Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.

The organization of the human cerebral cortex estimated by intrinsic functional connectivity

Many studies have shown how pigments and internal nanostructures generate color in nature. External surface structures can also influence appearance, such as by causing multiple scattering of light (structural absorption) to produce a velvety, super black appearance. Here we show that feathers from five species of birds of paradise (Aves: Paradisaeidae) structurally absorb incident light to produce extremely low-reflectance, super black plumages. Directional reflectance of these feathers (0.05-0.31%) approaches that of man-made ultra-absorbent materials. SEM, nano-CT, and ray-tracing simulations show that super black feathers have titled arrays of highly modified barbules, which cause more multiple scattering, resulting in more structural absorption, than normal black feathers. Super black feathers have an extreme directional reflectance bias and appear darkest when viewed from the distal direction. We hypothesize that structurally absorbing, super black plumage evolved through sensory bias to enhance the perceived brilliance of adjacent color patches during courtship display.

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Structural absorption by barbule microstructures of super black bird of paradise feathers

The neurons of the human cerebral cortex are arranged in a highly folded sheet, with the majority of the cortical surface area buried in folds. Cortical maps are typically arranged with a topography oriented parallel to the cortical surface. Despite this unambiguous sheetlike geometry, the most commonly used coordinate systems for localizing cortical features are based on 3-D stereotaxic coordinates rather than on position relative to the 2-D cortical sheet. In order to address the need for a more natural surface-based coordinate system for the cortex, we have developed a means for generating an average folding pattern across a large number of individual subjects as a function on the unit sphere and of nonrigidly aligning each individual with the average. This establishes a spherical surface-based coordinate system that is adapted to the folding pattern of each individual subject, allowing for much higher localization accuracy of structural and functional features of the human brain.

/pdf/high-resolution-intersubject-averaging-and-a-coordinate-4nq72z0n9o.pdf

High-resolution intersubject averaging and a coordinate system for the cortical surface.

We present a unified statistical theory for assessing the significance of apparent signal observed in noisy difference images. The results are usable in a wide range of applications, including fMRI, but are discussed with particular reference to PET images which represent changes in cerebral blood flow elicited by a specific cognitive or sensorimotor task. Our main result is an estimate of the P-value for local maxima of Gaussian, t, chi(2) and F fields over search regions of any shape or size in any number of dimensions. This unifies the P-values for large search areas in 2-D (Friston et al. [1991]: J Cereb Blood Flow Metab 11:690-699) large search regions in 3-D (Worsley et al. [1992]: J Cereb Blood Flow Metab 12:900-918) and the usual uncorrected P-value at a single pixel or voxel.

/pdf/a-unified-statistical-approach-for-determining-significant-4cj3zpmgr2.pdf

A unified statistical approach for determining significant signals in images of cerebral activation.

The borders of human visual areas V1, V2, VP, V3, and V4 were precisely and noninvasively determined. Functional magnetic resonance images were recorded during phase-encoded retinal stimulation. This volume data set was then sampled with a cortical surface reconstruction, making it possible to calculate the local visual field sign (mirror image versus non-mirror image representation). This method automatically and objectively outlines area borders because adjacent areas often have the opposite field sign. Cortical magnification factor curves for striate and extrastriate cortical areas were determined, which showed that human visual areas have a greater emphasis on the center-of-gaze than their counterparts in monkeys. Retinotopically organized visual areas in humans extend anteriorly to overlap several areas previously shown to be activated by written words.

https://www.cogsci.ucsd.edu/~sereno/papers/HumanRetin95.pdf

Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging

Statistical dependencies in the responses of sensory neurons govern both the amount of stimulus information conveyed and the means by which downstream neurons can extract it. Although a variety of measurements indicate the existence of such dependencies, their origin and importance for neural coding are poorly understood. Here we analyse the functional significance of correlated firing in a complete population of macaque parasol retinal ganglion cells using a model of multi-neuron spike responses. The model, with parameters fit directly to physiological data, simultaneously captures both the stimulus dependence and detailed spatio-temporal correlations in population responses, and provides two insights into the structure of the neural code. First, neural encoding at the population level is less noisy than one would expect from the variability of individual neurons: spike times are more precise, and can be predicted more accurately when the spiking of neighbouring neurons is taken into account. Second, correlations provide additional sensory information: optimal, model-based decoding that exploits the response correlation structure extracts 20% more information about the visual scene than decoding under the assumption of independence, and preserves 40% more visual information than optimal linear decoding. This model-based approach reveals the role of correlated activity in the retinal coding of visual stimuli, and provides a general framework for understanding the importance of correlated activity in populations of neurons.

/pdf/spatio-temporal-correlations-and-visual-signalling-in-a-2v7dmvcp2i.pdf

Spatio-temporal correlations and visual signalling in a complete neuronal population

/pdf/fmri-of-human-visual-cortex-4hgq3dbxc0.pdf

fMRI of human visual cortex

A white noise technique is presented for estimating the response properties of spiking visual system neurons. The technique is simple, robust, efficient and well suited to simultaneous recordings from multiple neurons. It provides a complete and easily interpretable model of light responses even for neurons that display a common form of response nonlinearity that precludes classical linear systems analysis. A theoretical justification of the technique is presented that relies only on elementary linear algebra and statistics. Implementation is described with examples. The technique and the underlying model of neural responses are validated using recordings from retinal ganglion cells, and in principle are applicable to other neurons. Advantages and disadvantages of the technique relative to classical approaches are discussed.

/pdf/a-simple-white-noise-analysis-of-neuronal-light-responses-a56aehnicm.pdf

A simple white noise analysis of neuronal light responses.

Current understanding of many neural circuits is limited by our ability to explore the vast number of potential interactions between different cells. We present a new approach that dramatically reduces the complexity of this problem. Large-scale multi-electrode recordings were used to measure electrical activity in nearly complete, regularly spaced mosaics of several hundred ON and OFF parasol retinal ganglion cells in macaque monkey retina. Parasol cells exhibited substantial pairwise correlations, as has been observed in other species, indicating functional connectivity. However, pairwise measurements alone are insufficient to determine the prevalence of multi-neuron firing patterns, which would be predicted from widely diverging common inputs and have been hypothesized to convey distinct visual messages to the brain. The number of possible multi-neuron firing patterns is far too large to study exhaustively, but this problem may be circumvented if two simple rules of connectivity can be established: (1) multi-cell firing patterns arise from multiple pairwise interactions, and (2) interactions are limited to adjacent cells in the mosaic. Using maximum entropy methods from statistical mechanics, we show that pairwise and adjacent interactions accurately accounted for the structure and prevalence of multi-neuron firing patterns, explaining ∼98% of the departures from statistical independence in parasol cells and ∼99% of the departures that were reproducible in repeated measurements. This approach provides a way to define limits on the complexity of network interactions and thus may be relevant for probing the function of many neural circuits.

https://www.jneurosci.org/content/jneuro/26/32/8254.full.pdf

The structure of multi-neuron firing patterns in primate retina

Functional asymmetries in the ON and OFF pathways of the primate visual system were examined using simultaneous multi-electrode recordings from dozens of retinal ganglion cells (RGCs) in vitro. Light responses of RGCs were characterized using white noise stimulation. Two distinct functional types of cells frequently encountered, one ON and one OFF, had non-opponent spectral sensitivity, relatively high response gain, transient light responses, and large receptive fields (RFs) that tiled the region of retina recorded, suggesting that they belonged to the same morphological cell class, most likely parasol. Three principal functional asymmetries were observed. (1) Receptive fields of ON cells were 20% larger in diameter than those of OFF cells, resulting in higher full-field sensitivity. (2) ON cells had faster response kinetics than OFF cells, with a 10-20% shorter time to peak, trough and zero crossing in the biphasic temporal impulse response. (3) ON cells had more nearly linear light responses and were capable of signaling decrements, whereas OFF cells had more strongly rectifying responses that provided little information about increments. These findings suggest specific mechanistic asymmetries in retinal ON and OFF circuits and differences in visual performance on the basis of the activity of ON and OFF parasol cells.

https://www.jneurosci.org/content/jneuro/22/7/2737.full.pdf

E. J. Chichilnisky

Papers

Spatio-temporal correlations and visual signalling in a complete neuronal population

fMRI of human visual cortex

A simple white noise analysis of neuronal light responses.

The structure of multi-neuron firing patterns in primate retina

Functional asymmetries in ON and OFF ganglion cells of primate retina