Dissociable laminar profiles of concurrent bottom-up and top-down modulation in the human visual cortex

AbstractRecent developments in human neuroimaging make it possible to non-invasively measure neural activity from different cortical layers. This can potentially reveal not only which brain areas are engaged by a task, but also how. Specifically, bottom-up and top-down responses are associated with distinct laminar profiles. Here, we measured lamina-resolved fMRI responses during a visual task designed to induce concurrent bottom-up and top-down modulations via orthogonal manipulations of stimulus contrast and feature-based attention. BOLD responses were modulated by both stimulus contrast (bottom-up) and by engaging feature-based attention (top-down). Crucially, these effects operated at different cortical depths: Bottom-up modulations were strongest in the middle cortical layer, while top-down modulations were strong at all depths, being significantly stronger in deep and superficial layers compared to bottom-up effects. As such, we demonstrate that laminar activity profiles can discriminate between concurrent top-down and bottom-up processing, and are diagnostic of how a brain region is activated.

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Dissociable laminar profiles of concurrent bottom-up and top-down modulation in the human visual cortex

eLife ◽

10.7554/elife.44422 ◽

2019 ◽

Vol 8 ◽

Cited By ~ 17

Author(s):

Samuel JD Lawrence ◽

David G Norris ◽

Floris P de Lange

Keyword(s):

Cortical Layer ◽

Stimulus Contrast ◽

Cortical Layers ◽

Top Down ◽

Brain Areas ◽

Bottom Up ◽

Bold Responses ◽

Recent Developments ◽

Feature Based ◽

Human Neuroimaging

Recent developments in human neuroimaging make it possible to non-invasively measure neural activity from different cortical layers. This can potentially reveal not only which brain areas are engaged by a task, but also how. Specifically, bottom-up and top-down responses are associated with distinct laminar profiles. Here, we measured lamina-resolved fMRI responses during a visual task designed to induce concurrent bottom-up and top-down modulations via orthogonal manipulations of stimulus contrast and feature-based attention. BOLD responses were modulated by both stimulus contrast (bottom-up) and by engaging feature-based attention (top-down). Crucially, these effects operated at different cortical depths: Bottom-up modulations were strongest in the middle cortical layer and weaker in deep and superficial layers, while top-down modulations were strongest in the superficial layers. As such, we demonstrate that laminar activity profiles can discriminate between concurrent top-down and bottom-up processing, and are diagnostic of how a brain region is activated.

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Bottom-Up Inputs are Required for the Establishment of Top-Down Connectivity Onto Cortical Layer 1 Neurogliaform Cells

SSRN Electronic Journal ◽

10.2139/ssrn.3787895 ◽

2021 ◽

Author(s):

Leena A. Ibrahim ◽

Shuhan Huang ◽

Marian Fernández-Otero ◽

Mia Sherer ◽

Spurti Vemuri ◽

...

Keyword(s):

Cortical Layer ◽

Top Down ◽

Bottom Up

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Recent developments in engineering Quaternary geology in the Geological Survey of The Netherlands

Geological Society London Engineering Geology Special Publications ◽

10.1144/gsl.eng.1991.007.01.50 ◽

1991 ◽

Vol 7 (1) ◽

pp. 527-531

Author(s):

E. F. J. de Mulder ◽

R. Hillen

Keyword(s):

The Netherlands ◽

Geological Mapping ◽

Quaternary Geology ◽

Basic Data ◽

Geological Survey ◽

Thematic Maps ◽

Top Down ◽

Bottom Up ◽

Data Aquisition ◽

Recent Developments

AbstractThe Geological Survey of The Netherlands is involved in a number of Quaternary engineering geological projects. Traditionally, a “top-down” approach is followed, that is, at a client’s request, thematic maps derived mainly from the basic data of the geological mapping Programme are produced. More recently, projects have been started that require a “bottom-up” approach: for each such project, criteria are formulated that are to be met throughout all phases of the project, that is, from data aquisition to the presentation of the results. Both approaches are needed to maintain the vitality of the geological advisory work as well as of the regular geological mapping programme.

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Bottom-up inputs are required for establishment of top-down connectivity onto cortical layer 1 neurogliaform cells

Neuron ◽

10.1016/j.neuron.2021.08.004 ◽

2021 ◽

Author(s):

Leena Ali Ibrahim ◽

Shuhan Huang ◽

Marian Fernandez-Otero ◽

Mia Sherer ◽

Yanjie Qiu ◽

...

Keyword(s):

Cortical Layer ◽

Top Down ◽

Bottom Up

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Feature-based attention: it is all bottom-up priming

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2013.0055 ◽

2013 ◽

Vol 368 (1628) ◽

pp. 20130055 ◽

Cited By ~ 70

Author(s):

Jan Theeuwes

Keyword(s):

Visual Field ◽

Imaging Studies ◽

Top Down ◽

Bottom Up ◽

Specific Stimulus ◽

Image Characteristics ◽

Feature Based ◽

Neuro Imaging ◽

Rule Out

Feature-based attention (FBA) enhances the representation of image characteristics throughout the visual field, a mechanism that is particularly useful when searching for a specific stimulus feature. Even though most theories of visual search implicitly or explicitly assume that FBA is under top-down control, we argue that the role of top-down processing in FBA may be limited. Our review of the literature indicates that all behavioural and neuro-imaging studies investigating FBA suffer from the shortcoming that they cannot rule out an effect of priming. The mere attending to a feature enhances the mandatory processing of that feature across the visual field, an effect that is likely to occur in an automatic, bottom-up way. Studies that have investigated the feasibility of FBA by means of cueing paradigms suggest that the role of top-down processing in FBA is limited (e.g. prepare for red). Instead, the actual processing of the stimulus is needed to cause the mandatory tuning of responses throughout the visual field. We conclude that it is likely that all FBA effects reported previously are the result of bottom-up priming.

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ADVANCED TISSUE ENGINEERING STRATEGIES FOR VASCULARIZED PARENCHYMAL CONSTRUCTS

Journal of Mechanics in Medicine and Biology ◽

10.1142/s0219519414300014 ◽

2014 ◽

Vol 14 (01) ◽

pp. 1430001 ◽

Cited By ~ 3

Author(s):

JIANKANG HE ◽

FENG XU ◽

YAXIONG LIU ◽

ZHONGMIN JIN ◽

DICHEN LI

Keyword(s):

Tissue Engineering ◽

Cell Types ◽

Great Promise ◽

Top Down ◽

Bottom Up ◽

Organ Specific ◽

Recent Developments ◽

Multiple Cell ◽

Complex Structural

The fabrication of vascularized parenchymal organs to alleviate donor shortage in organ transplantation is the holy grail of tissue engineering. However, conventional tissue-engineering strategies have encountered huge challenges in recapitulating complex structural organization of native organs (e.g., orderly arrangement of multiple cell types and vascular network), which plays an important role in engineering functional vascularized parenchymal constructs in vitro. Recent developments of various advanced tissue-engineering strategies have exhibited great promise in replicating organ-specific architectures into artificial constructs. Here, we review the recent advances in top-down and bottom-up strategies for the fabrication of vascularized parenchymal constructs. We highlight the fabrication of microfluidic scaffolds potential for nutrient transport or vascularization as well as the controlled multicellular arrangement. The advantages as well as the limitations associated with these strategies will be discussed. It is envisioned that the combination of microfluidic concept in top-down strategies and multicellular arrangement concept in bottom-up strategies could potentially generate new insights for the fabrication of vascularized parenchymal organs.

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MOLECULAR CORRELATE OF MOUSE EXECUTIVE FUNCTION. TOP-DOWN AND BOTTOM-UP COMPLEMENTATIONS BY PRESYNAPTIC VERTEBRATE BRAIN-SPECIFIC Ntng GENE PARALOGS

10.1101/139444 ◽

2017 ◽

Cited By ~ 1

Author(s):

Pavel Prosselkov ◽

Qi Zhang ◽

Hiromichi Goto ◽

Denis Polygalov ◽

Thomas J. McHugh ◽

...

Keyword(s):

Executive Function ◽

G Proteins ◽

Cognitive Abilities ◽

Neurological Disorders ◽

Information Flows ◽

Top Down ◽

Brain Areas ◽

Bottom Up ◽

Vertebrate Brain ◽

Control Brain

ABSTRACTExecutive function (EF) is a regulatory construct of learning and general cognitive abilities. Genetic variations underlying the architecture of cognitive phenotypes are likely to affect EF and associated behaviors. Mice lacking one of Ntng gene paralogs, encoding the vertebrate brain-specific presynaptic Netrin-G proteins, exhibit prominent deficits in the EF control. Brain areas responsible for gating the bottom-up and top-down information flows differentially express Ntng1 and Ntng2, distinguishing neuronal circuits involved in perception and cognition. As a result, high and low cognitive demand tasks (HCD and LCD, respectively) modulate Ntng1 and Ntng2 associations either with attention and impulsivity (AI) or working memory (WM), in a complementary manner. During the LCD Ntng2supported neuronal gating of AI and WM dominates over the Ntng1-associated circuits. This is reversed during the HCD, when the EF requires a larger contribution of cognitive control, supported by Ntng1, over the Ntng2 pathways. Since human NTNG orthologs have been reported to affect human IQ (1), and an array of neurological disorders (2), we believe that mouse Ntng gene paralogs serve an analogous role but influencing brain executive functioning.

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Laminar Computing by Cerebral Cortex

Conscious Mind, Resonant Brain ◽

10.1093/oso/9780190070557.003.0010 ◽

2021 ◽

pp. 353-369

Author(s):

Stephen Grossberg

Keyword(s):

Cerebral Cortex ◽

Adaptive Algorithms ◽

General Purpose ◽

Cortical Layers ◽

Top Down ◽

Bottom Up ◽

Feedback Processing ◽

Laminar Organization ◽

Intelligent Behavior ◽

Language And Cognition

The cerebral cortex computes the highest forms of biological intelligence in all sensory and cognitive modalities. Neocortical cells are organized into circuits that form six cortical layers in all cortical areas that carry out perception and cognition. Variations in cell properties within these layers and their connections have been used to classify the cerebral cortex into more than fifty divisions, or areas, to which distinct functions have been attributed. Why the cortex has a laminar organization for the control of behavior has, however, remained a mystery until recently. Also mysterious has been how variations on this ubiquitous laminar cortical design can give rise to so many different types of intelligent behavior. This chapter explains how Laminar Computing contributes to biological intelligence, and how layered circuits of neocortical cells support all the various kinds of higher-order biological intelligence, including vision, language, and cognition, using variations of the same canonical laminar circuit. This canonical circuit can be used in general-purpose VLSI chips that can be specialized to carry out different kinds of biological intelligence, and seamlessly joined together to control autonomous adaptive algorithms and mobile robots. These circuits show how preattentive automatic bottom-up processing and attentive task-selective top-down processing are joined together in the deeper cortical layers to form a decision interface. Here, bottom-up and top-down constraints cooperate and compete to generate the best decisions, by combining properties of fast feedforward and feedback processing, analog and digital computing, and preattentive and attentive learning, including laminar ART properties such as analog coherence.

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Learning Physical Parameters From Dynamic Scenes

10.31219/osf.io/47dhg ◽

2018 ◽

Author(s):

Tomer David Ullman

Keyword(s):

Physical Parameters ◽

Dynamic Scenes ◽

Top Down ◽

Bottom Up ◽

Intuitive Physics ◽

Feature Based ◽

Multiple Levels ◽

Computational Resources ◽

Physical Laws ◽

Point Of Departure

Humans acquire their most basic physical concepts early in development, and continue to enrich and expand their intuitive physics throughout life as they are exposed to more and varied dynamical environments. We introduce a hierarchical Bayesian framework to explain how people can learn physical parameters at multiple levels. In contrast to previous Bayesian models of theory acquisition (Tenenbaum et al., 2011), we work with more ex- pressive probabilistic program representations suitable for learning the forces and properties that govern how objects interact in dynamic scenes unfolding over time. We compare our model to human learners on a challenging task of estimating multiple physical parameters in novel microworlds given short movies. This task requires people to reason simultane- ously about multiple interacting physical laws and properties. People are generally able to learn in this setting and are consistent in their judgments. Yet they also make systematic errors indicative of the approximations people might make in solving this computationally demanding problem with limited computational resources. We propose two approximations that complement the top-down Bayesian approach. One approximation model relies on a more bottom-up feature-based inference scheme. The second approximation combines the strengths of the bottom-up and top-down approaches, by taking the feature-based inference as its point of departure for a search in physical-parameter space.

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