with the primate visual cortex. We find that with increasing depth and validation performance, ConvNet features are closer to cortical IT representations.

To evaluate the efficacy of visual cortex continuous and intermittent theta burst transcranial magnetic stimulation (TMS) on visual function

This article is from Frontiers in Aging Neuroscience , volume 5 . Abstract There is considerable interest in understanding food cravings given the obesogenic environment of Western Society. In this paper we examine how the imagery of palatable foods affects cravings and functional connectivity in the visual cortex for people who differ on the power of food scale (PFS). Fourteen older, overweight/obese adults came to our laboratory on two different occasions. Both times they ate a controlled breakfast meal and then were restricted from eating for 2.5 h prior to scanning. On 1 day they consumed a BOOST® liquid meal after the period of food restriction, whereas on the other day they only consumed water (NO BOOST® condition). After these manipulations, they had an fMRI scan in which they were asked to image both neutral objects and their favorite snack foods; they also completed visual analog scales for craving, hunger, and the vividness of the imagery experiences. Irrespective of the BOOST® manipulation, we observed marked increases in food cravings when older, overweight/obese adults created images of favorite foods in their minds as opposed to creating an image of neutral objects; however, the increase in food craving following the imagery of desired food was more pronounced among those scoring high than low on the PFS. Furthermore, local efficiency within the visual cortex when imaging desired food was higher for those scoring high as compared to low on the PFS. The active imagery of desired foods seemed to have overpowered the BOOST® manipulation when evaluating connectivity in the visual cortex.

David Heeger, New York University: "What fMRI Can Tell Us about How Visual Cortex Works" This is the 7th talk given at the Redwood Center for Theoretical Neuroscience Inaugural Symposium UC Berkeley, October 7, 2005

In this project, we will examine the effects of offline continuous theta burst stimulation to dorsolateral prefrontal cortex (dlPFC) on metacognition and the interaction between visual working memory and perception. Continuous theta burst stimulation is a transcranial magnetic stimulation (TMS) protocol whereby 50Hz “bursts” of TMS pulse triplets are delivered to a single cortical site in a continuous chain, with a carrier frequency of 5Hz (i.e. five 50hz triplets per second). Continuous theta burst stimulation has been found to elicit short-term alterations to cortical excitability, functional connectivity, and associated task behaviour, and has been routinely applied to dlPFC and visual areas under both clinical and experimental conditions. We will deliver offline neuronavigated continuous theta burst stimulation (cTBS) to area p9-46v (dlPFC) and primary motor cortex (M1), defined using individualised fMRI data (based on resting-state connectivity), and manual mapping of motor excitability with single-pulse TMS over the scalp, respectively. We will use a multi-featural visual working memory task involving change detection for dot motion stimuli. Subjects must remember the speed, orientation, and dot density of an initial motion pattern (pattern 1), before identifying the perceived orientation of a second motion pattern (pattern 2). Next, subjects are shown two test patterns (pattern 3 and pattern 4) and asked to select which of the two test patterns is the same pattern that they remembered (where the other pattern on each trial has been altered in one of three visual feature dimensions: either speed, orientation, or dot density). We refer to this as a 2-alternative-forced-choice (2AFC) change detection task, which is used to assess working memory precision (for pattern 1) in this study. Here, we first aim to replicate a known motion repulsion effect whereby subjects mis-judge the direction of pattern 2 as being oriented further away (clockwise or anticlockwise) from the true pattern 2 direction, respective to the angular separation of pattern 2 from pattern 1 (Kang et al., 2012, doi: 10.3758/s13423-011-0126-5). For example, if subjects remember motion pattern 1 with orientation 45 degrees, and are subsequently presented with motion pattern 2 with orientation 75 degrees, subjects are likely to mis-judge the perceived orientation of pattern 2 as being greater than 75 degrees. Second, we will also measure subjects’ individual change detection thresholds independently for three motion feature dimensions: speed, orientation, and dot density (which will be independently titrated throughout the experimental task using adaptive staircases to maintain the difficulty of the task at approximately 79% correct performance in the 2AFC change detection task). We will also collect trial-by-trial confidence ratings for the 2AFC change detection task. We will measure the effects of continuous theta burst stimulation (cTBS) to dlPFC on 1) the magnitude of the motion repulsion effect, 2) change detection stimulus thresholds (i.e. change magnitude required to keep subjects at 75% correct in the 2AFC change detection task), and 3) metacognitive performance (correspondence between confidence and accuracy; see details in below sections), by comparing the relevant metrics pre- and post-stimulation, within an experimental session. We will examine the anatomical specificity of the effects by comparing these outcomes across stimulation sites (area p9-46v/dlPFC compared to M1, where M1 will serve as a control stimulation site).

In this project, we will examine the effects of offline continuous theta burst stimulation to dorsolateral prefrontal cortex (dlPFC) on metacognition and the interaction between visual working memory and perception. Continuous theta burst stimulation is a transcranial magnetic stimulation (TMS) protocol whereby 50Hz “bursts” of TMS pulse triplets are delivered to a single cortical site in a continuous chain, with a carrier frequency of 5Hz (i.e. five 50hz triplets per second). Continuous theta burst stimulation has been found to elicit short-term alterations to cortical excitability, functional connectivity, and associated task behaviour, and has been routinely applied to dlPFC and visual areas under both clinical and experimental conditions. We will deliver offline neuronavigated continuous theta burst stimulation (cTBS) to area p9-46v (dlPFC) and primary motor cortex (M1), defined using individualised fMRI data (based on resting-state connectivity), and manual mapping of motor excitability with single-pulse TMS over the scalp, respectively. We will use a multi-featural visual working memory task involving change detection for dot motion stimuli. Subjects must remember the speed, orientation, and dot density of an initial motion pattern (pattern 1), before identifying the perceived orientation of a second motion pattern (pattern 2). Next, subjects are shown two test patterns (pattern 3 and pattern 4) and asked to select which of the two test patterns is the same pattern that they remembered (where the other pattern on each trial has been altered in one of three visual feature dimensions: either speed, orientation, or dot density). We refer to this as a 2-alternative-forced-choice (2AFC) change detection task, which is used to assess working memory precision (for pattern 1) in this study. Here, we first aim to replicate a known motion repulsion effect whereby subjects mis-judge the direction of pattern 2 as being oriented further away (clockwise or anticlockwise) from the true pattern 2 direction, respective to the angular separation of pattern 2 from pattern 1 (Kang et al., 2012, doi: 10.3758/s13423-011-0126-5). For example, if subjects remember motion pattern 1 with orientation 45 degrees, and are subsequently presented with motion pattern 2 with orientation 75 degrees, subjects are likely to mis-judge the perceived orientation of pattern 2 as being greater than 75 degrees. Second, we will also measure subjects’ individual change detection thresholds independently for three motion feature dimensions: speed, orientation, and dot density (which will be independently titrated throughout the experimental task using adaptive staircases to maintain the difficulty of the task at approximately 79% correct performance in the 2AFC change detection task). We will also collect trial-by-trial confidence ratings for the 2AFC change detection task. We will measure the effects of continuous theta burst stimulation (cTBS) to dlPFC on 1) the magnitude of the motion repulsion effect, 2) change detection stimulus thresholds (i.e. change magnitude required to keep subjects at 75% correct in the 2AFC change detection task), and 3) metacognitive performance (correspondence between confidence and accuracy; see details in below sections), by comparing the relevant metrics pre- and post-stimulation, within an experimental session. We will examine the anatomical specificity of the effects by comparing these outcomes across stimulation sites (area p9-46v/dlPFC compared to M1, where M1 will serve as a control stimulation site).

Voluntary allocation of visual attention is controlled by top-down signals generated within the Frontal Eye Fields able to change the excitability of visual areas. However, the mechanism through which this control is achieved remains elusive. Here, we emulated the generation of an attentional signal using single-pulse transcranial magnetic stimulation to activate the Frontal Eye Fields and tracked its consequences over the visual cortex. First, we documented electrophysiological changes of this activation using electroencephalography and found evidence for a phase-reset of oscillatory activity over remote occipital sites at beta frequency. We then probed for perceptual consequences of this top-down triggered phase-reset and found that Frontal Eye Field-activation generates cyclic modulation of visual motion discrimination ability and extrastriate but not primary visual cortex excitability, again at beta frequency. We conclude that top-down signals originating in Frontal Eye Fields causally shape perception by modulating visual cortex activity through mechanisms of oscillatory phase-realignment.

This article is from Frontiers in Neural Circuits , volume 7 . Abstract Two theories have influenced our understanding of cortical development: the integrated network theory, where synaptic development is coordinated across areas; and the cascade theory, where the cortex develops in a wave-like manner from sensory to non-sensory areas. These different views on cortical development raise challenges for current studies aimed at comparing detailed maturation of the connectome among cortical areas. We have taken a different approach to compare synaptic development in rat visual, somatosensory, and frontal cortex by measuring expression of pre-synaptic (synapsin and synaptophysin) proteins that regulate vesicle cycling, and post-synaptic density (PSD-95 and Gephyrin) proteins that anchor excitatory or inhibitory (E-I) receptors. We also compared development of the balances between the pairs of pre- or post-synaptic proteins, and the overall pre- to post-synaptic balance, to address functional maturation and emergence of the E-I balance. We found that development of the individual proteins and the post-synaptic index overlapped among the three cortical areas, but the pre-synaptic index matured later in frontal cortex. Finally, we applied a neuroinformatics approach using principal component analysis and found that three components captured development of the synaptic proteins. The first component accounted for 64% of the variance in protein expression and reflected total protein expression, which overlapped among the three cortical areas. The second component was gephyrin and the E-I balance, it emerged as sequential waves starting in somatosensory, then frontal, and finally visual cortex. The third component was the balance between pre- and post-synaptic proteins, and this followed a different developmental trajectory in somatosensory cortex. Together, these results give the most support to an integrated network of synaptic development, but also highlight more complex patterns of development that vary in timing and end point among the cortical areas.

This article is from Frontiers in Neural Circuits , volume 7 . Abstract Prolonged viewing of high contrast gratings alters perceived stimulus contrast, and produces characteristic changes in the contrast response functions of neurons in the primary visual cortex (V1). This is referred to as contrast adaptation. Although contrast adaptation has been well-studied, its underlying neural mechanisms are not well-understood. Therefore, we investigated contrast adaptation in mouse V1 with the goal of establishing a quantitative description of this phenomenon in a genetically manipulable animal model. One interesting aspect of contrast adaptation that has been observed both perceptually and in single unit studies is its specificity for the spatial and temporal characteristics of the stimulus. Therefore, in the present work we determined if the magnitude of contrast adaptation in mouse V1 neurons was dependent on the spatial frequency and temporal frequency of the adapting grating. We used protocols that were readily comparable with previous studies in cats and primates, and also a novel contrast ramp stimulus that characterized the spatial and temporal specificity of contrast adaptation simultaneously. Similar to previous work in higher mammals, we found that contrast adaptation was strongest when the spatial frequency and temporal frequency of the adapting grating matched the test stimulus. This suggests similar mechanisms underlying contrast adaptation across animal models and indicates that the rapidly advancing genetic tools available in mice could be used to provide insights into this phenomenon.

This article is from PLoS ONE , volume 9 . Abstract Neurofeedback based on real-time functional magnetic resonance imaging (fMRI) is a new approach that allows training of voluntary control over regionally specific brain activity. However, the neural basis of successful neurofeedback learning remains poorly understood. Here, we assessed changes in effective brain connectivity associated with neurofeedback training of visual cortex activity. Using dynamic causal modeling (DCM), we found that training participants to increase visual cortex activity was associated with increased effective connectivity between the visual cortex and the superior parietal lobe. Specifically, participants who learned to control activity in their visual cortex showed increased top-down control of the superior parietal lobe over the visual cortex, and at the same time reduced bottom-up processing. These results are consistent with efficient employment of top-down visual attention and imagery, which were the cognitive strategies used by participants to increase their visual cortex activity.

This article is from BMC Neuroscience , volume 15 . Abstract None

This article is from PLoS ONE , volume 9 . Abstract The lower areas of the hierarchically organized visual cortex are strongly retinotopically organized, with strong responses to specific retinotopic stimuli, and no response to other stimuli outside these preferred regions. Higher areas in the ventral occipitotemporal cortex show a weak eccentricity bias, and are mainly sensitive for object category (e.g., faces versus buildings). This study investigated how the mapping of eccentricity and category sensitivity using functional magnetic resonance imaging is affected by a retinal lesion in two very different low vision patients: a patient with a large central scotoma, affecting central input to the retina (juvenile macular degeneration), and a patient where input to the peripheral retina is lost (retinitis pigmentosa). From the retinal degeneration, we can predict specific losses of retinotopic activation. These predictions were confirmed when comparing stimulus activations with a no-stimulus fixation baseline. At the same time, however, seemingly contradictory patterns of activation, unexpected given the retinal degeneration, were observed when different stimulus conditions were directly compared. These unexpected activations were due to position-specific deactivations, indicating the importance of investigating absolute activation (relative to a no-stimulus baseline) rather than relative activation (comparing different stimulus conditions). Data from two controls, with simulated scotomas that matched the lesions in the two patients also showed that retinotopic mapping results could be explained by a combination of activations at the stimulated locations and deactivations at unstimulated locations. Category sensitivity was preserved in the two patients. In sum, when we take into account the full pattern of activations and deactivations elicited in retinotopic cortex and throughout the ventral object vision pathway in low vision patients, the pattern of (de)activation is consistent with the retinal loss.

This article is from Frontiers in Psychology , volume 5 . Abstract Although several studies have suggested that cortical alterations underlie such age-related visual deficits as decreased acuity, little is known about what changes actually occur in visual cortex during healthy aging. Two recent studies showed changes in primary visual cortex (V1) during normal aging; however, no studies have characterized the effects of aging on visual cortex beyond V1, important measurements both for understanding the aging process and for comparison to changes in age-related diseases. Similarly, there is almost no information about changes in visual cortex in Alzheimer's disease (AD), the most common form of dementia. Because visual deficits are often reported as one of the first symptoms of AD, measurements of such changes in the visual cortex of AD patients might improve our understanding of how the visual system is affected by neurodegeneration as well as aid early detection, accurate diagnosis and timely treatment of AD. Here we use fMRI to first compare the visual field map (VFM) organization and population receptive fields (pRFs) between young adults and healthy aging subjects for occipital VFMs V1, V2, V3, and hV4. Healthy aging subjects do not show major VFM organizational deficits, but do have reduced surface area and increased pRF sizes in the foveal representations of V1, V2, and hV4 relative to healthy young control subjects. These measurements are consistent with behavioral deficits seen in healthy aging. We then demonstrate the feasibility and first characterization of these measurements in two patients with mild AD, which reveal potential changes in visual cortex as part of the pathophysiology of AD. Our data aid in our understanding of the changes in the visual processing pathways in normal aging and provide the foundation for future research into earlier and more definitive detection of AD.

Humans and other primates are capable of learning to recognize new visual stimuli throughout their lifetimes. Most theoretical models assume that such learning occurs through the adjustment of the large number of synaptic weights connecting the visual cortex to downstream decision-making areas. While this approach to learning can optimize performance on behavioral tasks, it can also be costly in terms of time and energy. An alternative hypothesis is that the brain favors simpler learning rules that do not necessarily optimize the readout of information from visual cortical neurons. Here we have examined these hypotheses by reversibly inactivating visual area V4 in non-human primates at different stages of training on form discrimination tasks. We find that V4 inactivation generally has a behavioral effect for only a subset of the stimuli that are encoded in the V4 population activity, specifically those that can be represented efficiently in the population firing rate. As a result, there neural measures of discriminability do not necessarily predict the causal contribution of V4 neurons to task performance. This pattern of results can be explained by incorporating a strong inductive bias for simpler perceptual readouts into existing theoretical frameworks. Such a simplicity bias is suboptimal in the sense that it ignores information that could theoretically be extracted from the neural population, but it has the likely advantage of facilitating efficient learning on ecologically-relevant timescales.

This is talk 19 (of 31) at the Conference on Brain Network Dynamics held at the University of California at Berkeley on January 26-27, 2007. Speaker is Friedrich T. Sommer, from the Redwood Center for Theoretical Neuroscience, University of California Helen Wills Neuroscience Institute, Berkeley, CA. http://redwood.berkeley.edu/wiki/Fritz_Sommer Abstract: Visually evoked changes in retinal firing rate convey information downstream to the thalamus and to cortex. It is widely held that retinal spike trains code information about the visual stimulus solely by a process that depends on how reproducibly firing rates lock to stimulus onset, that is, by stimulus-locked coding. Yet retinal firing patterns are not only influenced by external stimuli but also by dynamics of intrinsic neuronal networks. In fact, work in other systems suggests that information can be encoded by stimulus-induced changes in ongoing oscillatory activity. Thus it is natural to ask if the early visual system processes sensory information not only by means of stimulus-locked coding but also by a mechanism that compares spike timing to intrinsic activity. To address this question we used whole-cell recording in vivo to record retinal EPSPs and the spikes they evoke from relay cells in the lateral geniculate nucleus of the thalamus in response to naturalistic stimuli. Using information theory to interpret the results, we found that visual information can indeed be transmitted by two separate channels. The first channel transmits stimulus locked information about patterns within the receptive field and is limited to relaying visual signals slower than 30 Hz. The second, novel, channel uses spike timing relative to intrinsic retinal oscillations at fine temporal scales, corresponding to the gamma band (50-70 Hz). Remarkably, the amount of information in the second channel could match or even exceed that conveyed by the first, a result that we were able to reproduce in a simple model of a relay cell. Because retinal oscillations involve large-scale networks, the novel channel could convey distributed, contextual aspects of the stimulus that complement stimulus-locked information about local features.

We describe a quantitative theory to account for the computations performed by the feedforward path of the ventral stream of visual cortex and the local circuits implementing them. We show that a model instantiating the theory is capable of performing recognition on datasets of complex images at the level of human observers in rapid categorization tasks. We also show that the theory is consistent with (and in some case has predicted) several properties of neurons in V1, V4, IT and PFC. The theory seems sufficiently comprehensive, detailed and satisfactory to represent an interesting challenge for physiologists and modelers: either disprove its basic features or propose alternative theories of equivalent scope. The theory suggests a number of open questions for visual physiology and psychophysics.

This report describes working hardware and software developed to realize large-scale Brain-State-in-a-Box (BSB) models on a workstation with hardware acceleration using a Field Programmable Gate Array (FPGA). Just one Xilinx XC2VP70 FPGA was able to support about 600 128-dimensional BSB models to run at 10ms reaction time. Software was developed that controls the hardware operations and sends/receives data through publish/subscribe routines provided by an open-source package. Next, the confabulation based knowledge base training function on the Cell Broadband Engine (CBE) was implemented. The workload of the training function was distributed to 6 Synergistic Processing Elements (SPEs) in the Cell processor. Dynamic memory management techniques were developed to enable the SPE to load and write back information from/to the main memory during the training process. Preliminary software profiling was performed to indicate the performance bottleneck and guide the software optimization. The Cell-based implementation achieved 4X9X speedups comparing to traditional processors.

This report describes working hardware and software developed to realize large-scale Brain-State-in-a-Box (BSB) models on a workstation with hardware acceleration using a Field Programmable Gate Array (FPGA). Just one Xilinx XC2VP70 FPGA was able to support about 600 128-dimensional BSB models to run at 10ms reaction time. Software was developed that controls the hardware operations and sends/receives data through publish/subscribe routines provided by an open-source package. Next, the confabulation based knowledge base training function on the Cell Broadband Engine (CBE) was implemented. The workload of the training function was distributed to 6 Synergistic Processing Elements (SPEs) in the Cell processor. Dynamic memory management techniques were developed to enable the SPE to load and write back information from/to the main memory during the training process. Preliminary software profiling was performed to indicate the performance bottleneck and guide the software optimization. The Cell-based implementation achieved 4X9X speedups comparing to traditional processors.

This article is from Brain , volume 136 . Abstract Visual motion perception is fundamental to many aspects of visual perception. Visual motion perception has long been associated with the dorsal (parietal) pathway and the involvement of the ventral ‘form’ (temporal) visual pathway has not been considered critical for normal motion perception. Here, we evaluated this view by examining whether circumscribed damage to ventral visual cortex impaired motion perception. The perception of motion in basic, non-form tasks (motion coherence and motion detection) and complex structure-from-motion, for a wide range of motion speeds, all centrally displayed, was assessed in five patients with a circumscribed lesion to either the right or left ventral visual pathway. Patients with a right, but not with a left, ventral visual lesion displayed widespread impairments in central motion perception even for non-form motion, for both slow and for fast speeds, and this held true independent of the integrity of areas MT/V5, V3A or parietal regions. In contrast with the traditional view in which only the dorsal visual stream is critical for motion perception, these novel findings implicate a more distributed circuit in which the integrity of the right ventral visual pathway is also necessary even for the perception of non-form motion.

Dataset for PLoS Biology publication

This article is from Frontiers in Human Neuroscience , volume 7 . Abstract The relationship between blood oxygenation level dependent-functional magnetic resonance imaging (BOLD-fMRI) and magnetoencephalography (MEG) metrics were explored using low-level visual stimuli known to elicit a rich variety of neural responses. Stimuli were either perceptually isoluminant red/green or luminance-modulated black/yellow square-wave gratings with spatial frequencies of 0.5, 3, and 6 cycles per degree. Neural responses were measured with BOLD-fMRI (3-tesla) and whole head MEG. For all stimuli, the BOLD response showed bilateral activation of early visual cortex that was greater in the contralateral hemisphere. There was variation between individuals but weak, or no evidence, of amplitude dependence on either spatial frequency or the presence of luminance contrast. In contrast, beamformer analysis of MEG data showed activation in contralateral early visual cortex and revealed: (i) evoked responses with stimulus-dependent amplitude and latency; (ii) gamma and high-beta oscillations, with spatial frequency dependent peaks at approximately 30 and 50 Hz, but only for luminance-modulated gratings; (iii) The gamma and beta oscillations appeared to show different spatial frequency tuning profiles; (iv) much weaker gamma and beta responses, and at higher oscillation frequencies, for isoluminant compared to luminance-modulated gratings. The results provide further evidence that the relationship between the fMRI-BOLD response and cortical neural activity is complex, with BOLD-fMRI being insensitive to substantial changes in neural activity. All stimuli were clearly visible to participants and so the paucity of gamma oscillations to isoluminant stimuli is inconsistent with theories of their role in conscious visual perception.

This article is from Frontiers in Human Neuroscience , volume 8 . Abstract Recent research suggests that the medial temporal lobe (MTL) is involved in perception as well as in declarative memory. Amnesic patients with focal MTL lesions and semantic dementia patients showed perceptual deficits when discriminating faces and objects. Interestingly, these two patient groups showed different profiles of impairment for familiar and unfamiliar stimuli. For MTL amnesics, the use of familiar relative to unfamiliar stimuli improved discrimination performance. By contrast, patients with semantic dementia—a neurodegenerative condition associated with anterolateral temporal lobe damage—showed no such facilitation from familiar stimuli. Given that the two patient groups had highly overlapping patterns of damage to the perirhinal cortex, hippocampus, and temporal pole, the neuroanatomical substrates underlying their performance discrepancy were unclear. Here, we addressed this question with a multivariate reanalysis of the data presented by Barense et al. (2011), using functional connectivity to examine how stimulus familiarity affected the broader networks with which the perirhinal cortex, hippocampus, and temporal poles interact. In this study, healthy participants were scanned while they performed an odd-one-out perceptual task involving familiar and novel faces or objects. Seed-based analyses revealed that functional connectivity of the right perirhinal cortex and right anterior hippocampus was modulated by the degree of stimulus familiarity. For familiar relative to unfamiliar faces and objects, both right perirhinal cortex and right anterior hippocampus showed enhanced functional correlations with anterior/lateral temporal cortex, temporal pole, and medial/lateral parietal cortex. These findings suggest that in order to benefit from stimulus familiarity, it is necessary to engage not only the perirhinal cortex and hippocampus, but also a network of regions known to represent semantic information.

This article is from Frontiers in Psychology , volume 4 . Abstract Humans are remarkably proficient at categorizing visually-similar objects. To better understand the cortical basis of this categorization process, we used magnetoencephalography (MEG) to record neural activity while participants learned–with feedback–to discriminate two highly-similar, novel visual categories. We hypothesized that although prefrontal regions would mediate early category learning, this role would diminish with increasing category familiarity and that regions within the ventral visual pathway would come to play a more prominent role in encoding category-relevant information as learning progressed. Early in learning we observed some degree of categorical discriminability and predictability in both prefrontal cortex and the ventral visual pathway. Predictability improved significantly above chance in the ventral visual pathway over the course of learning with the left inferior temporal and fusiform gyri showing the greatest improvement in predictability between 150 and 250 ms (M200) during category learning. In contrast, there was no comparable increase in discriminability in prefrontal cortex with the only significant post-learning effect being a decrease in predictability in the inferior frontal gyrus between 250 and 350 ms (M300). Thus, the ventral visual pathway appears to encode learned visual categories over the long term. At the same time these results add to our understanding of the cortical origins of previously reported signature temporal components associated with perceptual learning.

This article is from BMC Neuroscience , volume 14 . Abstract Background: Individuals suffering from vision loss of a peripheral origin may learn to understand spoken language at a rate of up to about 22 syllables (syl) per second - exceeding by far the maximum performance level of normal-sighted listeners (ca. 8 syl/s). To further elucidate the brain mechanisms underlying this extraordinary skill, functional magnetic resonance imaging (fMRI) was performed in blind subjects of varying ultra-fast speech comprehension capabilities and sighted individuals while listening to sentence utterances of a moderately fast (8 syl/s) or ultra-fast (16 syl/s) syllabic rate. Results: Besides left inferior frontal gyrus (IFG), bilateral posterior superior temporal sulcus (pSTS) and left supplementary motor area (SMA), blind people highly proficient in ultra-fast speech perception showed significant hemodynamic activation of right-hemispheric primary visual cortex (V1), contralateral fusiform gyrus (FG), and bilateral pulvinar (Pv). Conclusions: Presumably, FG supports the left-hemispheric perisylvian “language network”, i.e., IFG and superior temporal lobe, during the (segmental) sequencing of verbal utterances whereas the collaboration of bilateral pulvinar, right auditory cortex, and ipsilateral V1 implements a signal-driven timing mechanism related to syllabic (suprasegmental) modulation of the speech signal. These data structures, conveyed via left SMA to the perisylvian “language zones”, might facilitate – under time-critical conditions – the consolidation of linguistic information at the level of verbal working memory.

In the early visual cortex, information is processed within functional maps whose layout is thought to underlie visual perception. However, the precise organization of these functional maps as well as their interrelationships remains unresolved. Here, we show that spatial frequency representation in cat areas 17 and 18 exhibits singularities around which the map organizes like an electric dipole potential. These singularities are precisely co-located with singularities of the orientation map: the pinwheel centers. We first show, using high resolution optical imaging, that a large majority (around 80%) of pinwheel centers exhibit in their neighborhood semi-global extrema in the spatial frequency map. These extrema created a sharp gradient that was confirmed with electrophysiological recordings. Based on an analogy with electromagnetism, a mathematical model of a dipolar structure is proposed, that was accurately fitted to optical imaging data for two third of pinwheel centers with semi-global extrema. We conclude that more than half of orientation pinwheel centers form spatial frequency dipoles in cat early visual cortex. Given the functional specificities of neurons at singularities in the visual cortex, it is argued that the dipolar organization of spatial frequency around pinwheel centers could be fundamental for visual processing.

This article is from Nature Communications , volume 5 . Abstract Propagating waves occur in many excitable media and were recently found in neural systems from retina to neocortex. While propagating waves are clearly present under anaesthesia, whether they also appear during awake and conscious states remains unclear. One possibility is that these waves are systematically missed in trial-averaged data, due to variability. Here we present a method for detecting propagating waves in noisy multichannel recordings. Applying this method to single-trial voltage-sensitive dye imaging data, we show that the stimulus-evoked population response in primary visual cortex of the awake monkey propagates as a travelling wave, with consistent dynamics across trials. A network model suggests that this reliability is the hallmark of the horizontal fibre network of superficial cortical layers. Propagating waves with similar properties occur independently in secondary visual cortex, but maintain precise phase relations with the waves in primary visual cortex. These results show that, in response to a visual stimulus, propagating waves are systematically evoked in several visual areas, generating a consistent spatiotemporal frame for further neuronal interactions.

This article is from Frontiers in Human Neuroscience , volume 8 . Abstract Brain reorganization associated with altered sensory experience clarifies the critical role of neuroplasticity in development. An example is enhanced peripheral visual processing associated with congenital deafness, but the neural systems supporting this have not been fully characterized. A gap in our understanding of deafness-enhanced peripheral vision is the contribution of primary auditory cortex. Previous studies of auditory cortex that use anatomical normalization across participants were limited by inter-subject variability of Heschl's gyrus. In addition to reorganized auditory cortex (cross-modal plasticity), a second gap in our understanding is the contribution of altered modality-specific cortices (visual intramodal plasticity in this case), as well as supramodal and multisensory cortices, especially when target detection is required across contrasts. Here we address these gaps by comparing fMRI signal change for peripheral vs. perifoveal visual stimulation (11–15° vs. 2–7°) in congenitally deaf and hearing participants in a blocked experimental design with two analytical approaches: a Heschl's gyrus region of interest analysis and a whole brain analysis. Our results using individually-defined primary auditory cortex (Heschl's gyrus) indicate that fMRI signal change for more peripheral stimuli was greater than perifoveal in deaf but not in hearing participants. Whole-brain analyses revealed differences between deaf and hearing participants for peripheral vs. perifoveal visual processing in extrastriate visual cortex including primary auditory cortex, MT+/V5, superior-temporal auditory, and multisensory and/or supramodal regions, such as posterior parietal cortex (PPC), frontal eye fields, anterior cingulate, and supplementary eye fields. Overall, these data demonstrate the contribution of neuroplasticity in multiple systems including primary auditory cortex, supramodal, and multisensory regions, to altered visual processing in congenitally deaf adults.