scholarly journals Toward a unified theory of efficient, predictive, and sparse coding

2017 ◽  
Vol 115 (1) ◽  
pp. 186-191 ◽  
Author(s):  
Matthew Chalk ◽  
Olivier Marre ◽  
Gašper Tkačik
Keyword(s):  
Sensory Neurons ◽  
Sparse Coding ◽  
Visual Motion ◽  
Predictive Coding ◽  
Cell Types ◽  
Low Noise ◽  
Neural Responses ◽  
Unified Framework ◽  
Efficient Coding ◽  
The Past

A central goal in theoretical neuroscience is to predict the response properties of sensory neurons from first principles. To this end, “efficient coding” posits that sensory neurons encode maximal information about their inputs given internal constraints. There exist, however, many variants of efficient coding (e.g., redundancy reduction, different formulations of predictive coding, robust coding, sparse coding, etc.), differing in their regimes of applicability, in the relevance of signals to be encoded, and in the choice of constraints. It is unclear how these types of efficient coding relate or what is expected when different coding objectives are combined. Here we present a unified framework that encompasses previously proposed efficient coding models and extends to unique regimes. We show that optimizing neural responses to encode predictive information can lead them to either correlate or decorrelate their inputs, depending on the stimulus statistics; in contrast, at low noise, efficiently encoding the past always predicts decorrelation. Later, we investigate coding of naturalistic movies and show that qualitatively different types of visual motion tuning and levels of response sparsity are predicted, depending on whether the objective is to recover the past or predict the future. Our approach promises a way to explain the observed diversity of sensory neural responses, as due to multiple functional goals and constraints fulfilled by different cell types and/or circuits.

scholarly journals Towards a unified theory of efficient, predictive and sparse coding

2017 ◽  
Author(s):  
Matthew Chalk ◽  
Olivier Marre ◽  
Gašper Tkačik
Keyword(s):  
Sparse Coding ◽  
Visual Motion ◽  
Synergistic Effects ◽  
Predictive Coding ◽  
Low Noise ◽  
Neural Responses ◽  
Unified Framework ◽  
Response Properties ◽  
Efficient Coding ◽  
Special Cases

A central goal in theoretical neuroscience is to predict the response properties of sensory neurons from first principles. Several theories have been proposed to this end. “Efficient coding” posits that neural circuits maximise information encoded about their inputs. “Sparse coding” posits that individual neurons respond selectively to specific, rarely occurring, features. Finally, “predictive coding” posits that neurons preferentially encode stimuli that are useful for making predictions. Except in special cases, it is unclear how these theories relate to each other, or what is expected if different coding objectives are combined. To address this question, we developed a unified framework that encompasses these previous theories and extends to new regimes, such as sparse predictive coding. We explore cases when different coding objectives exert conflicting or synergistic effects on neural response properties. We show that predictive coding can lead neurons to either correlate or decorrelate their inputs, depending on presented stimuli, while (at low-noise) efficient coding always predicts decorrelation. We compare predictive versus sparse coding of natural movies, showing that the two theories predict qualitatively different neural responses to visual motion. Our approach promises a way to explain the observed diversity of sensory neural responses, as due to a multiplicity of functional goals performed by different cell types and/or circuits.

scholarly journals Spatio-temporally efficient coding assigns functions to hierarchical structures of the visual system

2021 ◽  
Author(s):  
Duho Sihn ◽  
Sung-Phil Kim
Keyword(s):  
Visual System ◽  
Predictive Coding ◽  
Hierarchical Structures ◽  
Brain Structures ◽  
External World ◽  
Neural Responses ◽  
Brain Areas ◽  
Efficient Coding ◽  
Neural Representations ◽  
Computational Processes

Hierarchical structures constitute a wide array of brain areas, including the visual system. One of the important questions regarding visual hierarchical structures is to identify computational principles for assigning functions that represent the external world to hierarchical structures of the visual system. Given that visual hierarchical structures contain both bottom-up and top-down pathways, the derived principles should encompass these bidirectional pathways. However, existing principles such as predictive coding do not provide an effective principle for bidirectional pathways. Therefore, we propose a novel computational principle for visual hierarchical structures as spatio-temporally efficient coding underscored by the efficient use of given resources in both neural activity space and processing time. This coding principle optimises bidirectional predictions over hierarchical structures by simultaneously minimising temporally differences in neural responses and maximising entropy in neural representations. Simulations demonstrated that the proposed spatio-temporally efficient coding was able to assign the function of appropriate neural representations of natural visual scenes to visual hierarchical structures. Furthermore, spatio-temporally efficient coding was able to predict well-known phenomena, including deviations in neural responses to unfamiliar inputs and bias in preferred orientations. Our proposed spatio-temporally efficient coding may facilitate deeper mechanistic understanding of the computational processes of hierarchical brain structures.

Study of the Molecular Architecture of Keratin Filaments by Electron Microscopy

1982 ◽  
Vol 40 ◽  
pp. 118-119
Author(s):  
U. Aebi ◽  
P. Rew ◽  
T.-T. Sun
Keyword(s):  
Electron Microscopy ◽  
Structural Organization ◽  
Cell Types ◽  
Structural Features ◽  
Molecular Architecture ◽  
The Past ◽  
Keratin Filaments ◽  
Different Types ◽  
10 Nm Filaments ◽  
Different Cell Types

Various types of intermediate-sized (10-nm) filaments have been found and described in many different cell types during the past few years. Despite the differences in the chemical composition among the different types of filaments, they all yield common structural features: they are usually up to several microns long and have a diameter of 7 to 10 nm; there is evidence that they are made of several 2 to 3.5 nm wide protofilaments which are helically wound around each other; the secondary structure of the polypeptides constituting the filaments is rich in ∞-helix. However a detailed description of their structural organization is lacking to date.

Mental time travel? A neurocognitive model of event simulation

2020 ◽  
Author(s):  
Donna Rose Addis
Keyword(s):  
Predictive Coding ◽  
Time Travel ◽  
Simulation System ◽  
Mental Time Travel ◽  
Event Representation ◽  
Conceptual Information ◽  
Fine Grained ◽  
The Past ◽  
The Future ◽  
General Capacity

Mental time travel (MTT) is defined as projecting the self into the past and the future. Despite growing evidence of the similarities of remembering past and imagining future events, dominant theories conceive of these as distinct capacities. I propose that memory and imagination are fundamentally the same process – constructive episodic simulation – and demonstrate that the ‘simulation system’ meets the three criteria of a neurocognitive system. Irrespective of whether one is remembering or imagining, the simulation system: (1) acts on the same information, drawing on elements of experience ranging from fine-grained perceptual details to coarser-grained conceptual information and schemas about the world; (2) is governed by the same rules of operation, including associative processes that facilitate construction of a schematic scaffold, the event representation itself, and the dynamic interplay between the two (cf. predictive coding); and (3) is subserved by the same brain system. I also propose that by forming associations between schemas, the simulation system constructs multi-dimensional cognitive spaces, within which any given simulation is mapped by the hippocampus. Finally, I suggest that simulation is a general capacity that underpins other domains of cognition, such as the perception of ongoing experience. This proposal has some important implications for the construct of ‘MTT’, suggesting that ‘time’ and ‘travel’ may not be defining, or even essential, features. Rather, it is the ‘mental’ rendering of experience that is the most fundamental function of this simulation system, enabling humans to re-experience the past, pre-experience the future, and also comprehend the complexities of the present.

scholarly journals The Microbiota–Gut–Brain Axis and Alzheimer Disease. From Dysbiosis to Neurodegeneration: Focus on the Central Nervous System Glial Cells

2021 ◽  
Vol 10 (11) ◽  
pp. 2358
Author(s):  
Maria Grazia Giovannini ◽  
Daniele Lana ◽  
Chiara Traini ◽  
Maria Giuliana Vannucchi
Keyword(s):  
Alzheimer Disease ◽  
Glial Cells ◽  
Cell Types ◽  
The Past ◽  
The Central Nervous System ◽  
Diseased State ◽  
The Brain ◽  
Alzheimer Disease Pathogenesis ◽  
Brain Homeostasis

The microbiota–gut system can be thought of as a single unit that interacts with the brain via the “two-way” microbiota–gut–brain axis. Through this axis, a constant interplay mediated by the several products originating from the microbiota guarantees the physiological development and shaping of the gut and the brain. In the present review will be described the modalities through which the microbiota and gut control each other, and the main microbiota products conditioning both local and brain homeostasis. Much evidence has accumulated over the past decade in favor of a significant association between dysbiosis, neuroinflammation and neurodegeneration. Presently, the pathogenetic mechanisms triggered by molecules produced by the altered microbiota, also responsible for the onset and evolution of Alzheimer disease, will be described. Our attention will be focused on the role of astrocytes and microglia. Numerous studies have progressively demonstrated how these glial cells are important to ensure an adequate environment for neuronal activity in healthy conditions. Furthermore, it is becoming evident how both cell types can mediate the onset of neuroinflammation and lead to neurodegeneration when subjected to pathological stimuli. Based on this information, the role of the major microbiota products in shifting the activation profiles of astrocytes and microglia from a healthy to a diseased state will be discussed, focusing on Alzheimer disease pathogenesis.

scholarly journals EWAS Data Hub: a resource of DNA methylation array data and metadata

2019 ◽  
Vol 48 (D1) ◽  
pp. D890-D895 ◽  
Author(s):  
Zhuang Xiong ◽  
Mengwei Li ◽  
Fei Yang ◽  
Yingke Ma ◽  
Jian Sang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Complex Traits ◽  
Cell Types ◽  
Great Promise ◽  
Methylation Array ◽  
Array Data ◽  
The Past ◽  
Comprehensive Collection ◽  
Dna Methylation Array ◽  
Brain Parts

Abstract Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.

scholarly journals Ca(2+) Oscillations and Its Transporters in Mesenchymal Stem Cells

2010 ◽  
pp. 323-329 ◽  
Author(s):  
B Ye
Keyword(s):  
Tissue Engineering ◽  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Replacement Therapy ◽  
Cell Types ◽  
Cell Replacement Therapy ◽  
Cell Replacement ◽  
Cell Functions ◽  
The Past ◽  
Intracellular Ca

Intracellular free Ca(2+) is one of important biological signals regulating a number of cell functions. It has been discussed widely and extensively in several cell types during the past two decades. Attention has been paid to the Ca2+ transportation in mesenchymal stem cells in recent years as mesenchymal stem cells have gained considerable interest due to their potential for cell replacement therapy and tissue engineering. In this paper, roles of intracellular Ca(2+) oscillations and its transporters in mesenchymal stem cells have been reviewed.

Placebos in chronic pain: evidence, theory, ethics, and use in clinical practice

BMJ ◽  
2020 ◽  
pp. m1668 ◽  
Author(s):  
Ted J Kaptchuk ◽  
Christopher C Hemond ◽  
Franklin G Miller
Keyword(s):  
Chronic Pain ◽  
Clinical Practice ◽  
Predictive Coding ◽  
Evidence Theory ◽  
Placebo Treatment ◽  
Placebo Effects ◽  
Unified Framework ◽  
Open Label ◽  
Double Blind ◽  
Bayesian Brain

ABSTRACTDespite their ubiquitous presence, placebos and placebo effects retain an ambiguous and unsettling presence in biomedicine. Specifically focused on chronic pain, this review examines the effect of placebo treatment under three distinct frameworks: double blind, deception, and open label honestly prescribed. These specific conditions do not necessarily differentially modify placebo outcomes. Psychological, clinical, and neurological theories of placebo effects are scrutinized. In chronic pain, conscious expectation does not reliably predict placebo effects. A supportive patient-physician relationship may enhance placebo effects. This review highlights “predictive coding” and “bayesian brain” as emerging models derived from computational neurobiology that offer a unified framework to explain the heterogeneous evidence on placebos. These models invert the dogma of the brain as a stimulus driven organ to one in which perception relies heavily on learnt, top down, cortical predictions to infer the source of incoming sensory data. In predictive coding/bayesian brain, both chronic pain (significantly modulated by central sensitization) and its alleviation with placebo treatment are explicated as centrally encoded, mostly non-conscious, bayesian biases. The review then evaluates seven ways in which placebos are used in clinical practice and research and their bioethical implications. In this way, it shows that placebo effects are evidence based, clinically relevant, and potentially ethical tools for relieving chronic pain.

Oscillatory Calcium Signals in Hormone-Stimulated Cells

Physiology ◽  
1989 ◽  
Vol 4 (6) ◽  
pp. 211-215
Author(s):  
PH Cobbold
Keyword(s):  
Single Cells ◽  
Cell Types ◽  
Calcium Signals ◽  
Inositol Polyphosphates ◽  
The Past ◽  
Intracellular Ca

For many cell types a signalling role for cytoplasmic free Ca was established over 10 years ago, and the past decade has seen an explosion in understanding the role played by inositol polyphosphates in receptor-controlled mobilization of intracellular Ca stores. Now an increasing number of laboratories are reporting measurements in single cells of oscillations in free Ca induced by Ca-mobilising agonists.

scholarly journals Isoprostanes: an overview and putative roles in pulmonary pathophysiology

2001 ◽  
Vol 280 (6) ◽  
pp. L1067-L1082 ◽  
Author(s):  
L. J. Janssen
Keyword(s):  
Oxidative Stress ◽  
Membrane Lipids ◽  
Cell Types ◽  
Oxygen Species ◽  
Cell Type ◽  
Experimental Conditions ◽  
The Past ◽  
Disease States ◽  
Biological Responses ◽  
Markers Of Oxidative Stress

Isoprostanes are produced during peroxidation of membrane lipids by free radicals and reactive oxygen species. Initially, they were recognized as being valuable markers of oxidative stress, and in the past 10 years, dozens of disease states and experimental conditions with diverse etiologies have been shown to be associated with marked increases in urinary, plasma, and tissue levels of isoprostanes. However, they are not just mere markers; they evoke important biological responses on virtually every cell type found within the lung, and these responses exhibit compound-, tissue-, and species-related variations. In fact, the isoprostanes may mediate many of the features of the disease states for which they are used as indicators. In this review, I describe the chemistry, metabolism, and pharmacology of isoprostanes, with a particular emphasis on pulmonary cell types, and the possible roles of isoprostanes in pulmonary pathophysiology.

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