Coding of distributed, topographic and non-specific representations within the brain

This article explores the theoretical basis of coding within topographic representations, where neurons encoding specific features such as locations, are arranged into maps. A novel type of representation, termed non-specific, where each neuron does not encode specific features is also postulated. In common with the previously described distributed representations [Rolls, E.T., Treves, A., 1998. Neural Networks and Brain Function. Oxford University Press, Oxford], topographic representations display an exponential relationship between stimuli encoded and both number of neurons and maximum firing rate of those neurons. The non-specific representations described here display a binomial expansion between the number of stimuli encoded and the sum of the number of neurons and the maximum firing rate; therefore groups of non-specific neurons usually encode less stimuli than equivalent topographic layers of neurons. Lower and higher order sensory regions of the brain use either topographic or distributed representations to encode information. It is proposed that non-specific representations may occur in regions of the brain where different types of information may be represented by the same neurons, as occurs in the prefrontal cortex.     

Age-related neural dedifferentiation in the motor system

Recent neuroimaging studies using multi-voxel pattern analysis (MVPA) show that distributed patterns of brain activation elicited by different visual stimuli are less distinctive in older adults than in young adults. However, less is known about the effects of aging on the neural representation of movement. The present study used MVPA to compare the distinctiveness of motor representations in young and older adults. We also investigated the contributions of brain structure to age differences in the distinctiveness of motor representations. We found that neural distinctiveness was reduced in older adults throughout the motor control network. Although aging was also associated with decreased gray matter volume in these regions, age differences in motor distinctiveness remained significant after controlling for gray matter volume. Our results suggest that age-related neural dedifferentiation is not restricted to sensory perception and is instead a more general feature of the aging brain.     

Behavioral correlates of cortical semantic representations modeled by word vectors

The quantitative modeling of semantic representations in the brain plays a key role in understanding the neural basis of semantic processing. Previous studies have demonstrated that word vectors, which were originally developed for use in the field of natural language processing, provide a powerful tool for such quantitative modeling. However, whether semantic representations in the brain revealed by the word vector-based models actually capture our perception of semantic information remains unclear, as there has been no study explicitly examining the behavioral correlates of the modeled brain semantic representations. To address this issue, we compared the semantic structure of nouns and adjectives in the brain estimated from word vector-based brain models with that evaluated from human behavior. The brain models were constructed using voxelwise modeling to predict the functional magnetic resonance imaging (fMRI) response to natural movies from semantic contents in each movie scene through a word vector space. The semantic dissimilarity of brain word representations was then evaluated using the brain models. Meanwhile, data on human behavior reflecting the perception of semantic dissimilarity between words were collected in psychological experiments. We found a significant correlation between brain model- and behavior-derived semantic dissimilarities of words. This finding suggests that semantic representations in the brain modeled via word vectors appropriately capture our perception of word meanings.     

Transforming bottom-up topographic representations with top-down signals in the brain

There has been considerable success in allocating function to the different parts of the brain. We also know much about brain organisation in different regions of the brain and how different brain regions connect to one another. One of the most important next steps for modern neuroscience is to work out how different areas of the brain interact with one another. In particular we need to know how sensory regions communicate with association areas and vice versa. This article explores how top-down signals originating from association areas may be used to process and transform bottom-up representations originating from sensory areas of the brain. Simple models of networks containing topographically organised ensembles of neurons used to integrate and process information are described. The different models can be used to process information in a variety of different ways that could be used as the starting point for a variety of cognitive operations, in particular the extraction of abstract information from sensory representations.     

Transforming bottom-up topographic representations with top-down signals in the brain

There has been considerable success in allocating function to the different parts of the brain. We also know much about brain organisation in different regions of the brain and how different brain regions connect to one another. One of the most important next steps for modern neuroscience is to work out how different areas of the brain interact with one another. In particular we need to know how sensory regions communicate with association areas and vice versa. This article explores how top-down signals originating from association areas may be used to process and transform bottom-up representations originating from sensory areas of the brain. Simple models of networks containing topographically organised ensembles of neurons used to integrate and process information are described. The different models can be used to process information in a variety of different ways that could be used as the starting point for a variety of cognitive operations, in particular the extraction of abstract information from sensory representations.     

Selection of preconfigured cell assemblies for representation of novel spatial experiences

Internal representations about the external world can be driven by the external stimuli or can be internally generated in their absence. It has been a matter of debate whether novel stimuli from the external world are instructive over the brain network to create de novo representations or, alternatively, are selecting from existing pre-representations hosted in preconfigured brain networks. The hippocampus is a brain area necessary for normal internally generated spatial–temporal representations and its dysfunctions have resulted in anterograde amnesia, impaired imagining of new experiences, and hallucinations. The compressed temporal sequence of place cell activity in the rodent hippocampus serves as an animal model of internal representation of the external space. Based on our recent results on the phenomenon of novel place cell sequence preplay, we submit that the place cell sequence of a novel spatial experience is determined, in part, by a selection of a set of cellular firing sequences from a repertoire of existing temporal firing sequences in the hippocampal network. Conceptually, this indicates that novel stimuli from the external world select from their pre-representations rather than create de novo our internal representations of the world.     

Searching through functional space reveals distributed visual,auditory, and semantic coding in the human brain

The extent to which brain functions are localized or distributed is a foundational question in neuroscience. In the human brain, common fMRI methods such as cluster correction, atlas parcellation, and anatomical searchlight are biased by design toward finding localized representations. Here we introduce the functional searchlight approach as an alternative to anatomical searchlight analysis, the most commonly used exploratory multivariate fMRI technique. Functional searchlight removes any anatomical bias by grouping voxels based only on functional similarity and ignoring anatomical proximity. We report evidence that visual and auditory features from deep neural networks and semantic features from a natural language processing model, as well as object representations, are more widely distributed across the brain than previously acknowledged and that functional searchlight can improve model-based similarity and decoding accuracy. This approach provides a new way to evaluate and constrain computational models with brain activity and pushes our understanding of human brain function further along the spectrum from strict modularity toward distributed representation.     

Spatial Hyperschematia without Spatial Neglect after Insulo-Thalamic Disconnection

Different spatial representations are not stored as a single multipurpose map in the brain. Right brain-damaged patients can show a distortion, a compression of peripersonal and extrapersonal space. Here we report the case of a patient with a right insulo-thalamic disconnection without spatial neglect. The patient, compared with 10 healthy control subjects, showed a constant and reliable increase of her peripersonal and extrapersonal egocentric space representations - that we named spatial hyperschematia - yet left her allocentric space representations intact. This striking dissociation shows that our interactions with the surrounding world are represented and processed modularly in the human brain, depending on their frame of reference.     

Creating abstract topographic representations: Implications for coding,learning and reasoning

Topographic maps are a fundamental and ubiquitous feature of the sensory and motor regions of the brain. There is less evidence for the existence of conventional topographic maps in associational areas of the brain such as the prefrontal cortex and parietal cortex. The existence of topographically arranged anatomical projections is far more widespread and occurs in associational regions of the brain as well as sensory and motor regions: this points to a more widespread existence of topographically organised maps within associational cortex than currently recognised. Indeed, there is increasing evidence that abstract topographic representations may also occur in these regions. For example, a topographic mnemonic map of visual space has been described in the dorsolateral prefrontal cortex and topographically arranged visuospatial attentional signals have been described in parietal association cortex. This article explores how abstract representations might be extracted from sensory topographic representations and subsequently code abstract information. Finally a simple model is presented that shows how abstract topographic representations could be integrated with other information within the brain to solve problems or form abstract associations. The model uses correlative firing to detect associations between different types of stimuli. It is flexible because it can produce correlations between information represented in a topographic or non-topographic coordinate system. It is proposed that a similar process could be used in high-level cognitive operations such as learning and reasoning.     

听觉皮层信号处理

听觉系统和视觉系统的不同之处在于：听觉系统在外周感受器和听皮层间具有更长的皮层下通路和更多的突触联系。该特殊结构反应了听觉系统从复杂听觉环境中提取与行为相关信号的机制与其他感觉系统不同。听皮层神经信号处理包括两种重要的转换机制,声音信号的非同构转换以及从声音感受到知觉层面的转换。听觉皮层神经编码机制同时也受到听觉反馈和语言或发声过程中发声信号的调控。听觉神经科学家和生物医学工程师所面临的挑战便是如何去理解大脑中这些转换的编码机制。我将会用我实验室最近的一些发现来阐述听觉信号是如何在原听皮层中进行处理的,并讨论其对于言语和音乐在大脑中的处理机制以及设计神经替代装置诸如电子耳蜗的意义。我们使用了结合神经电生理技术和量化工程学的方法来研究这些问题。     

Two-nuclear neurons: sincitial fusion or amitotic division

In the review the history of research two-nuclear neurons is stated and two hypotheses about mechanisms of their formation are analysed: by sincitial fusion or amytotic divisions. The facts of discrepancy of the former orthodox cellular theory categorically denying possibility sincitial of communications in nervous system and of sincitial fusion neurons are mentioned. As an example results of ultrastructural researches of occurrence sincitium in a cortex of the big brain of rats, in autonomic ganglions, in hypocampus and a cerebellum of adult animals are presented. The video data of the sincitial fusion of live neurons and the mechanism of formation multinuclear neurons in tissue culture are analyzed. Existing data about amytotic a way of formation two-nuclear neurons are critically considered. The conclusion becomes, that the mechanism of formation two-nuclear neurons is cellular fusion. Simultaneously the review confirms our representations about existence in nervous system sincitial interneural communications.     

In-vitro evaluation of Polylactic acid (PLA) manufactured by fused deposition modeling

October 10th, 2016 marked the 9th anniversary for the Journal of Biological Engineering (JBE), the official journal of Institute of Biological Engineering (IBE), published by BioMed Central. We are entering into the 10th year of its exciting and productive history. In this editorial, a brief history of JBE is summarized, along with a series of analyses on average number of citations, breakdown of topical subjects, geographical representations and so forth for all published articles in JBE. Future prospects and new directions of JBE are also described in this editorial.     

Multisensory integration and the body schema: close to hand and within reach

There has been a recent and dramatic growth of interest in the psychological and neural mechanisms of multisensory integration between different sensory modalities. Much of this recent research has focused specifically on how multisensory representations of body parts and of the 'peripersonal' space immediately around them, are constructed. Research has also focused on how this may lead to multisensorially determined perceptions of body parts, to action execution, and even to attributions of agency and self-ownership for the body parts in question. Converging evidence from animal and human studies suggests that the primate brain constructs various body-part-centred representations of space, based on the integration of visual, tactile and proprioceptive information. These representations can plastically change following active tool-use that extends reachable space and also modifies the representation of peripersonal space. These new results indicate that a modern cognitive neuroscience approach to the classical concept of the 'body schema' may now be within reach.     

The art of seeing and painting

The human urge to represent the three-dimensional world using two-dimensional pictorial representations dates back at least to Paleolithic times. Artists from ancient to modern times have struggled to understand how a few contours or color patches on a flat surface can induce mental representations of a three-dimensional scene. This article summarizes some of the recent breakthroughs in scientifically understanding how the brain sees that shed light on these struggles. These breakthroughs illustrate how various artists have intuitively understood paradoxical properties about how the brain sees, and have used that understanding to create great art. These paradoxical properties arise from how the brain forms the units of conscious visual perception; namely, representations of three-dimensional boundaries and surfaces. Boundaries and surfaces are computed in parallel cortical processing streams that obey computationally complementary properties. These streams interact at multiple levels to overcome their complementary weaknesses and to transform their complementary properties into consistent percepts. The article describes how properties of complementary consistency have guided the creation of many great works of art.     

Numerical Cognition: Reading Numbers from the Brain

How the human brain encodes numbers is revealed by a new analysis of patterns of brain activity. The findings address the nature of numerical representations and homology between humans and non-human primates.     

Unsupervised Feature Learning Improves Prediction of Human Brain Activity in Response to Natural Images

Encoding and decoding in functional magnetic resonance imaging has recently emerged as an area of research to noninvasively characterize the relationship between stimulus features and human brain activity. To overcome the challenge of formalizing what stimulus features should modulate single voxel responses, we introduce a general approach for making directly testable predictions of single voxel responses to statistically adapted representations of ecologically valid stimuli. These representations are learned from unlabeled data without supervision. Our approach is validated using a parsimonious computational model of (i) how early visual cortical representations are adapted to statistical regularities in natural images and (ii) how populations of these representations are pooled by single voxels. This computational model is used to predict single voxel responses to natural images and identify natural images from stimulus-evoked multiple voxel responses. We show that statistically adapted low-level sparse and invariant representations of natural images better span the space of early visual cortical representations and can be more effectively exploited in stimulus identification than hand-designed Gabor wavelets. Our results demonstrate the potential of our approach to better probe unknown cortical representations.     

Notation-dependent and -independent representations of numbers in the parietal lobes

It is a commonly held view that numbers are represented in an abstract way in both parietal lobes. This view is based on failures to find differences between various notational representations. Here we show that by using relatively smaller voxels together with an adaptation paradigm and analyzing subjects on an individual basis it is possible to detect specialized numerical representations. The current results reveal a left/right asymmetry in parietal lobe function. In contrast to an abstract representation in the left parietal lobe, the numerical representation in the right parietal lobe is notation dependent and thus includes nonabstract representations. Our results challenge the commonly held belief that numbers are represented solely in an abstract way in the human brain.     

Modelling brain representations of abstract concepts

Abstract conceptual representations are critical for human cognition. Despite their importance, key properties of these representations remain poorly understood. Here, we used computational models of distributional semantics to predict multivariate fMRI activity patterns during the activation and contextualization of abstract concepts. We devised a task in which participants had to embed abstract nouns into a story that they developed around a given background context. We found that representations in inferior parietal cortex were predicted by concept similarities emerging in models of distributional semantics. By constructing different model families, we reveal the models’ learning trajectories and delineate how abstract and concrete training materials contribute to the formation of brain-like representations. These results inform theories about the format and emergence of abstract conceptual representations in the human brain.     

Molecular, anatomical, and functional organization of the Drosophila olfactory system

BACKGROUND: Olfactory receptor neurons (ORNs) convey chemical information into the brain, producing internal representations of odors detected in the periphery. A comprehensive understanding of the molecular and neural mechanisms of odor detection and processing requires complete maps of odorant receptor (Or) expression and ORN connectivity, preferably at single-cell resolution. RESULTS: We have constructed near-complete maps of Or expression and ORN targeting in the Drosophila olfactory system. These maps confirm the general validity of the "one neuron--one receptor" and "one glomerulus--one receptor" principles and reveal several additional features of olfactory organization. ORNs in distinct sensilla types project to distinct regions of the antennal lobe, but neighbor relations are not preserved. ORNs grouped in the same sensilla do not express similar receptors, but similar receptors tend to map to closely appositioned glomeruli in the antennal lobe. This organization may serve to ensure that odor representations are dispersed in the periphery but clustered centrally. Integrated with electrophysiological data, these maps also predict glomerular representations of specific odorants. Representations of aliphatic and aromatic compounds are spatially segregated, with those of aliphatic compounds arranged topographically according to carbon chain length. CONCLUSIONS: These Or expression and ORN connectivity maps provide further insight into the molecular, anatomical, and functional organization of the Drosophila olfactory system. Our maps also provide an essential resource for investigating how internal odor representations are generated and how they are further processed and transmitted to higher brain centers.     

The evolution of large brain size in birds is related to social,not genetic,monogamy

There are several hypotheses suggesting that social complexity, including pair bonding, is important in the evolution of increased brain size. I examined whether genetic or social monogamy was related to large brain size in birds. Recent work has indicated that the length and strength of pair bonds are associated with large brain size. I tested several hypotheses for the evolution of large brain size in 42 species of bird by including life history variables in a regression model. A test on 100 phylogenetic trees revealed no phylogenetic signal in brain size. Controlling for body size, a principal components analysis was run on the life history variables and degrees of extra‐pair paternity. The main principal component (PC1) was regressed on brain size revealing a strong, positive association. Social, but not genetic, monogamy was positively related to brain size. Large brain size is related to the selective pressures of procuring extra‐pair copulations whilst maintaining a social partnership. However, other life history variables also loaded positively and significantly on brain size. These results indicate that the evolution of large brain size in birds was driven by several important selective pressures. © 2014 The Linnean Society of London, Biological Journal of the Linnean Society, 2014, 111 , 668–678.